This is not necessary to say in the methods. You can just start with A 125mL Erlenmeyer flask was used...

This was written as instructions, when it should be written with a passive voice.

The equation was previously stated, so you could refer back to an equation number.

There is no mention of identifying the metal rod.

The equation could have been better formatted. This would normally be in the introduction, so typically the report would refer to the equation number.

No need to explain the steps of using a balance.

This would be known to a chemist already and isn't necessary.

This is imperative (telling the reader what to do), but the report should be written telling the reader what procedure was followed during the experiment, in passive tense (not mentioning who did what).

This is 2nd person, but the report should be in 3rd person.

The legacy of redlining has created enduring inequalities that hinder economic mobility, increase vulnerability to predatory lending, and amplify the effects of climate change, particularly in marginalized communities. These systemic issues also contribute to higher rates of crime and incarceration. To help, individuals can advocate for policies that promote affordable housing, support community investment, and push for criminal justice reform. Additionally, I believe that educating oneself and others about these issues can foster greater awareness and solidarity. However, it's unfortunate that these things have to be advocated for in the first place.

This quote effectivelty emphasizes the impact that redlining had on already existing prejudices and systemic racism. The New Deal programs gave existing racist systems more legal and federal support. Giving outdated practices and beliefs reason to figuritively "redline" their clients and people who contributed to their businesses.

These negative manifestations are always controlled by trying to get rid of the byproduct and not targeting the source itself. If instead of making anti-homeless architecture and continuing to disregard climate change, we could target our resources into WHY the homelessness rates are up. If we can solve that problem, then that in itself will resolve the increase of homeless people.

Reviewer #1 (Public review):

Summary:

The present work from Velloso and collaborators investigated the transcription profiles of resident and recruited hypothalamic microglia. They found sex-dependent differences between males and females and identified the protective role of chemokine receptor CXCR3 against diet-induced obesity.

Strengths:

(1) Novelty<br /> (2) Relevance, since this work provides evidence about a subset of recruited microglia that has a protective effect against DIO. This provides a new concept in hypothalamic inflammation and obesity.

Comments on revised version:

All my comments have been addressed.

Reviewer #2 (Public review):

Summary:

This study by Mendes et al provides novel key insights in the role of chemotaxis and immune cell recruitment into the hypothalamus in the development of diet-induced obesity. Specifically, the authors first revealed that although transcriptional changes in hypothalamic resident microglia following exposure to high-fat feeding are minor, there are compelling transcriptomic differences between resident microglia and microglia recruited to the hypothalamus, and these are sexually dimorphic. Using independent loss-of-function studies, the authors also demonstrate an important role of CXCR3 and hypothalamic CXCL10 in the hypothalamic recruitment of CCR2+ positive cells on metabolism following exposure to high-fat diet-feeding in mice. This manuscript puts forth conceptually novel evidence that inhibition of chemotaxis-mediated immune cell recruitment accelerates body weight gain in high-fat diet-feeding, suggesting that a subset of microglia which express CXCR3 may confer protective, anti-obesogenic effects.

Strengths:

The work is exciting and relevant given the prevalence of obesity and the consequences of inflammation in the brain on perturbations of energy metabolism and ensuant metabolic diseases. Hypothalamic inflammation is associated with disrupted energy balance, and activated microglia within the hypothalamus resulting from excessive caloric intake and saturated fatty acids are often thought to be mediators of impairment of hypothalamic regulation of metabolism. The present work reports a novel notion in which immune cells recruited into the hypothalamus which express chemokine receptor CXCR3 may have a protective role against diet-induced obesity. In vivo studies reported herein demonstrate that inhibition of CXCR3 exacerbates high-fat diet-induced body weight gain, increases circulating triglycerides and fasting glucose levels, worsens glucose tolerance, and increases the expression of orexigenic neuropeptides, at least in female mice.

This work provides a highly interesting and needed overview of preclinical and clinical brain inflammation, which is relevant to readers with an interest in metabolism and immunometabolism in the context of obesity.

Using flow cytometry, cell sorting, and transcriptomics including RNA-sequencing, the manuscript provides novel insights on transcriptional landscapes of resident and recruited microglia in the hypothalamus. Importantly, sex differences are investigated.

Overall, the manuscript is perceived to be highly interesting, relevant, and timely. The discussion is thoughtful, well-articulated, and a pleasure to read and felt to be of interest to a broad audience.

Weaknesses:

There were no major weaknesses perceived. Some comments for potential textual additions to the results/discussion are provided below.

