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Referee #1

Evidence, reproducibility and clarity

In this manuscript Wu et al., present results from a comparative analysis of transcriptomes of primary hepatocytes and organoid cultures derived from intrahepatic cholangiocytes. The authors also performed scRNA-seq and ATAC-seq experiments. Using SCENIC R computational tool and ENCODE ChIP-seq data they performed regulon analysis. The main findings of the paper are the following: 1) The cell-to-cell heterogeneity of primary hepatocytes are mainly due to their zonal expression patterns within porto-central axis. 2) AP1 family of factors (JUN, FOS, ATF3 and others) co-occupy gene regulatory regions bound by HNF4 and the associated transcriptome profiles suggest that AP1 factors cooperate with liver-specific factors to regulate hepatic genes. 3) Different sets of transcription factors are active in primary hepatocytes and intrahepatic cholangiocyte organoids that were differentiated in vitro to hepatocyte-like cells. 4) Identification of ELF3 as a factor required for cholangiocyte to hepatocyte conversion. The findings are interesting, although in many cases are expected. There are some issues that need to be addressed.

Main comments:

1. The expression levels of many genes, including some major TFs (like CEBPa or HNF4) in isolated primary hepatocytes greatly differ from that in normal liver. This is due to the disruption of cell-cell contacts. For this reason, single nuclei sequencing is more reliable and it is the preferred method. It is not indicated how many biological replicates were used and what level of variability was observed between different preparations.
2. The regulome studies involved analysis of ENCODE data sets (ChIP-seq), while the RNA-seq data were obtained in the current work. Due to the different source of the data (e.g primary hepatocytes used for ENCODE consortia members and this study) differences are expected. In the present study the cells were FACS-sorted immediately after isolation, while the ones used to produce ENCODE data sets were not subjected to sorting and were also probably cultured. This limits the accuracy of comparisons. Furthermore, the authors should indicate exactly which ENCODE data-sets were used. It is also unusual to observe broad distribution of the ATF3, JUND and EGR1 ChIP-seq reads over the PCK1 gene or the Alb gene (Fig S3). Peaks called by MACS should be indicated. Have the authors verified this distribution, e.g by ChIP-PCR or other means? It is quite unlikely that binding motifs are present all over the gene bodies. Is it possible that these factors interact with elongating RNA Pol-II complexes? What is the situation in other actively transcribing gene bodies?
3. The synergism between AP1 and HNF4 is based on RNA and ChIP data in Primary hepatocytes. The main evidence for the synergism are co-binding of the two factors and the regulome profiles in the individual cells. In ICOs where both factors are expressed at high levels ChIP-seq data are not available and the potential binding distribution is estimated by the presence of binding motifs in ATAC-seq positive areas. Considering the concern described in point 2, it is important to obtain ChIPs-seq data in ICOs too. In addition, more direct experimental evidence for the synergism is needed. For example, demonstrating the synergism between HNF4 and some AP1 factors in specific genes by co-transfection experiments.
4. Transcriptome comparisons between primary hepatocytes and intrahepatic cholangiocyte organoids (ICO) or ICOs cultured in hepatocyte differentiation medium (DM-ICO) were performed before (Ref. 6). These cells were derived from the same donor. In the current study ICOs were obtained from a biobank, thus they were from different donors. Differences between the expression patterns of primary cells and EM-IOC and DM-IOC organoid cultures are expected even if they derived from the same donor. In Ref.6 it is clearly demonstrated that DM-IOCs closely mimic many, but not all aspects of the liver phenotype. The present paper therefore provides only incremental new knowledge about the usefulness of organoid cultures in general. On the other hand, the scRNA-seq data with cells from the organoids point to the lack of zonation, which is an important new information, not analysed in Ref.6
5. In the methods section the description of ICO culture conditions are very epigrammatic. It refers to previously published protocols but also mentions the addition of BMP7 in the first round of culturing without explaining why was this important. It would be useful if the authors describe exactly the culture conditions they used. Were the ICOs from the biobank established under culture conditions described in Ref 6 or by previous protocols?
6. The results about ELF3 function are interesting and convincing. This is a novel finding and may worth to perform a global transcriptome analysis and some immunostainings with specific markers in siELF3 cells to further strengthen its regulatory role in cholangiocyte-hepatocyte conversion.

Referees cross-commenting

I fully agree with the comments of Reviewer 2. Addressing them would clearly improve the paper. I also fully agree with Reviewer 3. In my opinion, special emphasis should be put on addressing point 1, 3, 4 and 5. Properly addressing these points would also answer at least partially my concerns (Reviewer 1) described in point 1, 2, 3 and 6. I would recommend the authors focus on the above issues.

Significance

Strengths: combines scRNA-seq with regulome analysis to identify synergism between different classes of transcription factors.

Weaknesses: The data sets come from different sources. Key conclusions drawn from computational analysis are not validated experimentally. Comparing expression patterns of primary cells with those of organoid cultures is risky due to a number of technical limitations.

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Reply to the reviewers

We appreciate the time and effort that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. Those comments are all valuable and very helpful for revising and improving our paper, as well as the importance guiding significance to our researches. We have highlighted the changes in yellow within the manuscript.

*Here is a point-by-point response to the reviewers’ comments and concerns. *

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

The provided document, titled "Camel Milk Affects Serum Metabolites by Modulating the Intestinal Microflora," is an extensive research paper. My summary covers the first 44 pages of the total 63 pages. The document begins with a standard review commons manuscript notice and provides contact information for the Review Commons office.

The research focuses on the effects of camel milk on serum metabolites and the intestinal microflora. It starts with a detailed introduction to the topic, outlining the crucial role of gut microbes in human health and the influence of various factors like diet, genetics, and environment on these microbes. The paper emphasizes the nutritional richness of camel milk and its potential as a functional food, particularly its impact on gut microbiota and host metabolism.

Initial sections of the paper discuss the research methodologies, including the study's keywords, abstract, and introduction. The abstract highlights the study's significant findings, such as the presence of various beneficial bacteria in sour camel milk, the inter- and intra-species transportation of microbiomes, and the impact of camel milk on the gut microflora and serum metabolites of type 2 diabetic rats.

The introduction further delves into the composition of the human gut microbiota and the shaping factors of the adult gut microbiome. It also examines the role of diet in modulating gut microbiota and the potential health benefits of dairy products, with a particular focus on camel milk.

Subsequent sections present detailed research findings, including the results of microbial composition and source analysis in camel milk, the composition and changes of rat gut microbiota under camel milk regulation, and the effects of camel milk-regulated gut microbiota on metabolism in rats. The research also explores the interspecies transfer of microbes using camel milk as a vector and analyzes the gut microbiota in people consuming camel milk.

The paper further discusses the endophytic flora of camel edible desert plants and their possible influence on the camel's gut microbiota. The discussion section integrates the findings, offering insights into the potential health benefits of camel milk and its probiotic qualities. It also compares the effects of camel milk with other dairy products and discusses its role as a vector for beneficial microbes.

Materials and methods used in the study are detailed towards the end of the summarized portion, describing sample collection and processing, the experimental setup for rats, and data processing and analysis techniques.

Reviewer #1 (Significance (Required)):

The paper continues with detailed research findings, including the microbial composition in camel milk, the impact on the gut microflora of rats and humans, and the serum metabolism effects.

There's a focus on how camel milk, as a vector, can transfer beneficial microbes between species, influencing gut microbiota and host metabolism.

The paper compares the effects of camel milk with other dairy products, emphasizing its unique health benefits and its role in transferring beneficial microbes.

It discusses various bacteria found in camel milk and their potential health benefits.

The research findings extend to understanding how camel milk affects human gut microbiota, with studies on pastoral herders who consume camel or bovine milk.

Author response: We thank you for your approval and constructive and valuable feedback from you and other reviewers.

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

summary:

The authors introduce a study assessing the bacterial flora of sour fermented camel milk and its capability to introduce beneficial species into consumer's gut. They further tested the potential of its nutrients and species for beneficial effects on type 2 diabetic (t2d) rats. They claim that t2d rats fed with high-dose camel whey reveal a microbiota closer to that of healthy rats rather than that of other t2d rats not receiving the camel whey treatment. Further they claim that this effect is due to the presence of Eubacterium limnetica that was exclusively found in the gut microflora of rats taking camel milk and producing MtcB protein. They conclude that camel milk may have the potential to be functional food.

Overall, I think the approach of looking into camel milk and its microbiota is of broad interest, as it is food consumed traditionally by many tribes and in several countries. However, to me the presentation of the findings, the data and the analysis is often unprecise and confusing.

For example, the MtcB protein they claim to be the mechanism of reducing the risk for t2d in the abstract is mentioned only once in the whole study and there only as a finding of another study (cited). According to my understanding the abstract should contain the main findings of the study, rather than some side-finding from other studies happens to match with the study results. I assume the authors have plenty of results from their sequencing data and metabolomics that they could mention in the abstract.

In the text the authors mention the analysis of the microbial composition and source analysis of camel milk, the analysis of the gut microbiota of young camels, the composition, and changes of rat gut microbiota under the regulation of camel milk, the structure and changes of gut microbiota in people taking camel milk and the analysis of the endophytic flora of camel edible desert plants. And this just quoting the headers in the results section. Why is that not represented/mentioned in the abstract? Instead the authors focus on the t2d rats and the MtcB mechanism they fail to present.

Further the authors are sloppy when it comes to typos and preciseness. For example, in the abstract they talk first about sour camel milk, then whey and then milk again.

I suggest a major restructuring/rewriting and if necessary partial reanalysing of the results and the conclusions.

It would be good to have an overview figure combining the work done, also stating the number of samples for each experiment.

__Author response: __Thank you very much for your nice suggestion on our manuscript, we applied some restructuring to our manuscript and the changes were highlighted in yellow.

Major comments:

1) Please make sure all raw data (sequences and filtering/assembly results) are deposited in public databases, like NCBI, ENA or else.

__Author response: __The corresponding data is available as Mendeley Data, V1, https://doi.org/10. 17632/4w8n8n96tc.1, some datasets with bigger size uploaded failed owing to internet problem. The full version could be offered in other approaches if requested.

2) Please state briefly for each dataset analysed, which sequencing method was used, how many samples were collected and how many were pooled for the sequencing runs:

AmpliAeq, whole metagenome HiSeq, MiSeq?

__Author response: __Sample and dataset information for sequence was supplied in Supplementary Table 9 and 12. Sequencing library was prepared following Illumina library preparation instructions, and sequenced using Illumina Miseq platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) with pair-end (PE) 150 bp reads.

3) Page14 line283:

F082? What is it? A strain, species or a sample?

Please state clearly in the text.

Also please avoid using abbreviations where possible and if you have to use them, please define.

__Author response: __When applying diversity analysis at the specie level, a species annotated as unclassified_g_norank_f_F082 was found abundant in camel feces in Darbancheng.

4) Page14 line307:

"These evidenced that camel milk was a vector transferring microbes from the female camel to their cubs."

Yes, that may be likely, but 16S amplicon-seq cannot provide evidence. Evidence would be strain similarity confirmed by SNP's or the like. So please state that this is speculative or show appropriate evidence.

__Author response: __We completely agree that SNP’s is better evidence for this point and thank you. Microbial diversity analysis was a main part of initial design, and our limited sample couldn’t meet the needs of diversity and SNPs in the same time. There also were reports which used 16S based methods to trace the microbes source(Du et al., 2022; El-Mokdad, 2014; Wang et al., 2018).

5) Page15 line322 ff:

"Besides, using raw milk was not effective in type 2 diabetic rat model, so we chose camel whey and bovine whey as the diet of type 2 diabetic rats in follow-up experiments"

Data/evidence? How is it different from whey on a nutrient perspective, as whey was more effective? Any explanation for this difference? And the bovine whey, what species did it contain? Can they be transferred regarding the processing of whey prior to application?

__Author response: __This is an interesting and valuable question. We prepared raw milk and whey for the pre-test, then directly turned to validate the function of whey. Maybe we will investigate the composition difference in the future. The whey was prepared using the following protocol: Centrifuge fresh milk for 20 mins at 5000 r/min, discard the fat, and precipitate and obtain the middle layer of skim milk. After 20 mins in a 40 ℃ water bath, adjust the pH to 4.6 with 10% glacial acetic acid, and store in a 4°C refrigerator, overnight. Then, the skim milk was centrifuged at 8000 r/min for 20 min, repeated twice, and the middle whey fraction was collected. The centrifuged whey was poured into a petri dish and sealed. It was frozen at -80°C for 12 hours and then pierced with a sterile toothpick on the petri dish and then freeze-dried to get whey powders. A speculation was the preparing progress of whey played an important role in their functional difference. A comprehensive comparison of camel raw milk, camel whey, bovine raw milk, and whey will be an interesting point and we may investigate it shortly.

6) Page17 line366ff:

"Taking the number of microbes involved in this pathway, 8001 species were noted in the high-dose camel whey group, 3447 in the positive drug group, and only 1467 in the diabetics." How many species were present in the rats initially? Was species abundance different in the first place, or did they get lost, or came from the camel whey?

__Author response: __The rats were fed with broad-spectrum antibiotics for 2 weeks, which ensured the same species abundance in the beginning.

7) Page17 line369 ff:

"It indicated that these microbes might resist the high glucose environment of the host through the synthesis and metabolism of their amino acids, and the effect of high-dose camel milk was more effective than that of metformin"

-> How high was the glucose level in the rat gut? Or were there any obvious physiological changes in the t2d model rats that are characteristic for such a high-glucose environment? Please explain.

__Author response: __This is an interesting and critical question. We didn’t measure the glucose level in the rat gut directly because we had to make sure other related characterizations worked properly. Besides, we thought camel milk could regulate microbial community, and further influence the blood sugar level, which was more representative in our sight. Blood sugar level is supplied in Fig.4O and Supplementary Table 11.

8) The resolution/quality of the figures is low and the labelling often small. So not all text is readable.

__Author response: __We adjusted the figures in the manuscript and offered additional independent picture files. Additionally, it seemed caused by the PDF merge progress, please check the pictures in .docx or .png files for details.

9) Page19 line400 ff:

What serum metabolites were analysed and why? Please write an intro-sentence to make it easier for the reader.

Please write more precise what methods were used. Maybe I missed it, but I didn't find it in the methods part as well (Page40/41).

__Author response: __The rats fed high-dose camel whey or metformin showed similar improvement in serum metabolite imbalance and were closer to normal. Caproylcarnitine, taurodeoxycholic acid, acetylcarnitine, creatinine, linoleic acid, and tridecanoic acid were detected as upregulated; 2-deoxyuridine, cyclohexylamine, L-pipecolic acid, LysoPC(18:0), uracil, caprylic acid, cholesterol sulfate, L-citrulline, pelargonic acid, and phenol downregulated. Carnitine supplementation, due to its key role in lipid metabolism and antioxidant effects, may effectively manage Type 2 Diabetes by addressing fatty acid metabolism dysregulation and oxidative stress(Bene, Hadzsiev, & Melegh, 2018). Studies have shown that taurodeoxycholic acid can enhance the effect of insulin and reduce blood sugar levels by regulating endoplasmic reticulum stress, and have potential in the treatment of diabetes(Xing, Zhou, Wang, & Xu, 2023). Low serum creatinine is associated with the development of T2D(Song, Hong, Sung, & Lee, 2022). Increased linoleic acid consumption was recommended for the prevention of T2D(Henderson, Crofts, & Schofield, 2018). The uridine is phosphorylated into uracil, which is converted to 2-deoxyuridine. Then 2-deoxyuridine is further converted to thymine with thymidine phosphorylase, the expression of thymidine phosphorylase was lost or considerably reduced when the organism suffered nephropathy and the high concentration of thymidine is a cause of DNA impairment, which is related to diabetes and diabetic nephropathy(Spinazzola et al., 2002; Szabo et al.; Xia, Hu, Liang, Zou, Wang, & Luo, 2010). L-Pipecolic acid are associated with higher incidence of T2D(Razquin et al., 2019). A research showed LysoPC(16:0) and (18:0) may mediated a fast progression of diabetic kidney disease(Yoshioka et al., 2022). Cholesterol sulfate is the most abundant known sterol sulfate in human plasma, and it plays a significant role in the control of glucose metabolism, which contribute to the pathogenesis of insulin resistance and the resultant development of diabetes(Shi et al., 2014; Zhang et al., 2022). L-citrulline supplementation might improve glucose homeostasis, some lipid factors and inflammatory markers in overweight and obese patients with T2D(Azizi, Mahdavi, Mobasseri, Aliasgharzadeh, Abbaszadeh, & Ebrahimi-Mameghani, 2021). T2D mellitus is associated with increased total plasma free fatty acid and modulating its concentration is the mechanism of some fibrates and statins drugs(I. S. Sobczak, A. Blindauer, & J. Stewart, 2019). Most of these metabolites have been reported as causes of T2D or consequences of T2D progress, some have been designed as therapeutic target.

The serum metabolites were carried out using Agilent 1290 Infinity UHPLC system equipped with a HILIC column. The mobile phase of the optimized method consisted of (A) water with 25 mM ammonium acetate and 25 mM ammonia; and (B) acetonitrile (ACN). The following gradient elution was used: 5% A at 0-1min; 5-35% A at 1-14 min; 35-60% A at 14-16 min; 60% A at 16-18 min ; 60-5% A at 18-18.1 min and 5% A at 18.1-23 min. The flow rate was 0.3 mL/min, injection volume 2 μL, and column temperature was 25 ℃. Triple TOF 5600 mass spectrometer was applied for mass spectrometer analysis. The condition was used as following: Ion Source Gas1：60，Ion Source Gas2：60，Curtain gas：30，source temperature：600℃，IonSapary Voltage Floating ± 5500 V. TOF MS scan m/z range：60-1000 Da，product ion scan m/z range：25-1000 Da，TOF MS scan accumulation time 0.20 s/spectra, product ion scan accumulation time 0.05 s/spectra.MS/MS was gathered by information dependent acquisition (IDA) using high sensitivity mode, Declustering potential：±60 V, Collision Energy：35±15 eV, and IDA was set as Exclude isotope within 4 Da, Candidate ions to monito per cycle: 6. The methods part was complemented.

Minor comments:

1) Page1, line56-58 ff

Please phrase more clearly:

"This study specified that the transportation of microbiome happened both intra- and inter-species and played a principal role in the formation of progeny gut microflora."

While the content is mostly comprehensible, there is a need for rephrasing and correction of language also in the following text.

__Author response: __As suggested by the reviewer, we have rephrased and modified the abstract part.

2) Page14 line300 ff:

There is no need to show the OTU numbers in the text, please provide your results as a table in the supplements and refer to it in the text.

Author response: We deleted OTU numbers in the manuscript and added the corresponding table in supplementary file.

3) Page15 line328: Please check for typos, it is Shannon index, not Shanno.

__Author response: __The corresponding correction was applied in the manuscript.

4) Page16 line334:

Please mention the number, age and sex of the rats used and how many groups you had in your experiments.

__Author response: __SPF-grade male rats weighing 180-220 g were used for our related experiments. The detailed information is available in Supplementary Material (Supplementary Table 11-13).

5) The headlines should logically structure the paper:

For example, the authors have two very similar sections in the results part: "Composition and changes of rat gut microbiota under the regulation of camel milk" and "Analysis of the composition of gut microbiota in rats". Those can be combined or stated more concise.

Also, other headlines improvement to make it easier for the reader to follow.

__Author response: __We adjusted this part in the manuscript according to the reviewer’s suggestion.

Reviewer #2 (Significance (Required)):

I do think the study is of broad interest and relevance. However, the presentation of the analysis and data needs major revision. Especially it is lacking clarity on what was done for which samples and how the authors draw their conclusions. Also, I think that abstract and main text have a different focus. I would suggest to the authors to concentrate on their findings in abstract and text and state precisely what was done and what they found.

__Author response: __Thank you very much for your recognition of our manuscript.

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

Learn more at Review Commons

---

Referee #2

Evidence, reproducibility and clarity

Summary:

The authors introduce a study assessing the bacterial flora of sour fermented camel milk and its capability to introduce beneficial species into consumer's gut. They further tested the potential of its nutrients and species for beneficial effects on type 2 diabetic (t2d) rats. They claim that t2d rats fed with high-dose camel whey reveal a microbiota closer to that of healthy rats rather than that of other t2d rats not receiving the camel whey treatment. Further they claim that this effect is due to the presence of Eubacterium limnetica that was exclusively found in the gut microflora of rats taking camel milk and producing MtcB protein. They conclude that camel milk may have the potential to be functional food.

Overall, I think the approach of looking into camel milk and its microbiota is of broad interest, as it is food consumed traditionally by many tribes and in several countries. However, to me the presentation of the findings, the data and the analysis is often unprecise and confusing. For example, the MtcB protein they claim to be the mechanism of reducing the risk for t2d in the abstract is mentioned only once in the whole study and there only as a finding of another study (cited). According to my understanding the abstract should contain the main findings of the study, rather than some side-finding from other studies happens to match with the study results. I assume the authors have plenty of results from their sequencing data and metabolomics that they could mention in the abstract. In the text the authors mention the analysis of the microbial composition and source analysis of camel milk, the analysis of the gut microbiota of young camels, the composition, and changes of rat gut microbiota under the regulation of camel milk, the structure and changes of gut microbiota in people taking camel milk and the analysis of the endophytic flora of camel edible desert plants. And this just quoting the headers in the results section. Why is that not represented/mentioned in the abstract? Instead the authors focus on the t2d rats and the MtcB mechanism they fail to present. Further the authors are sloppy when it comes to typos and preciseness. For example, in the abstract they talk first about sour camel milk, then whey and then milk again.

I suggest a major restructuring/rewriting and if necessary partial reanalysing of the results and the conclusions.

It would be good to have an overview figure combining the work done, also stating the number of samples for each experiment.

Major comments:

1. Please make sure all raw data (sequences and filtering/assembly results) are deposited in public databases, like NCBI, ENA or else.
2. Please state briefly for each dataset analysed, which sequencing method was used, how many samples were collected and how many were pooled for the sequencing runs: AmpliAeq, whole metagenome HiSeq, MiSeq?
3. Page14 line283: F082? What is it? A strain, species or a sample? Please state clearly in the text. Also please avoid using abbreviations where possible and if you have to use them, please define.
4. Page14 line307: "These evidenced that camel milk was a vector transferring microbes from the female camel to their cubs." Yes, that may be likely, but 16S amplicon-seq cannot provide evidence. Evidence would be strain similarity confirmed by SNP's or the like. So please state that this is speculative or show appropriate evidence.
5. Page15 line322 ff: "Besides, using raw milk was not effective in type 2 diabetic rat model, so we chose camel whey and bovine whey as the diet of type 2 diabetic rats in follow-up experiments" Data/evidence? How is it different from whey on a nutrient perspective, as whey was more effective? Any explanation for this difference? And the bovine whey, what species did it contain? Can they be transferred regarding the processing of whey prior to application?
6. Page17 line366ff: "Taking the number of microbes involved in this pathway, 8001 species were noted in the high-dose camel whey group, 3447 in the positive drug group, and only 1467 in the diabetics." How many species were present in the rats initially? Was species abundance different in the first place, or did they get lost, or came from the camel whey?
7. Page17 line369 ff: "It indicated that these microbes might resist the high glucose environment of the host through the synthesis and metabolism of their amino acids, and the effect of high-dose camel milk was more effective than that of metformin"
8. How high was the glucose level in the rat gut? Or were there any obvious physiological changes in the t2d model rats that are characteristic for such a high-glucose environment? Please explain.
9. The resolution/quality of the figures is low and the labelling often small. So not all text is readable.
10. Page19 line400 ff: What serum metabolites were analysed and why? Please write an intro-sentence to make it easier for the reader. Please write more precise what methods were used. Maybe I missed it, but I didn't find it in the methods part as well (Page40/41).

Minor comments:

1. Page1, line56-58 ff Please phrase more clearly: "This study specified that the transportation of microbiome happened both intra- and inter-species and played a principal role in the formation of progeny gut microflora." While the content is mostly comprehensible, there is a need for rephrasing and correction of language also in the following text.
2. Page14 line300 ff: There is no need to show the OTU numbers in the text, please provide your results as a table in the supplements and refer to it in the text.
3. Page15 line328: Please check for typos, it is Shannon index, not Shanno.
4. Page16 line334: Please mention the number, age and sex of the rats used and how many groups you had in your experiments.
5. The headlines should logically structure the paper: For example, the authors have two very similar sections in the results part: "Composition and changes of rat gut microbiota under the regulation of camel milk" and "Analysis of the composition of gut microbiota in rats". Those can be combined or stated more concise. Also, other headlines improvement to make it easier for the reader to follow.

Significance

I do think the the study is of broad interest and relevance. However, the presentation of the analysis and data needs major revision. Especially it is lacking clarity on what was done for which samples and how the authors draw their conclusions. Also I think that abstract and main text have a different focus. I would suggest to the authors to concentrate on their findings in abstract and text and state precisely what was done and what they found.

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

Learn more at Review Commons

---

Referee #1

Evidence, reproducibility and clarity

The provided document, titled "Camel Milk Affects Serum Metabolites by Modulating the Intestinal Microflora," is an extensive research paper. My summary covers the first 44 pages of the total 63 pages. The document begins with a standard review commons manuscript notice and provides contact information for the Review Commons office.

The research focuses on the effects of camel milk on serum metabolites and the intestinal microflora. It starts with a detailed introduction to the topic, outlining the crucial role of gut microbes in human health and the influence of various factors like diet, genetics, and environment on these microbes. The paper emphasizes the nutritional richness of camel milk and its potential as a functional food, particularly its impact on gut microbiota and host metabolism.

Initial sections of the paper discuss the research methodologies, including the study's keywords, abstract, and introduction. The abstract highlights the study's significant findings, such as the presence of various beneficial bacteria in sour camel milk, the inter- and intra-species transportation of microbiomes, and the impact of camel milk on the gut microflora and serum metabolites of type 2 diabetic rats.

The introduction further delves into the composition of the human gut microbiota and the shaping factors of the adult gut microbiome. It also examines the role of diet in modulating gut microbiota and the potential health benefits of dairy products, with a particular focus on camel milk.

Subsequent sections present detailed research findings, including the results of microbial composition and source analysis in camel milk, the composition and changes of rat gut microbiota under camel milk regulation, and the effects of camel milk-regulated gut microbiota on metabolism in rats. The research also explores the interspecies transfer of microbes using camel milk as a vector and analyzes the gut microbiota in people consuming camel milk.

The paper further discusses the endophytic flora of camel edible desert plants and their possible influence on the camel's gut microbiota. The discussion section integrates the findings, offering insights into the potential health benefits of camel milk and its probiotic qualities. It also compares the effects of camel milk with other dairy products and discusses its role as a vector for beneficial microbes.

Materials and methods used in the study are detailed towards the end of the summarized portion, describing sample collection and processing, the experimental setup for rats, and data processing and analysis techniques.

Significance

The paper continues with detailed research findings, including the microbial composition in camel milk, the impact on the gut microflora of rats and humans, and the serum metabolism effects. There's a focus on how camel milk, as a vector, can transfer beneficial microbes between species, influencing gut microbiota and host metabolism. The paper compares the effects of camel milk with other dairy products, emphasizing its unique health benefits and its role in transferring beneficial microbes. It discusses various bacteria found in camel milk and their potential health benefits. The research findings extend to understanding how camel milk affects human gut microbiota, with studies on pastoral herders who consume camel or bovine milk.

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

Learn more at Review Commons

---

Reply to the reviewers

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

DBF4 and DRF1 knockout cells were generated and used to separate DBF4- and CDC7-dependent from DRF1- and CDC7-dependent activities. DBF4- and CDC7-dependent activities at replication forks were independent of DRF1. These include the replication timing pattern, replication fork velocity, DNA damage signaling. DBF4 is required to recruit CDC7 to active replication forks. The study is in large part exceptional.

The inclusion of quantitation for a modest bandshift on CDC7 in figure 2 (30% vs 50% reduced) is not justified given the abundance of the main band and our knowledge of the lack of linearity of western blot quantitation. This should be removed.

We thank the reviewer for evaluating our manuscript and for the positive feedback.

In the revised manuscript we have removed the quantification of the bandshift related to CDC7 autophosphorylation in mitotic cells which was reported in Figure 1E. We recognise that the quantification may not be accurate although performed using semiquantitative near-infrared scanning technology. Importantly the experiment was performed three times with almost identical results.

The only significant weakness in the paper is the explanation of the replication timing analyses in Figure 3. I don't understand what the differences between the plots equate to in terms of timing. I understand the replication of these regions that diverge is either early or late, but their were only two fractions of cells - 2N-3N and 3N-4N (the cells are "normal"). If this is the case, isn't the readout binary? a sequence either replicates in S phase between 2N and 3N or in S phase between 3N and 4N. Why are the differences so small? Are they only evident in a small population of cells? If that is the case, then what does the difference really mean? I think the description of these data needs to be precise.

The replication timing experiments were performed with a well-established and reliable protocol (Ryba et al., 2011, https://doi.org/10.1038/nprot.2011.328). Asynchronous cells are labelled with a short pulse of BrdU, and sorted in two fractions, early and late S-phase, as described in Hiratani et al., 2008, Ryba et al., 2010, Hadjadj et al, 2016 and 2020 (https://doi.org/10.1371/journal.pbio.0060245) (https://doi.org/10.1101/gr.099655.109, https://doi.org/10.1016/j.gdata.2016.07.003, https://doi.org/10.1093/nargab/lqaa045).

This method does not take into account the variation in the DNA copy number (2N vs 4N) between replicated and non-replicated parts of the genome (S/G1 ratio) as in Siefert et al., 2017 (https://doi.org/10.1101/gr.218602.116).

The profiles depict the average replication timing of a population of 20,000,000 cells; thus, the readout is not binary.

Replication timing profiles display the log ratio between early and late replicated fractions along the chromosome. Early replicated regions show positive log ratios and late replicated regions show negative ratios. The differential analysis performed with the START-R suite allows the comparison of the profiles (Ctrl vs either CDC7i-treated or DBF4-deficient cells). The genomic regions with altered timing are shown in green or in purple below the profiles, showing advanced and delayed regions, respectively.

Importantly, the differences in replication timing are expressed with log ratio, that explains why the profiles are varying from -2 (very late replicating regions) and +2 (very early replicating regions). The differences we observed in Figure 3 are representative of two experiments, each composed of two technical replicates that are highly reproducible.

To better describe the data, we have modified the text in the results section with the words in bold, as below: “These two neo-synthesized DNA fractions were then hybridised on human whole genome microarrays, as previously described. The log ratio between early and late replicated fractions was calculated and visualised for the whole genome.” We also changed the labelling of the replication profiles in Figure 3 and former Figure S3 (now Figure S4) by adding Log2 (Early/Late) to intensity and added two new sentences to the figure legend 3.“____Replication timing profiles display the log ratio between early and late replicated fractions along the chromosome. Positive log ratios correspond to early replicated regions whereas negative ratios correspond to late replicated regions.”

Reviewer #1 (Significance (Required)):

I think this paper is a significant advance that should be published. CDC7 is a critical kinase and identifying its co-factor at the replication fork is important both for our understanding of mechanisms of DNA replication and the impact of CDC7 kinase inhibitors in the clinic. I think the majority of the experiments are well designed and the results are unambiguous and precisely described.

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

CDC7 is a master cell cycle kinase with essential functions in DNA replication and important roles in the DNA damage response. For its functions, CDC7 relies on a regulatory factor, DBF4, which is essential in many species but not in human cells as a consequence of the presence of a second DBF4-related factor, DRF1. In this work, Göder and colleagues study the relative relevance of these regulatory proteins in CDC7 roles. Their study reveals DBF4 as the major regulatory subunit both in DNA replication, DNA damage checkpoint and fork dynamics. The objective of the study is highly relevant to understand an essential cell cycle kinase with potential applications in cancer therapies, the experiments are well performed and the conclusions are "in principle" sound.

We thank this reviewer for the time and attention in evaluating the manuscript, for the positive feedback and for indicating key points for improvement and discussion.

The major handicap of the study is the absence of western blots showing the elimination of DBF4 and DRF1 in the edited cell lines due to the lack of specific antibodies. The authors have generated homozygous mutations that lead to premature stop codons behind critical CDC7 domains. However, as they mention, it is not possible to fully exclude some proteins arising from internal start sites or exon skipping events with residual (functional or altered, and not necessarily residual) activity. This is not unexpected, especially for essential proteins. This would not be a major handicap if the study were focused in a specific factor because it would only question the impact of but not the affected function, but it aims to compare the relative effect of two defective genes. In this case, it is essential to confirm that both genes are eliminated, at least to the same degree.

We agree with the reviewer that it would be valuable to confirm the effect of the mutations by immunoblotting.

Over the years we have had multiple attempts at generating sensitive antibodies against both DBF4 and DRF1, using recombinant proteins and synthetic peptides. We also tested several commercially available anti-DBF4 and anti-DRF1 antibodies. While often we were able to detect overexpressed proteins, the detection of endogenous levels has been particularly challenging especially in non-transformed cells, such MCF10A.

Nevertheless, with an anti-DBF4 serum we obtained from the Diffley lab, which was generated against the C-terminus fragment of hDBF4, we managed to detect endogenous full length DBF4 in parental but not in the DBF4-KO cells (this blot is now included as supplementary Fig S1B). Even with this reagent the detection levels are low and multiple non-specific immunoreactive bands are present, making the detection of DBF4 particularly challenging across the experiments. Interestingly, while DBF4 is no longer detectable in DBF4-11, one the two clones used in this work , we detect a new immunoreactive band of approximately 55kDa in the other clone DBF4-30. We reckon that this may be the result of mRNA translation from the next downstream methionine. In this case this aberrant protein would lack the N domain and most of the M domain, involved in CDC7 binding and activation, and thus this fragment is very likely not functional.

Importantly, most results in this study were obtained using both DBF4-11 and DBF4-30 clones with indistinguishable results. Only the replication timing experiments were done using a single clone DBF4-11, in which DBF4 protein is not detected.

We had less success with the direct detection of DRF1. As also suggested by reviewer #3, to screen the clones after genome editing, we originally performed IP-western experiments. We used an anti-DRF1 mAb and unrelated IgG for the immunoprecipitations and an anti-CDC7 antibody as a probe in western blotting. We detected an immunoreactive band above the background at the expected molecular weight for CDC7 when the immunoprecipitation was performed with extracts from parental cells (as well as in a clone obtained with a different sgRNA, targeting DRF1 Exon1 and never used in this study) but not when the immunoprecipitation was performed with extracts from the DRF1- 5 and DRF1-7 clones used in the study. These original co-IPs are credible although not particularly pretty and importantly the result was confirmed in a more convincing experiment in the DRF1-5 clone.

These new data are now included in the resubmission in Figure S1. So, while the detection of the CDC7 regulatory subunits still remains particularly difficult, we can now provide evidence that their expression is altered in the engineered cell lines used in the study.

The computational analysis in Figure 1C is consistent with the major conclusion about the primary regulatory role of DBF4 in replication, but it is insufficient to validate the specific phenotypes addressed in the study.

The figure reports the effects of targeting single genes with multiple sgRNA (4 to 8 according to the library used) on proliferation rate/fitness measured after multiple days in more than 1000 screens across many different human cell types. Loss of fitness can be due either to a direct problem with DNA replication or with other cellular processes.

We agree with the reviewer that the analysis in Fig 1C is consistent with the phenotypes shown in the study. Particularly it is consistent with the lack of a major defect of DRF1-deficient cells in DNA replication, and it strongly indicates an essential role for CDC7 which was somehow challenged by Suski and co-workers (see also below).

Indeed, there is a result that is hard to understand if the edited cell lines are defective in the expression of the regulators, specially DRF1. Figure S2D-E shows no synergistic defect in DNA synthesis when the second regulator is knock down with specific siRNAs, not even DRF1 defective cell lines treated with a siDBF4 that reduces its expression 10 times. Also, it is not clear why the defects, specially in DBF4-defective cell lines, are less severe than in cells treated with an inhibitor that causes a partial inhibition of CDC7. If it is due to the expression of DRF4, a siRNA against DRF4 should cause more severe defects.

Yes, we did not detect synergy or additive effect on the rate of DNA replication when targeting both DBF4 and DRF1 by multiple approaches. This was also for us an unexpected result, that we examined to the best of our capabilities.

The lack of the expected synergy in the replication assays could be explained in multiple ways and could be of biological or technical nature such as 1) residual low levels of DBF4/DRF1 proteins remaining in the cells upon either CRISPR/Cas9 or siRNA targeting, 2) alternative mechanisms of kinase activation by a different, yet unidentified protein, 3) minimal residual enzymatic activity of hCdc7 kinase not requiring an activating subunit.

We performed further computational analysis using the dataset of the DepMap project, assessing if the effect of targeting DBF4 on fitness may be dependent on the levels of DRF1 expression. In several instances, when dealing with paralogues the gene effect of knocking out one of the paralogues directly correlates with the expression levels of the second, a phenomenon known as paralogue buffering (De Kegel et al. 2019 https://doi.org/10.1371/journal.pgen.1008466 ).

In the case of DBF4 and DRF1, this correlation is minimal (plot below: X and Y axes are DRF1 expression levels and DBF4 gene effect respectively, Pearson's correlation = 0.12) so that there are ~ 470 other genes whose expression is more correlated with DBF4 essentiality. Furthermore, by stratifying cell lines according to whether DBF4 was essential or not and then looking at DBF4B (DRF1) expression, we failed to see significant association (graph below).

Thus, this analysis reinforces the idea that if cooperation between DBF4 and DRF1 exists, it is particularly difficult to demonstrate. To date the interplay between DBF4 and DRF1 is only indicated by the partial impairment on MCM2 phosphorylation and CDC7 autophosphorylation observed in the individual KOs and by the fact that we were unable to obtaining viable double KO mutant clones. We recognise that the latter is a negative result and double KO may be generated in other cellular models or with different strategies.

We are happy to include the above computational analysis in a revised manuscript and to expand the discussion on the essentiality of CDC7, DBF4 and DRF1.

The effects of directly inhibiting CDC7 with 10 microM XL413 (concentration used in this study) are indeed stronger than DBF4 KO / depletion on both DNA synthesis (Fig 2A-B) and MCM2 phosphorylation (Fig 4A and Fig 5A).

We and others have previously shown that CDC7 inhibition by XL413 causes a dose dependent decrease in MCM2 phosphorylation and DNA synthesis. Importantly in the experiments where XL413 was titrated on MCF10A cells from 0.3 microM to 80 microM, we demonstrated that these parameters are uncoupled and that doses that are ~20-fold higher are required to cause a strong impediment of DNA synthesis compared to the dose required to cause full MCM2 dephosphorylation (Rainey et al. 2017 https://doi.org/10.1021/acschembio.7b00117 ).

DBF4 deficiency only partially affects MCM2 phosphorylation thus it is comparable to very low doses of XL413, that we can estimate to be in the range between 1 and 2 microM.

Minor points

• Title in Pag 12. "DBF4 mediates the majority of CDC7 functions in the replication stress response". In this section the authors address only the role of CDC7 in checkpoint signalling but not in other processes related to the replication stress response.

We agree and we have modified the title of this section accordingly.

• Figure 2. "EdU incorporation in late S-phase/ per cell" is clearer

We have modified the label of this figure.

• Right panels in Figures 3A and 3B are duplicated

We sincerely apologise for the mistake occurred while assembling the figure. The figure has been corrected, and shows that the changes in the replication timing with the CDC7i or with DBF4-KO are indeed similar but not identical.

**Referees cross-commenting**

I am aware of the difficulty to sort out the detection problem, a major handicap of the work. Immunoprecipitation as suggested by rev. 3 might be an interesting possibility. The results should be published, in any case, as they are well performed and try to answer a relevant question. But, if finally the authors fail to detect the proteins, they should make clear in the paper the limitation of their conclusions by the possibility that the expression of the regulators is not completely eliminated or could be altered. Indeed, the apparent contradiction with Suski's results raised by Rev 3 might be discussed in this context.

We appreciate the reviewer’s recognition of the technical problems we have encountered. We are glad that we now are in a position to provide evidence of impairment of DBF4 and DRF1 expression in the engineered cells (discussed above and reported in new Figure S1 and S2).

Also, it is important to explain the lack of synergism when combining the edited mutations with siRNAs.

In a revised manuscript we will explain the potential reasons why lack of synergism either doesn’t exist or is not observed, as discussed above.

Reviewer #2 (Significance (Required)):

In summary, the work is relevant and interesting, but the lack of controls about the effect of the edition rises important concerns about the conclusions. It is evident from the acknowledgment section that the authors have tried without success to generate specific antibodies. An alternative possibility would be 1) to get similar results with at least two clones addressing different exons (actually, only one clone was used for DRF1 in most cases) and 2) show synergistic effects for the more important phenotypes in edited cells transfected with efficient siRNAs. This is particularly important for DRF1-defective cells, which show no phenotypes except for an increase in micronuclei. If DBF4 is not essential because the complementary activity of DRF1, impairment of DBF4 expression with siRNAs in DRF1 deficient cells should cause synergistic defects at least in DNA replication and cell viability.

We hope we have satisfactory addressed this reviewer’s comments, by providing experimental evidence of the impairment of DBF4 and DRF1 expression/function in the engineered cells and several points for discussion addressing the lack of obvious synergy between DBF4 and DRF1.

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

Summary Assembly of the CMG helicase during DNA replication initiation is regulated by the DBF-Dependent Kinase known as CDC7 (or DDK), which also plays roles at DNA replication forks during elongation. In vertebrates, DDK has two regulatory subunits called DBF4 and DRF1. Until now, the division of labour between these two activators of CDC7 was poorly understood in mammalian cells. To address this issue, the authors used CRISPR-Cas9 to edit the DBF4 and DRF1 genes in immortalised human breast cells (MCF10A), thereby truncating key domains of the DBF4 and DRF1 proteins. The DBF4-deficient and DRF1-deficient lines are viable, whereas the double mutant was unobtainable and likely inviable, as reported previously by the authors for knockout of CDC7 in MCF10A cells. The authors compare the DBF4-deficient and DRF1-deficient lines with the CDC7 inhibitor XL413, providing evidence that DBF4 has the major role in supporting CDC7 activity in MCF10A cells compared to DRF1, in terms of DNA replication, origin firing, fork progression, and checkpoint activation. Curiously, DRF1 appears to be more important in preventing the formation of micronuclei - another phenotype seen upon inhibition of CDC7 kinase activity.

Major comments: The data are of high quality and the key conclusions are convincing, although it is unfortunate that the authors were not able to monitor the level of DBF4 and DRF1 by immunoblotting to validate their edited cell lines. The authors previously reported using immunoprecipitation of CDC7, DBF4 and DRF1 (Tenca et al, 2007, 10.1074/jbc.M604457200) to monitor DDK subunits in HeLa cells, which would presumably have been helpful here in MCF10A cells. Nevertheless, the DNA sequence of the edited clones indicates frameshift mutations that lead to premature STOP codons, and the various phenotypes reported in this manuscript are consistent with loss of DBF4 / DRF1 function as described.

We thank the reviewer the time an effort in carefully assessing the manuscript, and with his/her positive assessment.

We have now included experimental evidence indicating that DBF4 expression is deficient in the DBF4 KO cells used in this study and that the interaction with DRF1 and CDC7 is deficient in the DRF1-KO cells using the same Co-IP strategy previously reported in Hela cells. Please see also the response to reviewer #2 to the same point.

Minor comments: 1. The authors should discuss their data in the context of the recent study by Suski et al (https://doi.org/10.1038/s41586-022-04698). The latter study reported that knockout of DBF4 in mouse fibroblasts impairs proliferation but is not lethal, in agreement with the present manuscript, but Suski et al also argue that CDC7 is dispensable for DNA replication in mammalian cells due to redundancy with CDK1.

The requirement for CDC7 kinase activity for genome duplication in mammalian cells has become a contentious point of debate. CRISPR screens in more than 1000 cell lines indicate that CDC7 is a core essential gene required for proliferation (DepMap.org). Clearly human cells can clearly withstand reduced CDC7 activity, and several proteins contribute both positively and negatively to the effectiveness of CDC7 inhibition in DNA replication and cell proliferation e.g. RIF1 depletion, ATR inhibition, PTBP1 mutation. (Hiraga et al. 2017 https://doi.org/10.15252/embr.201641983 ; Rainey et al. 2020 https://doi.org/10.1016/j.celrep.2020.108096 : Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004 ; Göder et al. 2023 https://doi.org/10.1016/j.isci.2023.106951).

Specifically CDK1-phosphporylatyon of RIF1 was shown to disrupt RIF1/PP1 interaction and PP1’s ability to counteract CDC7-dependnet phosphorylation of the MCM complex (Moiseeva et al. 2019 https://doi.org/10.1073/pnas.1903418116 ; Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004). Thus increased CDK1 activity can be helpful in dealing with low levels of CDC7 kinase.

Suski et al argue that CDC7 is dispensable for DNA replication in human cells based on acute degradation of CDC7 or by its inhibition using an “Shokat type” analogue sensitive CDC7 allele. However, another study showed that DNA replication is not completed using the same approach and the same analogue sensitive allele (Jones et al. 2021 https://doi.org/10.1016/j.molcel.2021.01.004). In mouse embryonic stem cells, the Masai group had previously shown that CRE-Lox mediated inactivation of mDBF4 leads to a strong decrease of DNA synthesis and that mDBF4, like mCDC7 is essential for cell ES cells viability (Kim et al, 2002 https://doi.org/10.1093/emboj/21.9.2168 and Yamashita 2005 https://doi.org/10.1111/j.1365-2443.2005.00857.x ). Intriguingly mDRF1 has yet not been identified nor characterised. In our opinion, the simplest explanation to reconciliate the different reports is that human and mouse CDC7 are indeed required for DNA replication and for cell proliferation, but the phenotype of the most severe effects of its inhibition requires the complete loss of function of the kinase and may be delayed in time. We are happy to add these considerations in the discussion section of the revised manuscript.

1. Some discussion of the increased frequency of micronuclei in DRF1-deficient cells compared to DBF4-deficient lines would be useful (c.f. Figure 1F-G).

In the discussion we have suggested that the increase of micronucleated cells in the DRF1 deficient clones “could be consistent with a (DRF1) specific but not yet identified function in chromosome segregation, in the fine-tuning of DNA replication or the DNA repair process”. Of interest, CDC7 kinase was recently involved in modulating ATR function in cytokinetic abscission, and impairment of this process can lead to increase frequency of micro nucleated cells (Luessing et al. 2023 https://doi.org/10.1016/j.isci.2022.104536 ). It is possible that this new role of CDC7 could be dependent on DRF1, an hypothesis at present purely speculative, that we will be testing in the future. We are happy to add these considerations to the discussion section of the revised manuscript.

1. It would be helpful to present actual p values in Figure 2, rather than asterisks.

Asterisks report the range in which the p values fall into, which currently is specified in the legend. These can be substituted with actual numbers in the figures, and we will comply with the requirement of the journal in which the manuscript will be accepted.

Reviewer #3 (Significance (Required)):

The main strength of this manuscript is the exploration of the division of labour between DBF4 and DRF1 in human cells, regarding the roles of CDC7 kinase during DNA replication initiation, fork progression and checkpoint control. A limitation would be the failure to monitor the level of DBF4 and DRF1 in the CRISPR-edited cell lines, whilst it is also possible that the relative roles of DBF4 and DRF1 might vary in different cell types.

Previous studies of DNA replication in Xenopus egg extracts (e.g. Takahashi et al, 2005: doi: 10.1101/gad.1339805) indicated that DRF1 is the dominant activator of CDC7. In contrast, past work from the current authors (Tenca et al, 2007, 10.1074/jbc.M604457200) indicated that DBF4 is the major partner of CDC7 in human HeLa cells, at least at the level of promoting MCM2 phosphorylation (the only parameter monitored in the previous study, whereas the present manuscript goes much deeper into the various roles of CDC7 in DNA replication control and focusses on the role of CDC7 at replication forks and in checkpoint control).

This study should be of interest to those studying chromosome replication, checkpoints and genome integrity. It should also interest those with a more clinical perspective, due to the potential importance of CDC7 kinase inhibitors as anti-cancer agents.

My own expertise is in the field of chromosome replication.

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Referee #3

Evidence, reproducibility and clarity

Summary

Assembly of the CMG helicase during DNA replication initiation is regulated by the DBF-Dependent Kinase known as CDC7 (or DDK), which also plays roles at DNA replication forks during elongation. In vertebrates, DDK has two regulatory subunits called DBF4 and DRF1. Until now, the division of labour between these two activators of CDC7 was poorly understood in mammalian cells. To address this issue, the authors used CRISPR-Cas9 to edit the DBF4 and DRF1 genes in immortalised human breast cells (MCF10A), thereby truncating key domains of the DBF4 and DRF1 proteins. The DBF4-deficient and DRF1-deficient lines are viable, whereas the double mutant was unobtainable and likely inviable, as reported previously by the authors for knockout of CDC7 in MCF10A cells. The authors compare the DBF4-deficient and DRF1-deficient lines with the CDC7 inhibitor XL413, providing evidence that DBF4 has the major role in supporting CDC7 activity in MCF10A cells compared to DRF1, in terms of DNA replication, origin firing, fork progression, and checkpoint activation. Curiously, DRF1 appears to be more important in preventing the formation of micronuclei - another phenotype seen upon inhibition of CDC7 kinase activity.

Major comments:

The data are of high quality and the key conclusions are convincing, although it is unfortunate that the authors were not able to monitor the level of DBF4 and DRF1 by immunoblotting to validate their edited cell lines. The authors previously reported using immunoprecipitation of CDC7, DBF4 and DRF1 (Tenca et al, 2007, 10.1074/jbc.M604457200) to monitor DDK subunits in HeLa cells, which would presumably have been helpful here in MCF10A cells. Nevertheless, the DNA sequence of the edited clones indicates frameshift mutations that lead to premature STOP codons, and the various phenotypes reported in this manuscript are consistent with loss of DBF4 / DRF1 function as described.

Minor comments:

1. The authors should discuss their data in the context of the recent study by Suski et al (https://doi.org/10.1038/s41586-022-04698). The latter study reported that knockout of DBF4 in mouse fibroblasts impairs proliferation but is not lethal, in agreement with the present manuscript, but Suski et al also argue that CDC7 is dispensable for DNA replication in mammalian cells due to redundancy with CDK1.
2. Some discussion of the increased frequency of micronuclei in DRF1-deficient cells compared to DBF4-deficient lines would be useful (c.f. Figure 1F-G).
3. It would be helpful to present actual p values in Figure 2, rather than asterisks.

Significance

The main strength of this manuscript is the exploration of the division of labour between DBF4 and DRF1 in human cells, regarding the roles of CDC7 kinase during DNA replication initiation, fork progression and checkpoint control. A limitation would be the failure to monitor the level of DBF4 and DRF1 in the CRISPR-edited cell lines, whilst it is also possible that the relative roles of DBF4 and DRF1 might vary in different cell types.

Previous studies of DNA replication in Xenopus egg extracts (e.g. Takahashi et al, 2005: doi: 10.1101/gad.1339805) indicated that DRF1 is the dominant activator of CDC7. In contrast, past work from the current authors (Tenca et al, 2007, 10.1074/jbc.M604457200) indicated that DBF4 is the major partner of CDC7 in human HeLa cells, at least at the level of promoting MCM2 phosphorylation (the only parameter monitored in the previous study, whereas the present manuscript goes much deeper into the various roles of CDC7 in DNA replication control and focusses on the role of CDC7 at replication forks and in checkpoint control).

This study should be of interest to those studying chromosome replication, checkpoints and genome integrity. It should also interest those with a more clinical perspective, due to the potential importance of CDC7 kinase inhibitors as anti-cancer agents.

My own expertise is in the field of chromosome replication.

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Referee #2

Evidence, reproducibility and clarity

CDC7 is a master cell cycle kinase with essential functions in DNA replication and important roles in the DNA damage response. For its functions, CDC7 relies on a regulatory factor, DBF4, which is essential in many species but not in human cells as a consequence of the presence of a second DBF4-related factor, DRF1. In this work, Göder and colleagues study the relative relevance of these regulatory proteins in CDC7 roles. Their study reveals DBF4 as the major regulatory subunit both in DNA replication, DNA damage checkpoint and fork dynamics. The objective of the study is highly relevant to understand an essential cell cycle kinase with potential applications in cancer therapies, the experiments are well performed and the conclusions are "in principle" sound.

The major handicap of the study is the absence of western blots showing the elimination of DBF4 and DRF1 in the edited cell lines due to the lack of specific antibodies. The authors have generated homozygous mutations that lead to premature stop codons behind critical CDC7 domains. However, as they mention, it is not possible to fully exclude some proteins arising from internal start sites or exon skipping events with residual (functional or altered, and not necessarily residual) activity. This is not unexpected, especially for essential proteins. This would not be a major handicap if the study were focused in a specific factor because it would only question the impact of but not the affected function, but it aims to compare the relative effect of two defective genes. In this case, it is essential to confirm that both genes are eliminated, at least to the same degree. The computational analysis in Figure 1C is consistent with the major conclusion about the primary regulatory role of DBF4 in replication, but it is insufficient to validate the specific phenotypes addressed in the study. Indeed, there is a result that is hard to understand if the edited cell lines are defective in the expression of the regulators, specially DRF1. Figure S2D-E shows no synergistic defect in DNA synthesis when the second regulator is knock down with specific siRNAs, not even DRF1 defective cell lines treated with a siDBF4 that reduces its expression 10 times. Also, it is not clear why the defects, specially in DBF4-defective cell lines, are less severe than in cells treated with an inhibitor that causes a partial inhibition of CDC7. If it is due to the expression of DRF4, a siRNA against DRF4 should cause more severe defects.

Minor points

• Title in Pag 12. "DBF4 mediates the majority of CDC7 functions in the replication stress response". In this section the authors address only the role of CDC7 in checkpoint signalling but not in other processes related to the replication stress response.
• Figure 2. "EdU incorporation in late S-phase/ per cell" is clearer
• Right panels in Figures 3A and 3B are duplicated

Referees cross-commenting

I am aware of the difficulty to sort out the detection problem, a major handicap of the work. Immunoprecipitation as suggested by rev. 3 might be an interesting possibility. The results should be published, in any case, as they are well performed and try to answer a relevant question. But, if finally the authors fail to detect the proteins, they should make clear in the paper the limitation of their conclusions by the possibility that the expression of the regulators is not completely eliminated or could be altered. Indeed, the apparent contradiction with Suski's results raised by Rev 3 might be discussed in this context. Also, it is important to explain the lack of synergism when combining the edited mutations with siRNAs.

Significance

In summary, the work is relevant and interesting, but the lack of controls about the effect of the edition rises important concerns about the conclusions. It is evident from the acknowledgment section that the authors have tried without success to generate specific antibodies. An alternative possibility would be 1) to get similar results with at least two clones addressing different exons (actually, only one clone was used for DRF1 in most cases) and 2) show synergistic effects for the more important phenotypes in edited cells transfected with efficient siRNAs. This is particularly important for DRF1-defective cells, which show no phenotypes except for an increase in micronuclei. If DBF4 is not essential because the complementary activity of DRF1, impairment of DBF4 expression with siRNAs in DRF1 deficient cells should cause synergistic defects at least in DNA replication and cell viability.

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Referee #1

Evidence, reproducibility and clarity

DBF4 and DRF1 knockout cells were generated and used to separate DBF4- and CDC7-dependent from DRF1- and CDC7-dependent activities. DBF4- and CDC7-dependent activities at replication forks were independent of DRF1. These include the replication timing pattern, replication fork velocity, DNA damage signaling. DBF4 is required to recruit CDC7 to active replication forks.

The study is in large part exceptional. The inclusion of quantitation for a modest bandshift on CDC7 in figure 2 (30% vs 50% reduced) is not justified given the abundance of the main band and our knowledge of the lack of linearity of western blot quantitation. This should be removed.

The only significant weakness in the paper is the explanation of the replication timing analyses in Figure 3. I don't understand what the differences between the plots equate to in terms of timing. I understand the replication of these regions that diverge is either early or late, but their were only two fractions of cells - 2N-3N and 3N-4N (the cells are "normal"). If this is the case, isn't the readout binary? a sequence either replicates in S phase between 2N and 3N or in S phase between 3N and 4N. Why are the differences so small? Are they only evident in a small population of cells? If that is the case, then what does the difference really mean? I think the description of these data needs to be precise.

Significance

I think this paper is a significant advance that should be published. CDC7 is a critical kinase and identifying its co-factor at the replication fork is important both for our understanding of mechanisms of DNA replication and the impact of CDC7 kinase inhibitors in the clinic. I think the majority of the experiments are well designed and the results are unambiguous and precisely described.

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Reply to the reviewers

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

This research article describes genetic identification and expression analyses of six Ephrin type-B receptor 4 (EPHB4) variants identified in patients with dilated cardiomyopathy (DCM). Variants were identified Variants were identified in a cohort of 573 patients enrolled through the multicenter DZHK-TORCH (TranslatiOnal Registry for CardiomyopatHies) study and the Institute for Cardiomyopathies Heidelberg registry. Expression of downstream molecules, CAV1 and CD36, was assessed in human cardiac tissues by immunohistochemistry. EPHB4 cardiac expression was assessed using recently published single-cell/nucleus RNA sequencing data (Nicin et al 2022) incorporating siRNA-seq data from two other studies (healthy cardiac tissue, Litvinukova et al 2020) and (hypertrophic/aortic stenosis, Nicin et al. 2020).

We thank the reviewer for the recommendations that have improved our manuscript.

Major Comments:

1. Details of identified truncating RBM20 and TTN variants must be provided. These should be integrated into Table 1 alongside each co-occurring EPHB4 variant. List whether the TTN truncating variant is located in the A-band and whether these variants would be adjudicated as pathogenic/likely pathogenic, variant of uncertain significance by ACMG and/or similarly refined DCM criteria (Morales et al. 2020, Circ-Genom Precis Med).

Details of the truncating RNM20 and TTN have been provided in the new supplementary table 1. As indicated in the table both mutations are pathogenic, and thus, most probable the cause for the disease in these patients. In case of TTN this is a truncating variant and is located in the M-band in exon 358, which is annotated with a PSI in DCM of 100% in cardiodb.org. The fact that these mutations are most probably the cause for DCM in these patients has been included in the discussion section and reads as follows:

Although it is most probable that in the case of the patients carrying TNN and RNM20 variants this would be the cause of the disease, this study further supports, the importance of EPHB4 regulating CD36 caveolar trafficking to the membrane, whether this happens in endothelial cells or cardiomyocytes, maintaining cardiac homeostasis in humans and its implication on DCM

1. Discuss co-occurrence of multiple EPHB4 variants in two patients (DCM1, DCM3) and identification of 2 EPHB4 variants in more than one proband.

As shown in Figure 1A, the detected variants are found in multiple domains of the protein, hence no clear hotspot is detected. We did not yet investigate on the exact mechanisms of action, however, when we compare the two patients with multiple EPHB4 variants, the average LVEF (echo) is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

Since we do not postulate the detected variants as independently disease-causing, and we also did not explicitly filter for very rare variants, it is not surprising that we find two variants in multiple patients. As stated above, we did not investigate this further, but evidence is growing that compound heterozygosity is playing a role in heritable diseases. It will be interesting to analyze e.g. phasing (Hofmeister et al., Nature Genetics, 2023) or additive (biallelic) effects, which have come to attention also in cardiomyopathies recently (Lipov et al., Nature Cardiovascular Research, 2023).

This fact has now been included in the manuscript, both in the results and in the discussion. It reads as follows:

Interestingly, two of the analysed patients present more than one variant of EPHB4 and we could identify the same variant in more than one patient (Table 1)

(…)

Nevertheless, two of the patients carrying one benign or likely benign also carry another variant classified as likely pathogenic or of uncertain significance (Table 1) and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

1. Three of the six variants (p.Lys635Asn, Val113Ile, Glu890Asp) are classified as Clinvar Benign/Likely Benign. Additionally, p.Glu890Asp has been identified in 50 homozygotes in gnomAD non-Finnish European population. These data cast doubt on the pathogenicity of these variants. These classifications, as well as VUS classification of p.Pro79Leu, should be listed in Table 1. The authors should reconcile the benign/likely benign Clinvar classifications with their presented evidence for pathogenicity in the discussion.

We have now included the ACMG classification in Table 1. Similar to the Clinvar classification, some of the variants are classified benign or likely benign. Still, the fact that the patients that carry them also carry another variant and that the histological findings are similar among the patients carrying an EPHB4 variant and different to those that don’t and the enriched presence of EPHB4 variants in the DCM population support our hypothesis that the Eph-ephrin signalling pathway plays a role in the development of DCM.

Nevertheless, we agree with the reviewer that the fact that some of these variants have been classified as benign, and the presence of mutations in other genes already related to DCM like TNN or RMM20 may suggest that the EPHB4 mutations may not be the only cause for the disease but rather have an additive effect. As a consequence, we have toned down our conclusions and the discussion reads now as follows:

Finally, although not as the main disease cause, this study not only supports the role of EPHB4 in the heart, but it also corroborates the importance of CD36 and CAV1 for the cardiac health, and has the potential to improve diagnosis and risk stratification tools for DCM. In addition, as other genes crucial for fatty acid transport may be involved in cardiac disease, this study may help identify new diagnostic or therapeutic targets.

1. CD36 and CAV1 expression are not quantified. Qualitatively, it is difficult to confirm CD36 reduction in DCM and disruption in EPHB4 variant samples as imaging parameters are not specified and do not appear to be standardized across treatments. Clearly state (either in the figure legend or in the methods) whether identical imaging parameters were used across panels 1C-1E. Note any differences in these parameters.

We have now quantified the two IHC. It is very clear that the total CD36 is significantly reduced in both groups when compared to the healthy donor (Figure for the reviewer 1A). In case of CAV1 this is not so evident, although the signal seems reduced this is not significant (Figure for the reviewer 1B). These new data have been included in the figure of the manuscript.

Figure for the reviewer 1. Quantification of (A) CD36 and (B) CAV1 in the immunohistochemistry analysis of patients biopsies. Data shown as mean ± SEM. (A) P value was calculated using one sample one sample Wilcoxon test for DCM and one sample t test for DCM EPHB4. Both cohorts where compared to the mean of HD. P value < 0.05 was considered significant. (B) P value was calculated with one sample t test for both cohorts. P value < 0.05 was considered significant.

All the images have been taken in the same conditions. The observed difference in the background is due to the disease conditions of the DCM samples. Furthermore, the apparent reduced number of capillaries observed in the DCM patients are caused by the hypertrophic state of the cardiomyocytes in the diseased state. These are bigger and thus, less cells and capillaries appear per picture. The parameters have been included in the methods and read as follow:

Immunohistochemistry was imaged in a Leica Stellaris confocal microscope. All images were obtained with 63x magnification and the same laser and gain intensities. Images were acquired using the software LAS X (Leica, version 4.4) and quantified using the Volocity Software (Quorum Technologies, version 6.5.1)

1. Why was EPHB4 membrane localization not assessed or reported?

We agree with the reviewer that this would be a very interesting point. Unfortunately, we had very limited amount of material and we did not have a proper working antibody.

1. A key finding of the manuscript is that all six variants produce similar histological impacts on CAV1 and CD36 expression, denoting downstream impacts of EPHB4 genetic disruption. There is no granular data presented to support this claim. Additional discussion is also required to address how the authors anticipate variants in functionally distinct domains on either side of the plasma membrane to similarly impact downstream expression of CAV1/CD36. Mapping to available crystal structures in the Protein Data Bank (PDB) may be insightful to determine which variants may be most likely to have an impact on heterotetramer formation or to exert dominant negative effects on receptor function.

As an appendix to this revision we have included a figure with representation images of all biopsies analysed to support our claim.

The whole protein structure is not solved and only some individual domains are present in the Protein Data Bank making difficult to analyse the effect on the tetramer without crystallising the whole protein.

1. Study limitations are not discussed and are significant. 5 of the 6 samples were from male patients, there are limitations to analyses of non-diverse patient ancestry, there is uncertainty regarding pathogenic contributions of variants in established DCM genes in 2/6 patients, data is limited to expression-only analyses highlighting need for additional functional modeling in cell or animal based systems.

We have now included a limitation sections that includes all the points raised by the reviewer. It reads as follows:

Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.

It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.

1. Language used in conclusions overstates study findings ["our results confirm a crucial role of the Eph-ephrin signaling pathway in DCM" (page 3), "this study not only confirms the crucial role of EPHB4 in the heart..." (page 8)]. Change to "suggest" or "support".

We have revised our discussion according to the limitations discussed in the previous remark and these words have been corrected.

Major Methods Comments:

1. DCM diagnostic criteria (clinical and imaging) for inclusion in the DZHK-TORCH study and the Institute for Cardiomyopathies Heidelberg registry should be stated or referenced. Likewise, describe and/or reference DCM exclusion criteria. State any relevant differences in DCM enrolment criteria for the two registries.

We have now included our inclusion criteria in the methods and include two references to support this. The paragraph reads as follows:

The criteria to be included in the study was reduced left ventricular ejection fraction (LVEF) <50% validated either with two independent image techniques or at two different time points with the same imaging technique. Furthermore, patients should include left ventricular dilation (LVEDD) >117% corrected with age and body surface according to the Henry-Formel formula (LVEDD= 45,3 * BSA1/3 – 0,03*Age –7,2). In both cases the heart were analysed either by echocardiography or magnetic resonance tomography (MRT)

1. Describe how the final cohort of 573 DCM patients was reached. (All patients with DCM in the DZHK-TORCH study/Heidelberg registry? All patients with available exome data meeting QC standards and having available cardiac tissue?).

From the 573 DCM patients, 100 have been recruited as part of the DZHK-TORCH registry and have been genome sequenced. Further 62 genomes and 411 exomes have been sequenced from patients of the cohort from the Institute for Cardiomyopathies (ICH) at the Heidelberg University Hospital.

From this cohort, we selected 6 patients with and 6 without an EPHB4 variant and received heart tissue slides from the pathology department.

1. State whether any family/segregation data is available for these patients.

DCM4 has a mother and aunt (mother’s sister) who are also affected by CMP. In case of DCM6, the mother was also diagnosed with CMP. Unfortunately, no further biomaterial nor genetic testing of those individuals is available. This has been included in the new limitation sections as described above.

1. Description of genetic testing methods are inadequate. Describe how genetic analyses were completed for each study/registry and how results were filtered/quality controlled. If sequencing methods were different across registries, state which patients were tested by which methods. If any testing was gene-targeted rather than whole exome/genome, list the specific DCM genes tested.

All data has been sequenced using Illumina paired-end technology with either 2x100bp or 2x150bp. Exome enrichment was achieved using SureSelect Human All Exon V6 Target Enrichment (Agilent Genomics) was used. Bioinformatics analysis pipeline was based on “Best Practices Guideline” from the Genome Analysis Toolkit (GATK) (https://gatk.broadinstitute.org/hc/en-us). Besides the analysis for EPHB4, we assessed further genes associated with cardiomyopathies (ACTC1, ACTN2, ALPK3, BAG3, CRYAB, CSRP3, DES, DMD, DSC2, DSG2, DSP, FLNC, GLA, HCN4, HRAS, JPH2, JUP, KRAS, LAMP2, LDB3, LMNA, MIB1, MYBPC3, MYH7, MYL2, MYL3, MYPN, NEXN, PKP2, PLN, PRDM16, PRKAG2, PTPN11, RAF1, RBM20, RYR2, SCN5A, SHOC2, TAZ, TMEM43, TNNC1, TNNI3, TNNT2, TPM1,TTN, TTR, VCL).

This is information has been included in the methods section.

1. Provide additional detail for human cardiac biopsies. Was the same chamber/tissue biopsied in all samples? Is an endomyocardial biopsy available for all 573 patients included in this study? If not, were additional EPHB4 variants identified in patients without biopsy samples?

All biopsies investigated are from left-ventricular tissue, accessed during cardiac catheterization.

We did find additional, mainly non-coding variants in the cohort. However, as the focus on the study was on the histological analysis of the CD36 and CAV1 expression, we did restrict our analysis to our selected samples as described in the response to comment 2.

1. Describe the source of the healthy control biopsy, alongside brief clinical detail establishing suitability as a control. Did DCM controls carry variants in known DCM genes (including truncating variants in RBM20 or TTN)? How were DCM controls selected?

The healthy control biopsy was kindly donated by Prof. Dettmeyer from the University Gießen. This is a postmortem sample with unrelated cause of death. Cardiac biopsy was examined to discard any pathological alterations. This sample originates from a 27 years old female, and thus ideal as a healthy sample. This information has been included in the methods.

1. List statistical analyses and associated experiments. (Page 5).

Statistical tests have been included in the figure legend of each experiment. This reads as follows:

(B) EPHB4 variant allelle frequency analysis. Each variant is compared in a paired wise manner between the two population. P value was calculated with a paired one-tailed Student’s t test comparing the frequencies of the different variants in the two populations.

And

(F) Quantification of CD36 and CAV1 expression in the immunohistochemistry analysis of patients biopsies. Data shown as mean ± SEM. In the case of CD36, P value was calculated using one sample one sample Wilcoxon test for DCM and one sample t test for DCM EPHB4. P value < 0.05 was considered significant. In the case of CAV1, P value was calculated with one sample t test for both cohorts. P value < 0.05 was considered significant. In both cases, the cohorts where compared to the mean of HD.

1. List microscopes/equipment and software used to complete immunohistochemistry experiments. Describe imaging parameters to facilitate comparisons between treatments in Figure 1C-E.

Immunohistochemistry was imaged in a Leica Stellaris confocal microscope. All images were obtained with 63x magnification and the same laser and gain intensities. Images were acquired using the software LAS X (Leica, version 4.4) and quantified using the Volocity Software (Quorum Technologies, version 6.5.1)

This paragraph has now been included in the methods section.

1. Please reword the following passage, which is almost verbatim to the same passage in Nicin et al. 2022.

Page 4

**"In brief, a combination of two human snRNA-seq datasets was used. Data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

Nicin et al. 2022 (https://doi.org/10.1038/s44161-022-00019-7)**

"Two human snRNA-seq datasets were used: data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

We have reworded the paragraph in the methods sections. Now it reads as follows:

Healthy cardiac tissue data was derived from the cardiac septum of 14 individuals 15. Subsequently, it was integrated with data from the septum of hypertrophc cardiac tissue from 5 patients with aortic stenosis 16.

Minor Comments:

1. Results: List source for Non-Finnish European Control cohort (gnomAD) (Page 5).

The Non-Finnish European Control cohort (gnomAD) was obtained from https://gnomad.broadinstitute.org/. This information has been included in the methods section.

1. Discussion: "all DCM patients" (page 6) requires clarification.

We have made clear that this refers to the patients analysed in this study. The new sentence reads as follows:

Furthermore, our results stress the importance of the endothelial CD36 in the onset of cardiac disease as all DCM patients analysed by immunohistochemistry show a downregulation of CD36 in the endothelium and warrant a more detailed assessment of genes involved in vascular function20

1. Discussion: Define acronyms. CSF, IL4, LPS (Page 7)

We have defined the acronyms in the discussion. The new sentence reads as follows:

CD36 expression is upregulated by the nuclear hormone transcription factor Peroxisome Proliferator-Activated Receptor-Gamma (PPAR-ɣ), cerebrospinal fluid (CSF) cytokines and Interleukin-4 (IL4). In the other hand, lipopolysaccharides (LPS) and dexamethasone downregulate its expression In microvascular endothelial cells, CD36 is downregulated by lysophosphatidic acid.

1. Table 1. Table is confusingly arranged. It would make more sense to organize the table by cDNA/AAchange to better correspond to Figure 1A. List the impacted protein domain for each variant in a separate column. It is also unclear how DCM allele frequencies were calculated as the reported number of patients (DCM1-6) carrying each variant do not universally correspond to the listed allele frequencies (see AFs of 0.0052 and 0.0208). Clarification should be added to the legend so it is clear to the reader how these frequencies were determined

In case of the EPHB4 variants table, we agree with the reviewer and to make the table more understandable we have removed the first three columns, which are the same for all variants. This information has been included in the table legend. Nevertheless, this information has been kept in the new Supplementary table 1 that contains the variants on the other DCM causing genes.

Regarding the calculation of the allele frequency we made by dividing the number of alleles found in the population by the total number of alleles in the population. This information has been included in the methods.

We want to note that we performed a mistake in the original table. We had calculated the frequencies by dividing the number of alleles by the number of individuals in the population. We have now corrected both Table 1 and Figure 1B.

1. Figure 1B. Add variant labels. Indicate relevant p-values for each variant. It is unclear to which comparison the p = 0.024 belongs. State in legend that 2 variants were omitted (presumably due to absence from gnomAD)

No variants were omitted in the representation of Figure 1B. Some of them have the same allele frequency in the DCM population and thus, the individual data points appear overlapping. The variants that were not detected in the genomAD population were considered as 0 for the representation and for the analysis.

For the comparison with P=0.024 (now corrected to 0.0011) between the two groups we have performed a one tail paired t test comparing the frequencies in both populations. The information regarding the test has been included in the figure legend and included in the methods section as indicated above.

1. Figure 1E. Add label to indicate which EPHB4 variant is depicted.

The DCM sample from which the images originates is now indicated in Figure 1E.

<br /> Referees cross-commenting****

As is, this manuscript is not ready for publication. Our comments are in complete alignment. Like the other reviewer, I also emphasize the need for other DCM genes tested to be listed. I also reiterate that any similarly worded passages to other published material must be corrected

Reviewer #1 (Significance): This study presents genetic and expression data on a novel DCM gene candidate (EPHB4) from a European cohort of 573 DCM patients. This work is of interest as much of genetic DCM remains unexplained and identification of novel genes and pathways will be critical to advance understanding of the disease and to develop novel treatments. Reported data will be of greatest interest to cardiovascular practitioners and translational/basic researchers working with genetic heart disease/DCM. The fact that cardiac tissue was available for histological analyses for all six patients is an asset. There are considerable weaknesses to the paper, as written. There is a lack of detail in the included genetic methods and results. While the premise of the study is intriguing, additional detail is required for identified TTN and RBM20 truncating variants and additional discussion is needed to resolve confusion regarding reported allele frequencies and benign/likely benign Clinvar classifications. Because study design is restricted to genetic and expression analyses, reported data do not address possible pathogenic mechanisms. Overall, there is insufficient data presented to confirm a role for EPHB4 in causing DCM. Manuscript-specific (as-opposed to study specific) weaknesses include insufficient methods detail, a lack of clarity in the presented genetic and expression data (particularly Figure 1), insufficiently described study limitations, and overstated study conclusions. These scientific and manuscript issues will need to be addressed for the manuscript to be suitable for publication.

Reviewer fields of expertise: cardiovascular genetics, DCM.

Insufficient expertise to evaluate statistical methods.

Reviewer #2 (Evidence, reproducibility and clarity):<br /> I reviewed a paper by Luxan et al. describing EPHB4 variants as a novel disease gene for dilated cardiomyopathy (DCM).

The short report is interesting, however, not enough evidence is given to convince me EPHB4 is indeed a novel disease gene for DCM. More work is needed before this can be published.

Major points:

1. Genetics: two individuals have EPHB4 variants together with DCM causing TTN tv or RBM20 variants. Which other DCM genes were excluded for the remaining four cases? GnomAD MAF of 0.008748404 suspiciously high.

So overall the small case number makes it hard to judge whether these are truly pathogenic variants.<br /> Could the authors attempt co-segregation of DCM with EPHB4 variant in families?

Unfortunately we do not have family information from these patients. We have included this in the new limitation sections in the discussion that reads as follows:

Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.

It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.

1. Only CADD tools was used for pathogenicity, several tools should be used. Is the structure solved? Structural predictions on the consequences of the variants should be done.

We have now included the ACMG classification in Table 1. As discussed above in the comments of Reviewer 1, some of the variants are classified as benign or likely benign. For this reason we have now toned down our conclusion suggesting that the EPHB4 may not be sufficient to trigger DCM but act as modifiers. This is supported by the fact that the histological analysis revealed that the patients carrying EPHB4 variants are similar among themselves and different to the other patients. Furthermore, our hypothesis is also supported by the fact that those patients carrying benign or potentially benign variants also carry another variant and the fact that they even have lower LVEF. The new classification has been included in the results and discussion sections and it reads as follows:

Nevertheless, the classification of the variants according to the American College of Medical Genetics (ACMG) 25 suggests that two of the variants are benign, two likely benign, one likely pathogenic and one variant of uncertain significance (Table1). Nevertheless, two of the patients carrying one benign or likely benign also carry another variant classified as likely pathogenic or of uncertain significance (Table 1) and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

And

Our analysis identified several variants in EPHB4 enriched in a cohort of DCM patients. According to the CADD score prediction, all these variants have a deleterious potential. Nevertheless, the ACMG classified some of the variants as benign or potentially benign. Also the fact, that one variant has identified in two non-related patients suggests that this variant may be benign for the protein. Nevertheless, two of the patients carrying a benign or potentially benign variant also carried another potentially pathogenic or of uncertain significance. During Eph-ephrin signalling, the binding of the ligand induces Eph receptor heterotetramers to initiate the signalling via Eph–Eph cis interactions30. Thus, variant EPHB4 molecules could have a dominant negative effect on these heterotetramers, and while maybe not completely abrogating its function, reducing the functionality of the heterotetramers. This observation could explain why the presence of one variant copy in the DCM patients of our cohort would be sufficient to reduce the activity of the Eph-ephrin signalling pathway. Although this shows that some of the variants may indeed not be the sole cause for DCM it shows that the Eph-ephrin signalling pathway, and in particular EPHB4 may be important for the development of DCM.

Only parts of the protein have been resolved and present in the Protein Data Base.

1. The microscopy Figure 1C-E is not convicing. Only one sample shown while 6 were available/investigated. I would not be comfortable to identify cardiomyocytes/endothelial cells from these sections

As an appendix to this document, we included figures with images obtained from all the analysed patients. These were not included on the original figure for space reasons.

These sections are perfect to identify cardiomyocytes and endothelial cells in cardiac tissue. First, endothelial cells, that form the microvasculature are labelled with ULEX, a well known marker of endothelial cells. Secondly, cardiomyocytes are really big cells easy to score for their size and location between the capillaries in the heart. Other cells present in the heart, like fibroblasts, macrophages, or pericytes would also be located in the space left in between cardiomyocytes but would need to be labelled for visualization. We believe that our interpretation of the immunohistochemistry pictures is correct.

1. Functional work is needed to understand the interplay between EPHB4, CAV1 and CD36. Such as transfecting mutant EPHB4 into cells and probing for altered localisation/attachment of binding partners, most likely in endothelial - cardiomyocyte co-culture systems.

Our study is based in our previous murine study in which we showed that the deletion of EphB4 or its ligand ephrinB2 would induce a phenotype similar to DCM in mice. At the molecular level, defects in the Ephb4 are linked to compromised caveolar function and reduced CAV1 phosphorylation, which involves the kinase Src, a known mediator of Eph receptor signalling. In the healthy heart, caveolar transport is required for the membrane translocation and correct function of fatty acid translocase FAT/CD36, which mediates the uptake of fatty acids. The objective of this follow up study was to study whether we could identify EPHB4 mutations in DCM patients. As seen in the results we have observed that there is an enrichment of EPHB4 variants in the DCM population. We think that the previous study supports our conclusions and hope that the reviewer agrees with us. Nevertheless, we agree with the reviewer that functional assays could be performed with every variant. We have included this in the new limitation sections of the manuscript described above.

Minor points:

1. Figure 1B does not make sense

Figure 1B confirms the enrichment of EPHB4 mutations in the DCM population. We have corrected the labelling to make this clearer. We have now labelled the figure “EPHB4 variant allele frequency in control and DCM population”.

1. Statistics: Which tests were performed, if normality tests were applied, which one was used?

The tests used for every comparison are included in the figure legend. In case of EPHB4 variant allele frequency, we performed a paired one-tailed Student’s t test comparing the frequencies of the different variants in the two populations. In case of the CD36 and CAV1 quantifications, we performed a two-tailed one sample t test. In this case, we compare the expression of CD36 and CAV1 to an hypothetical healthy population with mean equal 1 as que have used this value for normalization.

1. Please do not use contractions, e.g. 'can't' in discussion section

Contractions have been removed from the manuscript.

<br /> Referees cross-commenting****

Overall I agree with the other reviewer on the points raised.

Reviewer #2 (Significance): Description of EPHB4 as a novel DCM gene is of interest, but the current data are not convincing enough to make this statement.

Mechanistic work on the interplay of endothelial cells and cardiomyocytes and consequences of EPHB4 variants would make it a very compelling story.

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

The authors of this manuscript studied the prevalence of a population of Ephrin type-B receptor 4 (EPHB4) in a cohort of 573 DCM patients and found six new EPHB4 variants, possibly pathogenic based on the Combined Annotation Dependent Depletion (CADD) score and population frequency. Moreover, the authors perform immunofluorescence (IF) and histologic analysis on 6 EPHB4 variant carrying DCM patients, 6 DCM patients with wild type EPHB4 and one healthy control biopsy and found dysregulation of Caveolin 1 (CAV1) and CD36 (which are implicated in fatty acid transport in endothelial cells and cardiomyocytes) in both groups of DCM patients.

Major comments:

• Additional experiments are necessary to prove the hypothesis: for example, co-IF staining with endothelial markers should be provided. IF should be supported by western blots and qPCR.

The objective of this study was to explore whether we could identify EPHB4 mutants in a DCM cohort. Interestingly we have shown that EPHB4 mutations are enriched in the DCM population when compared to the general population. Nevertheless, we agree with the reviewer that a more in depth mechanistic study would improve the significance of the study. We have included a limitations section that reads as follows:

Although this study offers valuable insights to the potential implication of the Eph-ephrin signalling pathway in the development of DCM it has some limitations that need to be discussed. Despite finding increased presence of EPHB4 variants in the DCM population when compared to the healthy population, analysis of the identified variants in using different classifications (CADD and ACMG) not always predicted pathogenicity for these variants. For this reason, further experiments should be performed to determine the effect of every variant.