Could the authors comment on the choice of peripheral administration of CXCR3 antagonist as opposed to central (e.g. icv) administration? Indeed, systemic inhibition of CXCR3 produced significant alterations in body weight gain and glucose tolerance in female mice given high-fat diet and reduced CCR2 and CXCR3 immunostaining in the hypothalamus. Could changes to peripheral (e.g. WAT, liver) immune responses to the diet underlie the metabolic changes observed?

Besides hypothalamic mRNA levels of chemokines and chemokine receptors, does systemic CXCR3 antagonism affect other aspects linked to diet-induced impairments of hypothalamic regulation of energy homeostasis, like inflammation, ER stress and/or mitochondrial dynamics/function? It would be interesting to reveal the consequence of reduced CCR2+ microglial migration to the hypothalamus with chronic high-fat diet exposure.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The present work from Velloso and collaborators investigated the transcription profiles of resident and recruited hypothalamic microglia. They found sex-dependent differences between males and females and identified the protective role of chemokine receptor CXCR3 against diet-induced obesity.

Strengths:

(1) Novelty;

(2) Relevance, since this work provides evidence about a subset of recruited microglia that has a protective effect against DIO. This provides a new concept in hypothalamic inflammation and obesity.

Weaknesses:

(1) Lack of mechanistic insight into the sex-dependent effects;

(2) Analysis of indirect calorimetry data requires more depth;

(3) A deeper analysis of hypothalamic inflammation and ER stress pathways would strengthen the manuscript.

Reviewer #2 (Public Review):

Summary:

This study by Mendes et al provides novel key insights into the role of chemotaxis and immune cell recruitment into the hypothalamus in the development of diet-induced obesity. Specifically, the authors reveal that although transcriptional changes in hypothalamic resident microglia following exposure to high-fat feeding are minor, there are compelling transcriptomic differences between resident microglia and microglia recruited to the hypothalamus, and these are sexually dimorphic. Using independent loss-of-function studies, the authors also demonstrate an important role of CXCR3 and hypothalamic CXCL10 in the hypothalamic recruitment of CCR2+ positive cells on metabolism following exposure to high-fat diet-feeding in mice. This manuscript puts forth conceptually novel evidence that inhibition of chemotaxis-mediated immune cell recruitment accelerates body weight gain in high-fat diet-feeding, suggesting that a subset of microglia that express CXCR3 may confer protective, anti-obesogenic effects.

Strengths:

The work is exciting and relevant given the prevalence of obesity and the consequences of inflammation in the brain on perturbations of energy metabolism and ensuant metabolic diseases. Hypothalamic inflammation is associated with disrupted energy balance, and activated microglia within the hypothalamus resulting from excessive caloric intake and saturated fatty acids are often thought to be mediators of impairment of hypothalamic regulation of metabolism. The present work reports a novel notion in which immune cells recruited into the hypothalamus that express chemokine receptor CXCR3 may have a protective role against diet-induced obesity. In vivo studies reported herein demonstrate that inhibition of CXCR3 exacerbates high-fat diet-induced body weight gain, increases circulating triglycerides and fasting glucose levels, worsens glucose tolerance, and increases the expression of orexigenic neuropeptides, at least in female mice.

This work provides a highly interesting and needed overview of preclinical and clinical brain inflammation, which is relevant to readers with an interest in metabolism and immunometabolism in the context of obesity.

Using flow cytometry, cell sorting, and transcriptomics including RNA-sequencing, the manuscript provides novel insights into transcriptional landscapes of resident and recruited microglia in the hypothalamus. Importantly, sex differences are investigated.

Overall, the manuscript is perceived to be highly interesting, relevant, and timely. The discussion is thoughtful, well-articulated, and a pleasure to read and felt to be of interest to a broad audience.

Weaknesses:

There were no major weaknesses perceived. Some comments for potential textual additions to the results/discussion are listed in recommendations to authors.

Comments from the authors regarding the evaluation of the article: We publicly express our gratitude for the work of both Reviewers. The comments were timely and constructive and guided us toward preparing a new version of the article which contains novel data that strengthened the overall quality of the study.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Experiments with ovariectomized female mice with (and without) estrogen replacement would help to address the physiological basis of the observed sexdependent effects.