It is also important to note that given the lower number of patients analysed these are not age and gender matched. The EPHB4 carrying DCM patients were younger than the DCM patients carrying a wild type EPHB4 sequence and mainly male. Finally, no biomaterial nor genetic testing from family related patients is available.

• The DCM samples with wild type EPHB4, have no CD36: the mechanism by which a mutation in another gene could affect the Eph-ephrin signaling pathway should be at least discussed.

These patients do not have any mutation on EPHB4. Based in the literature and the previous murine study show that the Eph-ephrin signaling pathway is upstream of CD36. For these reasons we believe that our observation that shows that CD36 expression is reduced in all DCM patients confirms the important role of CD36 in cardiac homeostasis and the development of DCM. We further, as indicated in the discussion, other genes crucial for fatty acid transport may be involved in cardiac disease and thus, this study may help identify new diagnostic or therapeutic targets.

• The authors should discuss and possibly prove the correlation between mutant EPHB4 and CD36 and CAV1 expression and localization in endothelial cells vs cardiomyocytes and explain the mechanistic implications of co-localization of CAV1 with CD36.

In a previous study we showed that the deletion of EphB4 or its ligand ephrinB2 would induce a phenotype similar to DCM in mice. At the molecular level, defects in the Ephb4 are linked to compromised caveolar function and reduced CAV1 phosphorylation, which involves the kinase Src, a known mediator of Eph receptor signalling. In the healthy heart, caveolar transport is required for the membrane translocation and correct function of fatty acid translocase FAT/CD36, which mediates the uptake of fatty acids. We have expanded the introduction to explain the relationship between these molecules. It reads as follows:

Mechanistically, EPHB4 deficient endothelial cells are characterized by compromised caveolar function and reduced Caveolin 1 (CAV1) phosphorylation. EPHB4 is required for the phosphorylation of CAV1 at Tyr-149. The phosphorylation of CAV1 promotes the release of caveolae from the plasma membrane10. Caveolae are required for the correct membrane translocation of the fatty acid translocase FAT/CD3611 and fatty acids are used by cardiomyocytes to obtain about 50% to 70% of their energy12. Absence of CD36 in cardiomyocytes reduces fatty acid uptake by the cardiac muscle cells13 and accelerates the progression from compensated hypertrophy to heart failure14. Finally, some cardiomyopathies a causally related to defects in the synthesis of the proteins required for fatty acid uptake in the heart15.

• The available snRNAseq raw data are from normal subjects and aortic stenosis patients who are different from DCM patients. A better dataset would be the one from Reichart D, et al. Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 2022.

The single nucleus RNA sequencing data was used in an exploratory manner to study whether EPHB4 would also be expressed in cardiomyocytes. We did not perform any study on gene expression comparing the two groups. We believe that the use of this dataset is justified. We hope that the reviewer agrees with us.

• Furthermore, the link between the analysis done on the published snRNA seq datasets and the authors' own data is not clearly explained.

As we stated above and in the methods, we have used the single nucleus RNA sequencing to explore whether cardiomyocytes express EPHB4. The sentence in the methods reads as follows:

The single-nucleus-RNA-sequencing data set generated in the paper by Nicin et al.14 was used to explore EPHB4 expression in human cardiac cells

• DCM1 and DCM 3 carry 2 EPHB4 variants: please describe if the phenotype was more severe.

As discussed above in the response to reviewer 1, the two patients with multiple EPHB4 variants present an average LVEF (echo) of 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

This information has been included in the manuscript and reads as follows:

and interestingly, the average LVEF of the two patients with multiple EPHB4 variants is 17.5 compared to 38,67 for the remaining 4 patients with only one EPHB4 variant and 35,17 for the six non-EPHB4 variant-carriers. Although the sample number only allows for a semi-quantitively analysis, it still hints at a possible EPHB4-variant effect, which certainly needs verification in a larger cohort.

• Provide p values on suppl table 1. The 2 groups are not matched by age and maybe gender, and this could affect the histological findings.

We have not performed any comparison between the two groups in the characteristics shown in supplementary table 1. Nevertheless, we agree with the reviewers that the fact that the patients are not matched in age and gender is a limitation to our study. We have acknowledged this in the new included limitations section that is mentioned above.

• Please discuss why in the DCM population the EPHB4 variant is enriched as compared with controls. Causal role? Modifiers?

The deletion of EphB4 and its ligand ephrin-B2 induce DCM in mouse. The objective of this study was to determine whether there would be mutations in EPHB4 associated to DCM. We agree with the reviewer that in depth mechanistic studies both in vivo and in vitro would be required to determine the exact role of the here identified mutations in the development of DCM. This has been acknowledged in the new limitations sections and indicated in the discussion of the results as follows:

Finally, this study not only supports the crucial role of EPHB4 in the heart, but it also corroborates the importance of CD36 and CAV1 for the cardiac health, and has the potential to improve diagnosis and risk stratification tools for DCM. Nevertheless, whether mutations in EPHB4 are causative or modifiers of the disease should be further studied. In addition, as other genes crucial for fatty acid transport may be involved in cardiac disease, this study may help identify new diagnostic or therapeutic targets.

• The data and the methods are presented in such a way that they could be reproduced however,

We thank the reviewer for the positive comment on our methods section.

• At least 2 more healthy controls should be included, and the DCM groups should be matched by gender and age.

Healthy donor biopsies are very rare and difficult to obtain. Although we agree with the reviewer that this could strengthen our study, we cannot add more healthy biopsies. We hope the reviewer understands this.

As stated above, we have included a limitation section in the manuscript discussing the issue with the gender and age.

• The causal mutation of the DCM patients should be provided.

Only 35% of DCM cases have been related to mutations in genes encoding cytoskeletal, sarcomere or nuclear envelope proteins. In our case, the DCM patients that we use do not carry a variant in any of the DCM known genes. We have now expanded the methods sections explaining the inclusion criteria for the DCM patients including this issue:

The criteria to be included in the study was reduced left ventricular ejection fraction (LVEF) <50% validated either with two independent image techniques or at two different time points with the same imaging technique. Furthermore, patients should include left ventricular dilation (LVEDD) >117% corrected with age and body surface according to the Henry-Formel formula (LVEDD= 45,3 * BSA1/3 – 0,03*Age –7,2). In both cases the heart were analysed either by echocardiography or magnetic resonance tomography (MRT).

Minor comments:

• I would explain in more detail the interactions among EPHB4, CD36 and CAV1 in the introduction, as the readers may not be familiar with this pathway.

We have completed the introduction expanding the paragraph where the relationship between EPHB4, CD36 and CAV1 is presented. It now reads as follows:

Mechanistically, EPHB4 deficient endothelial cells are characterized by compromised caveolar function and reduced Caveolin 1 (CAV1) phosphorylation. EPHB4 is required for the phosphorylation of CAV1 at Tyr-149. The phosphorylation of CAV1 promotes the release of caveolae from the plasma membrane10. Caveolae are required for the correct membrane translocation of the fatty acid translocase FAT/CD3611 and fatty acids are used by cardiomyocytes to obtain about 50% to 70% of their energy12. Absence of CD36 in cardiomyocytes reduces fatty acid uptake by the cardiac muscle cells13 and accelerates the progression from compensated hypertrophy to heart failure14. Finally, some cardiomyopathies a causally related to defects in the synthesis of the proteins required for fatty acid uptake in the heart15.

• Panel B in Fig 1 shows 4 variants and not 6.

All variants are shown in the panel As stated in the response to reviewer 1, it the fact that some variants have the same value that induces to think that only four are shown. The variants that do not appear in the genomAD have been considered 0 for this analysis.

• IF in Fig 1: make sure that control and DCM are at the same magnification.

Both control and DCM are at the same magnification. The reason why it looks different is the DCM phenotype. Cardiomyocytes are hypertrophic in the in the disease samples giving the impression that they are shown in a higher magnification.

• The authors analyze snRNA seq data from available datasets and not from their own patients: so, the paragraph title in the method section should be changed as it is misleading.

We have changed the title of this section of the methods. We have labelled it now “Analysis of single-nucleus-RNA-sequencing”.

Reviewer #3 (Significance): Despite the main focus of the manuscript is EPHB4, dysregulation of CD36 and its interaction with CAV1 seem to be a common mechanism in the pathogenesis of all DCM. The significance of these findings is higher than the role of EPHB4 alone and should be improved.<br /> Metabolic abnormalities, mainly affecting the fatty acid metabolism, have been described as causes or modifiers of DCM pathogenesis but in my knowledge the role of EPHDB4, CD36 and CAV 1 have not been studied in human tissues. The discovery of the mechanisms through which dysregulation of metabolism is induced by DCM genetic mutations would be an advance in the field. However, the paper in the present form is not going to have a significant impact. There is no clear connection between the sets of experiments and more mechanistic experiments should be provided to prove causality. This may take months or even years depending on the availability of human tissues and resources.

The type of audience interested in this research are mainly translational scientists mainly in the field of genetic cardiomyopathies. Furthermore, the elucidation of the metabolic effects of genetic mutations on DCM evolution may be of interest in the field of heart failure in general.

The focus of my research is genetic and molecular pathogenesis of cardiomyopathies.

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Referee #3

Evidence, reproducibility and clarity

Summary:

The authors of this manuscript studied the prevalence of a population of Ephrin type-B receptor 4 (EPHB4) in a cohort of 573 DCM patients and found six new EPHB4 variants, possibly pathogenic based on the Combined Annotation Dependent Depletion (CADD) score and population frequency. Moreover, the authors perform immunofluorescence (IF) and histologic analysis on 6 EPHB4 variant carrying DCM patients, 6 DCM patients with wild type EPHB4 and one healthy control biopsy and found dysregulation of Caveolin 1 (CAV1) and CD36 (which are implicated in fatty acid transport in endothelial cells and cardiomyocytes) in both groups of DCM patients.

Major comments:

• Additional experiments are necessary to prove the hypothesis: for example, co-IF staining with endothelial markers should be provided. IF should be supported by western blots and qPCR.
• The DCM samples with wild type EPHB4, have no CD36: the mechanism by which a mutation in another gene could affect the Eph-ephrin signaling pathway should be at least discussed.
• The authors should discuss and possibly prove the correlation between mutant EPHB4 and CD36 and CAV1 expression and localization in endothelial cells vs cardiomyocytes and explain the mechanistic implications of co-localization of CAV1 with CD36.
• The available snRNAseq raw data are from normal subjects and aortic stenosis patients who are different from DCM patients. A better dataset would be the one from Reichart D, et al. Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 2022.
• Furthermore, the link between the analysis done on the published snRNA seq datasets and the authors' own data is not clearly explained.
• DCM1 and DCM 3 carry 2 EPHB4 variants: please describe if the phenotype was more severe.
• Provide p values on suppl table 1. The 2 groups are not matched by age and maybe gender, and this could affect the histological findings.
• Please discuss why in the DCM population the EPHB4 variant is enriched as compared with controls. Causal role? Modifiers?
• The data and the methods are presented in such a way that they could be reproduced however,
• At least 2 more healthy controls should be included, and the DCM groups should be matched by gender and age.
• The causal mutation of the DCM patients should be provided.

Minor comments:

• I would explain in more detail the interactions among EPHB4, CD36 and CAV1 in the introduction, as the readers may not be familiar with this pathway.
• Panel B in Fig 1 shows 4 variants and not 6.
• IF in Fig 1: make sure that control and DCM are at the same magnification.
• The authors analyze snRNA seq data from available datasets and not from their own patients: so, the paragraph title in the method section should be changed as it is misleading.

Significance

Despite the main focus of the manuscript is EPHB4, dysregulation of CD36 and its interaction with CAV1 seem to be a common mechanism in the pathogenesis of all DCM. The significance of these findings is higher than the role of EPHB4 alone and should be improved.

Metabolic abnormalities, mainly affecting the fatty acid metabolism, have been described as causes or modifiers of DCM pathogenesis but in my knowledge the role of EPHDB4, CD36 and CAV 1 have not been studied in human tissues. The discovery of the mechanisms through which dysregulation of metabolism is induced by DCM genetic mutations would be an advance in the field. However, the paper in the present form is not going to have a significant impact. There is no clear connection between the sets of experiments and more mechanistic experiments should be provided to prove causality. This may take months or even years depending on the availability of huma tissues and resources.

The type of audience interested in this research are mainly translational scientists mainly in the field of genetic cardiomyopathies. Furthermore, the elucidation of the metabolic effects of genetic mutations on DCM evolution may be of interest in the field of heart failure in general.<br /> The focus of my research is genetic and molecular pathogenesis of cardiomyopathies.

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Referee #2

Evidence, reproducibility and clarity

I reviewed a paper by Luxan et al. describing EPHB4 variants as a novel disease gene for dilated cardiomyopathy (DCM).

The short report is interesting, however, not enough evidence is given to convince me EPHB4 is indeed a novel disease gene for DCM. More work is needed before this can be published.

Major points:

1. Genetics: two individuals have EPHB4 variants together with DCM causing TTN tv or RBM20 variants. Which other DCM genes were excluded for the remaining four cases? GnomAD MAF of 0.008748404 suspiciously high.<br /> So overall the small case number makes it hard to judge whether these are truly pathogenic variants.<br /> Could the authors attempt co-segregation of DCM with EPHB4 variant in families?
2. Only CADD tools was used for pathogenicity, several tools should be used. Is the structure solved? Structural predictions on the consequences of the variants should be done.
3. The microscopy Figure 1C-E is not convicing. Only one sample shown while 6 were available/investigated. I would not be comfortable to identify cardiomyocytes/endothelial cells from these sections
4. Functional work is needed to understand the interplay between EPHB4, CAV1 and CD36. Such as transfecting mutant EPHB4 into cells and probing for altered localisation/attachment of binding partners, most likely in endothelial - cardiomyocyte co-culture systems.

Minor points:

1. Figure 1B does not make sense
2. Statistics: Which tests were performed, if normality tests were applied, which one was used?
3. Please do not use contractions, e.g. 'can't' in discussion section

Referees cross-commenting<br /> Overall I agree with the other reviewer on the points raised.

Significance

Description of EPHB4 as a novel DCM gene is of interest, but the current data are not convincing enough to make this statement.

Mechanistic work on the interplay of endothelial cells and cardiomyocytes and consequences of EPHB4 variants would make it a very compelling story.

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Referee #1

Evidence, reproducibility and clarity

Summary:

This research article describes genetic identification and expression analyses of six Ephrin type-B receptor 4 (EPHB4) variants identified in patients with dilated cardiomyopathy (DCM). Variants were identified Variants were identified in a cohort of 573 patients enrolled through the multicenter DZHK-TORCH (TranslatiOnal Registry for CardiomyopatHies) study and the Institute for Cardiomyopathies Heidelberg registry. Expression of downstream molecules, CAV1 and CD36, was assessed in human cardiac tissues by immunohistochemistry. EPHB4 cardiac expression was assessed using recently published single-cell/nucleus RNA sequencing data (Nicin et al 2022) incorporating siRNA-seq data from two other studies (healthy cardiac tissue, Litvinukova et al 2020) and (hypertrophic/aortic stenosis, Nicin et al. 2020).

Major Comments:

1. Details of identified truncating RBM20 and TTN variants must be provided. These should be integrated into Table 1 alongside each co-occurring EPHB4 variant. List whether the TTN truncating variant is located in the A-band and whether these variants would be adjudicated as pathogenic/likely pathogenic, variant of uncertain significance by ACMG and/or similarly refined DCM criteria (Morales et al. 2020, Circ-Genom Precis Med).
2. Discuss co-occurrence of multiple EPHB4 variants in two patients (DCM1, DCM3) and identification of 2 EPHB4 variants in more than one proband.
3. Three of the six variants (p.Lys635Asn, Val113Ile, Glu890Asp) are classified as Clinvar Benign/Likely Benign. Additionally, p.Glu890Asp has been identified in 50 homozygotes in gnomAD non-Finnish European population. These data cast doubt on the pathogenicity of these variants. These classifications, as well as VUS classification of p.Pro79Leu, should be listed in Table 1. The authors should reconcile the benign/likely benign Clinvar classifications with their presented evidence for pathogenicity in the discussion.
4. CD36 and CAV1 expression are not quantified. Qualitatively, it is difficult to confirm CD36 reduction in DCM and disruption in EPHB4 variant samples as imaging parameters are not specified and do not appear to be standardized across treatments. Clearly state (either in the figure legend or in the methods) whether identical imaging parameters were used across panels 1C-1E. Note any differences in these parameters.
5. Why was EPHB4 membrane localization not assessed or reported?
6. A key finding of the manuscript is that all six variants produce similar histological impacts on CAV1 and CD36 expression, denoting downstream impacts of EPHB4 genetic disruption. There is no granular data presented to support this claim. Additional discussion is also required to address how the authors anticipate variants in functionally distinct domains on either side of the plasma membrane to similarly impact downstream expression of CAV1/CD36. Mapping to available crystal structures in the Protein Data Bank (PDB) may be insightful to determine which variants may be most likely to have an impact on heterotetramer formation or to exert dominant negative effects on receptor function.
7. Study limitations are not discussed and are significant. 5 of the 6 samples were from male patients, there are limitations to analyses of non-diverse patient ancestry, there is uncertainty regarding pathogenic contributions of variants in established DCM genes in 2/6 patients, data is limited to expression-only analyses highlighting need for additional functional modeling in cell or animal based systems.
8. Language used in conclusions overstates study findings ["our results confirm a crucial role of the Eph-ephrin signaling pathway in DCM" (page 3), "this study not only confirms the crucial role of EPHB4 in the heart..." (page 8)]. Change to "suggest" or "support".

Major Methods Comments:

1. DCM diagnostic criteria (clinical and imaging) for inclusion in the DZHK-TORCH study and the Institute for Cardiomyopathies Heidelberg registry should be stated or referenced. Likewise, describe and/or reference DCM exclusion criteria. State any relevant differences in DCM enrolment criteria for the two registries.
2. Describe how the final cohort of 573 DCM patients was reached. (All patients with DCM in the DZHK-TORCH study/Heidelberg registry? All patients with available exome data meeting QC standards and having available cardiac tissue?).
3. State whether any family/segregation data is available for these patients.
4. Description of genetic testing methods are inadequate. Describe how genetic analyses were completed for each study/registry and how results were filtered/quality controlled. If sequencing methods were different across registries, state which patients were tested by which methods. If any testing was gene-targeted rather than whole exome/genome, list the specific DCM genes tested.
5. Provide additional detail for human cardiac biopsies. Was the same chamber/tissue biopsied in all samples? Is an endomyocardial biopsy available for all 573 patients included in this study? If not, were additional EPHB4 variants identified in patients without biopsy samples?
6. Describe the source of the healthy control biopsy, alongside brief clinical detail establishing suitability as a control. Did DCM controls carry variants in known DCM genes (including truncating variants in RBM20 or TTN)? How were DCM controls selected?
7. List statistical analyses and associated experiments. (Page 5).
8. List microscopes/equipment and software used to complete immunohistochemistry experiments. Describe imaging parameters to facilitate comparisons between treatments in Figure 1C-E.
9. Please reword the following passage, which is almost verbatim to the same passage in Nicin et al. 2022.

Page 4<br /> "In brief, a combination of two human snRNA-seq datasets was used. Data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

Nicin et al. 2022 (https://doi.org/10.1038/s44161-022-00019-7)<br /> "Two human snRNA-seq datasets were used: data from healthy cardiac tissue from the septum of 14 individuals in the Litvinukova et al. study and data from location-matched hypertrophic cardiac tissues from five patients with aortic stenosis."

Minor Comments:

1. Results: List source for Non-Finnish European Control cohort (gnomAD) (Page 5).
2. Discussion: "all DCM patients" (page 6) requires clarification.
3. Discussion: Define acronyms. CSF, IL4, LPS (Page 7)
4. Table 1. Table is confusingly arranged. It would make more sense to organize the table by cDNA/AAchange to better correspond to Figure 1A. List the impacted protein domain for each variant in a separate column. It is also unclear how DCM allele frequencies were calculated as the reported number of patients (DCM1-6) carrying each variant do not universally correspond to the listed allele frequencies (see AFs of 0.0052 and 0.0208). Clarification should be added to the legend so it is clear to the reader how these frequencies were determined
5. Figure 1B. Add variant labels. Indicate relevant p-values for each variant. It is unclear to which comparison the p = 0.024 belongs. State in legend that 2 variants were omitted (presumably due to absence from gnomAD)
6. Figure 1E. Add label to indicate which EPHB4 variant is depicted.

Referees cross-commenting

As is, this manuscript is not ready for publication. Our comments are in complete alignment. Like the other reviewer, I also emphasize the need for other DCM genes tested to be listed. I also reiterate that any similarly worded passages to other published material must be corrected

Significance

This study presents genetic and expression data on a novel DCM gene candidate (EPHB4) from a European cohort of 573 DCM patients. This work is of interest as much of genetic DCM remains unexplained and identification of novel genes and pathways will be critical to advance understanding of the disease and to develop novel treatments. Reported data will be of greatest interest to cardiovascular practitioners and translational/basic researchers working with genetic heart disease/DCM. The fact that cardiac tissue was available for histological analyses for all six patients is an asset. There are considerable weaknesses to the paper, as written. There is a lack of detail in the included genetic methods and results. While the premise of the study is intriguing, additional detail is required for identified TTN and RBM20 truncating variants and additional discussion is needed to resolve confusion regarding reported allele frequencies and benign/likely benign Clinvar classifications. Because study design is restricted to genetic and expression analyses, reported data do not address possible pathogenic mechanisms. Overall, there is insufficient data presented to confirm a role for EPHB4 in causing DCM. Manuscript-specific (as-opposed to study specific) weaknesses include insufficient methods detail, a lack of clarity in the presented genetic and expression data (particularly Figure 1), insufficiently described study limitations, and overstated study conclusions. These scientific and manuscript issues will need to be addressed for the manuscript to be suitable for publication.

Reviewer fields of expertise: cardiovascular genetics, DCM.

Insufficient expertise to evaluate statistical methods.

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Reply to the reviewers

Revision summary.

Additional new data.

• CYPA expression levels in Scrm Vs KO Vs R55A isogenic cell lines as new Fig 1C.
• ATR signaling: western blot analysis of HU-induced p-CHK1 (S345) in Scrm, KO and R55A isogenic cell lines as new Suppl Fig 1B.
• MRN expression: western blot analysis of expression of NBS1, MRE11, RAD50 and MCM2 is Scrm, KO and R55A isogenic cell lines as new Suppl Fig 7A.
• NBS1 subcellular fractionation: western blot analysis of NBS1 from whole cell extract Vs cytoplasmic extract Vs nuclear extract comparing expression/distribution in Scrm, KO and R55A isogenic cell lines, as new Suppl Fig 7B.
• CYPA immunofluorescence (IF) staining on untreated and HU treated U2OS, as new Suppl Fig 7C.
• CYPA immunofluorescence (IF) staining on untreated and HU treated U2OS following pre-extraction, as new Suppl Fig 7D.
• DepMap Project Score Cancer Gene Dependency cell survival (“fitness”) following PPIA/CYPA-KO in breast carcinoma cell lines mapped against BRCA2 status, as a new Suppl Table 5.
• DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Neuroblastoma cell lines, as a new Suppl Spreadsheet 4.
• DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Multiple Myeloma cell lines, as a new Suppl Spreadsheet 4.
• DepMap Project Score Cancer Gene Dependency cell fitness following PPIA/CYPA-KO in Chronic Myelogenous Leukaemia cell lines, as a new Suppl Spreadsheet 4.

Revised and/or additional text.

The Abstract, Introduction, Materials & Methods, Results and Discussion have been amended as necessary, to facilitate the issues raised by the Reviewers.

Reviewer #1: We thank this reviewer for their understanding and appreciation of our CYPA study as espoused by their comprehensive summary of the content, importance, and potential implications of our work; “The manuscript presents clear and comprehensive data, demonstrating the profound impact of CYPA on DNA repair.” Furthermore, we very much appreciate their robust and complementary words regarding the significance of our work and its wide appeal; “The significance of this study is twofold: it adds a new layer to our understanding of DNA repair mechanisms and, importantly, it could point the way to novel therapeutic strategies for cancer. It will spark interest from molecular biologists to clinicians and pharmaceutical researchers.”

Query:

It's surprising to find that the loss of CYPA abolished HU-induced NBS1 foci, as the MRE11 interactive domain of NBS1 should remain intact in CYPA deficient conditions and the N-terminus of NBS1 is dispensable for ATM activation (Kim et al., 2017; Stracker and Petrini, 2011). A more detailed mechanistic explanation of this phenotype would be appreciated. The authors should check the subcellular localization of NBS1 and the stability of MRN in wildtype and CYPA KO cells. Additionally, including the kinetics of NBS1 foci formation using multiple timepoints in wildtype and CYPA KO cells after damage will further support the observation.

RESPONSE:

Regarding NBS1 foci formation, we note that rather than abolish HU-induced NBS1 foci formation, CYPA loss (through KO) and/or inhibition (through p.R55A) in fact results in a “…spontaneously elevated yet unresponsive amount of NBS1 foci/cells when compared to scrambled” (see original Fig 9A legend and associated Results section text). We have reinforced this observation in the revised Results section entitled ‘CYPA influences NBS1 and MDC1 foci formation’ and in the Discussion section. We do describe a kinetic impairment of RAD51 foci formation in the CYPA-engineered lines up to 16hrs post HU-treatment (Fig 6D). Our mechanistic working model is that CYPA interacts directly with NBS1 via a Pro residue within the short linking peptide between the FHA and BRCT1, and that this likely influences the relative dynamic positioning of the FHA with BRCA1-BRCT2, at least following acute HU treatment; replication fork stalling, likely biased towards ATR-dependent signaling initially, rather than that of ATM. The relative positioning of these functional domains can impact MRN function, and we discuss this possible mechanism in the section entitled ‘CYPA and the MRN complex’, with reference to the detailed structure-function analyses and complementary DDR activation models described by<br /> - Williams, R.S., et al., Nbs1 flexibly tethers Ctp1 and Mre11-Rad50 to coordinate DNA double-strand break processing and repair. Cell, 2009. 139(1): p. 87-99.<br /> and<br /> - Lloyd, J., et al., A supramodular FHA/BRCT-repeat architecture mediates Nbs1 adaptor function in response to DNA damage. Cell, 2009. 139(1): p. 100-11.<br /> and<br /> - Rotheneder, M., et al., Cryo-EM structure of the Mre11-Rad50-Nbs1 complex reveals the molecular mechanism of scaffolding functions. Mol Cell, 2023. 83(2): p. 167-185.e9.

The N-terminal FHA-BRCT region of NBS1 does indeed influence MRN recruitment and HRR execution, a point we highlight in the section entitled ‘CYPA influences NBS1 and MDC1 foci formation’, with reference to the seminal original observations of<br /> - Sakamoto, S., et al., Homologous recombination repair is regulated by domains at the N-<br /> and C-terminus of NBS1 and is dissociated with ATM functions. Oncogene, 2007. 26(41): p.6002-6009<br /> and<br /> - Tauchi, H., et al., The forkhead-associated domain of NBS1 is essential for nuclear foci formation after irradiation but not essential for hRAD50-hMRE11-NBS1 complex<br /> DNA repair activity. J Biol Chem, 2001. 276(1): p. 12-15.<br /> and<br /> - Zhao, S., W. Renthal, and E.Y. Lee, Functional analysis of FHA and BRCT domains of NBS1 in chromatin association and DNA damage responses. Nucleic Acids Res, 2002. 30(22): p. 4815-22.<br /> and<br /> - Cerosaletti, K.M. and P. Concannon, Nibrin forkhead-associated domain and breast cancer C-terminal domain are both required for nuclear focus formation and phosphorylation. J Biol Chem, 2003.<br /> 278(24): p. 21944-21951.

HU-unresponsive NBS foci (indicative of MRN dysfunction) and MDC1 foci formation are consistent with the DNA-R (i.e., DR-GFP reporter systems: Fig 3A-C and impaired RAD51 foci formation: Fig 6D) and resection-related phenotypes (Fig 6A-B) we report here and are also consistent with the relative resistance to HU-induced killing we report for CYPA-KO and CYPA-R55A cells (Fig 11A and as reported by Manthey, K.C., et al., NBS1 mediates ATR-dependent RPA hyperphosphorylation following replication-fork stall and collapse. J Cell Sci, 2007. 120(Pt 23): p. 4221-9).

At the reviewer’s request we include additional novel experimental data showing that MRN expression is stable and equivalent in control, CYPA-KO and CYPA-R55A cells (Suppl Fig 7A). We also provide evidence that NBS1 subcellular distribution (via extract fractionation) is not altered upon CYPA loss and/or inhibition (Suppl Fig 7B).

Query:

The authors showed that the interaction between CYPA and MRN didn't change after HU treatment. The authors should also include co-localization analysis of CYPA and NBS1 after HU.

RESPONSE:

At the reviewer’s suggestion we undertook a series of IF analyses concerning endogenous CYPA (i.e., +/- HU, +/- pre-extraction). We found that endogenous CYPA failed to form foci following HU thereby precluding CYPA-NBS1 foci co-localization analysis (Suppl Fig 7C-D).

Query:

The paper demonstrated that BRCA2 knockdown cells were sensitive to CsA. The authors should also examine CsA sensitivity in BRCA2 deficient cancer cells. In addition, the authors could elaborate more on their criteria for selecting cancers for CYPA inhibition, whether it is based on high genomic instability or an addiction to HRR for survival.

RESPONSE:

Despite repeated attempts we have been unable to successfully routinely culture the TNBC suspension line HCC1599 (BRCA2 c.4154_5572del1419 and p.K1517fs*23), consistent with its reported ~5 days population doubling time. Although not a tumour line per se, we also failed to effectively culture the FANC-D1 patient FB line HSC62 (BRCA2 c.8488-1 G>A (IVS19-1G>A)) to enable survival analysis. We provide new quantification analysis of the CsA survival on the H1299 conditional shBRCA2 line (Fig 11E). Additionally, we include a comprehensive new analysis of cell survival (“fitness”) of a range of breast carcinoma cell lines following PPIA/CYPA-KO, extracted from DepMap Project Score Cancer Gene Dependency portal (https://score.depmap.sanger.ac.uk/), and also specify the BRCA2 status of each line. Interestingly, we find that reduced BRCA2 copy number is more commonly associated with loss of fitness following PPIA/CYPA loss (Suppl Table 5). We also include similar cell line fitness datasets for each of the cancers for whom we demonstrate elevated sensitivity to CYPAi (i.e., Neuroblastoma, Multiple Myeloma and CML) (Suppl Spreadsheet 4). Fascinatingly, PPIA/CYPA loss clearly results in loss of fitness in most of these cancer cell lines. Collectively, these new independent comprehensive datasets support our argument that targeting CYPA in select cancer scenarios shows impact in the preclinical setting and may represent an effective new strategy.

The unifying features of the cancers showing elevated sensitivity to CYPAi are indeed high genomic instability, denoted by elevated RS and hence a dependency upon replication fork protection machinery. This would be consistent with the observed lethality of our CYPA-panel to shBRCA2, siXRCC3 and siRAD51C. The cancers are additionally characterised by aberrantly elevated HRR (i.e. an addiction to/dependency on HRR). This would be consistent with the observed lethality of our CYPA-panel to siCtIP, siRAD52, siXRCC3, and siRAD51C. At the Reviewer’s request we have reinforced and better clarified this point in the section Potential rational applications of CYPA inhibition in select cancers and in the Discussion.

Reviewer #2:

We thank this reviewer for their positive and supportive comments concerning our work; “Authors have quite conclusively explored the interaction between NBS1 and cyclophilinA as well as the putative proline residue important for this interaction.” We appreciate the constructive feedback concerning the range of consequences/impacts of CYPA impairment and we concur with their contention that “This manuscript will have broad interest from groups working on genomic stability, immunology as well as cancer therapy.”; a general view also voiced by Reviewer #1.

We do stress that whilst other prolyl isomerases have previously been linked to DNA repair (e.g., most notably the Parvulin family member PIN1), this is the first time that CYPA has been directly implicated in DNA repair, and the first time CYPA has been shown to directly interact with a known DNA-R protein (i.e. NBS1).

We believe that the comprehensive CYPA-BioID we describe is worthy of report and should serve as a very useful starting point for additional studies concerning CYPA biology, which is undoubtedly complex. The interactome will also function as a useful tool in helping dissect the clinically significant wider biological consequences of CYPA inhibition. Our interactome findings demonstrate that CYPA may influence DNA-R via multiple, and not necessarily mutually exclusive, routes. We do not argue that CYPA’s role in DNA-R is exclusively via NBS1/MRN. This is clearly demonstrated by our validation of CYPA interactions via co-IP with endogenous CYPA with proteins including PCNA, 53BP1, CHAMP1 and ILF2-3 complex (Fig 5). These are completely novel observations that furthermore reinforce the validity and efficacy of our experimental approach in leveraging the CYPA-BioID to provide new biological insight into this druggable prolyl cis-trans isomerase.

Query:

Authors show delayed S-phase transit along with reduced replication speed indicating replication stall. However, authors have not discussed how cyclophilinA might regulate replication (other than hypothesizing regarding altered dynamism of FHA-BRCT). It is conceivable that it could be an indirect effect on cellular metabolism or if authors believe it could be due to direct disruption to core replication machinery or signaling. In this regard, it will be helpful to see if there is shortening of (premature entry) G1 phase and comment on the status of the associated G1/S checkpoint.

RESPONSE:

The reviewer makes a very interesting and astute observation concerning the DNA replication phenotypes we report following CYPA loss and/or inhibition. The bases of these phenotypes are likely multifactorial, and we have revised the associated Discussion text to reflect this. Specifically, we highlight the elevated and unresponsive NBS1 and MDC1 foci seen in the CYPA-KO lines (Fig 9. i.e., persistent protein-DNA complexes) and dependence upon fork protection factors (XRCC3, RAD51C, BRCA2: Fig 11). We also report that a range of DNA replication factors are found in the CYPA-BioID (Fig 5A). Untangling the functional significance of these putative interactions would involve further study. Are they direct/indirect interactors? If direct, are they prolyl isomerase substrates or chaperone clients or regulated by liquid-liquid phase separation (LLPS)? Similarly, the CYPA-BioID throws-up an extensive set of RNA binding factors (Suppl Table 2), many of whom may conceivably contribute to the replication–transcription fork conflicts/collisions under conditions of CYPA-dysfunction. As this is the first comprehensive report of the cellular impacts of CYPA loss and inhibition, we thought it worth reporting the DNA replication associated phenotypes specifically to demonstrate the pleiotropic impact of loss and inhibition of this particular prolyl isomerase, to underscore its significance/importance. Although we have indeed found cell cycle phase transition impairments in our CYPA-KO and CYPA-R55A cells (for both G1-S and G2-M), these constitute additional studies requiring more thorough molecular-mechanistic characterization. We chose to focus on DNA repair for this first manuscript, as the CYPA-NBS1 interaction was the physical relationship for which we have assembled the most detailed and interconnected datasets, to-date. We do intend to pursue the cell cycle work as it too is derived from our CYPA-BioID (Suppl Spreadsheet 1), and we have already validated some of those relevant interactions by CYPA co-IP, but this is very much a work-in-progress. With this manuscript we’re endeavoring to tread a fine line by showcasing a wide range of cellular phenotypes resultant from CYPA loss and inhibition, but then also showing a deeper level of characterisation with at least one relevant interactor known to function in a range of DNA-R pathways wherein we’ve found impairments and dependencies.

Query:

In connection to this, it will also be interesting to see if the ATR/Chk1 signaling axis is intact in CYPA KO cells with or without additional DNA damage compared to WT.

RESPONSE:

At the reviewer’s request we include new data showing that HU-induced ATR-dependent CHK1 phosphorylation is normal in CYPA-KO and CYPA-R55A cells, and that ATR does not appear to be spontaneously activated in the absence of replication stress in these cells (Suppl Fig 1B).

Query:

Authors show that the P112 residue of NBS1 is important for the binding of cyclophilinA. What is the status of interaction among components of the MRN complex in CYPAKO cells and P112G NBS1? Further, what are the authors' thoughts on rescue experiments and whether P112G containing NBS1 to perform resection function.

RESPONSE:

We include new data showing normal expression of MRN components and normal subcellular localisation of NBS1 in the CYPA-KO and CYPA-R55A cells (Suppl Fig 7A-B). Regarding the interaction status of P112G, we show that this fails to co-IP endogenous CYPA when transiently expressed in HEK293 cells, in marked contrast to WT-NBS1 (Fig 8A). Furthermore, we show that ablation of another FHA Pro residue (P64) does not impair co-IP with endogenous CYPA under similar conditions, suggesting P112G is unique in this regard. Our recombinant protein interaction work demonstrates that CYPA-Step directly interacts with a HIS-(FHA-BRCT1) peptide and that P112G abolishes this interaction (Fig 8B). Regarding rescue experiments, we’ve found that stable overexpression of NBS1 can be neomorphic, resulting in resistance to certain DNA damaging agents, thereby complicating cell-based rescue analyses. We stress that along with our engineered KO and R55A (isomerase-dead) lines we have employed the well-known CYPAi Cyclosporin A (CsA) to reproduce several of the DNA-R related phenotypes (e.g., Fig 1, Fig 3, Fig 6, Fig 10, Fig 11). To further examine impacts upon resection specifically, a logical approach would be to engineer P112G into a full-length recombinant (baculoviral produced) human MRN complex for in vitro kinetic assessment using various labelled DNA substrates. But we think that this specialist and not insignificant undertaking is outside the scope of our report of the extensive cellular consequences of CYPA loss and dysfunction and it’s potential (pre)clinical significance with regards CYPAi repurposing.

Query:

What are the protein levels of MRN, RAD51 etc. in CYPAKO cells? It will be important control to delineate the effects of CYPA on global transcription and translation vs specific and direct effect on end-resection. Can overexpression of NBS1 rescue the observed resection and focus phenotypes?

RESPONSE:

Basal levels of RAD51 foci/cell are comparable between Scrm and both CYPA-KO and R55A cells (Fig 6D). We also find comparable levels of MRN components between these lines (Suppl Fig 7A). Importantly, we observe the pRPA/resection defect following an acute (up to 3hrs) treatment with CsA; conditions unlikely to grossly impair translation to an extent that would result in reduced expression of the relevant DNA-R proteins. Furthermore, microarray based transcriptomic analyses of these isogenic lines did not show evidence of a global impact upon transcription following CYPA-KO or R55A, nor was there evidence of reduced expression of any genome stability/DNA-R genes. We did not include this negative data so as to maintain the focus on the functional link with DNA repair.

Reviewer #3: This critically negative review is myopic, unbalanced, self-contradictory and frustratingly mis-represents some of our key findings. The dismissive tone of the text unnecessarily and unprofessionally crosses into the pejorative (“Either evidence is lacking or experiments were not performed in a convincing way”). The stark contrast between this review and the summations of Reviewer #1 and Reviewer #2 serve to highlight this hyper-negative approach.

It is very frustrating that this reviewer describes our findings as “…an interesting story…”, that “…the identification of NBS1 as a novel substrate of CYPA is significant” , that the “..manuscript may provide new insight…”, and that “…the role of CYPA in DNA repair is fairly well described using its inhibitor or KO cells”, and yet then concludes by stating “… the current manuscript suffers lack of evidence to support the main conclusion”. This is self-contradictory and unbalanced. Again, the contrast with Reviewer #1 and Reviewer #2 in this regard is stark.

Major critical theme no. 1.

Expression of CYPA-R55A: “…vastly different…”

RESPONSE.

This reviewer dismisses the entirety of the R55A model cell line work based upon the apparent “…vastly different…” expression levels of the reconstituted lines. This is an overstatement of the situation and notably not an issue for either Reviewer #1 or Reviewer #2. Nonetheless, we have replaced the original CYPA blot in Fig 1C with a clearer and more representative depiction of expression levels between the engineered lines and control. Importantly, the pRPA/resection work, siRAD52 and siXRCC3 dependency work were all corroborated/reproduced using the CYPA PPI inhibitor Cyclopsorine A (CsA). The plurality of our complementary approaches showing the influence of CYPA upon DNA-R is minimised and/or ignored by this Reviewer. Although not shown in this study, we find that the R55A cells are selectively sensitive to DNA cross-linker melphalan, in contrast to the CYPA-KO cells. Although we don’t yet understand the basis of this observation, this clearly indicates that R55A expression is a valid model in our hands and is not a like-for-like mimic of CYPA-KO simply because of reduced expression. We appreciate the reviewer could not know this.

Major critical theme no. 2.

CYPA-NBS1 work: “Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment.”

RESPONSE:

We do not claim that NBS1 is ”… the major substrate of CYPA.” . We do not claim that all the DNA-R deficits we have identified are specifically a consequence of impaired NBS1 function. These are misrepresentations of our findings and how we’ve presented and discussed them. This Reviewer ignores our comprehensive CYPA-BioID, and specifically our discussion pertaining to the DNA-R and Replication factors found therein (section entitled ‘CYPA Interacting protein partners’ and Fig 5A). We explicitly discuss the fact that “A recurring theme amongst these CYPA interactors is that all are involved in end-resection” whilst also demonstrating CYPA co-IP with 53BP1, CHAMP1 and ILF2-3 (Fig 5C-E). In the ‘Discussion’ section we describe a “homesostatic role for CYPA in genome stability”, including possible contributions to controlling LLPS of well-known DNA-R factors and the fact that several mitotic, kinetochore, centrosomal and spindle proteins are found in the CYPA-BioID.

Major critical theme no. 3.

A major repeated criticism levelled by this reviewer as a basis for dismissing the entirety our findings is that we have failed to demonstrate that the catalytic activity of CYPA is required for DSB repair.

• Their conclusion should be supported by additional key experiments to prove that the catalytic activity of CYPA is indeed required for DSB repair…

• Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment.

• One major weakness of this study is that it focuses on characterizing the interaction between CYPA and NBS1, then jumps into a conclusion that the catalytic activity of CYPA is required for DSB repair based on its direct interaction with NBS1

RESPONSE:

As this criticism is repeated, the impression created, and no doubt intended, is that the manuscript is irreparably flawed (“…major weakness…”). This is an over-simplification and a misdirection. It’s notable that this critique isn’t raised in such a manner by either Reviewer #1 or Reviewer #2. This is likely because any modest inferences we made concerning the possible role of CYPA catalytic isomerase activity were based on a combination of differing but complementary approaches. Firstly, we routinely used the p.R55A engineered CYPA variant, although this Reviewer regards our use of this as invalid. This longstanding peptidyl prolyl isomerase (PPI)-dead mutant model has frequently been employed to invoke the catalytic function of CYPA. The mutant was originally proposed and characterized as catalytically-dead using the in vitro chymotrypsin-coupled prolyl isomerase assay using N-succinyl-AAPF-p-nitroanilide as a substrate as far back as 1992 (Zydowsky, L.D., et al., Active site mutants of human cyclophilin A separate peptidyl-prolyl isomerase activity from cyclosporin A binding and calcineurin inhibition. Protein Science, 1992. 1(9): p.1092-1099). In addition, we routinely use Cyclopsorin A (CsA), the longstanding clinically relevant CYPA PPI inhibitor, and we also use a different and more potent CYPA PPI inhibitor, namely NIM811 (N-methyl-4-isoleucine-cyclosporine) for the DR-GFP reporter assays of individual DNA-R pathway function (i.e.’ NHEJ, HRR and SSA).

With regards to our findings concerning CYPA-NBS1 interaction, in the Discussion section we clearly state that mechanistic analyses of prolyl isomerase on the dynamism of NBS1 FHA-BRCT would require specialist approaches outside the scope of this manuscript, as the manuscript is firmly within the realm of cellular biology. This is ignored by this Reviewer. Specifically, we state that “A regulated cis-trans isomerisation of the E111-P112 peptide bond could conceivably dynamically alter the relative positioning of the FHA domain with the tandem BRCTs of NBS1 (Fig 7C-D). This may then impact on these domains’ abilities to dynamically interact with their respective phospho-threonine (for FHA) and phospho-serine (BRCT) containing targets, consequently likely shaping/impacting NBS1 recruitment dynamics and/or plasticity of its interactome [120-122]. Demonstrating this hypothesis would require additional structural analysis using techniques such as 2D-NMR which is outside the scope of this manuscript.”

Minor comments: 1.

Fig. 1E; is the survival between KO and R55A statistically significant? If so, do the authors have an explanation? Why is the reconstitution of R55A more toxic than KO alone?

RESPONSE:

Yes, R55A is slightly more sensitive compared to KO for this endpoint. The irony that this observation runs contrary to the Reviewer’s dismissal of the R55A model line is not lost on us (Major critical theme no. 1). As is well-known for PARP1, inhibition is not equivalent to absence. A possible speculative explanation is that the R55A isomerase-dead could have additional dominant impacts compared to the KO situation. Nonetheless, we suspect this Reviewer would object to such speculation in the absence of ever more data.

Minor comments: 2.

In Fig. 3D, the NHEJ activity of CsA- or NIM811-treated cells is significantly downregulated in comparison to control, which raises the possibility of the pleiotropic effect of CYPA inhibition. The authors should discuss this issue.

RESPONSE:

Not necessarily indicative of a pleiotropic effect if one accepts that absence of a protein is not always biologically equivalent to the presence of an inhibited version the same protein. Of note, we do see somewhat reduced NHEJ following siCYPA (Fig 3A), something not mentioned by this Reviewer. Furthermore, we explicitly discuss and show interaction between CYPA and 53BP1, CHAMP1 and ILF2-3 complex, all players in NHEJ and in the intricate balance between NHEJ and resection-mediated recombination directed repair pathways.

Minor comments: 3.

In Figure 8A, since the expressions of Flag-NBS1 WT, P112G, and P64G are very different, the conclusion that the isomerization of CYPA is essential for NBS1 cannot be supported. Given the variation of input levels, it appears that the P64G mutation actually enhances the interaction with endogenous CYPA. Is this reproducible? This co-IP result may need to be quantified from independent sets for statistical analysis.

RESPONSE:

We do not claim that “…isomerization of CYPA is essential for NBS1…”. Fig 8A data is derived from a transient transfection. Whilst there is some variation in expression, we do not make any precise quantitative conclusions from these co-IPs. Nonetheless, FLAG-NBS1-P112G clearly interacts less with endogenous CYPA in this system. Importantly, and ignored by this Reviewer, the associated recombinant protein work shown in Fig 8B clearly confirms that NBS1-P112G is profoundly compromised in its ability to interact with CYPA.

Minor comments: 4.

A defect in DSB repair generally hypersensitizes cells to DNA replication stress, including HU. In this regard, resistance of the CYPA KO (or R55A cells) to HU is interesting, but it may be due to the nonspecific effect of the CYPA loss in multiple DNA damage signaling and repair processes. Alternatively, cell cycle may be affected nonspecifically, rendering cells resistant to replication-associated genotoxic stress. This needs to be addressed further. Analysis of overall cell cycle profile may be required.

RESPONSE:

Resistance to HU is likely multifactorial and cell cycle transition kinetics may be relevant here. That is why we linked the DNA replications phenotypes to this discussion in the section entitled “Impaired CYPA function reveals novel genetic dependencies/vulnerabilities”. A comprehensive analysis of cell cycle profile and phase transits is outside the scope of the current manuscript (see response to Reviewer #2).<br /> Impaired HU-induced pRPA has been linked to HU-resistance via NBS1 previously: Manthey, K.C., et al., NBS1 mediates ATR-dependent RPA hyperphosphorylation following replication-fork stall and collapse. J Cell Sci, 2007. 120(Pt 23): p. 4221-9.

Minor comments: 5.

Text not to mention Abstract is too dense. The manuscript will benefit a lot from extensive editing and rearrangement of figures to make the story more succinct for journal submission.

RESPONSE:

The Reviewer’s view concerning a lack of succinctness is not shared by Reviewer #1 and Reviewer #2. We have endeavored to draft a concise and accessible manuscript, the main body of which comes in at just over 23x sides of A4 (including Materials & Methods). Considering we guide the reader through 12x multipart figures, 5x supplementary tables and 8x supplementary figure, we believe we have achieved succinctness. Nonetheless, we will of course take direction from the appropriate journal editorial team regarding house style and format.

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Referee #3

Evidence, reproducibility and clarity

In this manuscript, O'Driscoll and colleagues identify the role of cyclophilin A (CYPA), a peptidyl-prolyl cis-trans isomerase, in promoting DNA repair. They propose that the catalytic activity of CYPA is required for the action of the MRE11-RAD50-NBS1 (MRN) complex and thus double-strand break (DSB) repair. This study originated from their previous finding that cyclosporin A (CsA) induces replication-associated DNA breakage and genome instability in LIG4 syndrome patient fibroblasts. As CsA is an inhibitor of the CYPA, the authors reasoned that the negative effect of CsA in DNA repair results from its inhibition of CYPA and presumably its essential downstream substates in DNA repair. Using CRISPR/Cas-based U2OS knockout cells, they showed that the catalytic activity of CYPA is necessary for homology-directed repair. Series of BioID-proximity interactome analysis, biochemical studies (e.g., co-immunoprecipitation), and AIphaFold-derived structural determination revealed that CYPA directly interacts with the MRN complex, specifically through the Pro112 of NBS1, and its catalytic activity is required for damage-induced NBS1 foci formation, which all together led to the conclusion that the MRN complex is a direct substrate of CYPA and that CYPA controls DNA end resection and DSB repair via isomerization of NBS1.

This is an interesting story as it reveals a new role of prolyl isomerization, which is mediated by CYPA, in promoting DSB repair. The identification of NBS1 as a novel substrate of CYPA is significant, and the manuscript may provide new insight into how prolyl isomerization of NBS1 regulates the function of the MRN complex that is engaged in DNA end resection during DSB repair. However, the authors' major claim that CYPA controls DSB repair via the MRN complex is not substantiated by the data provided at its current form. Either evidence is lacking or experiments were not performed in a convincing way. Their conclusion should be supported by additional key experiments to prove that the catalytic activity of CYPA is indeed required for DSB repair and NBS1 is a major substrate of CYPA, through which CYPA regulates DNA end resection at the stalled DNA replication fork.

Major comments

1. The authors reconstituted the CYPA knockout (KO) cells with WT or a catalytic mutant (R55A) for the structure-function analysis. However, re-expression levels of CYPA are vastly different between WT vs. R55A, R55A being expressed at much lower levels (not near to endogenous CYPA) (Fig. 1C). Consequently, the loss-of-function phenotypes of R55A may be simply explained by its inadequate reconstitution, thus failing to complement KO phenotypes. For instance, the lack of pRPA2 S4/S8 induction in R55A cells may be just due to the insufficient expression of R55A, thus resulting in the same phenotype as KO. Additionally, the R55A cells were compared to parental cells, not to the WT-reconstituted cells for the majority of functional analysis, so it is not clear whether WT is able to complement the KO phenotype in their system (Figs. 1, 2, 6, 9, 10, and 11). Whether the catalytic activity of CYPA is indeed responsible for the phenotypes of DNA repair deficiency is not supported. The authors should compare the phenotypes between WT- vs. R55A-reconstitued cells side-by-side for the key experiments. Ideally, expression of WT and R55A should be similar in KO cells to exclude the possibility that the R55A phenotypes merely result from insufficient mutant expression rather than true loss of catalytic activity.
2. Another major concern is that the evidence to support that NBS1 is the major substrate of CYPA is lacking since all the experiments were performed with the CYPA mutant or CsA treatment. Whether the NBS1 P112G isomerization-defective mutant indeed exhibits a defect in DNA repair similarly to the CYPA mutant is not shown. For instance, one key experiment would be to test whether the P112G mutant fails to form damage-inducible NBS1 foci formation.
3. In Figure 7A, the authors showed that the interaction between CYPA and NBS1 is dependent on the isomerization activity of CYPA. It should be checked whether the CYPA R55A mutant fails to interact with NBS1 in contrast to WT to support the main conclusion that NBS1 is controlled by the isomerization activity of CYPA.
4. OPTIONAL) One major weakness of this study is that it focuses on characterizing the interaction between CYPA and NBS1, then jumps into a conclusion that the catalytic activity of CYPA is required for DSB repair based on its direct interaction with NBS1. How the isomerization of NBS1 affects its localization, stability, and/or function is not addressed. At its current form, the functional link between NBS1 isomerization and stalled fork processing is weak. Elucidating how the catalytic activity of CYPA controls the action of the MRN complex via the isomerization of NBS1 will add significant impact on the manuscript. Otherwise, the story fails to fully support the description of its title.

Minor comments

1. Fig. 1E; is the survival between KO and R55A statistically significant? If so, do the authors have an explanation? Why is the reconstitution of R55A more toxic than KO alone?
2. In Fig. 3D, the NHEJ activity of CsA- or NIM811-treated cells is significantly downregulated in comparison to control, which raises the possibility of the pleiotropic effect of CYPA inhibition. The authors should discuss this issue.
3. In Figure 8A, since the expressions of Flag-NBS1 WT, P112G, and P64G are very different, the conclusion that the isomerization of CYPA is essential for NBS1 cannot be supported. Given the variation of input levels, it appears that the P64G mutation actually enhances the interaction with endogenous CYPA. Is this reproducible? This co-IP result may need to be quantified from independent sets for statistical analysis.
4. A defect in DSB repair generally hypersensitizes cells to DNA replication stress, including HU. In this regard, resistance of the CYPA KO (or R55A cells) to HU is interesting, but it may be due to the nonspecific effect of the CYPA loss in multiple DNA damage signaling and repair processes. Alternatively, cell cycle may be affected nonspecifically, rendering cells resistant to replication-associated genotoxic stress. This needs to be addressed further. Analysis of overall cell cycle profile may be required.
5. Text not to mention Abstract is too dense. The manuscript will benefit a lot from extensive editing and rearrangement of figures to make the story more succinct for journal submission.

Referees cross-commenting

I agree with concerns on the pleiotropic effect of CYPA KO, which exhibit many distinct phenotypes in DNA repair and replication fork stability.

Significance

While establishing a new link between CYPA-dependent prolyl isomerization and DSB repair is significant, the current manuscript suffers lack of evidence to support its main conclusion. Specifically, although the role of CYPA in DNA repair is fairly well described using its inhibitor or KO cells, whether its isomerization activity is indeed essential and whether NBS1 is the major target for its action in DSB repair is not clear. Existence of many other targets cannot be excluded. Whether the role of CYPA is specific to replication-associated DSB repair processes or can be generally applicable to homologous recombination in any DSB repair is not shown. The role of MRN in stalled fork processing and in response to DSBs could be different, but how CYPA would modulate these distinct processes is not addressed. As such, the manuscript is targeting more specialized audience, but if the link between CYPA and the MRN complex can be further elaborated, including how isomerization affects the function of NBS1 (e.g., using the isomerization-defective NBS1 mutant), it could reach out to broader readership.

My field of expertise includes DNA replication stress and replication-associated repair processes including stalled fork processing and recovery. I am familiar with most of the genetic, cellular, and biochemical experiments presented in the manuscript. I do not have significant expertise on the structural analysis of protein-protein interactions.

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Referee #2

Evidence, reproducibility and clarity

The current manuscript by Bedir et al. explores the role of cyclophilin A in DNA repair, particularly homologous recombination. Authors show that the absence of cyclophilin A or loss of PP1 activity affects end-resection via direct interaction with NBS1. Authors have conducted a series of experiments to confirm their findings. While the findings are interesting, further discussion/ experiments mentioned below will perhaps assure readers with respect to pointed direct vs consequence facilitated indirectly through global cellular effects of CYPA.

1. Authors show delayed S-phase transit along with reduced replication speed indicating replication stall. However, authors have not discussed how cyclophilinA might regulate replication (other than hypothesizing regarding altered dynamism of FHA-BRCT). It is conceivable that it could be an indirect effect on cellular metabolism or if authors believe it could be due to direct disruption to core replication machinery or signaling. In this regard, it will be helpful to see if there is shortening of (premature entry) G1 phase and comment on the status of the associated G1/S checkpoint.
2. In connection to this, it will also be interesting to see if the ATR/Chk1 signaling axis is intact in CYPA KO cells with or without additional DNA damage compared to WT.
3. Authors show that the P112 residue of NBS1 is important for the binding of cyclophilinA.
4. What is the status of interaction among components of the MRN complex in CYPAKO cells and P112G NBS1? Further, what are the authors' thoughts on rescue experiments and whether P112G containing NBS1 to perform resection function.
5. What are the protein levels of MRN, RAD51 etc. in CYPAKO cells? It will be important control to delineate the effects of CYPA on global transcription and translation vs specific and direct effect on end-resection. Can overexpression of NBS1 rescue the observed resection and focus phenotypes?

Significance

Current study highlights the role of cyclophilin A or in large peptidyl-prolyl cis- trans isomerases activity in DNA repair. Although this is not the first study showing the relevance of cyclophilin A in DNA repair, they do highlight its role in homologous recombination and DNA repair. Authors have quite conclusively explored the interaction between NBS1 and cyclophilinA as well as the putative proline residue important for this interaction.

One of the drawbacks of the study is the pleotrophic effects of CyclophilinA. This needs to be at least discussed. Authors themselves observe induction of DSBs, replication stall, reduced NHEJ, SSA as well as HR efficiencies. Taken together, the effects of CyclophilinA even on resection could be a combination of both direct and indirect effects.

This manuscript will have broad interest from groups working on genomic stability, immunology as well as cancer therapy. I have expertise in NHEJ, mammalian replication and replication-stress response.

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Referee #1

Evidence, reproducibility and clarity

In this manuscript, the authors reveal a previously unexplored role of CYPA in DNA repair, particularly in the context of cells sensitive to the CsA. The authors' multi-faceted approach involved using CRISPR/Cas9-engineering, siRNA, BioID, co-immunoprecipitation, and specific DNA repair investigations. They suggest that CYPA, through its PPI activity, plays an active role in DNA repair, specifically in DNA end resection. They also demonstrate that inhibition or loss of CYPA results in impaired HRR following DNA replication fork stalling. Furthermore, the authors associate the loss and inhibition of CYPA with certain genetic vulnerabilities, suggesting potential therapeutic applications by exploiting CYPA PPI inhibition to selectively target cancer cells with characteristic genomic instability.

The manuscript presents clear and comprehensive data, demonstrating the profound impact of CYPA on DNA repair. It would be suitable for publication after addressing the following points:

1. It's surprising to find that the loss of CYPA abolished HU-induced NBS1 foci, as the MRE11 interactive domain of NBS1 should remain intact in CYPA deficient conditions and the N-terminus of NBS1 is dispensable for ATM activation (Kim et al., 2017; Stracker and Petrini, 2011). A more detailed mechanistic explanation of this phenotype would be appreciated. The authors should check the subcellular localization of NBS1 and the stability of MRN in wildtype and CYPA KO cells. Additionally, including the kinetics of NBS1 foci formation using multiple timepoints in wildtype and CYPA KO cells after damage will further support the observation.
2. The authors showed that the interaction between CYPA and MRN didn't change after HU treatment. The authors should also include co-localization analysis of CYPA and NBS1 after HU.
3. The paper demonstrated that BRCA2 knockdown cells were sensitive to CsA. The authors should also examine CsA sensitivity in BRCA2 deficient cancer cells. In addition, the authors could elaborate more on their criteria for selecting cancers for CYPA inhibition, whether it is based on high genomic instability or an addiction to HRR for survival.

Significance

The significance of this study is twofold: it adds a new layer to our understanding of DNA repair mechanisms and, importantly, it could point the way to novel therapeutic strategies for cancer. It will spark interest from molecular biologists to clinicians and pharmaceutical researchers.

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Reply to the reviewers

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

Redhardt and colleagues describe a structure of the voltage and Ca-activated Slo1 channel in complex with an auxiliary subunit, γ1. In complex with γ1, Slo1 adopts an open state that closely resembles previous open state structures. Of γ1, only the single membrane-spanning helix, which binds to the periphery of the Slo1 VSD, is resolved. There, it establishes several interactions with Slo1 that authors propose may favor adoption of the open state, potentially explaining how γ1 can shift I-V profile of Slo1 to be activated at more negative membrane potentials. The interactions described fit well with existing mutagenesis analyses.

While this report provides a first glimpse of how γ1 can bind to Slo1, its impact will be minimal. It describes a single structural snapshot and there are no functional analyses presented. Additional analyses would be helpful in understanding of how γ1 can regulate Slo1 channels.

We thank the reviewer for their honest judgment. We agree that validating the structure by biochemical and/or functional data would have significantly strengthened the manuscript. However, we are convinced that our structural data alone already provides significant novel understanding of the assembly of the Slo1-γ1 complex and regulation of Slo1 by γ1. Thus, we feel that publication of this manuscript is justified by the high importance of Slo channels and our data will have an impact in the field.

__Major comments: __ 1. The authors propose several models for how γ1 regulates Slo1, yet none of them are experimentally evaluated. For example, on page 8, it is written that "we propose that the combination of three different principles, namely shape complementarity, covalent anchoring and lowering the resting state potential by a positively charged intracellular stretch, act in concert to stabilize an active VSD conformation in the Slo1-γ1 complex." This is a testable hypothesis and one that should be experimentally evaluated to better understand regulation by γ1.

We agree with the reviewer that experimental validation of this hypothesis would have been an asset. Nevertheless, we think that our structural data in context of previous functional data e.g. from Li et al. 2015,2016) and also in comparison with the other two manuscripts on the same topic which have been published while this manuscript was under review, allows us to draw conclusions about the mechanism of γ1-mediated activation of Slo1. We have now, however, toned down some of the earlier statements and changed parts of our interpretations in light of the novel findings by Yamanouchi et al. and Kallure et al.

The authors analysis of the extracellular domain of γ1 is incomplete. The only presented structure was performed with C4 symmetry imposed, in which extracellular domains were largely lost. The authors propose that these domains are dynamic and that their dynamism would enable simultaneous binding of both γ and b subunits, as occurs in cells. A more thorough analysis of the dynamics and well as potential asymmetric conformations should be performed to better understand how these domains interact with Slo1.

We completely agree with the reviewer that a thorough analysis of the extracellular domain is important and thank the reviewer for their valuable suggestions. We had attempted such analysis already from the beginning, but were not successful. More specifically, we have attempted reconstructions with lower symmetry (C2 and C1) from the beginning or by symmetry relaxation after initial C4 reconstruction. Also, we tested different masking and signal subtraction strategies in combination with different global and local refinements, as well as symmetry expansion and 3D classification. Unfortunately, none of these strategies led to a better resolved LRR module.

We now think that in comparison with Kallure et al. and Yamanouchi et al., the ice in our sample was thinner, which allowed us to reach higher resolution in the core particle (Slo1 and γ1 TM helix), but at the cost of the γ1 LRRs being denatured or at least distorted by the air-water interface.

The refinement statistics suggest that the model was incompletely refined. This reviewer was not provided with the map or models, but the validation report lists a clashscore of 9 and 5.7% of the rotamers as being outliers, both of which are high for the reported resolution of the structure. It is also strange that the Q-score varied between different γ1 protomers. Why are the four protomers not identical when the map is 4-fold symmetric? The authors should carefully inspect their model to insure that it is as correct as possible.

We thank the reviewer for pointing this out, and while the values for clashscores and rotamers were not outside the range of values typically found in many other cryo-EM structures, we agree that there was still some room for improvement. We have worked on this and could lower the values to a clashscore of 7.0 and 1.8 % rotamer outliers.

The difference in Q-score is also something not too uncommon since, while the map is indeed C4-symmetric, during model refinement the NCS restraints are not completely preventing small deviations between the protomers. We have now also successfully attempted to minimize these differences further.

Reviewer #1 (Significance (Required)):

The impact of this report is limited. Functional analyses will be necessary to uncover precisely how gamma subunits regulate Slo1 channels.

We thank the reviewer for this honest statement, but respectfully disagree. While additional functional analyses would have certainly boosted the impact, we are certain that our structural data and their interpretation will be very valuable for the field, because they provide (as stated by Reviewer 3) new insights into the regulation of Slo channel activity by the γ subunits and suggest (as stated by reviewer 2) a novel mechanism of activation of voltage-gated ion channels..

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

Summary This study presents a high resolution cryo-EM study of a voltage-gated Ca++-dependent K+ channel in the presence of a gamma1 subunit. Analysis of the structure and sequence alignments suggest a novel mechanism of activation of voltage-gated ion channels.

__Major comments __ The major issue in this paper is that it is only a structural biology paper. There is no structure-function relationship study, no functional studies of mutants that could validate -or not- the inferred underlying mechanism. Even though the authors have identified good candidates for mutations (e.g. p. 6) they have not attempted to validate their importance experimentally. As a result, reading their discussion is somewhat frustrating and full of assumptions, as indicated by sentences (p.7) like

"a possible mechanism... might be... which would make... more likely".

"... which might act ... seems important... might indicate... might lower... likely most pronounced... could be responsible..."

"... might play an important role... does not allow a certain conclusion..."

We completely agree with the reviewer that the paper would have been much stronger if we would have been able to perform biochemical or functional assays testing mutations in the binding interface. However, this would have unfortunately been beyond the scope of the project. We are nevertheless confident that our structural data will be of value for the field, also in context of the two structure-function papers that have been published since which confirm and validate our data and provide the link to function.

__Minor comments which could be confidently addressed __ The Introduction contains no description of the state-of-the-art in the field concerning the available structures in the same system or similar ones. Hence, it is difficult to judge for people outside the field if the novelty. is incremental or significant.

We have adjusted the introduction to explicitly mention previously published structural data on the Slo channels.

References 10 and 42 (eLife) lacj some details.

We have adjusted said references accordingly.

__Reviewer #2 (Significance (Required)): ______

---

Significance general assessment As it turns out, at least two papers in exactly the same field just appeared: -one in Molecular Cell by a Japanese group, which is much more developed and contains functional tests and structure-function relationships, in addition to beautiful structures (available on-line early December) https://www.sciencedirect.com/science/article/pii/S1097276523009218

-one in biorxiv, deposited yesterday https://www.biorxiv.org/content/biorxiv/early/2023/12/20/2023.12.20.572542.full.pdf

Advances wrt known results See above. As a result of these new papers in Mol Cell and biorxiv, I think the authors should reconsider submitting their article elsewhere, perhaps for a more specialized audience.

We agree with the reviewer that in light of the other two publications which both were published a while after we deposited our preprint on biorxiv and while the manuscript was under review, the uniqueness of our data is somewhat lowered. However, since our data is overall in large agreement with these two other publications, but we report a structure at significantly higher resolution and from a different species (indeed the first Slo1 structure from rabbit, a model organism of BK channel characterization in the last decades), we are confident that our data are still very valuable for the field and qualify for publication in one of the affiliate journals of Review Commons. After all, the fact that three papers reporting very similar data were published within a few weeks (plus another preprint reporting structures of a Slo channel, but unrelated to γ subunits) illustrates the importance for understanding the regulation of this essential ion channel and the impact of all structural data enhancing this understanding, and independent confirmation by three different labs is something very valuable to the community.

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

"This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. "This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation. The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit. However, there are some important questions below that should be addressed."

1. In Figure 1D panel, the calcium ions appear to be indistinct, likely due to the figure's low resolution. The authors are recommended to enhance the figure quality and consider a better positioning to effectively illustrate the ions.

We have adjusted the coloring of calcium ions Fig. 1D to increase their visibility.

It would be beneficial for the readers if the authors provided detailed methodology explaining how they arrived at the 7% and 11% coexpression, aiding in the complex formation. Additionally, it would be informative to know the observed shift in the size exclusion chromatography (SEC) profile of Slo1-Y1 compared to apo Slo1.

We have arrived at these concentrations of the respective viruses by empirically testing ranges between 3 % and 15 %. We have now added a sentence to the manuscript to explain this.

Is there any rationale behind initially purifying using strep affinity followed by His affinity?

The idea behind using a dual-affinity protocol is to ensure that all purified complexes contain at least one copy of Slo1 and one copy of γ1. Using the Strep tag first allows to remove most contaminants already in the first step, due to its higher specificity compared to the His tag. We have added a sentence to the methods section to explain this.

Regarding the Slo1 tetramer with gamma subunit binding, are there other classes where one, two, or three gamma subunits are bound to Slo1? Or is there only one class where all protomers of Slo1 are occupied by the gamma subunit? How do these classes appear when refined in C1 symmetry? Are there classes displaying C1 or C2 symmetry, or is the four-fold symmetry preserved across all refined classes?"

We exclusively observe complexes with four γ1 subunits. This is also in agreement with the other two recent publications reporting Slo1-γ1 complex structures, but could in principle be an artifact of artificial overexpression. Also when we refine the particles in C1, we retain C4 symmetry and do not observe any classes with C2 or C1 symmetry.

The authors utilized nearly 1.9 million particles to reconstruct the final class, resulting in a high resolution. Is such a large number of particles truly necessary to achieve high resolution in this context?

The large number of particles is not strictly necessary, i.e. we could obtain similar quality by using fewer particles. In the end, we have now further classified down to ~827k particles, which very slightly improved the resolution and quality of the map.

Authros mentioned that F273 of γ1 forms pi-stacking interactions, it remains unclear with which components of the channel these interactions occur.

F273 forms (slightly distorted) T stacking interactions with F164 in S2 and F187 in S3. We now changed the sentence in the manuscript to mention the residues that line the hydrophobic pocket to make it more clear which elements contribute to the interaction with F273.

The authors propose that the disulfide bond between the γ subunit and Slo1 could play a crucial role in their interaction. Was there any observation of a covalent linkage in SDS page analysis? Furthermore, how would this interaction be affected if either cysteine C253 of gamma1 or C141 on the channel were mutated or neutralized?"

We have run all our SDS-PAGE experiments under reducing conditions, thus destroying any disulfide bridges that might have been present in the complex. We have now, however obtained a slightly better defined reconstruction (as pointed out in our answer to point 5 raised by this reviewer) where we do not see as clear continuous density anymore between the two cysteine side chains. Thus, we have removed the cystine bond from the final model and have adjusted text and figures accordingly. We still think that it might be more than coincidence that those two side chains come into such close proximity, though, and still discuss the possibility of a cystine bridge in the manuscript.

Author's state that "The presence of several immobile positive charges on the intracellular side in close proximity to the VSD as in the case of the Slo1-γ1 complex is likely to locally lower the resting state potential and repulse the gating charges, thereby reducing the energy to overcome for the VSD to transition to the active conformation." Authors need to be little more elaborative here as it is not clear what authors mean repulse of gating charges.

We have expanded our description of the proposed repulsive effect of the positive charges in the manuscript and in addition also discuss the additional role of the charges in stabilizing the Ca2+-bound conformation of the gating ring as proposed by Yamanouchi et al.

Probably beyond this study but I was wondering whether it is possible that Beta and gamma subunit can together assemble as heteromers to form a cage-like structure with contribution from both.

We agree with the reviewer that this is an interesting question which we have also thought about and one which should be tested, but as the reviewer already mentioned, this would go beyond the present study and should be subject to an independent follow-up investigation.

Are there any specific lipids observed within the structure that could potentially contribute to the functional conformation or stability of the complex?"

Given the high resolution of our structure, we observe a number of ordered lipid and detergent molecules, most of which were located at similar positions as in previous structures of Slo channels. Besides those molecules clustering in the deep cleft between neighboring voltage-sensor domains, we also observe lipid densities close to the binding site of γ1 on the distal side of the VSD. However, as their relevance for γ1 binding is unclear, we don’t discuss them in the manuscript. In general, of course, we agree with the reviewer that lipids can have a large impact on the function of membrane proteins.

It would be interesting to see if the kink in the gamma subunit is entirely neutralized through mutations of proline and glycine, how these alteration might impact the assembly of the mutated gamma subunit with the channel. The authors should provide insights into whether this mutated form of the gamma subunit assembles effectively with the channel and whether there are functional consequences associated with this alteration.

As shown by Kallure et al., substituting P270 in the kink by serine (the native residue at this position in γ3) strongly diminished the ability of γ1 to associate with Slo1 in vitro, demonstrating the importance of the kink and providing a rationale for the observed differences in the potency of the TM helices of γ1 and γ3 in Slo1 activation.

It would be generally beneficial for the authors to provide functional insights that can support the physiological relevance of this kink in the gamma subunit. Understanding the potential consequences of this mutation and its implications for the assembly and function of the channel complex will offer valuable insights into the physiological role of the kink.

We absolutely agree with the reviewer that functional insights on the relevance of the kink would be very valuable, but we think that the available experimental data together with the natural sequence differences in γ1-γ4 and the correlation with their physiological activity are very clear indications that the kink is relevant. However, future follow-up studies that prove this beyond any doubt would be valuable.

Is it known that binding of beta or gamma subunit can impact the subsequent binding of beta and gamma to channels. If it is, it need to be discussed briefly in the discussion part.

This is, to the best of our knowledge, not known. The only existing data that suggests co-presence of beta and gamma subunits on Slo1, reported in Gonzalez-Perez et al., 2015, stems from electrophysiological experiments and does not reveal anything about hierarchy and temporal order of binding events.

Reviewer #3 (Significance (Required)):

The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit.

We thank the reviewer for this positive assessment of the data and agree that our structural data, also when regarded together with the complementary manuscripts by Kallure et al. and Yamanouchi et al., provides significant new insight into the assembly and activity of γ subunits.

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

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Referee #3

Evidence, reproducibility and clarity

"This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation.

"This manuscript by Redhardt et al. presents the cryo-EM structure of the Slo K+ channel from rabbits in conjunction with its auxiliary subunit, γ1, and proposes a mechanistic model for regulating channel activation.

The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit. However, there are some important questions below that should be addressed."

1. In Figure 1D panel, the calcium ions appear to be indistinct, likely due to the figure's low resolution. The authors are recommended to enhance the figure quality and consider a better positioning to effectively illustrate the ions.
2. It would be beneficial for the readers if the authors provided detailed methodology explaining how they arrived at the 7% and 11% coexpression, aiding in the complex formation. Additionally, it would be informative to know the observed shift in the size exclusion chromatography (SEC) profile of Slo1-Y1 compared to apo Slo1.
3. Is there any rationale behind initially purifying using strep affinity followed by His affinity?
4. Regarding the Slo1 tetramer with gamma subunit binding, are there other classes where one, two, or three gamma subunits are bound to Slo1? Or is there only one class where all protomers of Slo1 are occupied by the gamma subunit? How do these classes appear when refined in C1 symmetry? Are there classes displaying C1 or C2 symmetry, or is the four-fold symmetry preserved across all refined classes?"
5. The authors utilized nearly 1.9 million particles to reconstruct the final class, resulting in a high resolution. Is such a large number of particles truly necessary to achieve high resolution in this context?
6. Authros mentioned that F273 of Y1 forms pi-stacking interactions, it remains unclear with which components of the channel these interactions occur.
7. The authors propose that the disulfide bond between the Y subunit and Slo1 could play a crucial role in their interaction. Was there any observation of a covalent linkage in SDS page analysis? Furthermore, how would this interaction be affected if either cysteine C253 of gamma1 or C141 on the channel were mutated or neutralized?"
8. Author's state that "The presence of several immobile positive charges on the intracellular side in close proximity to the VSD as in the case of the Slo1-γ1 complex is likely to locally lower the resting state potential and repulse the gating charges, thereby reducing the energy to overcome for the VSD to transition to the active conformation." Authors need to be little more elaborative here as it is not clear what authors mean repulse of gating charges.
9. Probably beyond this study but I was wondering whether it is possible that Beta and gamma subunit can together assemble as heteromers to form a cage-like structure with contribution from both.
10. Are there any specific lipids observed within the structure that could potentially contribute to the functional conformation or stability of the complex?"
11. It would be interesting to see if the kink in the gamma subunit is entirely neutralized through mutations of proline and glycine, how these alteration might impact the assembly of the mutated gamma subunit with the channel. The authors should provide insights into whether this mutated form of the gamma subunit assembles effectively with the channel and whether there are functional consequences associated with this alteration.
12. It would be generally beneficial for the authors to provide functional insights that can support the physiological relevance of this kink in the gamma subunit. Understanding the potential consequences of this mutation and its implications for the assembly and function of the channel complex will offer valuable insights into the physiological role of the kink.
13. Is it known that binding of beta or gamma subunit can impact the subsequent binding of beta and gamma to channels. If it is, it need to be discussed briefly in the discussion part.

Significance

The Slo channel, also known as the large-conductance calcium-activated potassium channel or BK channel, is an ion channel type found in various cell membranes, including neurons, muscle cells, and other tissue types. Its key features encompass Ca2+ activation, voltage dependence, and regulation by auxiliary subunits. Different auxiliary subunits have been shown to modulate channel functions distinctly; notably, the γ1 subunit enables channel activation at lower voltages compared to the wild-type channel. This manuscript offers a structural-functional framework that enhances our comprehension of how Slo channels are regulated by auxiliary subunits, such as gamma and beta subunits. While the structure of Slo channels in complex with the beta subunit is understood, the binding and interaction of the gamma subunit with the channels remain elusive due to the absence of corresponding structures. Along these lines, the presented structure here indeed provides new insights into the regulation of Slo channel activity by the gamma subunit.

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 presents a high resolution cryo-EM study of a voltage-gated Ca++-dependent K+ channel in the presence of a gamma1 subunit.

Analysis of the structure and sequence alignments suggest a novel mechanism of activation of voltage-gated ion channels.

Major comments

The major issue in this paper is that it is only a structural biology paper. There is no structure-function relationship study, no functional studies of mutants that could validate -or not- the inferred underlying mechanism. Even though the authors have identified good candidates for mutations (e.g. p. 6) they have not attempted to validate their importance experimentally. As a result, reading their discussion is somewhat frustrating and full of assumptions, as indicated by sentences (p.7) like "a possible mechanism... might be... which would make... more likely". "... which might act ... seems important... might indicate... might lower... likely most pronounced... could be responsible..." "... might play an important role... does not allow a certain conclusion..."

Minor comments which could be confidently addressed

The Introduction contains no description of the state-of-the-art in the field concerning the available structures in the same system or similar ones. Hence, it is difficult to judge for people outside the field if the novelty is incremental or significant.

References 10 and 42 (eLife) lack some details.

Significance

Significance general assessment

As it turns out, at least two papers in exactly the same field just appeared:

• one in Molecular Cell by a Japanese group, which is much more developed and contains functional tests and structure-function relationships, in addition to beautiful structures (available on-line early December) https://www.sciencedirect.com/science/article/pii/S1097276523009218
• one in biorxiv, deposited yesterday https://www.biorxiv.org/content/biorxiv/early/2023/12/20/2023.12.20.572542.full.pdf

Advances

wrt known results

See above.

As a result of these new papers in Mol Cell and biorxiv, I think the authors should reconsider submitting their article elsewhere, perhaps for a more specialized audience.

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

Redhardt and colleagues describe a structure of the voltage and Ca-activated Slo1 channel in complex with an auxiliary subunit, 1. In complex with 1, Slo1 adopts an open state that closely resembles previous open state structures. Of 1, only the single membrane-spanning helix, which binds to the periphery of the Slo1 VSD, is resolved. There, it establishes several interactions with Slo1 that authors propose may favor adoption of the open state, potentially explaining how 1 can shift I-V profile of Slo1 to be activated at more negative membrane potentials. The interactions described fit well with existing mutagenesis analyses. While this report provides a first glimpse of how 1 can bind to Slo1, its impact will be minimal. It describes a single structural snapshot and there are no functional analyses presented. Additional analyses would be helpful in understanding of how 1 can regulate Slo1 channels.

Major comments:

1. The authors propose several models for how 1 regulates Slo1, yet none of them are experimentally evaluated. For example, on page 8, it is written that "we propose that the combination of three different principles, namely shape complementarity, covalent anchoring and lowering the resting state potential by a positively charged intracellular stretch, act in concert to stabilize an active VSD conformation in the Slo1-γ1 complex." This is a testable hypothesis and one that should be experimentally evaluated to better understand regulation by 1.
2. The authors analysis of the extracellular domain of 1 is incomplete. The only presented structure was performed with C4 symmetry imposed, in which extracellular domains were largely lost. The authors propose that these domains are dynamic and that their dynamism would enable simultaneous binding of both  and  subunits, as occurs in cells. A more thorough analysis of the dynamics and well as potential asymmetric conformations should be performed to better understand how these domains interact with Slo1.
3. The refinement statistics suggest that the model was incompletely refined. This reviewer was not provided with the map or models, but the validation report lists a clashscore of 9 and 5.7% of the rotamers as being outliers, both of which are high for the reported resolution of the structure. It is also strange that the Q-score varied between different 1 protomers. Why are the four protomers not identical when the map is 4-fold symmetric? The authors should carefully inspect their model to insure that it is as correct as possible.

Significance

The impact of this report is limited. Functional analyses will be necessary to uncover precisely how gamma subunits regulate Slo1 channels.

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

Learn more at Review Commons

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Reply to the reviewers

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

The coupling between cell polarity and cell cycle progression is an important aspect of symmetric and asymmetric cell division. Although there are several examples of cell cycle kinases phosphorylating polarity proteins, it has been difficult to assess the importance of these on cell division due to the strong and pleiotropic effects of manipulating these kinases. Here, the authors generate an analogue-sensitive allele of cdk1 in flies to tackle this question in neuroblasts (NBs) and sensory organ precursors (SOPs), two well characterised examples of asymmetric cell divisions. They show that partial Cdk1 inhibition (which still allows cell cycle progression) does not block Bazooka (PARD3 in mammals) polarization in NBs, but prevents coalescence of the Baz crescent, which has previously been shown to be an actomyosin-based process. They further identify a Cdk1 consensus site on Baz (S180) for which they generate a phospho-specific antibody, allowing them to show that this site is specifically phosphorylated in dividing NBs and SOPs. Although mutations at this site do not recapitulate the effect of Cdk1 on Baz coalescence, they do delay Miranda polarization in NBs and affect lateral inhibition and asymmetric cell division of SOPs. Finally, the authors show that human PARD3 can also be phosphorylated by Cyclin B/Cdk1 in vitro.

Major comments:

• Figure 2A: it would be good to show that polarization of Baz::GFP in consecutive divisions is maintained in cdk1as2 animals in the absence of 1-NA-PP1. We now show in Fig S2B a panel with two consecutive divisions of a cdk1as2 neuroblast in the absence of 1-NAP-PP1, followed by a third division in the presence of 1-NAP-PP1. The neuroblast shows high levels of Baz polarization in the two first divisions.