We performed an experiment with female C57BL/6J Unib, subdivided into Sham, OVX, and OVX+EST groups, which were exposed to HFD for 4 weeks. We monitored the weekly evolution of body weight and food intake. At the end of the protocol, the animals fasted for 4 hours. Then, we measured fasting blood glucose and estradiol; and extracted tissues (hypothalamus and

WAT). In the hypothalamus samples, we evaluated, by RT-qPCR, the expression of chemokines, chemokine receptors, and some pro-inflammatory cytokines and neuropeptides. We evaluated the body mass relative WAT weight. The new results are presented in Supplementary Figure 1.

Indirect calorimetric analysis of energy expenditure will benefit from ANCOVA analysis using body weight as a covariate. Moreover, locomotor activity should be also controlled.

All statistical analysis regarding energy expenditure is corrected by body mass, thus, there is no need for ANCOVA, we clarified this in the text. The determination of locomotor activity is now included in Supplementary Figures 2 and 3. 

A deeper analysis of hypothalamic inflammation and ER stress pathways would strengthen the manuscript.

We performed new experiments to determine the expression of hypothalamic inflammation and ER stress pathaways. This is shown in Suppl. Fig. 2 and 3. 

Mechanistic inhibition of CXCR3 was performed by CXCL10 immunoneutralization and CXCR3 antagonism. Those approaches are correct and well-performed, however considering the experience of the group in hypothalamic studies, I miss a virogenetic-based knockdown. Do the authors have any data on that?

This is indeed a great point. Unfortunately, we did not succeed in obtaining mice Cre lineages that would be needed for the proposed experiments. We included this as a weakness of the study. 

Reviewer #2 (Recommendations For The Authors):

There are a few typographical errors for correction:

-  Page 4, line 157: CCL10 to CXCL10.

-  Page 6, line 226: makers to markers.

-  Page 7, lines 283 and 287, Figure 6C: INF to IFN.

All errors were corrected, as recommended. 

Parts of the manuscript may be difficult for readers without knowledge of transcriptomics to interpret; thus, further description of several of the figures (e.g. Figure 3 and 4) may be helpful.

We expanded the text in Results to clarify this issue.

Could the authors comment on the choice of peripheral administration of CXCR3 antagonist as opposed to central (e.g. icv) administration? Indeed, systemic inhibition of CXCR3 produced significant alterations in body weight gain and glucose tolerance in female mice given high-fat diets and reduced CCR2 and CXCR3 immunostaining in the hypothalamus. Could changes to peripheral (e.g. WAT, liver) immune responses to the diet underlie the metabolic changes observed?

CXCR3+ cells are present in very small numbers in the hypothalamus under basal conditions. In HFD, these are recruited from the periphery to the CNS, so, we believe ICV treatment with AMG487 would not reduce recruitment to the hypothalamic parenchyma. With the same animals in which we performed the locomotor activity, we performed RT-qPCR of WAT and liver and analyzed the expression of genes involved in lipid and glucose metabolism. This is now in Supplementary Figures 2 and 3. We included a comment in the text to explain our rationale for this approach.

Besides hypothalamic mRNA levels of chemokines and chemokine receptors, does systemic CXCR3 antagonism affect other aspects linked to diet-induced impairments of hypothalamic regulation of energy homeostasis, like inflammation, ER stress and/or mitochondrial dynamics/function? It would be interesting to reveal the consequence of reduced CCR2+ microglial migration to the hypothalamus with chronic high-fat diet exposure.

We performed new experiments shown in Supplementary Figures 2 and 3 to deal with these important questions. In the hypothalamus of females there were no changes in the expression of transcripts encoding proteins involved in endoplasmic reticulum homeostasis and mitochondrial turnover, whereas in males there was a reduction of Ddit3 and Mfn1. Moreover, in females the inhibition of CXCR3 promoted no changes in the liver expression of lipidogenic and gluconeogenic genes, and no changes in the white adipose tissue expression of lipidogenic genes. In the liver of males, there was a reduction in the expression of Fasn and an increase in the expression of G6pc3. As for the females, in males, there were no changes in the white adipose tissue expression of lipidogenic genes.

Remove this section

Essence of your problem container

so they can what? Do more complicated patterns, improve skills, enjoy knitting more. Maybe remove thrive & add the 'so you can ...'

Add heading, re the problem. Switch these containers

Love the emotion, empathy, describing the ideal scenario. Title - make it about the ideal scenario, e.g. "A place to..."