• The interpretation of the observed SOP phenotypes is complicated by the uneven expression of the pnr-GAL4 driver and the fact that it is expressed in epithelial cells rather than just SOPs. The authors could express their control and mutant Baz constructs under the control of neurP72-GAL4. It is not likely they would be able to deplete endogenous Baz as they have done in NBs, as neurP72-GAL4 is expressed too late to deplete most proteins before SOP division, but they could at least look at localization of the mutants and any possible gain-of-function phenotypes.

Following this suggestion, we have recombined Neur-GAL4 with UAS-delta RNAi to attempt to deplete both endogenous Baz::mScarlet and Delta while expressing our Baz::GFP constructs specifically in SOPs. Baz::mScarlet depletion was surprisingly efficient considering, as the reviewer points out, the late timing of Neur-GAL4 expression. However, the adult flies did not present any sensory organs transformations, perhaps because Delta might not be as efficiently depleted. We can at least rule out dominant-negative effects.

We thank the reviewer for his constructive feedback and as suggested, we now extensively analysed the localisation of the Baz-S180 mutants in SOPs and found significant defects. We describe these observations in a new Figure 6. Briefly, we observed that the Baz phosphomutants have localisation defects during the pIIa cell division but not the pI cell division. We also observed a very surprising mosaicism of expression of our UASz-driven constructs within the SOP lineage that allowed us to make a few interesting observations which should be of interest to SOP specialists. Briefly, mosaic expression of Baz::GFP within the SOP lineage allowed to analyse the relative contributions of pIIa and pIIb/pIIIb to different Baz cortical pools and revealed an unexpected cell non-autonomous mechanism controlling pIIb division orientation. We describe these findings in a new associated supplemental figure.

The authors speculate that Baz phosphorylation during lateral inhibition may be the reason for the observed excess specification of SOPs in the S180 mutants. This could easily be tested by looking at their antibody staining at earlier stages in the notum. Following this suggestion (also coming from Reviewer #2), we have stained nota between around 8h APF. We observed that patches of cells of the early notum display a strong Baz-pS180 phospho-signal. These patches partially overlap with the Delta-positive stripes in which lateral inhibition occurs (as described for example in (Corson et al., 2017), consistent with the possibility that Baz-S180 phosphorylation does somehow regulate lateral inhibition.

These new experiments clearly show that Baz can be phosphorylated on S180 in cells that do not divide asymmetrically. This led us to change the title.

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

Cell polarization in dividing cells, including stem cells, is typically coupled such that polarity can inform the architecture, orientation, and/or asymmetry during cell division. In Drosophila neural stem cells (neuroblasts/SOP), Par polarity is coupled to the cell cycle, but the nature of this coupling remains unclear. In this work, Loyer and colleagues report on impacts of CDK1 inhibition on Bazooka/Par3 localization and basal fate determinant localization. They provide evidence for a novel phosphorylation site that appears unique to asymmetrically dividing cells and may be involved in regulation of asymmetric division. Finally, they show that CDK1 can, at least in principle, phosphorylate human Par3 in vitro.

Overall, the major claims of the abstract appear supported by the experimental work; however, we think the title overstates the overall conclusions that can be drawn from the work.

Major comments:

• The major claim of the paper is the role of specific phosphorylation of S180 in asymmetrically dividing cells in polarization and sensory organ formation, which relies heavily on interpretation of S180A/D phosphomutants. The experiments are carefully performed and quantified, and are consistent with the conclusions drawn. However, we wondered if it possible that the phenotypes are not linked to phosphorylation (the authors acknowledge this in the Discussion)? In other words could the A/D mutants simply be weak Baz mutants? This could this potentially explain the extra-SOP phenotype if Baz function is generally altered, especially given that it is difficult to rationalise a role for SOP-specific phosphorylation in the processes that specify SOP cells in the precursor epithelial cells. The authors speculate that these early precursors may exhibit also phosphorylation, but this isn't examined. Chasing this down seems key to support the core titular claim of the paper. Following this suggestion (also coming from Reviewer #1), we have stained nota around 8h APF. We observed that patches of cells of the early notum display a strong Baz-pS180 phospho-signal. These patches partially overlap with the Delta-positive stripes in which lateral inhibition occurs (as described for example in Corson et al., 2017). This result is presented in Fig. 5H. As would be the case for any phosphomutant, this does not strictly rule out that the S180A and S180D could simply be weak Baz mutants, but it strongly supports the possibility that the lateral inhibition defects observed in these mutants result from defective Baz-S180 phosphorylation.

• Implicit in the core message of the paper is the elucidation of CDK1 regulation of polarity and specifically Baz. However, the connection between CDK1 and S180 (and Baz regulation overall) is relatively tenuous in this work. First, the S180A mutant does not phenocopy CDK1 inhibition with respect to basal determinant phenotypes, though obviously CDK1 may be more pleiotropic. Second, whether the CDK1 inhibition phenotype is linked to any effect on Baz/PAR behaviour is not really explored. Third, they do not test whether S180 phosphorylation is CDK1-dependent. We fully agree with these comments. We cannot think of any way of addressing the first two points, which would require fully inhibiting CDK1 and somehow maintaining neuroblasts in mitosis to examine how it impacts Baz localisation. We tried to arrest neuroblasts in mitosis and block the proteasome as this at least in HeLa cells led to persistence of mitosis when CDK1 was inhibited (Skoufias et al., 2007). However, neuroblasts arrested in mitosis by proteasome inhibition slipped out of mitosis.

However, concerning the third point, we now provide evidence showing that, at least in vitro, Drosophila BazS180 is phosphorylated by CDK1 (see below).

The method for quantifying domain signal only references prior work and should be described in this work. From our search of the cited reference, it appears to be peak signal intensity at a user specified point on the cortex. While this does not undermine the core findings as presented, it may not capture additional features that may be informative (domain size, fluorescence distribution, total signal etc.). For example domain coalescence would imply smaller, brighter domains, but similar total protein amounts, which appears to be the case from images, but isn't quantified per se. We now describe our method for quantifying average signal intensity in the middle of the Baz crescents. We agree that quantifying additional features to check whether they are affected by partial CDK1 inhibition would be interesting. However, doing so requires determining exactly where Baz crescents start and end. As Baz crescent edges in neuroblasts often end in a gradient rather than a sharp edge (Hannaford et al., 2018), we are not sure to be able to confidently do so in every case with the image quality of our dataset: we prioritised limiting photobleaching to accurately quantify the levels of endogenously expressed Baz rather than obtaining very sharp and high contrast images. This is further complicated by the fact that, depending on the depth of neuroblasts within the tissue and the orientation of their division relative to the imaging plane, the signal intensity of Baz crescents is quite variable, preventing a simple thresholding approach to arbitrarily determine the limits of crescents based on signal intensity. In short, accurately determining the size of crescents is very challenging.

The phosphospecific antibody signal is relatively weak, leading to relatively low signal to noise, which could compromise the ability to detect phospho-S180 in non-asymmetrically dividing cells or generally in cells in which Baz is not polarised and thus signal would be diffused around the cell rather than concentrated. Similar caveats could also apply to the lack of signal in interphase cells, where Baz may be less enriched at the cortex and not polarized. We are inclined to believe the authors conclusions, particularly given their examination of multiple cell types and tissues. However, it is a potential caveat as it may be most visible in polarised cells where it is asymmetrically enriched. We thank the reviewer for pointing this out. Given the fact that Baz levels at the neuroepithelial cells adherens junctions are similar, we are confident that Baz-S180 is phosphorylated in dividing neuroblasts but not in non-mitotic epithelial cells, which is at least consistent with our new finding that CDK1 phosphorylates Baz-S180 in vitro. However, we agree that we cannot strictly rule out that Baz-S180 is phosphorylated but below a detection threshold in mitotic neuroepithelial cells as cortical Baz levels decrease in these cells.

We have also gathered new data showing that, in the early notum, Baz-S180 is detected in epithelial cells that are not dividing asymmetrically, definitely ruling out the notion that Baz-S180 is strictly ACD-specific. We have changed the title of the paper accordingly, toned down the mention of apparently ACD-specific Baz-S180 phosphorylation in the abstract and now describe and discuss the fact that the apparent ACD-specificity of Baz-S180 phosphorylation is context-specific.

Examination of in vitro phosphorylation of human Par3D (Figure 6) seems out of place and does not add much. It is human, not Bazooka. They reveal 30 sites, 18 of which in both replicates, but most are not obvious CDK sites and the S180 equivalent site is missing. None of these sites is validated in vivo, at least in this work.

We fully agree with these comments. We initially attempted to purify both full length Baz and human PARD3 but only managed to purify small amounts of PARD3, which is why our analysis was limited to human PARD3. To circumvent these difficulties, we instead purified a smaller N-terminal fragment of Baz and PARD3, which was successful for both proteins and gave us much higher quantities of sample for analysis. Using two different approaches (Western blot with our phospho-specific antibody on Baz and targeted mass spectrometry on Baz and PARD3), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro.

Minor comments: Figure 1: Uses metaphase arrested cells, presumably colcemid, but colcemid is only noted in Figure 2. We now mention Colcemid in the legend of Figure 1. - Figure 2A: Scale bar is truncated. We have corrected this. - Figure 2A: Example images of control neuroblasts could be useful to readers. We now show control neuroblasts in Figure 2A. - Figure 2G' vs H': Because G' has two panels and H' has only one, we often confused the PKC and Mira box plots when comparing to Numb. Perhaps Mira could be in a separate sub panel or be more closely juxtaposed with Numb? The quantification of the Mira signal is now right next to Numb. - Whereas both Numb/Mira were examined in CDK1(as), only Mira is reported for the S180A/D experiments. Is there a Numb phenotype as well?

We actually co-stained Numb and Miranda in the dataset that we analysed in the S180A/D experiments shown in Fig 4E, F. We did not analyse Numb localisation in the first version we submitted because of a penetration issue of the Numb antibody: the Numb signal fades extremely fast as we image deeper in the tissue, causing large difference of signal intensity even within a single cell. This prevents us from performing any meaningful quantitative measurement of the Numb signal like the one we did in Fig. 2H, K, for which we did not encounter this issue. All our further immunostaining experiments with this antibody have had the same problem since then, even after using Triton concentrations up to 4% for permeabilization.

Nonetheless, following the reviewer’s question, we have at least performed a simple qualitative analysis of Numb localisation in this experiment. We observed that Numb localised to the basal pole in most cases in controls and Baz phosphomutants, but localised uniformly at the cortex in half the cases where Miranda showed very low levels of polarisation in metaphase in BazS180D mutants. This Numb localisation defect suggests a loss of function of the PAR complex whereas, intriguingly, the Miranda localisation defect suggests a gain of function of the PAR complex. These new observations are described in Fig. 4G-H’.

• The discussion of the notch / Baz phenotypes (Figure 5) is rather complicated and a bit difficult to follow. We agree with this, we have rewritten this part. This is further simplified by our new observation that Baz-S180 is phosphorylated in the early notum during lateral inhibition.

• Figure 5A: captions should indicate that RFP RNAi is depleting Baz. We have modified the figure accordingly.

• Box plots are used, but not described. i.e. outliers seem to be marked, but criteria unclear. Mean vs median, etc. We now describe boxplots in the legend in the first instance they are used (Fig 2A’), and in the material and methods
• Some grammatical mistakes:
• Title: neuroblast (no 's'),
• Page 1: Cell fate difference(s?) in the resulting daughter cells
• Page 4: (As) CDK1 inhibition with 10 μM 1-NA-PP1 prevents neuroblasts from cycling and causes metaphase- arrested neuroblasts to slip out of mitosis. (Reword)
• Page 6: increased levels of basal fate(no 's') determinants

We have corrected these mistakes.

Reviewer #2 (Significance (Required)):

The links between cell cycle and cell polarity are clearly important and remain poorly understood. Hence, the work addresses key conceptual/mechanistic questions relevant to our fundamental understanding of stem cell biology and regulation of polarity and asymmetric cell division. In our opinion, there are clearly some interesting observations in the manuscript, the experiments are performed carefully, and the data are generally well described. That said, overall, the work seems somewhat premature.

The direct impact of CDK1 on Baz behaviour remains somewhat unclear. The authors do a good job of limiting the concentration of inhibitor to decouple effects of cell cycle progression from CDK1 levels per se, but this does potentially impact the strength of the phenotypes they can detect and hence the observed phenotypes are relatively minor. Note that driving cells out of mitosis with stronger CDK1 inhibition clearly impacts Baz localization, so the 'real' effect of CDK1 inhibition on Baz could be stronger than reported here. It is also unclear whether the phenotypes observed are directly linked to CDK1 regulation of PAR polarity or an indirect effect of cell cycle control of other processes. The authors' suggestion that it could be related to defects in cortical actin organization, which is known to be cell cycle controlled, seems most likely, but neither this or other models are explored further. We agree but are not aware of any experiment that would allow testing full inhibition of CDK1 on membrane-bound Baz in mitotic neuroblasts. As mentioned above in our response to reviewer #1 we tried to arrest neuroblasts in mitosis and block the proteasome as this at least in HeLa cells led to persistence of mitosis when CDK1 was inhibited (Skoufias et al., 2007). However, neuroblasts arrested in mitosis by proteasome or Colcemid or both slipped out of mitosis upon inhibition of CDK1.

We agree it would be interesting to study how CDK1 affects the actomyosin network in neuroblasts but feel that this is somewhat beyond the scope of the manuscript.

Using phosphospecific antibodies, they report on a novel putative CDK1 phosphorylation site, but aside from looking like a consensus CDK1 site, whether this site is CDK1 dependent is not examined. Notably, the corresponding phosphomutants have modest effects and don't obviously account for the CDK1 inhibition phenotype, leaving it somewhat unclear whether it is under cell cycle regulation. We now provide a new figure 7 to address this point. As mentioned already above, using two different approaches (Western blot with our phospho-specific antibody on Baz and targeted mass spectrometry on Baz and PARD3 using), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro. Again, we cannot identify any experiment that would allow us testing whether S180 Baz is a direct target of CDK1 in vivo. The fact that we now report significant defects on Baz localisation in pIIa divisions, strongly suggests functional relevance and CDK1 seems a plausible kinase based on the new in vitro results.

The observation that S180 phosphorylation appears unique to asymmetrically dividing cells is very curious, but this observation is not followed up extensively. Again phenotypes of phosphomutants are quite modest, and while one can propose models to rationalise the phenotypes observed, these models are not fully explored. As mentioned above, we now show that Baz-S180 phoshorylation is not strictly ACD-specific and changed the title accordingly. We also have new data showing that the S180 phosphomutants of Baz have localisation defects in mitotic pIIa divisions (new figure 6). Therefore, this phosphorylation event on Baz can be linked to Baz’s cortical localisation and interestingly shows context dependency.

The findings that human Par3D can be phosphorylated by CDK1 in vitro do not add much particularly as they obtain a very large number of putative sites raising questions of specificity, the sites are not validated, and an S180 equivalent site was not identified. We agree that this has been a weakness which we feel we have addressed. We paste here the answer already provided above when replying to reviewer #1.

We initially attempted to purify both full length Baz and human PARD3 but only managed to purify small amounts of PARD3, which is why our phospho-proteomics analysis was limited to human PARD3. To circumvent these difficulties, we instead purified a smaller N-terminal fragment of Baz and PARD3, which was successful for both proteins and gave us much higher quantities of sample for analysis. Using two different approaches (Western blot with our phospho-specific antibody on Baz and phosphor proteomics on Baz and PARD3 using mass spectrometry), we now show in a new Figure 7 that CDK1 phosphorylates Baz-S180 and PARD3-S187 in vitro.

References

CORSON, F., COUTURIER, L., ROUAULT, H., MAZOUNI, K. & SCHWEISGUTH, F. 2017. Self-organized Notch dynamics generate stereotyped sensory organ patterns in Drosophila. Science, 356.

HANNAFORD, M. R., RAMAT, A., LOYER, N. & JANUSCHKE, J. 2018. aPKC-mediated displacement and actomyosin-mediated retention polarize Miranda inDrosophilaneuroblasts. eLife, 7__,__ 166.

SKOUFIAS, D. A., INDORATO, R. L., LACROIX, F., PANOPOULOS, A. & MARGOLIS, R. L. 2007. Mitosis persists in the absence of Cdk1 activity when proteolysis or protein phosphatase activity is suppressed. J Cell Biol, 179__,__ 671-85.

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Referee #2

Evidence, reproducibility and clarity

Cell polarization in dividing cells, including stem cells, is typically coupled such that polarity can inform the architecture, orientation, and/or asymmetry during cell division. In Drosophila neural stem cells (neuroblasts/SOP), Par polarity is coupled to the cell cycle, but the nature of this coupling remains unclear. In this work, Loyer and colleagues report on impacts of CDK1 inhibition on Bazooka/Par3 localization and basal fate determinant localization. They provide evidence for a novel phosphorylation site that appears unique to asymmetrically dividing cells and may be involved in regulation of asymmetric division. Finally, they show that CDK1 can, at least in principle, phosphorylate human Par3 in vitro.

Overall, the major claims of the abstract appear supported by the experimental work; however, we think the title overstates the overall conclusions that can be drawn from the work.

Major comments:

1. The major claim of the paper is the role of specific phosphorylation of S180 in asymmetrically dividing cells in polarization and sensory organ formation, which relies heavily on interpretation of S180A/D phosphomutants. The experiments are carefully performed and quantified, and are consistent with the conclusions drawn. However, we wondered if it possible that the phenotypes are not linked to phosphorylation (the authors acknowledge this in the Discussion)? In other words could the A/D mutants simply be weak Baz mutants? This could this potentially explain the extra-SOP phenotype if Baz function is generally altered, especially given that it is difficult to rationalise a role for SOP-specific phosphorylation in the processes that specify SOP cells in the precursor epithelial cells. The authors speculate that these early precursors may exhibit also phosphorylation, but this isn't examined. Chasing this down seems key to support the core titular claim of the paper.
2. Implicit in the core message of the paper is the elucidation of CDK1 regulation of polarity and specifically Baz. However, the connection between CDK1 and S180 (and Baz regulation overall) is relatively tenuous in this work. First, the S180A mutant does not phenocopy CDK1 inhibition with respect to basal determinant phenotypes, though obviously CDK1 may be more pleiotropic. Second, whether the CDK1 inhibition phenotype is linked to any effect on Baz/PAR behaviour is not really explored. Third, they do not test whether S180 phosphorylation is CDK1-dependent.
3. The method for quantifying domain signal only references prior work and should be described in this work. From our search of the cited reference, it appears to be peak signal intensity at a user specified point on the cortex. While this does not undermine the core findings as presented, it may not capture additional features that may be informative (domain size, fluorescence distribution, total signal etc.). For example domain coalescence would imply smaller, brighter domains, but similar total protein amounts, which appears to be the case from images, but isn't quantified per se.
4. The phosphospecific antibody signal is relatively weak, leading to relatively low signal to noise, which could compromise the ability to detect phospho-S180 in non-asymmetrically dividing cells or generally in cells in which Baz is not polarised and thus signal would be diffused around the cell rather than concentrated. Similar caveats could also apply to the lack of signal in interphase cells, where Baz may be less enriched at the cortex and not polarized. We are inclined to believe the authors conclusions, particularly given their examination of multiple cell types and tissues. However, it is a potential caveat as it may be most visible in polarised cells where it is asymmetrically enriched.
5. Examination of in vitro phosphorylation of human Par3D (Figure 6) seems out of place and does not add much. It is human, not Bazooka. They reveal 30 sites, 18 of which in both replicates, but most are not obvious CDK sites and the S180 equivalent site is missing. None of these sites is validated in vivo, at least in this work.

Minor comments:

• Figure 1: Uses metaphase arrested cells, presumably colcemid, but colcemid is only noted in Figure 2.
• Figure 2A: Scale bar is truncated
• Figure 2A: Example images of control neuroblasts could be useful to readers.
• Figure 2G' vs H': Because G' has two panels and H' has only one, we often confused the PKC and Mira box plots when comparing to Numb. Perhaps Mira could be in a separate sub panel or be more closely juxtaposed with Numb?
• Whereas both Numb/Mira were examined in CDK1(as), only Mira is reported for the S180A/D experiments. Is there a Numb phenotype as well?
• The discussion of the notch / Baz phenotypes (Figure 5) is rather complicated and a bit difficult to follow.
• Figure 5A: captions should indicate that RFP RNAi is depleting Baz.
• Box plots are used, but not described. i.e. outliers seem to be marked, but criteria unclear. Mean vs median, etc.

Some grammatical mistakes:

• Title: neuroblast (no 's'),
• Page 1: Cell fate difference(s?) in the resulting daughter cells
• Page 4: (As) CDK1 inhibition with 10 μM 1-NA-PP1 prevents neuroblasts from cycling and causes metaphase- arrested neuroblasts to slip out of mitosis. (Reword)
• Page 6: increased levels of basal fate(no 's') determinants

Significance

The links between cell cycle and cell polarity are clearly important and remain poorly understood. Hence, the work addresses key conceptual/mechanistic questions relevant to our fundamental understanding of stem cell biology and regulation of polarity and asymmetric cell division. In our opinion, there are clearly some interesting observations in the manuscript, the experiments are performed carefully, and the data are generally well described. That said, overall, the work seems somewhat premature.

1. The direct impact of CDK1 on Baz behaviour remains somewhat unclear. The authors do a good job of limiting the concentration of inhibitor to decouple effects of cell cycle progression from CDK1 levels per se, but this does potentially impact the strength of the phenotypes they can detect and hence the observed phenotypes are relatively minor. Note that driving cells out of mitosis with stronger CDK1 inhibition clearly impacts Baz localization, so the 'real' effect of CDK1 inhibition on Baz could be stronger than reported here. It is also unclear whether the phenotypes observed are directly linked to CDK1 regulation of PAR polarity or an indirect effect of cell cycle control of other processes. The authors' suggestion that it could be related to defects in cortical actin organization, which is known to be cell cycle controlled, seems most likely, but neither this or other models are explored further.
2. Using phosphospecific antibodies, they report on a novel putative CDK1 phosphorylation site, but aside from looking like a consensus CDK1 site, whether this site is CDK1 dependent is not examined. Notably, the corresponding phosphomutants have modest effects and don't obviously account for the CDK1 inhibition phenotype, leaving it somewhat unclear whether it is under cell cycle regulation.
3. The observation that S180 phosphorylation appears unique to asymmetrically dividing cells is very curious, but this observation is not followed up extensively. Again phenotypes of phosphomutants are quite modest, and while one can propose models to rationalise the phenotypes observed, these models are not fully explored.
4. The findings that human Par3D can be phosphorylated by CDK1 in vitro do not add much paritcularly as they obtain a very large number of putative sites raising questions of specificity, the sites are not validated, and an S180 equivalent site was not identified.

In summary, the individual findings of this work are interesting and generally solid. Each could be followed up to provide mechanistic insight into cell cycle- or cell type-dependent regulation of Par polarity. However, in their current state, the results seem more like a loosely connected set of observations.

Expertise: Cell polarity and asymmetric cell division

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Referee #1

Evidence, reproducibility and clarity

The coupling between cell polarity and cell cycle progression is an important aspect of symmetric and asymmetric cell division. Although there are several examples of cell cycle kinases phosphorylating polarity proteins, it has been difficult to assess the importance of these on cell division due to the strong and pleiotropic effects of manipulating these kinases. Here, the authors generate an analogue-sensitive allele of cdk1 in flies to tackle this question in neuroblasts (NBs) and sensory organ precursors (SOPs), two well characterised examples of asymmetric cell divisions. They show that partial Cdk1 inhibition (which still allows cell cycle progression) does not block Bazooka (PARD3 in mammals) polarization in NBs, but prevents coalescence of the Baz crescent, which has previously been shown to be an actomyosin-based process. They further identify a Cdk1 consensus site on Baz (S180) for which they generate a phospho-specific antibody, allowing them to show that this site is specifically phosphorylated in dividing NBs and SOPs. Although mutations at this site do not recapitulate the effect of Cdk1 on Baz coalescence, they do delay Miranda polarization in NBs and affect lateral inhibition and asymmetric cell division of SOPs. Finally, the authors show that human PARD3 can also be phosphorylated by Cyclin B/Cdk1 in vitro.

Major comments:

1. Figure 2A: it would be good to show that polarization of Baz::GFP in consecutive divisions is maintained in cdk1as2 animals in the absence of 1-NA-PP1.
2. The interpretation of the observed SOP phenotypes is complicated by the uneven expression of the pnr-GAL4 driver and the fact that it is expressed in epithelial cells rather than just SOPs. The authors could express their control and mutant Baz constructs under the control of neurP72-GAL4. It is not likely they would be able to deplete endogenous Baz as they have done in NBs, as neurP72-GAL4 is expressed too late to deplete most proteins before SOP division, but they could at least look at localization of the mutants and any possible gain-of-function phenotypes.
3. The authors speculate that Baz phosphorylation during lateral inhibition may be the reason for the observed excess specification of SOPs in the S180 mutants. This could easily be tested by looking at their antibody staining at earlier stages in the notum.

Significance

This work advances our knowledge of the coupling between the cell cycle and cell polarity during cell division, and shows that Baz/PARD3 receives inputs from Cdk1 that is specific to asymmetrically dividing cells. The reagents generated here (cdk1as2 and phospho-specific antibody) will also be of interest to the field. The data are convincing and well documented. This work should be of broad interest to the stem cell and developmental biology fields. Above are a few suggestions to improve the manuscript.

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Reply to the reviewers

Point-by-point response to reviewers’ comments:

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

Major comments: 1. Previous studies using HDR and donor templates have shown that mutating the PAM sites in donor templates can enhance repair efficiencies. It would be helpful to add a discussion about the fact that SpRY does not have a PAM sequence that could be mutated and the potential consequences on repair efficiency.

We find that one mismatch in the target sequence (i.e. albino wt v. albino[b4]) is enough to completely abolish activity of SpRY. We have stated this more clearly in the manuscript.

It is also unclear how the template for the induction of mutations in kcnj13 was chosen. From the experiment with SpRY it seems that an HDR template equivalent to the sequence of the sgRNA target strand was most efficient, while in this experiment the alternative strand was used. An explanation should be added to the text.

Oligonucleotides corresponding to both DNA strands were tested, only one of them yielded positive results. We do not know the mechanistic basis for this finding, but amended the manuscript accordingly.

Minor comments: 1. It is not directly evident what the difference between the OP2 and OP2* sgRNA is. A short explanation would help clarify this and make it easier for the reader to understand.

OP2 (now re-named: U6) targets the wild type sequence, whereas OP2* (now: U6*) targets the albino[b4] sequence, which has one mutation leading to a premature stop codon. As this mutation is in the target region, we need adapt the sgRNA accordingly. We have stated this in the text more clearly now.

Similarly, it would be helpful to add the length of the different donor templates to Figure 2.

We have added the lengths of the oligonucleotides (in nt) to Fig.2.

While the PAM sequences and their difference between guides is discussed for two of them (OP2 and U5), it would be helpful to add the PAM sequences for all guides to Table 1 or figure 1.

We have added a table with all target sites including PAM sequences.

For people who are unfamiliar with the obelix phenotype/pigment pattern, it would be helpful to add a picture of an obelix mutant to Figure 4, so they would know what the phenotype would look like and how obvious it would be.

We have added a panel showing an obelix mutant fish to Fig.4.

Reviewer #2:

While every new and improved method to generate stable allele swap lines is greatly needed in the community, the results are not sufficient to convince me that the new version is leading to better success than previous methods. While they found one successful founder event, a single one is not enough to calculate efficiencies. Could just be luck that they got one. It is already known that HDR is very locus-specific, so maybe the locus they chose is such a locus.

This comment is difficult to address; while we found that the improved HDR method we present in the paper leads to better success for the repair of the albinob4 mutation and the one specific allele exchange we performed, we, of course, agree that one founder event is not enough to calculate efficiencies. However, we would like to maintain that one founder will in almost all cases be better than none. We also think that the locus we chose, kcnj13, is not a particularly lucky one yielding positive results easily, because it used to be refractory to editing following published protocols for a long time.

Overall, the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus towards refining and showcasing their methodological approach. This dual identity results in a study that, while informative, lacks the comprehensive exploration typical of dedicated research papers or the focused, technical depth one might expect from methodological publications.

Overall, we feel that there might be a slight misunderstanding here. The reviewer states that ‘… the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus…’, which is quite the opposite of what actually lead to the writing of the manuscript. We had already suspected that the single amino acid difference in the protein sequence between the two sister species might not be responsible for the observed functional divergence of the gene. We had also already found allele-specific differences in expression levels in hybrids, which make cis-regulatory evolution more likely. So, the null-hypothesis of our experiments was that both protein sequences would be functionally equivalent. However, as we had difficulties with the allele exchange due to low HDR efficiencies we needed to improve the method before we could definitively show this.

We have re-written some parts of the manuscript to make it clearer that we do not claim to have invented a method for HDR that is superior to all previously published ones. Rather, we think that we offer a variation of these published methods, which other researchers, struggling with low editing efficiencies (as we did), might want to try. What we do show in the manuscript is that the addition of an aNLS to Cas9 or SpRY leads to an increase in the efficiency in the generation of albino k.o. alleles and in HDR to repair the albinob4 mutation (see Fig. 3). If this will also be the case when editing other genes in the zebrafish genome needs to be investigated, but is clearly beyond the scope of this manuscript. We investigated one other locus in the zebrafish genome and could get one founder fish for the allele exchange in kcnj13, as opposed to zero we obtained with previously tried methods (conventional Cas9 with long or short donor-DNAs, prime editing). One advantage of ’our method’ is the simplicity of implementation. The Cas9 and SpRY proteins are easy to express in E. coli and the purification using two affinity tags is highly efficient resulting in samples of sufficient purity and high enough concentration for immediate use in injection experiments. So, we think that other researchers could easily try out the aNLS tagged proteins without changing much else of the protocols they usually employ for genome editing in zebrafish.

Reviewer #3:

Major comments: • The Cas9SpRY has been previously analyzed for the efficiency in zebrafish (Liang et al, Nat Comm 2022). This becomes only clear after reading the discussion. A comparison of these previously published SpRYCas9 proteins containing the bpNLS is missing, also a comparison of the efficiencies. The same locus (Albino) has been used in the study, are the guides identical? This study has not efficiently put the results in perspective of published results of the afore mentioned paper. And it seems that addition of the aNLS is not providing any benefit, which is good to know for the community.

We have added information to the introduction making it clear that the SpRY protein has previously been used in zebrafish. We also expanded the discussion and added more details comparing our results to previously published ones. However, this comparison is not always easy because the evaluation methods are different, sequencing v. phenotypic read-out. While the addition of the aNLS to the SpRY protein did not significantly enhance the (already high) k.o. efficiency for the albino locus, it did result in a significant boost of the repair efficiency of the albino[b4] mutation (see Fig.3C). Therefore, we think that the general statement it ’is not providing any benefit’ might not be entirely accurate. We think that the use of SpRY could be beneficial in some instances, but it must be assessed one a case-by-case basis.

• The HDR numbers is relying on 1 germline founder fish and might not be representative. More loci and higher numbers would be desirable.

We completely agree with the reviewer on this point. However, we feel that this is beyond the scope of this manuscript; we are looking forward to seeing other labs using the aNLS tagged proteins and finding out about their experiences.

• The allele exchange in Obelix is an interesting approach to use HDR but should be explained a little bit more. The motivation behind this experiments rains unclear.

We have added some information on obelix to provide more context

minor points: • All y axes require a labeling: % of what?!

We have changed the labels to % of larvae.

• When showing the specific classes of phenotpes the reader would benefit if the classes were written directly into the fish picture rather than using B, C, D, etc...

We have added this information directly to the pictures.

• OP2 should be called U6 to avoid unnecessary confusion, or is there anything special about it, why does it have another name?

We have changed OP2 to U6, as requested. The naming was completely due to historic reasons, there is nothing special about this target site / sgRNA.

• Differences in efficiency could potentially attributed to the PAM sequence as discussed. Please list the different PAM sequences and discuss in more detail. Why are so many gRNAs not efficient in the KO approach (Figure1)?

We added a table with the different target sites and the corresponding PAM sequences.

While we cannot provide a satisfactory explanation for the low efficiencies of five from six sgRNAs in our experiments, we notice that in the published data from Liang et al., 2022, a sizeable proportion of the tested sgRNAs with the SpRY protein also show low efficiency or no activity at all (see Fig. 2B, Liang et al., 2022, https://doi.org/10.1038/s41467-022-31034-8). This phenomenon is likely to be locus-specific and more data will be needed to come to a mechanistic understanding. We also do acknowledge that there is the possibility that our assay, the albino mutant phenotype in larvae, is likely not as sensitive as sequencing-based approaches. For one, we rely on the bi-allelic k.o. of the target gene, and we only assess a small proportion of all larval cells. However, we think that our approach with a phenotypic read-out is still valid, as it will reflect the practical requirements for an HDR method in many laboratories, where low efficiencies will result in no or weak and variable F0 phenotypes and in very low probabilities for germ-line transmission, which in most cases researchers will want to avoid.

• Line 217: correct co.injected to co-injected

done

The scientific advancement is not clear. Readers would benefit if the advancement can be worked out better. Most readers would like to decide if it is worth changing their Cas9 design for genome editing in zebrafish and what efficiencies to expect.

We have modified the manuscript to better convey the scientific advancement it presents. We think it lies mainly in the fact that no other changes to the design of genome editing experiments is required, but to exchange the Cas9 protein usually employed for the aNLS tagged proteins. Both proteins, aNLS tagged Cas9 or SpRY, can easily be produced and purified in the lab following standard protocols. In less than one week enough protein for several hundred or thousands of injection experiments can be purified and aliquoted. We suggest that everybody uses their tried and tested method to produce knock-in alleles, and, as long as it works for them, don’t change it. If, however, the efficiencies are too low to get the desired allele, it will be very quick and simple to try our method. This is what we wanted to demonstrate with the editing of the obelix locus. In all cases we can envisage identifying one founder fish will be considerably better than not finding a single one.

Reviewer #4:

Major

1. The authors use a mutated version of the widely used Cas9 protein from Streptococcus pyogenes, SpRY which basically does not rely on a PAM motif adjacent to the sgRNA target site. While this has certain advantages which are properly described, lowering stringency also comes with disadvantages, i.e. enhanced off target site activity. While assessing these is of the scope of the paper, these considerations should be properly discussed. Under which circumstances do the authors suggest to use SpRY and at which the conventional Cas9 or TALENs?

This is an important point and we have expanded on this. We think that SpRY offers a possibility to target sites that are not accessible to conventional Cas9, but it should not be expected to work as well as Cas9 for all loci (see also Liang et al., 2022 Fig.2). Whether the reduced stringency leads to more off-target effects is unclear; we did not experience higher rates of deformations or mortality in the injected larvae. This is, admittedly, a very crude measure for potential off-target effects, but is also in good accordance with the findings of Liang et al., 2022. In contrast to this, all labs that produce their own Cas9 protein could easily switch to the aNLS tagged version. It does not seem to have any disadvantages.

The authors designed 6 guides against slc42a2/alb according to the text and to Fig1 U1-U5+OP. Table 1 contains 16 sequences fitting these criteria. Which ones where used? Why are they named differently (U vs OP)? What method was used to design them? Does their design include PAM requirements? Have these guides been used previously and confirmed to work efficiently using CAS9? If the authors intend to provide an improved method that can widely and easily be adopted by other labs, they should put special emphasis in describing the procedure properly possibly including a supplemental figure detailing the workflow.

We have added a table with the target sites and the corresponding PAMs (see response to reviewer #1). The oligonucleotides shown in Table 1, which is now Table 2, are the ones used to generate the plasmid templates for the in vitro transcription of the sgRNAs.

The naming of the target sites, which was solely due to ’historic’ reasons, has been changed to U1 - U6.

They were designed (basically by hand) to allow in vitro transcription with T7 RNA polymerase (i.e. 5’ with GG), to have a G/C content of 50 - 65% and to represent a variety of different PAM sequences, that should potentially result in high activity (according to the data published by Walton et al., 2020 DOI: 10.1126/science.aba8853).

These sgRNAs could not be tested with Cas9 as they lack the PAM (NGG) required for activity of this protein.

We think that the main advantage of ’our’ method lies in the fact that aNLS-Cas9 (and aNLS-SpRY) can easily incorporated into the experimental procedures and workflows already in place in other laboratories. There is no need to follow exactly our protocol, eg. regarding sgRNA production or target site selection. We think that we showed that SpRY can be as effective as conventional Cas9, but not for all target sites, and that the addition of an aNLS sequence to Cas9 or SpRY is beneficial for genome editing in zebrafish, even when the aNLS is not combined with a myc-tag, as is the case shown by Thumberger et al., 2022, i.e. hei-tag.

The authors use a recessive pigment mutant (albino) to validate and quantify precise genome editing by HDR applying their toolbox. This is very clever and probably the most robust readout possible. The authors found that adding an aNLS to CAS9 and SpRY improves rescue efficiency, possibly also for germ line transmission. The authors should compare their efficiency for accurate editing with that of other papers in the field to allow for a better comparison.

We have now included a more detailed comparison of our results with previously published data in the discussion. However, this comparison is not always easy because the evaluation methods are different, sequencing v. phenotypic read-out. In terms of accuracy of the methods, we found that the majority of the HDR events we detected were associated with additional mutations. Some of these were possibly due to synthesis errors in the donor oligonucleotides, which might be alleviated by different purification methods. Other mutations, however, most likely occurred during cellular repair of dsDNA breaks and are therefore not easily avoided, unless double strand breaks are avoided, which would be the case if base editors are used. However, with base editors it is so far not possible to introduce every possible DNA change, making HDR methods still useful.

Minor:

1. Fig.1A: Please indicate orientation of the gene

done

Line 168: ... tested sperm... à Method not explained in the methods section

The sperm samples extracted from anaesthetized males were used in exactly the same way as larvae were in other genotyping experiments; as is mentioned in the methods section. We have re-phrased this section a bit to make it clearer that we used larvae or sperm in exactly the same way for genotyping.

Kcnj13 editing. Explain obelix pigment phenotype to the non expert reader in pigmentation possibly illustrating D. aesculapii. This is a very powerful method allowing such comparisons, however it is not properly explained.

We have added some information on the obelix phenotype and included a panel of a mutant zebrafish in Fig.4.

Line 130: 'hei-tag' not properly explained

The hei-tag, published by Thumberger et al., 2022, consists of a myc-tag, a flexible linker and an aNLS in exactly that order. We have added some more details on the hei-tag to the text.

The co-editing of a restriction site for later identification of the edited allele is clever. However precise editing should be performed carefully and include splice site prediction algorithms to avoid enabling ectopic splice sites by silent mutagenesis. Also, an example of the analysis would be benefitial to Fig.4 or in the supplement.

We agree that this is an important point. We originally designed the edit in a way that would not result in the generation of a strong ectopic splice site by avoiding the creation of AG or GT di-nucleotide sequences.

We now also performed analysis with spliceator (http://www.lbgi.fr/spliceator/), a splice site prediction tool using convolutional neural networks, which confirmed that no ectopic splice site should be generated.

We could include this into a supplementary figure, if deemed necessary.

The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.

As mentioned above, we think that it will be easy for other labs to incorporate our improvements into their existing protocols by exchanging normal Cas9 for aNLS-Cas9 or aNLS-SpRY. There should not be the need to strictly follow our protocols, e.g., for target site selection or sgRNA synthesis. The proteins can easily be expressed in bacteria and purified by standard methods using the His- and Strep-tags, as we published previously for conventional Cas9 (Podobnik et al. 2023).

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Referee #4

Evidence, reproducibility and clarity

In this manuscript, Dorner, Stratmann et al. developed a new variant of the homologous directed repair mediated genome editing technique in zebrafish using modified Cas9 proteins. They focus on the SpRY Cas9 protein variant, which offers a more relaxed PAM requirement for gene targeting. The requirement of a PAM has particularly hampered the feasabilty of HDR in the zebrafish model as the genomic sites of interest often do not meet the PAM requirements for conventional Cas9. Their improved method enhances the versatility of CRISPR/Cas methods in zebrafish, a crucial model organism in biomedical research. The authors also demonstrate that integrating an artificial nuclear localization signal (aNLS) into Cas9 variants not only improves gene knockout efficiency but also boosts homology-directed repair (HDR) frequency. This advancement allows for more precise genetic modifications, including single base pair changes, offering significant potential for research and other applications in genetics.

The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.

Major comments:

1. The authors use a mutated version of the widely used Cas9 protein from Streptococcus pyogenes, SpRY which basically does not rely on a PAM motif adjacent to the sgRNA target site. While this has certain advantages which are properly described, lowering stringency also comes with disadvantages, i.e. enhanced off target site activity. While assessing these is of the scope of the paper, these considerations should be properly discussed. Under which circumstances do the authors suggest to use SpRY and at which the conventional Cas9 or TALENs?

2. The authors designed 6 guides against slc42a2/alb according to the text and to Fig1 U1-U5+OP. Table 1 contains 16 sequences fitting these criteria. Which ones where used? Why are they named differently (U vs OP)? What method was used to design them? Does their design include PAM requirements? Have these guides been used previously and confirmed to work efficiently using CAS9? If the authors intend to provide an improved method that can widely and easily be adopted by other labs, they should put special emphasis in describing the procedure properly possibly including a supplemental figure detailing the workflow.

3. The authors use a recessive pigment mutant (albino) to validate and quantify precise genome editing by HDR applying their toolbox. This is very clever and probably the most robust readout possible. The authors found that adding an aNLS to CAS9 and SpRY improves rescue efficiency, possibly also for germ line transmission. The authors should compare their efficiency for accurate editing with that of other papers in the field to allow for a better comparison.

Minor comments:

1. Fig.1A: Please indicate orientation of the gene

2. Line 168: ... tested sperm...  Method not explained in the methods section

3. Kcnj13 editing. Explain obelix pigment phenotype to the non expert reader in pigmentation possibly illustrating D. aesculapii. This is a very powerful method allowing such comparisons, however it is not properly explained.

4. Line 130: 'hei-tag' not properly explained

5. The co-editing of a restriction site for later identification of the edited allele is clever. However precise editing should be performed carefully and include splice site prediction algorithms to avoid enabling ectopic splice sites by silent mutagenesis. Also, an example of the analysis would be benefitial to Fig.4 or in the supplement.

Significance

The manuscript is well written, the data are presented in an accessible way and the results look convincing. The work clearly shows a path to improvement of a fundamental method of gene editing in zebrafish and other species and clearly provides essential data on the topic. However, some aspects of the work are not properly described for the non-expert. Given the nature of the work which aims to improve an important, established method a more precisely described workflow in form of a table and workflow chart would certainly help the reader to focus on the essentials of the procedure.

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Referee #3

Evidence, reproducibility and clarity

The manuscript "efficient genome editing using modified Cas9 Proteins in zebrafish" by Dorner et al. is using the modified SpRY Cas9 protein with the addition of an artificial nuclear localization sequence (aNLS) and compares its efficiency in the generation of making KO animals with other Cas9 proteins and its use to generate a HDR mediated KI in zebrafish. The paper shows that the SpPY Cas9 works efficiently and that addition of aNLS can increase the HDR mediated efficiency in one locus.

Major comments:

• The Cas9SpRY has been previously analyzed for the efficiency in zebrafish (Liang et al, Nat Comm 2022). This becomes only clear after reading the discussion. A comparison of these previously published SpRYCas9 proteins containing the bpNLS is missing, also a comparison of the efficiencies. The same locus (Albino) has been used in the study, are the guides identical? This study has not efficiently put the results in perspective of published results of the afore mentioned paper. And it seems that addition of the aNLS is not providing any benefit, which is good to know for the community.

• The HDR numbers is relying on 1 germline founder fish and might not be representative. More loci and higher numbers would be desirable.

• The allele exchange in Obelix is an interesting approach to use HDR but should be explained a little bit more. The motivation behind this experiments rains unclear. minor points:

• All y axes require a labeling: % of what?!

• When showing the specific classes of phenotpes the reader would benefit if the classes were written directly into the fish picture rather than using B, C, D, etc...

• OP2 should be called U6 to avoid unnecessary confusion, or is there anything special about it, why does it have another name?

• Differences in efficiency could potentially attributed to the PAM sequence as discussed. Please list the different PAM sequences and discuss in more detail. Why are so many gRNAs not efficient in the KO approach (Figure1)?

• Line 217: correct co.injected to co-injected

Significance

The scientific advancement is not clear. Readers would benefit if the advancement can be worked out better. Most readers would like to decide if it is worth changing their Cas9 design for genome editing in zebrafish and what efficiencies to expect.

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Referee #2

Evidence, reproducibility and clarity

The manuscript: Efficient genome editing using modified Cas9 proteins in zebrafish by Dorner and Stratmann et al. provides a putative improved method of modifying single base pairs in the genome of zebrafish through homology-directed repair. The authors use a modified Cas9 protein called SpRY in zebrafish. The SpRY protein has fewer restrictions on the PAM sequence it requires, which broadens its genome targeting potential. The paper presents experiments on zebrafish using SpRY for efficient genome editing. However, not all target sites are equally efficient, and the authors suggest that individual sequences may need to be evaluated on a case-by-case basis.

The paper also explores the benefits of using an optimized artificial nuclear localization signal (aNLS) for the Cas9 protein, which significantly increases genome editing efficiency in zebrafish. Using this improved method, the researchers demonstrate precise editing of the kcnj13 gene in zebrafish to match the sequence found in Danio aesculapii, their closest sister species. The edited zebrafish do not show any visible phenotypic changes, suggesting that the Kcnj13 proteins from both species are functionally equivalent.

While every new and improved method to generate stable allele swap lines is greatly needed in the community, the results are not sufficient to convince me that the new version is leading to better success than previous methods. While they found one successful founder event, a single one is not enough to calculate efficiencies. Could just be luck that they got one. It is already known that HDR is very locus-specific, so maybe the locus they chose is such a locus.

Significance

Overall, the paper suffers from the problem that the authors initially set out to investigate a specific genetic mutation in zebrafish but, upon observing that the resultant mutant exhibited no discernible phenotype, they shifted their focus towards refining and showcasing their methodological approach. This dual identity results in a study that, while informative, lacks the comprehensive exploration typical of dedicated research papers or the focused, technical depth one might expect from methodological publications.

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Referee #1

Evidence, reproducibility and clarity

Summary:

The manuscript "Efficient genome editing using modified Cas9 proteins in zebrafish" by Dorner et al. describes the utility of combining Cas9 variants with an alternative NLS to improve the efficiency of induction of single base pair changes in zebrafish through HDR. The authors confirm findings from previous studies, that the SpRY variant of Cas9 can be used in zebrafish to induce knockouts at efficiencies similar to Cas9 and additionally show the ability of SpRY to induce point mutations via HDR. They further confirm other studies that showed that the addition of an artificial NLS can significantly increase targeting efficiency of Cas9 in zebrafish. They extend their studies to show that the increased efficiency through addition of this alternative NLS also enhances HDR mediated induction of single base-pair changes using donor templates for both Cas9 variants. Most conclusions of the paper are well supported by the presented data and the experiments are explained in sufficient detail for replication. The paper could benefit from a few modifications/additions to the text to clarify a few details.

Major comments:

Previous studies using HDR and donor templates have shown that mutating the PAM sites in donor templates can enhance repair efficiencies. It would be helpful to add a discussion about the fact that SpRY does not have a PAM sequence that could be mutated and the potential consequences on repair efficiency. It is also unclear how the template for the induction of mutations in kcnj13 was chosen. From the experiment with SpRY it seems that an HDR template equivalent to the sequence of the sgRNA target strand was most efficient, while in this experiment the alternative strand was used. An explanation should be added to the text.

Minor comments:

1. It is not directly evident what the difference between the OP2 and OP2* sgRNA is. A short explanation would help clarify this and make it easier for the reader to understand.

2. Similarly, it would be helpful to add the length of the different donor templates to Figure 2.

3. While the PAM sequences and their difference between guides is discussed for two of them (OP2 and U5), it would be helpful to add the PAM sequences for all guides to Table 1 or figure 1.

4. For people who are unfamiliar with the obelix phenotype/pigment pattern, it would be helpful to add a picture of an obelix mutant to Figure 4, so they would know what the phenotype would look like and how obvious it would be.

Significance

General assessment: Strength of the study are the use of multiple, independent injection experiments for each group to test guide and repair efficiency. Clear presentation of methods which will allow replication of experiments and also production of reagents. While the study clearly shows that SpRY does work for HDR mediated repair, only one specific repair template design (single stranded oligo) was tested. This study could be enhanced through testing of additional HDR template designs and a direct comparison of repair efficiency between Cas9 and SpRY.

Advance: This study does provide a minor advance in our understanding of how the efficiency of Cas9 and its variants can be optimized and how these modifications can enhance repair efficiency. The use of the SpRY variant in zebrafish as well as the enhancement of Cas9 efficiency through the use of the aNLS has been shown before (Liang et al. 2022, Thumberger et al. 2022). Novelties in this study are the use of SpRY for HDR mediated repair and the improvement of the repair efficiency through the addition of the aNLS to SpRY and Cas9.

Audience: The methods described in this paper will be of interest to the zebrafish and Medaka communities as well as people using HDR mediated repair for the induction of mutations.

Expertise: I am a geneticist who has worked with the zebrafish model for over 20 years and uses CRISPR/Cas for genome editing in zebrafish routinely.

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Reply to the reviewers

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

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Referee #3

Evidence, reproducibility and clarity

Genome-wide association studies (GWAS) were used to identify potential risk variants associated with amyotrophic lateral sclerosis (ALS), and a specific variant of GGNBP2 has emerged as a critical player, exhibiting increased expression, and prompting the authors to investigate its role in the disease progression.

The study, focusing on Drosophila Ggnbp2 (dGgnbp2) in motor neurons, revealed crucial insights into its function. Loss-of-function experiments underscored the necessity of dGgnbp2 in motor neuron synaptic development. Strikingly, introducing a human transgene fully restored these phenotypes, demonstrating functional conservation between humans and flies. Contrary to expectations, overexpression of dGgnbp2 resulted in severe locomotor defects in adult flies, mirroring aspects of ALS pathology, suggesting a tight regulation for this protein in the control of NMJ function.

The authors also suggest a role of the gene in regulating autophagy, as RNA-seq showed abnormalities in the expression levels of genes involved in autophagy when dGGNPB2 was mutated. Finally, they described a potential molecular mechanism through which GGNBP2 may regulate autophagy and that is by controlling phospholipid levels specifically PI(3)P.

Understanding the cellular mechanisms, the study suggests dGgnbp2's role in regulating autophagy, a process frequently impaired in ALS, and both overexpression and depletion of dGgnbp2 led to altered levels of phosphorylated lipid PI(3)P, a vital component of autophagosomes. Add PI3K This comprehensive investigation provides compelling evidence that Ggnbp2 plays a pivotal role in motor neurons, exerting regulatory control over a cellular process commonly compromised in ALS. These findings also provide insights into the functional implications of the GGNBP2 variant and also open new avenues for potential therapeutic crucial pathways like autophagy and InR, offering a promising direction in ALS treatment.

Major:

The experiments outlined in this paper, which elucidate the function of the Ggnbp2 in the neuromuscular junction (NMJ), are compelling and crucial for characterizing a novel gene implicated in ALS. However, my primary concern revolves around the demonstration of the influential role of the Ggnbp2 in regulating autophagy and its responsiveness to insulin signaling.

Indeed, the author should better analyze and also genetically demonstrate an interaction between Ggnbp2 and components of the insulin signaling pathway. For instance, analyzing PTEN (utilizing available mutants) could enhance the understanding of the pathway linking Ggnbp2 downstream of PIP2.

The connections drawn in the paragraph regarding autophagy (paragraph title: dGgnbp2 is linked to autophagy in motor neurons) might be a bit tenuous for the described observations. In the end it seems to only suggest a link to autophagy without explicitly asserting that it drives autophagy. The authors have overlooked providing a clear explanation or speculation on the correlation between GGNBP2's regulation of autophagy and its impact on synaptic development. A more explicit emphasis, then, on whether a loss-of-function or gain-of-function is more pertinent to human disease is necessary.

The authors should take advantage of the available Drosophila lines to elucidate the relative dependence of the autophagic flux controlled by Ggnbp2 and macroautophagy, using mutants or RNAi lines for Atg1, Atg5, and potentially Atg6/beclin, as these factors have been demonstrated to be relevant in neurodegenerative diseases, including ALS and Parkinson's.

Furthermore, alternative approaches for testing InR activation exist, such as the widely employed tPH-GFP method (Britton et al., 2002) that could be used to implement the activation of Akt in NMJ.

The observation that dGgnbp2 serves specific functions in the cytoplasm of motor neurons is particularly interesting, and further investigation to better understand this function would be valuable. Additionally, is this soluble form also identified in humans?

Minor:

Line 113-119: This does not seem relevant to the study. This is not discussed or investigated anywhere else in this work. However, I understand and appreciate the intent.

Line 135-138/Figure 2L: The authors do not address the non-significant "continuous" data.

Line 191: Define the age of young animals.

Line 192: Why did the authors change to OK371-Gal4 promoter in the experiments in Figure 4.

Line 192: The authors need to specify how young were the animals.

Line 202: Is the human GGNBP2 expressed with OK6-Gal4 able to rescue the reduced motility of the d Ggnbp2null flies?

Line 223: Typo, "to the" is repeated.

Referees cross-commenting

The comments I read are all feasible and in line with what I also suggest, and I accept them. What is not clear is how much time the authors need if they reply to all, which, of course, depends on how much deeper they decide to go to complete the characterization of GGNBP2 in autophagy and the relevance of InR/TOR signaling. This will also depend on the journal they decide for their final submission.

Significance

This study outlined in this paper rests on a robust experimental design and yields conclusive results. It shows strong evidence of a role of the GGNBP2 gene in ALS pathology. It provides clear evidence of a synaptic development defect as well as a locomotor dysfunction in mutants, building on its relevance in human pathology. It solidly proves a functional conservation between flies and humans. It then suggests a potential role in regulating autophagy. However, further experiments demonstrating the actual interaction between GGNBP2 and class I and III PI3K is needed to fully elucidate the mechanisms through which GGNBP2 controls autophagy.

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Referee #2

Evidence, reproducibility and clarity

Kerwin et al. conducted a study on the function of dGgnbp2 and its role in motoneurons. There are some general oversights that make the paper less robust than it could be. Firstly, the connection between autophagy dysregulation and the autophagic defects shown in the last figures is not clear. Combining these two parts would add more value to the paper. Secondly, the actual connection to ALS - made by the authors throughout the study - is not very strong. The only link with ALS is mentioned at the beginning when it is stated that Futsch is a target of TDP-43 and later when the authors mention that autophagy is a key dysregulated pathway in ALS. Although this is true, there is no strong connection to ALS pathology. It would have been appropriate to measure TDP-43 mislocalization in the animals and see whether the Futsch decrease observed in both null and OE models is related to it, or whether TDP-43 aggregates.

Figure 2: Although the results presented in Fig S3R-X suggest a possible reduction in dGgnbp2 protein, it would be more reliable to validate the knockout strategy used for this figure with a PCR or a WB. The same comment applies to Figure 3.

Figure 5H: Why aren't the results with dGgnbp2 OE shown in the locomotion sets, but rather a het null + GGNBP2OE is reported? This does not match the groups represented in the previous panels of the same figure.

Line 223 typo: In motor neurons, it was localized to the cytoplasm

Figure 6: I suggest performing N/C fractionation and WB probing for V5 to better characterize protein localization. This data is relevant given results in the next figure.

Figure 6I:To claim dGgnbp2 function is cytoplasmic, data on mutant alone needed (not in null background).

Figure 7: The volcano plot shows that the over expression system and the insertion only exhibit similar genes, which suggests that most of the observed changes are due to the insertion alone. As we do not have a clear understanding of GGNBP2's function in the nucleus, we need more precise data on over expression.

Figure 8: Autophagy experiments are very interesting, despite the lack of crucial data. While it is evident that autophagy dysregulation occurs due to dGgnbp2 dysregulation, it is unclear whether it is a direct cause of the pathology. This assumption can only be confirmed by conducting a few experiments. Firstly, auto-Nagy defects should be measured in rescue models such as the one presented in figure 5. Secondly, treatment should be administered to restore autophagic flux, such as rapamycin or Torin1, as these drugs are known to help in cases of autophagy dysregulation. Another experiment that could be conducted is the overexpression of key autophagic proteins, such as Atg8.

Significance

This study is unique as few studies have focused on this protein and none on its role in motor neurons. The experiments were well-conducted, with the proper controls in place. The authors clearly demonstrate the significance of balanced protein levels for proper synapsis development and optimal motor neuron performance. The study also evaluated RNA dysregulation in different models used in the previous section of the paper. The authors found that autophagy was one of the dysregulated pathways. They characterized the autophagic defects in these cells.

The study would be of interest to a specialized audience since its potential translational implications.

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Referee #1

Evidence, reproducibility and clarity

In this paper, Kerwin et al. investigate the role of the GGNBP2 in synaptic morphology and autophagy in motor neurons. Using Drosophila, the authors performed functional studies of GGNBP2, a putative nuclear protein which has been linked to ALS through GWAS. Through creating clean mutants using CRISPR, the authors found that the null mutants of the fly homolog of GGNBP2 (CG2182, a previously uncharacterized gene which they propose to name Ggnbp2) are viable and fertile, but exhibit motor defects in adult flies accompanied by synaptic phenotypes in the larval neuromuscular junction (NMJ). In addition, the authors show that overexpression of Ggnbp2 also cause behavioral and NMJ defects, which is significant for ALS studies since the variant associated with this condition seems to increase the levels of GGNBP2 based on eQTL studies. Interestingly, the human GGNBP2 was able to rescue the fly LOF mutant phenotypes, suggesting that they have conserved molecular functions. Surprisingly, while mammalian GGNBP2 has been suggested to function as a transcription factor and gain and loss of this gene seems to mildly alter the transcriptome in flies, the authors showed that majority of the endogenously expressed fly Ggnbp2 protein is found in the cytoplasm and that the predicted nuclear localization signal (NLS) is not required for its function in motor neurons. Finally, the authors performed some additional experiments to propose a functional link between this gene and autophagy, focusing on its potential regulation of PI(3)P and genetic interaction with a fly ortholog of TBK1, which have also been linked to ALS in human.

Overall, I feel this work addresses an important question in the field and the genetics experiments have been conducted with rigor. This study somewhat lacks mechanistic insights (e.g. how does Ggnbp2 regulate PI(3)P and motor neuron function?) but there are a number of novel findings (e.g. first generation and characterization of the null mutant of Ggnbp2 in flies, showing that it's predicted NLS is not important) that makes this paper provide value to the literature and community in its current form. While I have several major and minor issues that I would like to see addressed the authors, I would be generally in favor of this paper to be published in an appropriate journal that targets readers with interests in human neurological disorders and Drosophila biology.

Major Points

Major #1: In Figs 5, 6 and S3, the authors demonstrated significant rescue of Ggnbp2 null phenotypes by overexpressing fly Ggnbp2 or human GGNBP2 protein using the GAL4/UAS system. However, data shown in Fig 3 and elsewhere reveals that overexpression of fly Ggnbp2 results in smaller bouton numbers and larger boutons. Regarding this...

1A: Does overexpression of human GGNBP2 in a wild-type background show similar NMJ and motor behavioral defects as fly Ggnbp2?

1B: It is quite surprising that the authors were able to rescue the null mutant NMJ phenotype using GAL4/UAS (in this case OK6-GAL4) system considering that overexpression of this protein seems to have a strong effect using this driver as well. Is this because they used the UAS-dGgpnb2::V5 as a heterozygous in FigS3, which is a condition in which the overexpression phenotype is not seen? If so, the genotype of FigS3 (and Fig3) should be matched with FigS4 (otherwise, it looks like the authors used homozygous of the UAS in FigS3).

Major #2: To assess adult fly locomotor performance, the authors employed the negative geotaxis assay to measure their climbing activity (Fig4). While the data show that the flies with LOF or GOF of Ggnbp2 have age-dependent defects, it is possible that the effect is developmental, especially for the overexpression paradigm. Considering that ALS is considered to be an adult onset neurodegenerative disease, it would be valuable if the authors can perform a conditional overexpression study of Ggnbp2[OE-EPgy2] using the Gal80[ts] system in which the fly Ggnbp2 that is overexpressed post-developmentally (i.e. overexpression of this protein induced only after eclosion) can also have an age-dependent motor defect. Considering that the authors do not perform any synaptic studies in adults (i.e. all NMJ experiments are performed in the larva), such experiments will increase the value of this work in the context of ALS research.

Major #3: The authors generated several of UAS-fly Ggnbp2 (V5 tagged with or without the NLS) and UAS-human GGNBP2 (Myc tagged). Regarding these...

3A: Other than in Fig6A, the authors do not show their expression pattern in motor neurons. It would appreciate if the authors can provide an immunostaining image of the all three proteins in the cell body and neurons of flies when expressed using OK6 or OK371. This way, the readers can appreciate whether the human and fly proteins behave similarly, and whether the deletion of the predicted NLS alters the subcellular localization of the protein. I acknowledge that it may be already difficult to observe the wild-type Ggnbp2 in the nucleus so one may not see a major difference but it would be important to document these.

3B: Considering that the Ggnbp2::V5 seems to show a punctate pattern, may be interesting to see if this signal overlaps with the Atg8a, PIP2 and 2xFYVE::GFP in the cell body or in the synapse.

Minor points

Minor #1: In line 62, "Given that 75% of genes..." needs a minor correction, as 77% is the the number of gene that is mentioned in the cited reference (77%). Perhaps the authors can say "Given that about 75% of genes...".

Minor #2: In line 266, the title of this section is "dGgnbp2 is linked to autophagy in motor neurons" but the author only shows data regarding the genetic interaction between Ggnbp2 and ik2 (official gene name is IKKε in FlyBase) in this section. Although IKKε and its mammalian homolog TBK1 is known to regulate autophagy, these are kinases that are involved in other processes (e.g. cell proliferation, cell death, cell polarity) so the title is a bit of an overstatement. Since the connection to autophagy is more directly shown in subsequent sections, I would recommend modifying the title of this section (e.g. "dGgnbp2 genetically interacts with IKKε, an ortholog of mammalian TBK1"". Also, note that IKKε is orthologous to both TBK1 and IKBKE so this may need to be clearly mentioned in the text.

Minor #3: In line 282, the loss-of-function (lof) allele for ik2[1] requires proper reference that experimentally showed that this is indeed a lof allele. Also, please change the 'ik2' nomenclature to 'IKKε' to match with the latest official gene name.

Minor #4: In FigS2, can the author show where the predicted NLS of the fly protein is that they deleted in Fig6E so the readers can see how conserved this region is between the fly and human proteins?

Minor #5: I personally feel that the section regarding "RNA-seq analysis of Ggnbp2" is a bit out of place. Currently, this follows the section that says Ggnbp2 is does not function in the nucleus, so it doesn't make much sense to perform RNA-seq experiment for something that you think primarily works in the cytoplasm if the goal of this assay was to find direct mechanistic targets. Perhaps the authors can consider showing moving this section to before the "dGgnbp2 functions in the cytoplasm of motor neurons" (and place Fig7 before Fig6) so you can use the fact that you didn't see much dramatic gene expression changes in the LOF/GOF mutants as a rationale of why you decided to question its nuclear requirements. Just a suggestion, but this may make your paper flow better.

Significance

Overall, I feel this work addresses an important question in the field and the genetics experiments have been conducted with rigor. This study somewhat lacks mechanistic insights (e.g. how does Ggnbp2 regulate PI(3)P and motor neuron function?) but there are a number of novel findings (e.g. first generation and characterization of the null mutant of Ggnbp2 in flies, showing that it's predicted NLS is not important) that makes this paper provide value to the literature and community in its current form. While I have several major and minor issues that I would like to see addressed the authors, I would be generally in favor of this paper to be published in an appropriate journal that targets readers with interests in human neurological disorders and Drosophila biology.

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Reply to the reviewers

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

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Referee #3

Evidence, reproducibility and clarity

In this manuscript, the authors reveal the genetic basis for why two different null alleles of Fasiclin II (Fas2), a member of the Igg superfamily of cell surface proteins, result in very different phenotypes in the follicular epithelia of the developing Drosophila egg chamber. One null allele - Fas2G0336 - results in rare occurrences of follicular cells being found outside of and apical to the plane of the epithelia in mutant clones, whereas the other null allele - Fas2EB112 - results in frequent occurrences of cells apical to the plane of the epithelia in mutant clones. Using recombination, they map a second mutation on the Fas2EB112 chromosome and demonstrate that it is a known allele of another Igg superfamily protein member - Neuroglian (Nrg). Thus, the severe phenotypes associated with only one of the two Fas2 null alleles can be explained by the additional absence of Nrg function, supporting previous studies that, in the follicular epithelia, the functions of Fas2 and Nrg are overlapping and compensatory.

The authors fully support this finding by several carefully done experiments, all of which are thoroughly described and nicely illustrated in the figures in the main body of the paper, with helpful information provided in the supplemental figures. Indeed, the authors explore a number of possible explanations for the phenotypic differences with the two null Fas2 alleles and their conclusion of there being a known mutation in Nrg on one of the two null chromosomes is supported by several independent approaches. No additional experiments are necessary, and the findings should be easily reproducible by others using the reagents described in the study.

Minor point: On the second page of the results, the last paragraph starts with "The second chromosome" in the first sentence. This is a bit confusing - could be considered chromosome 2, when the authors do not mean chromosome 2. It would be better to refer to this as "The other chromosome generated by recombination".

Referees cross-commenting

The other two reviewers have picked up some minor issues that should be addressed by the authors (quantitation of the Western, labels on all figure panels, etc). These changes would definitely improve the manuscript and should be done. I'm not convinced that the overall findings are important for a significant part of the Drosophila community - seems more of a specialty audience who needs to know that there is a second mutation in Neuroglian on one of the Fas2 null chromosomes that are available through the stock centers.

Significance

The findings are particularly relevant to anyone who has used the Fas2EB112 allele for their studies or who plans to do so. Otherwise, it serves as a cautionary tale to all to examine and report phenotypes using multiple different alleles as a control for what other mutations may also exist on mutant chromosomes of interest.

I am a Drosophila developmental biologist who uses most of the same tools used in this manuscript on a regular basis. I am also quite familiar with the experimental system used for this work.

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Referee #2

Evidence, reproducibility and clarity

Epithelial integrity is fundamental to organ function and development. There are mechanisms to reintegrate cells that divide outside of the cell layer that depend on cell adhesion. In many cases, including the Drosophila follicular epithelium, this adhesion and reintegration is dependent on partially redundant functions of the IgCAMs Fas2, Fas3, and Neruoglian (Nrg).

Here, Finegan et al have identified discrepancies in phenotypic strength between two null alleles of Fas2 and show that this is due to an additional mutation in Nrg on the phenotypically stronger chromosome (likely due to a submission of a double mutant rather than a single mutant to the stock center, as this Nrg allele seems to be the same aberration as the Nrg14 null alle used in this study as well). Overall, the data is sound and of interest to people working with these genes in the adhesion field, but not of a broader interest. Over passages the paper is lengthy (such as a description of recombinations separating the mutations (or not) on p5 or the extensive description of the Nrg splice variants on p7.

Points to address:

Major:

Fig 1C and Fig 4B: Why do the shRNAs used for Fas2 and Nrg have stronger phenotypes than the mutants? As clones were used, the argument of adaptation is harder to make. Specificity of shRNAs may have to be shown in a mutant background. Therefore, actually, this is particularly puzzling/worrisome in case of Fig. 4B where Nrg RNAi is stronger than the Nrg14 null allele (i.e. e(Fas2)mut) background.

P8/Fig 3F Western blot: Despite description of quantification of blots in methods, nothing is quantified, and the arguments of dosage compensation thus cannot be made. Comes up again in the discussion. Furthermore, would the resolution of the blot allow distinction of Nrg180-YFP from Nrg167-YFP to really exclude that only one of them is expressed from the tagged locus?

Discussion: Similarly, Mannheim Fas2EB112 has a lower average number of...., though this difference is not significant. Thus, is does not have a lower average!

Discussion: Sentence ending in '...that E(Fas2)mut is suppressed' is confusing. Suppressed with repressed to what by what?

Minor:

• P2 second paragraph: insert 'Drosophila' before 'follicular epithelium'.
• P4: Dr. Riechmann's first name is misspelled.
• P8 last line: Fig. X should be Fig. 4A.
• P12, legend of Fig. 2: description of panel B missing.
• Tables are supplementary and should be labeled as such in the methods.
• Fig. S3C: the non-disjunction aspect is not straight forward to see in the figure (e.g. XXY genotype and its correlation to eye shape from balancers).

Significance

Overall, the data is sound and of interest to people working with these genes in the adhesion field, but not of a broader interest.

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Referee #1

Evidence, reproducibility and clarity

This manuscript reports an intriguing genetic puzzle and its solution that is very relevant to Drosophila researchers studying the Immunoglobulin-superfamily cell adhesion molecules (IgCAMs) Fasciclin 2 (Fas2) and Neuroglian (Nrg), homologs of vertebrate NCAM and L1-CAM, respectively. In their earlier work, the authors described the roles of these IgCAMs in the Drosophila follicle epithelium, where Fas2 and Nrg are required for cell reintegration after mitosis. During cell division, errors in spindle positioning can cause newly born cells to get displaced from the epithelial sheet. Such apically extruded cells normally re-integrate with high efficiency into the epithelium. As the authors previously showed through genetic studies in the Drosophila follicle epithelium, mutations in Fas2 and Nrg act synergistically to disrupt reintegration, leading to the accumulation of extruded ("popped out") cells. A puzzle arose when the authors compared the phenotypes of two different presumed protein-null alleles of Fas2 (Fas2(EB112) and Fas2(G0336)), which showed different strengths of epithelial cell reintegration defects. They systematically examined the phenotypes of Fas2(G0336) and two different fly strains carrying the Fas2(EB112) allele and discovered that the more severe defects seen in one of the Fas2(EB112) strains are due to the presence of an additional mutation in Nrg on the same chromosome. Intriguingly, they identified the mutation in the Nrg locus as the previously characterized Nrg(14) allele. This suggests that the Fas2 Nrg double mutant chromosome did not arise naturally through random appearance of a second-site mutation, but that it was generated intentionally and then apparently got mixed up with the Fas2(EB112) strain (however, the authors do not comment on this point). The authors spared no effort to resolve this genetic puzzle in a clear and convincing manner. The used clever genetics, genome sequencing and polytene chromosome preparations to unveil the Nrg mutation as Nrg(14). The results are very clearly documented, and the text is well written, almost in the style of a criminal investigation. I have only minor comments to be addressed by the authors before the manuscript should be published. p. 5: " The second chromosome that we generated through recombination did not demonstrate decreased anti-Fas2 immunoreactivity or the presence of popped-out cells (Figure 2A,B)..." The latter finding is surprising, as the authors previously showed that the Nrg(14) mutation leads to an increase in the number of popped out cells (Cammarota et al. 2020). They discuss this issue later in the text, but the reason for this discrepancy remains unclear. In the same context, p. 9: " Consistent with this, we find that E(Fas2)mut does not increase the number of popped-out cells in Nrg knockdown tissue (Figure 4B)." But Fig. 4B shows that Nrg knockdown increases the number of popped out cells in E(Fas2) mutant clones. Assuming that Nrg14 is a true null allele, this result would suggest that the effect of Nrg knockdown on the frequency of popped out cells is an RNAi artifact (off-target effect)? The authors should comment on this issue.

Fig. 3F: The Nrg(167) band in the Fas2(EB112) Mannheim lane is stronger than in the control (w1118), suggesting that Nrg(167) expression is upregulated when Fas2 levels are reduced. Please comment.

The authors refer to the enhancer of Fas2 mutation interchangeably as e(Fas2) and E(Fas2). As I understand, the mutation is recessive, and should therefore be referred to as e(Fas2).

p. 4: "Both Fas2EB112 (Grenningloh, Rehm, and Goodman 1991) and Fas2G0336 are thought to be protein null (Bergstralh, Lovegrove, and St Johnston 2015)." The authors should explain why these mutations are "thought to be protein null". They show that Nrg immunoreactivity is lost in Nrg(14) mutants, and likewise for Fas2. If both anti-Fas2 (1D4) and anti-Nrg antisera detect all isoforms of the respective proteins, the authors should state this clearly and modify their rather vague statement on p. 4 ("thought to be protein null").

Fig. 4C: Please add labels to indicate the gene locus (Fas2, Nrg) analyzed in each panel.

Fig. 4D: The chromosomes shown are from heterozygous flies carrying the respective mutation in trans to the w1118 X-chromosome. Correct genotypes should be indicated.

For the genome sequencing, what was the exact genotype of the flies that were sequenced? Hemizygous (lethal) embryos or heterozygotes? If DNA from heterozygotes was analyzed, how were short reads assigned to one of the parental (mutation-bearing or wild-type) chromosomes?

p. 8/9: "Figure X".

Figure legends: scale bars are in µm, not µM.

Referees cross-commenting

I agree that the results are important for a specialty audience concerned with the specific mutant strains described here.

Significance

Although the manuscript does not report a conceptual advance, the findings are very important for a significant part of the Drosophila community, particularly those studying Fas2 and Nrg. These proteins are involved in development of the nervous system, in synapse formation, as well as in epithelial morphogenesis and barrier formation. The Fas2(EB112) mutant has been widely used in at least 37 publications (dating back to 1991), several of which will need to be revisited in the light of the new findings reported here. This reviewer is a cell and developmental biologist with expertise in Drosophila genetics.

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Reply to the reviewers

We would like to sincerely thank both reviewers for taking the time to examine our work, for the cogent points they have raised, and their constructive attitude aimed at improving our manuscript.

Reviewer #1

• Single-cell RNAseq (Fig. 1B) and in situ (Fig. 3D) results both indicate that SNHG7 is broadly expressed in multiple epidermal layers but more enriched in the spinous layer. Although most assays, such as colony formation and Ki67 staining, did not specifically examine the role of SNHG7 in the spinous layer, the raft culture experiment seemed to indicate specific reduction of the spinous layer (Fig. 3H), which was more prominent than basal defects. The authors should examine the defects more carefully in the raft culture system by using basal, spinous and granular markers. It is possible that SNHG7 functions to maintain limited cell proliferation while restrict premature differentiation. In addition, they should perform serial passage experiments to distinguish whether overexpression of SNGH7 can indeed confer self-renewal in long-term experiments.*

We have included staining of a range of epidermal markers in the raft cultures (ITGB1, K14, K10 and IVL) in the revised manuscript (Fig. S6B). We do not observe major changes in the distribution of any of the differentiation markers.

In terms of serial passage, we have cultured SNHG7-overexpressing or control cells for multiple passages until their growth capacity was exhausted. The SNHG7-overexpressing cells grew for approximately seven more passages than the control cells. We have added this information to the revised manuscript (Fig. S6L).

• The main proposed mechanism is the sequestration of miR34 by SNHG7. While miR34 is well known for its function in inhibiting cell proliferation, the ability of coding or noncoding RNA to sequestrate miRNAs is highly dependent on the stability and copy number of these RNAs. Since they have single-cell data with UMI information, they should estimate the copy number of SNHG7 in epithelial cell populations, and this could provide a range for the "buffering" capacity of SNHG7. They should also examine, ideally by in situ hybridization, the expression patterns of miR34 in human vs mouse skin. While miR34 expression can be induced by p53 activation, it is possible that its expression varies in different species. It'll be interesting to determine whether the lack of miR34 expression in mouse keratinocyte or mouse skin could explain the insensitivity of mouse keratinocytes to SNHG7. Finally, to further demonstrate the competition between SNHG7 and miR34 targets, they can use a heterologous luciferase reporter system with a canonical miR34 targeting site in the 3'UTR and quantify luciferase activities with or without SNHG7 (or SNHG7 mut34 variant). This assay could quantify the impact of SNHG7 on individual miR34 targets.*

We will include the analysis of the scRNAseq data to estimate the copy number of SNHG7 in the epidermal populations.

We will also perform in situ hybridization staining for miR-34 in human and mouse epidermis as well as mouse keratinocytes.

Finally, we will carry out the luciferase reporter experiments.

Reviewer #2

Major comments:

1) The premise of the study relies on the observation that SNHGs have low levels of sequence conservation. Indeed the authors aim to prove that biological functions can be identified even in the absence of evolutionary conservation. However, the extent of evolutionary conservation strongly depends on the phylogenetic scale at which it is analyzed. Here, the authors evaluate sequence conservation using PhastCons and PhyloP scores determined using alignments of human and 99 other vertebrate species. These scores reflect the extent of long-term sequence conservation. At this scale, only a small percentage of the human genome can be considered to be "conserved". It is thus not surprising that SNHG and other lncRNAs are not conserved at this scale, even if they carry some biological functions in the human genome. Here, it would be useful to redo the sequence conservation analyses using PhastCons and PhyloP scores computed on less distant species. Pre-computed scores exist for alignments containing human and other mammalian species, mainly primates (UCSC genome browser). It would also be good to provide comparisons of sequence conservation levels on the snoRNA genes and on the non-snoRNA parts of SNHGs. In addition to protein-coding genes, pseudogenes and lncRNAs, it would be good to add a perfectly neutral control for the sequence conservation in Figure 1C - for example, flanking intergenic regions for SNHGs. It might also be a good idea to analyze the GC content of SNHGs compared to other lncRNAs, since GC content can be correlated with sequence conservation levels, in particular in noncoding regions.

Importantly, the SNHG selected for detailed investigation (SNHG7) appears to be more conserved than the bulk of human lncRNAs, given that it is found in another primate and in mouse. It would be interesting to analyze in details what sequence features of this lncRNAs are conserved among species - for example, are the SNHG7 splice sites and promoter regions conserved? Are the snoRNA genes always located in the introns?

The reviewer raises very good points. We have added the conservation data of snoRNA genes (all or SNHG-resident, both significantly more conserved than SNHGs or lncRNA), and a “true neutral” control (we used the introns of 10,000 randomly sampled genes) to our PhastCons analysis (Fig.1C). We also added a conservation analysis of the promoters (defined as the 500 bp upstream of the transcription start site) of coding genes, pseudogenes, lncRNA and SNHGs (Fig, S1B). We have now performed all our conservation analyses using both PhastCons scores generated from the 100-vertebrate alignment and PhastCons scores generated from the 30-mammals (28 primate) alignment (Fig. S1E-G). We do not detect any marked difference between the two alignment sets. We have also added a comparison of the GC content in lncRNA, SNHGs, coding genes and introns (Fig.S1C).

Due to the nature of the PhyloP scores, the 30-mammal PhyloP track (phyloP30) would be unsuitable to detect additional conservation in the primate lineage using the thresholding analysis we employed in Fig. 1E. The PhyloP track gives base-wise p-values for conservation (positive values) or accelerated evolution (negative values). Using alignments of genomes that are overall more similar to each other (as in the 30-mammal alignment set) makes it more difficult to distinguish between conserved and neutrally evolving regions, because even segments that are not under constraint will look relatively similar due to the evolutionary proximity of the species in the set. For the same reason this alignment set is quite sensitive to accelerated evolution, as it contains many relatively similar genomes it the alignment.

This causes the PhyloP30 scores to be very asymmetrical around zero: the conservation (positive) scores never reach 2 (p-value of 0.01) in the whole track (not even coding regions of very well-conserved genes), while acceleration scores can reach very significant values, down to -20. Conversely, the PhyloP100 track (used in Fig.1E) is quite symmetrical around 0 and is thus better suited for the purposes of the analysis in Fig.1E, which are to detect both conserved and accelerated portions of SNHGs. We have however also inspected the PhyloP30 track manually and do not observe any clear evidence of presence of additional conserved elements in SNHG7. We have added all conservation tracks for SNHG7 to Fig. 3A.

While lncRNA orthologs can be identified by using a combination of sequence conservation, conserved synteny with surrounding genes and in some cases conserved gene structure, SNHG orthologs can additionally be identified by the embedded (conserved) intronic snoRNA sequence, which makes them easier to find even when the transcript sequence bears no similarity across species. The mouse SNHG7 sequence, for example, does not match with human SNHG7 even using the least stringent BLAST parameters. The monkey sequence is similar enough to match with the human in the 3’ of the gene, but the intron-exon structure of the 5’ is completely different. We agree with the reviewer’s assessment, however, when it comes to identification of SNHG orthologs in more evolutionary distant species, closer to the root of the vertebrate clade.

Regarding splice sites, they are often conserved among lncRNA in general (gene structure conservation occurs more frequently than sequence conservation, see Ulitsky, Nat Rev Genet, 2016). In the case of SNHG7 the structure of the gene appears conserved in the mouse (though this annotation has likely not been fully confirmed experimentally), and in the monkey based on genome alignments. However, our RACE experiments show that the 5’ end of SNHG7 in the monkey has a radically different splicing pattern when compared to human, so it is difficult to assess splicing conservation in the absence of full isoform characterization.

2) I am not perfectly convinced by the enrichment of miRNA target genes among the genes that are downregulated upon SNHG knockdown. The methods do not clearly explain how this enrichment is calculated. What is the background used for this enrichment analysis? In Figure 5C, we see that the genes predicted to be targeted by the top 10 microRNAs tend to have negative fold changes in the differential expression analysis (downregulation following knockdown). However, from Figure 5A it seems that the great majority of significantly differentially expressed (DE) genes have negative fold changes. How do the miRNA target genes differ from all other DE genes? What proportions of all predicted miRNA target genes (expressed in keratinocytes) are DE following knockdown, and how does this compare with the target genes of other miRNAs?

We have added a description of the statistical test used by MIENTURNET for the enrichment analysis to the methods section. More details can be found in the original publication. The significance of the enrichment is calculated by performing a hypergeometric test using as background the total number of miRNA-target interactions in the database and the total interactions the individual miRNA being tested engages in.