Is this really the driving motivator to join the membership? Is this secondary. Is the main driver the help, tips, questions answered

This article seems to cherry-pick signs of fast progress in AI.

eLife Assessment

This study presents the cryo-EM structures of two human biotin-dependent mitochondria carboxylases involved in various biological pathways, including the metabolism of certain amino acids, cholesterol, and odd chain fatty acids. The cryo-EM structures offer a valuable addition to the structural description of biotin-dependent carboxylases and provide solid evidence to support the major conclusions of this study. This paper would be of interest to biochemists and structural biologists working on biotin-dependent carboxylases.

Reviewer #1 (Public review):

Summary:

The manuscript by Zhou et al offers new high resolution Cryo-EM structures of two human biotin-dependent enzymes: propionyl-CoA carboxylase (PCC) and methycrotonyl-CoA carboxylase (MCC). While X-ray crystal structures and Cryo-EM structures have previously been reported for bacterial and trypanosomal versions of MCC and for bacterial versions of PCC, this marks one of the first high resolution Cryo-EM structures of the human version of these enzymes. Using the biotin cofactor as an affinity tag, this team purified a group of four different human biotin-dependent carboxylases from cultured human Expi 293F (kidney) cells (PCC, MCC, acetyl-CoA carboxylase (ACC), and pyruvate carboxylase). Following further enrichment by size-exclusion chromatography, they were able to vitrify the sample and pick enough particles of MCC and PCC to separately refine the structures of both enzymes to relatively high average resolutions (the Cryo-EM structure of ACC also appears to have been determined from these same micrographs, though this is the subject of a separate publication). To determine the impact of substrate binding on the structure of these enzymes and to gain insights into substrate selectivity, they also separately incubated with propionyl-CoA and acetyl-CoA and vitrified the samples under active turnover conditions, yielding a set of cryo-EM structures for both MCC and PCC in the presence and absence of substrates and substrate analogues.

Strengths:

The manuscript has several strengths. It is clearly written, the figures are clear and the sample preparation methods appear to be well described. This study demonstrates that Cryo-EM is an ideal structural method to investigate the structure of these heterogeneous samples of large biotin-dependent enzymes. As a consequence, many new Cryo-EM structures of biotin-dependent enzymes are emerging, thanks to the natural inclusion of a built-in biotin affinity tag. While the authors report no major differences between the human and bacterial forms of these enzymes, it remains an important finding that they demonstrate how/if the structure of the human enzymes are or are not distinct from the bacterial enzymes. The MCC structures also provide evidence for a transition for BCCP-biotin from an exo-binding site to an endo-binding site in response to acetyl-CoA binding. This contributes to a growing number of biotin-dependent carboxylase structures that reveal BCCP-biotin binding at locations both inside (endo-) and outside (exo-) of the active site.

Weaknesses:

There are some minor weaknesses. Notably, there are not a lot of new insights coming from this paper. The structural comparisons between MCC and PCC have already been described in the literature and there were not a lot of significant changes (outside of the exo- to endo- transition) in the presence vs. absence of substrate analogues. There are sections of this manuscript that do not sufficiently clarify what represents a new insight from the current set of structures (there are few of them), vs. what is largely recapitulating what has been seen in previous structures.

There is not a great deal of depth of analysis in the discussion. For example, no new insights were gained with respect to the factors contributing to substrate selectivity (the factors contributing to selectivity for propionyl-CoA vs. acetyl-CoA in PCC). The authors acknowledge that they are limited in their interpretations as a consequence of the acyl groups being unresolved in all of the structures. They offer a simple, overarching and not particularly insightful explanation that the longer acyl group in propionyl-CoA may mediate stronger hydrophobic interactions that stabilize the alpha carbon of the acyl group at the proper position. The authors did not take the opportunity to describe the specific interactions that may be responsible for the stronger hydrophobic interaction nor do they offer any plausible explanation for how these might account for an astounding difference in the selectivity for propionyl-CoA vs. acetyl-CoA. Essentially, the authors concede that these cryo-EM structures offer no new insights into the structural basis for substrate selectivity in PCC, confirming that these structures do not yet fully capture the proper conformational states.

Some of these minor deficiencies aside, the overall aim of contributing new cryo-EM structures of the human MCC and PCC has been achieved. While I am not a cryo-EM expert, I see no flaws in the methodology or approach. While the contributions from these structures are somewhat incremental, it is nevertheless important to have these representative examples of the human enzymes and it is noteworthy to see a new example of the exo-binding site in a biotin-dependent enzyme.

Reviewer #2 (Public review):

Summary:

This paper reports the structures of two human biotin-dependent carboxylases. The authors used endogenously purified proteins and solved the structures in high resolutions. Based on the structures, they defined the binding site for acyl-CoA and biotin and reported the potential conformational changes in biotin position.