Figure 5C only includes the genes we used in our enrichment analysis (i.e. the significantly downregulated genes, not all DE genes) and it’s meant to show the extent of downregulation exhibited by the targets of the most significantly enriched miRNAs within this group of genes.

The reviewer is correct in pointing out that the imbalance between downregulated and upregulated genes (which we now further highlight in the plots in Fig. 5A-B) will tend to skew any group of genes towards having a relatively large number of downregulated genes. However, we found this bias to be particularly strong in the case of our candidate miRNAs. We now show this in volcano plots for validated targets of the candidate miRNAs and a control miRNA (Fig. S8E). In a similar way, when looking at the cumulative distributions of the fold changes of all predicted targets for a certain miRNA and comparing it to the fold change cumulative distribution of all other genes, our candidate miRNAs displayed a more pronounced shift towards downregulation than the control miR-21-5p (which we now added in Fig. S8F).

3) If keratinocyte RNA-seq data is available for other species (for example mouse), it would be interesting to test whether the high expression levels of SNHG7 and the other analyzed SNHGs are also conserved in the other species.

We will include the RNA-seq data, if available.

Minor comments:

1) The AD (atopic dermatitis) abbreviation should be explained the first time it is mentioned in the text.

We thank the reviewer for pointing out the missing abbreviation, we have now added it.

2) More details are needed regarding the MIENTURNET analyses in the methods and in the main text

We have added more details about the statistics involved to the methods (see above).

*3) Figure 5C, it is not clear how to interpret the color code for the boxplot. Does this represent the median or mean FDR of the target genes? Are only genes with FDRThe genes included in the enrichment analysis are all downregulated genes with an adjusted p-value (or FDR adjustment after the Wald test) adj”. The color scale in Fig 5C reports the significance of the enrichment for targets of the single miRNAs within the significantly downregulated genes list (FDR adjustment after the hypergeometric test), not the significance of the downregulation itself. FDR values are also used for all other enrichment analyses (GO terms, REACTOME Pathways). We apologise to the reviewer for the confusion, we have now modified the text and figures to make this clearer.

4) Figure 6D, I am not sure how to the D panel. Do the gray rectangles represent the exonic length of the SNHGs? Do the dots correspond to the positions of the miRNA target sites? Here, a more quantitative comparison with the extent of sequence conservation of miRNA binding sites in SNHGs, other lncRNAs and in protein-coding genes would be perhaps better suited.

The grey rectangles in Fig. 6D represent the total exonic length of the SNHGs (basically all exons are “stitched together” head to tail irrespective of the actual isoforms) and the dots represent the positions of the miRNA binding sites within this “maximum exonic coverage”. Since not all individual isoforms are analysed it is possible that some additional miRNA sites can be created at alternatively spliced junctions, however we would estimate the number of such sites to be small. We have added this caveat to the methods section.

The degree of conservation that is estimated by TargetScan to underlie a functional MRE in coding genes is taken into account in this analysis, as sites within SNHGs that pass this threshold are highlighted with yellow borders in the figure. We have now added a plot of the distribution of Branch length scores for MREs in SNHGs and the distribution of Branch length scores for MREs in a random sample of 250 Coding genes UTRs (Fig. S9E). A similar comparison for lncRNA is more challenging as the data is not readily available and is likely to be confounded by the nuclear localisation of a majority of lncRNA species.

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Referee #2

Evidence, reproducibility and clarity

Summary

The manuscript submitted by M. Vietri Rudan and co-authors presents a functional analysis of a specific class of long non-coding RNA transcripts, namely the small nucleolar RNA host genes (SNHGs). These genes are defined by the fact that snoRNA molecules are embedded within their loci, often in the SNHGs introns. The rationale presented by the authors for studying this specific class of lncRNA genes is the fact that they display very low levels of evolutionary sequence conservation (even compared to the generally low conserved lncRNA transcripts) and that they are expressed at remarkably high levels (contrary to most lncRNA genes, which are very weakly expressed). The overarching goal of this study thus appears to be determining whether functional transcripts can exist in the absence of evolutionary conservation.

The authors study SNHGs in the human keratinocytes model system. They analyze the expression levels of SNHGs in skin affected by atopic dermatitis and psoriasis, compared to normal skin. They identify several SNHGs that are differentially expressed between diseased and normal skin, and which are also detected at strong expression levels in single cell RNA-seq assays of human keratinocytes. The authors use knockdown assays to investigate the potential roles of these SNHGs in keratinocytes and show that the knockdown of each of 5 selected SNHGs results in a loss of clonogenicity.

The last part of the manuscript focuses on the functional characterization of SNHG7, chosen because it is dysregulated in both atopic dermatitis and psoriasis and because its knockdown strongly affects clonogenicity. Additional assays showed that SNHG7 knockdown results in a reduced rate of proliferation and an increase in the fraction of differentiating cells. To ensure that the effects of the knockdown are not simply due to the absence of the snoRNA molecules embedded in the SNHG7 locus, the authors overexpressed the spliced form of SNHG7 (which lacks the snoRNA genes), successfully rescuing the cellular phenotype. They also verified that the knockdown does not affect the abundance of the corresponding snoRNA molecules.

To propose a potential mechanism for the involvement of SNHG7 in keratinocyte proliferation, the authors investigated its capacity to act as a miRNA "decoy". They searched for an enrichment of miRNA binding sites among the genes that are downregulated following SNHG7. They identified several miRNAs which are predicted to target SNHG7 as well as (a substantial fraction of) the genes that are downregulated following SNHG7 knockdown. The transfection of two of these miRNAs (miR-193-3p and miR-34-5p) has a negative effect on keratinocyte proliferation, supporting the authors's hypothesis that SNHG7 may act via "sponging" these miRNAs, thereby positively contributing to the control of the expression of the other miRNA target genes. Consistent with this hypothesis, the authors show that overexpression of a SNHG7 mutant sequence that lacks the miRNA binding sites is not able to rescue the knockdown phenotype.

However, this hypothesis is not supported (or at leat not further reinforced) by the evolutionary analysis performed by the authors. They were able to identify homologues for SNHG7 in another primate species (night monkey) and in the mouse. Transfection of the human SNHG7 sequence was able to increase clonogenicity in night monkey cells, but not in mouse cells. Given that miR-34 is also present in mouse and was previously shown to affect keratinocyte proliferation, it is not clear why the human SNHG7 sequence is not able to act as a miRNA sponge in this species. Likewise, only a slight effect on clonogenicity is observed upon SNHG7 transfection in night monkey. The authors conclude (correctly, in my view) that further investigations are needed to confirm the potential functions of SNHG7.

Overall, I find that this study is interesting and carefully conducted. Nevertheless, I have several comments that I hope can improve this manuscript.

Major comments:

1. The premise of the study relies on the observation that SNHGs have low levels of sequence conservation. Indeed the authors aim to prove that biological functions can be identified even in the absence of evolutionary conservation. However, the extent of evolutionary conservation strongly depends on the phylogenetic scale at which it is analyzed. Here, the authors evaluate sequence conservation using PhastCons and PhyloP scores determined using alignments of human and 99 other vertebrate species. These scores reflect the extent of long-term sequence conservation. At this scale, only a small percentage of the human genome can be considered to be "conserved". It is thus not surprising that SNHG and other lncRNAs are not conserved at this scale, even if they carry some biological functions in the human genome. Here, it would be useful to redo the sequence conservation analyses using PhastCons and PhyloP scores computed on less distant species. Pre-computed scores exist for alignments containing human and other mammalian species, mainly primates (UCSC genome browser). It would also be good to provide comparisons of sequence conservation levels on the snoRNA genes and on the non-snoRNA parts of SNHGs. In addition to protein-coding genes, pseudogenes and lncRNAs, it would be good to add a perfectly neutral control for the sequence conservation in Figure 1C - for example, flanking intergenic regions for SNHGs. It might also be a good idea to analyze the GC content of SNHGs compared to other lncRNAs, since GC content can be correlated with sequence conservation levels, in particular in noncoding regions.

Importantly, the SNHG selected for detailed investigation (SNHG7) appears to be more conserved than the bulk of human lncRNAs, given that it is found in another primate and in mouse. It would be interesting to analyze in details what sequence features of this lncRNAs are conserved among species - for example, are the SNHG7 splice sites and promoter regions conserved? Are the snoRNA genes always located in the introns? 2. I am not perfectly convinced by the enrichment of miRNA target genes among the genes that are downregulated upon SNHG knockdown. The methods do not clearly explain how this enrichment is calculated. What is the background used for this enrichment analysis? In Figure 5C, we see that the genes predicted to be targeted by the top 10 microRNAs tend to have negative fold changes in the differential expression analysis (downregulation following knockdown). However, from Figure 5A it seems that the great majority of significantly differentially expressed (DE) genes have negative fold changes. How do the miRNA target genes differ from all other DE genes? What proportions of all predicted miRNA target genes (expressed in keratinocytes) are DE following knockdown, and how does this compare with the target genes of other miRNAs? 3. If keratinocyte RNA-seq data is available for other species (for example mouse), it would be interesting to test whether the high expression levels of SNHG7 and the other analyzed SNHGs are also conserved in the other species.

Minor comments:

1. The AD (atopic dermatitis) abbreviation should be explained the first time it is mentioned in the text.
2. More details are needed regarding the MIENTURNET analyses in the methods and in the main text
3. Figure 5C, it is not clear how to interpret the color code for the boxplot. Does this represent the median or mean FDR of the target genes? Are only genes with FDR<5% included in this analysis?
4. Figure 6D, I am not sure how to the D panel. Do the gray rectangles represent the exonic length of the SNHGs? Do the dots correspond to the positions of the miRNA target sites? Here, a more quantitative comparison with the extent of sequence conservation of miRNA binding sites in SNHGs, other lncRNAs and in protein-coding genes would be perhaps better suited.

Significance

Overall, this study is highly relevant in the field of lncRNA functionality and evolution. It presents evidence for a potential involvement in the regulation of cell proliferation for SNHGs, a role that appears to be independent of the snoRNAs produced by these loci. This study reinforces the current body of work suggesting that lncRNAs and other noncoding transcripts can sometimes function as miRNA "decoy" targets. This study will be of interest for a specialized audience, oriented towards understanding lncRNA biological functions.

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Referee #1

Evidence, reproducibility and clarity

Vietri Rudan and colleagues present an interesting study to examine the function and mechanism of small nucleolar RNA Host Gene 7 (SNHG7) in human keratinocytes. The key findings are that a widely expressed SNHG7, a long noncoding RNA hosting two snoRNAs in the introns, promotes keratinocyte proliferation and inhibits differentiation likely by sequestrating miR34a from its targets. The experiments are generally well-executed with proper controls. Notably, they leveraged human, night monkey and mouse keratinocytes to reveal primate specific functions of SNHG7 in a miR34 dependent manner. I have a few comments and suggestions that should be addressed to further strengthen the study.

1. Single-cell RNAseq (Fig. 1B) and in situ (Fig. 3D) results both indicate that SNHG7 is broadly expressed in multiple epidermal layers but more enriched in the spinous layer. Although most assays, such as colony formation and Ki67 staining, did not specifically examine the role of SNHG7 in the spinous layer, the raft culture experiment seemed to indicate specific reduction of the spinous layer (Fig. 3H), which was more prominent than basal defects. The authors should examine the defects more carefully in the raft culture system by using basal, spinous and granular markers. It is possible that SNHG7 functions to maintain limited cell proliferation while restrict premature differentiation. In addition, they should perform serial passage experiments to distinguish whether overexpression of SNGH7 can indeed confer self-renewal in long-term experiments. Based on these results, they may need to refine their hypothesis/conclusion whether SNHG7 functions primarily on stem cell self-renewal or transiently maintain proliferation in transitioning cells.
2. The main proposed mechanism is the sequestration of miR34 by SNHG7. While miR34 is well known for its function in inhibiting cell proliferation, the ability of coding or noncoding RNA to sequestrate miRNAs is highly dependent on the stability and copy number of these RNAs. Since they have single-cell data with UMI information, they should estimate the copy number of SNHG7 in epithelial cell populations, and this could provide a range for the "buffering" capacity of SNHG7. They should also examine, ideally by in situ hybridization, the expression patterns of miR34 in human vs mouse skin. While miR34 expression can be induced by p53 activation, it is possible that its expression varies in different species. It'll be interesting to determine whether the lack of miR34 expression in mouse keratinocyte or mouse skin could explain the insensitivity of mouse keratinocytes to SNHG7. Finally, to further demonstrate the competition between SNHG7 and miR34 targets, they can use a heterologous luciferase reporter system with a canonical miR34 targeting site in the 3'UTR and quantify luciferase activities with or without SNHG7 (or SNHG7 mut34 variant). This assay could quantify the impact of SNHG7 on individual miR34 targets.

Significance

This study reveals a potential function and mechanism of primate specific noncoding RNA for its role in modulating gene expression and cellular functions in the skin. It provides a new paradigm for identifying molecular functions of poorly conserved RNAs.

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Reply to the reviewers

Manuscript number: #RC-2023-02281

Corresponding author(s): Maurizio Molinari

Point-by-point description of the revisions

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

• *

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

In this manuscript from Fasana et al., the authors present data that investigates potential compensatory degradation pathways for misfolded glycoproteins in the ER - postulating that the ER-to-lysosome associated degradation (ERLAD) pathway becomes employed in the absence of a path for substrates to reach the ER-associated degradation (ERAD) mechanism. Using the classic ERAD substrate alpha1-antitrypsin NHK variant (NHK), the authors first demonstrate that pharmacologically preventing access of NHK to ERAD either with KIF (early) or PS-341 (late) elevates the number of LAMP-1 positive endolysosomes also immunoreactive for NHK (via HA), similar to what is observed for the ATZ variant that forms polymers in the ER (Fig 2). The authors next use shRNAs that silence essential ERAD factors (EDEM1, OS-9) involved in glycan recognition to demonstrate comparable enrichment of NHK in endolysosomes through genetic disruption (Fig 3). Next, the authors employ FAM134B-deficient MEFs to demonstrate the requirement for this ER-phagy receptor when ERAD is unavailable (Fig 4). Reconstituting FAM134B-/- MEFs treated with KIF/PS-341 + Baf, with a full length FAM134B rescue plasmid restores endolysosomal accumulation of NHK while a FAM134B-∆LIR does not, providing supporting evidence for substrate rerouting to ERLAD. Finally, the authors use knockouts of Atg7 and Atg13 to demonstrate dependence on LC3 lipidation and independence from macro-ERphagy (Fig 6), that points towards a pathway that is like that used to remove ATZ polymers. From these data, the authors conclude that ERLAD is increasingly engaged for substrate degradation when ERAD is impaired.

MAJOR COMMENTS 1. All assays rely on quantification of the NHK-HA substrates by microscopy. Would it be possible for the authors to also include biochemical analysis of NHK - potentially including data assessing its changing abundance and glycosylation state?

To consider this, and other comments, the new submission includes biochemical data (pulse-chase analyses) on NHK (new panels A-D in Fig. 2) and on BACE457delta, an additional ERAD substrate (new Fig. 6). Please also refer to Comment 3.

In Figure 3D, the knockdown of OS-9.1/2 is modest compared to that of EDEM1 (Fig 3A). Moreover, there is only data from single shRNAs presented. Could the authors please at least include another shRNA to confirm and demonstrate whether the targeting to ERLAD is accordingly scaled to loss of access to ERAD (based on the degree of OS-9 or EDEM1 remaining)?

__The reviewer is right. The phenotype (i.e., lysosomal delivery of NHK, Figs. 3B, 3C) is quite modest upon EDEM1 silencing. However, one has to consider that in contrast to OS9 lectins, EDEM1 is an enzyme, and residual protein may partially facilitate NHK de-mannosylation and access to the ERAD pathways and therefore reduce the ERLAD contribution for NHK clearance in these cells. Moreover, cells also express EDEM2 and 3 that may partially compensate the loss of EDEM1. __

While degradation is implied, it is not specifically demonstrated at any point in the manuscript. Perhaps the authors might include some demonstration of NHK stabilization in one of the figures via a translational shutoff or pulse-chase assay.

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__In the new submission, we show biochemical analyses (pulse-chase) that reveal the decay of radiolabeled NHK (Fig. 2A, lanes 1-3) and BACE457delta (Fig. 6A, lanes 1-3), the inhibition by PS341 (lanes 4, 5) and by KIF (lanes 8, 9), and the intervention of lysosomal enzymes when ERAD is inhibited (lanes 6, 7 and 10, 11). Moreover, we confirm that the protein delivered to the endolysosome is eventually degraded by performing a Bafilomycin washout experiment (new Fig. 2J-2O). __

10-30% of NHK-HA positive endolysosomes are detected even with Baf alone (e.g. Fig 2E)? Does this mean that Baf impairs ERAD to some extent since or is it evidence for continuous ERLAD involvement when ERAD is intact? If so, how much is its contribution?

Pulse-chase analyses (new Fig. 2D) and published data show that BafA1 or chloroquine do not inhibit clearance of the ERAD substrates NHK and BACE457delta (e.g., Liu et al 1999, Molinari et al 2002, references in the manuscript). A basal level of endolysosomal delivery between the 20 and 30% as quantified with LysoQuant is observed in all experiments (Figs. 2I, 2O, 3C, 3F, 4C, 4K, 5H, 6G, 6O), which have been performed in 3 different cell lines (3T3, HEK293, MEF). We measure similar basal levels also when ER-phagy is monitored on quantification of lysosomal delivery of endogenous ER marker proteins (e.g., CNX), possibly to be ascribed to constitutive ER phagy that controls physiologic ER turnover.

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An accounting of how much ERLAD is contributing to NHK degradation with or without ERAD impairment is not really present.. Effectively, how much degradation capacity is ERLAD making up? These would be interesting data to include if possible as they would speak to the "division of labour" for ER substrate degradation its potentially dynamic nature.

The biochemical analyses show the contribution of ERLAD on NHK (new Figs 2B, 2C, grey zones) and BACE457delta (new Figs. 6B,C, grey zones) clearance, when ERAD is dysfunctional.

MINOR COMMENTS 1. In Figure 4, an increase is observed for the rescue of FAM134B-/-MEFs with WT FAM134B that is 50% greater that of WT MEFs, suggesting that its availability might be rate limiting. Could the authors compare the relative levels of FAM134B for the WT and KO-rescue MEFs to address this possibility?

__The referee is right in assuming that FAM134B, expressed at low levels in these cells, is limiting. We now show the levels of endogenous FAM134B and of recombinant FAM134B in WB (new Fig. 4A). __

In Figures 1 and 6, the terms siOS9 and siEDEM1 are used but Figure 3 shows data from shRNAs and not siRNAs.

We apologize for the mistake. We have corrected this in the new Figures 1 and 7.

Samples from Figure 3 treated with Baf but this is not indicated in the figure or figure legend.

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We have corrected this, thank you.

VCP/p97 inhibitors typically stabilize ERAD glycoprotein substrates better than proteasome inhibitors do. Is the same degree of endolysosomal targeting present ?

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__For the convenience of the reviewer (we did not put these data in the new manuscript). In our experiments, the p97 inhibitor DBeQ is less efficient in deviating NHK to the endolysosomal degradative compartments, if compared with KIF (see below). At higher doses, DBeQ also inhibits other AAA-ATPases (e.g., VPS4, which plays a role in certain types of autophagy). This, or other cross-reactivities of DBeQ could explain the moderate capacity to activate ERLAD pathways as a response of ERAD inhibition, if compared with the phenotypes observed when ERAD is inhibited with KIF or PS341. __

Reviewer #1 (Significance (Required)):

Deconvolution of the different pathways taken by misfolded proteins to escape the ER is of great interest not only to the ER community but also represents consequences to consider for those interested in therapeutics involving UPS inhibition. While concise, this manuscript does a good job of trying to demonstrate the principal of substrate rerouting and the prioritisation of degradation pathways. Overall, the manuscript is well written, the experiments presented are performed to a sufficient standard, the data are lean but of good quality, and the appropriate statistical analyses have mostly been included where necessary and are described. The Methods and Materials is brief but describes the experiments that have been performed. The manuscript is brief in its results and would obviously benefit from additional complementary assays that would strengthen and broaden the authors arguments for rerouting. But too their credit, the authors do not grossly overstate their findings and merely present the culmination of a set of experiments to answer a single question - what happens to a misfolded glycoprotein substrate when ERAD is impaired. This is a key question with broad implications.

While their limited data clearly demonstrates an acquired dependence on ERLAD, one can't help but wonder how broadly these findings hold true, as only a single glycoprotein substrate example is used.

We have now added a complete set of experiments (imaging + biochemical to monitor clearance of the model polypeptides by pulse-chase analyses) performed with a second ERAD substrate (BACE457delta, Fig. 6). These data fully recapitulate the results obtained with NHK.

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Moreover, it is not clear what percentage ERLAD contributes to overall NHK degradation (with or without ERAD) as the total NHK amount remaining is not assessed or measured.

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Pulse-chase analyses (new Fig. 2D) and published data (e.g., Liu et al 1999, Molinari et al 2002, references in the manuscript) show that BafA1 or chloroquine do not inhibit clearance of the ERAD substrates NHK and BACE457delta. The biochemical analyses now show the contribution of ERLAD on NHK (new Figs 2B, 2C, grey zones) and BACE457delta (new Figs. 6B,C, grey zones) clearance, when ERAD is dysfunctional.

Nevertheless, the manuscript is an advancement of understanding of the fate of substrates unable to access ERAD and raises many future questions of interdependency between the ERAD and ERLAD pathways. The data just need a bit of shoring up.

Expertise - ERAD, UPS, protein quality control

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

The endoplasmic reticulum (ER) is a crucial site for protein synthesis and folding within the cell, and strict protein quality control is essential for maintaining ER homeostasis. In this context, ER-associated degradation (ERAD) and the unfolded protein response (UPR) play pivotal roles. Recent researches have highlighted the significance of ER-phagy in protein quality control. In this manuscript, the authors demonstrate the role of FAM134B in degrading misfolded proteins such as ATZ through the ER-phagy pathway when the ERAD pathway is obstructed. This work partially addresses a prominent issue in the field, unveiling the interconnections between different regulatory pathways in maintaining ER homeostasis.

Major issues: 1: In a multitude of experiments, the authors employed Bafilomycin A1 (BafA1) to block the fusion between autophagosomes and lysosomes, attempting to demonstrate that the clearance of misfolded proteins mediated by FAM134B is independent of autolysosomes. However, in Figure 4, the lack of rescue of FAM134B knockout by overexpressing FAM134B△LIR suggests a dependence on the interaction between FAM134B and LC3. The conclusions drawn before and after appear contradictory.

We apologize if our explanations were unclear. We have now modified the text and performed new experiments to clarify these issues.

__The inhibitor of the V-ATPase BafA1 is used here to inhibit the activity of lysosomal hydrolases and to accumulate undegraded material in the LAMP1-endolysosomes (note that these endolysosomes also display RAB7 at their limiting membrane) (Fregno et al 2018, Forrester et al 2019, Fregno et al 2021, …). __

__In Figs. 2A-2D, we now monitor the lack of NHK stabilization by cell exposure to BafA1 (Fig. 2D), which correlates with lack of accumulation of NHK in the LAMP1-positive compartment (e.g., Fig. 2F, 2J, and quantifications in 2I and 2O). The biochemical data also show that BafA1 stabilizes NHK in cells where ERAD has been inactivated with PS341 or KIF (Fig. 2A, lanes 6, 7, 10, 11 and grey zones in Figs. 2B and 2C), which correlates with accumulation of NHK in LAMP1-positive organelles (Figs. 2G, 2H, 2I, 2K, 2M, 2O). __

__In Figs. 2J-2O, we have now added panels showing that NHK clearance from the LAMP1-positive endolysosome lumen is restored upon BafA1 washout. __

Importantly, the involvement of the lipidation machinery, of the ER-phagy receptor FAM134B and of the LC3-binding function of FAM134B (the LIR), does not necessarily imply the involvement of autophagosomes in the process under investigation, as the comment by the referee seems to suggest. For example, both the clearance from the ER of ATZ polymers and of mutant forms of procollagen rely on the LC3 lipidation machinery and on the LC3-binding function of FAM134B, but ERLAD of ATZ polymers does not rely on autophagosomes intervention (new Fig. 1B, arrow 1 and Fregno et al 2018), whereas ERLAD of procollagen relies on intervention of autophagosomes (new Fig. 1B, arrow 2 and Forrester et al 2019).

2: Some Western blot data are insufficient to substantiate the author's conclusions. For instance, in Figure 5D, the ATG7 KO line is inadequately supported

The WB show____s the absence of ATG7 in the ATG7-KO cells (a well-established cell line generated in the lab of Masaaki Komatsu (____Komatsu M, et al. J Cell Biol 169: 425-434_) and used in many_ laboratories, including our lab in Fumagalli et al 2016, Fregno et al 2018, Fregno et al 2021, Loi et al 2019, Kucinska et al 2023). We agree with the reviewer that the anti-Atg7 shows cross-reactions. We have now added a WB showing the lack of LC3 lipidation in the Atg7-KO cells exposed to nutrient deprivation (new Fig. 5D).

3: The author employed Lamp1 antibody for lysosomal staining in cells and observed a significant abundance of lysosomes in some experiments, as depicted in Figure 2C, 2D, 4I, etc. Is the phenomenon of lysosomes extensively filling the entire cell a common occurrence? Is it indicative of a normal physiological state?

There may be variations depending on the cell type used for the experiments. In the new version of the manuscript, we now present imaging data for 3 cell lines (NIH 3T3 with stable expression of NHK and ATZ (Figs. 2E-2H), MEF (Figs. 2J-2N, 4, 5, 6) and HEK293 with transient expression of ERAD clients (Figs. 3).

Minor issues： 1: Some immunofluorescence experimental data are unclear. Please request the authors to replace these with more distinct images, as seen in Figure 3B and 3E.

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We hope that the quality of the new images will be considered sufficient for publication.

2: Some expressions appear to be questionable. For instance, the necessity of utilizing endolysosomes requires clarification.

For the use of endolysosomes (lysosome would be incorrect in our opinion to indicate these LAMP1/RAB7-positive degradative organelles), we now refer to the papers by Bright et al ____Endolysosomes Are the Principal Intracellular Sites of Acid Hydrolase Activity_ Curr Biol 2016, and the original definition by Huotari and Helenius _Endosome maturation EMBO J 2011 (Introduction, page 2).

3: Some writing lacks precision, such as referring to FAM134B as FAM134.

__Corrected, thank you____ __ Reviewer #2 (Significance (Required)):

o General assessment: o Advance: provide an meaningful evidence that how two degradative pathways are coordinated in maintaining ER homeostasis. o Audience: cell biologist o Reviewer's expertise: autophagy, vesicle trafficking, organelle biolgy Reviewer #3 (Evidence, reproducibility and clarity (Required)):

In their study, Fasana and colleagues investigate protein quality control in the ER. Specifically, they test whether folding-incompetent proteins that are normally cleared by ER-associated degradation (ERAD) can also be targeted for degradation by direct vesicular transport from the ER to lysosomes in case ERAD is blocked. They show that blocking ERAD pharamacologically or genetically indeed leads to re-rerouting of an ERAD model substrate (the NHK variant of alpha-antitrypsin) to lysosomes and that this pathway requires the reticulon-like protein FAM134B, the ability of FAM134B to interact with the ubiquitin-like protein LC3 and the machinery for LC3 lipidation.

The paper is, for the most part, easy to follow. There are, however, a few minor issues and I think the authors could do more to connect their work with similar studies in the literature. Accordingly, I have some general and specific suggestions to make the manuscript more accessible for the reader.

General suggestions

1. To avoid confusion, it would be helpful to more clearly distinguish between vesicular transport to endolysosomes and autophagy. Previous work by the authors has defined a trafficking pathway from the ER to endolysosomes that appears to rely on conventional vesicle-mediated transport (Fregno et al, EMBO J 2018). This pathway delivers material from the ER lumen to the lumen of endolysosomes, which are both topologically equivalent to the extracellular space. Hence, this pathway is distinct from autophagy, which is the transport of cytoplasmic components to endolysosomes and thus the transport of material from intracellular to extracellular space. This distinction is particularly important as both vesicular ER-to-lysosome transport and autophagy of the ER involve LC3 and FAM134B, which is typically referred to as an ER-phagy receptor. To make this less confusing, it may be helpful to explain that FAM134B appears to be a multifunctional molecule that can function as a receptor for macroautophagy but also in the vesicular transport pathway studied here. In addition, it would be helpful to point out that LC3 appears to also have roles unrelated to autophagosome formation.

The reviewer is referring to the original definition of ERLAD to describe the mechanisms of clearance of ATZ polymers (Fregno et al 2018). The definition of ERLAD has now been expanded and is given, for example, in Klionsky DJ, et al (2021) Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition). Autophagy 17: 1-382 and is explained in detail in our recent review Rudinskiy M, Molinari M (2023) ER-to-lysosome-associated degradation in a nutshell: mammalian, yeast, and plant ER-phagy as induced by misfolded proteins. Febs Letters: 1928-1945.

__Notably, the acronym ERAD for ER-associated degradation has originally been used to describe ____the proteasomal clearance from the ER of misfolded pro-alpha factor in a reconstituted yeast system in McCracken AA, Brodsky JL (1996) Assembly of ER-associated protein degradation in vitro: dependence on cytosol, calnexin, and ATP. The Journal of cell biology 132: 291-298. Only later on, the acronym has been used as an umbrella term that now covers all the pathways that control proteasomal clearance of misfolded proteins from the ER. A short historical excursus is presented in the new introduction to better explain these issues. __

It is well established that LC3 and the LC3 lipidation machinery have functions that go beyond macroautophagy (which involves double membrane autophagosomes). Micro-autophagy (or micro-ER-phagy to remain on the topic of our paper) is an example of autophagic pathway relying on ER-phagy receptor that engage LC3, on the LC3 lipidation machinery, without involving autophagosomes. This is schematically represented in the new Fig. 1B.

Several recent papers that appear relevant to the present study are not mentioned. In particular, Sun et al., Dev Cell 2023 (PMID: 37922908) appears worthy of discussion, as does Gonzalez et al., Nature 2023 (PMID: 37225996).

Thank you. Both papers are not directly linked to our study addressing the intervention of ERLAD pathways when ERAD activity is impaired. In particular the work of Gonzales et al describes post-translational modification of ER-phagy receptors for their activation. The Sun et al paper is not really related to the topic covered in our manuscript, but we cite it as an alternative pathway that removes ATZ from the ER (page 8).

Specific suggestions

1. Abstract: The abstract begins with "About 40% of the eukaryotic cell's proteome is synthesized ... in the ER." Similar statements can be found in many papers and purportedly reflect common knowledge. However, it is unclear where the figure of 'about 40%' comes from. It would be proper to provide a reference and demonstrate that giving such a fairly precise estimate is supported by experimental data. Alternatively, the statement could be modified to avoid being precise than is justified.

No reference is allowed in the abstract. We therefore modified the sentence as suggested by the reviewer.

1. p2: "The ER is site of gene expression in nucleated cells and ... native proteins to be delivered at their site of activity ...". There is something missing at the beginning of this sentence. Also, it should be 'delivered to their site of activity', not 'delivered at'.

Thank you

1. p2: "... by mechanistically distinct ER-phagy pathways collectively defined as ER-to-lysosome-associated degradation ERLAD." This statement suggests that all pathways subsumed under the term ERLAD are ER-phagy pathways, which I believe is misleading (see comment above on the distinction between autophagy and vesicular transport pathway).

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See point 1.

1. p2: "KIF selectively ...". Please spell out KIF and explain what kind of compound it is.

Thank you, we changed to “_The alkaloid kifunensine (KIF) is a cell permeable selective inhibitor of the members of the glycosyl hydrolase 47 family of a____1,2-mannosidases_”____ __ 5. p3: "Notably, ERAD inhibition delays, rather than blocking degradation of ERAD clients ...". Please correct, for example: Notably, ERAD inhibition delays rather than blocks degradation of ERAD clients ...

Thank you

Figures 2 - 5: The number of quantified cells is given but it is not clear if experiments were done once or in biological replicates. Please indicate this in the figure legends.

__N is now given for all panels in the corresponding figure legends.____ __ 7. p4: "To verify if ERAD inactivation ..." sounds odd. Less ambiguous would be 'To test whether' or 'To ask if'.

Thank you

1. p7, beginning of discussion: Please correct "delivered at" to 'delivered to'.

Thank you

Reviewer #3 (Significance (Required)):

This is a concise and convincing manuscript with a clear message. The idea that proteins that cannot be processed by ERAD can be eliminated by other means, for instance by autophagy, is not new. Similarly, the FAM134B- and LC3-dependent pathway for ER-to-lysosome transport has been described by the authors before (Fregno et al, EMBO J 2018). Furthermore, the study exclusively relies on microscopy and does not attempt to tackle new mechanistic questions. Still, this study presents a definite functional advance in our understanding of the interplay of various ER quality control pathways.

The findings presented here will be of interest mainly to molecular cell biologists working on protein quality control and organelle homeostasis. However, given the disease-relevance of misfolded proteins, and alpha-antitrypsin in particular, the impact of this study may eventually go beyond basic research and may also interest translational researchers.

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

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Referee #3

Evidence, reproducibility and clarity

In their study, Fasana and colleagues investigate protein quality control in the ER. Specifically, they test whether folding-incompetent proteins that are normally cleared by ER-associated degradation (ERAD) can also be targeted for degradation by direct vesicular transport from the ER to lysosomes in case ERAD is blocked. They show that blocking ERAD pharamacologically or genetically indeed leads to re-rerouting of an ERAD model substrate (the NHK variant of alpha-antitrypsin) to lysosomes and that this pathway requires the reticulon-like protein FAM134B, the ability of FAM134B to interact with the ubiquitin-like protein LC3 and the machinery for LC3 lipidation.

The paper is, for the most part, easy to follow. There are, however, a few minor issues and I think the authors could do more to connect their work with similar studies in the literature. Accordingly, I have some general and specific suggestions to make the manuscript more accessible for the reader.

General suggestions

1. To avoid confusion, it would be helpful to more clearly distinguish between vesicular transport to endolysosomes and autophagy. Previous work by the authors has defined a trafficking pathway from the ER to endolysosomes that appears to rely on conventional vesicle-mediated transport (Fregno et al, EMBO J 2018). This pathway delivers material from the ER lumen to the lumen of endolysosomes, which are both topologically equivalent to the extracellular space. Hence, this pathway is distinct from autophagy, which is the transport of cytoplasmic components to endolysosomes and thus the transport of material from intracellular to extracellular space. This distinction is particularly important as both vesicular ER-to-lysosome transport and autophagy of the ER involve LC3 and FAM134B, which is typically referred to as an ER-phagy receptor. To make this less confusing, it may be helpful to explain that FAM134B appears to be a multifunctional molecule that can function as a receptor for macroautophagy but also in the vesicular transport pathway studied here. In addition, it would be helpful to point out that LC3 appears to also have roles unrelated to autophagosome formation.
2. Several recent papers that appear relevant to the present study are not mentioned. In particular, Sun et al., Dev Cell 2023 (PMID: 37922908) appears worthy of discussion, as does Gonzalez et al., Nature 2023 (PMID: 37225996).

Specific suggestions

1. Abstract: The abstract begins with "About 40% of the eukaryotic cell's proteome is synthesized ... in the ER." Similar statements can be found in many papers and purportedly reflect common knowledge. However, it is unclear where the figure of 'about 40%' comes from. It would be proper to provide a reference and demonstrate that giving such a fairly precise estimate is supported by experimental data. Alternatively, the statement could be modified to avoid being precise than is justified.
2. p2: "The ER is site of gene expression in nucleated cells and ... native proteins to be delivered at their site of activity ...". There is something missing at the beginning of this sentence. Also, it should be 'delivered to their site of activity', not 'delivered at'.
3. p2: "... by mechanistically distinct ER-phagy pathways collectively defined as ER-to-lysosome-associated degradation ERLAD." This statement suggests that all pathways subsumed under the term ERLAD are ER-phagy pathways, which I believe is misleading (see comment above on the distinction between autophagy and vesicular transport pathway).
4. p2: "KIF selectively ...". Please spell out KIF and explain what kind of compound it is.
5. p3: "Notably, ERAD inhibition delays, rather than blocking degradation of ERAD clients ...". Please correct, for example: Notably, ERAD inhibition delays rather than blocks degradation of ERAD clients ...
6. Figures 2 - 5: The number of quantified cells is given but it is not clear if experiments were done once or in biological replicates. Please indicate this in the figure legends.
7. p4: "To verify if ERAD inactivation ..." sounds odd. Less ambiguous would be 'To test whether' or 'To ask if'.
8. p7, beginning of discussion: Please correct "delivered at" to 'delivered to'.

Significance

This is a concise and convincing manuscript with a clear message. The idea that proteins that cannot be processed by ERAD can be eliminated by other means, for instance by autophagy, is not new. Similarly, the FAM134B- and LC3-dependent pathway for ER-to-lysosome transport has been described by the authors before (Fregno et al, EMBO J 2018). Furthermore, the study exclusively relies on microscopy and does not attempt to tackle new mechanistic questions. Still, this study presents a definite functional advance in our understanding of the interplay of various ER quality control pathways.

The findings presented here will be of interest mainly to molecular cell biologists working on protein quality control and organelle homeostasis. However, given the disease-relevance of misfolded proteins, and alpha-antitrypsin in particular, the impact of this study may eventually go beyond basic research and may also interest translational researchers.

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 endoplasmic reticulum (ER) is a crucial site for protein synthesis and folding within the cell, and strict protein quality control is essential for maintaining ER homeostasis. In this context, ER-associated degradation (ERAD) and the unfolded protein response (UPR) play pivotal roles. Recent researches have highlighted the significance of ER-phagy in protein quality control. In this manuscript, the authors demonstrate the role of FAM134B in degrading misfolded proteins such as ATZ through the ER-phagy pathway when the ERAD pathway is obstructed. This work partially addresses a prominent issue in the field, unveiling the interconnections between different regulatory pathways in maintaining ER homeostasis.

Major issues:

1. In a multitude of experiments, the authors employed Bafilomycin A1 (BafA1) to block the fusion between autophagosomes and lysosomes, attempting to demonstrate that the clearance of misfolded proteins mediated by FAM134B is independent of autolysosomes. However, in Figure 4, the lack of rescue of FAM134B knockout by overexpressing FAM134B△LIR suggests a dependence on the interaction between FAM134B and LC3. The conclusions drawn before and after appear contradictory.
2. Some Western blot data are insufficient to substantiate the author's conclusions. For instance, in Figure 5D, the ATG7 KO line is inadequately supported
3. The author employed Lamp1 antibody for lysosomal staining in cells and observed a significant abundance of lysosomes in some experiments, as depicted in Figure 2C, 2D, 4I, etc. Is the phenomenon of lysosomes extensively filling the entire cell a common occurrence? Is it indicative of a normal physiological state?

Minor issues:

1. Some immunofluorescence experimental data are unclear. Please request the authors to replace these with more distinct images, as seen in Figure 3B and 3E.
2. Some expressions appear to be questionable. For instance, the necessity of utilizing endolysosomes requires clarification.
3. Some writing lacks precision, such as referring to FAM134B as FAM134.

Significance

• General assessment:
• Advance: provide an meaningful evidence that how two degradative pathways are coordinated in maintaining ER homeostasis.
• Audience: cell biologist
• Reviewer's expertise: autophagy, vesicle trafficking, organelle biolgy

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

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Referee #1

Evidence, reproducibility and clarity

In this manuscript from Fasana et al., the authors present data that investigates potential compensatory degradation pathways for misfolded glycoproteins in the ER - postulating that the ER-to-lysosome associated degradation (ERLAD) pathway becomes employed in the absence of a path for substrates to reach the ER-associated degradation (ERAD) mechanism. Using the classic ERAD substrate alpha1-antitrypsin NHK variant (NHK), the authors first demonstrate that pharmacologically preventing access of NHK to ERAD either with KIF (early) or PS-341 (late) elevates the number of LAMP-1 positive endolysosomes also immunoreactive for NHK (via HA), similar to what is observed for the ATZ variant that forms polymers in the ER (Fig 2). The authors next use shRNAs that silence essential ERAD factors (EDEM1, OS-9) involved in glycan recognition to demonstrate comparable enrichment of NHK in endolysosomes through genetic disruption (Fig 3). Next, the authors employ FAM134B-deficient MEFs to demonstrate the requirement for this ER-phagy receptor when ERAD is unavailable (Fig 4). Reconstituting FAM134B-/- MEFs treated with KIF/PS-341 + Baf, with a full length FAM134B rescue plasmid restores endolysosomal accumulation of NHK while a FAM134B-∆LIR does not, providing supporting evidence for substrate rerouting to ERLAD. Finally, the authors use knockouts of Atg7 and Atg13 to demonstrate dependence on LC3 lipidation and independence from macro-ERphagy (Fig 6), that points towards a pathway that is like that used to remove ATZ polymers. From these data, the authors conclude that ERLAD is increasingly engaged for substrate degradation when ERAD is impaired.

Major comments:

1. All assays rely on quantification of the NHK-HA substrates by microscopy. Would it be possible for the authors to also include biochemical analysis of NHK - potentially including data assessing its changing abundance and glycosylation state?
2. In Figure 3D, the knockdown of OS-9.1/2 is modest compared to that of EDEM1 (Fig 3A). Moreover, there is only data from single shRNAs presented. Could the authors please at least include another shRNA to confirm and demonstrate whether the targeting to ERLAD is accordingly scaled to loss of access to ERAD (based on the degree of OS-9 or EDEM1 remaining)?
3. While degradation is implied, it is not specifically demonstrated at any point in the manuscript. Perhaps the authors might include some demonstration of NHK stabilization in one of the figures via a translational shutoff or pulse-chase assay.
4. 10-30% of NHK-HA positive endolysosomes are detected even with Baf alone (e.g. Fig 2E)? Does this mean that Baf impairs ERAD to some extent since or is it evidence for continuous ERLAD involvement when ERAD is intact? If so, how much is its contribution?
5. An accounting of how much ERLAD is contributing to NHK degradation with or without ERAD impairment is not really present.. Effectively, how much degradation capacity is ERLAD making up? These would be interesting data to include if possible as they would speak to the "division of labour" for ER substrate degradation its potentially dynamic nature.

Minor comments:

1. In Figure 4, an increase is observed for the rescue of FAM134B-/-MEFs with WT FAM134B that is 50% greater that of WT MEFs, suggesting that its availability might be rate limiting. Could the authors compare the relative levels of FAM134B for the WT and KO-rescue MEFs to address this possibility?
2. In Figures 1 and 6, the terms siOS9 and siEDEM1 are used but Figure 3 shows data from shRNAs and not siRNAs.
3. Samples from Figure 3 treated with Baf but this is not indicated in the figure or figure legend.
4. VCP/p97 inhibitors typically stabilize ERAD glycoprotein substrates better than proteasome inhibitors do. Is the same degree of endolysosomal targeting present

Significance

Deconvolution of the different pathways taken by misfolded proteins to escape the ER is of great interest not only to the ER community but also represents consequences to consider for those interested in therapeutics involving UPS inhibition. While concise, this manuscript does a good job of trying to demonstrate the principal of substrate rerouting and the prioritisation of degradation pathways. Overall, the manuscript is well written, the experiments presented are performed to a sufficient standard, the data are lean but of good quality, and the appropriate statistical analyses have mostly been included where necessary and are described. The Methods and Materials is brief but describes the experiments that have been performed. The manuscript is brief in its results and would obviously benefit from additional complementary assays that would strengthen and broaden the authors arguments for rerouting. But too their credit, the authors do not grossly overstate their findings and merely present the culmination of a set of experiments to answer a single question - what happens to a misfolded glycoprotein substrate when ERAD is impaired. This is a key question with broad implications.

While their limited data clearly demonstrates an acquired dependence on ERLAD, one can't help but wonder how broadly these findings hold true, as only a single glycoprotein substrate example is used. Moreover, it is not clear what percentage ERLAD contributes to overall NHK degradation (with or without ERAD) as the total NHK amount remaining is not assessed or measured. Nevertheless, the manuscript is an advancement of understanding of the fate of substrates unable to access ERAD and raises many future questions of interdependency between the ERAD and ERLAD pathways. The data just need a bit of shoring up.

Expertise - ERAD, UPS, protein quality control

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Referee #3

Evidence, reproducibility and clarity

The authors used hIPSCs to generate spheroids capable of elongation when cultured in KSR and exposed to BMP4. After examining all three developmental lineages of these treatments, the spheroids were embedded in different hydrogels to restrict movement and observed how this affected elongation and lineage differentiation. This manuscript was difficult to review because of the the style of the writing, the sometimes confused narrative of results, the problematic statistics and questionable interpretation of the literature. Authors should actively address the issues presented below with a significant overhaul of the text and presentation.

Overall comments

Major concerns - The body of the manuscript should be re-written to offer a coherent narrative that delivers a clear and condensed message . In fact, it was quite surprising given the well written and concise format of the introduction. However, there is some confusion about the interpretation of the first reference (https://doi.org/10.1038/s41586-020-2383-9) in which it was already presented that BMP4 treatment did not induce elongation in a hIPSC-derived gastruloid model. This is not to say that there is anything wrong with repeated experiments and different results, but the results from this reference were interpreted as if BMP4 treatment had induced elongation. The use of the methodology present in this manuscript as opposed to the validated model of using Wnt agonism to induce elongation is not convincingly justified. The results themselves have potential if reworded and condensed but in their current format they are not convincing. Statistics have substantial problems. According to the methodology, only one-way ANOVAs were used, when many of the circumstances would call for t-tests (if parametric) or at least mention the normality tests used to justify the ANOVAs. There is no clear mention of the number of independent differentiations and only one cell line was used. As a result of this, and the state of the statistics and interpretation of the data, the conclusions presented in this paper are inconclusive or misrepresented. The article should be re-written in a coherent scientific style, including not writing in the first person/active voice, and addressing the grammatical errors mentioned below.

Minor concerns - Throughout the methods there are issues with inconsistent notation, e.g. acronyms aren't always in brackets (HBSS, PBS, KSR), units are sometimes spaced from the value (10ng/mL or 10 µg/mL), units are incorrectly written (u instead of µ). There are also typographical errors such as basic grammar (capital letters and full stops), double spacing, typos, strange sentence construction, as well as interchangeable use of commas and semi colons when listing antibodies. These issues were not confined to the methods, but were particularly noticeable there, and so the whole manuscript requires thorough proofreading. Positive comments - The introduction was well written and concise, the images were mostly clear and easy to interpret, illustrating a result even if not directly the one described.

Specific Comments

Introduction - Comments

The introduction was well written and easy to follow. However, certain aspects should be refined in order to highlight the argument as to why the mechanical forces and environment are of importance to lineage determination in hIPSCs. For example, the paragraph describing 2D micropattern cultures could be reduced or integrated into the introduction of 3D gastruloid models. In its place, further exploration of examples of mechanical force's impact on stem cell/embryonic differentiation, both in vitro and in vivo, would be beneficial (perhaps including the geometric shape aspect mentioned in the 2D micropattern paragraph here instead). This would emphasise the necessity for investigation of environmental forces on 3D in vitro differentiation, tying it back to the first paragraph's broader developmental questions. Currently, it lacks the reiteration of the overarching purpose of this investigation.

Materials and Methods - Comments

hIPSC culture - The paper suggests that only one hIPSC line was used for this research; considering the variability innate to each stem cell line and their differentiation capabilities, at least two cell lines should be used. Please reference that stem cell validation was conducted by HipSci. It is concerning that antibiotics were used for tissue culture on such a short protocol and should not be used in future. Similarly, were these hIPSCs tested regularly for mycoplasma? Reference briefly the method in which hIPSCs were passaged and what range of passage number was used.

Spheroids derivation from hIPSCs - There is no mention of hIPSC confluency upon differentiation. Based on the brief 4 minutes of Accutase exposure, colonies would either be small to achieve single cell dissociation (which is not in the best interest of hIPSC colonies) or that single cell dissociation was not achieved. Seeding density is also close to double seeding density for currently circulating gastruloid protocols (see https://doi.org/10.1242/dev.150391) with no explanation as to why this cell count was chosen. Make mention of whether or not they were fed during the initial 48 hours. There is also no reference to how many independent differentiations were executed and therefore replicability is of significant concern considering the use of an unvalidated protocol.

Gastrulation-like induction of 3D hIPSCs - Difficult to follow timeline of treatments without reference to Figure 1 and therefore requires a rewrite for clarity. In addition, media 3 and 4 are formatted differently from 1 and 2, making it more confusing. Do not rely on Figure 1 to explain the treatment course, it should be clear in the methodology.

Live Imaging - No need to state each media, particularly if it is out of numerical order as described previously. Can be written as "Live hIPSC spheroids were imaged for 96 hours....". Also include magnification and time frame of each hour, e.g. between 48 and 96 hours. Immunofluorescence staining - Other than the grammatical errors referenced above, as there are numerous in this paragraph in particular, the catalogue number for each antibody should also be supplied. Considering the number of antibodies, perhaps this would be best supplied as a supplemental table. No mention either here or previously as to how non-encapsulated spheroids were mounted and if cleared.

Results - Comments

As mentioned previously, the results are written in a style which is not sufficiently rigorous for a scholarly article and should therefore be edited to reflect the standard expected quality. BMP4 signalling induces axial elongation in 3D gastrulation-like models -

Figure 1 - Nice and clean diagram but unnecessarily large, could be shrunk and placed at the top of Figure 2. Also is lacking key methodological details e.g. seeding density, reference to media changes in time line, etc.

An example of a statement that lacks rigor and specificity is the following: "We used defined medium conditions that provided consistent shape variation in spheroid morphology. E8 medium promotes self-renewing conditions, while KSR BMP4 triggers differentiation [31,32]". Self-renewing conditions of what? Differentiation of what? Into what cells?

These statements are too vague and remain without connection to the research This kind of issues are unfortunately recurrent throughout the manuscript. They are easily rectifiable with concise text rather than expecting the reader to search through references. "Consistent with our previous results..." - not referenced. Mention of size is brief in text and instead description of results is found in Figure 2 legend.

Figure 2 - Although Figure 2.A and 2.B are clear images, Figure 2.B is unnecessary and doesn't add anything to the message. Figure 2.C: The statistics for this table are hard to believe, except between E8 and KSR BMP4, due to the spread of the data. Change references to "size" to "sphericity", as size would arguably be better investigated using area as a metric, again be precise in choice of language. There isn't even a description of what Figure 2.D is portraying, nor error bars or notation of statistical testing.

Figure 3 - Figure 3.A Writing on scale bars is too small to be useful and unnecessary if mentioned in the legend. The images highlight the issue with the size/sphericity issue, although the images themselves are reasonably clear and will highlighted (if slightly overexposed and not cleared). The title of this figure is also misleading - E8 BMP4 is not emulating gastruloid development, and the gastruloid-like entity of KSR BMP4 has yet to be validated. A more appropriate title would be "Exposure to BMP4 in spheroid and elongated spheroid culture increases SOX17 expression". There is no mention of how cells were counted in methods and considering the variable fluorescence observed in Figure 3.A OCT4 for E8, this could easily be misconstrued. Inappropriate dictation of p value, should only be reporting the alpha. Much like the similar issue with sphericity, the error bars in Figure 3.E in particular make it difficult to believe the statistical significance achieved. Overall it seems inappropriate to focus solely on endodermal lineage and leave ectoderm and mesoderm to supplementals, when classically axial elongation in gastruloids is punctuated not just by SOX17 but also by BRACH expression throughout the extended region. This suggests that the authors may not have sufficiently evaluated the literature referenced. The justification provided by the authors for choosing SOX17 reinforces this fact by declaring that SOX17 is expressed during early development, as if SOX2 and BRACH isn't! Most concerningly, claims of SOX2's absence in E8 media spheroids as if to be a positive should actually be worrisome, considering SOX2 is a Yamanaka factor. Arguably, without further validation, this result undermines the foundation of this work.

PEG-peptide hydrogel encapsulation disturbs SOX17 patterning - The interchangeable use of "control" and E8 makes for difficult reading. Although no further substantial issues were taken with Figure 4 that had not already been addressed (scale bars, overexposure), the final comment of this section is simply inaccurate: "Overall, this suggests that embedding hiPSCs in a confining environment blocks morphogenesis, and despite the addition of BMP4, this was not sufficient to enable SOX17 expression.". It does not define that the hIPSCs in this case are spheroids and determines this assumption based off data in Figure 6.B and Figure 6.C which could have been easily integrated into Figure 4. Rather than comparing non-deg PEG to deg-PEG, in order to make this statement, it is necessary to compare the non-embedded spheroids to the embedded spheroids. There is also reference to a Figure 3.C. that does not exist.

Modulating PEG-peptide degradability promotes SOX17 expression - This section had similar issues to the one above, predominantly flitting between Figure 5 and 6 when it could have been condensed. The microscope images are also particularly poor, with high background in the 488 channel, overexposure for Hoechst and incomplete light penetrance in the centre for both E8 and E8 BMP4. Despite the lack of methodological explanation of how counting was conducted, these aspects are still likely to have had significant impact on cell count regardless of how the count was conducted. The last comment of this section is again questionable, as there is no definitive comparison as to what the deg-PEG is improving upon with regards to SOX17 expression.

Biochemical cues regulate morphogenesis via cell proliferation and cellular tension - There is no explanation as to why the manuscript pivots away from hydrogels to look at proliferation and F-actin. It does not appear to benefit the overarching goal of this manuscript (i.e. investigating the impact of confinement on 3D hIPSC-derived elongation models), with proliferation investigations feeling like an afterthought and F-actin investigations being placed about 3 sections too late. It was surprising to see EdU to check cell proliferation in this manner; similar can and should be achieved by using KI67 staining. This was a significantly missed opportunity to do pulse-chase experiments to understand potential cell cycle changes, and suggests the experimental design was not thought through. However, it is more reasonable to examine the F-actin network as shown by the manuscript. Although the pipeline in Figure 7.D is an interesting take on quantifying F-actin staining, no statistical analysis was undertaken to confirm a link between conditions and F-actin, nor F-actin and SOX17 expression, despite what this manuscript suggests. This should be coupled with information prior to the introduction to hydrogels, and then re-evaluated in those confined to hydrogels.

Overall these results need to be substantially edited for clarity, rigor and completeness. The narrative of the results is lost half way through, the statistics are questionable or non-existent and the logic behind certain experiments are debatable.

Discussion - Comments

To consider the models generated in this manuscript as gastruloids is misleading and inaccurate and should be replaced with something that reflects what was actually generated, e.g., BMP4-induced elongated spheroids. A quick search of key gastruloid papers, such as https://doi.org/10.1242/dev.113001, indicates how far detached the spheroids examined in this paper are, only sharing similar polarised SOX17 expression. In fact, the above referenced paper already examined aspects of classic gastruloid differentiation when exposed to BMP4, albeit using mESCs, and indicated that elongation only occurred in a proportion of the population. Similarly in the first reference which used hIPSCs specifically, https://doi.org/10.1038/s41586-020-2383-9, it was reported that BMP4 treatment did not induce elongation. At no point in this manuscript were these results discussed, which is concerning. Instead, this manuscript claims to have "robustly" concluded many of the results which have been questioned in detail above, with little reference to the variability across multiple differentiations or adequate statistical analysis. Noticeably they have also not mentioned their results on proliferation, which again makes the question of its relevance to the paper's aims.

Significance

The authors used hIPSCs to generate spheroids capable of elongation when cultured in KSR and exposed to BMP4. After examining all three developmental lineages of these treatments, the spheroids were embedded in different hydrogels to restrict movement and observed how this affected elongation and lineage differentiation. This manuscript was difficult to review because of the the style of the writing, the sometimes confused narrative of results, the problematic statistics and questionable interpretation of the literature. Authors should actively address the issues presented here with a significant overhaul of the text and presentation.

Our expertise is in stem cell biology, 2D and 3D model systems, microscopy, and single cell analysis.

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Referee #2

Evidence, reproducibility and clarity

Within the manuscript "Morphogen-driven human iPSCs differentiation in 3D in vitro models of gastrulation is precluded by physical confinement" by Alsehli et al, the authors aim to dissect the effects of biochemical cues and physical confinement using gastruloid models. Using this model, the authors find some indications that physical confinement prevents morphological changes and reduces lineage commitment of cells (as assayed by Sox 17).

While the manuscript addresses an interesting and important question, I do not think that the setup and data as present in the manuscript provide conclusive insight in any of the questions studied. First of all, the authors use a very different system (BMP4 induction) as compared to mainstream conditions for gastruloid formation. Based on the images and movies within the manuscript, symmetry breaking and elongation seem to be very sub-optimal under the conditions used by the authors, which makes any further functional assaying highly challenging. Importantly, it remains unclear why the authors did not (at least) include mainstream conditions (Chiron pulse) within their assays for comparative purposes, I feel this is a missed chance. On top of that, KSR is known to be poorly compatible with gastrulation and further development, at least in mouse (https://pubmed.ncbi.nlm.nih.gov/35988542/), so it remains unclear why the authors include a KSR condition.

Referees cross-commenting

Like me, both other reviewers indicated (major) shortcomings of the current paper, and indicated potential directions for improvement. Both these other reviews are very balanced as well. Altogether, there are significant changes required for the manuscript, and it depends on the authors which direction they would like to take this manuscript. Hence, I do not know what else to conclude than that in the current format there too many shortcomings to be of added value to current literature (similar to reviewer 3, and in line w/ reviewer 1 but who is somewhat more mild in their evaluation). If the authors decide to move on with this story, this paper requires a re-evaluation of a much improved version.

Significance

Secondly, I am not convinced by the data quality and representation in the manuscript. As outlined above, symmetry breaking and elongation seem to be very sub-optimal. Also, Fig 4b and Fig 5b hardly show any visible SOX17, in particular also not in the deg-PEG E8 BMP4 condition. Yet, the authors claim high expression of SOX17 in this condition in Fig 6C, as well as large and significant differences between conditions. To my feeling, Fig 6C does not represent the Sox17 observations of the IF. Similarly, I am not convinced by the EdU staining in Fig 7A. Importantly, the authors base their conclusions on only a single cell line, very few spheroid of this cell line, and an unknown number of biological experimental replicated (which to me seems single experiments). Altogether, the setup and data lacks reliability and robustness.

Currently, the efficiency of gastruloid formation is a important discussion in the field. Therefore, it is important to report on this in the current manuscript.

Altogether, while the manuscript makes a few interesting observations, it is very preliminary and not-well worked out or validated. Without being more robust and conclusive, I do not think the manuscript is of much added value to current literature.

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Referee #1

Evidence, reproducibility and clarity

Summary: This manuscript developed a BMP-based culturing protocol for gastruloid-like tissue that eexpresses markers from ectoderm, mesoderm, and endoderm. Through modulating the mechanical properties of extracellular environments, the expression of endodermal marker, SOX17, was found to correlate with the mechanical properties of the extracellular environment. However, the data presented only constitute a crude characterization of the cell lineages within the tissue and, therefore, the biological relevance of the gastruloid-like tissue, together with the associated discoveries, is not immediately evident.

Major comments

1. Extra explanation should be provided to justify why mechanical property of extracellular environments is a relevant/important factor for either early embryo development or gastruloid technology.
2. (OPTIONAL) To demonstrate the impact of mechanical property of extracellular environments, the authors compared two different gels, a stiffer gel with non-significant stress relaxation, and a softer gel with non-trivial stress relaxation. However, such comparison can be somewhat non-intuitive since a variety of mechanical properties are modulated simultaneously between two groups, including both tissue stiffness and its time-dependency. Since it has been well established that both elasticity and viscoelasticity can affect cell behavior, respectively, I would suggest the authors consider adding an extra comparison between a stiff elastic gel and a soft elastic gel.

Minor comments

1. The author provided individual staining of SOX2, BRA and SOX17, it would be more helpful to co-stain these markers to demonstrate their relative spatial distribution.
2. The quantification method for Fig. 7D&E seems missing from the method section, and more explanation for the method would be helpful. What is the area ratio between the inner and outer ROI? What does the y-axis number mean in Fig.7E?
3. In the last 2nd paragraph of "Biochemical cues regulate morphogenesis via cell proliferation and cellular tension", it was mentioned that "spheroids cultured in E8 medium exhibited organised and tightly packed F-actin with a homogenous network orientation", yet in the next paragraph, it was claimed that "F-actin orientation in round spheroids in E8 medium is mostly distributed in the inner core". Aren't these statements contradictory? Also in this paragraph, it was mentioned "Whereas in KSR conditions, F-actin was distributed in the periphery without significant differences compared to KSR medium conditions", I assume the authors intended to say "KSR BMP4" here?
4. The authors mentioned that "cells in the KSR BMP4 spontaneously elongate mirroring A-P elongation", yet based on the data presented, the elongation orientation appears more consistent with the D-V embryo axis?

Significance

This manuscript demonstrates a rudimentary investigation towards how mechanical properties of the extracellular environment may affect the marker expression within a gastruloid-like tissue. Such information may provide certain useful knowledge for the field of gastruloid. However, compared with the established gastruloid models in the field, the advantage of the tissue model developed in this study isn't very clear. Further, the physiological relevance of extracellular mechanics (and particularly, matrix viscoelasticity, which is studied in this manuscript) is not immediately evident.

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Referee #3

Evidence, reproducibility and clarity

This is a manuscript that focuses on understanding the function of BLTP2 protein in regulation of ciliation. BLTP family of proteins recently emerged as a lipid transporters in several contexts, such as formation and extension of autophagic membrane. The entire study is build on very intriguing observation that BLTP2 depletion leads to enhanced ciliation in RPE1 cells grown in the presence of serum. That makes BLPT2 a negative regulation of cilia formation that appears to mediate serum-dependent inhibition of ciliation in RPEs. Since molecular machinery governing serum-dependent inhibition of cilia formation remains poorly understood, this study does have a potentially high significance and interest. Unfortunately, most of the study (besides Figure 1) is done using Hela cells. It is a puzzling choice since Hela cells do not form cilia. Additionally, mots analyses are fairly descriptive and do not really lead to any specific hypothesis. As the result author's conclusion is very vague, specifically stating that "BLTP2 may suppress ciliogenesis by altering the lipid dynamics and/or densities of unidentified integral membrane proteins that suppress ciliogenesis". Thus, as it stands, this study does not really lead to new insights in BLPT2-dependent regulation of cilia formation.

Few specific other comments are listed below.

1. Figure 1. Two different individual siRNAs for each target should be used (unless authors show rescues) to minimize the possibility of off target effects.
2. Figure 2-4. Not quite sure what was the rationale to study BLTP2 localization in HeLa cells instead of RPE1. Considering that the main focus of this manuscript is ciliation, one would want to see extensive analysis of localization of BLPT2 in RPE1 cells.
3. The key to this manuscript (considering its focus on ciliation) would be to look at BLPT2 dynamics in the RPE1 cells in the presence and absence of serum, especially during ciliary vesicle and cilia formation. Instead, authors do most of their analysis in HeLa cells that do not even form cilia.

Significance

This is a manuscript that focuses on understanding the function of BLTP2 protein in regulation of ciliation. BLTP family of proteins recently emerged as a lipid transporters in several contexts, such as formation and extension of autophagic membrane. The entire study is build on very intriguing observation that BLTP2 depletion leads to enhanced ciliation in RPE1 cells grown in the presence of serum. That makes BLPT2 a negative regulation of cilia formation that appears to mediate serum-dependent inhibition of ciliation in RPEs. Since molecular machinery governing serum-dependent inhibition of cilia formation remains poorly understood, this study does have a potentially high significance and interest. Unfortunately, most of the study (besides Figure 1) is done using Hela cells. It is a puzzling choice since Hela cells do not form cilia. Additionally, mots analyses are fairly descriptive and do not really lead to any specific hypothesis. As the result author's conclusion is very vague, specifically stating that "BLTP2 may suppress ciliogenesis by altering the lipid dynamics and/or densities of unidentified integral membrane proteins that suppress ciliogenesis". Thus, as it stands, this study does not really lead to new insights in BLPT2-dependent regulation of cilia formation.

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Referee #2

Evidence, reproducibility and clarity

The manuscript by Parolek at al demonstrates the role of Bridge-like lipid transfer protein family member 2 (BLTP2) as a negative regulator of ciliogenesis in cultured retinal pigmental epithelial (RPE-1) cells. Based on genetic interaction of BLTP2 with another ciliogenesis negative regulator, WDR44, a RAB11 effector, the authors mechanistically study the regulation of cilia by these proteins. The authors nicely show Hela cell specific colocalization of BLTP2 and WDR44 in the ER-tubular endosome network membrane contact sites (ER-TEN MCS). They demonstrate that the C-terminus of BLTP2 is necessary for localization to the TEN. They also find that the WDR44 network to be present in higher proportion of Hela cells lacking BLTP2. Interestingly, BLTP2 and WDR44 also localize at tips of GFP-Rab8 and GFP Rab10 tubular membrane network in Hela cells. However, RPE-1 cells do not possess WDR44- and BLTP2-associated tubules, so the context of the TEN with the ciliogenesis phenotype in RPE cells, if any, is presently unclear. The rigor and reproducibility of the presented experiments is high and the presented results are novel for cilia, membrane trafficking, memembrane contact sites and lipid transfer fields. Overall, the authors suggest that BLTP2 and WDR44 are common components of a pathway that suppresses ciliogenesis in serum-fed RPE-1 cells.

Major comments

How general are the effects of BLTP2 on ciliogenesis? Effects on ciliogenesis in other cells would consolidate the current results in RPE-1 cells.

Are the effects on ciliogenesis in RPE cells mediated by the role of BLTP2 and WDR44 in TEN network shown in Hela cells? If not, can the authors demonstrate the subcellular localization of these proteins with respect to ciliogenesis, and optionally if possible with the Rab8-Rabin8-Rab11 cascade? For eg., WDR44 knockdown has been shown to increase peri-centrosomal localization of Rabin8 in serum-fed conditions. Does BLTP2 knockdown have similar effects?

The authors show that the C-term of BLTP2 is necessary for its recruitment into TEN network, irrespective of WDR44 in Hela cells. Does the C-term of BLTP2 also regulate ciliogenesis?

Optional: Interactions between BLTP2 and WDR44 are currently unclear other than their colocalization. Can the authors further address if there are close physical interactions between these proteins and/or Rab11?

Minor comments

Fig 3C. In merge/inset: please check the white bar.

If possible, show rescue of ciliogenesis phenotype from BLTP2 knockdown or knockout.

Significance

The roles of lipid transfer proteins in ciliogenesis are currently unknown. By showing the function of BLTP2 in ciliogenesis, the authors suggest the possibility of lipid transfer between the ER and the endo-lysosomal network in regulating ciliogenesis pathways. The results showing co-localization of BLTP2 and WDR44 in ER-tubular endosome network membrane contact sites (ER-TEN MCS) is nicely done and the effects on TEN upon WDR44 loss is also very intriguing. Recent papers suggest a role of WDR44 in ciliogenesis and in ciliopathies. The current data will be of broad interest to readers in ciliogenesis, intracellular trafficking, and lipid transport fields. From my own expertise in cilia biology, I think the results are exceptionally novel but needs more context to further solidify the role of BLTP2 in ciliogenesis.

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Referee #1

Evidence, reproducibility and clarity

Summary

This manuscript by Parolek and Burd addresses the role of the evolutionarily conserved Bridge-like lipid transfer protein 2 (BLTP2) VPS13 family member in negatively regulating ciliogenesis. BLTP proteins are thought to mediate the transfer of lipids between a variety of different organelles, and while BLTP2 loss-of-function in plants and multicellular organism including flies and mice has been connected to various phenotypes, the role of human BLTP2 is poorly understood. In the current study, the authors initially used the Cancer Dependency Map Portal to find a very high mutual co-dependency between the BLTP2 gene and WDR44, a previously well-established negative regulator of primary ciliogenesis. This led the authors to ask whether BLTP2 (similar to WDR44) affects ciliogenesis and indeed they demonstrated that knock-down of either protein in serum-containing RPE1 cells (conditions that normally do not facilitate robust cilia formation) led to an increased percentage of ciliated cells. The authors next addressed the localization of human BLTP2, finding it on ER membranes as well as in linear/tubular structures that correlate with ER subdomains, at least in HeLa cells. Moreover, BLTP2 localization overlapped with that of WDR44. The authors then demonstrated that in BLTP2 knockout cell lines a significantly greater percentage of cells displayed a robust tubular endosome network than in wild-type cells. Finally, the authors show that both BLTP2 and WDR44 tend to localize to the tips of the endocytic tubular network, suggesting that these proteins may localize to contact sites between the ER and (tubular) endosomes, and further, that these contact sites may be required for primary ciliogenesis.

Major Comments

This is an interesting manuscript that addresses a poorly understood protein, and potentially provides a novel connection between ER-recycling endosome contact and ciliogenesis. The experimentation is well executed, and the presented data are clear. The strengths of the manuscript lie in partially unveiling new function for BLTP2, functionally associating BLTP2 with WDR44, and the potentially novel relationship between ER-endosome contact sites and ciliogenesis. Moreover, the tubular network of endosomes (which has been primarily implicated in recycling), remains an incompletely understood organelle and this manuscript suggests a new role for it. The weaknesses lie in the preliminary nature of the studies (which in the current form are largely correlative/speculative), and the somewhat descriptive nature of the study. For example, while the proposed connection between ER-endosome contacts, TEN, and cilia is intriguing, there is little attempt to address how such contact sites and TEN might affect ciliogenesis. Developing these ideas would greatly increase the significance of the findings, which as presented are mainly correlative. Other key questions include whether these proteins affect functions previously attributed to tubular endosomes, such as receptor recycling and endocytosis? What is the function of the TEN in maintenance or generation of ER contact sites? There is some literature suggesting that TEN serve in the sorting and/or fission process that might separate Rab5 anterograde transport from Rab4 recycling endosomes, but this is not addressed in the context of the current manuscript. How do ER contact sites and TEN impact ciliogenesis at a molecular level? How might a lipid transfer protein affect primary ciliogenesis? Is the TEN network connected to lipid transfer? Reports hold that PI4,5P2, PI4P, PA and other lipids might be enriched in the TEN; are these (or other lipids in the TEN) affected by BLTP2? In addition, while BLTP2 and WDR44 are linked by localization (and their mutual co-dependency), little attempt has been made to understand how these proteins function together. Do they physically interact? Are Rab8/10 responsible for their recruitment to the tips of endosomes?

Minor comments:

Could endogenous Rab proteins be used to address localization of BLTP2 and WDR44 to tubule tips?

Could the authors please explain how the R=0.61 mutual co-dependency was arrived at? This reviewer used the portal website to find an R value of 0.58. Admittedly these numbers are both very high and the difference between them not significant, but nonetheless they are not identical.

Significance

The novelty of this study is that it identifies a new player, BLTP2, involved in the regulation of primary ciliogenesis. Since ciliogenesis impacts so many physiological events and underlies over 100 distinct ciliopathgies, there is clear significance in identifying new proteins that regulate this process (even if hundreds have already been identified). Perhaps the most (potentially) novel finding is the relationship between the ER contact sites, the tubular network of endosomes and ciliogenesis. Few papers have made any connection between tubule generation and ciliogenesis, with the exception of Insinna et al. (Nat Comm., 2019), a paper reporting that the tubular endosome scaffold MICAL-L1 is required for ciliogenesis (Xie et al., J. Cell Sci., 2019), and the recent Biorxiv manuscript by Ott and colleagues suggesting that tubules allow formation of "deconstructed" cilia, none of these connect ciliogenesis to ER contact sites. The limitations of the study are the preliminary nature; as noted, while the individual experiments are clear, substantial data that clearly connect ER contact sites, tubular endosomal networks and ciliogenesis remain largely uncharacterized in this study. In terms of the audience, if a more tangible relationship between ER contact sites/TEN and cilia could be derived, the study would be cross-disciplinary and of interest to a wide audience.

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1. General Statements [optional]

Response: We would like to thank both reviewers for their insightful comments. We have addressed most comments in the transferred manuscript and are willing to perform additional experiments to respond to some remaining points, as detailed in the following sections.

1. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

Reviewer #1:

Fig. 5, It would also be interesting to explore the involvement of IFN-I receptors (IFNAR1 vs IFNAR2) by dissecting IFN-α from IFN-β responses.

Response: Our understanding is that IFNAR1 and IFNAR2 form a heterodimer, which can be activated by both IFN-α and IFN-β. It is thus difficult to dissect the role of individual receptors or cytokines from each other. However, to confirm that IFN-α and IFN-β are both acting through the IFNAR1 receptor to prime for IL-1b activation and release in human neutrophils, we will perform additional experiments by treating neutrophils isolated from healthy individuals with both cytokines individually (as opposed to using them synergistically as in the current manuscript) and blocking their effects by a commercial IFNAR1 blocking antibody. 

Reviewer #2:

- The authors are encouraged to specify the number of independent experiments conducted. For mouse model studies, it is recommended to include results that are either representative of, or aggregated from, a minimum of two independent experiments to ensure robustness of the data.

Response: We did three independent animal experiments in total. The first two experiments involved two time points (2 and 4 days post infection) with different downstream experiments: The first experiment was used for the detection of viral loads by PCR as well as IHC-based quantification of viral antigen and neutrophil influx into the lungs (Exp1, new suppl. Fig 6) while the second experiment (Exp2) was used to isolate neutrophils from the lungs in order to assess neutrophil caspase1 activity and to obtain samples for RNAseq (new Fig.7 A-D). The third experiment (Exp3) was to perform anti-IFNAR and isotype treatments for infected mice; here, all animals were at day 2 post infection. For this experiment we prepared lung samples for IHC and PCR (new suppl Fig. 7) and isolated neutrophils for the assessment of caspase1 activity and for PCR assays (new Fig. 7E-G). We have now improved the text and supplementary Table S2 to indicate these separate experiments more clearly.  In our experience, this approach, i.e. making use of the lungs of oe animals for the determination of several parameters, is of benefit not only because we can directly compare these parameters in a given animal and can thereby reduce the number of animals used for the project (following the 3R principles).

However, in order to increase sample size and to respond to the various issues raised by the reviewer regarding our mouse work, we have decided to undertake another mouse infection experiment to analyze the effect of the anti-IFNAR treatment on viral loads by assaying for viral titers in the lung sample (which will hopefully directly answer the reviewer’s concerns raised below regarding the effect of anti-IFNAR treatment on viral replication). We will also confirm the negative effect of anti-IFNAR treatment on the expression of IFN-responsive genes by measuring OAS2 mRNA levels by PCR in the lungs of the anti-IFNAR treated as compared to isotype-treated mice. Finally, we will isolate neutrophils from the lungs to repeat the experiment showing the effect of anti-IFNAR treatment on neutrophil inflammasome activity as shown in Fig 7. E-G and will take a sample each for the histological and immunohistological analysis to complement the other tests.

• The authors are advised to employ more quantitative methods, such as flow cytometry, to measure neutrophil recruitment in mice. Additionally, it should be clarified how many tissue sections from each mouse were assessed for every experimental condition to ensure the reproducibility and statistical validity of the results. 

Response: While we are not aware that flow cytometry can be considered as a “more quantitative method” than morphometry, we agree that it is an alternative, i.e. complementary quantitative method. Furthermore, we feel that direct quantification of isolated Ly-6G+ neutrophils which are obtained from homogenized lung tissue by magnetic beads (as we have done for some mouse experiments of the current manuscript) is another quantitative approach and a method comparable to flow cytometry. Therefore, we are willing to repeat the mouse infection experiments and quantify the isolated neutrophils in parallel to IHC-based morphometry in order to determine the robustness of our morphometrical neutrophil quantification but are not inclined to undertake flow cytometry, in particular since this would not allow the assessment of all other relevant parameters in the same lung.

The reviewer asked for information regarding the number of tissue sections that were assessed from each mouse. In our opinion, for quantitative purposes (i.e. morphometry), it is more meaningful to determine the total tissue area that is examined, as different pathologists take different approaches to trim the lung for histological examination (cross sections vs. longitudinal section of a lobe). In our study we examined a tissue area of 19.5 ± 6 mm2 for each lung, which is stated now also in the revised manuscript.

Revised manuscript, methods section, line 307:

“The average total tissue area used for the quantification was 19.5 ± 6 mm2”.

• The authors need to address discrepancies in their text regarding the effects of anti-IFNAR1 blockade on viral titers and neutrophil recruitment in SARS-CoV-2 infected mice. While they state there is no change, Supplementary Figure 5D suggests increased SARS-CoV-2 NP staining with anti-IFNAR1 treatment, and there appears to be a lack of quantitative data on lung neutrophils to substantiate the claim that neutrophil recruitment remains unaffected. It is necessary for the authors to provide a more detailed explanation or additional data to resolve these inconsistencies *

Response: We did not observe any significant differences in the antigen expression between anti-IFNAR treated and isotype-treated mice. The lack of differences in viral loads was also shown by PCR (suppl Fig. 6B). However, since we are suggesting to repeat the anti-IFNAR experiment which will also include the quantification of viral titers in lung tissue with and without anti-IFNAR treatment, we will gain further insight whether and how IFN-I activity could regulate infection kinetics. We will also repeat the quantification of neutrophils in the lungs of anti-IFNAR and isotype-treated mice by IHC-based morphometry as well as by determining the number of isolated LY-6G+ neutrophils. 

• The authors should demonstrate the effectiveness of anti-IFNAR1 blockade in mice by providing evidence of sustained inhibition of IFN-I signaling throughout the duration of the experiment to validate the treatment protocol used. 

Response: We feel the observed inhibition of inflammasome-related pathways by anti-IFNAR treatment strongly argues that blockade of IFNAR activity was successful during the 2 day time course of the direct experiment (Exp3). However, the reviewer’s comment is valid since we have not shown the effect of anti-IFNAR treatment on specific IFN-induced genes. Therefore, we will repeat the anti-IFNAR treatment in infected mice and confirm its negative effect on the expression of IFN-responsive genes by detecting the expression of OAS2 mRNA in lung samples by PCR (OAS2 is one of the mostly upregulated genes by SARS-CoV-2 infection based on our neutrophil transcriptomics analysis). We will also assess whether the treatment directly affects the levels of infectious virus by quantifying viral titers in lung tissue.

*Referee Cross-Commenting*

• I agree with Reviewer#1 about trying to dissect the role of IFNAR-1 vs IFNAR-2. Authors partially look at this in the in vivo mice experiments using the anti-IFNAR1 blocking Ab, but it would reinforce the study to see if this holds with human cells. 

Response: To confirm that IFN-α and IFN-β are both acting through the IFNAR1 receptor to prime for IL-1b activation in human neutrophils, we will perform additional experiments by treating neutrophils isolated from healthy individuals with both cytokines individually (as opposed to using them synergistically as done for the current manuscript) and blocking their effects by a commercial IFNAR1 blocking antibody. 

The study presents an investigation into the role of neutrophils and inflammasome formation in COVID-19 pathology, contributing to the field with transcriptomic profiling of neutrophils from varying severity of patient cases and a SARS-CoV-2 mouse model. A significant IFN-I gene signature in severe cases was confirmed, and differences in inflammasome response were identified, adding to our understanding of disease mechanisms.

Strengths of the paper include the comprehensive analysis of neutrophil maturation states and the novel insights into the priming of inflammasome activation by IFN-I. However, limitations were noted in the purity of samples for RNAseq analysis and the lack of conclusive in vivo evidence for the direct role of IFN-I in neutrophil inflammasome priming. The study's implications suggest potential avenues for targeted therapies, but the authors were advised to moderate their conclusions without stronger in vivo evidence and to clarify the potential therapeutic implications of their findings.

Additional suggestions for improvement include the use of more quantitative methods like flow cytometry for neutrophil recruitment measurements, clarification on experimental replication, and resolving discrepancies in data presentation regarding anti-IFNAR1 blockade effects. Furthermore, the paper would benefit from discussing the relevance of autoantibodies against IFN-I in the context of their findings and from exploring the causal relationship between inflammasome patterns and disease severity.

Response: We would like to thank the reviewer for highly impactful comments. As suggested, we have redone the RNAseq analysis including only samples of higher neutrophil content, with similar conclusions as those previously made, and have amended the discussion based on the reviewer’s comments. Furthermore, to address the remaining questions raised by the reviewer, we will undertake the following additional animal experiments:

• Five groups of animals (n = 4);  

• PBS-inoculated animals 

• Infected with SARS-CoV-2 for 2 days, treated with isotype 
• Infected with SARS-CoV-2 for 2 days, treated with anti-IFNAR
• Infected with SARS-CoV-2 for 2 days 

• Infected with SARS-CoV-2 for 4 days 

• Measurements from lung tissue  

• Quantification of LY-6G neutrophils by morphometry 

• RT-PCR for OAS2 mRNA (assessment of the successful blockade of IFN-I signaling by IFNAR antibody) 

• Viral titers by quantification of infectious virus in cell culture (assessment of the successful blockade of IFN-I signaling by IFNAR antibody) 

• Isolation of LY-6G neutrophils from lung tissue 

• Quantification of the number of isolated LY-6G neutrophils 

• Repeating measurement of caspase1 activity 

• Repeating RT-PCR for caspase1 and IL-1b mRNA

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

Reviewer #1:

IFN-I promotes immune responses to diverse viruses. Some of them have evolved to dampen IFN-I responses in order to weaken or delay antiviral responses. A number of studies support the idea that this could be the case of SARS-CoV-2 (0.1038/s41586-022-04447-0, 10.1016/j.it.2021.02.003, 10.1038/s41467-022-34895-1, to cite a few). The authors should refer to some of these studies to counterbalance the statements of increased IFN-I response in severe COVID-19 patients in some parts of the manuscript, such as in the Discussion.

Response: This is a good point and we added discussion on this topic.

Revised manuscript, discussion section, between lines 634-648:

“It should be noted that several SARS-CoV-2 encoded proteins have been shown to inhibit IFN-I signaling (60). However, no evidence suggests that neutrophils can be infected by SARS-CoV-2 and therefore it seems unlikely that such direct virus mediated effects could play a role in the observed neutrophil unresponsiveness to IFN-I.  

The dualistic nature of the IFN-I response in COVID-19 has been recognized previously. It seems that a strong initial IFN-I response to SARS-CoV-2 is more likely to result in asymptomatic or mild COVID-19 whereas a decreased initial IFN-I activity, due to e.g. genetic defects or increased levels of IFN-I autoantibodies, can lead to more severe COVID-19 (61). This initial beneficial effect of IFN-I is probably due to its ability to limit viral replication at early stages of the infection. However, at later stages of the disease IFN-I can be detrimental by promoting inflammatory pathways instead of direct antiviral effects (62). Thus, similarly to the IFN-I response in general, the role of neutrophil inflammasomes in development and severity of COVID-19 might be dualistic in nature with an initial protective effect while damaging when sustained for prolonged periods.”

1. Rashid F, et al. Roles and functions of SARS-CoV-2 proteins in host immune evasion [preprint]. Front Immunol. 2022;13. https://doi.org/10.3389/fimmu.2022.940756.
2. da Silva RP, et al. Circulating Type I Interferon Levels and COVID-19 Severity: A Systematic Review and Meta-Analysis. Front Immunol. 2021;12. https://doi.org/10.3389/fimmu.2021.657363.
3. Smith N, et al. Defective activation and regulation of type I interferon immunity is associated with increasing COVID-19 severity. Nat Commun. 2022;13(1). https://doi.org/10.1038/s41467-022-34895-1.

In Fig 5, the authors stimulate PMNs from healthy controls in vitro with IFN-I and use mainly IL-1b as a readout for neutrophil priming. The authors should analyse whether IFN-I-mediated priming ultimately leads to NETosis, given the relevance of NETs to COVID-19 pathology (10.1016/j.tips.2023.06.007), which is acknowledged by the authors in the Introduction.

Response: We agree that NETosis is a potential outcome of neutrophil activation. This is in part why we assayed for the release of MPO, which can be used as a marker of NETosis, in the ex vivo activated PMNs. However, while a clear increase in MPO levels was observed in response to nigericin treatment, no increase was seen with IFN-I or LPS treatments alone in COVID-19 or HC PMNs (Fig. 4C). We slightly modified the text to make it clearer that MPO served to detect PMN degranulation and NETosis in our study. 

Revised manuscript, results section, lines 440-444:

“However, the release of myeloperoxidase (MPO), used as a marker of degranulation and/or NETosis, in response to nigericin was similar between COVID-19 PMNs and HC PMNs, and therefore the observed diminished IL-1β release by COVID-19 PMNs is not due to general cellular inertia but may be specific to the ex vivo induced inflammasome pathway.”

In Methods (Histology and immunohistochemistry), the authors mention that histone H3 is a NET marker and use this in Supp Fig 5 to support evidence of NETosis. The authors should state which antibody clone/company was used. Histone H3 is expressed in high levels by non-NETotic neutrophils. Citrullinated histone H3 (CitH3), on the other hand, is detectable by few commercially available antibodies and can be used as a NET marker in conjunction with other markers such as DNA staining (10.1084/jem.20201129).

Response: For immunohistochemical detection of NETosis, we have used the following antibody: rabbit anti-histone H3 (citrulline R2 + R8 + R17; Abcam). We have provided a reference to a publication of a co-author (Schmid AS, et al. Antibody-based targeted delivery of interleukin-4 synergizes with dexamethasone for the reduction of inflammation in arthritis. Rheumatology (United Kingdom). 2018;57(4):748–755. Doi: 10.1093/rheumatology/kex447) which includes this information and fully describes the staining protocol. We admit that our labelling of the figure and the text was misleading by stating that the used antibody was anti-histone H3 instead of indicating that an antibody detecting citrullinated form of histone H3 was used. We have therefore relabeled Supplementary Fig. 7 and rewritten the text to indicate this more clearly.

In the publication kindly referred to by the reviewer, the following antibody was used: rabbit anti-histone H3 (H3Cit; Abcam; cat. ab5103; 1:500) in immunofluorescence, where DAPI fluorescence served to highlight the DNA. We generally work with immunohistochemistry instead of immunofluorescence as it allows better alignment with histopathological features. However, we have now applied the anti-H3cit antibody in a fluorescence protocol, using the same tissues and antibody as shown in the immunohistochemistry image of suppl. Fig7, to indicate that the used antibody works equally well in immunofluorescence and immunohistochemistry.

In the PDF version of this revision there is a figure plate that shows: NET IHC, showing abundant expression in the lumen of a bronchiole (top) and NET IF, showing part of a bronchiole with NET (green) and nuclei (DAPI; blue) and a closer view (bottom) with NET expression in a cell with the nuclear morphology of a neutrophil (arrowhead).

In Fig 8, the authors show that neutrophils migrate to the lungs of infected animals. This finding is showed in many previous studies and does not seem to favour the structure of the manuscript. Insteand, it seems it would fit a Supp Fig better, or a portion of the following figure.

Response: We are aware that neutrophil recruitment into the lungs with SARS-CoV-2 infection has been shown previously. However, this was so far not done in the model that we have used, mouse-adapted SARS-CoV-2 infection in wild type (BALB/C) mice in which the infection is short-lived and wanes off after 4 days (Gawish et al., 2022). We are happy to move this figure plate to the Supplements as Reviewer #2 shares this opinion. In the revised manuscript, it now features as Supplementary Fig. 6.

Reviewer #2:

Major points:

-Figure 2A: for this RNAseq analysis, the authors claim that "This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils (Figure 2A)". Nevertheless, there are 2 samples in the "Severe COVID-19" group that show a fraction of neutrophils {less than or equal to}0.6, which indicates low levels of purity. In addition, there is one "PMN" sample with high LDG fraction (around 40%). Authors should remove from this analysis samples with such a low purity since the big fraction ({greater than or equal to}40%) of contaminating cells could introduce a bias in this group. Are the differences observed still present in the absence of these low-purity samples?

Response: For Figure1 of the original manuscript, we first performed the analyses including all the samples, and after assessing their purity, included only the samples with highest purity in the following figures. However, we followed the reviewer’s recommendation and redefined the purity of the samples as >65% of total neutrophils, independent of their maturity. Of note, unlike the reviewer suggests, we did not remove the one “PMN” sample with high degree of immaturity, since PMNs and LDGs are defined based on their isolation method and not their degree of maturity. Along these lines, we have decided to move the new unsupervised heatmap and present it together with the RNA deconvolution plot as supplementary Figure 1. Therefore, Figure 1 now contains the samples with high purity based on the redefined criteria, with PCA in panel A, pathway analyses in panel B (PMN vs LDG) and interferon-related genes heatmap in panel C. We also redid suppl Fig. 2 to include samples with the redefined criteria and modified the results text accordingly.

Revised manuscript, results section, lines 333-380:

“Unsupervised RNA-seq analysis reveals an antiviral gene expression signature of circulating neutrophils in COVID-19 that is strongly influenced by maturity

With our recent findings on increased frequencies of low-density granulocytes (LDGs, isolated from the PBMC fraction) during COVID-19 and their likely relevant role in disease progression (7), we sought to understand in more detail how the transcriptomic profile of LDGs differs from their higher “normal” density counterpart, the circulating polymorphonuclear cells (PMNs) (31), typically consisting mainly of mature neutrophils. Neutrophils isolated from different cohorts comprised three PMN groups (severe COVID-19, mild COVID-19, and healthy controls), and one LDG group. Initial deconvolution of the RNA sequencing (RNA-seq) data allowed us to gain a comprehensive understanding of the cellular composition within PMN and LDG fractions and verified that most cells present in the samples were neutrophils (Supplementary Figure 1A). This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils.

The samples with predominant neutrophil cell populations were selected for subsequent gene expression analysis (neutrophils ≥ 65 %). The high variance in gene expression between PMNs and LDGs was confirmed by principal component analysis (PCA) (Figure 1A), which revealed that the gene expression patterns of COVID-19 LDGs differed from those of all PMNs regardless of the patients’ disease state. Functional enrichment analyses through gene overrepresentation (ORA) and gene-set enrichment analyses (GSEA) (Figure 1B) compared PMNs with LDGs from severe COVID-19 patients. The most statistically significant result was an overrepresentation of the NOD-like receptor signaling pathway in PMNs in contrast with LDGs, highlighting that the different neutrophil fractions have a distinct inflammatory profile. This was supported by GSEA, where the most obvious increases in fold changes were the enrichment of the interferon signaling pathways. Another relevant difference was the cell cycle and DNA replication pathways, identified by both ORA and GSEA, which supported our previous findings suggesting LDGs to be predominantly immature cells (7). Furthermore, a heatmap of selected type I IFN (IFN-I) related genes confirmed a robust IFN-I gene signature in severe COVID-19 PMNs, while LDGs from severe COVID-19 distinctively lacked this signature (Figure 1C). Unsupervised clustering analysis, namely Iterative Clustering and Guide Gene Selection (ICGS) using the AltAnalyze software, supported these findings by identifying the top 118 differentially expressed (DE) genes, including several IFN-related genes (Supplementary Fig. 1B). Similarly to the selected samples included in Figure 1, this analysis classified the samples into two major clusters: a first one containing all isolated LDG samples, and a second one comprising all isolated PMN samples. The former cluster consisted of neutrophil antimicrobial and granule marker genes (e.g. DEFA3, DEFA4, SERPINB10, CTSG), while in the latter cluster the most significantly upregulated genes in the PMNs from severe COVID-19 subgroup were mainly interferon inducible (e.g. IFI44L, IFI6, GBP3, IRF7). These differences were supported by a detailed gene analysis (Supplementary Fig. 2A).

Inflammasomes are activated in severe COVID-19 PMNs, but not directly by SARS-CoV-2

Looking more closely into PMN fractions, pathway analyses identified the inflammasome related NOD-like and RIG-like receptor signaling pathways among the most significantly overrepresented pathways, differentially expressed in severe COVID-19 PMNs versus HC PMNs (Figure 2A and Supplementary Fig. 2B-C) or mild COVID-19 PMNs (Figure 2B and Supplementary Fig. 2D, E). However, mild COVID-19 PMNs did not significantly differ from HC PMNs in their inflammatory profile (Supplementary Fig. 2F).”

Finally, to respond to the reviewer’s specific question concerning whether the observed differences are still present in the absence of the newly defined low-purity samples, we can conclude that the results continue to highlight the differences we had previously described (increased cell cycle and metabolism-related pathways in LDGs and a distinct IFN-I signature in severe COVID-19 PMNs). 

- While the in vitro data suggest that IFN-I may prime the inflammasome response in neutrophils, in vivo evidence remains inconclusive. The systemic blockade of IFNAR1 with antibodies in infected mice does not confirm that IFN-I directly primes neutrophil inflammasomes, as other cells could initially sense IFN-I and subsequently produce neutrophil-activating stimuli. In the absence of in vivo experiments utilizing conditional IFNAR1 knockout models, such as Mrp8-Cre x IFNAR1 fl/fl mice, the authors should consider moderating the stated significance of these findings in the discussion about the limitations of the study.

Response: We agree with the reviewer on this point. Thus, we modified the “limitations of study” paragraph in the discussion.

Revised manuscript, discussion section, lines 674-677:

“Furthermore, the observed inhibitory effects on neutrophil inflammasome activity by IFNAR blockade does not exclude the possibility that IFN-I could promote neutrophil inflammasome formation by indirect effects such as stimulating the release of pro-inflammatory cytokines by other cell types.” 

- Given the reports of life-threatening COVID-19 infections occurring in conjunction with autoantibodies against type I IFNs (DOI: 10.1126/science.abd4585), the authors should explore how this intersects with their findings. A discussion is needed on whether patients with such autoantibodies may exhibit inflammasome activation patterns similar to the severe cases in this study, which could provide valuable insights into patient stratification and treatment approaches.

Response: This is a good point, thank you. Based on our data it is unlikely that patients with IFN-I autoantibodies or genetic defects in the production of IFN-I would show significant neutrophil inflammasome activation. Like with IFN-I response in general, neutrophil inflammasomes can probably be either protective or damaging to the host, depending on the context and durability of the response. We have discussed this topic further in the revised manuscript, in response to this concern and the first point of reviewer 1.

Revised manuscript, discussion section, lines 639-648:

“The dualistic nature of the IFN-I response in COVID-19 has been recognized previously. It seems that a strong initial IFN-I response to SARS-CoV-2 is more likely to result in asymptomatic or mild COVID-19 whereas a decreased initial IFN-I activity, due to e.g. genetic defects or increased levels of IFN-I autoantibodies, can lead to more severe COVID-19 (61). This initial beneficial effect of IFN-I is probably due to its ability to limit viral replication at early stages of the infection. However, at later stages of the disease IFN-I can be detrimental by promoting inflammatory pathways instead of direct antiviral effects (62). Thus, similarly to the IFN-I response in general, the role of neutrophil inflammasomes in development and severity of COVID-19 might be dualistic in nature with an initial protective effect while damaging when sustained for prolonged periods.” 

- The authors need to delve deeper into whether the inflammasome patterns observed in severe COVID-19 cases are a contributing factor to the disease's progression or a result of the infection's severity, thereby clarifying the causality in their discussion.

Response: This is an important aspect of the study and we agree that the relationship between neutrophil inflammasome activity and disease severity could be highlighted better. However, understanding causality by analyzing clinical patient samples is difficult due to the typical lack of patient samples from the early phase of the disease. Hospitalization and thereby patient sample collection typically occurs when the patients are already experiencing the peak of symptomatic phase of the disease. To highlight the link between neutrophil inflammasome formation and disease severity more clearly, we have marked the statistically significant correlations between inflammasome activation and disease severity parameters by an asterisk in the correlation plot (Fig. 5) and added text in the discussion accordingly.

Revised manuscript, discussion section, lines 649-654:

“Our study demonstrated a strong association between PMN caspase1 activity and plasma levels of calprotectin, a marker of neutrophil activation. Additionally, increased disease severity, as assessed by the WHO ordinal scale, was significantly linked to PMNs being less responsive to ex vivo IFN-induced inflammasome activation, which is suggestive of prior in vivo inflammasome activation. Thus, these results suggest that neutrophil inflammasomes play a potential role in disease severity rather than being protective in COVID-19.” 

This point links to the previous comment by the reviewer regarding the role of IFN-I in disease severity. We have added text in the discussion highlighting the dual nature of the IFN-I response and neutrophil inflammasome activation in COVID-19 disease severity (see response above).     

-Authors should clarify if and how their findings may lead to any therapeutic advantage for severe COVID-19 patients.

Response: The text has been adapted accordingly, and more details have been added into the revised manuscript.

Revised manuscript, discussion section, lines 685-687:

“For example, pharmacologically targeting the inflammasome pathway in neutrophils with novel inhibiting molecules, may help mitigate the exaggerated inflammatory response observed in severe cases.”

Reference added: Mangan, M. S., Olhava, E. J., Roush, W. R., Seidel, H. M., Glick, G. D., & Latz, E. (2018). Targeting the NLRP3 inflammasome in inflammatory diseases. Nature reviews Drug discovery, 17(8), 588-606.

Minor points:

- Authors should increase the font in all the figures as most of them are difficult to be read

Response: Thank you for your suggestion. The font sizes have been increased, but their size will ultimately depend on the requirements of the journal where is the work will be published.

Thank you for your suggestion. The font sizes have been increased, but their size will ultimately depend on the requirements of the journal where the work will be published.

- Authors should better clarify how the choice for statistics tests was conducted "depending on sample distribution and the number of groups analyzed" in the Methods.

Response: We added additional details to the methods.

Revised manuscript, methods section, lines 329-331:

“To elaborate, nonparametric tests like Mann-Whitney and Kruskall-Wallis were employed when the data violated assumptions of normality, while ANOVA tests were applied when the data met parametric assumptions”. 

Referee Cross-Commenting*

-I agree with Reviewer#1 with adding relevant references about the evolution of some viruses, including SARS-COV-2, in evading type I IFN response.

Response: We added this information into the manuscript.

Revised manuscript, discussion section, lines 635-638:

“It should be noted that several SARS-CoV-2 encoded proteins have been shown to inhibit IFN-I signaling. However, no evidence suggests that neutrophils can be infected by SARS-CoV-2 and therefore it seems unlikely that such direct virus mediated effects could play a role in the observed neutrophil unresponsiveness to IFN-I".   

Reference added: Rashid F, et al. Roles and functions of SARS-CoV-2 proteins in host immune evasion [preprint]. Front Immunol. 2022;13.

-I agree with Reviewer#1 about Figure 8 not delivering a novel message. I also suggest to move this to the supplementary section.

Response: We have moved the figure plate to the Supplements. 

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

Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

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Referee #2

Evidence, reproducibility and clarity

The authors of this study seek to examine the role of neutrophils, particularly their inflammasome formation potential, in the pathophysiology of COVID-19. They conducted transcriptomic profiling of neutrophils from both mild and severe COVID-19 patients, as well as SARS-CoV-2 infected mice, and compared these profiles to non-infected healthy controls. Their analysis confirmed a prominent IFN-I gene signature in severe cases previously reported by others. Furthermore, they observed that neutrophils from severe COVID-19 patients have an altered response to inflammasome activation and that IFN-I can serve as a priming stimulus for neutrophil inflammasomes, a finding further supported by a COVID-19 mouse model. Last, in this study the authors revealed that in severe COVID-19, LDGs show gene upregulation indicating immaturity, while PMNs exhibit enhanced pathogen-responsive NLR signaling.

Major points:

• Figure 2A: for this RNAseq analysis, the authors claim that "This analysis also demonstrated that cells in the LDG fraction were predominantly immature neutrophils, meanwhile PMNs were composed of mainly mature neutrophils (Figure 2A)". Nevertheless, there are 2 samples in the "Severe COVID-19" group that show a fraction of neutrophils {less than or equal to}0.6, which indicates low levels of purity. In addition, there is one "PMN" sample with high LDG fraction (around 40%). Authors should remove from this analysis samples with such a low purity since the big fraction ({greater than or equal to}40%) of contaminating cells could introduce a bias in this group. Are the differences observed still present in the absence of these low-purity samples?

• While the in vitro data suggest that IFN-I may prime the inflammasome response in neutrophils, in vivo evidence remains inconclusive. The systemic blockade of IFNAR1 with antibodies in infected mice does not confirm that IFN-I directly primes neutrophil inflammasomes, as other cells could initially sense IFN-I and subsequently produce neutrophil-activating stimuli. In the absence of in vivo experiments utilizing conditional IFNAR1 knockout models, such as Mrp8-Cre x IFNAR1 fl/fl mice, the authors should consider moderating the stated significance of these findings in the discussion about the limitations of the study.

• The authors are encouraged to specify the number of independent experiments conducted. For mouse model studies, it is recommended to include results that are either representative of, or aggregated from, a minimum of two independent experiments to ensure robustness of the data

• The authors are advised to employ more quantitative methods, such as flow cytometry, to measure neutrophil recruitment in mice. Additionally, it should be clarified how many tissue sections from each mouse were assessed for every experimental condition to ensure the reproducibility and statistical validity of the results.

• The authors need to address discrepancies in their text regarding the effects of anti-IFNAR1 blockade on viral titers and neutrophil recruitment in SARS-CoV-2 infected mice. While they state there is no change, Supplementary Figure 5D suggests increased SARS-CoV-2 NP staining with anti-IFNAR1 treatment, and there appears to be a lack of quantitative data on lung neutrophils to substantiate the claim that neutrophil recruitment remains unaffected. It is necessary for the authors to provide a more detailed explanation or additional data to resolve these inconsistencies

• The authors should demonstrate the effectiveness of anti-IFNAR1 blockade in mice by providing evidence of sustained inhibition of IFN-I signaling throughout the duration of the experiment to validate the treatment protocol used.

• Given the reports of life-threatening COVID-19 infections occurring in conjunction with autoantibodies against type I IFNs (DOI: 10.1126/science.abd4585), the authors should explore how this intersects with their findings. A discussion is needed on whether patients with such autoantibodies may exhibit inflammasome activation patterns similar to the severe cases in this study, which could provide valuable insights into patient stratification and treatment approaches

• The authors need to delve deeper into whether the inflammasome patterns observed in severe COVID-19 cases are a contributing factor to the disease's progression or a result of the infection's severity, thereby clarifying the causality in their discussion.

• Authors should clarify if and how their findings may lead to any therapeutic advantage for severe COVID-19 patients.

Minor points:

• Authors should increase the font in all the figures as most of them are difficult to be read

• Authors should better clarify how the choice for statistics tests was conducted "depending on sample distribution and the number of groups analyzed" in the Methods.

Referee Cross-Commenting

• I agree with Reviewer#1 with adding relevant references about the evolution of some viruses, including SARS-COV-2, in evading type I IFN response.

• I agree with Reviewer#1 about trying to dissect the role of IFNAR-1 vs IFNAR-2. Authors partially look at this in the in vivo mice experiments using the anti-IFNAR1 blocking Ab, but it would reinforce the study to see if this holds with human cells.

• I agree with Reviewer#1 about Figure 8 not delivering a novel message. I also suggest to move this to the supplementary section.

Significance

• The study presents an investigation into the role of neutrophils and inflammasome formation in COVID-19 pathology, contributing to the field with transcriptomic profiling of neutrophils from varying severity of patient cases and a SARS-CoV-2 mouse model. A significant IFN-I gene signature in severe cases was confirmed, and differences in inflammasome response were identified, adding to our understanding of disease mechanisms.

• Strengths of the paper include the comprehensive analysis of neutrophil maturation states and the novel insights into the priming of inflammasome activation by IFN-I. However, limitations were noted in the purity of samples for RNAseq analysis and the lack of conclusive in vivo evidence for the direct role of IFN-I in neutrophil inflammasome priming. The study's implications suggest potential avenues for targeted therapies, but the authors were advised to moderate their conclusions without stronger in vivo evidence and to clarify the potential therapeutic implications of their findings.

• Additional suggestions for improvement include the use of more quantitative methods like flow cytometry for neutrophil recruitment measurements, clarification on experimental replication, and resolving discrepancies in data presentation regarding anti-IFNAR1 blockade effects. Furthermore, the paper would benefit from discussing the relevance of autoantibodies against IFN-I in the context of their findings and from exploring the causal relationship between inflammasome patterns and disease severity.

• The study is of relevance to immunologists specializing in viral infections and researchers focused on neutrophil biology.

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Referee #1

Evidence, reproducibility and clarity

• IFN-I promotes immune responses to diverse viruses. Some of them have evolved to dampen IFN-I responses in order to weaken or delay antiviral responses. A number of studies support the idea that this could be the case of SARS-CoV-2 (0.1038/s41586-022-04447-0, 10.1016/j.it.2021.02.003, 10.1038/s41467-022-34895-1, to cite a few). The authors should refer to some of these studies to counterbalance the statements of increased IFN-I response in severe COVID-19 patients in some parts of the manuscript, such as in the Discussion.

• In Fig 5, the authors stimulate PMNs from healthy controls in vitro with IFN-I and use mainly IL-1b as a readout for neutrophil priming. The authors should analyse whether IFN-I-mediated priming ultimately leads to NETosis, given the relevance of NETs to COVID-19 pathology (10.1016/j.tips.2023.06.007), which is acknowledged by the authors in the Introduction. It would also be interesting to explore the involvement of IFN-I receptors (IFNAR1 vs IFNAR2) by dissecting IFN-a from IFN-b responses.

• In Methods (Histology and immunohistochemistry), the authors mention that histone H3 is a NET marker and use this in Supp Fig 5 to support evidence of NETosis. The authors should state which antibody clone/company was used. Histone H3 is expressed in high levels by non-NETotic neutrophils. Citrullinated histone H3 (CitH3), on the other hand, is detectable by few commercially available antibodies and can be used as a NET marker in conjunction with other markers such as DNA staining (10.1084/jem.20201129).

• In Fig 8, the authors show that neutrophils migrate to the lungs of infected animals. This finding is showed in many previous studies and does not seem to favour the structure of the manuscript. Instead, it seems it would fit a Supp Fig better or a portion of the following figure.

Significance

By conducting transcriptomics analyses, Cabrera LE et al. elucidate the inflammasome formation in neutrophils during SARS-CoV-2 infection. The authors have found a strong IFN-I signature in neutrophils from severe COVID-19 patients and show that IFN-I functions as a priming stimulus for neutrophil inflammasome.

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1. General Statements

We thank the reviewers for their excellent work that greatly improved our work. We are very content that reviewer #1 considered our work to be “novel, interesting and important for understanding the mitochondrial biology of PD”. This reviewer also valued our work as “a significant advancement” and suggested further study of the relationship of CISD1 (dimerization) to general mitophagy/autophagy. We addressed this in the already transferred revision (version 1, v1).

Also reviewer #2 considered our work to be “an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate”. This reviewer had a very specific suggestion on how to improve our manuscript which makes a lot of sense and is feasible. As the suggested experiments include fly breeding and behavioral analysis, these experiments will be included in the second revision to be uploaded as soon as possible (version 2, v2).

Finally, reviewer #3 gathered that parts of our results “are confirmatory to recently published work” but also appreciated that our results established that iron-depleted apo-Cisd is an important determinant of toxicity which has not been shown before. I would like to comment here, that in contrast to the paper mentioned by this reviewer, our contribution includes data from dopaminergic neurons obtained from human patients suffering from familial Parkinson’s disease that demonstrate the same increase in apo-Cisd levels as the flies. This reviewer mainly suggested that the manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data which we did in the revised version of our manuscript. We also added data on the expression levels of Cisd and apo-Cisd in transgenic flies as also suggested.

2. Description of the planned revisions

Reviewer #1 (Evidence, reproducibility and clarity):

Summary: The manuscript focuses on mitochondrial CISD1 and its relationship to two Parkinson's disease (PD) proteins PINK1 and Parkin. Interestingly, CISD1 is a mitochondrial iron sulfur binding protein and an target of Parkin-mediated ubiquitinylation. Disruption of iron metabolism and accumulation of iron in the brain has long since been reported in PD but the involvement of iron sulfur binding is little studied both in vivo and in human stem cell models of PD. This work addresses the relationship between CISD1 and two mitochondrial models of PD (PINK1 and Parkin) making use of in vivo models (Drosophila), PINK1 patient models (iPSC derived neurons) and Mouse fibroblasts. The authors report a complex relationship between CISD1, PINK1 and Parkin, where iron-depleted CISD1 may illicit a toxic gain of function downstream of PINK1 and Parkin.

Major comments:

The conclusions are overall modest and supported by the data. One question remains unaddressed. Is mitochondrial CISD1 a downstream target that specifically mediates PINK1 and Parkin loss of function phenotypes or are the phenotypes being mediated because CISD1 is downstream of mitophagy in general?

It would be interesting to know what happens to CISD1 (dimerization?) upon initiation of mitophagy in wild type cells? Would dissipation of mitochondrial membrane potential be sufficient to induce changes to CISD1 in wild type cells or PINK1 deficient cells? Since iron chelation is a potent inducer of mitophagy (Loss of iron triggers PINK1/Parkin-independent mitophagy. George F G Allen, Rachel Toth, John James, Ian G Ganley. EMBO Reports (2013)14:1127-1135) it would be useful to show one experiment addressing the role of CISD1 dimerization under mitochondrial depolarizing and non-depolarizing conditions in cells.

Based on the overall assumption of the reviewer that our work is “novel, interesting and important for understanding the mitochondrial biology of PD” and “a significant advancement” we understand the word “modest” here as meaning “not exaggerated”. To address this question, we studied CISD1 dimerization in response to more classical activators of mitophagy namely FCCP and antimycin/oligomycin which had no significant effect on dimerization suggesting that this phenotype is more pronounced under iron depletion. These data are shown in the new Fig. 2c.

Alternatively, the authors should discuss the topic of mitophagy (including PINK1-parkin independent mitophagy), the limitation of the present study not being able to rule out a general mitophagy effect and previous work on the role of iron depletion on mitophagy induction in the manuscript.

The data and the methods are presented in such a way that they can be reproduced.

The experiments are adequately replicated and statistical analysis is adequate.

Minor comments:

Show p values even when not significant (ns) since even some of the significant findings are borderline < p0.05.

Here, I decided to leave it as it is, because the figures became very cluttered and less easy to understand. Borderline findings are however indicated and mentioned in the text.

Because the situation for CISD1 is complicated (overexpression, different models etc.) it would be helpful if in the abstract the authors could summarize the role. E.g. as in the discussion that iron-depleted CISD1 could represent a toxic function.

The abstract has been completely rewritten and now mentions the potential toxic function of iron-depleted CISD1.

If there is sufficient iron (accumulation in PD) why would CISD1 be deactivated? Perhaps that could be postulated or discussed in a simplified way?

We actually think that apo-CISD1 without its iron/sulfur cluster is incapable of transferring its Fe/S cluster to IRP1 and IRP2. This then results in increased levels of apo-IRP1/2 and subsequent changes that lead to iron overload. Such a sequence of events would place CISD1 upstream of the changes in iron homeostasis observed in PD and models of PD. This is now discussed in more detail.

In the methods section both reducing and non-reducing gel/Western blotting is mentioned but the manuscript only describes data from blots under reducing conditions. Are there blots under non-reducing conditions that could be shown to see how CISD1 and dimerized CISD1 resolve?

We now show these blots as supplemental data in new supplemental Figure 2.

In the results section, PINK1 mutant flies, it is said that the alterations to CISD1 (dimerization) are analogous to the PINK1 mutation patient neurons. The effect is seen in old but not young flies. Since iPSC-derived neurons are relatively young in the dish, would one not expect that young flies and iPSC-derived neurons have similar CISD1 phenotypes? Could the authors modify the text to reflect that? or discuss the finding in further context.

We only studied one time point in PINK1 mutation patient neurons and controls. It would indeed be interesting whether neuronal aging (as far as this can be studied in the dish) would result in increased CISD1 dimerization. This is now discussed.

Reviewer #1 (Significance):

The strengths of this work are in the novelty of the topic and the use of several well established in vivo and cell models including patient-derived neurons. The findings discussed in the text are honest and avoid over-interpretation. The findings are novel, interesting and important for understanding the mitochondrial biology of PD.

We thank the reviewer for their kind words.

Limitations include the lack of strong phenotypes in the CISD1 models and the lack of robust, sustained and consistent increase in CISD1 dimers in the patient and fly models (just significant because of variability). The relationship of CISD1 (dimerization) to general mitophagy/autophagy is not shown here.

We do not completely agree with the assumption that all CISD1 models lack a strong phenotype. At least the CISD1-deficient fibroblasts exhibit a strong phenotype consisting of fragmented mitochondria and increased oxidative stress. The lack of a strong phenotype in Cisd-deficient flies could actually hint to a potential compensatory mechanism that could also protect the Pink1 mutant x Cisd-deficient double-knockout flies. It is correct that the increase in CISD1/Cisd dimers in the PD models are not overwhelming but – as also mentioned by the reviewer – this could be increased in “older” cultures. This is now discussed in more detail. As suggested by the reviewer, we have now added experiments that study the relationship between CISD1 dimerization and conventional mitophagy as described above.

There is a significant advancement. So far researchers were able to describe the importance of iron metabolism in PD (For example refer to work from the group of Georg Auburger such as PMID 33023155 and discussion of therapeutic intervention such as reviewed by Ma et al. PMID: 33799121) but few papers describe involvement of iron sulfur cluster proteins specifically (such as Aconitase) in relation to PINK1 and parkin (these are cited). The fact that CISD1 is a protein of the mitochondrial outer membrane makes it particularly interesting and further studies looking more closely at the interaction of CISD1 with mitochondrial proteins associated with PD will be of interest.

We thank the reviewer for pointing out these excellent publications. Key et al present an enormous wealth of data on protein dysregulation of wildtype and Pink1-/- fibroblast cell lines upon perturbation of the iron homeostasis (Key et al, 2020). Both cell lines exhibit a downregulation of CISD1 levels upon iron deprivation with the agent 2,2′ -Bipyridine possibly as a compensatory mechanism to limit the toxic gain of function of iron-depleted CISD1. The other paper, Ma et al. is a recent review on changes in iron homeostasis in PD and PD models (Ma et al, 2021). Both papers are now cited in the manuscript.

This paper describes CISD1 as a new and relevant player in PINK1 and Parkin biology. Further work could lead to exploration of whether CISD1 could be a therapeutic target, considering its role in maintaining mitochondrial redox and mitochondrial health. This is of particular interest to mitochondrial biologists and pre-clinical research in PD.

This preprint was reviewed by three scientists whose research focus in the mitochondrial biology underlying Parkinson's disease. The group has a special interest in the functions of the mitochondrial outer membrane. We work with several cell models of Parkinson's disease and work with patient donated samples. We do not have expertise in Drosophila models of PD nor the quantification of iron described in the manuscript.

Reviewer #2 (Evidence, reproducibility and clarity):

Summary: In the paper entitled 'Mitochondrial CISD1 is a downstream target that mediates PINK1 and Parkin loss-of-function phenotypes', Bitar and co-workers investigate the interaction between CISD1 and the PINK1/Parkin pathway. Mutations in PINK1 and PARKIN cause early onset Parkinson's disease and CISD1 is a homodimeric mitochondrial iron-sulphur binding protein. They observed an increase in CISD1 dimer formation in dopaminergic neurons derived from Parkinson's disease patients carrying a PINK1 mutation. Immuno-blots of cells expressing CISD1 mutants that affects the iron sulphur cluster binding and as well as cells treated with iron chelators, showed that the tendency of CISD1 to form dimers is dependent on its binding to iron-sulphur clusters. Moreover, the Iron-depleted apo-CISD1 does not rescue mitochondrial phenotypes observed in CISD1 KO mouse cells. Finally, In vivo studies showed that overexpression of Cisd and mutant apo-Cisd in Drosophila shortened fly life span and, using a different overexpression model, apo-Cisd caused a delay in eclosion. Similar as patient derived neurons, they observed an increase in Cisd dimer levels in Pink1 mutant flies. Additionally, the authors showed that double mutants of Cisd and Pink1 alleviated all Pink1 mutant phenotypes, while double mutants of Prkn and Cisd rescued most Prkn mutant phenotypes.

Major comments:

1) The authors observed an increase in the levels of Cisd dimers in Pink1 mutant flies and removing Cisd in Pink1 mutant background rescues all the mutant phenotypes observed in Pink1 mutant flies, suggesting that the Cisd dimers are part and partial of the Pink1 mutant phenotype. The authors also generated a UAS_C111S_Cisd fly which can overexpress apo-Cisd. Overexpression of the C111S_Cisd construct with Tub-Gal4 showed a developmental delay. Since apo-Cisd forms more dimeric Cisd, my question is: does the strong overexpression (e.g. with Tub-Gal4) of the C111S_Cisd in wild type flies shows any of the Pink1 mutant phenotypes? If not, the authors should mention this and elaborate on it.

We thank the reviewer for their comments. In fact, we only observed very few flies ecclosing after overexpression of wildtype Cisd or C111S Cisd using the strong tubP-Gal4 driver during development. We considered these very few flies to be escapees (also indicated by the rather low induction of Cisd mRNA suggesting compensatory downregulation) and only used them to conduct the analysis shown in Figure 4c-e. This is now mentioned in more detail in the manuscript.

2) Figure 6g: Shows the TEM pictures of the indirect flight muscles of Pink1 mutant flies and Pink1, Cisd double mutants. To me, the Picture of Pink1 mutant mitochondria is not very convincing. We expect swollen (enlarged) mitochondria with disrupted mitochondrial matrix. However, this is not clear in the picture. Moreover, in my opinion, Figure6 g, is missing an EM Picture of the Cisd mutant indirect flight muscles.

We now show exemplary pictures from Pink1 mutant and DKO in a higher magnification which better demonstrate the rounded Pink1 mutant mitochondria and the disrupted cristae structure. EM pictures of all four genotypes in different magnifications are now shown in new supplemental Figure 6.

3) OPTIONAL: The authors suggest that most probably apo-Cisd, assumes a toxic function in Pink1 mutant flies and serves as a critical mediator of Pink1-linked phenotypes. If this statement is correct, we can hypothesize that increasing apo-Cisd in Pink1 mutant background should worsen the pink1 mutant defects.

Therefore, I suggest overexpressing Cisd1 wild type (and/or C111S Cisd) in pink1 mutant flies, as pink1 is on the X chromosome, and mild overexpression of Cisd1 with da is not lethal, these experiments could be done in 3-4 fly crosses and hence within 1.5 - 2 months.

We have set up this experiment and will report in the second revision (v2) of our manuscript.

Since Pink1 mutant flies contain higher levels of endogenous Cisd dimers, we can expect that overexpression of wild type Cisd will result in an even stronger increase of dimers. If these dimers indeed contribute to Pink1 mutant phenotypes we can expect that overexpression of Cisd will result in a worsening of the Pink1 mutant phenotypes.

We have set up this experiment and will report in the second revision of our manuscript.

Minor Comments:

-) In the Introduction (Background) there are some parts without references:

E.g., there is not a single reference in the following part between

'However, in unfit mitochondria with a reduced mitochondrial membrane potential ...&... compromised mitochondria safeguards overall mitochondrial health and function.'

We thank the reviewer for pointing out this flaw. We have now added a suitable reference to the introduction.

-) In the introduction there is some confusion about the nomenclature used in the article: e.g. following comments are made in the text: Cisd2 (in this publication referred to as Dosmit) or fly Cisd2 (in this publication named MitoNEET).

However, the names Dosmit and MitoNEET do not appear in the manuscript (except in references)

The literature and nomenclature for CISD1 are indeed confusing. We have now revised the introduction.

-) Figure 1: I am not sure why some gels are shown in this figure. The two last lanes of figure 1c are redundant and Figure 1c' which is also not mentioned in the text, is also a repetition of figure 1c.

The blots in 1c and 1c’ represent all data points (different patients and different individual differentiations) shown in the quantification in 1d. This is now explained better in the revised manuscript.

-) The authors mention in material and methods that T2A sites are used at the C-terminus of CISD1 to avoid tagging of CISD1. However, this is not entirely true as T2A will leave some amino acids (around 20) after the self-cleaving and therefore CISD1 will be tagged.

This is indeed true and we have now changed the wording in the revised manuscript.

-) In figure 5 P1 is used to abbreviate Pink1 mutants, however P1, to me, refers to pink1 wild type. It would be clearer to abbreviate Pink1 mutants as P1B9 in the graphs as B9 is the name of the mutant pink1 allele.

We thank the reviewer for pointing out this flaw. We have now altered Fig. 5 to be clearer.

-) In figure 7: Parkin is abbreviated both as Prkn and as Park

We thank the reviewer for pointing out this flaw, we indeed mixed up both names because it is complicated. The gene symbol is Prkn, the fly line is called Park25. We have now clarified this in the text and Fig. 7.

-) I suggest changing the title. Recently an article (Ham et al, 2023 PMID: 37626046) was published showing similar genetic interactions between Pink1/Prkn and Cisd. However, the article of Ham et al, 2023 was focused on Pink1/Prkn regulation of ER calcium release, while this article is more related to iron homeostasis. I suggest that the title shows this distinction.

This is indeed a very good suggestion. We have now altered the title to “Iron/sulfur cluster loss of mitochondrial CISD1 mediates PINK1 loss-of-function phenotypes”.

Reviewer #2 (Significance):

In general, this is an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate. Very recently, a similar genetic interaction between Cisd and Pink1/Prkn in flies was published (Ham et al, 2023 PMID: 37626046) however, from a different angle. While, Ham et al focused on the role of Pink1/Prkn and Cisd in IP3R related ER calcium release, this manuscript approaches the Pink1/Prkn - Cisd interaction from an iron homeostasis point of view. Since, iron dysregulation contributes to the pathogenesis of Parkinson's disease, the observations in this manuscript are relevant for the disease. Hence, the work is sufficiently novel and deserves publication. However, additional experiments are suggested to strengthen the authors' conclusions.

We thank the reviewer for their kind words. As mentioned above, these additional experiments are on their way and will be included in version 2 of our revised manuscript (v2).

I work on Drosophila models of Parkinson's disease

Referees cross-commenting

I agree with the reviewer number 1 that it would be interesting to investigate CISD1 dimerisation status during mitophagy.

As mentioned above, we now studied CISD1 dimerization in response to more classical activators of mitophagy namely FCCP and antimycin/oligomycin which had no significant effect on dimerization suggesting that this phenotype is more pronounced under iron depletion. These data are shown in the new Fig. 2c.

Reviewer #3 (Evidence, reproducibility and clarity):

Here the authors provide evidence that Cisd is downstream of Parkin/Pink1 and suggest that the levels of apo-Cisd correlate with neurotoxicity. The data presented generally supports the conclusions of the authors and will be useful to those in the field. The manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data.

We thank the reviewer for their comments aimed to improve our manuscript. We have now discussed the strengths and weaknesses of our study in more detail.

Introduction. While iron has been implicated in Parkinson's disease, it is an overstatement to say that disruption in iron metabolism contributes significantly to the pathogenesis of the disease.

There is certainly a plethora of data implicating perturbed iron homeostasis in PD as also pointed out by reviewer #1. We have tried to tone down our wording in the text and added a recent review on the topic (Ma et al, 2021) as also suggested by reviewer #1.

Introduction. The discussion of the various names for Cisd2 is important, but confusing as written. Specifically, the use of "this" makes the wording unclear.

We thank the reviewer for pointing out this flaw. We have altered the wording in the introduction.

Methods. It would be preferable to use heterozygous driver lines or a more similar genetic control rather than w-1118.

The exact controls were indeed not well explained in the Methods section, this has been corrected in the revised version. In brief, homozygous driver and UAS lines were indeed used in Fig. 4, this will be addressed in the second revision of our manuscript together with the experiments reviewer #2 suggested. The data shown in Fig. 5, 6, and 7 all used w1118 as control because all other fly strains are on the same genetic background.

Page 10. It appears that the PINK1 lines have been described previously. The authors should clarify this point and ensure that the new data presented in the current manuscript (presumably the mRNA levels, Fig. 1a) is indicated, as well as data that is confirmatory of prior findings (Fig. 1b).

Yes, these PINK1 lines have been described previously as pointed out in the manuscript. The original paper did not quantify the PINK1 mRNA levels shown in Fig. 1a. The blots shown in Fig. 1b are from new differentiations and have also not been shown before but confirm findings published in Jarazo et al. (Jarazo et al, 2022). This has been clarified in the revised version of our manuscript.

Fig. 3 legend. There is a typographical error, "ne-way ANOVA."

We thank the reviewer for pointing out this flaw. This has been corrected in the revised version.

Page 15. The nature of the Pink1-B9 mutant should be specified.

We now added a supplemental Figure 1 that depicts the specific mutation in these flies.

Fig. 4. Levels of mutant and wild type Cisd should be compared in transgenic flies.

We now added a quantification of mutant and wildtype Cisd levels to the new Figure 4d.

Fig. 5b,d. The striking change seems to be the decrease in dimers in young Pink1 mutant animals, not the small increase in dimers in the older Pink1 mutants.

It is always difficult to find a “typical” picture that reflects all changes observed in quantitative data. This Figure actually shows a decrease of total Cisd levels in young flies in Fig. 5c but no difference of the dimer/monomer ratio in Fig. 5d.

Fig. 5f. Caution should be used in interpreting the results. Deferiprone has toxicity to wildtype flies (trend) and may simply be making sick Pink1 mutants sicker.

There is certainly a tendency for wildtype flies to thrive less in food containing deferiprone. To make this more obvious, we have now added the exact p value (0.0764, which we don’t consider borderline but a tendency) to this figure and mention this fact in the text.

Fig. 5e. The data are hard to interpret. The number of animals is very small for a viability study and the strains are apparently in different genetic backgrounds, though this is not clearly specified. The experiment in Supplementary Fig. 1 appears better controlled and supports the Pink1 data; however, a similar concern pertains to Fig. 7. The authors may thus wish to be more circumspect in their interpretation, especially of the Parkin data.

In Fig 5e we quantified total iron levels and the Fe3+/Fe2+ ratio using capillary electrophoresis-inductively coupled plasma mass spectrometry (CE-ICP-MS). Although indeed not so many flies were used in this quantification, the results are highly significant. If the reviewer was referring to Fig. 5f, we agree that this experiment was not well (to be honest, even wrongly explained) which we corrected in the revised version of this manuscript. We thank the reviewer for pointing out this flaw.

Reviewer #3 (Significance):

The major significance of the study is in putting downstream of Parkin/Pink1 (largely confirmatory to recently published work) and suggesting that the levels of apo-Cisd are an important determinant of toxicity. The work will be of interest to those in the field.

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

The changes already carried out and included in the transferred manuscript (v1) are indicated above in bold orange. All changes pending on ongoing experiments to be included in the second revision of the manuscript are indicated above in bold magenta.

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

All changes suggested by the reviewers were addressed (v1) or will be addressed (v2).

References

Jarazo J, Barmpa K, Modamio J, Saraiva C, Sabaté-Soler S, Rosety I, Griesbeck A, Skwirblies F, Zaffaroni G, Smits LM, et al (2022) Parkinson’s Disease Phenotypes in Patient Neuronal Cultures and Brain Organoids Improved by 2-Hydroxypropyl-β-Cyclodextrin Treatment. Mov Disord 37: 80–94

Key J, Sen NE, Arsović A, Krämer S, Hülse R, Khan NN, Meierhofer D, Gispert S, Koepf G & Auburger G (2020) Systematic Surveys of Iron Homeostasis Mechanisms Reveal Ferritin Superfamily and Nucleotide Surveillance Regulation to be Modified by PINK1 Absence. Cells 9

Ma L, Gholam Azad M, Dharmasivam M, Richardson V, Quinn RJ, Feng Y, Pountney DL, Tonissen KF, Mellick GD, Yanatori I, et al (2021) Parkinson’s disease: Alterations in iron and redox biology as a key to unlock therapeutic strategies. Redox Biol 41: 101896

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Referee #3

Evidence, reproducibility and clarity

Here the authors provide evidence that Cisd is downstream of Parkin/Pink1 and suggest that the levels of apo-Cisd correlate with neurotoxicity. The data presented generally supports the conclusions of the authors and will be useful to those in the field. The manuscript would be improved by a more balanced discussion of the strengths and weaknesses of the study and more circumspection in interpretation of data.

• Introduction. While iron has been implicated in Parkinson's disease, it is an overstatement to say that disruption in iron metabolism contributes significantly to the pathogenesis of the disease.

Introduction. The discussion of the various names for Cisd2 is important, but confusing as written. Specifically, the use of "this" makes the wording unclear.<br /> - Methods. It would be preferable to use heterozygous driver lines or a more similar genetic control rather than w-1118.<br /> - Page 10. It appears that the PINK1 lines have been described previously. The authors should clarify this point and ensure that the new data presented in the current manuscript (presumably the mRNA levels, Fig. 1a) is indicated, as well as data that is confirmatory of prior findings (Fig. 1b).<br /> - Fig. 3 legend. There is a typographical error, "ne-way ANOVA."<br /> - Page 15. The nature of the Pink1-B9 mutant should be specified.<br /> - Fig. 4. Levels of mutant and wild type Cisd should be compared in transgenic flies.<br /> - Fig. 5b,d. The striking change seems to be the decrease in dimers in young Pink1 mutant animals, not the small increase in dimers in the older Pink1 mutants.<br /> - Fig. 5f. Caution should be used in interpreting the results. Deferiprone has toxicity to wildtype flies (trend) and may simply be making sick Pink1 mutants sicker.<br /> - Fig. 5e. The data are hard to interpret. The number of animals is very small for a viability study and the strains are apparently in different genetic backgrounds, though this is not clearly specified. The experiment in Supplementary Fig. 1 appears better controlled and supports the Pink1 data; however, a similar concern pertains to Fig. 7. The authors may thus wish to be more circumspect in their interpretation, especially of the Parkin data.

Significance

The major significance of the study is in putting downstream of Parkin/Pink1 (largely confirmatory to recently published work) and suggesting that the levels of apo-Cisd are an important determinant of toxicity. The work will be of interest to those in the field.

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Referee #2

Evidence, reproducibility and clarity

Summary:

In the paper entitled 'Mitochondrial CISD1 is a downstream target that mediates PINK1 and Parkin loss-of-function phenotypes', Bitar and co-workers investigate the interaction between CISD1 and the PINK1/Parkin pathway. Mutations in PINK1 and PARKIN cause early onset Parkinson's disease and CISD1 is a homodimeric mitochondrial iron-sulphur binding protein. They observed an increase in CISD1 dimer formation in dopaminergic neurons derived from Parkinson's disease patients carrying a PINK1 mutation. Immuno-blots of cells expressing CISD1 mutants that affects the iron sulphur cluster binding and as well as cells treated with iron chelators, showed that the tendency of CISD1 to form dimers is dependent on its binding to iron-sulphur clusters. Moreover, the Iron-depleted apo-CISD1 does not rescue mitochondrial phenotypes observed in CISD1 KO mouse cells. Finally, In vivo studies showed that overexpression of Cisd and mutant apo-Cisd in Drosophila shortened fly life span and, using a different overexpression model, apo-Cisd caused a delay in eclosion. Similar as patient derived neurons, they observed an increase in Cisd dimer levels in Pink1 mutant flies. Additionally, the authors showed that double mutants of Cisd and Pink1 alleviated all Pink1 mutant phenotypes, while double mutants of Prkn and Cisd rescued most Prkn mutant phenotypes.

Major comments:

1. The authors observed an increase in the levels of Cisd dimers in Pink1 mutant flies and removing Cisd in Pink1 mutant background rescues all the mutant phenotypes observed in Pink1 mutant flies, suggesting that the Cisd dimers are part and partial of the Pink1 mutant phenotype. The authors also generated a UAS_C111S_Cisd fly which can overexpress apo-Cisd. Overexpression of the C111S_Cisd construct with Tub-Gal4 showed a developmental delay. Since apo-Cisd forms more dimeric Cisd, my question is: does the strong overexpression (e.g. with Tub-Gal4) of the C111S_Cisd in wild type flies shows any of the Pink1 mutant phenotypes? If not, the authors should mention this and elaborate on it.
2. Figure6 g: Shows the TEM pictures of the indirect flight muscles of Pink1 mutant flies and Pink1, Cisd double mutants. To me, the Picture of Pink1 mutant mitochondria is not very convincing. We expect swollen (enlarged) mitochondria with disrupted mitochondrial matrix. However, this is not clear in the picture. Moreover, in my opinion, Figure6 g, is missing an EM Picture of the Cisd mutant indirect flight muscles.
3. OPTIONAL: The authors suggest that most probably apo-Cisd, assumes a toxic function in Pink1 mutant flies and serves as a critical mediator of Pink1-linked phenotypes. If this statement is correct, we can hypothesize that increasing apo-Cisd in Pink1 mutant background should worsen the pink1 mutant defects.

Therefore, I suggest overexpressing Cisd1 wild type (and/or C111S Cisd) in pink1 mutant flies, as pink1 is on the X chromosome, and mild overexpression of Cisd1 with da is not lethal, these experiments could be done in 3-4 fly crosses and hence within 1.5 - 2 months.

Since Pink1 mutant flies contain higher levels of endogenous Cisd dimers, we can expect that overexpression of wild type Cisd will result in an even stronger increase of dimers. If these dimers indeed contribute to Pink1 mutant phenotypes we can expect that overexpression of Cisd will result in a worsening of the Pink1 mutant phenotypes.

Minor Comments:

1. In the Introduction (Background) there are some parts without references:<br /> E.g., there is not a single reference in the following part between<br /> 'However, in unfit mitochondria with a reduced mitochondrial membrane potential ...&... compromised mitochondria safeguards overall mitochondrial health and function.'
2. In the introduction there is some confusion about the nomenclature used in the article: e.g. following comments are made in the text: Cisd2 (in this publication referred to as Dosmit) or fly Cisd2 (in this publication named MitoNEET).<br /> However, the names Dosmit and MitoNEET do not appear in the manuscript (except in references)
3. Figure 1: I am not sure why some gels are shown in this figure. The two last lanes of figure 1c are redundant and Figure 1c' which is also not mentioned in the text, is also a repetition of figure 1c.
4. The authors mention in material and methods that T2A sites are used at the C-terminus of CISD1 to avoid tagging of CISD1. However, this is not entirely true as T2A will leave some amino acids (around 20) after the self-cleaving and therefore CISD1 will be tagged.
5. In figure 5 P1 is used to abbreviate Pink1 mutants, however P1, to me, refers to pink1 wild type. It would be clearer to abbreviate Pink1 mutants as P1B9 in the graphs as B9 is the name of the mutant pink1 allele.
6. In figure 7: Parkin is abbreviated both as Prkn and as Park
7. I suggest changing the title. Recently an article (Ham et al, 2023 PMID: 37626046) was published showing similar genetic interactions between Pink1/Prkn and Cisd. However, the article of Ham et al, 2023 was focused on Pink1/Prkn regulation of ER calcium release, while this article is more related to iron homeostasis. I suggest that the title shows this distinction.

Referees cross-commenting

I agree with the reviewer number 1 that it would be interesting to investigate CISD1 dimerisation status during mitophagy.

Significance

In general, this is an exciting and well-executed piece of research focusing on the defects in iron homeostasis observed in Parkinson's disease which a wide audience will appreciate. Very recently, a similar genetic interaction between Cisd and Pink1/Prkn in flies was published (Ham et al, 2023 PMID: 37626046) however, from a different angle. While, Ham et al focused on the role of Pink1/Prkn and Cisd in IP3R related ER calcium release, this manuscript approaches the Pink1/Prkn - Cisd interaction from an iron homeostasis point of view. Since, iron dysregulation contributes to the pathogenesis of Parkinson's disease, the observations in this manuscript are relevant for the disease. Hence, the work is sufficiently novel and deserves publication. However, additional experiments are suggested to strengthen the authors' conclusions.<br /> I work on Drosophila models of Parkinson's disease

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Referee #1

Evidence, reproducibility and clarity

Summary:

The manuscript focuses on mitochondrial CISD1 and its relationship to two Parkinson's disease (PD) proteins PINK1 and Parkin. Interestingly, CISD1 is a mitochondrial iron sulfur binding protein and an target of Parkin-mediated ubiquitinylation. Disruption of iron metabolism and accumulation of iron in the brain has long since been reported in PD but the involvement of iron sulfur binding is little studied both in vivo and in human stem cell models of PD. This work addresses the relationship between CISD1 and two mitochondrial models of PD (PINK1 and Parkin) making use of in vivo models (Drosophila), PINK1 patient models (iPSC derived neurons) and Mouse fibroblasts. The authors report a complex relationship between CISD1, PINK1 and Parkin, where iron-depleted CISD1 may illicit a toxic gain of function downstream of PINK1 and Parkin.

Major comments:

• The conclusions are overall modest and supported by the data. One question remains unaddressed. Is mitochondrial CISD1 a downstream target that specifically mediates PINK1 and Parkin loss of function phenotypes or are the phenotypes being mediated because CISD1 is downstream of mitophagy in general?<br /> It would be interesting to know what happens to CISD1 (dimerization?) upon initiation of mitophagy in wild type cells? Would dissipation of mitochondrial membrane potential be sufficient to induce changes to CISD1 in wild type cells or PINK1 deficient cells?

• Since iron chelation is a potent inducer of mitophagy (Loss of iron triggers PINK1/Parkin-independent mitophagy. George F G Allen, Rachel Toth, John James, Ian G Ganley. EMBO Reports (2013)14:1127-1135) it would be useful to show one experiment addressing the role of CISD1 dimerization under mitochondrial depolarizing and non-depolarizing conditions in cells.

• Alternatively, the authors should discuss the topic of mitophagy (including PINK1-parkin independent mitophagy), the limitation of the present study not being able to rule out a general mitophagy effect and previous work on the role of iron depletion on mitophagy induction in the manuscript.

• The data and the methods are presented in such a way that they can be reproduced.<br /> The experiments are adequately replicated and statistical analysis is adequate.

Minor comments:

• Show p values even when not significant (ns) since even some of the significant findings are borderline < p0.05.

• Because the situation for CISD1 is complicated (overexpression, different models etc.) it would be helpful if in the abstract the authors could summarize the role. E.g. as in the discussion that iron-depleted CISD1 could represent a toxic function.

• If there is sufficient iron (accumulation in PD) why would CISD1 be deactivated? Perhaps that could be postulated or discussed in a simplified way?

• In the methods section both reducing and non-reducing gel/Western blotting is mentioned but the manuscript only describes data from blots under reducing conditions. Are there blots under non-reducing conditions that could be shown to see how CISD1 and dimerized CISD1 resolve?

• In the results section, PINK1 mutant flies, it is said that the alterations to CISD1 (dimerization) are analogous to the PINK1 mutation patient neurons. The effect is seen in old but not young flies. Since iPSC-derived neurons are relatively young in the dish, would one not expect that young flies and iPSC-derived neurons have similar CISD1 phenotypes? Could the authors modify the text to reflect that? or discuss the finding in further context.

Significance

• The strengths of this work are in the novelty of the topic and the use of several well established in vivo and cell models including patient-derived neurons. The findings are discussed in the text are honest and avoid over-interpretation. The findings are novel, interesting and important for understanding the mitochondrial biologyof PD.
• Limitations include the lack of strong phenotypes in the CISD1 models and the lack of robust, sustained and consistent increase in CISD1 dimers in the patient and fly models (just significant because of variability). The relationship of CISD1 (dimerization) to general mitophagy/autophagy is not shown here.
• There is a significant advancement. So far researchers were able to describe the importance of iron metabolism in PD (For example refer to work from the group of Georg Auburger such as PMID 33023155 and discussion of therapeutic intervention such as reviewed by Ma et al. PMID: 33799121) but few papers describe involvement of iron sulfur cluster proteins specifically (such as Aconitase) in relation to PINK1 and parkin (these are cited). The fact that CISD1 is a protein of the mitochondrial outer membrane makes it particularly interesting and further studies looking more closely at the interaction of CISD1 with mitochondrial proteins associated with PD will be of interest.
• This paper describes CISD1 as a new and relevant player in PINK1 and Parkin biology. Further work could lead to exploration of whether CISD1 could be a therapeutic target, considering its role in maintaining mitochondrial redox and mitochondrial health. This is of particular interest to mitochondrial biologists and pre-clinical research in PD.
• This preprint was reviewed by three scientists whose research focus in the mitochondrial biology underlying Parkinson's disease. The group has a special interest in the functions of the mitochondrial outer membrane. We work with several cell models of Parkinson's disease and work with patient donated samples. We do not have expertise in Drosophila models of PD nor the quantification of iron described in the manuscript.

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Reply to the reviewers

1. General Statements [optional]

__We thank all the reviewers for their time and their constructive criticism, based on which we will revise our manuscript. All our responses are indicated in red. __

2. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

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

The manuscript by Nguyen and Cheng is investigating the timing and mechanism of cessation of neuroblasts in the pupal optic lobe. Previous studies by several groups have determined the spatial and temporal factors required for the neuroepithelial to neuroblast transition and neuroblast to neural/glycogenesis in third instar larvae such that neuroblasts are eliminated. The mechanism of elimination of neuroblasts in the VNC or mushroom bodies have been investigated, but the mechanism(s) and the timing of elimination of medulla neuroblasts has not been investigated. The authors suggest that medulla neuroblasts are eliminated via a combination of mechanisms including apoptosis, prospero induced size symmetric terminal differentiation and a switch to gliogenesis by gcm expression. Expression of Tailless also was found to affect the timing of medulla neuroblast termination. They also ruled out several mechanisms such as ecdysone pulses.

Major comments

Clearly written and logical flow to experiments and results not over interpreted.

Clearly show that the neuroblast number and size decrease (12 to 18 hrs) and are eliminated by 30 hours

Figure 2a Marking of the Neuroepithelium. Would be more convincing if shown by PatJ expression and is clonal analysis. While the following panels use PatJ in clones suggesting are NE and NBs present it is more difficult to put into the context in the higher magnification images (Figure 2 D- M) and the Miranda expression in F' seems to be the entire lobe and it is not clear if would be any NE which does not agree with what is shown in panel A.

We will perform clonal analysis using MARCM to show that the elimination of medulla NBs (marked by Dpn) is accompanied by the depletion of NE (marked by PatJ). For Figure 2 D, E, I, L, we will change the images to the whole lobes to clearly show the shift in the NE-NB transition upon Notch OE/KD.

Is difficult to see the neuroblasts in Figure 2 D D" and E. The figure does not match what is stated in the results in that the neuroblasts are difficult to observe. If the point is that there is fewer NE cells and more neuroblasts then this is hard to see. It has been previously shown that with Notch RNAi clones prematurely extrude form the NE (Egger 20210; Keegan 2023) and could be expressing more Neuroblast markers but this is not visible in the panels as shown. Are the images single focal plane or maximum projections? Imaging more deeply in the brain or viewing in cross section would account for these possibilities. The possibility that are more neuroblasts but not all at the surface of the OL should be addressed as this could also alter the overall results.

Figure 2 is key to first point of the paper so needs to be addressed.

The images are single focal plane of the superficial layer of the medulla. We will specify this information in the figure legends. We will include cross-section of the notch RNAi clones to show the delamination of precocious NBs.

Minor comments

Why express volume of DPN in clone volume. Would make the point more clear and more strong be to express as number of NB in the 3-D volume of the clone. This measurement occurs in several figures.

We will redo the quantification as suggested.

Use of Miranda to mark NBs is unclear in Figure 2. Perhaps more clear in B&W.

We will redo the staining with Dpn instead of Mira to mark medulla NBs. Figures will be presented in B&W as suggested.

Make clear in figures (or figure legend) if single focal plane or projections.

We will do so.

It is unclear what percentage of NB the Gal4 line eyR16F10 are expressed in. Veen 2023 state that the GAL4 is also expressed in neurons and at different levels whether deeper within the brain or superficially on the surface of the brain. At 16 APF it is expressed but it is not clear whether it is in all cells at a low level or only within a few cells

We will further characterize the expression of eyR16F10-GAL4 in the pupal medulla as suggested.

Some RNAi lines referenced as previously validated and other are not. For example: EcR, Oxphos, Med27, Notch need references or confirmation of specificity to the intended target (qRT)

We will perform RT-qPCR to validate the use of UAS-med27 RNAi. For RNAi stocks such as UAS-EcR RNAi, UAS-Atg1 RNAi, UAS-notch RNAi that have been previously used in other publications, we will provide appropriate references.

At least 2 animals per genotype were used. While I appreciate the technical difficulty of working in pupae this seems a bit low in terms of number of samples and data would be more robust with more numbers.

Any experiments in which less than 3 animals were used, we will redo the experiments.

Reviewer #1 (Significance (Required)):

This provides mechanism and timing for the elimination of neuroblasts (NE to NB) that arise from the medulla. As these are most similar to mammalian brain development (Radial glial to NSC) this information provides more context to interpret the formation of glial and neurons in the adult optic lobe given the effect on timing and mechanisms of elimination.

This paper would be of interest to developmental biologist who work with Drosophila or mice who are looking at neural development. An understanding of how neural diversity is achieved and the mechanisms behind this that can be dysfunctional in terms of etiology of neural diseases. Is a well done study for the most part that would be improved by clarifying some data and provided more replicates for robustness of the data.

I am a developmental biologist working with Drosophila in larval and adult neural development.

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

Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.

The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

There are no major issues affecting the conclusions

• The paper shows that the end of production of neural stem cells occurs the neuroepithelium is completely transformed. The experiments performed by the authors are fine and show that, if the transition is delayed, neural stem cells terminate their life later, and vice versa. However, the lifespan of the neural stem cells is not affected by the timing of the transition. Therefore, these experiments do not tell us how neural stem cells terminate their life, which is the central question of the study. The discussion should be written accordingly and the title and the model in Fig 6 modified to reflect the importance of the end of life of the stem cells, the main theme of the paper.

We agree that our said experiments did not elucidate how NBs terminate at the end of neurogenesis. Nevertheless, our aim is to show that the timing of NB termination in the medulla is dependent on the timing of the NE-NB transition.

In Supplementary Figure 1, we showed that factors previously shown to be involved in NB termination in other lineages did not play similar roles in the medulla NBs. Thus, we think that NB termination in the medulla is likely regulated at the levels of the NE, but not the NBs themselves. Although we have briefly mentioned this in our manuscript, we hope by conducting the experiments suggested by the reviewer (see below), we can subsequently modify our model in Figure 6 and our discussion.

• The authors talk about Pros-dependent symmetric division and gliogenic switch as two separate processes, but these may be two sides of the same phenomenon. Tll+ gcm+ neural stem cells undergo Pros-dependent cell cycle exit, generating glial progeny. If the authors agree with this, could they update their model (and discussion) to reflect the fact that gliogenic switch occurs via a Pros-dependent symmetric division, and these are not two separate processes independently contributing to the depletion of the neural stem cell pool? Ideally, a triple staining between Dpn, Pros, and gcm would show that the symmetrically dividing cells seen by the authors are committed to the glial fate.

We will further test how gliogenesis is affected in pros RNAi clones. The results may shed light on whether Pros-mediated symmetric division is required for Gcm-mediated gliogenesis in the medulla. Regarding the model, we have summarized our findings and suggestions in Figure 5K, however, we will integrate this information into our final model.

In Figure 5C, we showed that at 12h APF, there are Dpn+ NBs in the medulla that expressed both Pros and Gcm, suggesting that it is very likely that Pros is upstream of Gcm to induce the glial cell fate switch of the medulla NBs.

• Why were Notch RNAi experiments assessed for the presence of neural stem cells at P12 and gcm RNAi experiments at P24? Given that most optic lobe neural stem cells disappear between P12-18, a subtle effect of gcm RNAi may have been missed. Do the authors have data for gcm RNAi at P12?

We hypothesized that the timing of NE-NB transition affects the timing of NB termination in the medulla. Because Notch KD was previously shown to induce precocious NE-NB transition in the OL, meaning that medulla NBs are born prematurely, we expected that this manipulation will lead to a corresponding premature elimination of the NBs. In contrast, gcm RNAi which inhibits the switch into the glial cell fate of the NBs, is expected to prolong the neurogenic phase of the NBs, and thereby, their persistence by 24h APF when WT NBs are eliminated.

• The authors should acknowledge that the inhibition of either apoptosis or autophagy alone may not be fully sufficient to prevent the death of NBs. In mushroom body neural stem cells, both processes must be inhibited simultaneously to produce a strong effect on their survival (Pahl et al. 2019, PMID 30773368).

We will add this information in our discussions.

• There is an important missing point that should be addressed: is there a specific point in time when all neural stem cells must stop their lineage wherever they are in the temporal series and either die or divide symmetrically? One possibility that is not discussed is that most neural stem cells end their life through a gliogenic symmetric division while those that were generated late must stop en route and die by apoptosis and/or autophagy. This would solve the strange diversity of end-of-life, which could be easily addressed by identifying the temporal stage of the neural stem cells that undergo apoptosis

We agree that it would be of interest to understand how there are diverse mechanisms by which medulla NBs terminate during pupal development. To address if temporal progression is involved in apoptosis of the medulla NBs, we will first characterize the expression of some temporal TFs (e.g., Ey, Slp, Tll) at 12h APF when we found a subset of medulla NBs undergo apoptosis in the wildtype animals.

Minor suggestions:

We agree with these minor modifications.

• Line 46: Specify that there are 8 type II neural stem cells in each hemisphere*.

• The statement in lines 181-182 that "cell death, and not autophagy, makes a minor contribution to..." should be replaced with "apoptosis, and not autophagy," as autophagy is also a type of cell death.

• The authors should adjust the logic of the section "Medulla neuroblasts terminate during early pupal development": Describe the wild-type pattern first (the decrease in the number of neural stem cells and their size with age) and then describe the perturbations aimed at disrupting the number and the size of neural stem cells

• Line 151 should refer to Fig. 2I-K, not Fig. 2J-K.

**Referees cross-commenting**

How can NBs die by different mechanisms?? This might only happen is they are in a different states, an issue that is not addressed.

it has been shown that optic lobe NBs end their life by a symmetric, gliogenic last division at the end of the last temporal window, and not by PCD.

It is likely, and the authors do hint at it, that NBs only die by PCD when they prematurely interrupt the temporal series in early pupation when neurons synchronously start undergoing maturation.

I believe that the authors should explain this, if this is indeed their model, and show that NBs die while still in early temporal windows.

Reviewer #2 (Significance (Required)):

Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.

The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

There are no major issues affecting the conclusions

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

Summary

In this manuscript, the authors address the timing and mechanisms responsible for the termination of medulla neuroblasts in Drosophila visual processing centres, also known as optic lobes. Through time course experiments the authors demonstrate the medulla NBs are completely eliminated by 30h APF during early pupal development. By manipulating the Notch signalling pathway as well as proneural genes such as lethal of scute, the authors show that altering the NE-NB transition is sufficient to change the timing of NB termination. In contrast, ecdysone signalling and components of the mediator complex, known to terminate proliferation of central brain NBs, are not required for the termination of medulla NBs. Medulla NBs sequentially express a variety of temporal transcription factors to promote cellular diversity, however, the authors demonstrate that altering temporal factors such as Ey, Sco or Hth, does not affect the timing of the medulla NBs termination. Interestingly however overexpression of the transcription factor tailless can cease medulla NB termination via the conversion of type I to type II NB fate. They further go on to show the importance of the differentiation factor, Prospero, in promoting the differentiation of medulla NBs as well as terminating medulla neurogenesis during pupal development. Finally, in addition to differentiation, the authors show another mechanism responsible for the cessation of neurogenesis which is the commencement of gliogenesis. Through manipulation of the neurogenic to gliogenic switch by knockdown or overexpressing the glial regulatory gene, gcm, the authors show that even though the downregulation of gcm is is not sufficient to induce NB persistence, gcm overexpression can cause premature termination of NBs.

Major comments:

• Are the key conclusions convincing?

Yes, the key conclusions are convincing with proper controls, quantifications and statistical analyses.

• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

The conclusion that temporal transcription factors (TTF) do not affect the timing of medulla NB termination is somewhat preliminary. The authors investigated a simplified temporal series including Homothorax, Eyeless, Sloppy-paired, Dichaete and Tailless. However, there are additional temporal factors that have not been examined for their potential involvement in medullar NB termination. Previous reports have identified several other temporal factors that play a role in medulla TTF cascade, such as, SoxNeuro (SoxN) and doublesex-Mab related 99B (Dmrt99B) that start their expression in the NE similar to Hth, however, Dmrt99B is likely to be repressed much later than Hth (Li, Erclik et al. 2013, Zhu, Zhao et al. 2022). At this point, it remains challenging to completely rule out the possibility that other temporal factors play a role in medullar NB termination or have redundant functions in regulating the timing of medulla NB cessation. It is suggested to tone down this claim and provide a brief discussion on alternative possibilities, citing relevant papers on the functions of other temporal factors in medullar NBs.

We agree.

• Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

Loss of pros by RNAi caused the formation of ectopic NBs and the NBs persist even at 24h APF. Do these NBs persist at 30h or 48h APF? Does overexpression of Pros result in early termination of medulla NBs?

We will do these experiments in clones as suggested.

• Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3 months to complete the experiments.

• Are the data and the methods presented in such a way that they can be reproduced?

Yes.

• Are the experiments adequately replicated and statistical analysis adequate?

The experiments are straight forward and were performed with proper controls, supported by quantifications and proper statistical analyses. However, there is no mention about how many replicates were used.

We will add this information in our Material and Methods section.

Minor comments:

1. The authors use the eyR6F10-Gal4 driver in certain experiments. The eyR6F10-Gal4 driver is however expressed only in a subset of medulla NBs. Can the authors comment on what percentage of medulla NBs is the driver expressed in? We will characterize this.

Does the EGFR signalling pathway or JAK/STAT pathway affect the timing of termination of medulla NBs? Experiments are not necessary. The author can speculate on their roles.

We will modify our discussion accordingly.

Figure 1C has a p value of only 0.03 (*) but shows a strong reduction in the number of Dpn+ cells from 12h to 18h, etc. Is this correct? Also, is the p value the same for the comparison between 12h and 24h as well as 12h and 30h APF?

Yes. P-values showed no significant differences between 28-24h and 24-30h APF.

The controls in figure 2B and to some extent figure 2H show one major outlier (much higher than the other brain lobes in the control). Will the removal of this outlier affect the significance/ p-value of the experiment?

No, removing the outliers do not change the statical results.

In figure 2B what is the p-value between 12h and 18h APF? Is it *** as well?

No, it’s not significant.

Line 84 of the introduction introduces Tll, Gcm and Pros for the first time in the manuscript and should be written out in full.

We will change this.

• Are prior studies referenced appropriately?

Yes.

• Are the text and figures clear and accurate?

Yes.

• Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Quite a few of data mentioned in the manuscript have been described as data not shown. I think it would be nice to show quantifications or representative images in the supplementary figures.

We will add the data which was previously not shown.

Reviewer #3 (Significance (Required)):

Since the mechanisms by which medulla NBs are terminated are currently unknow, this is an important and interesting study to understand how medulla neuroblasts in the optic lobe are terminated. The balance between stem cell maintenance and differentiation is critical for proper brain development and the results presented in this paper are impactful. Furthermore, Drosophila melanogaster is an excellent model to study stem cell niches and neuroblast temporal patterning. The authors provide key mechanisms namely cell death, Pros-mediated differentiation and the gliogenic switch that contribute to a better understanding of how the NB progenitor pool can be terminated in the Drosophila OL, which is largely supported by the data.

• Place the work in the context of the existing literature (provide references, where appropriate).

So far, most work in this field has focused on the regulation of the temporal factors to promote the progression of the TTF transcriptional cascade and thereby diversity of the neural progenitors (Li, Erclik et al. 2013, Naidu, Zhang et al. 2020, Ray and Li 2022, Zhu, Zhao et al. 2022). Furthermore, work on pathways such as EGFR and Notch signalling that allows the proneural wave to progress and subsequently induce neuroblast formation in a precise and orderly manner have also been studied (Yasugi, Umetsu et al. 2008, Yasugi, Sugie et al. 2010). Here, considering previous literature, the authors move one step forward to determine how and when these neuroblast progenitors cease proliferation during development thus providing mechanisms for the regulation of the neuroepithelial stem cell pool, its timely conversion into NSCs and the switch from neurogenesis to gliogenesis thus providing important implications for brain size determination and function.

• State what audience might be interested in and influenced by the reported findings.

Stem cell research, neurobiologists and developmental biologists.

• Define your field of expertise

Stem cells, developmental biology

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Referee #3

Evidence, reproducibility and clarity

Summary

In this manuscript, the authors address the timing and mechanisms responsible for the termination of medulla neuroblasts in Drosophila visual processing centres, also known as optic lobes. Through time course experiments the authors demonstrate the medulla NBs are completely eliminated by 30h APF during early pupal development. By manipulating the Notch signalling pathway as well as proneural genes such as lethal of scute, the authors show that altering the NE-NB transition is sufficient to change the timing of NB termination. In contrast, ecdysone signalling and components of the mediator complex, known to terminate proliferation of central brain NBs, are not required for the termination of medulla NBs. Medulla NBs sequentially express a variety of temporal transcription factors to promote cellular diversity, however, the authors demonstrate that altering temporal factors such as Ey, Sco or Hth, does not affect the timing of the medulla NBs termination. Interestingly however overexpression of the transcription factor tailless can cease medulla NB termination via the conversion of type I to type II NB fate. They further go on to show the importance of the differentiation factor, Prospero, in promoting the differentiation of medulla NBs as well as terminating medulla neurogenesis during pupal development. Finally, in addition to differentiation, the authors show another mechanism responsible for the cessation of neurogenesis which is the commencement of gliogenesis. Through manipulation of the neurogenic to gliogenic switch by knockdown or overexpressing the glial regulatory gene, gcm, the authors show that even though the downregulation of gcm is is not sufficient to induce NB persistence, gcm overexpression can cause premature termination of NBs.

Major comments:

• Are the key conclusions convincing?

Yes, the key conclusions are convincing with proper controls, quantifications and statistical analyses. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

The conclusion that temporal transcription factors (TTF) do not affect the timing of medulla NB termination is somewhat preliminary. The authors investigated a simplified temporal series including Homothorax, Eyeless, Sloppy-paired, Dichaete and Tailless. However, there are additional temporal factors that have not been examined for their potential involvement in medullar NB termination. Previous reports have identified several other temporal factors that play a role in medulla TTF cascade, such as, SoxNeuro (SoxN) and doublesex-Mab related 99B (Dmrt99B) that start their expression in the NE similar to Hth, however, Dmrt99B is likely to be repressed much later than Hth (Li, Erclik et al. 2013, Zhu, Zhao et al. 2022). At this point, it remains challenging to completely rule out the possibility that other temporal factors play a role in medullar NB termination or have redundant functions in regulating the timing of medulla NB cessation. It is suggested to tone down this claim and provide a brief discussion on alternative possibilities, citing relevant papers on the functions of other temporal factors in medullar NBs. - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

Loss of pros by RNAi caused the formation of ectopic NBs and the NBs persist even at 24h APF. Do these NBs persist at 30h or 48h APF? Does overexpression of Pros result in early termination of medulla NBs? - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3 months to complete the experiments. - Are the data and the methods presented in such a way that they can be reproduced?

Yes. - Are the experiments adequately replicated and statistical analysis adequate?

The experiments are straight forward and were performed with proper controls, supported by quantifications and proper statistical analyses. However, there is no mention about how many replicates were used.

Minor comments:

1. The authors use the eyR6F10-Gal4 driver in certain experiments. The eyR6F10-Gal4 driver is however expressed only in a subset of medulla NBs. Can the authors comment on what percentage of medulla NBs is the driver expressed in?
2. Does the EGFR signalling pathway or JAK/STAT pathway affect the timing of termination of medulla NBs? Experiments are not necessary. The author can speculate on their roles.
3. Figure 1C has a p value of only 0.03 (*) but shows a strong reduction in the number of Dpn+ cells from 12h to 18h, etc. Is this correct? Also, is the p value the same for the comparison between 12h and 24h as well as 12h and 30h APF?
4. The controls in figure 2B and to some extent figure 2H show one major outlier (much higher than the other brain lobes in the control). Will the removal of this outlier affect the significance/ p-value of the experiment?
5. In figure 2B what is the p-value between 12h and 18h APF? Is it *** as well?

6. Line 84 of the introduction introduces Tll, Gcm and Pros for the first time in the manuscript and should be written out in full.

7. Are prior studies referenced appropriately?

Yes. - Are the text and figures clear and accurate?

Yes. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Quite a few of data mentioned in the manuscript have been described as data not shown. I think it would be nice to show quantifications or representative images in the supplementary figures.

Significance

Since the mechanisms by which medulla NBs are terminated are currently unknow, this is an important and interesting study to understand how medulla neuroblasts in the optic lobe are terminated. The balance between stem cell maintenance and differentiation is critical for proper brain development and the results presented in this paper are impactful. Furthermore, Drosophila melanogaster is an excellent model to study stem cell niches and neuroblast temporal patterning. The authors provide key mechanisms namely cell death, Pros-mediated differentiation and the gliogenic switch that contribute to a better understanding of how the NB progenitor pool can be terminated in the Drosophila OL, which is largely supported by the data.

• Place the work in the context of the existing literature (provide references, where appropriate).

So far, most work in this field has focused on the regulation of the temporal factors to promote the progression of the TTF transcriptional cascade and thereby diversity of the neural progenitors (Li, Erclik et al. 2013, Naidu, Zhang et al. 2020, Ray and Li 2022, Zhu, Zhao et al. 2022). Furthermore, work on pathways such as EGFR and Notch signalling that allows the proneural wave to progress and subsequently induce neuroblast formation in a precise and orderly manner have also been studied (Yasugi, Umetsu et al. 2008, Yasugi, Sugie et al. 2010). Here, considering previous literature, the authors move one step forward to determine how and when these neuroblast progenitors cease proliferation during development thus providing mechanisms for the regulation of the neuroepithelial stem cell pool, its timely conversion into NSCs and the switch from neurogenesis to gliogenesis thus providing important implications for brain size determination and function. - State what audience might be interested in and influenced by the reported findings.

Stem cell research, neurobiologists and developmental biologists. - Define your field of expertise

Stem cells, developmental biology

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Referee #2

Evidence, reproducibility and clarity

Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla. The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

There are no major issues affecting the conclusions

• The paper shows that the end of production of neural stem cells occurs the neuroepithelium is completely transformed. The experiments performed by the authors are fine and show that, if the transition is delayed, neural stem cells terminate their life later, and vice versa. However, the lifespan of the neural stem cells is not affected by the timing of the transition. Therefore, these experiments do not tell us how neural stem cells terminate their life, which is the central question of the study. The discussion should be written accordingly and the title and the model in Fig 6 modified to reflect the importance of the end of life of the stem cells, the main theme of the paper.
• The authors talk about Pros-dependent symmetric division and gliogenic switch as two separate processes, but these may be two sides of the same phenomenon. Tll+ gcm+ neural stem cells undergo Pros-dependent cell cycle exit, generating glial progeny. If the authors agree with this, could they update their model (and discussion) to reflect the fact that gliogenic switch occurs via a Pros-dependent symmetric division, and these are not two separate processes independently contributing to the depletion of the neural stem cell pool? Ideally, a triple staining between Dpn, Pros, and gcm would show that the symmetrically dividing cells seen by the authors are committed to the glial fate.
• Why were Notch RNAi experiments assessed for the presence of neural stem cells at P12 and gcm RNAi experiments at P24? Given that most optic lobe neural stem cells disappear between P12-18, a subtle effect of gcm RNAi may have been missed. Do the authors have data for gcm RNAi at P12?
• The authors should acknowledge that the inhibition of either apoptosis or autophagy alone may not be fully sufficient to prevent the death of NBs. In mushroom body neural stem cells, both processes must be inhibited simultaneously to produce a strong effect on their survival (Pahl et al. 2019, PMID 30773368).
• There is an important missing point that should be addressed: is there a specific point in time when all neural stem cells must stop their lineage wherever they are in the temporal series and either die or divide symmetrically? One possibility that is not discussed is that most neural stem cells end their life through a gliogenic symmetric division while those that were generated late must stop en route and die by apoptosis and/or autophagy. This would solve the strange diversity of end-of-life, which could be easily addressed by identifying the temporal stage of the neural stem cells that undergo apoptosis

Minor suggestions:

• Line 46: Specify that there are 8 type II neural stem cells in each hemisphere*.
• The statement in lines 181-182 that "cell death, and not autophagy, makes a minor contribution to..." should be replaced with "apoptosis, and not autophagy," as autophagy is also a type of cell death.
• The authors should adjust the logic of the section "Medulla neuroblasts terminate during early pupal development": Describe the wild-type pattern first (the decrease in the number of neural stem cells and their size with age) and then describe the perturbations aimed at disrupting the number and the size of neural stem cells
• Line 151 should refer to Fig. 2I-K, not Fig. 2J-K.

Referees cross-commenting

How can NBs die by different mechanisms?? This might only happen is they are in a different states, an issue that is not addressed. it has been shown that optic lobe NBs end their life by a symmetric, gliogenic last division at the end of the last temporal window, and not by PCD. It is likely, and the authors do hint at it, that NBs only die by PCD when they prematurely interrupt the temporal series in early pupation when neurons synchronously start undergoing maturation. I believe that the authors should explain this, if this is indeed their model, and show that NBs die while still in early temporal windows.

Significance

Lineages of neural stem cells are of great interest to understand how many neural types are generated. They produce very diverse neurons, often in a highly stereotyped series. However, they must terminate their life when the animal becomes functional or if neurons need time to become mature before birth.

In the Drosophila optic lobes, neural stem cells are produced over a period of several days by a wave of neurogenesis that transforms a neuroepithelium into neural stem cells that undergo a series of temporal patterning steps. It has been reported that they finish their life when a symmetric division generates glial cells. The authors however analyze the end of a particular lineage, that of the latest born neural stem cells of the medulla.

The paper shows that neural stem cells stop being produced when the neuroepithelium is consumed. But how do the latest born neural stem cells stop their lineage?

The results show that they do so by several means, which is quite unexpected: they may die from apoptosis, or autophagy, by becoming glioblasts or by a terminal symmetric division.

There are no major issues affecting the conclusions

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Referee #1

Evidence, reproducibility and clarity

The manuscript by Nguyen and Cheng is investigating the timing and mechanism of cessation of neuroblasts in the pupal optic lobe. Previous studies by several groups have determined the spatial and temporal factors required for the neuroepithelial to neuroblast transition and neuroblast to neural/glycogenesis in third instar larvae such that neuroblasts are eliminated. The mechanism of elimination of neuroblasts in the VNC or mushroom bodies have been investigated, but the mechanism(s) and the timing of elimination of medulla neuroblasts has not been investigated. The authors suggest that medulla neuroblasts are eliminated via a combination of mechanisms including apoptosis, prospero induced size symmetric terminal differentiation and a switch to gliogenesis by gcm expression. Expression of Tailless also was found to affect the timing of medulla neuroblast termination. They also ruled out several mechanisms such as ecdysone pulses.

Major comments

Clearly written and logical flow to experiments and results not over interpreted. Clearly show that the neuroblast number and size decrease (12 to 18 hrs) and are eliminated by 30 hours

Figure 2a Marking of the Neuroepithelium. Would be more convincing if shown by PatJ expression and is clonal analysis. While the following panels use PatJ in clones suggesting are NE and NBs present it is more difficult to put into the context in the higher magnification images (Figure 2 D- M) and the Miranda expression in F' seems to be the entire lobe and it is not clear if would be any NE which does not agree with what is shown in panel A.<br /> Is difficult to see the neuroblasts in Figure 2 D D" and E. The figure does not match what is stated in the results in that the neuroblasts are difficult to observe. If the point is that there is fewer NE cells and more neuroblasts then this is hard to see. It has been previously shown that with Notch RNAi clones prematurely extrude form the NE (Egger 20210; Keegan 2023) and could be expressing more Neuroblast markers but this is not visible in the panels as shown. Are the images single focal plane or maximum projections? Imaging more deeply in the brain or viewing in cross section would account for these possibilities. The possibility that are more neuroblasts but not all at the surface of the OL should be addressed as this could also alter the overall results. Figure 2 is key to first point of the paper so needs to be addressed.

Minor comments

Why express volume of DPN in clone volume. Would make the point more clear and more strong be to express as number of NB in the 3-D volume of the clone. This measurement occurs in several figures. Use of Miranda to mark NBs is unclear in Figure 2. Perhaps more clear in B&W. Make clear in figures (or figure legend) if single focal plane or projections. It is unclear what percentage of NB the Gal4 line eyR16F10 are expressed in. Veen 2023 state that the GAL4 is also expressed in neurons and at different levels whether deeper within the brain or superficially on the surface of the brain. At 16 APF it is expressed but it is not clear whether it is in all cells at a low level or only within a few cells Some RNAi lines referenced as previously validated and other are not. For example: EcR, Oxphos, Med27, Notch need references or confirmation of specificity to the intended target (qRT) At least 2 animals per genotype were used. While I appreciate the technical difficulty of working in pupae this seems a bit low in terms of number of samples and data would be more robust with more numbers.

Significance

This provides mechanism and timing for the elimination of neuroblasts (NE to NB) that arise from the medulla. As these are most similar to mammalian brain development (Radial glial to NSC) this information provides more context to interpret the formation of glial and neurons in the adult optic lobe given the effect on timing and mechanisms of elimination.

This paper would be of interest to developmental biologist who work with Drosophila or mice who are looking at neural development. An understanding of how neural diversity is achieved and the mechanisms behind this that can be dysfunctional in terms of etiology of neural diseases. Is a well done study for the most part that would be improved by clarifying some data and provided more replicates for robustness of the data. I am a developmental biologist working with Drosophila in larval and adult neural development.

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Reply to the reviewers

Rebuttal for Review Commons to:

“A specific innate immune response silences the virulence of Pseudomonas aeruginosa in a latent infection model in the Drosophila melanogaster host”

We thank the reviewers for their careful scrutiny of our manuscript. We believe that we have addressed satisfactorily the points raised by the reviewers and that our revised manuscript is definitely improved. Our replies below are in blue and use a distinctive font.

Reviewer #1

__Evidence, reproducibility and clarity __

This works describes a latent Drosophila intestinal infection, which spreads systemically, with a direct systemic Drosophila infection using a common laboratory strain of Pseudomonas aeruginosa. The major observation of this study is that P. aeruginosa can cause a latent infection via its passage through the gut (as opposed to being injected). In doing so it exhibits cell rounding (instead of elongation), reduced cell motility, loss of O5-antigen, antibiotic resistance, ability to cross the intestinal barrier and circulate in the hemolymph and infiltrate the host tissue underneath the cuticle. In addition, latent infection bacteria induce all brunches of the systemic response: the Imd pathway, phagocytosis, and the melanization cascade. Moreover, the melanization pathway protects the host from a secondary systemic infection with various types of bacterial and fungal microbes.

An issue that needs to be clarified is the sensitivity of P. aeruginosa virulence to its biochemical environment. The authors note that. For example, liquid bacterial culture in BHI induces the latent form of bacteria. So the growth conditions and the infection media play a major role in the infection process. They authors need to clarify further the effect of media and infection vehicles, sucrose (high/low), LB, and BHI (as well as temperature) on the latent phenotype.

Temperature is definitely an important parameter and bacteria appear to be somewhat more virulent at 25°C. This point is now addressed in the Material and Methods section (lines 675-679) and in Fig. S6I.

As regards the influence of the composition of the infection solution, it does not seem to be a critical parameter that we have described in the context of continuous feeding on the bacterial solution (Limmer et al., PNAS, 2011). In preliminary experiments, we had tried LB or BHB medium to grow the bacteria and this did not make any difference (see Panel A below for LB [BHB used in our experiments]). As regards the sucrose concentration to the infection solution, we have tried two concentrations and did not observe any difference as regards the establishment of the latent infection. (see panel B below for 50 mM sucrose [100mM used in our experiments]). Of note, P. aeruginosa does not grow on sucrose solution alone. However, a latent infection was still established upon feeding the flies with PAO1 in sucrose alone, albeit likely with a mildly increased virulence, in the absence of any BHB medium (see panels C-D) below.

A) Comparison of LB vs. BHB B) Establishment of latent infection with 50mM sucrose

C) Establishment of a latent infection with a sucrose-only bacterial solution D) Colonization of host tissues by PAO1 ingested in a sucrose-only bacterial solution Minor issues: -Lines 579-581> How were the PAO1GFP/RFP constructed (details are needed)

Done; please, see lines 641-643.

-Figure 1D and other figures > CFUs given as Log2 are unconventional. One cannot easily deduce the burden unless e.g. translate 2e10 to ~1000 and 2e30 to ~10e9 CFUs.

True, but bacterial titer increases by a factor of two at each division cycle. Even though we have previously used a Log10 representation, we now prefer using a Log2 representation. This representation has also been used by other authors in the field, e.g., Duneau et al., eLife, 2019.

-Figire S1DB (now S1C)> "but from the outside of the gut". The given experiment does not prove that statement.

This issue has been already dealt with in the Nehme et al. PLoS Pathogens 2007 article, as cited in the manuscript. We further provide in Fig. S1B pictures documenting the presence of bacteria associated with visceral muscles. Finally, we also show that the gut lumen is essentially cleared of bacteria after a period of feeding on a sucrose solution or gentamicin. Hence, most bacterial colonies originate from the outer layer of the gut. We clarify the issue in the text (lines 154-158).

-Lines 146-7 > data are missing in support to the statement.

We have now added Fig. S1B to document that the gentamicin treatment does work, as actually does feeding on sucrose solution alone, as previously documented in Limmer et al., 2011 (Fig. S2B). Of note, we cannot exclude that a few bacteria remain, especially in the crop, but those would be at very low titer. Please, see also reply to Reviewer 2.

-Figure S1C > The effect of injury seems to be huge, and may account for much/most of the differences observed (including those between latent and active infection). This is further supported by Figure4A, injury may account for gut collapse and/or systemic stress.

It is well known that injury alone induces the systemic IMD pathway response 6 hours after injury but largely subsides by 24 hours. The point of Fig. S1C is that the level of induction reached during latent infection is very low as compared to that observed during a systemic infection, here obtained for reference with an Escherichia coli injection and to a lesser extent with a PBS injection. In our latent infection model, we do not perform any injury, except as noted by the reviewer in Fig. 4: the effects of an experimental injury are observed only while the bacteria are crossing the intestinal barrier and hardly any effect is observed when the injury is performed on day 10 (Fig. S4B).

-Figure S1D > How was "fated to die" assessed?

The fluorescent flies were sorted out and their subsequent survival was monitored. As compared to nonfluorescent flies from the same batch, they died within two days of sorting them.

-Figure 3B/10th day > Average line is misplaced.

We thank the reviewer for pointing out this problem. The line is not the average but the median. We have now added a precise description of the bars to all the figure legends.

-Lines 382-5 > what is the evidence of gut damage (or the absence of it)? How do the bacteria escape the gut?

The absence of major gut damages has been documented in Limmer et al, PNAS, 2011. How the bacteria escape the gut remains an open question (intracellular and/or paracellular route).

-Lines437-442 > The distinction between dormant P. aeruginosa in the fly tissues and persister cells (upon antibiotic treatment) cannot be justifies on the basis of relative bacterial numbers in the two systems. The extent of resistance to antibiotics though my serve that purpose.

In our latent infection model, most of the bacteria that have crossed the gut barrier become dormant and are associated with tissues, except at the beginning of the infection. In contrast, when a bacterial culture is treated with antibiotics, most of the bacteria are killed by the treatments and only a few ones persist, likely because of an inactive metabolism. Thus, the induction of dormancy in our latent infection model does not rely on the selection of a few metabolically-inactive bacteria able to withstand an immune response or an antibiotic treatment.

Significance

The study is a significant advance to our knowledge. Notwithstanding further explanations, it provides a solid basis of understanding active versus dormant bacteria. It further establishes a mode of intestinal to systemic infection as a tool for further explorations.

Reviewer #2

Evidence, reproducibility and clarity

Summary: In this study, Chen and colleagues investigated a new latent infection model for Pseudomonas aeruginosa using Drosophila melanogaster as a host. First, the authors established a new model for latent Pseudomonas infection. The key feature of this model is the translocation of P. aeruginosa from the gut to the hemolymph and the colonization of fly tissues by the dormant bacteria. Bacteria that translocated from the gut appeared strikingly different in morphology and resistance to antibiotics compared to bacteria that were directly injected. Next, the authors suggest that melanization but not the Imd pathway or hemocytes are necessary to promote dormancy and colonization of fly tissues. Finally, flies with latent P. aeruginosa infection exhibit improved survival after secondary infections in a melanisation-dependent manner. The study reports an interesting model for latent infection, provides insights into the host factors promoting latency and describes some of the consequences of such latent infection for the host. However, some of the conclusions are not fully supported by the data and need further experimental evidence.

Major comments: 1. The latent infection model requires some clarifications. First, temperature. Could the authors explain why they used 18 {degree sign}C and could low temperature contribute to the establishment of dormancy?

As shown in Fig.S6I, the latent infection model is less compelling at 25°C in terms of survival curves, which may reflect an increased rate of spontaneous reactivation of the virulence, a phenomenon we have not studied at 25°C. In another manuscript in preparation (Lin et al.), we actually show that a small heat shock does contribute to reactivation of the bacteria, an issue that is outside of the scope of the present study. Please, see also reply to reviewer 1.

Second, the use of gentamycin. How does gentamicin affect PAO1 outside the gut? From Fig.1C It looks like the cfus in the hemolymph diminished rapidly after gentamicin treatment (around day 3), suggesting the potential effect of the antibiotic. Once the bacteria have crossed the gut and entered the hemolymph, they could still be affected by feeding flies the antibiotic. Is there a possibility that gentamicin treatment is a stress factor that could trigger or facilitate the transition to dormancy? The authors could test this experimentally either by omitting the antibiotic and assessing dormancy or by feeding injected flies with gentamycin and scoring dormancy.

We had actually tested the issue about the potential role of gentamicin outside of the gut compartment. We have thus fed flies on different concentrations of gentamicin and monitored the survival of those flies to the injection of PAO1 bacteria (please, see Figure below). When flies were feeding on the highest concentration of gentamicin tested, 32 mg/mL, they were succumbing fast to the PAO1 challenge, but not as fast as nontreated positive control PAO1 injected flies. The use of lower concentrations (16, 8, and 4 mg/mL) led to a progressively stronger protection from PAO1 injection that inversely correlated with the gentamicin dose. We interpret the data with high gentamicin concentrations as an indication that gentamicin at such concentrations is likely directly toxic to the flies, an issue that could be experimentally tested but is not relevant to this study. Interestingly, lower doses led to a much-decreased protection from PAO1 (2mg/mL) to no protection at the dose we use to establish latent infection (100 µg/mL). Thus, these data show that gentamicin can pass the gut barrier when provided at high concentrations, down to 2 mg/mL. However, there is no proof of such a passage at the dose we use. In keeping with this latter possibility, we made a control experiment in which the gentamicin treatment step was replaced by simply feeding on the sucrose solution: the bacterial titer decreased in the hemolymph at the same rate as for gentamicin-treated flies (new Fig. S1F), demonstrating that ingested gentamicin does not contribute to the decreased titer. Rather, the likely depletion of the “source”, that is PAO1 in the gut lumen, best accounts for this phenomenon.

We have now cited references which document a lack of permeability of the gut barrier to ingested gentamicin in vertebrate animals (lines 130-133).

As regards the possibility that gentamicin acts as a stress factor on bacteria, our data do not support this possibility, as a latent infection is established in the absence of gentamicin by just feeding the flies on a sucrose solution. We had previously reported that flies fed with P. aeruginosa for up to three days do not succumb within the next two weeks when they are fed on a sterile sucrose solution after having ingested the bacterial solution (Limmer et al., PNAS, 2011; Fig. 1C). Under the conditions of two days of PAO1 ingestion, we document in novel Fig. S1G that the carcass is equally well colonized under these conditions.

Figure: impact of gentamicin ingestion at diverse concentrations on the survival of injected PAO1 bacteria. The ingested antibiotics can act on bacteria present in the hemocoel at concentrations over 2 mg/mL and not at that used in our experiments (100 µg/mL).

Does melanization really induce the dormant state of the bacteria? I am not sure the provided data fully support this claim. Addressing these questions might provide a stronger evidence: Fig. 2 A-F: What causes the morphological changes of the bacteria? Melanization or the passage through the gut? Do authors see the same changes in bacteria retrieved from PO-deficient mutant flies? Fig. 2G: Do the authors see the same resistance of PAO1 that colonized PO mutant flies to antibiotics?

In a novel Fig. S4, we now document comprehensively the physiological state of PAO1 bacteria fed to PO-deficient flies. We find that these bacteria are susceptible to antibiotics treatment as they can be rescued from death by the injection of antibiotics on day 3 (Fig. S4A-B). Second, they show a mixed phenotype in terms of colony morphology (Fig. S4C) and bacterial morphology and cell wall properties: even though most bacteria appeared to have kept a rounded morphology, they predominantly (about 75%) expressed the O5-LPS antigen. We interpret these data in terms of a slower transition to virulence than in a septic injury model. Melanization thus strongly contributes to the establishment of latency, even though it is likely that other factors contribute to the establishment of dormancy, but at best provide a minor contribution.

How do PO mutants behave after PAO1 injection? Are they similarly more susceptible?

PPO1-PPO2 mutants are not more susceptible to PAO1 injection than wt controls (new Fig. S3C).

Fig. 3F: PPO1 is believed to be the fast-acting PPO, whereas PPO2 is deployed later in infection.

This statement is based on experimental data gained on larvae, not adults. It is not really clear whether the about 10% adult hemocytes that express PPO2 actually contain crystals, in as much as the adult may be better oxygenated than larvae that grow in a hypoxic environment (description by the laboratory of Prof. Jiwon Shim of a role for PO in respiration at the latest EDRC meeting).

How does the Western blot look for PPO1? Will it show an early induction of melanization that could drive the change into the dormant state?

We provide below a characterization of the PPO antibody we use by Western blot analysis. This antibody had originally been raised by the late Dr. Hans-Michael Müller against a PPO from mosquito cell lines, hence explaining its cross-reaction to both * Drosophila PPO1 and PPO2 (Muller, H.M., Dimopoulos, G., Blass, C., and Kafatos, F.C. (1999)). A hemocyte-like cell line established from the malaria vector Anopheles gambiae expresses six prophenoloxidase genes. J Biol Chem 274*, 11727-11735.). It follows that at least one PO is partially cleaved at day 2 and that both are fully cleaved by day6 of the establishment of the latent infection (Fig. 3F, Fig. S3F).

Figure: characterization of the antibody raised against A. gambiae PPO

Alternatively, the induction of melanization could also be measured with an L-DOPA test.

This experiment is not needed given the explanation provided above.

Fig. 3E: Melanization prevents the growth of PAO1 adhering to tissues, as shown in Fig. 3E. One can see higher levels of cfus in the carcass in PO deficient flies compared to wt flies. However, after, 5 days, there is no difference in the cfus of wt and mutant flies anymore. If the growth inhibition was melanization mediated, would we not expect a consistent growth of bacteria in PO mutants? How to explain the drop in cfus in PO deficient mutants?

This observation is difficult to account for and the explanations we can put forward at this stage are somewhat speculative. It appears that bacteria found in the tissues in PO-deficient flies have a morphology found in in vitro culture and within the gut, which does not correlate with virulence but also not with the avirulence state since they are LPS O5 positive. Given the shallow survival curves, we envision that there is a progressive release of bacteria from the tissue and then quick proliferation in the hemolymph in a few flies that would then die, but at a frequency too low to reliably ascertain in our hemolymph titer data, with a few flies displaying a high titer (Fig. 3D). By day5, the decreased titer in the carcass may reflect the progressive depletion of tissue-associated bacteria as they progressively become planktonic.

Fig. 5D: How do PAO1 bacteria react to Levofloxacin treatment? Do they still go into the dormant state? Do they still attach to tissues? The authors should show that Levofloxacin treatment leads to the same dormant state as gentamycin before interpreting the results of this experiment.

Taken together, our data yield a mixed result. When levofloxacin was fed for two days to latently-infected flies, we found that colonization was not altered (Fig. S2D’), in contrast to a septic injury model in which injected bacteria were susceptible to the ingested antibiotics (Fig. S2D”). Following the reviewer’s query, we have further monitored survival and bacterial colonization in the levofloxacin ingestion model. Fig. S2D had already demonstrated that ingested levofloxacin protects the flies from injected PAO1. Fig. S6F shows that the double mutant PO bacteria are protected from ingested PAO1 by the ingestion of this antibiotics. When we monitored the bacterial burden, we found for both wild-type and double PO mutant flies that the bacteria had been cleared in some 50% of the flies. The exact interpretation of the wild-type data is not straightforward. On the one hand, the colonizing bacteria may have become susceptible to the antibiotics even though they remained dormant. On the other hand, they might have been reactivated in their virulence and thus become secondarily susceptible to the antibiotics. For the double PO mutants, the 40% bacteria remaining may witness the mixed bacterial state of PAO1 in these mutants, as documented in Fig. S4. Nevertheless, the important point is that bacteria are unlikely to contribute to the demise of secondarily infected flies since they have been cleared in at least 50% of the flies, yet the secondarily challenged flies become susceptible only when the relevant melanization genes are affected. The nonPAO1-infected controls succumb faster to the infection than infected ones: the protection against secondary infections is provided by the activation of the melanization cascade by colonizing PAO1 bacteria, even if the colonization is transient in the levofloxacin treatment.

We have altered the main text to reflect these novel data: lines 387-403.

Minor comments:

Lines 68-72. Mechanisms that are listed are not specific against Gram-negative bacteria but rather general. Please correct.

We are of course aware of this. If it is general, it also applies to Gram-negative bacteria that are the focus of this article. Actually, an earlier version of the manuscript just mentioned the IMD pathway, hence the reference to Gram-negative bacteria. However, the Toll pathway is also required in the host defense against some Gram-negative pathogens such as P. aeruginosa. We have now deleted “Gram-negative” in this corrected version.

Line 95. In - as?

We are not sure we understand this comment. We have now added a reference documenting that P. aeruginosa can be found in rotting fruits (line 97).

Lines 182-187. Some background information is needed. What is O5 LPS antigen? What motivated the authors to look at it specifically?

The O-antigen is a long-chain polysaccharide motif that constitutes the outermost part of the cell wall. It varies according to the strain. We have added a couple of references that refer to O-antigen (line 198). We had actually already found out this result (unpublished) with the Serratia marcescens Db11 O-antigen (O18) that was not found in bacteria that had crossed the gut. The loss of the O5 antigen changes the surface of the bacterium and likely its interactions with tissues and/or the immune system. In the case of Serratia, we suspect that the loss of its O-antigen allows the bacterium to be phagocytosed in an eater-dependent manner.

Fig. 3C: Why PPO1 and Hayan and PPO1,2 and Sp7 are compared but not mutant vs wild type?

The reason is that it was obviously significant. We have now added the comparisons to wild-type in the revised figure.

How precise is estimation of bacteria in the carcass?

Even though it is not possible to measure how precise these measures are, they are nevertheless reproducible making us confident that they provide an estimate of the rough number of these bacteria found associated to tissues.

How do the authors prevent dissemination of the bacteria during dissection? I wonder if some bacteria might by lost during the dissection (when removing the gut and ovaries) or if you carry over some bacteria from the hemolymph into the carcass measurement? How to make sure, that the bacteria you recover were really adherent and were not leftover from the hemolymph?

It is not possible to prevent dissemination as we cannot fix the tissues and bacteria if we make cfu counts. However, the finding that bacteria are found in the hemolymph only for the first three days, with a distinct morphology from tissue-associated bacteria, and not at later time points make us confident that this is not an issue, which suggests that the bacteria are rather tightly attached to the tissues. As regards contamination of tissues by hemolymph, it is also not an issue since the hemolymph titers are so low. However, when the bacteria are actively proliferating to high levels, this is a legitimate concern.

I am also curious how the differences in the cfu levels between whole fly and carcass can be explained (Fig. 1D). After day 5 there are almost no bacteria left in the hemolymph, however, if you compare cfus in the whole fly vs. the carcass, one can see that the whole fly cfus are rising from day 4 onwards. Where do these bacteria come from if not from the hemolymph?

To assess the statement of the reviewer, we now have included the numerical values of the medians of the bacterial burdens displayed in Fig. 1D. There is no increased bacterial burden in whole flies between days 5 to 12; however, the titer is increased at days 15 and 22. Whether this slight increase is biologically relevant is questionable given the spread of the data (see also reply to previous point on the precision of measures). We cannot rigorously exclude that there might be a low-level proliferation of colonizing bacteria late in the latent infection, which has been observed in specific conditions of reactivation of dormant bacteria (Lin et al., in preparation).

Fig. S4D: If the protection to secondary PAO1 infection is not mediated via Imd or phagocytosis, is it mediated via melanization? How do melanization mutants (increased or decreased) respond to PAO1 secondary infection?

We have performed the experiment (Fig. S6A-B) and found that the protection was abrogated. As noted in the main text, the interpretation is however difficult since the bacteria are no longer in a dormancy state in the PPO mutants.

Significance

This study suggests that host factors, particularly specific immune responses, could drive the latent infections. Hence, besides bacterial mechanisms that received significant attention, we should not underestimate the host's contribution to promoting the latent state in bacteria.

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Referee #2

Evidence, reproducibility and clarity

Summary:

In this study, Chen and colleagues investigated a new latent infection model for Pseudomonas aeruginosa using Drosophila melanogaster as a host. First, the authors established a new model for latent Pseudomonas infection. The key feature of this model is the translocation of P. aeruginosa from the gut to the hemolymph and the colonization of fly tissues by the dormant bacteria. Bacteria that translocated from the gut appeared strikingly different in morphology and resistance to antibiotics compared to bacteria that were directly injected. Next, the authors suggest that melanization but not the Imd pathway or hemocytes are necessary to promote dormancy and colonization of fly tissues. Finally, flies with latent P. aeruginosa infection exhibit improved survival after secondary infections in a melanisation-dependent manner. The study reports an interesting model for latent infection, provides insights into the host factors promoting latency and describes some of the consequences of such latent infection for the host. However, some of the conclusions are not fully supported by the data and need further experimental evidence.

Major comments:

1. The latent infection model requires some clarifications. First, temperature. Could the authors explain why they used 18 {degree sign}C and could low temperature contribute to the establishment of dormancy? Second, the use of gentamycin. How does gentamicin affect PAO1 outside the gut? From Fig.1C It looks like the cfus in the hemolymph diminished rapidly after gentamicin treatment (around day 3), suggesting the potential effect of the antibiotic. Once the bacteria have crossed the gut and entered the hemolymph, they could still be affected by feeding flies the antibiotic. Is there a possibility that gentamicin treatment is a stress factor that could trigger or facilitate the transition to dormancy? The authors could test this experimentally either by omitting the antibiotic and assessing dormancy or by feeding injected flies with gentamycin and scoring dormancy.
2. Does melanization really induce the dormant state of the bacteria? I am not sure the provided data fully support this claim. Addressing these questions might provide a stronger evidence: Fig. 2 A-F: What causes the morphological changes of the bacteria? Melanization or the passage through the gut? Do authors see the same changes in bacteria retrieved from PO-deficient mutant flies? Fig. 2G: Do the authors see the same resistance of PAO1 that colonized PO mutant flies to antibiotics? How do PO mutants behave after PAO1 injection? Are they similarly more susceptible?
3. Fig. 3F: PPO1 is believed to be the fast-acting PPO, whereas PPO2 is deployed later in infection. How does the Western blot look for PPO1? Will it show an early induction of melanization that could drive the change into the dormant state? Alternatively, the induction of melanization could also be measured with an L-DOPA test.
4. Fig. 3E: Melanization prevents the growth of PAO1 adhering to tissues, as shown in Fig. 3E. One can see higher levels of cfus in the carcass in PO deficient flies compared to wt flies. However, after, 5 days, there is no difference in the cfus of wt and mutant flies anymore. If the growth inhibition was melanization mediated, would we not expect a consistent growth of bacteria in PO mutants? How to explain the drop in cfus in PO deficient mutants?
5. Fig. 5D: How do PAO1 bacteria react to Levofloxacin treatment? Do they still go into the dormant state? Do they still attach to tissues? The authors should show that Levofloxacin treatment leads to the same dormant state as gentamycin before interpreting the results of this experiment.

Minor comments:

Lines 68-72. Mechanisms that are listed are not specific against Gram-negative bacteria but rather general. Please correct.

Line 95. In - as?

Lines 182-187. Some background information is needed. What is O5 LPS antigen? What motivated the authors to look at it specifically?

Fig. 3C: Why PPO1 and Hayan and PPO1,2 and Sp7 are compared but not mutant vs wild type? How precise is estimation of bacteria in the carcass? How do the authors prevent dissemination of the bacteria during dissection? I wonder if some bacteria might by lost during the dissection (when removing the gut and ovaries) or if you carry over some bacteria from the hemolymph into the carcass measurement? How to make sure, that the bacteria you recover were really adherent and were not leftover from the hemolymph? I am also curious how the differences in the cfu levels between whole fly and carcass can be explained (Fig. 1D). After day 5 there are almost no bacteria left in the hemolymph, however, if you compare cfus in the whole fly vs. the carcass, one can see that the whole fly cfus are rising from day 4 onwards. Where do these bacteria come from if not from the hemolymph?

Fig. S4D: If the protection to secondary PAO1 infection is not mediated via Imd or phagocytosis, is it mediated via melanization? How do melanization mutants (increased or decreased) respond to PAO1 secondary infection?

Significance

This study suggests that host factors, particularly specific immune responses, could drive the latent infections. Hence, besides bacterial mechanisms that received significant attention, we should not underestimate the host's contribution to promoting the latent state in bacteria.

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Referee #1

Evidence, reproducibility and clarity

This works describes a latent Drosophila intestinal infection, which spreads systemically, with a direct systemic Drosophila infection using a common laboratory strain of Pseudomonas aeruginosa. The major observation of this study is that P. aeruginosa can cause a latent infection via its passage through the gut (as opposed to being injected). In doing so it exhibits cell rounding (instead of elongation), reduced cell motility, loss of O5-antigen, antibiotic resistance, ability to cross the intestinal barrier and circulate in the hemolymph and infiltrate the host tissue underneath the cuticle.

In addition, latent infection bacteria induce all brunches of the systemic response: the Imd pathway, phagocytosis, and the melanization cascade. Moreover, the melanization pathway protects the host from a secondary systemic infection with various types of bacterial and fungal microbes.

An issue that needs to be clarified is the sensitivity of P. aeruginosa virulence to its biochemical environment. The authors note that. For example, liquid bacterial culture in BHI induces the latent form of bacteria. So the growth conditions and the infection media play a major role in the infection process. They authors need to clarify further the effect of media and infection vehicles, sucrose (high/low), LB, and BHI (as well as temperature) on the latent phenotype.

Minor issues:

• Lines 579-581> How were the PAO1GFP/RFP constructed (details are needed)
• Figure 1D and other figures > CFUs given as Log2 are unconventional. One cannot easily deduce the burden unless e.g. translate 2e10 to ~1000 and 2e30 to ~10e9 CFUs.
• Figire S1D > "but from the outside of the gut". The given experiment does not prove that statement.
• Lines 146-7 > data are missing in support to the statement.
• Figure S1C > The effect of injury seems to be huge, and may account for much/most of the differences observed (including those between latent and active infection). This is further supported by Figure4A, injury may account for gut collapse and/or systemic stress.
• Figure S1D > How was "fated to die" assessed?
• Figure 3B/10th day > Average line is misplaced.
• Lines 382-5 > what is the evidence of gut damage (or the absence of it)? How do the bacteria escape the gut?
• Lines437-442 > The distinction between dormant P. aeruginosa in the fly tissues and persister cells (upon antibiotic treatment) cannot be justifies on the basis of relative bacterial numbers in the two systems. The extent of resistance to antibiotics though my serve that purpose.

Significance

The study is a significant advance to our knowledge.

Notwithstanding further explanations, it provides a solid basis of understanding active versus dormant bacteria.

It further establishes a mode of intestinal to systemic infection as a tool for further explorations.

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Reply to the reviewers

1. General Statements [optional]

All four reviewers have positive comments on the paper. We totally agree with their comments, and proposed controls and experiments. Most of them are already introduced in the present text and several new figures added, as we had the controls/experiments proposed. Few others are now being done and we hope to have the complete set of experiments ready in 2-3 months.

2. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

Reviewer #1

Most comments of this reviewer have already been done and included in the transferred manuscript, except for part of the first comment:

1.1 b. Is it possible that the loss of function of Wengen on its own has a phenotype? If so, that would suggest that Wgn in addition to its role in regeneration might be implicated in pro-survival processes in homeostatic conditions?

This issue is very important to understand the differential role of Wgn and Grnd. First of all, Wengen knock out (wgnKO; Andersen et al., 2015) is viable in homozygosis. However, in this paper we have focused on inducible mutants. Therefore, we have now crossed the flies to get the genotype hh-Gal UAS RNAi wgn and we will check for apoptotic phenotype, as suggested. This will take us few weeks of work.

Reviewer #2 Most comments have been already carried out and included in the transferred manuscript, except these ones:

*2.3. Aside from wgn, other RNAi experiments are not validated through independent RNAi lines. I suggest expanding the Supplemental Figures to reproduce a few key findings with independent RNAi lines. *

We have recently received a set of independent RNAi line to repeat the experiments for Traf1, Traf2, Ask1 from Bloomington Stock Center. And We did not do it before mainly because we wanted to focus on wgn and grnd. However, we agree with the Reviewer 2 and we will do the experiments. Another RNAi from VDRC for grnd and Tak1 have been ordered. These experiments will take about 2 months from the crosses to the analysis of results (some flies still to arrive, and many crosses will be done at 17ºC).

*2 4. In Figure 1E, the authors show that wgn RNAi enhances cell death caused by hh>egr. What is missing here is a wgn RNAi control without hh>egr. Is there any cell death caused by the loss of wgn alone (without hh>egr)? *

This control is now in progress. Expected to have it complete in 2 weeks.

*2.5. If wgn RNAi causes some degree of cell death, is the observed effect with hh>egr a significant genetic interaction, or merely additive? *

The result from the previous comment will help us to respond this point.

• 1. Is the wgn-p38 pathway sufficient to block egr induced cell death? The authors could test this by having hh>egr in the licT1.1 background. The authors have a more complex experiment in Figure 3, where licT1.1 is introduced into the hh>egr, wgn RNAi background. However, testing the effect of licT1.1 without wgn would establish a more direct relationship between egr and wgn-p38. *

We have set the crosses for the experiment hh>egr and licT1.1 as suggested. The results will be included in the new version of the manuscript. 1 month.

Reviewer #3

All comments already carried out and included in the transferred manuscript. See next sections.

__Reviewer #4 __

Major comments:

*4.3 In Figure 5, the cells expressing Rpr appeared to be pulled/extruded basally as expected. It would be beneficial to quantify Wgn and Grnd signals along cross-sections and provide higher magnification images of domain boundaries to illustrate differences in TNFR localization and levels. ** The micrographs for Grnd Figure 5B,D, F capture substantial signal from the peripodial epithelium where the salE/Pv> driver is likely not active? *

We will do a thorough quantification of high-resolution stacks of images and include higher magnification of the analyzed stacks. To this aim, we need some more weeks to collect the images of each genotype, processed and quantify them. We propose to do have this work done in two months.

*4.4 The non-autonomous induction of Wgn seems stronger when facing dying Rpr overexpressing cells simultaneously depleted of Eiger compared to Rpr OE alone. Should this be a reproducible, could the authors discuss potential reason for this observation? *

It is difficult to respond this question, without quantification. The quantification suggested in the previous point, will allow us to state if Wgn is more accumulated in rpr +egr than rpr alone. Therefore, the previous point will tell us if there are significant differences and if, so it will help us to discuss it.

Timing: The entire plan can be executed in 2-3 month.

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

__Reviewer #1 __

1.1 a- *The result in Fig1.H is somehow surprising. How does the overexpression of Egr induce caspase activation in the absence of its receptor Grnd? *

The results of Fig. 1H, in which egr+grndRNAi+wgnRNAi results in high apoptosis indicates that wgn down regulation compromises survival even in the absence of grnd. The reviewer correctly points that “How does the overexpression of Egr induce caspase activation in the absence of its receptor Grnd?”.

There is evidence that Eiger is involved in the regulation of the pro-apoptotic gene head involution defective (hid) in primordial germ cells (Maezawa 2009 Dev. Growth Differ., 51 (4) (2009), pp. 453-461) and in the elimination of damaged neurons during development (Shklover et al., 2015). Moreover, Eiger is necessary for HID stabilization and regulates HID-induced apoptosis independently of JNK signaling (Shklover et al., 2015). Therefore, in our discs egr activation in the absence of grnd and wgn can still result in apoptosis because of the absence of wgn’s survival signal and, presumably, activation of hid.

We have introduced this issue in the text as:

“To check for epistasis between grnd and wgn, we activated hh> egrweak and knocked down both TNFRs. We found high levels of cell death compared to wgn RNAi alone (Fig. 1H and 1I), which demonstrates that wgn down-regulation is dominant over grnd. This is surprising as it is generally assumed that Egr interacts with Grnd to induce apoptosis via JNK, which in turn activates the proapoptotic gene hid (Andersen et al., 2015; Diwanji & Bergmann, 2020; Fogarty et al., 2016; Igaki et al., 2002; Moreno, Yan, et al., 2002; Sanchez et al., 2019; Shlevkov & Morata, 2012). Interestingly, Egr is necessary for HID stabilization and can regulate HID-induced apoptosis independently of JNK (Shklover et al., 2015). Therefore, cells egrweak that downregulate grnd and wgn can still be eliminated because the lack of both Wgn-survival signal and the pro-apoptotic Grnd/JNK signal could result in an alternative pathway of apoptosis.”

*1.2- In Fig.6, it would be relevant to include wengen inactivation within the domain where rpr is expressed to show that wengen is not required autonomously for regeneration (sal>rpr + wgn RNAi). What is the phenotype of the adult wing of sal-lexA>rpr + nub-gal4 >wgn RNAi animals.? *

We have already added a new figure (Fig. S4C) containing this data. As shown, both wgnRNAi alone and wgn RNAi + rpr do not show relevant anomalies and regenerate normally. Therefore, we conclude that wgn is not autonomously required for regeneration.

The adult wings sal-lexA>rpr + nub-gal4 >wgn RNA result in a strong aberration, as regeneration is inhibited. This experiment has been also added in another figure (Fig. S4B) it is done.

*1.4 Minor- In fig.1I, it is surprising that knockdown of neither Grnd nor dTRAF2 significantly affects Egr-induced apoptosis *

After applying a One-Way ANOVA test to compare all the groups against all the groups in fig. 1B no significative differences were detected between Control and RNAi grnd or RNAi dTRAF2 (p>0,05). But if we apply a Student’s T test, which is less restrictive, we obtain, indeed, significative differences:

Control vs. RNAigrnd p=9,48x10-7

Control vs. RNAi dTRAF2 p=2,47x10-7

We have now added in the text:

“Note that when egrweak cells downregulated dTRAF2 or grnd the cell death area ratio is slightly lower than egrweak alone (Fig. 1I), comfirming that dTRAF2 and Grnd contribute to apoptosis in egrweak cells.”

*1.5 Minor The ability of the wing disc to regenerate has been associated with the induction of a developmental delay mediated by Dilp8. Are the authors observing this developmental delay is the case of sal-lexA>rpr + Ap-gal4 >wgn RNAi or sal-lexA>rpr + Ci-Gal4>wgn RNAi *

The developmental delay due to Dilp8 has been observed by many laboratories, indeed. The question of the reviewer is relevant because if there is no delay in pupariation, regeneration could be compromised not because regeneration has been affected but because after pupariation regeneration is impeded.

However, delay in pupariation has been found in our experiments. Usually for 11hrs of heat shock (to induce apoptosis) we found 1-2 days of delay.

We have added the following text:

“The ability of the wing disc to regenerate after genetic ablation has been associated with the induction of a developmental delay (Colombani et al., 2012; Garelli et al., 2012; Jaszczak et al., 2015; Katsuyama et al., 2015; Smith-Bolton et al., 2009). All genotypes analyzed in figure 6 showed a similar developmental delay of 1-2 days (at 17ºC) after genetic ablation in comparison to the animals of the same genotype in which no genetic ablation was induced, i.e. developed continuously at 17ºC (Fig. S4A). After the adults emerged, the wings were dissected, and regeneration was analyzed.”

*1.7 Minor - The investigation of the evolutionary origin of TNFR in drosophila included in Fig.2 is cutting a bit the flow of the results. *

The evolutionary origin starts now with a sentence that can smoothen the flow and few changes in that paragraph have been made:

“Opposing roles between proteins of the TNFR superfamily suggests that they have an ancient origin and have followed divergent evolutionary paths. To track the differences observed between grnd and wgn, we decided to investigate the evolutionary origin of these two Drosophila genes.”

*1.8 Minor The authors could explain in more details the double transactivation system for non-fly specialists. *

The entire section has been re-written in Material and Methods.

*1.9 Minor - It can be interesting to include and/or discuss these few references: *

*PLoS Genet. 2019 Aug; 15(8): e1008133. ** PLoS Genet. 2022 Dec 5;18(12):e1010533. FEBS Lett. 2023 Oct;597(19):2416-2432. *

*Curr Biol. 2016 Mar 7;26(5):575-84. *

*Nat Commun. 2020 Jul 20;11(1):3631. **

*

All these references, and few others, have been introduced in the text.

__Reviewer #2 __ *2. 1. The authors find that wgn RNAi enhances hh>egr-induced apoptosis. They validate the results with two independent RNAi lines in Figure S1. However, Figure S1 is missing a control without wgn RNAi, and therefore, the results are difficult to assess. *

Fig S1A now contains this control.

• 1. Are the two independent wgn RNAi lines targeting different regions of the coding sequence? *

As the regions targeted by the 2 RNAi’s are different, see below, we have included in the text:

“This observation was corroborated with an independent RNAi-wgn strain targeting a different region in the coding sequence (Fig. S1A and S1B). “

Bloomington BL55275 (dsRNA-HMCO3962)

VDRC GD9152 (dsRNA-GD3427)

*2.7. In Figure 4, the authors show that egr expression induces ROS and performs anti-oxidant experiments. This part could be strengthened if they show that the ROS sensor signal disappears after Sod::Cat expression. *

We had done this experiment and there is a definitively drop in Mitosox in discs in which the weak allele of egr is active. We have included this new image in Figure 4G and in the text.

*2.8. How effective is egr RNAi? In Figure 5E, F, the authors knock down egr and obtain negative results. Based on this, the authors argue that Wgn localization occurs through an egr-independent mechanism. Drawing strong conclusions based on a negative result with egr RNAi is not a good practice since one cannot rule out residual egr activity that mediates the effect (of course , because there is cell death as well, death cells express egr). I suggest either finding ways to completely abolish egr function, or tone down the conclusion. *

We have used ‘after knocking down eiger’ instead of in the ‘absence’ or ‘abolish’ eiger.

• 1. Figure 6 shows that wgn RNAi aggravates the reaper phenotype. What's missing is a control that expresses wgn RNAi but not reaper. *

Control experiments using the UAS-wgnRNAi in the absence of rpr are now shown in figure S4C.

Reviewer #3 ____ 3.1.Minor Fig 6C-E would need a control disc without induced apoptosis (ie wildtype disc) stained for phospho-p38 as a baseline comparison. This is important to judge the significance of the remaining phospho-p38 in panel E where wgn is knocked down. The authors write ** " However, after knocking down wgn, phosphorylated p38 in the wing pouch ** surrounding the apoptotic cells was abolished (Fig. 6E)." *Depending on the amount of phospho-p38 in control discs, this may need to be rephrased to "strongly reduced" instead of "abolished". *

A control disc stained with P-p38 has been added in Figure 6.

We have changes ‘abolished’ by ‘strongly reduced’.

* 3.2. This sentence in the Intro needs fixing because TNFa doesn't transduce the signal from TNFR to Ask1 since it's upstream of TNFR: "TNFα can transduce the TRAF-mediated signal from TNFR to Ask1 to modulate its activity (Hoeflich et al., 1999; Nishitoh et al., 1998, p. 0; Obsil & Obsilova, 2017; Shiizaki et al., 2013)." *

We have rephrased this sentence by:

“TNFα binds to TNFRs which in turn interact with TRAFs to transduce the signal to Ask1 to modulate its activity”.

*3.3a In the results section, the authors start by ectopically overexpressing Eiger. Are there conditions where Eiger expression is induced in the wing? If yes, it would be helpful for the reader to mention that this system with the genetically GAL4-induced expression of Eiger aims to phenocopy one of these conditions. *

Eiger ectopic expression has been induced in the wing to generate apoptosis. This is a common technique in Drosophila, and the Reviewer3 is right that a sentence should be useful for the reader.

A sentence has been introduced at the beginning of the results section:

“Ectopic expression of egr in Drosophila imaginal discs results in JNK-dependent apoptosis (Brodsky et al., 2004; Igaki et al., 2002; Moreno, Yan, et al., 2002).”

*3.3b Fig 2C is not very self-explanatory: it is worth writing out what Hsa (H. sapiens), Bla and Sco stand for (there is plenty of space). *

We have re-designed figure 2 to make it more self-explanatory.

*3.4. This sentence is confusing: ** " ...Wgn localization were due to ROS or to the expression of egr, we used RNAi to knock down egr in the apoptotic cells and found that reduced Egr/TNFα had no effect on Wgn localization (Fig. 5E, 5F)." The authors may want to specify that Wgn is still accumulated even without Egr. ("No effect" is unclear). *

This sentence has been modifies as:

“Wgn localization were due to ROS or to the expression of egr, we used RNAi to knock down egr in the apoptotic cells and found that Wgn accumulation was not altered by the knocking down Egr/TNFα (Fig. 5E, 5F). “

*3.5 Comment. It discovers that Wengen is activated by ROS. In fact, since Wengen binds TNF with an affinity that is several orders of magnitude lower than Grindelwald, and since Wengen is not even located at the cell membrane, these data call into question whether Wengen is a TNF receptor, or a ROS receptor? Could the authors comment on this ? Could it be that the results obtained in the past showing that Wengen is activated by TNF were actually due to TNF inducing apoptosis, leading to production of ROS, leading to activation of Wengen?

*

We totally agree with Reviewer#3. We have added a final paragraph in the discussion section.

“We speculate that the subcellular location of Wgn and Grnd may contribute to the different functions of both receptors. Grnd is more exposed at the apical side of the plasma membrane, which makes this receptor more accessible for ligand interactions (Palmerini et al., 2021). Wgn, embedded in cytoplasmic vesicles, is less accessible to the ligand and could be more restricted to being activated by local sources of signaling molecules, such as ROS. In contrast to initial reports (Kanda et al., 2002; Kauppila et al., 2003), los-of-function of wgn does not rescue Egr-induced apoptosis in the Drosophila eye (Andersen et al., 2015), which supports our observation in the wing that Wgn is not required for Egr-induced apoptosis. Instead, Egr-induced apoptosis generates ROS which target intracellular Wgn to foster a cell survival program of cells close to the apoptotic zone.”

__Reviewer #4 __

*4.1 b Are phospho-p38 levels increased in cells expressing Egr[weak]? *

We have the results of these experiments. To respond to this point, a new figure has been added (Fig. S4) in which we show the P-p38 levels are increased (non-autonomously) in egrw, as previously found for reaper. In addition, we show that egrw + activation of p35 and egrw + activation of Sod1::Cat results in strong reduction of P-p38. This indicates that P-p38 is stimulated by the ROS produced by apoptotic cells.

The text now:

“It is worth noting that cells egrw induce phosphorylation of p38 in neighboring cells (Fig. S4A) and that, as previously found for rpr (REF), depends on ROS generated by egrw apoptotic cells (Fig. S4B, C).”

*4.2 In Figure 4C it appears that the Dcp-1 positive cells move apically rather than basally. Including nuclear staining would be very informative allowing assessment of tissue morphology. ** The authors focus on the pouch region of the wing imaginal disc, where phenotypes are strong and obvious. However, the hh-Gal4 driver also affects posterior cells in the hinge and notum, where the effects of Eiger[weak] overexpression seem weaker (e.g., minimal to no MitoSox signal in hinge and notum posterior cells). Could the authors explain this observation? *

Point 1: Actually, cells move more basally, though some move more apical as well. Depending on the section cells the image could be confusing. To solve that, we show now a plane on these discs at apical and a plane basal. Both high magnifications. There one can see that there is more concentration of pyknotic nuclei basally. We have added this observation in a new supplementary figure (Fig. S3) and the corresponding text in page 5: “Apoptotic cells in egrweak are characterized by pyknotic nuclei and are positive for Dcp1. These cells tend to concentrate in the basal side of the epithelium, although some are scattered apically (Fig. S3). Accumulation of Wgn was observed in healthy anterior cells adjacent to both apical and basal egrweak cells (Fig. 4, Fig. S3A, B).”

Point 2 Comment on MitoSOX in notum: At the stages of the imaginal discs used in this study, almost all notum cells are anterior compartment. The hh positive cells in notum much less abundant, therefore most of the staining was found in the posterior compartment of the wing pouch.

*4.5 Figure 6 C-E. Does WgnRNAi potentiates and GrndRNAi suppress Rpr-induced apoptosis similarly to their effects when knocked down in Eiger[weak]OE cells? *

The areas controlled by salE/Pv >rpr (dotted lines) are full of pycnotic nuclei, which indicates concentration of apoptotic cells in all genotypes shown.

Thus, in the conditions generated here, apoptosis is not inhibited and grnd RNAi does not interfere with the activation of P-p38. In wgn knock down, phospho-p38 is strongly inhibited, indicating the importance of wgn in phosphorylation of p38.

To clarify this point, we have added in the text: “Note that rpr-induced apoptosis is not suppressed after knocking down grnd or wgn.” Also in the figure legend we added: “White lines in the confocal images outline the salE/Pv-LHG,LexO-rpr dark area full of pyknotic nuclei of apoptotic cells.”

4.6 The activation of p38 following salE/Pv>rpr-mediated ablation as shown by immunostaining is noteworthy. While loss Grnd knockdown leads to phospho-p38 signal enrichment around the rpr-expressing cells, WgnRNAi results in reduced phospho-p38 signal in the wing pouch but also beyond the nub-expression domain. Do salE/Pv>rpr nub>WgnRNAi cells still generate ROS?

So far there is no evidence of Wengen as a ROS scavenger. We have evidence that ROS (using MitoSox probe) are produced in egrweak + Wgn RNAi cells. Thus, the inhibition of wgn expression does not block ROS production. A new figure shows this observation (Figure S4A).

4.7 Are ROS responsible for the long-range signaling and p38 activation, referring to authors' previous work Santabarbara-Ruiz et al., 2019, PLoS Genet 15(1): e1007926. https://doi.org/10.1371/journal. pgen.1007926, Figure 5G?

ROS are responsible for p38 activation as shown in a new figure (Fig. S4). In this new figure egrweak is activated in hh, and p38 is most of cells in the posterior compartment, and also anterior. However, after blocking apoptosis or ROS production, this P-p38 is reduced.

4.8 Minor I propose rephrasing the description of "UAS-Egr[weak] transgene, a strain that produces a reduced Egr/TNFα activity". It could imply a loss of function strain rather than a transgene that causes mild/moderate Egr overexpression.

The sentence has been rephrases as suggested (End of the first paragragraph in results section).

*4.9 Minor. I recommend the authors to revise the charts for improved clarity in genotype representation. For example, in Figure 1I, the label "control-GFP" might be misleading. It would be beneficial to specify that "control" refers to Eiger[weak] alone with other manipulations being done simultaneously with Eiger[weak] overexpression. *

All charts have been revised.

4.10 Minor. Additionally, considering that individuals with color blindness may struggle to differentiate between red and green colors, I strongly suggest using a color-blind-friendly palette, especially in Figure 4A, C, G, and Figure 4A, C, E." ** All images have been revised for color blind code.

• 11 Minor. Providing detailed information regarding the reagents used in the study, such as Catalogue Numbers or RRIDs, is beneficial for enhancing reproducibility. *

We have added the RRID and Cat #. If no ID was available, we added the reference or contact.

4.12 This reviewer points two limitations that we are now trying to solve:

*Limitations: *

*Quality of the imaging – higher magnification images and quantification would enhance the study. ** The summarizing model may contain excessive speculations that lack support from the data or references to the existing literature. *

Quality of imaging. We have now an extra supplemental figure with higher magnifications. Extra higher magnifications will be included in the next version as well as quantification, as exposed for the Revision Plan points 4.3 and 4.4.

Model: We have re-written the paragraph on the model, introduced references and drop some speculations. We hope the current version will be more convincing for the reader.

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

Please include a point-by-point response explaining why some of the requested data or additional analyses might not be necessary or cannot be provided within the scope of a revision. This can be due to time or resource limitations or in case of disagreement about the necessity of such additional data given the scope of the study. Please leave empty if not applicable.

Reviewer 1

*1.3. Is the overexpression of Wengen sufficient to increase tissue regeneration? *

The suggestion of the reviewer is a key point in regeneration biology: how to accelerate regeneration?

We have demonstrated that Wengen is upstream the Ask1-p38 axis that drives regeneration. The reviewer wonders if Wengen overexpression can result in increase in regeneration. In a previous work we have demonstrated that p38 activation is key for regeneration but its overexpression can be deleterious (Esteban-Collado et al., 2021). Only in discs that sensitized for low p38 (starvation, low Akt, Ask1S83A mutant), the overexpression rescues regeneration. Therefore, the levels of the Wgn-Ask1-p38 have to be very tightly controlled. An excess will be deleterious. We are aware of the importance of the question, but at this point we do not have the technology to finely control Wgn-Ask1-p38 levels to do this experiment.

1.6 Minor - It possible to test the induction of apoptosis in a wgn null mutant background to see if the phenotype is even stronger than the one observed with RNAi (the wgn RNAi is induced at the same time than egr or rpr overexpression).

Flies wgnKO survive, but they gave us problems when carrying transgenes for our design of genetic ablation. Indeed, we tried to generate wgnKO carrying Gal4+tubGal80+eigerweak without success.

In addition, the reason we have used an inducible mutant is because it allows us to work in time and space without altering expression in other cell types beyond wing discs. Wgn is required in other organs during development like gut, trachea and axon growth, etc.., and thus, we ensure the affected cells belong to the tissue analyzed.

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Referee #4

Evidence, reproducibility and clarity

The study by Florenci Serras and colleagues presents compelling evidence highlighting distinct functions of the two Drosophila TNFRs, Wengen (Wgn) and Grindewald (Grnd) in developing imaginal epithelia. The study shows that while Grnd-dTraf2-Tak1 module controls apoptosis in Eiger (Egr)-dependent manner, Wgn-dTraf1-Ask1 promotes survival likely via p38 signaling independent of Egr. Their phylogenetic analysis underscores the ancient origin of both receptors while revealing their divergent evolutionary path, manifested by markedly different CRD sequences. Moreover, Wgn shows higher degree of similarity to mammalian TNFRs. Using functional genetics and confocal imaging of immunostained wing imaginal discs, the authors confirm the differential localization of Wgn and Grnd in imaginal cells, consistent with several recent studies. Interestingly, they demonstrate distinct responses between Grnd that is internalized upon Eiger[weak] overexpression from the plasma membrane, and Wgn, which cytoplasmic levels decrease in Eiger[weak] OE cells but become enriched in neighboring wild type cells. The non-autonomous accumulation of Wgn required ROS but not Eiger production by dying cells. Finally, employing an elegant double-driver lexA/lexO and Gal4/UAS system, enabling independent gene manipulation in specific domains of the wing imaginal discs, the authors established the essential role of Wgn, but not Grnd, in the regenerative response to apoptosis, including the occurrence of phosphorylated p38.

Major comments:

The conclusion regarding the protective role of p38 in response to Egr[weak] should be supported by a p38 knockdown experiment. Are phospho-p38 levels increased in cells expressing Egr[weak]?

In Figure 4C it appears that the Dcp-1 positive cells move apically rather than basally. Including nuclear staining would be very informative allowing assessment of tissue morphology. The authors focus on the pouch region of the wing imaginal disc, where phenotypes are strong and obvious. However, the hh-Gal4 driver also affects posterior cells in the hinge and notum, where the effects of Eiger[weak] overexpression seem weaker (e.g., minimal to no MitoSox signal in hinge and notum posterior cells). Could the authors explain this observation?

In Figure 5, the cells expressing Rpr appeared to be pulled/extruded basally as expected. It would be beneficial to quantify Wgn and Grnd signals along cross-sections and provide higher magnification images of domain boundaries to illustrate differences in TNFR localization and levels. The micrographs for Grnd Figure 5B,D, F capture substantial signal from the peripodial epithelium where the salE/Pv> driver is likely not active?

The non-autonomous induction of Wgn seems stronger when facing dying Rpr overexpressing cells simultaneously depleted of Eiger compared to RprOE alone. Should this be a reproducible, could the authors discuss potential reason for this observation?

Figure 6 C-E. Does WgnRNAi potentiates and GrndRNAi suppress Rpr-induced apoptosis similarly to their effects when knocked down in Eiger[weak]OE cells? The activation of p38 following salE/Pv>rpr-mediated ablation as shown by immunostaining is noteworthy. While loss Grnd knockdown leads to phospho-p38 signal enrichment around the rpr-expressing cells, WgnRNAi results in reduced phospho-p38 signal in the wing pouch but also beyond the nub-expression domain. Do salE/Pv>rpr nub>WgnRNAi cells still generate ROS? Are ROS responsible for the long-range signaling and p38 activation, referring to authors' previous work Santaba ́rbara-Ruiz et al., 2019, PLoS Genet 15(1): e1007926. https://doi.org/10.1371/journal. pgen.1007926, Figure 5G?

Minor comments:

I propose rephrasing the description of "UAS-Egr[weak] transgene, a strain that produces a reduced Egr/TNFα activity". It could imply a loss of function strain rather than a transgene that causes mild/moderate Egr overexpression.

I recommend the authors to revise the charts for improved clarity in genotype representation. For example, in Figure 1I, the label "control-GFP" might be misleading. It would be beneficial to specify that "control" refers to Eiger[weak] alone with other manipulations being done simultaneously with Eiger[weak] overexpression. Additionally, considering that individuals with color blindness may struggle to differentiate between red and green colors, I strongly suggest using a color-blind-friendly palette, especially in Figure 4A, C, G, and Figure 4A, C, E."

Providing detailed information regarding the reagents used in the study, such as Catalogue Numbers or RRIDs, is beneficial for enhancing reproducibility.

Significance

This is a very solid study that uncovers unique roles of Drosophila TNFRs in regulating imaginal cell behaviors crucial for tissue regeneration. It expands our knowledge on processes controlled by TNFR-mediated signaling, highlighting the potential for ligand-independent regulation. The study nicely complements recent findings by several laboratories (Letizia et al., 2023; Loudhaief et al., 2023; Palmerini et al., 2021). Beyond its contribution to fundamental biology, the study has biomedical implication for regenerative medicine. It emphasizes the necessity of balancing TNFR activities, downstream signaling and their dependence on ligands, providing important insights for the development of receptor agonists or antagonists. The findings are relevant to audience interested in developmental and regenerative biology, gene evolution.

Strengths: functional genetics revealing distinctive roles for the two TNFRs in Drosophila and their dependency on ligand in the paradigm of tissue regeneration.

Limitations: quality of the imaging - higher magnification images and quantification would enhance the study. The summarizing model may contain excessive speculations that lack support from the data or references to the existing literature.

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Referee #3

Evidence, reproducibility and clarity

Summary:

TNF receptors have a broad range of possible function, from inducing apoptosis to promoting cell survival and proliferation. How this works is not completely understood. Drosophila has two TNF receptors, Wengen and Grindelwald. This manuscript nicely shows that Grindelwald is pro-apoptotic while Wengen promotes cell survival and proliferation. Strikingly, if TNF is expressed in Drosophila tissue, knockdown of the receptor Wengen leads to elevated levels of apoptosis, clearly showing its cell-protective function. Interestingly, the authors find that Wengen is activated by ROS produced by neighboring dying cells - regardless of whether they are dying due to TNF signaling or not - and that Wengen then activates p38 downstream to mediate a regenerative response.

Major comments:

Overall the conclusions are interesting, clear and convincing. The data are of very good quality. I only have a few minor comments below.

Minor comments:

1. Fig 6C-E would need a control disc without induced apoptosis (ie wildtype disc) stained for phospho-p38 as a baseline comparison. This is important to judge the significance of the remaining phospho-p38 in panel E where wgn is knocked down. The authors write " However, after knocking down wgn, phosphorylated p38 in the wing pouch surrounding the apoptotic cells was abolished (Fig. 6E)." Depending on the amount of phospho-p38 in control discs, this may need to be rephrased to "strongly reduced" instead of "abolished".
2. This sentence in the Intro needs fixing because TNFa doesn't transduce the signal from TNFR to Ask1 since it's upstream of TNFR: "TNFα can transduce the TRAF-mediated signal from TNFR to Ask1 to modulate its activity (Hoeflich et al., 1999; Nishitoh et al., 1998, p. 0; Obsil & Obsilova, 2017; Shiizaki et al., 2013)."
3. In the results section, the authors start by ectopically overexpressing Eiger. Are there conditions where Eiger expression is induced in the wing? If yes, it would be helpful for the reader to mention that this system with the genetically GAL4-induced expression of Eiger aims to phenocopy one of these conditions.
4. Fig 2C is not very self-explanatory: it is worth writing out what Hsa (H. sapiens), Bla and Sco stand for (there is plenty of space).
5. This sentence is confusing: " ...Wgn localization were due to ROS or to the expression of egr, we used RNAi to knock down egr in the apoptotic cells and found that reduced Egr/TNFα had no effect on Wgn localization (Fig. 5E, 5F)." The authors may want to specify that Wgn is still accumulated even without Egr. ("No effect" is unclear).

Significance

This manuscript makes several important discoveries:

1. it clearly shows that one TNF receptor, Grindelwald, is mainly pro-apoptotic, while the other, Wengen, is mainly pro-survival. This provides a mechanistic explanation for the dual role of the TNF, Eiger.
2. It discovers that Wengen is activated by ROS. In fact, since Wengen binds TNF with an affinity that is several orders of magnitude lower than Grindelwald, and since Wengen is not even located at the cell membrane, these data call into question whether Wengen is a TNF receptor, or a ROS receptor? Could the authors comment on this ? Could it be that the results obtained in the past showing that Wengen is activated by TNF were actually due to TNF inducing apoptosis, leading to production of ROS, leading to activation of Wengen?
3. It was previously shown that damage, for instance in the fly intestine, induces production of ROS, which then activates p38, leading to a proliferative/regenerative response. This manuscript provides a missing mechanistic link, showing that the ROS activates Wengen, which in turn activates p38. This thereby completes the mechanistic chain of events from damage to the regenerative response.

Hence, overall, this is a very interesting study. It will be of interest for a broad audience of people studying TNF signaling, stress signaling and stress response, tissue damage and repair, and regeneration.

My expertise: Drosophila, growth, signaling

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Referee #2

Evidence, reproducibility and clarity

The Drosophila genome encodes a single TNFa ortholog, eiger (egr), and two TNF Receptros (TNFR), wengen (wgn) and grindelwald (grnd). While egr overexpression can cause apoptosis, the authors here report that wgn and grnd have opposing roles in cell death and survival. Specifically, the authors show evidence that grnd promotes cell death in response to egr expression, while wgn promotes cell survival through the p38 MAP Kinase pathway. They further show that apoptotic cells have high levels of ROS, which activates the wgn-p38 axis for tissue regeneration, independent of egr.

Overall, the manuscript is well written. At the same time, there are some technical concerns and missing controls that need to be addressed. Below are a few specific comments for the authors' consideration:

Major Comments

1. The authors find that wgn RNAi enhances hh>egr-induced apoptosis. They validate the results with two independent RNAi lines in Figure S1. However, Figure S1 is missing a control without wgn RNAi, and therefore, the results are difficult to assess.
2. Are the two independent wgn RNAi lines targeting different regions of the coding sequence?
3. Aside from wgn, other RNAi experiments are not validated through independent RNAi lines. I suggest expanding the Supplemental Figures to reproduce a few key findings with independent RNAi lines.
4. In Figure 1E, the authors show that wgn RNAi enhances cell death caused by hh>egr. What is missing here is a wgn RNAi control without hh>egr. Is there any cell death caused by the loss of wgn alone (without hh>egr)?
5. If wgn RNAi causes some degree of cell death, is the observed effect with hh>egr a significant genetic interaction, or merely additive?
6. Is the wgn-p38 pathway sufficient to block egr induced cell death? The authors could test this by having hh>egr in the licT1.1 background. The authors have a more complex experiment in Figure 3, where licT1.1 is introduced into the hh>egr, wgn RNAi background. However, testing the effect of licT1.1 without wgn would establish a more direct relationship between egr and wgn-p38.
7. In Figure 4, the authors show that egr expression induces ROS and performs anti-oxidant experiments. This part could be strengthened if they show that the ROS sensor signal disappears after Sod::Cat expression.
8. How effective is egr RNAi? In Figure 5E, F, the authors knock down egr and obtain negative results. Based on this, the authors argue that Wgn localization occurs through an egr-independent mechanism. Drawing strong conclusions based on a negative result with egr RNAi is not a good practice since one cannot rule out residual egr activity that mediates the effect. I suggest either finding ways to completely abolish egr function, or tone down the conclusion.
9. Figure 6 shows that wgn RNAi aggravates the reaper phenotype. What's missing is a control that expresses wgn RNAi but not reaper.

Significance

There is now a detailed understanding of mammalian TNFRs, which play pro-apoptotic and non-apoptotic roles depending upon the context. Previous studies had also reported that TNFR1 respond to ROS. By comparison, our understandings of the two TNFRs in Drosophila remain rudimentary. The two receptors have different loss-of-function phenotypes, some of which may be independent of egr signaling. The major significance of this work is in delineating the distinct behaviors of the two Drosophila TNFRs, centering around their pro-apoptotic, or pro-survival properties.

Audience: This study will draw the interest of Drosophila geneticists, those interested in Reactive Oxygen Species and cell death, and evolutionary biologists.

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Referee #1

Evidence, reproducibility and clarity

Tumor necrosis factor (TNF)-α stands out as a remarkably conserved pro-inflammatory cytokine that plays crucial roles in immunity, tissue repair, and cellular homeostasis. The Drosophila TNF-TNF receptor (TNFR) system, known for its simplicity, combined with a versatile genetic toolkit, has been instrumental in unraveling the intricate mechanisms governing both the physiological and pathological functions mediated by TNF. Recently, the fly TNFR Wengen has been described to have ligand independent functions in maintaining tissue homeostasis and tracheal remodeling. The current manuscript describes a novel TNF/Egr-independent function of Wengen in regulating tissue regeneration in imaginal discs. The authors identify both the upstream regulator (ROS) and the downstream signaling pathway through Ask1/p38 MAPK. The data presented are solid and support an interesting model where ROS emanating from damaged tissue triggers Wgn-dependent signaling in adjacent cells to promote regeneration. Few points could be addressed:

Major points:

• The result in Fig1.H is somehow surprising. How does the overexpression of Egr induce caspase activation in the absence of its receptor Grnd? Is it possible that the loss of function of Wengen on its own has a phenotype? If so, that would suggest that Wgn in addition to its role in regeneration might be implicated in pro-survival processes in homeostatic conditions?
• In Fig.6, it would be relevant to include wengen inactivation within the domain where rpr is expressed to show that wengen is not required autonomously for regeneration (sal>rpr + wgn RNAi). What is the phenotype of the adult wing of sal-lexA>rpr + nub-gal4 >wgn RNAi animals?
• Is the overexpression of Wengen sufficient to increase tissue regeneration?

Minor points:

• In fig.1I, it is surprising that knockdown of neither Grnd nor dTRAF2 significantly affects Egr-induced apoptosis
• The ability of the wing disc to regenerate has been associated with the induction of a developmental delay mediated by Dilp8. Are the authors observing this developmental delay is the case of sal-lexA>rpr + Ap-gal4 >wgn RNAi or sal-lexA>rpr + Ci-Gal4>wgn RNAi
• It possible to test the induction of apoptosis in a wgn null mutant background to see if the phenotype is even stronger than the one observed with RNAi (the wgn RNai is induced at the same time than egr or rpr overexpression).
• The investigation of the evolutionary origin of TNFR in drosophila included in Fig.2 is cutting a bit the flow of the results.
• The authors could explain in more details the double transactivation system for non-fly specialists.
• It can be interesting to include and/or discuss these few references:

PLoS Genet. 2019 Aug; 15(8): e1008133.

PLoS Genet. 2022 Dec 5;18(12):e1010533.

FEBS Lett. 2023 Oct;597(19):2416-2432.

Nat Commun. 2020 Jul 20;11(1):3631.

Curr Biol. 2016 Mar 7;26(5):575-84.

Significance

The understanding of the mechanistic interplay between TNFR in integrating TNF-dependent and independent signals to stimulate distinct downstream responses lays the foundation for investigating whether these insights can be generalized to other members within the TNFR superfamily in all organisms. This work is relevant for a large audience of researchers working in the field of inflammation and TNFR.

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Reply to the reviewers

We thank the reviewers for their reading of our manuscript, which we believe has led to substantial improvements.

To aid clarity, we have split Fig. 1 into three separate figures.

For convenience, we have put all major changes in the text in blue.

Reviewer #1

Evidence, reproducibility and clarity

Summary: Hui et al. tackle a crucial question in biology: what factors influence the preference for carbon sources in yeasts?

They reveal that the growth rate on palatinose exceeds that on glucose,

The above statement is incorrect --- we think the reviewer may have confused sugars.

despite palatinose utilization being repressed in the presence of glucose. Consequently, the favored carbon source does not necessarily align with the one supporting the fastest growth rate. The study also delves into potential regulatory mechanisms governing carbon source preference and dismisses certain existing theories, such as the general carbon flux sensing mechanism proposed by Okano et al. [25].

Major comments: None

Minor comments:

The authors suggest that a higher growth rate implies a higher glycolytic flux (l63), a crucial assumption underpinning their interpretation of the absence of a ``general carbon flux sensing mechanism' (l65). To substantiate this significant conclusion, they could calculate the extracellular uptake fluxes (based on the time-course concentrations of biomass and substrates).

This suggestion is a good one, but unfortunately the number of data points in the new Fig. 3 are insufficient to estimate the uptake flux reliably.

To address whether glycolytic flux increases, we have added a new paragraph to the introduction explaining how all the sugars we consider feed upper glycolysis, providing either its first or second metabolite. We therefore think it highly likely that any differences in growth rate are generated by differences in glycolytic flux. Indeed, Hackett et al., 2016, showed that the glycolytic flux increases with growth rate when they changed extracellular glucose concentrations. We now include this reference in the Discussion.

The accumulation of certain by-products is known to be toxic, reducing cellular growth rate (e.g., acetate DOI: 10.1038/srep42135, ethanol DOI: 10.1016/B978-0-12-040308-0.50006-9, etc.), while they can also enhance growth under specific conditions (e.g., acetate DOI: 10.15252/embj.2022113079). Considering this is crucial to rule out certain hypotheses, such as the possibility that a by-product produced during growth on the first carbon source would not modulate growth on the second carbon source, potentially influencing the growth rate differentially in each phase. Although the authors use mutant strains to eliminate the role of some C2 compounds (acetate and ethanol), alternative pathways could be implicated in the (co-)utilization of these by-products. This aspect should be discussed, and ideally, the authors could quantify the time-course concentrations of by-products to assess their potential role.

We agree with the reviewer that extracellular acetate and ethanol may inhibit growth, although budding yeast might be less sensitive than E. coli, the subject of most of the studies provided.

Nevertheless, we think it unlikely that these chemicals modify the decision-making we see. First, the icl1Δ mutant we tested is unable to consume ethanol (Fernandez et al., 1992) or acetate (Lee et al., 2011) --- we now include these references in the SI --- and yet has wild-type behaviour (Fig. S2D). Second, we observe that isomaltase expression strongly decreases in the presence of galactose when we grow cells in a microfluidic device (Fig. S4), just like it does in batch culture (Fig. 3A), even though the constant flow of medium through the device removes any chemicals the cells excrete.

The general flux-sensing regulatory mechanism proposed by Okano et al. [25], which has been dismissed by this study, has recently been questioned, as discussed in DOI: 10.15252/embj.2022113079. This aspect should be included in the discussion.

Okano et al. studied E. coli while we study budding yeast. We therefore have shown that the understanding for that organism does not transfer to our eukaryotic example. We suspect that control in budding yeast combines both flux-sensing and specific regulation, as we say in the discussion, and so we consider our results to build on those of Okano et al.

Significance

Strengths & limitations: The work is robust, and the experiments in the study have been appropriately designed and conducted. The primary question of this study has been tackled using a combination of experimental and computational methods to thoroughly assess various regulatory and functional aspects. However, there are gaps in the data that could enhance key conclusions, notably the absence of glycolytic flux measurements. Moreover, further evidence is needed to substantiate the assertion that by-products do not play a role in carbon source preference.

Advance: This study represents a significant step forward in comprehending the nutritional strategy of microbes. The authors demonstrate that the preferred carbon source may not necessarily be the one supporting the fastest growth rate. Furthermore, they dismiss certain theories that have been proposed to explain the growth strategy of microbes on mixed carbon sources.

Audience: By addressing a fundamental question in life science, this work is important in the field of biology in general and of particular interest in systems biology, biotechnology, synthetic biology, and health. Consequently, it will be of interest to a broad audience.

Reviewer #2

Evidence, reproducibility and clarity

Summary: The authors have used microtiter plates to produce growth profiles on combinations of different sugars. From this data they have evaluated whether the sugars are co-consumed or if there is a preference for either sugar, seen as a diauxic shift. They found diauxie between galactose and the disaccharide palatinose, but co-consumption between palatinose and fructose. They further used strains with perturbations in their GAL regulon to attempt to explain this discrepency.

Major comments:

I unfortunately found a large portion of the present manuscript unintelligable.

Firstly, figures were incorrect to the point I could not dechiffre them: Figure 2A-C have black solid and dashed lines in the legend that are not found in the graph, instead there are orange and blue dashed lines in the graph with no legends. Figure 4C has no description of the y-axis. The growth rates in Figure 1C are very hard to follow, and there are definitely local maxima in both the blue and green profiles that are not being discussed (at 15-20 h). I cannot evaluate the conclusions drawn from the data until these issues have been resolved.

We apologise for the difficulties experienced by this reviewer.

The black lines in the old Fig. 2's legend, now Fig. 4, explain the different styles used: dashed lines are for single sugars regardless of their concentration and full lines are for mixtures regardless of their concentration. We now explicitly say this in the caption.

We have fixed the missing label in what is now Fig. 6C and have moved the statement that we are showing two biological replicates for each set of concentrations earlier in Fig. 2's caption.

We now explore the meaning of the shoulder for the fructose-palatinose mixture in Fig. 2B in the Discussion. This point is not a local maximum, unlike the case for diauxie, because the growth rate always decreases. The shoulder for the glucose-palatinose mixture was likely an artefact generated by measurement noise at low ODs because it was not present when we repeated the experiment. We now use that data for Fig. 2A & B. We also include a new Fig. S5 showing that there are sucrose-palatinose concentrations too that have a similar shoulder.

Secondly, the language in the Results and Discussion sections is confusing. Alternating between present and imperfect tense as well as active and passive form makes it hard to distinguish the authors own results from literature findings (Results are usually written in passive, imperfect tense). Examples are found on lines 24, 29, 37-38, 59, 84, 131, and 165.

We have made both sections flow more smoothly with substantial re-writing. As before, we cite all results that are not our own.

The authors also do not consider the differences and similarities in catabolic pathways for assimilation of galactose, fructose and palatinose. Even if they do not see a reason to continue that as a possible explanation for the co-consumption between fructose and palatinose a discussion of why it is disregarded would not be out of place here.

A good point, and we now state in the Introduction that all the sugars we study feed upper glycolysis.

Significance

There is some novelty to the authors findings, but I would argue it is being overstated in the present manuscript. Some examples of studies looking at catabolite repression, the main cause of diauxie, of sugars other than glucose can be found in: Simpson-Lavy and Kupiec (2019), Gancedo (1998), Prasad and Venkatesh (2008) and Borgstrom et al (2022).

We strongly disagree with this statement. The papers cited do not address, as we do, the co-consumption between two sugars neither of which is glucose. Where they study two sugars, they always study glucose.

Simpson-Lavy and Kupiec, 2019, investigate the interaction between acetate and ethanol, neither of which are sugars. Further, they are not independent carbon sources because cells convert ethanol into acetate when catabolising ethanol.

Gancedo, 1998, is a review of glucose repression and describes how glucose represses the expression of genes for other sugars. Although Gancedo mentions ``galactose repression', this repression is of genes encoding enzymes for gluconeogenesis and the TCA and glyoxylate cycles, not of other sugar regulons, our subject.

Prasad and Venkatesh, 2008, also focus on glucose and the well studied diauxie between glucose and galactose.

Borgstrom et al., 2022, focus too on glucose and growth on glucose and xylose in recombinant strains. The standard laboratory strains we study have not be artificially engineered to consume xylose. They do mention that galactose causes repression of TPS1, which encodes an enzyme that synthesises the storage carbohydrate trehalose. This repression is again not of a sugar catabolic regulon, our subject.

I would not say that the field would be significantly advanced by the publication of this manuscript, and the authors have themselves not explained the application of futhering the understanding palatinose metabolism in yeast. As mentioned above, the catabolite repression potential of galactose is already known, it just hasn't been shown for palatinose specifically before.

We again strongly disagree. Our findings are novel. The reviewer did not provide any evidence for galactose repression of other sugar regulons, which is not widely recognised as we emphasised in the Discussion. We believe that the reviewer has confused the known "galactose repression' of gluconeogenic or TCA-cycle genes with our new report of repression of other sugar regulons in the presence of the sugar catabolised by the regulon.

I would recommend a complete rewrite of the manuscript as presented, with a lower stated novelty, clearer language and comprehensible figures.

Reviewer #3

Evidence, reproducibility and clarity

Summary: Microbes grow at different growth rates in different carbon sources. When more than one carbon sources are present in the media microbes often show a preference over certain carbon sources, and 'non-preferred' carbons sources are used only when the preferred carbon source is exhausted in the media, this process called diauxic shift.

Why microbes exhibit such utilization preference over certain carbon sources, is an interesting question in microbiology and evolutionary biology, and the molecular mechanisms that enable microbes to preferentially use one carbon over another is worth investigating. It is intuitive to think that microbes will prefer to use a carbon source that confers maximum growth rate, but when tested experimentally it has been often observed that a carbon source in which microbes grow at sub optimal growth rate is actually preferentially used.

Although the reviewer states that "it has been often observed that a carbon source in which microbes grow at sub optimal growth rate is actually preferentially used“, we are unaware of this work and would appreciate references, particularly for budding yeast. The most systematic study we know, in E. coli by Aidelberg et al., 2014 --- reference 13, concludes that "the faster the growth rate, the higher the sugar on the hierarchy“, the opposite behaviour.

In this study authors demonstrate that budding yeast prefer to use galactose over palatinose, but not over sucrose or fructose where all three sugars can support faster growth rate compared to palatinose. Authors presented data where preferential galactose use and diauxic shift is observed in the growth curve when galactose and palatinose or glucose and palatinose combinations were used.

No diauxic shift was observed in the growth curve when fructose-palatinose, or sucrose-palatinose combination were used. In fructose-palatinose and sucrose-palatinose combinations growth curves agree more with co-utilization strategies. Authors used transcriptomics and genetic perturbations to decipher the molecular mechanism of such preferential carbon use, and reports preference of galactose over palatinose is achieved by preventing positive feedback of MAL regulon, which encodes the genes for palatinose catabolism. We found this observation is interesting and the molecular mechanism of such preferential carbon use is nicely described in this paper. We also find claims authors made are well supported by experiments. Although catabolite repression and diauxic transitions are known in yeast, and authors also pointed out such previous references, but preferential use of a slower carbon source, i.e. galactose over at least one other fast-growing carbon is interesting enough for publication. We would like to support the publication of this article, but we have major concerns about the data analysis and data presentation. Authors must address our concerns which are mentioned below.

Major comments:

1. This study mainly hinges on growth rate measurements, but we found growth rates are not properly represented in the figures. Growth curves are always shown in linear scale, which makes it almost impossible to compare fast and slow growth when presented in same plot. All growth curves must be shown on log scale.

We have changed all growth curves to log2 scale, following New et al., 2014, rather than Monod's choice of linear scale that we had originally.

Our conclusions are unaffected.

1. Growth rates of the Yeast strain growing individual single carbon sources (galactose, palatinose, sucrose and fructose) should be shown as a figure panel and t-test should be performed to conclude if the individual growth rates are significantly different or not.

We already showed these growth rates in their own panel in Fig. 1B. Following the reviewer's suggestion, we have now added their statistical significance to the caption.

1. Growth phase, lag phase, diauxic shift and post shift growth should be clearly shown in figure 2 and 4, each phase should be clearly marked, carbons used in each phase should be mentioned on the plot. Also, the growth curve must be plotted using log scale.

Although we have changed all growth curves to log scale, we decided against include this additional labelling for two reasons. First, we are presenting evidence that some of the growth we observe is diauxic and labelling the curves as diauxic before we discuss this evidence undermines that discussion. Second, any further labels would clutter the figures, and we believe would hinder rather than help the reader.

Instead we changed the colour scheme and the boldness of the diauxic growth curves in Fig. 2, which we hope the reviewer agrees adds the clarity they felt was missing.

1. Authors has taken in account that MAL12 gene overexpression causes long lag when cells need to switch to maltose from glucose, and shown deletion of IMA1 decreases the lag with subsequent 2% growth rate increase in palatinose. How significant is this increase?

We have confirmed the statistical significance through a t-test and added the results to the caption of Fig. 6C.

1. Authors have an interesting observation that in sucrose-palatinose and fructose palatinose combinations, most probably co utilization of the carbons is taking place. Authors should discuss this in more details. In galactose-palatinose scenario intracellular galactose-based repression of gal80 and subsequent lack of feed forward of the Mal regulon is expected to stop co-utilization of palatinose. As authors have RNA seq data, can they make predictions for other carbon pairs, where sequential utilization can occur based on their model?

We agree and have added more discussion of the fructose- and sucrose-palatinose mixtures to the Discussion and a new figure, Fig. S5.

Our RNAseq data reveals the difference in gene expression caused by an active versus an inactive GAL regulon. In Fig. S11, we show that the hexose transporters HXT2 and HXT7 are down regulated in 0.1% fructose when the GAL regulon is active, perhaps implying that cells are able to prioritise galactose over other hexoses. Nevertheless, to predict if particular carbon sources are therefore favoured, we would need to know whether cells use specific hexose transporters to drive growth on different carbon sources, which has been little investigated.

Minor comments:

1. In figure 5, authors attempted to summarize the model, which is informative, but it will be more useful for non-specific reader if a cell-based cartoon, with transports on surface and catabolic enzymes inside is also added.

We have re-designed Fig. 5, now Fig. 7, following this suggestion and agree it improves clarity.

In this schematic diagram, switch from galactose (blue line) to red line (palatinose) shows a mixed color zone, it's a bit confusing, as this represents a bi-stable state. Authors should clearly comment on possibility of biostability while discussing their proposed mechanism.

In the new figure, this part has been removed.

1. The author may want to put their work in the context of other recent observations that bacteria do not try to maximize their growth rates in many conditions. Fast growth is often associated with expansive tradeoffs, and a carbon source which confers fast growth rate may confer selective disadvantage. Thus, there are evolutionary benefits of sub-optimal growth, which could be discussed in the manuscript. In this regard a recent study (bioRxiv (2023) doi:10.1101/2023.08.22.554312.) has established the link between resource allocation strategies, growth rates and tradeoffs, which may be taken in account while discussing. Are there any known tradeoffs, when galactose is used over palatinose and which is not the case sucrose or fructose?

This is an interesting reference looking at growth on a single carbon source. We are unaware of similar tradeoffs relevant to our study. For example, we see little evidence for a constraint on the proteome because in a strain with a constitutively active GAL regulon there is no change in phenotype if we delete the genes for the three highly expressed GAL enzymes (Fig. S6B). Nevertheless and as we state in the penultimate paragraph of the Discussion, we agree that such a constraint must exist, although perhaps this constraint is ecological.

Referees cross-commenting

As other reviewers pointed out, this study has merit and addressed interesting questions, but needed to be written well in a more understandable form, we agree with this assessment. Also figures must be made much clearer, as all of the reviewers pointed out. In summary, this is an interesting study, but needs some work before publication.

Significance

General assessment: Strength and limitations:

This study addressed an interesting question regarding resource preference and growth rate optimization in microbes. This is an important question in the field. Study is well designed and claims are backed up with experimental results. One of the limitations of the study is lack of predictability. Authors explained the mechanism for one pair of carbon sources, but how applicable that will be in general is not clear.

We would argue that one of our important findings is to demonstrate that the scientific community is missing the information needed to make such predictions. We provide a counter example to the generally accepted belief that accurate predictions can be made using growth rates. Our work poses the question: what then are the physiological variables required to predict how a cell will consume a pair of carbon sources?

Advance: This study helps to advance our knowledge. Their observation regarding preferential utilization of a carbon source which supports slower growth over a carbon source which can support faster growth, and the molecular mechanism provided will help researchers to understand resource allocation strategies better.

Audience: Microbiology, systems biology, evolutionary biology, fermentation and bio process engineering research.

Reviewer expertise: Biochemistry, systems biology, metabolic strategies and tradeoffs in microbes, microbial ecology.

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Referee #3

Evidence, reproducibility and clarity

Review of the paper by Yu Huo et al.

Summary:

Microbes grow at different growth rates in different carbon sources. When more than one carbon sources are present in the media microbes often show a preference over certain carbon sources, and 'non-preferred' carbons sources are used only when the preferred carbon source is exhausted in the media, this process called diauxic shift. Why microbes exhibit such utilization preference over certain carbon sources, is an interesting question in microbiology and evolutionary biology, and the molecular mechanisms that enable microbes to preferentially use one carbon over another is worth investigating. It is intuitive to think that microbes will prefer to use a carbon source that confers maximum growth rate, but when tested experimentally it has been often observed that a carbon source in which microbes grow at sub optimal growth rate is actually preferentially used. In this study authors demonstrate that budding yeast prefer to use galactose over palatinose, but not over sucrose or fructose where all three sugars can support faster growth rate compared to palatinose. Authors presented data where preferential galactose use and diauxic shift is observed in the growth curve when galactose and palatinose or glucose and palatinose combinations were used.

No diauxic shift was observed in the growth curve when fructose-palatinose, or sucrose-palatinose combination were used. In fructose-palatinose and sucrose-palatinose combinations growth curves agree more with co-utilization strategies. Authors used transcriptomics and genetic perturbations to decipher the molecular mechanism of such preferential carbon use, and reports preference of galactose over palatinose is achieved by preventing positive feedback of MAL regulon, which encodes the genes for palatinose catabolism. We found this observation is interesting and the molecular mechanism of such preferential carbon use is nicely described in this paper. We also find claims authors made are well supported by experiments. Although catabolite repression and diauxic transitions are known in yeast, and authors also pointed out such previous references, but preferential use of a slower carbon source, i.e. galactose over at least one other fast-growing carbon is interesting enough for publication. We would like to support the publication of this article, but we have major concerns about the data analysis and data presentation. Authors must address our concerns which are mentioned below.

Major comments:

1. This study mainly hinges on growth rate measurements, but we found growth rates are not properly represented in the figures. Growth curves are always shown in linear scale, which makes it almost impossible to compare fast and slow growth when presented in same plot. All growth curves must be shown on log scale.
2. Growth rates of the Yeast strain growing individual single carbon sources (galactose, palatinose, sucrose and fructose) should be shown as a figure panel and t-test should be performed to conclude if the individual growth rates are significantly different or not.
3. Growth phase, lag phase, diauxic shift and post shift growth should be clearly shown in figure 2 and 4, each phase should be clearly marked, carbons used in each phase should be mentioned on the plot. Also, the growth curve must be plotted using log scale.
4. Authors has taken in account that MAL12 gene overexpression causes long lag when cells need to switch to maltose from glucose, and shown deletion of IMA1 decreases the lag with subsequent 2% growth rate increase in palatinose. How significant is this increase?
5. Authors have an interesting observation that in sucrose-palatinose and fructose palatinose combinations, most probably co utilization of the carbons is taking place. Authors should discuss this in more details. In galactose-palatinose scenario intracellular galactose-based repression of gal80 and subsequent lack of feed forward of the Mal regulon is expected to stop co-utilization of palatinose. As authors have RNA seq data, can they make predictions for other carbon pairs, where sequential utilization can occur based on their model?

Minor comments

1. In figure 5, authors attempted to summarize the model, which is informative, but it will be more useful for non-specific reader if a cell-based cartoon, with transports on surface and catabolic enzymes inside is also added.

In this schematic diagram, switch from galactose (blue line) to red line (palatinose) shows a mixed color zone, it's a bit confusing, as this represents a bi-stable state. Authors should clearly comment on possibility of biostability while discussing their proposed mechanism. 2. The author may want to put their work in the context of other recent observations that bacteria do not try to maximize their growth rates in many conditions. Fast growth is often associated with expansive tradeoffs, and a carbon source which confers fast growth rate may confer selective disadvantage. Thus, there are evolutionary benefits of sub-optimal growth, which could be discussed in the manuscript. In this regard a recent study (bioRxiv (2023) doi:10.1101/2023.08.22.554312.) has established the link between resource allocation strategies, growth rates and tradeoffs, which may be taken in account while discussing. Are there any known tradeoffs, when galactose is used over palatinose and which is not the case sucrose or fructose?

Referees cross-commenting

As other reviewers pointed out, this study has merit and addressed interesting questions, but needed to be written well in a more understandable form, we agree with this assessment. Also figures must be made much clearer, as all of the reviewers pointed out. In summary, this is an interesting study, but needs some work before publication.

Significance

General assessment: Strength and limitations: This study addressed an interesting question regarding resource preference and growth rate optimization in microbes. This is an important question in the field. Study is well designed and claims are backed up with experimental results. One of the limitations of the study is lack of predictability. Authors explained the mechanism for one pair of carbon sources, but how applicable that will be in general is not clear.

Advance: This study helps to advance our knowledge. Their observation regarding preferential utilization of a carbon source which supports slower growth over a carbon source which can support faster growth, and the molecular mechanism provided will help researchers to understand resource allocation strategies better.

Audience: Microbiology, systems biology, evolutionary biology, fermentation and bio process engineering research.

Reviewer expertise: Biochemistry, systems biology, metabolic strategies and tradeoffs in microbes, microbial ecology.

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Referee #2

Evidence, reproducibility and clarity

Summary: The authors have used microtiter plates to produce growth profiles on combinations of different sugars. From this data they have evaluated whether the sugars are co-consumed or if there is a preference for either sugar, seen as a diauxic shift. They found diauxie between galactose and the disaccharide palatinose, but co-consumption between palatinose and fructose. They further used strains with perturbations in their GAL regulon to attempt to explain this discrepency.

Major comments: I unfortunately found a large portion of the present manuscript unintelligable.

Firstly, figures were incorrect to the point I could not dechiffre them: Figure 2A-C have black solid and dashed lines in the legend that are not found in the graph, instead there are orange and blue dashed lines in the graph with no legends. Figure 4C has no description of the y-axis. The growth rates in Figure 1C are very hard to follow, and there are definitely local maxima in both the blue and green profiles that are not being discussed (at 15-20 h). I cannot evaluate the conclusions drawn from the data until these issues have been resolved.

Secondly, the language in the Results and Discussion sections is confusing. Alternating between present and imperfect tense as well as active and passive form makes it hard to distinguish the authors own results from literature findings (Results are usually written in passive, imperfect tense). Examples are found on lines 24, 29, 37-38, 59, 84, 131, and 165.

The authors also do not consider the differences and similarities in catabolic pathways for assimilation of galactose, fructose and palatinose. Even if they do not see a reason to continue that as a possible explanation for the co-consumption between fructose and palatinose a discussion of why it is disregarded would not be out of place here.

Significance

There is some novelty to the authors findings, but I would argue it is being overstated in the present manuscript. Some examples of studies looking at catabolite repression, the main cause of diauxie, of sugars other than glucose can be found in: Simpson-Lavy and Kupiec (2019), Gancedo (1998), Prasad and Venkatesh (2008) and Borgstrom et al (2022).

I would not say that the field would be significantly advanced by the publication of this manuscript, and the authors have themselves not explained the application of futhering the understanding palatinose metabolism in yeast. As mentioned above, the catabolite repression potential of galactose is already known, it just hasn't been shown for palatinose specifically before.

I would recommend a complete rewrite of the manuscript as presented, with a lower stated novelty, clearer language and comprehensible figures.

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Referee #1

Evidence, reproducibility and clarity

Summary: Hui et al. tackle a crucial question in biology: what factors influence the preference for carbon sources in yeasts? They reveal that the growth rate on palatinose exceeds that on glucose, despite palatinose utilization being repressed in the presence of glucose. Consequently, the favored carbon source does not necessarily align with the one supporting the fastest growth rate. The study also delves into potential regulatory mechanisms governing carbon source preference and dismisses certain existing theories, such as the general carbon flux sensing mechanism proposed by Okano et al. [25].

Major comments: None

Minor comments:

• The authors suggest that a higher growth rate implies a higher glycolytic flux (l63), a crucial assumption underpinning their interpretation of the absence of a "general carbon flux sensing mechanism" (l65). To substantiate this significant conclusion, they could calculate the extracellular uptake fluxes (based on the time-course concentrations of biomass and substrates).
• The accumulation of certain by-products is known to be toxic, reducing cellular growth rate (e.g., acetate DOI: 10.1038/srep42135, ethanol DOI: 10.1016/B978-0-12-040308-0.50006-9, etc.), while they can also enhance growth under specific conditions (e.g., acetate DOI: 10.15252/embj.2022113079). Considering this is crucial to rule out certain hypotheses, such as the possibility that a by-product produced during growth on the first carbon source would not modulate growth on the second carbon source, potentially influencing the growth rate differentially in each phase. Although the authors use mutant strains to eliminate the role of some C2 compounds (acetate and ethanol), alternative pathways could be implicated in the (co-)utilization of these by-products. This aspect should be discussed, and ideally, the authors could quantify the time-course concentrations of by-products to assess their potential role.
• The general flux-sensing regulatory mechanism proposed by Okano et al. [25], which has been dismissed by this study, has recently been questioned, as discussed in DOI: 10.15252/embj.2022113079. This aspect should be included in the discussion.

Significance

Strengths & limitations: The work is robust, and the experiments in the study have been appropriately designed and conducted. The primary question of this study has been tackled using a combination of experimental and computational methods to thoroughly assess various regulatory and functional aspects. However, there are gaps in the data that could enhance key conclusions, notably the absence of glycolytic flux measurements. Moreover, further evidence is needed to substantiate the assertion that by-products do not play a role in carbon source preference.

Advance: This study represents a significant step forward in comprehending the nutritional strategy of microbes. The authors demonstrate that the preferred carbon source may not necessarily be the one supporting the fastest growth rate. Furthermore, they dismiss certain theories that have been proposed to explain the growth strategy of microbes on mixed carbon sources.

Audience: By addressing a fundamental question in life science, this work is important in the field of biology in general and of particular interest in systems biology, biotechnology, synthetic biology, and health. Consequently, it will be of interest to a broad audience.

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Reply to the reviewers

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

This well done and interesting paper examining the connection between TXNIP and GDF15. The main thrust is that TXNIP upregulation chemotherapies, such as Oxa, results in an a down regulation of GDF15 early in tumorigenesis. Later in tumorigenesis, TXNIP upregulation is less pronounced, elevating GFP15 resulting in a blockage of tumor suppressive immune responses. Generally the work is convincing. For example, it's clear that TXNIP is up regulated by Oxa in an ROS and MondoA-dependent manner. Likewise its quite clear TXNIP loss reads to an upregulation of GDF15. However, it's also quite clear that Oxa suppresses GDF15 in a manner that appears to be completely independent of TXNIP. The writing in the paper implies strongly that there is a mechanistic connection between TXNIP and GDF15, but no experiments investigate this possibility.

We feel this is very fair and is reflective of a) perhaps an overemphasis of the TXNIP knockout observation and supportive tissue data, which suggests a relationship but not a mechanistic understanding b) an underemphasis of the data in Figure 3 that shows a decrease in GDF15 after oxaliplatin treatment in TXNIP knockout lines.

We have addressed these concerns in several ways:

1. We have carried out knockdown experiments using siRNA for ARRDC4, which we felt, given its regulation by MondoA and ROS, and homology to TXNIP, may also regulate GDF15. This was found to be the case and may explain the data in Figure 3. At the very least it shows that other factors involved in oxidative stress management may have similar impacts – a form of functional redundancy. Lines 553-559 “Finally, given our previous data (Figure S4) we looked to assess the role of ARRDC4 on GDF15 expression. In the absence of oxaliplatin, knocking down ARRDC4 in DLD1 and HCT15 cells drove an increase in GDF15. When challenged with oxaliplatin, both ARRDC4 and TXNIP expression increased and GDF15 decreased. When the ARRDC4 knockdown was challenged TXNIP increased further and GDF15 decreased further (Figure S6G-J). Given the common regulatory pathways and homology between TXNIP and ARRDC4, and their similar functional roles, we suggest these data are evidence of redundancy within this system. “

We have included some context in the discussion:

Lines 930-933: “Further support for both TXNIP and ARRDC4’s role in regulating GDF15 after the induction of ROS comes from a pan cancer meta-analysis assessing the impact of metformin (which has been reported to inhibit ROS) on gene expression. Here the top two downregulated genes were TXNIP and ARRDC4 and the top four upregulated genes were DDIT4, CHD2, ERN1 and GDF1572

We have tempered the text:

Lines 522-524 “It is important to note however that here we saw clear evidence that TXNIP was not solely responsible for the downregulation of GDF15 post oxaliplatin treatment, with decreased levels seen in knockout lines (Figure 3C-G, S5E).”

Lines 926-929 “It must be stressed that these data do not place TXNIP as the sole regulator of GDF15, for example ARRDC4 can also be seen to regulate GDF15. We envisage TXNIP as one of a number of ROS-dependent GDF15 regulators, with this redundancy potential evidence of the importance of this regulatory framework.”

We have carried out additional analysis detailed in the discussion and in Figure S12 which suggests TXNIP impacts MYC function, as reported elsewhere (detailed below). For ease, the key paper can be accessed through this link https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001778

Lines 934-956: “The main shortcoming of this paper is the lack of mechanistic understanding linking TXNIP to GDF15. There are 650 transcription factors that have been shown, or are predicted, to bind to GDF15 promoter and/or enhancer regions. By assessing our list of differentially expressed genes (Suppl. Table 1-2) for the presence of these factors we identified 6 GDF15 binding TFs that show significantly decreased expression after oxaliplatin treatment in both cell lines (ATF4, MYC, SREBF1, PHB2, HBP1, KLF9). There was only one, MYC, that was downregulated by oxaliplatin treatment (validated; Figure S12A), and with this downregulation partially being rescued in a matched TXNIP knockout line (Figure S12B). We then observed that c-myc has been shown or is predicted to bind to promoter/enhancer regions of the top five transcriptomic and proteomic differentials in TXNIP knockout lines, including TXNIP itself (apart from C16orf90). Even with c-myc’s promiscuity (binds to 10-20% of all promoters/enhancers) this may be suggestive of a specific relationship. Finally, when looking at the correlations between these 6 TFs and TXNIP and GDF15 in the TCGA COAD dataset, MYC has the greatest and most significant negative correlation to TXNIP (r=-0.4631 p=1.42e-28) and the greatest and most significant positive correlation to GDF15 (r=0.4653 p=7.32e-29). ATF4 and PHB2 are the other TFs in the list, that show the same significant trends (Figure S12C), and therefore may play a role in the TXNIP-independent oxaliplatin-dependent regulation of GDF15. Further exploration of these additional TFs is outside the scope of the current manuscript.

MYC’s role in bridging from TXNIP to GDF15 is further supported by a recent paper which shows that TXNIP is “a broad repressor of MYC genomic binding” and that “TXNIP loss mimics MYC overexpression”73. Furthermore, the inter-dependent regulatory relationship between MondoA, TXNIP, and MYC has been seen in a variety of models74, whilst the impact of NAC on MYC-dependent pathways has been seen in lymphoma75. These studies lend credence to the idea that MYC is the most likely TXNIP-regulated TF that regulates GDF15 in our systems.”

It seems equally likely that TXNIP and GDF15 represent independent parallel pathways. Even if TXNIP is a direct regulator of GDF15, it's also clear that other "factors" up or down-regulated by Oxa also contribute to the regulation of GDF15. These are not explored and even though TXNIP is highly regulated genes shown Figure 2 that are not identified or discussed that may also be contributing to GDF15 regulation.

As mentioned above, the new data suggests that at least one other factor, ARRDC4, can regulate GDF15 (changes upon oxaliplatin treatment) and that MYC is a potential mechanistic bridge between TXNIP and GDF15. Whilst assessing for the transcription factor that may link TXNIP and GDF15 we found an additional 5 TXNIP-independent factors (ATF4, PHB2, SREBF1, HBP1, KLF9) that bind to GDF15 promoter/enhancer regions and are downregulated post-oxaliplatin treatment. When looking at correlations between these factors and GDF15 in the TCGA COAD dataset, ATF4 and PHB2 correlate most closely with GDF15 (when removing MYC) and so we would cautiously suggest that these may be the most pertinent. This data is now included.

Further, the experiments treating PBMCs with conditioned media contain other cytokines/factors, in addition to GDF15, that likely also contribute the observed effects on the different immune cells understudy. The conditioned media from GDF15 knock out cells are a good experiment, but the media is not rigorously tested to see what other cytokines/factors might have also been depleted.

The TXNIP knockout media is the same as that analysed by mass spec and the protein array, however as the reviewer states there is no analysis (excluding assessing for the presence or absence of GDF15) on the double knockout supernatant or over-expression supernatant. The text has been corrected as follows:

Lines 675-679. “In light of other secreted factors being seen to be regulated by TXNIP (Figure 3A-B), we included double knockouts (TXNIP and GDF15 knockout; GTKO) as well as an overexpression system (GDF15a) to test for GDF15 specific effects. However, we do not know the impact of knocking out or overexpressing GDF15 on the broader secretome.”

Perhaps a GDF15 complementation experiment would help here.

We felt that the association between GDF15 and Treg induction is reasonably well established in the literature, and so once we saw that the supernatant from our GDF15 overexpression system (+/- CD48 blockade) complemented what has already been demonstrated, we were encouraged. However we needed more – hence the TCGA data and IHC staining.

Finally, even if completely independent, a TXNIP/GDF15 ratio does seem to have utility in determining chemo-therapeutic response.

We agree – we feel that conceptually this may be the most interesting part of the project and is an example of what can be done with these tools.

Other major points: 1. Please label the other highly regulated genes shown in Fig 2A and B. Might they also explain some of the underlying biology. This could be on the current figures or in a supplement, though the former is preferred.

Many thanks – we have done this.

Please address why the TXNIP induction is so much less in patient-derived organoids vs. cell line spheroids (Fig S2). By the western blots, TXNIP inductions in the organoids looks quite modest. Further, the text is quite cryptic and implies that the "upregulation" is similar in both organoids and spheroids.

You are absolutely correct. Many apologies, the wording has changed:

Lines 320-323 “In both models we observed the upregulation of TXNIP mRNA (Figure S2E-H) and TXNIP protein (Figure S2I-L) after oxaliplatin treatment, with spheroids showing greater responsiveness. This difference is most likely due to culturing conditions or differences in the number and location of cycling cells.”

We have two possible explanations. Firstly the media in which the organoids are cultured contains a lower glucose concentration than that used for the spheroids. As per some of our new data (Figure S3 – later in the rebuttal), the upregulation of TXNIP after oxaliplatin is glucose dependant, with lower concentrations resulting in less of a differential. Secondly, while restricted to the periphery, the Ki67 signal in DLD1 spheroids is quite pronounced indicating that, within the outer zone, many cells (probably the majority) are in the S/G1/G2 phase of the cell cycle at any given point in time (figure below this text).

This is not the case for the organoids, where the Ki67 (and pCDK1) signal is quite weak, and only sporadic in the outer layer. So we believe that there are many more rapidly cycling cells in the most drug-exposed layer of spheroids when compared to the comparable region in organoids. As the spheroid cells are likely cycling more rapidly, they would also be expected to be more adversely affected by the drug within the finite drug treatment window. Indeed, these spheroids grow large, and quite quickly. If the organoid cells are cycling more slowly and if, within the cell layer most exposed to drug, these cycling cells are less abundant, then the TXNIP response may well be subdued in organoids when compared with spheroids.

We have decided to not include the above (full) explanation and figure within the new draft, as we feel it may distract from the central message. However do let ourselves and the editor know if you disagree.

What was the rationale of performing the MS experiment on control and TXNIP KO DLD1 cells in the absence of oxaliplatin? The other experiments in Fig 3 clearly show that Oxa can repress GDF15 even in the absence of TXNIP, which implicates other pathways. ARRDC4? Or something else? This needs to be addressed.

We adopted this approach because of the order in which the assays occurred and technical issues surrounding the use of post-oxaliplatin treated supernatant. By the time we moved to the proteomics we had already identified, and validated, GDF15 as our number one candidate (initially from the protein array), in terms of response to oxaliplatin and dependence on TXNIP. This led us to the next stage of the project – to assess the environmental impacts of this factor in vitro before validation in situ. To do this, aware of the issue of contaminated recombinant GDF15, we decided early on to use cell line supernatant. We carried out some pilot studies on immune cells using supernatant from oxaliplatin treated cell lines and we had several technical issues (difficulty in determining the correct controls, immune cell death…). This changed the emphasis to using supernatant from knockout models rather than knockout and treated models. Before we began these assays in earnest we wanted to assess exactly what was enriched in TXNIP knockout supernatant and so we turned to proteomics. When this further validated GDF15, we then generated GDF15 and TXNIP/GDF15 knockouts to further elucidate GDF15’s role specifically.

With regards the other pathways, as you correctly predicted, ARRDC4 also appears to regulate GDF15 – many thanks for helping with this line of enquiry. Please see earlier in the rebuttal for more details and the data.

The data in 3J with the MondoA knockdown is not convincing. The knockdown is weak and TXNIP goes down a smidge. Agree that GDF15 goes up

We agree. We have re-run this and pooled the densitometry data – see new figure below (Panel 3J).

Minor points 1. Line 79. The "loss" of TXNIP/GDF15 axis is confusing. It's really loss of TXNIP and upregulation of GDF15, right?

Absolutely - corrected to responsiveness.

Lines 144-147: “Intriguingly, multiple models including patient-derived tumor organoids demonstrate that the loss of TXNIP and GDF15 responsiveness to oxaliplatin is associated with advanced disease or chemotherapeutic resistance, with transcriptomic or proteomic GDF15/TXNIP ratios showing potential as a prognostic biomarker.”

Please provide an explanation for the different stages in tables 1 and 2. This will likely not be clear to non-clinicians.

Many thanks. The following has been added at the bottom of the second table.

Lines 304-309: “The TNM staging system stands for Tumor, Node, Metastasis. T describes the size of the primary tumor (T1-2; 5cm). N describes the presence of tumor cells in the lymph nodes (N0; no lymph nodes. N1-3 >0). M describes whether there are any observable metastases (M0; no metastases. M1; metastases). The clinical stage system is as follows: I/II; the tumor has remained stable or grown, but hasn’t spread. III/IV; the tumor has spread, either locally (III) or systemically (IV).”

Line 231 should probably read ...cysteine (NAC), a reactive oxygen species inhibitor,

Many thanks - corrected

Line 247, should be RT-qPCR I think.

Many thanks - corrected

Lines 343-345. I don't quite understand the wording. Does this mean to say that 675 soluble proteins were not changed between the condition media from both cell populations?

Yes, exactly this. We have removed as this is superfluous and confusing.

The data in FigS1 B and C don't seem to reach the standard p value of > 0.05

Very true – we have rewritten the text to make sure the reader knows there is no significance.

Lines 269-271. “High levels of both the protein (significantly) and the transcript (not significantly) were seen to be associated with favourable prognosis (Figure 1G,H and S1B,C).”

**Referee Cross-Commenting**

cross comment regarding referees 2 and 3 above. I'm am convinced that TXNIP is at least contemporaneously upregulated with GDF15 downregulation. However, the strong implication from the writing is that TXNIP regulates GDF15 directly. I agree with the comment above that exploring mechanisms may be open-ended especially as TXNIP has been implicated in gene regulation by several different mechanism. I'd be satisfied with a more open-minded discussion of potential mechanisms by which TXNIP may repress GDF15 and the possibility of other parallel pathways that likely contribute to GDF15 repression.

Many thanks, this is a generous and understanding approach. As described above we have carried out extra analysis and have found 6 differentially regulated transcription factors which have been shown to bind GDF15 promoter or enhancer regions with 1 of these, MYC, being significantly affected in the TXNIP knockout cell lines, which in combination with supportive literature suggests a degree of TXNIP dependence. We have also identified ARRDC4 as an additional regulator of GDF15 – again please see above.

Reviewer #1 (Significance (Required)):

This is an interesting contribution but the mechanistic connection between GDF15 and TXNIP is relatively weak. That said, even as independent variables they do seem to have utility in predicting therapeutic response.

Many thanks for the comment – we concur. We have reanalysed our data looking for relevant transcription factors (those that bind GDF15 promoter / enhancer regions) finding MYC as the most likely bridge. Please see above.

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

The manuscript by Deng et al. investigates a mechanistic link between TXNIP and GDF15 expression and oxaliplatin treatment and acquired resistance. They observe an upregulation in TXNIP expression in the tumors of patients who have previously received chemotherapy. They demonstrate oxaliplatin-driven MondoA transcriptional activity is what underlies the induction of TXNIP. They further demonstrate that TXNIP is a negative regulator of GDF15 expression. Together, oxaliplatin induces MondoA activity and TXNIP expression, resulting in a downregulation of GDF15 expression and consequently decreased Treg differentiation.

Major Comments

1. The authors suggest that TXNIP induction and GDF15 downregulation are a common effect of chemotherapies; however, the mechanistic studies were limited to oxaliplatin. The authors should clarify this point through further investigation using other commonly used CRC chemotherapies (5-FU, irinotecan, etc.),or through textual changes. To be clear, I think that the oxaliplatin results could potentially stand on their own but would require additional clarification. For example, regarding the patient samples analyzed in 1D and 4F, which patients received oxaliplatin? Could the analysis of publicly available molecular data be drilled down to just the patients who received oxaliplatin?

Many thanks – this is an excellent point. Firstly, all the patients in 1D and 4F received oxaliplatin. Secondly, we have included new data looking at the impact of other chemotherapies (FOLRIRI, FU-5 and SN-38) on aspects of the study, ultimately finding that these processes (especially an anti-correlation between GDF15 and TXNIP changes upon chemo treatment) appear to be specific to oxaliplatin. These data have been added (Figure S11) and throughout the emphasis has been switched from chemotherapeutic treatment to oxaliplatin treatment.

Lines 796-799: “To check if the pre-treatment GDF15/TXNIP ratio could be used for patients treated with FOLFIRI we performed the same analyses finding no significance (S11A-D). This oxaliplatin specificity was then confirmed by western blot analysis in DLD1 and HCT15 cells treated with 5-FU or SN38 (Figure S11E-F).

Example of change of emphasis from ‘chemotherapy’ to ‘oxaliplatin’ – lines 139-142: “Here, in colorectal adenocarcinoma (CRC) we identify oxaliplatin-induced Thioredoxin Interacting Protein (TXNIP), a MondoA-dependent tumor suppressor gene, as a negative regulator of Growth/Differentiation Factor 15 (GDF15).”

The data demonstrating the induction of MondoA transcriptional activity and TXNIP expression in response to oxaliplatin treatment is quite convincing. The data regarding ROS induction of TXNIP is interesting, especially in light of other studies arguing that ROS limits MondoA activity (PMID: 25332233). Given this apparent disparity, I think that this study could really be strengthened by also investigating other potential mechanisms of oxaliplatin induction of MondoA. In particular, given many studies arguing for direct nutrient-regulation of MondoA, the authors should address the potential for oxaliplatin regulation of glucose availability and a potential glucose dependence of oxaliplatin-induced TXNIP. 2

In line with the previous point, since MondoA activity and TXNIP expression are sensitive to glucose levels, the authors should investigate oxaliplatin-regulation of TXNIP under physiological glucose levels. No need to replicate everything, just key experiments.

We feel these are excellent point and really help the piece – many thanks. We have carried out assays around these points suggested and have included the findings in the new draft – see below.

Lines 332-339: “As such, we went back to first principles and assessed the impact of different concentrations of glucose on TXNIP induction +/- oxaliplatin treatment, finding a concentration dependent effect (Figure S3A). Intriguingly, high glucose alone was able to induce increased TXNIP expression. We then assessed if oxaliplatin treatment drove an increase in glucose uptake, with this seen at concentrations >10mM (Figure S3B). Next, to investigate the impact of glucose metabolism, and consequent ROS generation, on TXNIP induction we treated cells with Antimycin A, an inhibitor of oxidative phosphorylation, finding a complete block in oxaliplatin-induced TXNIP (Figure S3C).”

The authors did a good job of linking TXNIP and GDF15 in untreated conditions; however, the data arguing for oxaliplatin regulation of GDF15 through TXNIP is less clear. For example, in 3B-H, oxaliplatin treatment reduces GDF15 approximately to the same extent in the NTC and TKO cells, potentially in line with a mechanism of downregulation that doesn't involve TXNIP.

A very salient point and completely in line with the other reviewers. We have carried out a few additional analyses mentioned previously in this letter. The most pertinent for this specific point are the experiments around ARRDC4, where we found evidence to suggest that, like TXNIP, it regulates GDF15.

Minor Comments

1. The presentation of data in Figure 5 is confusing. A-B include raw cell numbers, whereas C-F show "normalized proliferation." What does this mean? And how was the normalization done?

Apologies for this. Legend test has been corrected to “Normalised proliferation (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) on gated CD3+CD8+ or CD3+CD4+ cells is shown. n=6. (G-H) Normalised IFNg concentrations (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) in the supernatant of cells from C-F.” (lines 727-729).

**Referee Cross-Commenting**

cross-comment regarding reviewer #1

I agree with the referee that the link between TXNIP and GDF15 is weak, though as I mentioned before, this is particularly true in the context of oxaliplatin-regulation of TXNIP. I agree that given all the presented data, it is likely that oxaliplatin-regulation of TXNIP and GDF15 are independent. In my opinion, the referee brought up all valid concerns, but this is by far the biggest concern that I share.

We agree that this is the weakest aspect of the paper, however our new analyses plus supportive literature, suggests that the relationship between TXNIP and GDF15 may be mediated by MYC (please see above)

cross-comment regarding reviewer #3

The major concern that this referee addresses is whether another transcription factor supersedes the proposed MondoA/TXNIP induction in regulating GDF15 expression in later stage CRC. In my opinion, this another other concerns of the referee are all valid, but still I remain unconvinced that TXNIP induction underlies the oxaliplatin-regulation of GDF15. I think fleshing out that aspect of the study would potentially help the authors tease apart how this potential MondoA-TXNIP-GDF15 axis is dysregulated later in CRC progression.

This is a great discussion. Interestingly enough, c-myc is seen at higher levels in late stage CRC (Hu X, Fatima S, Chen M, Huang T, Chen YW, Gong R, Wong HLX, Yu R, Song L, Kwan HY, Bian Z. Dihydroartemisinin is potential therapeutics for treating late-stage CRC by targeting the elevated c-Myc level. Cell Death Dis. 2021 Nov 5;12(11):1053. Doi: 10.1038/s41419-021-04247-w. PMID: 34741022; PMCID: PMC8571272.), is seen as an important factor in resistance, and as this review argues, is driven by stress (Saeed H, Leibowitz BJ, Zhang L, Yu J. Targeting Myc-driven stress addiction in colorectal cancer. Drug Resist Updat. 2023 Jul;69:100963. Doi: 10.1016/j.drup.2023.100963. Epub 2023 Apr 20. PMID: 37119690; PMCID: PMC10330748.). So it is very plausible that the partial TXNIP-mediated regulation of myc in early / sensitive CRCs that we may be observing, and has been reported recently (TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding Lim TY, Wilde BR, Thomas ML, Murphy KE, Vahrenkamp JM, et al. (2023) TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding. PLOS Biology 21(3): e3001778. https://doi.org/10.1371/journal.pbio.3001778) is lost in late stage / resistant CRCs. If this is the case, in effect what we would have observed is the loss of a stress-associated method (TXNIP) of controlling c-myc activity. What makes our collective lives difficult is that, as reported “this expansion of Myc-dependent transcription following TXNIP loss occurs without an apparent increase in Myc’s intrinsic capacity to activate transcription and without increasing Myc levels.” (TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding Lim TY, Wilde BR, Thomas ML, Murphy KE, Vahrenkamp JM, et al. (2023) TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding. PLOS Biology 21(3): e3001778. https://doi.org/10.1371/journal.pbio.3001778)

Reviewer #2 (Significance (Required)):

Generally speaking the experiments are well controlled and the findings are significant and novel. Though the link between MondoA activity and ROS could be strengthened, and the data could be validated under more physiological settings. Further, the authors should clarify their interpretations so as to not overstate the findings.

Many thanks for the comments. We have taken onboard the need for more physiological settings and have included varying levels of glucose to reflect concentrations in different environments. We have repeated the siMondoA work in 3J strengthening the conclusions wrt its impact on TXNIP and GDF15 expression (see above).

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

In this well-written manuscript, the authors show that chemotherapy increases a MondoA-dependent oxidative stress-associated protein, TXNIP, in chemotherapy-responsive colorectal cancer cells. They show that TXNIP negatively regulates GDF-15 expression. GDF-15, in turn, correlates with the presence of T cells (Treg), and inhibits CD4 and CD8 T cell stimulation. In advanced disease and chemo-resistant cancers, upregulation of TXNIP and downregulation of GDF-15 appear to get lost. Based on a somewhat smallish data set, the authors suggest that the pre-treatment GDF-15/TXNIP ratio can predict responses to oxaliplatin treatment. This is a very interesting, novel finding. In general, the quality of the experiments and the data are high and the conclusions appear sound. Still, there are a number of aspects that should still be improved:

The observed loss of the ROS - MondoA - TXNIP - GDF15 axis in chemoresistant and/or metastatic tumors implies that another transcription factor or pathway becomes dominant upon tumor progression. As this switch would be key to better understanding the mechanism underlying the prognostic role of the TXNIP/GDF15 ratio, the authors should at least do data mining followed by ChEA or Encode (or other) analysis to identify transcription factors or pathways that become activated in late-stage/metastatic CRC cells. There is a high likelihood that a transcription factor or pathway involved in GDF-15 upregulation in cancer (e.g. p53, HIF1alpha, Nrf2, NF-kB, MITF, C/EBPß, BRAF, PI3K/AKT, MAPK p38, EGR1) supersedes the inhibitory effect of the MondoA-TXNIP axis. As it stands, the proposed loss of function of the ROS - MondoA - TXNIP - GDF-15 axis is far less convincing than almost all other aspects of the study.

An extremely fair point. We adopted a similar approach to that suggested – as mentioned above, we looked at TFs that bind to GDF15 promoter/enhancer regions and then looked at the presence of these in our transcriptomic data – specifically any evidence of change post oxaliplatin treatment. We found 6 such TFs that were decreased post-oxaliplatin treatment. We then looked for any evidence of TXNIP dependence in these TFs by comparing post-oxaliplatin treatment across NTC and TXNIP knockout lines, when we did this we found only one GDF15 promoter/enhancer binding TF was significantly changed: MYC. We then looked at the relationship between MYC,TXNIP, and GDF15 against the other 5 ‘control’ TFs in the TCGA COAD dataset, we found that MYC showed the strongest correlations, in the ‘correct’ directions. This finding was further backed up in the literature where a TXNIP knockout in a breast cancer model drove c-myc-dependent transcription, whilst c-myc has been observed to increase in later stage CRC patients, is associated with cellular stress and resistance. The collective evidence therefore suggests that MYC is the factor that is initially at least partially regulated by TXNIP, before this regulation is lost in advanced / resistant disease. Continuing on this line, it is likely that the predictive GDF15/TXNIP ratio is at least in part, a measure of c-myc responsiveness to oxaliplatin. All the while we must bear in mind TXNIP-independent oxaliplatin-dependent regulation of GDF15, most likely ARRDC4, as described earlier in this document.

Using pathway analysis software to compare our transcriptomic data from cell lines treated with/without oxaliplatin, the most likely pathways upstream of MYC/c-myc that are negatively affected by chemotherapy are BAG2, Endothelin-1, telomerase, ErbB2-ErbB3 and Wnt/B-catenin. When looking at the comparison of UTC and resistant lines’ transcripts there is only one key component of these pathways which is upregulated in both lines - ERBB3 – which has already been shown to be important in CRC metastasis and resistance (Desai O, Wang R. HER3- A key survival pathway and an emerging therapeutic target in metastatic colorectal cancer and pancreatic ductal adenocarcinoma. Oncotarget. 2023 May 10;14:439-443. doi: 10.18632/oncotarget.28421. PMID: 37163206; PMCID: PMC10171365.). It is highly speculative, but our data suggests the most likely pathway to supersede TXNIP in its (partial) regulation of MYC is the ErbB2-ErbB3 pathway.

My further criticisms are mostly more technical:

Figure 2 I-L: What was the extent of MondoA downregulation achieved by siRNA treatment? Could the effects also be seen with the small molecule mondoA inhibitor SBI-477 (or a related substance)?

This experiment has been repeated. The pooled densiometric data is also now given (please see above).

How do you explain the different GDF-15 levels between untreated non-target control cells (NTC) and TXNIP knock-down cells (TKO) in Figures 3C-F?

The only way to interpret this is that there is a TXNIP-independent pathway regulating GDF15 expression after oxaliplatin treatment, as described this is most likely to be ARRDC4 - the text has been updated to:

Lines 522-524: “It is important to note, however, that we saw clear evidence that TXNIP was not solely responsible for the downregulation of GDF15 post oxaliplatin treatment (Figure 3C-G, S6E).”

In figures 3 E-G the dots for the individual measurements should be indicated. This would be more informative than just the bar graphs.

Completed.

Figure 4C,D and Table 3: Data on the role of GDF-15 in CRC are largely valedictory of previous work (e.g. Brown et al. Clin Cancer Res 2003, 9(7):2642-2650, Wallin et al., Br J Cancer. 2011 May, 10;104(10):1619-27). Therefore, the previous studies should be cited.

Apologies for the oversight and many thanks – this is an excellent addition.

Figure 5C-F: Please indicate in the figure legend how proliferation was assessed.

Many thanks. This was noticed by another reviewer also. We have changed the text to include how the data was normalised: “(C-F) Labelled PBMCs were stimulated with anti-CD3 and anti-CD28 for 4 days in the presence of fresh supernatant from indicated cell lines, before being stained with anti-CD3 and anti-CD8 (C-D) or anti-CD4 (E-F) antibodies and measured by flow cytometry. Normalised proliferation (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) on gated CD3+CD8+ or CD3+CD4+ cells is shown. n=6. (G-H) Normalised IFNg concentrations (normalised to MFI from control: i.e. cells treated with supernatant from NTC cells) in the supernatant of cells from C-F.” (lines 724-730)

Figure S8E-G: Please indicate the analysed parameters in the graphs. In Figure S8G, the legend just indicates that "aggression of tumour" is dichotomized and plotted. This clearly requires a better definition.

Many thanks, this has been changed as per the below.

Lines 862-868: “(E-G) Receiver operating characteristic (ROC) curves showing area under the curve and p values for the use of GDF15/TXNIP ratio in predicting origin of cell line (E; primary; DLD1, HCT15, HT29, SW48 [n=4] or secondary; DiFi, LIM1215 [n=2]), sensitivity to oxaliplatin (F; parental DLD1 (plus biological repeat), HCT15 [n=3] or resistant DLD1 (plus biological repeat), HCT15 [n=3]), aggression of tumor (G; non-aggressive; The authors propose a novel ROS - MondoA - TXNIP - GDF15 - Treg axis, where MondoA activation, TXNIP up- and GDF-15 downregulation enhance tumor immunogenicity. While this axis has been analyzed in some detail, GDF-15 is not only linked to induction of regulatory T cells. There has been a report showing that GDF-15/MIC-1 expression in colorectal cancer correlates with the absence of immune cell infiltration (Brown et al. Clin Cancer Res 2003, 9(7):2642-2650). The link between GDF-15 and immune cell exclusion has also been confirmed in other conditions, including different cancers (Kempf et al. Nat Med 2011, 17(5):581-588, Roth P et al. Clin Cancer Res 2010, 16(15):3851-3859, Haake et al. Nat Commun 2023, 14(1):4253). A key mechanism is the GDF-15 mediated inhibition of LFA-1 activation on immune cells. As the authors argue that the described pathways turns cold tumors hot in response to oxaliplatin-based chemotherapy, this GDF-15 dependent immune cell exclusion mechanism might be at least as relevant than induction of Treg. Likewise, inhibition of dendritic cell maturation by GDF-15 (Zhou et al. PLoS One 2013, 8(11):e78618) could explain why GDF-15high tumors are immunologically cold. Reviewed in 3

The authors propose that the pathways discovered by them contributed to the "heating up" of the tumor microenvironment after oxaliplatin-based chemotherapy. The authors should thus look in their data sets for the presence of cytotoxic T cells and their possible correlation with TXNIP and GDF-15 levels.

This is a wonderful explanation – many thanks. We have taken the opportunity to assess the impact of GDF15 expression on a variety of T cell markers (Figure S9). In this data a negative association between GDF15 and CD8 CTLs can clearly be seen, as predicted by the reviewer.

Lines 712-717: “To assess if the GDF15-dependent presence of Tregs may be associated with a decrease in activated cytotoxic CD8 T cells, we interrogated the TCGA COAD dataset. We found that low GDF15 tumors carried significantly higher levels of CD8, CD69, IL2RA, CD28, PRF1, GZMA, GZMK, TBX21, EOMES and IRF4 (Figure S9); transcripts indicative of activated cytotoxic CD8 T cells. High GDF15 tumors were enrichment for FOXP3 and, interestingly, RORC (Figure S9). These data support the hypothesis that GDF15 induces Foxp3+ve Tregs which inhibit CD8 T cell proliferation and activation in the TME.”

The paragraph on GDF-15 receptors needs to be corrected: The purported role of a type 2 transforming growth factor (TGF)-beta receptor in GDF-15 signalling had been due to a frequent contamination of recombinant GDF-15 with TGF-beta (Olsen et al. PLoS One 2017, 12(11):e0187349). There have been a number of screenings for GDF-15 receptors that have all failed to show an interaction between GDF-15 and TGF-beta receptors. Instead, only GFRAL was found in these large-scale screenings (Emmerson et al. Nat Med 2017, 23(10):1215-1219, Hsu et al. Nature 2017, 550(7675):255-259, Mullican et al. Nat Med 2017, 23(10):1150-1157, Yang et al. Nat Med 2017, 23(10):1158-1166). The one subsequent report that shows a link between GDF-15, engagement of CD48 on T cells and induction of a regulatory phenotype (Wang et al. J Immunother Cancer 2021, 9(9)) still awaits independent validation. Considering that CD48 lacks an intracellular signaling domain that would be critical for a classical receptor function, I recommend to be more cautious regarding the role of CD48 as GDF-15 receptor. Given the mechanism outlined by Wang et al. the word interaction partner might be more apt. Moreover, an anti-GDF-15 antibody would be a good control for the experiments involving an anti-CD48 antibody in Figure 5.

Thank you so much for this concise and highly informative paragraph. We have changed the text to read:

202-204: “As a soluble protein, GDF15 exerts its effects by binding to its cognate receptor, GDNF-family receptor a-like (GFRAL)44,45,46,47 or interaction partner, CD48 receptor (SLAMF2)43, with the latter still requiring additional verification.”

We would have ideally included an anti-GDF15 antibody in the CD48 assay at the time but didn’t have the foresight. We have included the additional text to temper any conclusions.

Lines 701-711: “Furthermore, when stimulating naïve CD4 T cells in the presence of GDF15 enriched supernatant we were able to both differentiate these cells into functional Tregs and also block the generation of this functionality using an anti-CD48 antibody (Figure 5M-N). However, it must be stressed that the binding and functional impacts of GDF15’s interaction with CD48 still require further verification.”

Cell surface externalization of annexin A1 has been described as a failsafe mechanism to prevent inflammatory responses during secondary necrosis (PMID: 20007579). Thus, I am surprised that the authors list annexin A1 among the immune-stimulatory molecules exposed or released in response to chemotherapy-induced cell death (line 103). Please clarify!

We agree – it shouldn’t be there!! Removed. Many thanks.

**Referee Cross-Commenting**

Regarding the cross-comment by referee 2: In my opinion, the data shown in Figure 3C-H clearly demonstrates that TXNIP can repress GDF-15 expression. I agree that there will likely be further regulators. The GDF-15 promoter is constantly regulated by a multitude of factors (which mostly induce transcription). As downregulation of GDF-15 in response to oxaliplatin is the opposite of the frequently described induction of GDF-15 upon chemotherapy, net effects may always be "smudged" by contributions from different pathways (e.g. by cell stress due to siRNA transfection). Therefore, I believe that the data are as good as it will get. Accordingly, I would not force the authors to further amplify the observed effect.

Many thanks for your understanding – yes, GDF15 has >650 TFs that bind its promoter/enhancer regions – a number we found rather daunting. Happily your comments and those of the other reviewers inspired us to dig and we now have data that is supportive of MYC’s and ARRDC4’s involvement – detailed throughout this reply.

cross comment regarding referee #1: I share the general assessment of the referee and recognize the very detailed mechanistic analysis. To further support the moderate effects of the MondoA knockdown, a small molecule inhibitor like SBI-477 might be useful. (I had already suggested using this inhibitor to support these data.)

Many thanks for the suggestion. We opted to increase the number of siRNA repeats instead – with the data included in Figure 3J (above).

Still, my view on the potential relevance of oxaliplatin-induced, TXNIP-independent downregulation of GDF-15 differs from that of referee 1. In the clinics, platinum-based chemotherapy is one of the strongest inducers of GDF-15 (compare Breen et al. GDF-15 Neutralization Alleviates Platinum-Based Chemotherapy-Induced Emesis, Anorexia, and Weight Loss in Mice and Nonhuman Primates. Cell Metabolism 32(6), P938-950, 2020.DOI:https://doi.org/10.1016/j.cmet.2020.10.023). I was thus surprised that the authors found a pathway, which leads to an outcome that an exactly opposite effect.

This is fascinating that oxaliplatin drives this increase in GDF15 – we were unaware of this paper. Looking at figure 2(H-K), GDF15 is being produced from multiple non-diseased tissues after systemic chemotherapy – even at day 19 post-treatment – this suggests that wrt this study, systemic GDF15 could not be used as a readout of success or otherwise – which is extremely helpful! Thank you.

Thus far, the only obvious reason for reduced GDF-15 secretion upon treatment with cytotoxic drugs was a reduction in tumor cell number due to cytotoxicity.

Please do not discount this. This study was focused on the cells which survived oxaliplatin treatment – the cells which did not were discarded. Our view, given your input, would be a complex picture where in early stages systemic GDF15 goes up, due to off-target effects, but locally levels drop owing to cell death and this, and other, stress-related pathways in the remaining tumor cells.

Still, the authors managed to convince me that the described pathway (ROS - MondoA - TXNIP - GDF-15) exists. (Here, I still largely concur with referee 1.) Moreover, as we have identified some factors required for GDF-15 biosynthesis that could easily interact with TXNIP, I find the proposed mechanism plausible.

Extremely encouraging for us to hear!

Nevertheless, as a downregulation of GDF-15 in response to chemotherapy is hardly ever observed in late-stage cancers, I believe that the observed switch in pathway activation between early- and late-stage cancers might be highly relevant - in particular, as there is so much evidence for platinum-based induction of GDF-15 in late-stage cancer patients. Emphasizing the divergent clinical observations (e.g. by Breen et al.) could thus help to put the finding into perspective.

Very much agree. We did see this phenomenon in LIM1215 cells (Figure 6B) and the resistant lines we generated continually produced higher levels.

Analysing TXNIP-independent mechanisms involved in the oxaliplatin-dependent repression of GDF-15, as suggested by referee #1, will require enormous efforts and resources, and may still turn out to be fruitless. Personally, I would thus be content if the authors just mentioned possible contributions from other pathways upon cancer progression. To me, the described pathway seems to be limited to early-stage cancers, and the actual finding that GDF-15 is downregulated is an interesting observation, irrespective of further involved pathways.

Many thanks – this is extremely fair. Happily we have managed to make some tentative steps forward in highlighting the potential role of MYC, and the suggestion of redundancy wrt ARRDC4, but as you say, much more work needs to be done to fully understand these processes.

cross comment regarding referee #2: I fully agree with the referee that activation of the pathway by further chemotherapeutic drugs could be a valuable addition. As Guido Kroemer´s lab has described oxaliplatin to induce a more immunogenic cell death compared to other platinum-based chemotherapies, even a rather limited comparison between oxaliplatin and cisplatin could be very interesting.

Absolutely agree – extra data on this has been included in Figure S11, which is included earlier in this letter. We also uncovered a meta-analysis using metformin, which has been seen to inhibit ROS, where TXNIP and ARRDC4 are the top two downregulated transcripts whilst GDF15 appears in the top four upregulated. This may suggest that chemotherapeutic immunogenicity, at least through the presence or absence of GDF15, may in part be driven by ROS.

Lines 930-933: “Further support for both TXNIP and ARRDC4’s role in regulating GDF15 after the induction of ROS comes from a pan cancer meta-analysis assessing the impact of metformin (which has been reported to inhibit ROS) on gene expression. Here the top two downregulated genes were TXNIP and ARRDC4 and the top four upregulated genes were DDIT4, CHD2, ERN1 and GDF1572 “

Reviewer #3 (Significance (Required)):

In general, this is a very interesting manuscript describing a cascade of events that may contribute to successful chemotherapy (which likely requires induction of an immune response against dying tumor cells.) The observation that this pathway is only active in early/non-metastatic cancer cells is striking. Unfortunately, the authors cannot explain inactivation of this pathway in later stage/ metastatic/ highly aggressive cancers. Understanding this switch could easily be the most important finding triggered by this report. Therefore, I highly recommend to make some effort in this direction. Strikingly, the authors find that disruption of TXNIP-mediated GDF-15 downregulation is strongly associated with worse prognosis. They also suggest that this ratio could indicate whether a patient will respond to oxaliplatin-based chemotherapy.

This is again very fair – we have posited a potential mechanism for the loss of this switch elsewhere in this reply– one which involves a change in TXNIP-mediated MYC regulation and/or increased HER2-HER3 signalling – but although reasonable for a rebuttal (and publication in that context) we do not feel we have the evidence to include this within the full manuscript.

Altogether, the findings described in manuscript are very novel and may have prognostic (or, in case of the presumed loss of the MondoA - TXNIP - GDF-15 pathway) therapeutic implications. Thus, the manuscript certainly fills various gaps and should be of major interest for cell biologists working on immunogenic cell death, or colorectal cancer, or MondoA, TXNIP or GDF-15. Still, due to its translational implications, it would also be worthwhile reading for a large number of researchers in the oncology field.

We are very grateful for your kind comments.

1 Sinclair, L. V., Barthelemy, C. & Cantrell, D. A. Single Cell Glucose Uptake Assays: A Cautionary Tale. Immunometabolism 2, e200029, doi:10.20900/immunometab20200029 (2020).

2 Yu, F. X., Chai, T. F., He, H., Hagen, T. & Luo, Y. Thioredoxin-interacting protein (Txnip) gene expression: sensing oxidative phosphorylation status and glycolytic rate. J Biol Chem 285, 25822-25830, doi:10.1074/jbc.M110.108290 (2010).

3 Wischhusen, J., Melero, I. & Fridman, W. H. Growth/Differentiation Factor-15 (GDF-15): From Biomarker to Novel Targetable Immune Checkpoint. Front Immunol 11, 951, doi:10.3389/fimmu.2020.00951 (2020).

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Referee #3

Evidence, reproducibility and clarity

In this well-written manuscript, the authors show that chemotherapy increases a MondoA-dependent oxidative stress-associated protein, TXNIP, in chemotherapy-responsive colorectal cancer cells. They show that TXNIP negatively regulates GDF-15 expression. GDF-15, in turn, correlates with the presence of T cells (Treg), and inhibits CD4 and CD8 T cell stimulation. In advanced disease and chemo-resistant cancers, upregulation of TXNIP and downregulation of GDF-15 appear to get lost. Based on a somewhat smallish data set, the authors suggest that the pre-treatment GDF-15/TXNIP ratio can predict responses to oxaliplatin treatment. This is a very interesting, novel finding. In general, the quality of the experiments and the data are high and the conclusions appear sound. Still, there are a number of aspects that should still be improved:

The observed loss of the ROS - MondoA - TXNIP - GDF15 axis in chemoresistant and/or metastatic tumors implies that another transcription factor or pathway becomes dominant upon tumor progression. As this switch would be key to better understanding the mechanism underlying the prognostic role of the TXNIP/GDF15 ratio, the authors should at least do data mining followed by ChEA or Encode (or other) analysis to identify transcription factors or pathways that become activated in late-stage/metastatic CRC cells. There is a high likelihood that a transcription factor or pathway involved in GDF-15 upregulation in cancer (e.g. p53, HIF1alpha, Nrf2, NF-kB, MITF, C/EBPß, BRAF, PI3K/AKT, MAPK p38, EGR1) supersedes the inhibitory effect of the MondoA-TXNIP axis. As it stands, the proposed loss of function of the ROS - MondoA - TXNIP - GDF-15 axis is far less convincing than almost all other aspects of the study.

My further criticisms are mostly more technical:

Figure 2 I-L: What was the extent of MondoA downregulation achieved by siRNA treatment? Could the effects also be seen with the small molecule mondoA inhibitor SBI-477 (or a related substance)?

How do you explain the different GDF-15 levels between untreated non-target control cells (NTC) and TXNIP knock-down cells (TKO) in Figures 3C-F?

In figures 3 E-G the dots for the individual measurements should be indicated. This would be more informative than just the bar graphs.

Figure 4C,D and Table 3: Data on the role of GDF-15 in CRC are largely valedictory of previous work (e.g. Brown et al. Clin Cancer Res 2003, 9(7):2642-2650, Wallin et al., Br J Cancer. 2011 May, 10;104(10):1619-27). Therefore, the previous studies should be cited.

Figure 5C-F: Please indicate in the figure legend how proliferation was assessed.

Figure S8E-G: Please indicate the analysed parameters in the graphs. In Figure S8G, the legend just indicates that "aggression of tumour" is dichotomized and plotted. This clearly requires a better definition.

The authors propose a novel ROS - MondoA - TXNIP - GDF15 - Treg axis, where MondoA activation, TXNIP up- and GDF-15 downregulation enhance tumor immunogenicity. While this axis has been analyzed in some detail, GDF-15 is not only linked to induction of regulatory T cells. There has been a report showing that GDF-15/MIC-1 expression in colorectal cancer correlates with the absence of immune cell infiltration (Brown et al. Clin Cancer Res 2003, 9(7):2642-2650). The link between GDF-15 and immune cell exclusion has also been confirmed in other conditions, including different cancers (Kempf et al. Nat Med 2011, 17(5):581-588, Roth P et al. Clin Cancer Res 2010, 16(15):3851-3859, Haake et al. Nat Commun 2023, 14(1):4253). A key mechanism is the GDF-15 mediated inhibition of LFA-1 activation on immune cells. As the authors argue that the described pathways turns cold tumors hot in response to oxaliplatin-based chemotherapy, this GDF-15 dependent immune cell exclusion mechanism might be at least as relevant than induction of Treg. Likewise, inhibition of dendritic cell maturation by GDF-15 (Zhou et al. PLoS One 2013, 8(11):e78618) could explain why GDF-15high tumors are immunologically cold.

The authors propose that the pathways discovered by them contributed to the "heating up" of the tumor microenvironment after oxalilatin-based chemotherapy. The authors should thus look in their data sets for the presence of cytotoxic T cells and their possible correlation with TXNIP and GDF-15 levels.

The paragraph on GDF-15 receptors needs to be corrected: The purported role of a type 2 transforming growth factor (TGF)-beta receptor in GDF-15 signalling had been due to a frequent contamination of recombinant GDF-15 with TGF-beta (Olsen et al. PLoS One 2017, 12(11):e0187349). There have been a number of screenings for GDF-15 receptors that have all failed to show an interaction between GDF-15 and TGF-beta receptors. Instead, only GFRAL was found in these large-scale screenings (Emmerson et al. Nat Med 2017, 23(10):1215-1219, Hsu et al. Nature 2017, 550(7675):255-259, Mullican et al. Nat Med 2017, 23(10):1150-1157, Yang et al. Nat Med 2017, 23(10):1158-1166). The one subsequent report that shows a link between GDF-15, engagement of CD48 on T cells and induction of a regulatory phenotype (Wang et al. J Immunother Cancer 2021, 9(9)) still awaits independent validation. Considering that CD48 lacks an intracellular signaling domain that would be critical for a classical receptor function, I recommend to be more cautious regarding the role of CD48 as GDF-15 receptor. Given the mechanism outlined by Wang et al. the word interaction partner might be more apt. Moreover, an anti-GDF-15 antibody would be a good control for the experiments involving an anti-CD48 antibody in Figure 5.

Cell surface externalization of annexin A1 has been described as a failsafe mechanism to prevent inflammatory responses during secondary necrosis (PMID: 20007579). Thus, I am surprised that the authors list annexin A1 among the immune-stimulatory molecules exposed or released in response to chemotherapy-induced cell death (line 103). Please clarify!

Referee Cross-Commenting

Regarding the cross-comment by referee 2: In my opinion, the data shown in Figure 3C-H clearly demonstrates that TXNIP can repress GDF-15 expression. I agree that there will likely be further regulators. The GDF-15 promoter is constantly regulated by a multitude of factors (which mostly induce transcription). As downregulation of GDF-15 in response to oxaliplatin is the opposite of the frequently described induction of GDF-15 upon chemotherapy, net effects may always be "smudged" by contributions from different pathways (e.g. by cell stress due to siRNA transfection). Therefore, I believe that the data are as good as it will get. Accordingly, I would not force the authors to further amplify the observed effect.

cross comment regarding referee #1: I share the general assessment of the referee and recognize the very detailed mechanistic analysis. To further support the moderate effects of the MondoA knockdown, a small molecule inhibitor like SBI-477 might be useful. (I had already suggested using this inhibitor to support these data.) Still, my view on the potential relevance of oxaliplatin-induced, TXNIP-independent downregulation of GDF-15 differs from that of referee 1. In the clinics, platinum-based chemotherapy is one of the strongest inducers of GDF-15 (compare Breen et al. GDF-15 Neutralization Alleviates Platinum-Based Chemotherapy-Induced Emesis, Anorexia, and Weight Loss in Mice and Nonhuman Primates. Cell Metabolism 32(6), P938-950, 2020.DOI:https://doi.org/10.1016/j.cmet.2020.10.023). I was thus surprised that the authors found a pathway, which leads to an outcome that an exactly opposite effect. Thus far, the only obvious reason for reduced GDF-15 secretion upon treatment with cytotoxic drugs was a reduction in tumor cell number due to cytotoxicity. Still, the authors managed to convince me that the described pathway (ROS - MondoA - TXNIP - GDF-15) exists. (Here, I still largely concur with referee 1.) Moreover, as we have identified some factors required for GDF-15 biosynthesis that could easily interact with TXNIP, I find the proposed mechanism plausible. Nevertheless, as a downregulation of GDF-15 in response to chemotherapy is hardly ever observed in late-stage cancers, I believe that the observed switch in pathway activation between early- and late-stage cancers might be highly relevant - in particular, as there is so much evidence for platinum-based induction of GDF-15 in late-stage cancer patients. Emphasizing the divergent clinical observations (e.g. by Breen et al.) could thus help to put the finding into perspective. Analysing TXNIP-independent mechanisms involved in the oxaliplatin-dependent repression of GDF-15, as suggested by referee #1, will require enormous efforts and resources, and may still turn out to be fruitless. Personally, I would thus be content if the authors just mentioned possible contributions from other pathways upon cancer progression. To me, the described pathway seems to be limited to early-stage cancers, and the actual finding that GDF-15 is downregulated is an interesting observation, irrespective of further involved pathways.

cross comment regarding referee #2: I fully agree with the referee that activation of the pathway by further chemotherapeutic drugs could be a valuable addition. As Guido Kroemer´s lab has described oxaliplatin to induce a more immunogenic cell death compared to other platinum-based chemotherapies, even a rather limited comparison between oxaliplatin and cisplatin could be very interesting.

Significance

In general, this is a very interesting manuscript describing a cascade of events that may contribute to successful chemotherapy (which likely requires induction of an immune response against dying tumor cells.) The observation that this pathway is only active in early/non-metastatic cancer cells is striking. Unfortunately, the authors cannot explain inactivation of this pathway in later stage/ metastatic/ highly aggressive cancers. Understanding this switch could easily be the most important finding triggered by this report. Therefore, I highly recommend to make some effort in this direction. Strikingly, the authors find that disruption of TXNIP-mediated GDF-15 downregulation is strongly associated with worse prognosis. They also suggest that this ratio could indicate whether a patient will respond to oxaliplatin-based chemotherapy.

Altogether, the findings described in manuscript are very novel and may have prognostic (or, in case of the presumed loss of the MondoA - TXNIP - GDF-15 pathway) therapeutic implications. Thus, the manuscript certainly fills various gaps and should be of major interest for cell biologists working on immunogenic cell death, or colorectal cancer, or MondoA, TXNIP or GDF-15. Still, due to its translational implications, it would also be worthwhile reading for a large number of researchers in the oncology field.

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Referee #2

Evidence, reproducibility and clarity

The manuscript by Deng et al. investigates a mechanistic link between TXNIP and GDF15 expression and oxaliplatin treatment and acquired resistance. They observe an upregulation in TXNIP expression in the tumors of patients who have previously received chemotherapy. They demonstrate oxaliplatin-driven MondoA transcriptional activity is what underlies the induction of TXNIP. They further demonstrate that TXNIP is a negative regulator of GDF15 expression. Together, oxaliplatin induces MondoA activity and TXNIP expression, resulting in a downregulation of GDF15 expression and consequently decreased Treg differentiation.

Major Comments

1. The authors suggest that TXNIP induction and GDF15 downregulation are a common effect of chemotherapies; however, the mechanistic studies were limited to oxaliplatin. The authors should clarify this point through further investigation using other commonly used CRC chemotherapies (5-FU, irinotecan, etc.), or through textual changes. To be clear, I think that the oxaliplatin results could potentially stand on their own but would require additional clarification. For example, regarding the patient samples analyzed in 1D and 4F, which patients received oxaliplatin? Could the analysis of publicly available molecular data be drilled down to just the patients who received oxaliplatin?
2. The data demonstrating the induction of MondoA transcriptional activity and TXNIP expression in response to oxaliplatin treatment is quite convincing. The data regarding ROS induction of TXNIP is interesting, especially in light of other studies arguing that ROS limits MondoA activity (PMID: 25332233). Given this apparent disparity, I think that this study could really be strengthened by also investigating other potential mechanisms of oxaliplatin induction of MondoA. In particular, given many studies arguing for direct nutrient-regulation of MondoA, the authors should address the potential for oxaliplatin regulation of glucose availability and a potential glucose dependence of oxaliplatin-induced TXNIP.
3. In line with the previous point, since MondoA activity and TXNIP expression are sensitive to glucose levels, the authors should investigate oxaliplatin-regulation of TXNIP under physiological glucose levels. No need to replicate everything, just key experiments.
4. The authors did a good job of linking TXNIP and GDF15 in untreated conditions; however, the data arguing for oxaliplatin regulation of GDF15 through TXNIP is less clear. For example, in 3B-H, oxaliplatin treatment reduces GDF15 approximately to the same extent in the NTC and TKO cells, potentially in line with a mechanism of downregulation that doesn't involve TXNIP.

Minor Comments

1. The presentation of data in Figure 5 is confusing. A-B include raw cell numbers, whereas C-F show "normalized proliferation." What does this mean? And how was the normalization done?

Referee Cross-Commenting

cross-comment regarding reviewer #1

I agree with the referee that the link between TXNIP and GDF15 is weak, though as I mentioned before, this is particularly true in the context of oxaliplatin-regulation of TXNIP. I agree that given all the presented data, it is likely that oxaliplatin-regulation of TXNIP and GDF15 are independent. In my opinion, the referee brought up all valid concerns, but this is by far the biggest concern that I share.

cross-comment regarding reviewer #3

The major concern that this referee addresses is whether another transcription factor supersedes the proposed MondoA/TXNIP induction in regulating GDF15 expression in later stage CRC. In my opinion, this another other concerns of the referee are all valid, but still I remain unconvinced that TXNIP induction underlies the oxaliplatin-regulation of GDF15. I think fleshing out that aspect of the study would potentially help the authors tease apart how this potential MondoA-TXNIP-GDF15 axis is dysregulated later in CRC progression.

Significance

Generally speaking the experiments are well controlled and the findings are significant and novel. Though the link between MondoA activity and ROS could be strengthened, and the data could be validated under more physiological settings. Further, the authors should clarify their interpretations so as to not overstate the findings.

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Referee #1

Evidence, reproducibility and clarity

This is well done and interesting paper examining the connection between TXNIP and GDF15. The main thrust is that TXNIP upregulation chemotherapies, such as Oxa, results in an a down regulation of GDF15 early in tumorigenesis. Later in tumorigenesis, TXNIP upregulation is less pronounced, elevating GFP15 resulting in a blockage of tumor suppressive immune responses. Generally the work is convincing. For example, it's clear that TXNIP is up regulated by Oxa in an ROS and MondoA-dependent manner. Likewise its quite clear TXNIP loss reads to an upregulation of GDF15. However, it's also quite clear that Oxa suppresses GDF15 in a manner that appears to be completely independent of TXNIP. The writing in the paper implies strongly that there is a mechanistic connection between TXNIP and GDF15, but no experiments investigate this possibility. It seems equally likely that TXNIP and GDF15 represent independent parallel pathways. Even if TXNIP is a direct regulator of GDF15, it's also clear that other "factors" up or down-regulated by Oxa also contribute to the regulation of GDF15. These are not explored and even though TXNIP is highly regulated genes shown Figure 2 that are not identified or discussed that may also be contributing to GDF15 regulation. Further, the experiments treating PBMCs with conditioned media contain other cytokines/factors, in addition to GDF15, that likely also contribute the observed effects on the different immune cells understudy. The conditioned media from GDF15 knock out cells are a good experiment, but the media is not rigorously tested to see what other cytokines/factors might have also been depleted. Perhaps a GDF15 complementation experiment would help here. Finally, even if completely independent, a TXNIP/GDF15 ratio does seem to have utility in determining chemo-therapeutic response.

Other major points:

1. Please label the other highly regulated genes shown in Fig 2A and B. Might they also explain some of the underlying biology. This could be on the current figures or in a supplement, though the former is preferred.
2. Please address why the TXNIP induction is so much less in patient-derived organoids vs. cell line spheroids (Fig S2). By the western blots, TXNIP inductions in the organoids looks quite modest. Further, the text is quite cryptic and implies that the "upregulation" is similar in both organoids and spheroids.
3. What was the rationale of performing the MS experiment on control and TXNIP KO DLD1 cells in the absence of oxaliplatin? The other experiments in Fig 3 clearly show that Oxa can repress GDF15 even in the absence of TXNIP, which implicates other pathways. ARRDC4? Or something else? This needs to be addressed.
4. The data in 3J with the MondoA knockdown is not convincing. The knockdown is weak and TXNIP goes down a smidge. Agree that GDF15 goes up

Minor points

1. Line 79. The "loss" of TXNIP/GDF15 axis is confusing. It's really loss of TXNIP and upregulation of GDF15, right?
2. Please provide an explanation for the different stages in tables 1 and 2. This will likely not be clear to non-clinicians.
3. Line 231 should probably read ...cysteine (NAC), a reactive oxygen species inhibitor,
4. Line 247, should be RT-qPCR I think.
5. Lines 343-345. I don't quite understand the wording. Does this mean to say that 675 soluble proteins were not changed between the condition media from both cell populations?
6. The data in FigS1 B and C don't seem to reach the standard p value of > 0.05

Referee Cross-Commenting

cross comment regarding referees 2 and 3 above. I'm am convinced that TXNIP is at least contemporaneously upregulated with GDF15 dowregulation. However, the strong implication from the writing is that TXNIP regulates GDF15 directly. I agree with the comment above that exploring mechanisms may be open-ended especially as TXNIP has been implicated in gene regulation by several different mechanism. I'd be satisfied with a more open-minded discussion of potential mechanisms by which TXNIP may repress GDF15 and the possibility of other parallel pathways that likely contribute to GDF15 repression.

Significance

This is an interesting contribution but the mechanistic connection between GDF15 and TXNIP is relatively weak. That said, even as independent variables they do seem to have utility in predicting therapeutic response.

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Reply to the reviewers

We are sincerely thankful to all reviewers for their work and constructive comments that allowed us to improve the quality of the present manuscript. We are very pleased to announce that we were able to tackle all the raised concerns (except the reporter assays which is a focus of future research for our laboratory, see below), and would like to briefly mention here three major improvements:

1) We have crossed our data in frog with available human ATAC-Seq datasets. We have followed a similar approach to the one we employed in Xenopus, by “subtracting” human osteoblastic ATAC-Seq peaks with human liver, heart and lung. This cross-species validation strategy led to the identification of osteoblast-specific NFRs in human that compare very well to the Xenopus osteoblastic regulatory landscape (new Fig 6). 2) We have included ChIP-Seq data that was performed by Patricia Hanna, a former PhD student from our laboratory, in collaboration with Laurent Sachs and Nicolas Buisine (these three researchers were incorporated as new co-authors). We were planning to publish this ChIP-Seq separately but find that it contributes very well to this manuscript (modified Fig 4, new Fig 7). 3) We have included in situ hybridization analyses on frog and shark performed by David Muñoz, a former PhD student from our laboratory, in collaboration with Melanie Debiais-Thibaud and Catherine Boisvert (these three researchers were incorporated as new co-authors). This data ends nicely the manuscript by providing a biological dimension and by strengthening our evolutionary model (See new Fig 7).

We hope that our responses match the quality criteria of Review Commons and of its affiliated journals, thank you very much once again and kind regards, Sylvain Marcellini

Point-by-point description of the revisions:

Reviewer #1 (Evidence, reproducibility and clarity (Required)): Summary: The paper investigates the genetic mechanisms driving osteoblast differentiation in Xenopus tropicalis, shedding light on bone diseases and early skeletal evolution. Through ATAC-seq analysis, the study identifies osteoblast-specific regulatory regions, confirming their role as osteogenic transcriptional enhancers. A substantial number of these enhancers are conserved in humans, potentially offering insights into skeletal disorders. Additionally, the research highlights an evolutionary perspective by revealing shared regulatory elements between Xenopus tropicalis and the elephant shark, suggesting an ancient origin for mineralized tissues in vertebrates.

Major comments:

Methodology of this paper is kinda vague and the paper seems to be fragmented and not logically organized in a linear fashion.

Reply: We have improved the methodology section. We provide the accession numbers for all raw sequencing datasets generated for this study have been submitted and linked to the NCBI BioProject database (page 27). The paper has been almost completely rewritten and the figures substantially modified. There are now less figure which contain more information presented in a friendly fashion. The logic of the paper is as follows: -Identification of enhancers and promoters (Figs 1 and 2) -Characterization of their nucleotide sequence and TFBSs (Fig 3) -Validation with RNA-Seq and ChIP-Seq (Fig 4) -Global sequence conservation (Fig 5) -Cross validation with ATAC-Seq in human (Fig 6) -Evolutionary model (Fig 7).

Authors could provide evidentiary support that the control tissues are non-mineralized (and exp tissues are) by simple calcein staining. Mineralization occurs during tadpole stage, and calcification of heart and lung tissue in amphibians is not well understood. This will strengthen the attestation of these tissues as controls and provide a useful diagram for exactly what tissues were used.

Reply: We have performed Alizarin reg staining on larval skull, liver, heart and lung and show that, like in mammals, only the calvaria is mineralized (see page 6 and new Supporting Information 1).

There appears to be no mention of osteocytes or other cell types. What measures were taken to ensure that osteoblasts are the principal cell type being described? The reference for bone tissue extraction refers to a cell culture technique in which it is likely no osteocytes would prevail.

Reply: This is an important point to clarify because osteoblasts and their osteocytic progeny harbour a completely different function, physiology and gene expression profile. Our laboratory has studied frog osteocytes in details (Fritz et al, 2018), and we have added the following sentence “Of note, this extraction procedure does not harvest osteocytes that lie embedded within the bone matrix, allowing us to exclusively study osteoblasts. As controls, we also included larval liver, heart and lung following the criteria that they are nonmineralized (Supporting information 1) and unrelated to skeletal tissues”. See page 6.

Minor comments:

Data on conservation of mentioned transcription factors could be easily added (NFAT, etc.)

Reply: We have performed extensive protein alignments showing broad conservation of the osteogenic transcription factors for which we detected binding site enrichment in osteoblast-specific enhancers (see page 10 and new Supporting Information 7).

The data presentation is poor, especially figure 2 and figure 4.

Reply: Following the reviewer’s advice these figures have been eliminated and replaced by Figures 2B and 2C, which, we believe, present the same information in a much clearer and friendly fashion.

Line 115-117: "By focusing on annotated Xt transcription start sites (TSSs), we found that the ATAC-Seq NFR and mononucleosome signals form two distinct clusters," it would be helpful to briefly explain the significance of these two clusters. What does it indicate about the regulatory regions associated with TSSs?

Reply: We have clarified this point by being more explicit: “The first cluster is composed of 5,949 promoters harbouring a robust NFR located immediately upstream of the TSS and flanked by two well-positioned nucleosomes (Fig 1B, left panel), likely corresponding to expressed genes. By contrast, the second cluster contains 16,947 promoters showing weak NFR and diffuse mononucleosome signals (Fig 1B, right panel), and is probably enriched in transcriptionally repressed genes or genes expressed at low levels”. See Page 6.

Line 133-139: When discussing hierarchical clustering and the similarity of NFR landscapes between different tissues, you could provide a sentence or two to speculate on the potential biological implications. For instance, why might heart and lung tissues exhibit more similarity in NFR landscapes compared to osteoblasts and liver?

Reply: This is an interesting point to raise because there is data in the literature supporting our findings. We have modified the following sentence on page 7: “Hierarchical clustering showed that the landscape of the NFRs from heart and lung are more similar to each other than to osteoblasts or liver, which is true both for TSS and non-TSS regions (Fig 1D) and which parallels data obtained in mouse [10]”. Our novel analysis with human ATAC-Seq data also leads to the same finding (Page 13): “Available human liver, heart and lung ATAC-Seq datasets were retrieved, and hierarchical clustering confirmed a higher similarity for heart and lung, and that the osteoblast sample substantially differs from the three other tissues (Supporting information 11), similarly to the situation in frog (Fig 1D) and mouse [10]”.

Line 134: To enhance clarity, you might consider using phrases like "Figure 3A" and "Figure 3B" instead of "Compare Fig 3A and B" to directly refer to the figures in the text.

Reply: This has been corrected has we have deeply improved the figures. See “Globally, the Pearson correlation coefficient was much higher for TSS than non-TSS peaks (Fig 1D), a finding consistent with previous studies showing that, between distinct cell types, histone marks are largely invariable at promoters while they display highly context-dependent patterns at enhancers [6, 7].” on page 7.

Line 142-144: Please consider briefly explaining why you chose liver, heart, and lung tissues as controls. What specific characteristics or functions of these tissues make them suitable for this comparative analysis?

Reply: We now mention “As controls, we also included larval liver, heart and lung following the criteria that they are nonmineralized (Supporting information 1) and unrelated to skeletal tissues.” on page 6.

When discussing the potential function of osteoblastic enhancers in cartilaginous fish, you might briefly mention the role of cartilage in these organisms and how these enhancers may have evolved to regulate cartilage-related processes.

Reply: We agree with the reviewer that this is an exciting point which is of high interest for our laboratory (see for instance our review, Cervantes et al, 2017). However, as we feel that the manuscript is already quite long and has many references, we preferred not to discuss this point and to simply focus on the osteoblast/odontoblast aspect of skeletal evolution.

Ensure that the formatting of your methods section is consistent. For example, consistently use italics for software/tool names (e.g., "SAMtools") and follow a standard format for listing parameters or options used in software/tools.

Reply: We have corrected these points.

Reviewer #1 (Significance (Required)): The paper's significance lies in its elucidation of osteoblast-specific regulatory regions in Xenopus tropicalis. By characterizing these regions and connecting them to specific genes and pathways, the study advances our understanding of osteogenesis. Additionally, the identification of conserved elements across vertebrates provides insights into the deep evolutionary origins of skeletal features, offering a unique perspective on vertebrate evolution. However, one of the main limitations of the study is the lack of extensive experimental validation for the identified regulatory regions, leaving a gap in confirming their functionality.

Reply: Thank you very much again for your helpful and constructive comments. As a functional validation, at least from the chromatin perspective, we have incorporated ChIP-Seq data (Fig 4) with four key histone marks present at active promoters (H3K4me3), active enhancers (H3K4me1), and at active chromatin (H3K27Ac) and repressed chromatin (H3K27me3). This ChIP-Seq was already available in our laboratory (thereby explaining the incorporation of three new co-authors, Dr Hanna, Dr Sachs and Dr Buisine), but we were planning to incorporate it in a different manuscript. However, we feel that it is important to include it in the present paper. Another functional validation lies in the identification of 138 conserved osteogenic enhancers harbouring a NFR both in frog and human (Fig 6). We do not intend to incorporate reporter assays at this stage, as this is a future direction of research for our laboratory, together with CRISPR mutagenesis.

Reviewer #2 (Evidence, reproducibility and clarity (Required)): In this study, Hector Castillo and the coauthors conducted ATAC-seq and RNA-seq analyses across several cell types in Xenopus tropicalis (Xt) to identify regulatory elements specific to osteoblasts. They explored the evolutionary conservation of the osteoblast regulatory elements across species. Their research encompassed the identification of osteoblast-specific regulatory elements through cross-tissue analysis, offering comprehensive insights into tissue-specific regulatory elements. These insights included cell-type-specific chromatin accessibility, biological functions predicted by gene ontology analysis, and potential transcriptional regulators associated with these regions. The cross-species analysis unveiled partial conservation of osteoblast-specific regulatory regions between the Xt and the human genome, with the shared genomic regions being linked to osteoblast-related genes. Additionally, the enriched transcription factors were identified in these regions. The study further explored comparative analyses involving multiple species, providing evolutionary insights into the gene regulatory mechanisms underlying osteoblast identity and pathology.

Major comment All the cross-species analyses in this study were primarily based on sequence conservation. However, since human osteoblast ATAC-seq data, as well as ChIP-seq and Hi-C data, are publicly available (PMID: 35906483), conducting a direct comparative analysis between Xenopus tropicalis (Xt) osteoblast ATAC-seq and human osteoblast ATAC-seq could provide more concrete evidence regarding the conservation of chromatin-accessible regions between these two species. This additional analysis has the potential to significantly strengthen the conclusions drawn in the study.

Reply: We are thankful to the reviewer for this insightful comment that dramatically improved the scope of our work. We have indeed incorporated available ATAC-Seq experiments performed on human osteoblasts (SRR12933513 and SRR12933514), liver (SRR21927033 and SRR21927032), heart (SRR21927531 and SRR21927534) and lung (SRR21927095 and SRR21927098). This is explained on pages 13-14 (results), pages 19-20 (discussion) and pages 22-24 (methods). Hence, we have uncovered 138 conserved enhancers that display an osteoblast-specific NFR both in frog and human (see new Fig 6). As the reviewer states, we believe that our conclusions have been significantly strengthened, allowing us to reformulate the manuscript title which now vehiculates a more functional message. Also, thanks to this comment, we were able to propose a more attractive title for our work: “Cross-validation of conserved osteoblast-specific enhancers illuminates bone diseases and early skeletal evolution”.

Minor comment 1 The authors made use of "annotated human enhancers" in their study; however, the specific definition or source of this annotation was not provided in the manuscript. It is crucial that the authors clarify the criteria or source used for annotating human enhancers to ensure transparency and allow readers to better understand the basis of their analyses and conclusions.

Reply: The reviewer is correct. These “annotated human enhancers” have now completely been eliminated for the study and replaced by the analysis shown in Fig 6 (and see our reply to the previous comment).

Minor comment 2 In relation to the association studies conducted between Xenopus tropicalis (Xt) osteoblast enhancers and genes related to human bone diseases, it's important for the authors to express their statements with caution. While the putative target genes may be potentially regulated by shared regulatory elements between Xt and humans, there exists no direct evidence demonstrating that these regulatory regions are the causative factors behind these diseases. It's worth noting that there are several other open chromatin regions in proximity to these putative target genes. As a result, the shared genomic regions may or may not have a direct relationship with human diseases. To establish a substantial linkage, more in-depth analyses would be required to provide evidence of a pathological connection.

Reply: This is an important point, on page 14 we now state “While the osteoblast-specific regulatory regions reported here might not be directly involved in the aetiology of the aforementioned diseases, their identification considerably improves our understating of the transcriptional control of these genes”.

Minor comment 3 In lines 394 to 397, the authors assert that the enrichment of TWIST1/2 transcription factor binding sites (TFBS) at Xenopus tropicalis (Xt) osteogenic enhancers is a novel finding. However, this claim lacks clarity regarding the novelty of this discovery, given that they reference previous literature (reference 42) that has already demonstrated the involvement of TWIST1/2 in osteoblast differentiation. The authors should provide a more precise explanation of how their specific findings related to TWIST1/2 TFBS enrichment contribute to existing knowledge or differ from previous studies to clarify the novelty of their results.

Reply: We now provide a clearer explanation by mentioning “In this respect, the reported enrichment in TWIST1/2 TFBS (Fig 3 and Supporting information 5) represents the first evidence that TWIST proteins might control the timing of osteoblastic differentiation through binding to hundreds of osteogenic enhancers, a possibility that could be confirmed by ChIP-Seq” on page 19.

Minor comment 4 Depositing the NGS data, including ATAC-seq and RNA-seq datasets, in a public database would be a valuable contribution to the research community.

Reply: Yes, this data has now been made available, see pages 26-27: “Data Availability. The raw sequencing datasets generated for this study have been submitted and linked to the NCBI BioProject database with the following accession numbers: PRJNA1011469 (ATAC-seq), PRJNA1021677 (RNA-seq), and PRJNA1056467 (ChIP-seq)”.

Reviewer #2 (Significance (Required)): The comparative analysis of ATAC-seq among different cell types in Xenopus tropicalis (Xt) provides a broad perspective on cell-type-specific chromatin accessible regions, which is a notable strength of the study. It's worth highlighting that, as far as known, this study represents the first report of ATAC-seq in Xt osteoblasts. However, it's important to acknowledge that the overall message of the study is consistent with previous findings in mammals. For example, the observation that non-transcription start site (TSS) regions were more cell-type-specific, correlating with cell-type distinct gene expressions, aligns with findings in mammalian systems. Additionally, many of the osteoblast regulators predicted from the data are already known osteogenic factors in mammals. The cross-species analysis provides valuable insights into the evolutionary aspects of putative enhancers in osteoblasts. The study identifies conserved gene regulatory regions and putative transcription factors associated with these genomic regions, shedding light on their potential roles in gene regulation. Moreover, the identification of conserved regions possibly linked to human skeletal diseases is a noteworthy aspect of the research, showcasing its strengths. However, it's essential to acknowledge a potential limitation related to this aspect of the study: the analyses conducted so far have been descriptive, primarily focusing on DNA sequence conservation. Given that several osteoblast ATAC-seq datasets from different species are publicly available, a more direct comparison between the Xt dataset and these other datasets could provide a deeper understanding of enhancer conservation and evolution. This study offers valuable resources for researchers in the field of skeletal biology and evolution. The comprehensive analysis of osteoblast-specific regulatory elements in Xenopus tropicalis, along with insights into their conservation and potential roles in human skeletal diseases, provides a foundation for further investigations in this area. Additionally, the evolutionary insights offered by the cross-species analysis contribute to the growing body of knowledge in evo-devo studies, shedding light on the evolution of gene regulatory mechanisms related to osteoblast identity. These resources and insights can serve as a valuable reference and guide for future research endeavors in both bone biology and evolutionary developmental biology. This reviewer specializes in the study of gene regulatory mechanisms in skeletal development and metabolism, primarily utilizing mouse and human tissues.

Reply: Thank you very much again for your helpful and constructive comments.

Reviewer #3 (Evidence, reproducibility and clarity (Required)): Summary Starting with ATAC-seq on the Xenopus tropicalis (Xt) genome, the authors tried to identify regulatory regions, which were evolutionally conserved and critical for osteoblasts, through computational approaches. They obtained profiles of the nucleosome-free regions (NFRs), i.e., open chromatin regions, in bone, liver, heart, and lung of Xt. The NFRs contain TSS-associated regions (TSS regions) and non-TSS regions. They then identified tissue-specific NFRs. Tissue-specific NFRs were predominantly located in introns and intergenic regions, and the trend was more highlighted in non-TSS regions. Regarding osteoblast-specific NFRs, non-TSS regions were associated with genes related to osteoblasts. Osteoblast-specific TSS- and non-TSS regions were enriched with motifs of osteoblast-related transcription factors (TFs), including Smad, AP-1, TEAD, Runx2, Nfic, Twist, and Nfat. By integrating ATAC-seq data with RNA-seq data, they found that osteoblast-specific NFRs were associated with transcriptionally active genes. When inter-species conservation of the Xt tissue-specific NFRs was analyzed, osteoblast-specific ones were well conserved in human, chick, and Callorhinchus milii (elephant shark). The authors further identified human homologous regions to Xt osteoblast-specific NFRs, which were enriched with binding motifs of osteoblast-related TFs, proposing putative osteogenic enhancers associated with skeletal diseases. Lastly, they identified a set of Xt osteoblast-specific NFRs that were conserved with the human, chick, and elephant shark genomes. The putative target genes of NFRs are enriched with osteogenesis-related TFs. Based on these data, they propose that evolutionary origins of osteoblast and odontoblasts are common, given that elephant shark is a cartilaginous fish, where bone is absent but odontoblast is present.

Major comments A major critical concern on this work is that their findings and claim fully rely on bioinformatic analyses. Bioinformatic prediction should be verified by wet-type experiments. Otherwise, it is quite difficult to draw definitive conclusions. In particular, it remains to be verified if the "putative enhancers" that they computationally identified have actual enhancer activities in in-vivo contexts. ATAC-seq alone identifies open chromatin regions on the genome and is not enough to define the location of enhancers and their activities. The authors need to perform ChIP-seq for enhancer marks and reporter assays for enhancer activities, in order to verify their prediction on at least several key regions they propose.

Reply: We have taken very seriously the reviewer´s comments and have incorporated three major experimental validations that go beyond bioinformatic analyses: -ChIP-Seq data on 4 key histone marks, previously performed in our laboratory, performed on Xenopus primary osteoblasts (see Fig 4). -Available human ATAC-Seq data for osteoblasts and control tissues (see new Fig 6). -In situ hybridization on elephant shark dental plates (see new Fig 7). We therefore have deeply modified the whole manuscript and now propose a more attractive title for our work: “Cross-validation of conserved osteoblast-specific enhancers illuminates bone diseases and early skeletal evolution”. We were not able to incorporate Reporter assays because (i) these experiments are lengthy, (ii) the current manuscript is already quite extensive and (iii) this is a major future research focus of our laboratory.

Minor comments Line 146: Fig S2 is unlikely to be provided.

Reply: We would like to keep this data available for readers, former Fig S2 is now “Supporting Information 3”.

Lines 158 to 163 and Fig. 4: GO analysis was performed only on non-TSS peaks. What about TSS peaks?

Reply: We now state on page 8 “Due to the low number of regions, no significant results were obtained with lung-specific non-TSS ATAC-Seq peaks, or with any category of TSS”.

Line 269: In the text, the authors describe that 48 osteoblast-specific TSS peaks are aligned to corresponding regions on the human genome. However, Fig. S7 shows 46 peaks are aligned. Please double-check.

Reply: This discrepancy has now been corrected.

Lines 289 to 296, Figs. 8, and S11: Although TRPS1 appears in Fig. S11, the authors did not mention it in the main text and Fig. 8. Why is the gene specifically excluded from the explanation?

Reply: This omission has now been corrected and now trps1 appears in Fig 6C, in Supporting Information 12, and is mentioned in the abstract and at pages 13-14 “Some cross-validated osteoblastic promoters and enhancers are located at loci of genes involved in skeletal diseases (See Supporting information 12 and Ref. [49]), such as osteoarthritis (adam12), osteoporosis (etv1), geroderma osteodysplasticum (gorab), keipert syndrome (gpc4), buschke-Ollendorff syndrome (lemd3), cleidocranial dysplasia (runx2) and trichorhinophalangeal syndrome type I (trps1).”.

Reviewer #3 (Significance (Required)): - This work is potentially interesting, not just leading to identification of regulatory regions critical for osteoblast biology, but also providing evolutionary insight into bone development. However, as mentioned, lack of validation of bioinformatic prediction is a major weakness of this work. This work's concept would engage the interest in the field of bone development and skeletal transcriptional programs. However, the reviewer is not sure how much this work engages general interest. - Expertise of the reviewer is mammalian skeletal development, particularly focusing on gene regulatory networks and epigenome during the process.

Reply: Thank you very much again for your helpful and constructive comments.

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Referee #3

Evidence, reproducibility and clarity

Summary

Starting with ATAC-seq on the Xenopus tropicalis (Xt) genome, the authors tried to identify regulatory regions, which were evolutionally conserved and critical for osteoblasts, through computational approaches. They obtained profiles of the nucleosome-free regions (NFRs), i.e., open chromatin regions, in bone, liver, heart, and lung of Xt. The NFRs contain TSS-associated regions (TSS regions) and non-TSS regions. They then identified tissue-specific NFRs. Tissue-specific NFRs were predominantly located in introns and intergenic regions, and the trend was more highlighted in non-TSS regions. Regarding osteoblast-specific NFRs, non-TSS regions were associated with genes related to osteoblasts. Osteoblast-specific TSS- and non-TSS regions were enriched with motifs of osteoblast-related transcription factors (TFs), including Smad, AP-1, TEAD, Runx2, Nfic, Twist, and Nfat. By integrating ATAC-seq data with RNA-seq data, they found that osteoblast-specific NFRs were associated with transcriptionally active genes. When inter-species conservation of the Xt tissue-specific NFRs was analyzed, osteoblast-specific ones were well conserved in human, chick, and Callorhinchus milii (elephant shark). The authors further identified human homologous regions to Xt osteoblast-specific NFRs, which were enriched with binding motifs of osteoblast-related TFs, proposing putative osteogenic enhancers associated with skeletal diseases. Lastly, they identified a set of Xt osteoblast-specific NFRs that were conserved with the human, chick, and elephant shark genomes. The putative target genes of NFRs are enriched with osteogenesis-related TFs. Based on these data, they propose that evolutionary origins of osteoblast and odontoblasts are common, given that elephant shark is a cartilaginous fish, where bone is absent but odontoblast is present.

Major comments

A major critical concern on this work is that their findings and claim fully rely on bioinformatic analyses. Bioinformatic prediction should be verified by wet-type experiments. Otherwise, it is quite difficult to draw definitive conclusions. In particular, it remains to be verified if the "putative enhancers" that they computationally identified have actual enhancer activities in in-vivo contexts. ATAC-seq alone identifies open chromatin regions on the genome and is not enough to define the location of enhancers and their activities. The authors need to perform ChIP-seq for enhancer marks and reporter assays for enhancer activities, in order to verify their prediction on at least several key regions they propose.

Minor comments

Line 146: Fig S2 is unlikely to be provided. Lines 158 to 163 and Fig. 4: GO analysis was performed only on non-TSS peaks. What about TSS peaks? Line 269: In the text, the authors describe that 48 osteoblast-specific TSS peaks are aligned to corresponding regions on the human genome. However, Fig. S7 shows 46 peaks are aligned. Please double-check. Lines 289 to 296, Figs. 8, and S11: Although TRPS1 appears in Fig. S11, the authors did not mention it in the main text and Fig. 8. Why is the gene specifically excluded from the explanation?

Significance

• This work is potentially interesting, not just leading to identification of regulatory regions critical for osteoblast biology, but also providing evolutionary insight into bone development. However, as mentioned, lack of validation of bioinformatic prediction is a major weakness of this work. This work's concept would engage the interest in the field of bone development and skeletal transcriptional programs. However, the reviewer is not sure how much this work engages general interest.
• Expertise of the reviewer is mammalian skeletal development, particularly focusing on gene regulatory networks and epigenome during the process.

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Referee #2

Evidence, reproducibility and clarity

In this study, Hector Castillo and the coauthors conducted ATAC-seq and RNA-seq analyses across several cell types in Xenopus tropicalis (Xt) to identify regulatory elements specific to osteoblasts. They explored the evolutionary conservation of the osteoblast regulatory elements across species. Their research encompassed the identification of osteoblast-specific regulatory elements through cross-tissue analysis, offering comprehensive insights into tissue-specific regulatory elements. These insights included cell-type-specific chromatin accessibility, biological functions predicted by gene ontology analysis, and potential transcriptional regulators associated with these regions.

The cross-species analysis unveiled partial conservation of osteoblast-specific regulatory regions between the Xt and the human genome, with the shared genomic regions being linked to osteoblast-related genes. Additionally, the enriched transcription factors were identified in these regions. The study further explored comparative analyses involving multiple species, providing evolutionary insights into the gene regulatory mechanisms underlying osteoblast identity and pathology.

Major comment

All the cross-species analyses in this study were primarily based on sequence conservation. However, since human osteoblast ATAC-seq data, as well as ChIP-seq and Hi-C data, are publicly available (PMID: 35906483), conducting a direct comparative analysis between Xenopus tropicalis (Xt) osteoblast ATAC-seq and human osteoblast ATAC-seq could provide more concrete evidence regarding the conservation of chromatin-accessible regions between these two species. This additional analysis has the potential to significantly strengthen the conclusions drawn in the study.

Minor comment 1

The authors made use of "annotated human enhancers" in their study; however, the specific definition or source of this annotation was not provided in the manuscript. It is crucial that the authors clarify the criteria or source used for annotating human enhancers to ensure transparency and allow readers to better understand the basis of their analyses and conclusions.

Minor comment 2

In relation to the association studies conducted between Xenopus tropicalis (Xt) osteoblast enhancers and genes related to human bone diseases, it's important for the authors to express their statements with caution. While the putative target genes may be potentially regulated by shared regulatory elements between Xt and humans, there exists no direct evidence demonstrating that these regulatory regions are the causative factors behind these diseases. It's worth noting that there are several other open chromatin regions in proximity to these putative target genes. As a result, the shared genomic regions may or may not have a direct relationship with human diseases. To establish a substantial linkage, more in-depth analyses would be required to provide evidence of a pathological connection.

Minor comment 3

In lines 394 to 397, the authors assert that the enrichment of TWIST1/2 transcription factor binding sites (TFBS) at Xenopus tropicalis (Xt) osteogenic enhancers is a novel finding. However, this claim lacks clarity regarding the novelty of this discovery, given that they reference previous literature (reference 42) that has already demonstrated the involvement of TWIST1/2 in osteoblast differentiation. The authors should provide a more precise explanation of how their specific findings related to TWIST1/2 TFBS enrichment contribute to existing knowledge or differ from previous studies to clarify the novelty of their results.

Minor comment 4

Depositing the NGS data, including ATAC-seq and RNA-seq datasets, in a public database would be a valuable contribution to the research community.

Significance

The comparative analysis of ATAC-seq among different cell types in Xenopus tropicalis (Xt) provides a broad perspective on cell-type-specific chromatin accessible regions, which is a notable strength of the study. It's worth highlighting that, as far as known, this study represents the first report of ATAC-seq in Xt osteoblasts. However, it's important to acknowledge that the overall message of the study is consistent with previous findings in mammals. For example, the observation that non-transcription start site (TSS) regions were more cell-type-specific, correlating with cell-type distinct gene expressions, aligns with findings in mammalian systems. Additionally, many of the osteoblast regulators predicted from the data are already known osteogenic factors in mammals.

The cross-species analysis provides valuable insights into the evolutionary aspects of putative enhancers in osteoblasts. The study identifies conserved gene regulatory regions and putative transcription factors associated with these genomic regions, shedding light on their potential roles in gene regulation. Moreover, the identification of conserved regions possibly linked to human skeletal diseases is a noteworthy aspect of the research, showcasing its strengths. However, it's essential to acknowledge a potential limitation related to this aspect of the study: the analyses conducted so far have been descriptive, primarily focusing on DNA sequence conservation. Given that several osteoblast ATAC-seq datasets from different species are publicly available, a more direct comparison between the Xt dataset and these other datasets could provide a deeper understanding of enhancer conservation and evolution.

This study offers valuable resources for researchers in the field of skeletal biology and evolution. The comprehensive analysis of osteoblast-specific regulatory elements in Xenopus tropicalis, along with insights into their conservation and potential roles in human skeletal diseases, provides a foundation for further investigations in this area. Additionally, the evolutionary insights offered by the cross-species analysis contribute to the growing body of knowledge in evo-devo studies, shedding light on the evolution of gene regulatory mechanisms related to osteoblast identity. These resources and insights can serve as a valuable reference and guide for future research endeavors in both bone biology and evolutionary developmental biology.

This reviewer specializes in the study of gene regulatory mechanisms in skeletal development and metabolism, primarily utilizing mouse and human tissues.

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

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Referee #1

Evidence, reproducibility and clarity

Summary:

The paper investigates the genetic mechanisms driving osteoblast differentiation in Xenopus tropicalis, shedding light on bone diseases and early skeletal evolution. Through ATAC-seq analysis, the study identifies osteoblast-specific regulatory regions, confirming their role as osteogenic transcriptional enhancers. A substantial number of these enhancers are conserved in humans, potentially offering insights into skeletal disorders. Additionally, the research highlights an evolutionary perspective by revealing shared regulatory elements between Xenopus tropicalis and the elephant shark, suggesting an ancient origin for mineralized tissues in vertebrates.

Major comments:

Methodology of this paper is kinda vague and the paper seems to be fragmented and not logically organized in a linear fashion. Authors could provide evidentiary support that the control tissues are non-mineralized (and exp tissues are) by simple calcein staining. Mineralization occurs during tadpole stage, and calcification of heart and lung tissue in amphibians is not well understood. This will strengthen the attestation of these tissues as controls and provide a useful diagram for exactly what tissues were used. There appears to be no mention of osteocytes or other cell types. What measures were taken to ensure that osteoblasts are the principal cell type being described? The reference for bone tissue extraction refers to a cell culture technique in which it is likely no osteocytes would prevail.

Minor comments:

Data on conservation of mentioned transcription factors could be easily added (NFAT, etc.) The data presentation is poor, especially figure 2 and figure 4. Line 115-117: "By focusing on annotated Xt transcription start sites (TSSs), we found that the ATAC-Seq NFR and mononucleosome signals form two distinct clusters," it would be helpful to briefly explain the significance of these two clusters. What does it indicate about the regulatory regions associated with TSSs? Line 133-139: When discussing hierarchical clustering and the similarity of NFR landscapes between different tissues, you could provide a sentence or two to speculate on the potential biological implications. For instance, why might heart and lung tissues exhibit more similarity in NFR landscapes compared to osteoblasts and liver? Line 134: To enhance clarity, you might consider using phrases like "Figure 3A" and "Figure 3B" instead of "Compare Fig 3A and B" to directly refer to the figures in the text. Line 142-144 :Please consider briefly explaining why you chose liver, heart, and lung tissues as controls. What specific characteristics or functions of these tissues make them suitable for this comparative analysis? When discussing the potential function of osteoblastic enhancers in cartilaginous fish, you might briefly mention the role of cartilage in these organisms and how these enhancers may have evolved to regulate cartilage-related processes. Ensure that the formatting of your methods section is consistent. For example, consistently use italics for software/tool names (e.g., "SAMtools") and follow a standard format for listing parameters or options used in software/tools.

Significance

The paper's significance lies in its elucidation of osteoblast-specific regulatory regions in Xenopus tropicalis. By characterizing these regions and connecting them to specific genes and pathways, the study advances our understanding of osteogenesis. Additionally, the identification of conserved elements across vertebrates provides insights into the deep evolutionary origins of skeletal features, offering a unique perspective on vertebrate evolution. However, one of the main limitations of the study is the lack of extensive experimental validation for the identified regulatory regions, leaving a gap in confirming their functionality.

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Reply to the reviewers

1. General Statements [optional]

We would like to extend our warmest thanks to the reviewers for their constructive comments and strong support for our study.

2. Point-by-point description of the revisions

Reviewer #1:

Table

1. It would be nice to have a table of isoform, dose, promoter, enhancer and other conditions tested and the brief summary of phenotype as Table.

We thank the reviewer for this valuable suggestion and have now included a summary Table (Table 1) cited in the last result section.

Discussion

1. This experiment was done on knockout condition but in real patient different form of mutant protein will exist in retinal tissue. Authors indicated that co‐expression of short and long form of FAM161A worked better to rescue function. How would authors cope with interfering endogenous mutant protein in real patients?

We thank the reviewer for raising this interesting point. Most mutations described so far are nonsense or frameshift mutations common to both long and short isoforms which, consequently, are not present at the protein level (Beryozkin et al 2020, doi.org/10.1038/s41598-020-72028-0, Matsevich et al 2022, doi.org/10.1016/j.xops.2022.100229). Thus, we don’t expect to have an imbalance between the remaining functional alleles and the therapeutic ones. However, we cannot exclude the discovery of missense mutations and the effect of such allele would have to be molecularly evaluated to determine if gene replacement is limited for this specific condition. This question could be assessed in cellular models by co-expression of both mutated and WT-tagged proteins or in organoid models.

1. Related to the first question, the expression of these retinal structural proteins will be different in mice and human. How would authors optimize the vector for human patient gene therapy?

Aware that the 60% homology between the human and mouse protein could cause important limitations for the evaluation of the vector in the mouse model, we are continuing the validation of our vectors in human retina organoïds. We plan to test both the reliable localization of the human isoforms in WT organoid and the rescue of structural photoreceptor defects of FAM161A-deficient human organoids. In parallel, vector-derived expression will also be validated in non-human primates.

Reviewer #2:

Scotopic and photopic ERG were performed to study retinal function. However, mouse behavior tests such as optomotor response should be employed to confirm vision restoration.

In our hand, we didn’t notice a significant modification of the optomotor response between 4 and 16 weeks (for figure on visual acuity changes with age in Fam161atmb/tmb mice (n=6-9), see uploaded word document), and consequently of the estimated visual acuity, in Fam161atmb/tmb mice at 3.5 months corresponding to the endpoint of our study (see figure below). In a separate study to this work, we are thus conducting a follow-up long term gene therapy study to be able to complete the functional analysis of the gene therapy rescue with the optomotor response at age with significant decreased visual acuity in untreated mice compared to WT. We will have to wait at least 6 months to expect to see a difference between groups.

The immunostaining in Figure 3 has some noise. Filtering the blocking solution before use could improve the quality of the staining.

We thank the reviewer for this suggestion. The blocking solution was already filtered and the limited success of the mouse FAM161A staining is due to the imperfect recognition of anti-human FAM161A antibodies to the mouse protein.

In Figure 5f, the data of wildtype mice should be included for comparison.

As noted by reviewer 3, in Fig5 F, the plain gray horizontal line surrounded by the 2 dotted ones are referring to the mean +/- SEM of the WT value respectively. We added “WT” on the right of the graph to highlight the plain line.

The cited paper, such as 'Garafalo AV, Cideciyan AV, Heon E, Sheplock R, Pearson A, WeiYang Yu C, Sumaroka A, Aguirre GD, and Jacobson SG. Progress in treating inherited retinal diseases: Early subretinal gene therapy clinical trials and candidates for future initiatives. Prog Retin Eye Res. 2020;77(100827),' should be an original research paper, not a review article.

As noted by reviewer 3, we think appropriate to cite this review which is a complete reference to the different gene therapy approaches developed for inherited retinal diseases.

Major:

Fig 1A‐B. Do hTERT‐RPE1 cells endogenously express FAM161A? This set of images lacks a negative control (i.e., no transfected RPE1 cells). Western blot of FAM161A is recommended, similar to Fig 1C.

We previously showed that hTERT-RPE1 cells express FAM161A in the basal body of the centriole (Di Gioia 2015), but we recognized that it is not apparent in Figure 1A and B, probably due to a limitation of the antibody reactivity which labeled only overexpressed proteins. We thus performed additional experiments using the human ARPE19 cell line to demonstrate endogenous FAM161A expression in untransfected cells and to perform a Western blot from human transfected cells. We observed that in untransfected cells FAM161A labeling is weak and is only revealed in the centriole labeled by centrin after a long exposure time (Figure 1A). When FAM161A HS or HL is overexpressed the FAM161A labeling is present in the cell body, very strong, and is observed with short exposure time (Figure 1A). We also extracted protein from untransfected and HS- or HL-transfected ARPE-19 cells to identify the FAM161A protein by Western blot (Figure 1B). Thus, we added the negative control and a western blot from human cells to answer reviewer comments.

Fig 1C. The authors noted in the discussion that HS isoform is more abundant than HL isoform from human retinal extract. Although this is from 661W, a mouse photoreceptor cell line, it seems this is aligned with the notion. To echo with the last comment, I am curious to see if under the same transfection, the HS isoform is preferentially expressed in hTERT‐RPE1 cells.

We do not think that transfection experiment is sufficient to prove that HS is preferentially express than HL. Even if we transfect the same amount of DNA, we would need an internal control for transfection to allow relative quantification of the protein expression after transfection. However, we performed an additional experiment in human RPE cells using the ARPE-19 cell line which is more efficiently transfected than hTERT-RPE1 in our hands. As shown in Figure 1B, we observed again more abundant expression of HS in these human transfected cells. However, we cannot exclude difference in transfection efficiency between HL and HS conditions that could explain the difference in the final amount of FAM161A protein.

Fig 3 and Fig 5: low mag WT images of FAM161A are the same. But higher mag images (presumably selected from ROIs in low mag) are not the same. Please make sure of no duplication images.

We are facing technical limits with the labeling of the mouse Fam161A. The antibodies available have limited affinity for the mouse Fam161A protein. While we were able to perform Uex-M from mouse tissue samples (flatmount retina) to study Fam161A expression in the connecting cilium (Mercey et al PLoS Biol 2022), it was more challenging to obtained low magnification picture from mouse retina sections. We propose to show in Figure 3 mouse Fam161A expression obtained from retina section and keep the low magnification from a flatmount for the figure 5. Thus, there will be no duplication of images as recommended by the reviewer.

Fig 4H. HS+HL combo, and HL alone, showed almost a polarized quantification, quite variable. Can the authors speculate the reason?

Despite the fact that injections are targeting similar retinal region in treated animals, there is still variation in the localization and extend of the gene transfer due to the surgical success. Indeed, the area of retinal detachment is hard to control in the mouse as of the quality of re-attachment. Moreover, the effective dose may lightly vary when some viral particles might be loss due to reflux. One would need to treat a larger number of eyes to really conclude that HS alone would be less variable than HL alone or HS+HL. However, we could also speculate that HS+HL and HL treatments being more efficient to rescue connecting cilium length compared to HS alone (Fig 5F) could, in the best injected eyes, have a better ONL thickness rescue than the limited ONL rescue induced by HS treatment.

Also can the authors comment on if there is any associated notable inflammation especially in high tier dosage (10^11 GC)?

We didn’t follow inflammation directly by fundus examination or OCT imaging following injection. However, despite the high dose used in our successful conditions (10E11 GC/eye), we didn’t notice any differences in the general mouse welfare after injection compare to lower doses. Systemic administration of Rimadyl (carprofen) was however adapted to each mouse during the 24 hrs post-surgery. In comparison to other groups with lower vector doses, no particular emergence of inflammatory cells or damages were observed by histology.

Can the authors comment on the difference in the injection time, PN14‐15 in this study vs. PN24‐29 in their previous study? Have the authors attempted to treat the older mice with the optimized vector?

The gene therapy study using the mouse cDNA was performed before establishing the time course of connecting cilia disruption in the Fam161atmb/tmb mouse (Mercey et al. 2022). Following the observation that CC develop similarly to healthy animal up to postnatal day 10, we decided to treat the mouse earlier for the second gene therapy study using human proteins. Nonetheless, the action of the vector occurred when the cilium is already disorganized as we expect expression of the WT Fam161A from 2 weeks post-injection. We are now testing treatments at different ages, including PN28, to determine the therapeutic window and if the optimal conditions (dose, ratio) may vary with the age at treatment.

Can the authors speculate on why IRBP‐GRK1 human FAM161A did not realize functional rescue (Fig 2) as it did with mouse FAM161A (previous work)?

Our hypothesis to explain the absence of functional rescue following IRBP-GRK1 vector injection is that the difference in human protein distribution compared to the mouse protein in the mouse retina could impact the function of the photoreceptor by interfering with physiological process such as transport. As mentioned in our discussion: “overexpression of these proteins could saturate the transport system impacting the cellular processes”.

As mentioned in the discussion, there is only 60% of homology between human and mouse proteins which could induce a major impact on protein localization and function. Post-translational modification which are also known to be crucial for modulating connecting cilium addressing (Rao et al. 2016) could also differ and impact both human protein distribution and function (for example 3 cysteines in the human protein sequence could be palmytoylated (C359, C366, C367) and are absent in the mouse sequence). Moreover, the exact role of the human long and short isoforms are unknown and their adaptability to the mouse system not yet identified. Further studies should be performed to understand the consequence of such differences on the function and to unravel the function of both long and short human isoforms in the retina.

Minor:

While the manuscript is overall well communicated, there are areas requiring further proofread. For example, in the Abstract section, "In 15 years" should be "For 15 years", "14‐days FAM161atm1b/tm1b mice" should be "14‐day old". In the Introduction, "... suggesting that protein miss‐localization" should be "mis‐localization". In the last paragraph before Discussion, "(iii) the restauration of CC..." should be "restoration", etc.

We corrected these errors and carefully proofread the whole manuscript to avoid typing mistakes.

I recommend the authors to use a table to summarize different promoters, titers and key findings (e.g., expression level, localization) used and refer back to each figure.

We thank the reviewer for this valuable suggestion and have now included a summary Table (Table 1) cited in the last result section.

Scale bars on all figures, or every set of images.

We added scale bars on figures containing microscopic images.

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Referee #3

Evidence, reproducibility and clarity

This manuscript led by Arsenijevic and Chang is an important technical development to the ocular gene therapy space, and touches on the important aspect of structural protein restoration by gene therapy, that is, the precise control of localization and subsequent functional realization. Overall the manuscript is well written, and the experiments are technically sound, with limitations acknowledged.

To briefly summarize, the authors wanted to understand precise control of FAM161A expression and connecting cilium (CC) restoration. They built on, and extended their previous work that showed limited structural and functional rescue by photoreceptor expression of the longer isoform of mouse FAM161A in Fam161a KO driven by IRBP-GRK1 promoter. In the current work, the authors experimented with delivering human ortholog of FAM161A cDNA, short, or long, or both isoforms using newly devised, relatively weak promoters. The main readouts include retinal morphology (e.g., ONL thickness), ERG, and protein localization by IHC (e.g., correct location, no ectopic expression). It is worth noting that the authors highlighted the use of expansion microscopy technology to examine the connecting cilium (CC) organization and protein expression, which may minimize the use of TEM for CC structure determination and enable acceleration.

My enthusiasm for recommending it for publication is high. Nonetheless, I have the following comments, hoping the authors could address to further improve the manuscript.

Major:

Fig 1A-B. Do hTERT-RPE1 cells endogenously express FAM161A? This set of images lacks a negative control (i.e., no transfected RPE1 cells). Western blot of FAM161A is recommended, similar to Fig 1C.

Fig 1C. The authors noted in the discussion that HS isoform is more abundant than HL isoform from human retinal extract. Although this is from 661W, a mouse photoreceptor cell line, it seems this is aligned with the notion. To echo with the last comment, I am curious to see if under the same transfection, the HS isoform is preferentially expressed in hTERT-RPE1 cells..

Fig 3 and Fig 5: low mag WT images of FAM161A are the same. But higher mag images (presumably selected from ROIs in low mag) are not the same. Please make sure of no duplication images.

Fig 4H. HS+HL combo, and HL alone, showed almost a polarized quantification, quite variable. Can the authors speculate the reason? Also can the authors comment on if there is any associated notable inflammation especially in high tier dosage (10^11 GC)?

Can the authors comment on the difference in the injection time, PN14-15 in this study vs. PN24-29 in their previous study? Have the authors attempted to treat the older mice with the optimized vector?

Can the authors speculate on why IRBP-GRK1 human FAM161A did not realize functional rescue (Fig 2) as it did with mouse FAM161A (previous work)?

Minor:

While the manuscript is overall well communicated, there are areas requiring further proofread. For example, in the Abstract section, "In 15 years" should be "For 15 years", "14-days FAM161atm1b/tm1b mice" should be "14-day old". In the Introduction, "... suggesting that protein miss-localization" should be "mis-localization". In the last paragraph before Discussion, "(iii) the restauration of CC..." should be "restoration", etc.

I recommend the authors to use a table to summarize different promoters, titers and key findings (e.g., expression level, localization) used and refer back to each figure.<br /> Scale bars on all figures, or every set of images.

Referees cross-commenting

To reviewer #2, Fig5f - WT data was shown as the gray horizontal line. I had the same question but then saw they noted in the legends. I think it is fine to cite the PRER review article to make their point.

I agree with the comments addressed by Reviewer #1 and am glad we both raise the point of using table for summarization.

Significance

This well-drafted paper represents a technical development that could supplement current gene therapy strategies to certain ciliopathies. In this particular case, the authors chose FAM161A, a disease causal gene to retinitis pigmentosa-28 and encodes for a microtubule-associated ciliary protein involved in organizing the connecting cilium in photoreceptors. Of importance, the authors devised novel promoters to drive gene expression and took advantage of expansion microscopy for quickly examining cilia proteins and structures. Conceptually, the techniques developed in this manuscript could be applicable to several other inherited retinal dystrophies that share similar disease mechanisms.

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Referee #2

Evidence, reproducibility and clarity

Arsenijevic et al. investigated the therapeutic function of the FCBR1-F0.4 promoter-driven expression of both the short and long isoforms of human FAM161A. The results showed that this method not only repaired the disorganized connecting cilium but also restored the appropriate expression and localization of other proteins in the connecting cilium, thus restoring retinal function. Additionally, the study systematically evaluated the AAV dose, different promoters, and FAM161A isoforms' effects on retinal survival and function. Overall, the study is novel and robust. Here are some suggestions that may help improve the manuscript:

Scotopic and photopic ERG were performed to study retinal function. However, mouse behavior tests such as optomotor response should be employed to confirm vision restoration.

The immunostaining in Figure 3 has some noise. Filtering the blocking solution before use could improve the quality of the staining.

In Figure 5f, the data of wildtype mice should be included for comparison.

The cited paper, such as 'Garafalo AV, Cideciyan AV, Heon E, Sheplock R, Pearson A, WeiYang Yu C, Sumaroka A, Aguirre GD, and Jacobson SG. Progress in treating inherited retinal diseases: Early subretinal gene therapy clinical trials and candidates for future initiatives. Prog Retin Eye Res. 2020;77(100827),' should be an original research paper, not a review article.

Referees cross-commenting

Agree with the comments addressed by Reviewer #1 and #3

Significance

Overall, the manuscript is clear and interesting. I suggest a major resion for the manuscript.

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Referee #1

Evidence, reproducibility and clarity

The manuscript "Fine-tuning FAM161A gene augmentation therapy to restore retinal function" submitted by Arsenijevic et al., describes gene therapy for RP28 caused by mutation in FAM161A in human. The authors worked on Fam161a-dficient mice by testing different isoforms, dose, promoter and enhancers to control the expression level and localization of the protein to functionally rescue the mice to prevent blindness. The tight control of protein expression is required for mutation in genes coding structural proteins in the retina.

The authors have clearly showed the optimized combination of conditions to restore function of Fam161atm1b/tm1b mice and also area of improvement to make.

Comments

Table

1. It would be nice to have a table of isoform, dose, promoter, enhancer and other conditions tested and the brief summary of phenotype as Table.

Discussion

1. This experiment was done on knockout condition but in real patient different form of mutant protein will exist in retinal tissue. Authors indicated that co-expression of short and long form of FAM161A worked better to rescue function. How would authors cope with interfering endogenous mutant protein in real patients?
2. Related to the first question, the expression of these retinal structural proteins will be different in mice and human. How would authors optimize the vector for human patient gene therapy?

Significance

This is an important and excellent work showing tight control of expression is required for future retinal gene therapy.

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Reply to the reviewers

1. General Statements [optional]

We are thankful to the reviewers for the time and effort invested in assessing our manuscript and for their suggestions to improve it. We have now considered the points raised by them, carried out additional experiments, and modified the text and figures to address them. We feel that the new experiments and modifications have been able to solve all concerns raised by the reviewers and have improved the manuscript substantially, strengthening and extending our conclusions.

The main modifications include:

• We have extended the analysis of the overexpression strains to highly stringent conditions, which revealed a mild acidification defect for the strain overexpressing Oxr1. In addition, we have included in our analysis a strain in which both proteins are overexpressed, which resulted in a further growth defect.
• We have analyzed the recruitment of Rtc5 to the vacuole under additional conditions: deletion of the main subunit of the RAVE complex RAV1, medium containing galactose as the sole carbon source and pharmacological inhibition of the V-ATPase. These experiments allowed us to strengthen and extend our conclusions regarding the requirements for Rtc5 targeting to the vacuole.
• We have analyzed V-ATPase disassembly in intact cells, by addressing the localization to the vacuole of subunit C (Vma5) in glucose and galactose-containing medium. The results strengthen our conclusion that both Rtc5 and Oxr1 promote an in vivo state of lower V-ATPase assembly.
• We have extended our analyses of V-ATPase function to medium containing galactose as a carbon source, since glucose availability is one of the main regulators of V-ATPase function in vivo. The results are consistent with what we observed in glucose-containing medium.
• We have included a diagram of the structure of the V-ATPase for reference.
• We have included a diagram and a paragraph describing Oxr1 and Rtc5 regarding protein length and domain architecture and comparing them to other TLDc domain-containing proteins.
• We have made changes to the text and figures to improve clarity and accuracy, including a methods section that was missing. We include below a point-by-point response to the reviewers´ comments.

2. Point-by-point description of the revisions

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

__ __Suggestions:

1. The authors observed that knockout of Rtc5p or Oxr1p does not affect vacuolar pH. If Rtc5p and Oxr1p both cooperate to dissociate V-ATPase, the authors may wish to characterize the effect of a ∆Rtc5p∆Oxr1p double knockout on vacuolar pH. The double mutant ∆rtc5∆oxr1 was already included in the original manuscript (the growth test is shown in Figure 5 B and the BCECF staining is shown in Figure 5C). This strain behaved like wt in both of these assays. Of note, what we observe for the deletion strains is increased assembly (Figure 5 D - G), so we expect that it would be hard to observe a difference in vacuole acidity or growth in the presence of metals.

Therefore, we have now also included a strain with the double overexpression of Oxr1 and Rtc5. Since overexpression of the proteins results in decreased assembly, it is more likely that this strain will show impaired growth under conditions that strongly rely on V-ATPase activity. Indeed, we observed that the overexpression of Oxr1 alone resulted in a slight growth defect in media containing high concentrations of ZnCl2 and the double overexpression strain showed an even further defect (Figure 6 A and C).

The manuscript would benefit from a well-labelled diagram showing the subunits of V-ATPase (e.g. in Figure 2D).

We agree with the reviewer and we have now added a diagram of the structure of the V-ATPase labeling the different subunits in Figure 2B.

The images of structures, especially in Figure 1-Supplement 1B, are not particularly clear and could be improved (e.g. by removing shadows or using transparency).

We are thankful to the reviewer for this suggestion. To improve the clarity of the structures in Figure 1 C and Figure 1 – Supplement 1A, we are now presenting the different subunits in the structures with different shades of blue and grey.

The authors should clearly describe the differences between Rtc5p and Oxr1p in terms of protein length, sequence identity, domain structure, etc.

We are thankful for this suggestion and we have now included a diagram of the domain architecture and protein length of Rtc5 and Oxr1, comparing with two human proteins containing a TLDc domain in Figure 5A. In addition, we have added the following paragraph describing the features of the proteins.

“Rtc5 is a 567 residue-long protein. Analysis of the protein using HHPred (Zimmermann et al., 2018), finds homology to the structure of porcine Meak7 (PDB ID: 7U8O, (Zi Tan et al., 2022)) over the whole protein sequence (residues 37-559). For both yeast Rtc5 and human Meak7 (Uniprot ID: Q6P9B6), HHPred detects homology of the C-terminal region to other TLDc domain containing proteins like yeast Oxr1 (PDBID: 7FDE), Drosophila melanogaster Skywalker (PDB ID: 6R82), and human NCOA7 (PDB ID: 7OBP), while the N-terminus has similarity to EF-hand domain calcium-binding proteins (PDB IDs: 1EG3, 2CT9, 1S6C6, Figure 5A). HHPred analysis of the 273 residue long Saccharomyces cerevisiae Oxr1, on the other hand, only detects similarity to TLDc domain containing proteins (PDB IDs: 7U80, 6R82, 7OBP), which spans the majority of the sequence of the protein (residues 71-273). The overall sequence identity between Oxr1 and Rtc5 is 24% according to a ClustalOmega alignment within Uniprot. The Alphafold model that we generated for Rtc5 is in good agreement with the available partial structure of Oxr1 (7FDE) (root mean square deviation (RMSD) of 3.509Å) (Figure 5 - S1 A), indicating they are structurally very similar, in the region of the TLDc domain. Taken together, these analyses suggest that Oxr1 belongs to a group of TLDc domain-containing proteins consisting mainly of just this domain like the splice variants Oxr1-C or NCOA7-B in humans (NP_001185464 and NP_001186551, respectively), while Rtc5 belongs to a group containing an additional N-terminal EF-hand-like domain and a N-myristoylation sequence, like human Meak7 (Finelli & Oliver, 2017) (Figure 5 A).”

Minor:

1. The "O" in VO should be capitalized. This has been corrected.

In Figure 4 supplement 1, the labels "I", "S", and "P" should be defined.

This has been clarified in the figure legend.

Please clarify what is meant by "switched labelling"

This refers to the SILAC vacuole proteomics experiments, for which yeast strains are grown in medium containing either L-Lysine or 13C6;15N2- L-Lysine to produce normal (‘light’) or heavy isotope-labeled (‘heavy’) proteins. This allows comparing two conditions. To increase the robustness of the comparisons, the experiments are done twice with both possible labeling schemes (condition A – light, condition B – heavy + condition A – heavy + condition B – light), which is commonly described as switched labeling or label switching.

We have exchanged the original sentence in the manuscript for:

“Performing the same experiments but switching which strain was labeled with heavy and light amino acids gave consistent results.”

The meaning of the sentence "Indeed, this was the case for both of them" is ambiguous.

We have now replaced this sentence with the following:

“Indeed, overexpression of either Rtc5 or Oxr1 resulted in increased growth defects in the context of Stv1 deletion (Figure 7 H and I).”

For Figure 1-Supplement 1B it is hard to see the crosslink distances.

We have updated this figure to improve the visibility of the cross-links. In addition, we now include a supplemental table (supplemental table 5) with a list of the Cα- Cα distances measured for all the crosslinks we mapped onto high-resolution structures.

The statement "The effects of Oxr1 are greater than those caused by Rtc5" requires more context. Is there a way of quantifying this effect for the reader?

We agree that this sentence was too general and vague. The effects caused by one or the other protein depend on the condition and the assay. We have thus deleted this sentence, and we think it is better to refer to the description of the individual assays performed.

The phrase "negative genetic interaction" should be clarified.

We have included in the text the following explanation of genetic interactions:

“A genetic interaction occurs when the combination of two mutations results in a different phenotype from that expected from the addition of the phenotypes of the individual mutations. For example, deletion of OXR1 or RTC5 has no impact on growth in neutral pH media containing zinc in a control background but improves the growth of RAV1 deletion strains (Figure 7 E and F), so this is a positive genetic interaction. On the other hand, overexpression of either Rtc5 or Oxr1 results in a growth defect in a background lacking Rav1 in neutral media containing zinc, a negative genetic interaction.”

* * In the sentence "Isogenic strains with the indicated modifications in the genome where spotted as serial dilutions in media with pH=5.5, pH=7.5 or pH=7.5 and containing 3 mM ZnCl2", "where" should be "were".

This has been corrected.

Figure 2D: the authors should consider re-coloring these models, as it is challenging to distinguish Rtc5p from the V-ATPase.

We have changed the coloring of this structure and added a diagram of the V-ATPase structure with the same coloring scheme to improve clarity.

Reviewer #1 (Significance (Required)):

The vacuolar protein interaction map alone from this manuscript is a nice contribution to the literature. Experiments establishing colocalization of Rtc5p to the vacuole are convincing, as is dependence of this association on the presence of assembled V-ATPase. Similarly, experiments related to myristoylation are convincing. The observed mislocalization of V-ATPases that contain Stv1p to the vacuole (which is also known to occur when Vph1p has been knocked out) upon knockout of Oxr1p is also extremely interesting. Overall, this is an interesting manuscript that contributes to our understand of TLDc proteins.

We are thankful to the reviewer for their appreciation of the significance of our work, including the interactome map of the vacuole as a resource and the advances on the understanding of the regulation of the V-ATPase by TLDc domain-containing proteins.

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

Major points:

1. The evidence of Oxr1 and Rtc5 as V-ATPase disassembly factors is circumstantial. The authors base their interpretation primarily on increased V1 (but not Vo) at purified vacuoles from Oxr1- or Rtc5-deleted strains, which does not directly address disassembly. Of course, the results regarding Oxr1 confirm detailed disassembly experiments with the purified protein complex (PMID 34918374), but on their own are open to other interpretations, e.g. suppression of V-ATPase assembly. Of note, the authors emphasize that they provide first evidence of the in vivo role of Oxr1, but monitor V1 recruitment with purified vacuoles and do not follow V-ATPase assembly in intact cells. We are thankful to the reviewer for pointing this out. We did not want to express that the molecular activity of the proteins is the disassembly of the complex, as our analyses include in vivo and ex vivo experiments and do not directly address this. We rather meant that both proteins promote an in vivo state of lower assembly of the V-ATPase. We have modified the wording throughout the manuscript to be clearer about this.

In addition, we have added new experiments to monitor V-ATPase assembly in intact cells, as suggested by the reviewer. Previous work has shown that in yeast, only subunit C leaves the vacuole membrane under conditions that promote disassembly, while the other subunits remain at the vacuole membrane (Tabke et al 2014). Our own experiments agree with what was published (Figure 3 D). We have thus monitored Vma5 localization to the vacuole under glucose or after shift to galactose containing media in cells lacking or overexpressing Rtc5 or Oxr1. We observed that cells overexpressing either TLDc domain protein show lower levels of Vma5 recruitment to the vacuole in glucose (Figure 6 D and E). Additionally cells lacking either Rtc5 or Oxr1 contain higher levels of Vma5 at the vacuole after 20 minutes in galactose medium (Figure 5 F and G). Thus, these results re-inforce our conclusions that Rtc5 and Oxr1 promote states of lower assembly.

Oxr1 and Rtc5 have very low sequence similarity. It would be helpful if the authors provided more detail on the predicted structure of the putative TLDc domain of Rtc5 and its relationship to the V-ATPase - Oxr1 structure. Is Rtc5 more closely related to established TLDc domain proteins in other organisms?

We have now included a diagram of the domain architecture of Rtc5 and Oxr1, and comparison to the features of other TLDc domain containing proteins in Figure 5 A, as well as a paragraph describing them:

“Rtc5 is a 567 residue-long protein. Analysis of the protein using HHPred (Zimmermann et al., 2018), finds homology to the structure of porcine Meak7 (PDB ID: 7U8O, (Zi Tan et al., 2022)) over the whole protein sequence (residues 37-559). For both yeast Rtc5 and human Meak7 (Uniprot ID: Q6P9B6), HHPred detects homology of the C-terminal region to other TLDc domain containing proteins like yeast Oxr1 (PDBID: 7FDE), Drosophila melanogaster Skywalker (PDB ID: 6R82), and human NCOA7 (PDB ID: 7OBP), while the N-terminus has similarity to EF-hand domain calcium-binding proteins (PDB IDs: 1EG3, 2CT9, 1S6C6, Figure 5A). HHPred analysis of the 273 residue long Saccharomyces cerevisiae Oxr1, on the other hand, only detects similarity to TLDc domain containing proteins (PDB IDs: 7U80, 6R82, 7OBP), which spans the majority of the sequence of the protein (residues 71-273). The overall sequence identity between Oxr1 and Rtc5 is 24% according to a ClustalOmega alignment within Uniprot. The Alphafold model that we generated for Rtc5 is in good agreement with the available partial structure of Oxr1 (7FDE) (root mean square deviation (RMSD) of 3.509Å) (Figure 5 - S1 A), indicating they are structurally very similar, in the region of the TLDc domain. Taken together, these analyses suggest that Oxr1 belongs to a subfamily of TLDc domain-containing proteins consisting mainly of just this domain like the splice variants Oxr1-C or NCOA7-B in humans (NP_001185464 and NP_001186551, respectively) , while Rtc5 belongs to a subfamily containing an additional N-terminal EF-hand-like domain and a N-myristoylation sequence, like human Meak7 (Finelli & Oliver, 2017) (Figure 5 A).”

The authors conclude vacuolar recruitment of Rtc5 depends on the assembled V-ATPase, based on deletion of different V1 and Vo domain subunits. However, these genetic manipulations likely cause a strong perturbation of vacuolar acidification; indeed, the images show drastically altered vacuolar morphology. To strengthen their conclusion, it would be helpful to show that Rtc5 recruitment is not blocked by inhibition of vacuolar acidification, and that conversely it is blocked by deletion of rav1.

We are thankful to the reviewer for this insightful suggestion and we have now performed both experiments suggested. The experiment regarding rav1Δ is now Figure 3C, and we observed that this mutation also disrupts Rtc5 localization to the vacuole. In addition, we decided to include an experiment showing the subcellular localization of Rtc5 after shifting the cells to galactose containing medium for 20 minutes, as a physiologically relevant condition that results in disassembly of the complex (Figure 3D). We observed that under these conditions Rtc5 re-localizes to the cytosol. This result is particularly interesting given that in yeast only subunit C (but not other V1 subunits) re-localizes to the cytosol under these conditions. In addition, the experiment using Bafilomycin A to inhibit the V-ATPase shows that Rtc5 is still localized at the vacuole membrane under conditions of V-ATPase inhibition (Figure 3 F). Taken together these results allowed us to strengthen our original interpretation that Rtc5 requires an assembled V-ATPase for its localization and extend it to the fact that the V-ATPase does not need to be active.

Reviewer #2 (Significance (Required)):

This is an interesting paper that confirms and extends previous findings on TLDc domain proteins as a novel class of proteins that interact with and regulate the V-ATPase in eukaryotes. The title seems to exaggerate the findings a bit, as the authors do not investigate V-ATPase (dis)assembly directly and only phenotypically describe altered subcellular localization of the Golgi V-ATPase in Oxr1-deleted cells. A recent structural and biochemical characterization of Oxr1 as a V-ATPase disassembly factor (PMID 34918374) somewhat limits the novelty of the results, but the function of Oxr1 in regulating subcellular V-ATPase localization and the identification of a second potential TLDc domain protein in yeast provide relevant insights into V-ATPase regulation. This paper will be of interest to cell biologists and biochemists working on lysosomal biology, organelle proteomics and V-ATPase regulation.

We thank the reviewer for the assessment of our work, and for recognizing the novel insights that we provide. Regarding the previous biochemical work on Oxr1 and the V-ATPase, we have clearly cited this work in the manuscript. In our opinion, our results complement and extend this article, showing that the function in disassembly is relevant in vivo. Additionally, this is only one of five major points of the article, the other four being

• The interactome map of the vacuole as a resource
• The identification of Rtc5 as a second yeast TLDc domain containing protein and interactor of the V-ATPase.
• The identification of the role of Rtc5 in V-ATPase assembly.
• The identification of the role of Oxr1 in Stv1 subcellular localization. We believe these additional points add important insights to researchers interested in lysosomes, the V-ATPase, intracellular trafficking and TLDc-domain containing proteins.

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

Major comments

__1) Re: A cross-linking mass spectrometry map of vacuolar protein interactions (results) __ While XL-MS is a very powerful method, it is a high-throughput approach and there should be some kind of negative control in these experiments. In cross-linking experiments, non-cross-linked samples are usually used as negative controls. What was the negative control in cross-linking mass-spectrometry experiments here? If there was no negative control, how the specificity of interactions was evaluated? Maybe the authors analyzed the dataset for highly improbable interactions and found very few of them?

We fully agree that it is crucial to ensure the specificity of the interactions detected by XL-MS. To achieve this, one needs to control (1) the specificity of the data analysis (i.e. that the recorded mass spectrometry data are correctly matched to cross-linked peptides from the sequence database) and (2) the biological specificity (i.e. that the cross-linking captured natively occurring interactions).

To ascertain that criterion (1) is met, cross-link identifications are filtered to a pre-defined false-discovery rate (FDR) – an approach that the XL-MS field adopted from mass spectrometry-based proteomics. As a result, low-confidence identifications (e.g. cross-linked peptides that are only supported by a few signals in a given mass spectrum) are removed from the dataset. FDR filtering in XL-MS is a rather complex matter as it can be done at different points during data analysis and the optimal FDR cut-off depends on the specific scientific question at hand (for more details see for example Fischer and Rappsilber, Anal Chem, 2017). Generally speaking, an overly restrictive FDR cut-off would remove a lot of correct identifications, thereby greatly limiting the sensitivity of the analysis. On the other hand, a too relaxed FDR cut-off would dilute the correct identifications with a high number of false-positives, which would impair the robustness and specificity of the dataset. While many XL-MS study control the FDR on the level of individual spectrum matches, we opted for a 2% FDR cut-off on the level of unique residue pairs, which is more stringent (see Fischer and Rappsilber, Anal Chem, 2017). Our FDR parameters are described in the Methods section (Cross-linking mass spectrometry of isolated vacuoles - Data analysis). Of note, we have made all raw mass spectrometry data publicly available through the PRIDE repository (https://www.ebi.ac.uk/pride/ ; accession code PXD046792; login details during peer review: Username = reviewer_pxd046792@ebi.ac.uk, Password = q1645lTP). This will allow other researchers to re-analyze our data with the data analysis settings of their choice in the future.

To ascertain that criterion (2) is met, we mapped the identified cross-links onto existing high-resolution structures of vacuolar protein complexes. Taking into account the length of our cross-linking reagent, the side-chain length of the cross-linkable amino acids (i.e. lysines), and a certain degree of in-solution flexibility, cross-links can reasonably occur between lysines with a mutual Cα-Cα distance of up to 35 Å. Using this cut-off, the lysine-lysine pairs in the high-resolution structures we studied can be split into possible cross-linking partners (Cα-Cα distance 35 Å). Of all cross-links we could map onto high-resolution structures, 95.2% occurred between possible cross-linking partners. In addition, our cross-links reflect numerous known vacuolar protein interactions that have not yet been structurally characterized. These lines of evidence increase our confidence that our XL-MS approach captured genuine, natively occurring interactions. These analyses are described in more detail in the first Results sub-section (“A cross-linking mass spectrometry map of vacuolar protein interactions”).

In addition, the high purity of vacuole preparation is critical. How was it assessed by the authors?

We disagree that the purity of the vacuole preparation is critical for this analysis to be valid. The accuracy of the protein-protein interactions detected will depend on their preservation during sample preparation until the sample encounters the cross-linker, and the data analysis, as described above. The experiment would have been equally valid if performed on whole cell lysates without any enrichment of vacuoles, but the coverage of vacuolar proteins would have likely been very low. For this reason, we decided to use the vacuole isolation procedure to obtain better coverage of the proteins of this particular organelle. The use of the Ficoll gradient protocol (Haas, 1995) was based on that it is a protocol that yields strong enrichment of proteins annotated with the GO Term “vacuole” (Eising et al, 2019) and that it preserves the functionality of the organelle, as evidenced by its use for multiple functional assays (vacuole-vacuole fusion (Haas, 1995), autophagosome-vacuole fusion (Gao et al, 2018), polyphosphate synthesis by the VTC complex (Desfougéres et al, 2016), among others).

2) Re: Rtc5 and Oxr1 counteract the function of the RAVE complex (results)

Taken together, data, presented in this section of the manuscript, provide strong evidence that Rtc5 and Oxr1 negatively regulate V-ATPase activity, counteracting the V-ATPase assembly, facilitated by the activity of the RAVE complex. However, the complete deletion of the major RAVE subunit Rav1p was required to observe this effect in vivo in yeast. The other way to induce V-ATPase disassembly in yeast is glucose deprivation. It will be interesting to study if there is a synergistic effect between glucose deprivation and RTC5/OXR1 deletion on V-ATPase assembly, vacuolar pH, and growth of single oxr1Δ, rtc5Δ or double oxr1Δrtc5Δ mutants (OPTIONAL). Glucose deprivation is a more physiologically relevant condition than a deletion of an entire gene.

We would like to point out that an effect on assembly is observed without deleting the RAVE complex: deletions of Oxr1 or Rtc5 resulted in increased V-ATPase assembly in vivo in the presence of glucose and of the RAVE complex (Figures 5 D and E). We have now also added the experiments showing that the overexpression strains have a mild growth defect under conditions that force cells to strongly rely on V-ATPase activity (Figures 6 A and C).

Nevertheless, we agree that addressing the effect of changing the levels of Oxr1 and Rtc5 under low-glucose conditions is an interesting physiologically relevant question. We have now included growth assays and BCECF staining in medium containing galactose as the carbon source (Figures 5 – Supplement 1 B and C, and Figure 6 C and Figure 6- Supplement 1A). In addition, we have addressed the vacuolar localization of Vma5 in medium containing glucose or after shifting to medium containing galactose for 20 minutes, as a proxy for V-ATPase disassembly in intact cells (Figure 5 F and G, Figure 6 D and E). Taken together, these analyses reinforce our conclusions that both Rtc5 and Oxr1 promote an in vivo state of lower V-ATPase assembly, based on the following observations:

• Higher localization of Vma5 to the vacuole after 20 mins in galactose in cells lacking Oxr1 or Rtc5 (Figure 5 F and G).
• Lower localization of Vma5 to the vacuole in medium containing glucose in cells overexpressing Oxr1 or Rtc5 (Figure 6 D and E).
• Growth defect of the strain overexpressing Oxr1 in medium containing galactose with pH = 7.5 and zinc chloride, with a further growth defect caused by additional overexpression of Rtc5 (Figure 6 C). 3) Re: Figure 6 - supplement 1. The title is relevant to panel D only, it should be renamed to reflect the results of the disassembly of V-ATPase in rav1Δ mutant strains, while results about the stv1Δ-based strains (Panel D) should be shown together with similar experiments in Figure 7 - supplement 2 for clarity.

We have shifted the Panel D from the original Figure 6 – Supplement 1 to the main Figure (now Figure 7 – H and I). Regarding the title of the Figure, whether Supplemental Figures have titles or not will depend on the journal where the manuscript is published. For now, we have removed all titles from supplemental figures, as they are conceived to complement the main Figures.

4) Re: Figure 7 - supplement 1, Panel A. The proper assay to show that Stv1-mNeonGreen is functional is to express it in double mutant vph1Δstv1Δ to see if the growth defect is reversed. In addition, the vph1Δ growth defect is not changed (improved or worsened) in the presence of Stv1-mNeonGreen, so it means that the expression of Stv1-mNeonGreen does not further compromise the V-ATPase function, but it does not mean that it improves its function.

It is clear from the experiment suggested by the reviewer that they think that we have expressed Stv1-mNeonGreen from a plasmid. This was not the case, Stv1 was C-terminally tagged with mNeonGreen in the genome. It is thus the only expressed version in the strain. The experiment we have performed is thus equivalent to the one suggested by the reviewer, but for genomically expressed variants. For reference, the genotypes of all the strains used can be found in Supplemental Table 1.

5) Re: Figure 7 - supplement 2. This figure should be combined with Fig. 6- suppl 1, panel D as also mentioned above. The figure seems to lack some labels, and conclusions are not accurate as discussed below. However, this data provides important additional information about relationships between isoform-specific subunits of V-ATPase Vph1 and Stv1 and both Rtc5 and Oxr1 and should be repeated if it is not done yet to have a better idea about these relationships.

Panel B: Based on this picture, deletion of RTC5 has a negative genetic interaction with the deletion of VPH1, since double deletion mutant vph1Δ rtc5Δ grows worse than each individual mutant. Although it also means that there is no positive interaction, it is not the same.

Indeed, there is a negative genetic interaction between the deletion of RTC5 and VPH1. We have replaced the growth tests in this figure (Figure 8 – Supplement 2 A in the new manuscript) to show this negative genetic interaction better. This effect is reproducible, as shown in the repetitions of the experiments.

Panel C: Same as for panel B. Based on this picture, the deletion of OXR1 has a weak negative genetic interaction with the deletion of STV1, since double deletion mutant stv1Δ oxr1Δ grows worse than each individual mutant at 6 mM ZnCl2.

Panel D: Same as for panels B and C. Based on this picture, deletion of RTC5 has a negative genetic interaction with the deletion of STV1, since double deletion mutant stv1Δ rtc5Δ grows worse than each individual mutant at 6 mM ZnCl2. There is no label in the middle panel (growth conditions) and no growth assay data in the presence of CaCl2.

However, these results will be then in contradiction with the results from Figure 6 - Supplement 1, panel D, showing negative genetic interaction between the overexpression of Rtc5 or Oxr1 and deletion of Stv1, since both deletion and overexpression of Rtc5 or Oxr1 would have negative genetic interactions with Stv1.

For both Panels C and D (Now Figure 8 - Supplement 2 B and C). The effect pointed out by the reviewer (slightly stronger growth defect for the double mutants than for the single mutants) is very mild. We have attempted to make it more evident by assessing growth in medium with higher and lower concentrations of zinc and this was not possible. This is in contrast with the very clear positive genetic interaction that we observe between the deletion of OXR1 and VPH1 (Now Figure 8 H). This is the reason that we decided to report the lack of a positive genetic interaction instead of the presence of a negative one, as we do not want to draw conclusions based on results that are borderline detectable.

In addition, there is no label for the media in the middle panel, is it just YPAD pH=7.5, without the addition of any metals?

Indeed, the media is YPAD pH=7.5, without the addition of any metals. The line drawn above several images based on this media indicated this. Since this form of labeling appears to be confusing, we have now replaced it and placed the label directly above the image.

Why there is no growth assay in the presence of CaCl2, like in panels A and B?

Every growth test shown in the manuscript was performed including growth in YPD pH=5,5 as a control of a permissive condition for lack of V-ATPase activity, and then in YPD pH=7,5 including a broad range of Zinc Chloride and Calcium chloride concentrations. From all these pictures, the conditions where the differences among strains were clearly visible were chosen to assemble the figures. Conditions that did not provide any information for that particular experiment were not included in the figure to avoid making them unnecessarily large and crowded.

Re: Figure 7 - supplement 2, continued. How many times all these experiments were repeated? These experiments should be repeated at least 3 times, which is especially necessary for the experiments in panel C, because the effects are borderline. If results are reproducible and statistically significant, although small, the conclusion should be changed from "no positive genetic interactions" to "negative genetic interactions", which is more precise and informative.

All growth tests shown in the manuscript were repeated at least three times for the conditions shown. We are thankful to the reviewer for pointing out that this was not mentioned, and we have added this to the methods section. We have assembled a file with all repetitions of the shown growth tests and added it at the end of this file. In doing so, these are already available for the public. These repetitions show that all effects reported are reproducible. We will then discuss with the editors of the journal where this manuscript is published about the necessity of including it with the final article.

Regarding reporting the lack of a positive genetic interaction vs. a negative one, we have discussed this above. Shortly, for Panel B (Figure 8 – Supplement 2 A in the new manuscript) we have changed the conclusion to “negative genetic interaction” as adjusting the zinc chloride concentration allowed us to show this clearly and reproducibly, as shown by the repetitions of the experiments. For panels C and D (Now Figure 8 - Supplement 2 B and C), the effect is really mild and barely detectable, even when we tried a wide range of zinc chloride concentrations. For this reason, we would prefer to maintain the “no positive genetic interaction” conclusion.

Re: Methods. There is no description of yeast serial dilution growth assay at all. In addition, why the specific media (neutral pH, in the presence of high concentrations of calcium or zinc) was used is not explained either in the results or methods. Appropriate references should be included, for example, PMID: 2139726, PMID: 1491236.

We apologize for the oversight of the missing methods section, which we have now included.

Regarding the explanation of the media used, the following section was already a part of the results section, before the description of the first growth test:

“The V-ATPase is not essential for viability in yeast cells, and mutants lacking subunits of this complex grow similarly to a wt strain in acidic media. However, when cells grow at near-neutral pH or in the presence of divalent cations such as calcium and zinc, the mutants lacking V-ATPase function show a strong growth impairment (Kane et al, 2006).”

We have now replaced this with the following, more complete version:

“As a first approach for addressing the role of these proteins, we tested growth phenotypes related to V-ATPase function in strains lacking or overexpressing them. The V-ATPase is not essential for viability in yeast cells, and mutants lacking subunits of this complex grow similarly to a wt strain in acidic media, but display a growth defect at near-neutral pH the mutants (Nelson & Nelson, 1990). In addition, the proton gradient across the vacuole membrane generated by the V-ATPase energizes the pumping of metals into the vacuole, as a mechanism of detoxification. Thus, increasing concentrations of divalent cations such as calcium and zinc, generate conditions in which growth is increasingly reliant on V-ATPase activity (Förster & Kane, 2000; MacDiarmid et al, 2002; Kane, 2006).”

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MINOR COMMENTS

Yeast proteins are named with "p" at the end, such as "Rtc5p".

This nomenclature rule is falling into disuse during the last decades, as the use of capitals vs lowercase and italics allows to distinguish between genes proteins and strains (OXR1 = gene, Oxr1 = protein, oxr1Δ = strain). As an example, I include a list of the latest papers by some of the major yeast labs around the world, all of which use the same nomenclature as we do (in alphabetical order). This list even includes some work in the field of the V-ATPase.

• Alexey Merz, USA. PMID: 33225520
• Benoit Kornmann, UK. PMID: 35654841
• Christian Ungermann, Germany. PMID: 37463208
• Claudio de Virgilio, Switzerland. PMID: 36749016
• Daniel E. Gottschling, USA. PMID: 37640943
• David Teis, Austria. PMID: 32744498
• Elizabeth Conibear, Canada. PMID: 35938928
• Fulvio Reggiori, Denmark. PMID: 37060997
• J Christopher Fromme, USA. PMID: 37672345
• Maya Schuldiner, Israel. PMID: 37073826
• Patricia Kane, USA. PMID: 36598799
• Scott Emr, USA. PMID: 35770973
• W Mike Henne, USA. PMID: 37889293
• Yoshinori Ohsumi, Japan. PMID: 37917025 In addition, we would prefer to keep the nomenclature that we already use, to keep consistency with other published articles from our lab.

Re: Introduction. In the introduction it should be indicated that Rtc5 was originally discovered as a "restriction of telomere capping 5", using screening of temperature-sensitive cdc13-1 mutants combined with the yeast gene deletion collection [PMID: 18845848]. A couple of sentences should be written about the RAVE complex and its role in V-ATPase assembly.

We are thankful for this suggestion and we have now included both pieces of information in the introduction.

*“The re-assembly of the V1 onto the VO complex when glucose becomes again available, is aided by a dedicated chaperone complex known as the RAVE complex, which also likely has a general role in V-ATPase assembly (Seol et al, 2001; Smardon et al, 2002, 2014).” *

“In our cross-linking mass spectrometry interactome map of isolated vacuoles we found that the only other TLDc-domain containing protein of yeast, Rtc5, is a novel interactor of the V-ATPase. Rtc5 is a protein of unknown function, originally described in a genetic screen for genes related to telomere capping (Addinall et al, 2008)”

Re: The TLDc domain-containing protein of unknown function Rtc5 is a novel interactor of the vacuolar V-ATPase (results)

1) It is important to understand, that Oxr1 was co-purified before with the V1 domain of V-ATPase from a certain mutant strain, not wild-type yeast [PMID: 34918374]. It may explain why the authors did not identify it in their original protein-protein interactions screen here.

The structural work on the V1 domain bound to Oxr1 (Khan et al, 2022) showed that the binding of Oxr1 prevented V1 from assembling onto the Vo. Since our experiments rely on the purification of vacuoles, they should contain mainly only V1 assembled onto the VO, and not the free soluble V1. This is likely the reason that we do not detect Oxr1, in addition to it being less abundant. We have clarified this now in the manuscript and added the fact that Oxr1 was co-purified with a V1 containing a mutant version of the H subunit.

“In a previous study, Oxr1 was co-purified with a V1 domain containing a mutant version of the H subunit, and its presence prevented the in vitro assembly of this V1 domain onto the VO domain and promoted disassembly of the holocomplex (Khan et al., 2022). This is likely the reason why we do not detect Oxr1 in our experiments, which rely on isolated vacuoles and thus would only include V1 domains that are assembled onto the membrane. In addition, Oxr1 is less abundant in yeast cells than Rtc5 according to the protein abundance database PaxDb (Wang et al, 2015).”

2) It is a wrong conclusion that because Rtc5 was co-purified with both V1 and V0 domain subunits it interacts with the assembled V-ATPase, this does not exclude a possibility that Rtc5 also interacts with separate V1 sector or separate V0 sector of V-ATPase.

We agree with the reviewer that the co-purification of Rtc5 with both V1 and VO domain subunits does not necessarily mean that it interacts with the assembled V-ATPase. Thus, we have modified the text in this part to:

“The fact that we can co-enrich Rtc5 both with Vma2 and with Vph1 indicates that it can interact either with both the VO and V1 domains or with the assembled V-ATPase.”

However, other results throughout the manuscript can be taken into account to strengthen this idea:

1. Rtc5 requires an assembled V-ATPase to localize to the vacuole membrane, and thus seems not to interact with free VO domains, which would be available when we delete V1 subunits or in medium containing galactose.
2. Rtc5 becomes cytosolic in galactose-containing media. This would indicate that it also does not interact with free V1 domains, which are still localized to the vacuole membrane under these conditions. Taken together with the pull-downs, these results suggest that Rtc5 interacts with the assembled V1-VO V-ATPase. Thus, we have included the following sentence after Figure 3, which shows the subcellular localization experiments.

*“Taking into account that Rtc5 is co-enriched with subunits of both the VO and V1 domain, and that it localizes at the vacuole membrane dependent on an assembled V-ATPase, we suggest that Rtc5 interacts with the assembled V-ATPase complex.” *

Re: Figure 1, Panel C. Is it possible to show individual proteins in different colors for clarity?

Panel D. How were cross-link distances measured? It is not obvious if you are not an expert in the field and it is not described in the methods.

We have modified Figure 1 C and Figure 1 – Supplement 1B (now Figure 1 – Supplement 1 A) to present the different subunits in the structures with different shades of blue and grey.

Furthermore, we have clarified the distance measurement approach in the methods section and in the legend of Fig 1D: “Ca-Ca distances were determined using the measuring function in Pymol v.2.5.2 (Schrodinger LLC).”

__Re: Figure 1 - Supplement 1, __

Panel A. What scientific information are we getting from this picture?

This panel was just a visual representation of the complexity of the protein network we obtained. Indeed, there was no specific scientific message, so we have decided to remove this panel from the revised manuscript.

Panel B. Why are these complexes shown separately from the complexes in Figure 1, panel C? Also, can individual proteins be colored differently here as well?

We did not want to overload Fig 1C, so we decided to show some of the protein complexes in Fig 1 – Supplement 1B. The most important information is the histogram showing that 95% of the mapped cross-links fall within the expected length range, and this is shown in the main Figure (Figure 1D). As stated above, we have adjusted the subunit coloring in Figure 1 C to improve clarity.

Re: Figure 3. It will be nice to show the localization of the untagged protein as well if antibodies are available (OPTIONAL).

Unfortunately, there are no available antibodies for either Rtc5 or Oxr1. This hinders us from detecting the endogenous untagged proteins. We would like to point out that we have been very careful in showing which tagged proteins are functional (C-terminally tagged Rtc5) and which are not (C-terminally tagged Oxr1), so that the reader can know how to interpret the localization data.

Re: Figure 4. Why different tags were used in panels A (GFP), C (msGFP2) and D

(mNeonGreen)?

In general, we prefer to use mNeonGreen as a tag for microscopy experiments because it is brighter and more stable, and msGFP2 as a tag for experiments involving Western blots because we have better antibodies available. There was a mistake in the labeling, and actually, all constructs labeled as GFP were msGFP2. We have now corrected this. Of note, we have tested the functionality of both tagged version (mNeonGreen and msGFP2).

Panels B and C. Were Rtc5 fusions detected using anti-GFP antibodies?

Indeed, Rtc5-msGFP2 was detected with an anti-GFP antibody. We have now indicated next to each Western blot membrane the primary antibody used. In addition, all antibodies are detailed in Supplemental Figure 3.

The authors should have full-size Western blots available, not just cut-out bands, as some journals and reviewers require them for publication.

For all western blots, we always showed a good portion of the membrane and not cut-out bands. The cropping was performed to avoid making figures unnecessarily large. The whole membranes are of course available and will be included in an “extended data file” if required by the journal.

Re: Figure 4 - Supplement 1, Panel A. Does "-" and "+" mean -/+ Azido-Myr?

Indeed. We have now added this label to the figure.

Panel B. There is no blot with a membrane protein marker (Vam3 or Vac8), it should be included.

We have replaced this western blot for a different repetition of this experiment in which a membrane protein marker was included. Of note, the two other repetitions of the experiment shown (Figure 4 – Supplement 1 panel C and Figure 4 panel C) also include both a membrane protein marker and a soluble protein marker.

Re: Figure 5. The title does not describe all results in this figure and should be modified accordingly.

The original data from Figure 5 is now separated into Figures 5 and 6 because of the additional experiments included during revisions. We have modified the Figure titles to be descriptive of the overall message of the Figures.

Panel C. Statistical significance value for *** should be indicated in the legend.

This has been indicated in the Figure legend.

It is not clear how many times yeast growth assays were repeated. Usually, all experiments should be done in triplicates or more.

All shown growth tests were performed at least three times for the conditions shown. We have now indicated this in the materials and methods section. In addition, we now provide in this response a file with all repetitions of growth tests, which will be appended to the article if deemed necessary by the editors.

Re: Figure 5 - supplement 1. No title

Re: Figure 5 - supplement 2. No title

Whether the supplemental Figures should have a title or not will depend on the style of the journal where the manuscript is finally published. The current idea of the supplemental Figures is that they complement the corresponding main Figure. For this reason, we have removed all titles from supplemental Figures.

Re: Figure 6. There is a typo on the second lane in the legend: "...the genome were", not "...the genome where".

This has been corrected.

Panel C. Why the analysis of BCECF vacuole staining of double mutants oxr1Δrav1Δ and rtc5Δrav1Δ is not shown? Was it done at all?

We had not included this piece of data, as we thought that the genetic interaction of RTC5 and OXR1 and rav1Δ was sufficiently well supported with the included data (growth tests in combination with the deletion, growth tests in combination with the overexpression, vacuole proteomics in combination with overexpression, and BCECF staining in combination with the overexpression). Because of the request of the reviewer, we have now included this experiment as Figure 7 G.

Re: Figure 6 - Supplement 2. Why were two different tags (2xmNG and msGFP2) used?

We tried both tags to see if one of them would be functional. Unfortunately, they both resulted in non-functional proteins, as shown by the corresponding growth tests.

Did the authors study N-terminally tagged Oxr1? Was it functional?

We have tagged Oxr1 N-terminally, and this unfortunately resulted in a protein that was not completely functional. We show below the localization of N-terminally mNeon-tagged Oxr1, under the control of the TEF1 promoter. The protein appears cytosolic (Panel A) but is not completely functional (Panel B). The localization of Oxr1 had already been misreported by using a tagged version that we now show to be non-functional. For this reason, we preferred not to include this data in the manuscript, to avoid again including in the literature subcellular localizations that correspond to non-functional or partially functional proteins.

Panel B. Results for the untagged TEF1pr-Oxr1 overexpression are not shown, thus tagged and untagged proteins can't be compared. Are they available? What is the promoter for the expression of 2xmNG fusion constructs?

Oxr1-2xmNG was C-terminally tagged in the genome, which means that the promoter is the endogenous one, it was not modified. For this reason, the correct controls are a strain expressing Oxr1 at endogenous levels (the wt strain) and a strain lacking Oxr1. Both controls were included in the Figure, and in all repetitions made of this experiment. For reference, all the genotypes of the strains used are found in Supplemental Table 1.

Re: Methods. Were vacuoles prepared differently for XL-MS and SILAC-based vacuole proteomics (there are different references) and why? Methods for XL-MS and quantitative SILAC-based proteomics can be placed together for clarity.

The basis for the method of vacuole purification is the same, from (Haas, 1995). This reference was included in both protocols that include vacuole purifications. However, modifications of this method were performed to fit the crosslinking method (higher pH, no primary amines) or to fit the SILAC labeling (combination of two differentially labeled samples in one purification). The reference for the vacuole proteomics (Eising et al 2022) corresponds to a paper in which the SILAC-based comparison of vacuoles from different mutant strains was optimized, and includes not only the vacuole purification but the growth conditions and downstream processing of the vacuoles.

Since both the SILAC-based vacuole proteomics and the XL-MS are multi-step methods, containing numerous parameters including the sample preparation, processing for MS, MS run and data analysis, we would prefer to keep them separate. We think this would allow a person attempting to reproduce these methods to go through them step by step.

What is CMAC dye? Why was it used to stain the vacuolar lumen?

We apologize for this oversight, we have included the definition of CMAC as 7-Amino-4-Chlormethylcumarin. It is a standard-used organelle marker for the lumen of the vacuole.

Some abbreviations (TEAB, ACN) are not explained.

We apologize for this oversight. We have now replaced these abbreviations with the full names of the compounds in the article.

What is 0% Ficoll?

We used the term 0% Ficoll, because this is the name given to the buffer in the original Haas 1995 paper on vacuole purifications. However, we agree that the term is misleading and we have now added the composition of the buffer (10 mM PIPES/KOH pH=6.8, 0.2 M Sorbitol).

Reviewer #3 (Significance (Required)):

The vacuolar-type proton ATPase, V-ATPase, is the key proton pump, that hydrolases ATP and uses this energy to pump protons across membranes. Amazingly, this proton pump and its function are conserved in eukaryotes from yeast to mammals. While V-ATPase structure and function have been studied for more than 30 years in various organisms, its regulation is not completely understood. The very recent discoveries of two new V-ATPase interacting proteins in yeast, first Oxr1 (OXidative Resistance 1), and now Rtc5 (Restriction of Telomere Capping 5), both the only two members of TLDc (The Tre2/Bub2/Cdc16 (TBC), lysin motif (LysM), domain catalytic) proteins in yeast, provide new insights in V-ATPase regulation in yeast, and because the interaction is conserved in mammals its relevance to mammalian V-ATPases regulation as well.

TLDc proteins are best known for their role in protection from oxidative stress, in particular in yeast and in the nervous system in mammals. The discovery of the novel Rtc5-V-ATPase interaction points to the role of V-ATPase not only in protection from oxidative stress but also in restriction of telomere capping in yeast and most likely higher species. The studies of other species also highlight the possible conserved role of V-ATPase in lifespan determination and Torc1 signaling, mediated through these interactions. Thus, the discovery of this new functionally important interaction between the second TLDc family member in yeast, Rtc5, and V-ATPase will shed light on the molecular mechanisms of all these essential biological processes and pathways.

In addition, because the authors performed a comprehensive proteomics protein-protein interaction study of the purified yeast vacuole it provides a valuable resource for all researchers who study vacuoles and/or related to them lysosomes.

The follow-up functional studies using the rav1Δ strain clearly demonstrated that Rtc5 and Oxr1 disassemble V-ATPase and counteract the function of V-ATPase assembly RAVE complex in vivo in yeast. Thus, they are essentially the first discovered endogenous eukaryotic protein inhibitors of V-ATPase. Moreover, because the authors obtained the evidence that Oxr1 is the regulator of the specific subunit isoform of V-ATPase Stv1p in vivo in yeast, it suggests that different TLDc proteins may regulate different specific V-ATPase subunit isoforms in cell- and tissue-specific manner in higher eukaryotes. The mechanism of this isoform-specific regulation in yeast and other species needs further investigation in the future.

Because of the conservation of the TLDc-V-ATPase interactions, all this information can be extrapolated to higher species, all the way to humans, in whom genetic mutations in various TLDc proteins are known to cause devastating diseases and syndromes.

We are thankful to the reviewer for their positive comments about the significance of our work.