Strengths:

The authors effectively utilized the biotin of the two proteins and obtained homogeneous proteins from human cells. They determined the high-resolution structures of the two enzymes in apo and substrate-bound states.

Comments and questions to the manuscripts:

(1) I'm quite impressed with the protein purification and structure determination, but I think some functional characterization of the purified proteins should be included in the manuscript. The activity of enzymes should be the foundation of all structures and other speculations based on structures.

(2) In Figure 1B, the structure of MCC is shown as two layers of beta units and two layers of alpha units, while there is only one layer of alpha units resolved in the density maps. I suggest the authors show the structures resolved based on the density maps and show the complete structure with the docked layer in the supplementary figure.

(3) In the introduction, I suggest the author provide more information about the previous studies about the structure and reaction mechanisms of BDCs, what is the knowledge gap, and what problem you will resolve with a higher resolution structure. For example, you mentioned in line 52 that G437 and A438 are catalytic residues, are these residues reported as catalytic residues or this is based on your structures? Has the catalytic mechanism been reported before? Has the role of biotin in catalytic reactions revealed in previous studies?

(4) In the discussion, the authors indicate that the movement of biotin could be related to the recognition of acyl-CoA in BDCs, however, they didn't observe a change in the propionyl-CoA bound MCC structure, which is contradictory to their speculation. What could be the explanation for the exception in the MCC structure?

(5) In the discussion, the authors indicate that the selectivity of PCC to different acyl-CoA is determined by the recognition of the acyl chain. However, there are no figures or descriptions about the recognition of the acyl chain by PCC and MCC. It will be more informative if they can show more details about substrate recognition in Figures 3 and 4.

(6) How are the solved structures compared with the latest Alphafold3 prediction?

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Weaknesses:

There are some minor weaknesses.

Comment 1:Notably, there are not a lot of new insights coming from this paper. The structural comparisons between MCC and PCC have already been described in the literature and there were not a lot of significant changes (outside of the exo- to endo- transition) in the presence vs. absence of substrate analogues.

We agree that the structures of the human MCC and PCC holoenzymes are similar to their bacterial homologs. That is due to the conserved sequences and functions of MCC and PCC across different species.

Comment 2: There is not a great deal of depth of analysis in the discussion. For example, no new insights were gained with respect to the factors contributing to substrate selectivity (the factors contributing to selectivity for propionyl-CoA vs. acetyl-CoA in PCC). The authors state that the longer acyl group in propionyl-CoA may mediate stronger hydrophobic interactions that stabilize the alpha carbon of the acyl group at the proper position. This is not a particularly deep analysis and doesn't really require a cryo-EM structure to invoke. The authors did not take the opportunity to describe the specific interactions that may be responsible for the stronger hydrophobic interaction nor do they offer any plausible explanation for how these might account for an astounding difference in the selectivity for propionyl-CoA vs. acetyl-CoA. This suggests, perhaps, that these structures do not yet fully capture the proper conformational states.

We appreciate this comment. Unfortunately, in the cryo-EM maps of the PCC holoenzymes, the acyl groups were not resolved (fig. S6), so we were unable to analyze the specific interactions between the acyl-CoAs and PCC. We have revised the manuscript and acknowledged this limitation in the second paragraph of the discussion section: 

“In the cryo-EM maps of the PCC holoenzymes, the acyl groups of acetyl-CoA and propionylCoA were not resolved (fig. S6), limiting the analysis of the interactions between the acyl groups and PCC. Nevertheless, the PCC-PCO and PCC-ACO structures determined in our study demonstrate that the conformations of the acyl-CoA binding pockets in the two structures are almost identical (Fig. 3F, fig. S7, B and C). In addition, the well resolved CoA groups of propionyl-CoA and acetyl-CoA bind at the same position in human PCC holoenzyme (Fig. 3F). These findings indicate that propionyl-CoA and acetyl-CoA bind to PCC with a similar binding mode.”

Comment 3: The authors also need to be careful with their over-interpretation of structure to invoke mechanisms of conformational change. A snapshot of the starting state (apo) and final state (ligand-bound) is insufficient to conclude *how* the enzyme transitioned between conformational states. I am constantly frustrated by structural reports in the biotin-dependent enzymes that invoke "induced conformational changes" with absolutely no experimental evidence to support such statements. Conformational changes that accompany ligand binding may occur through an induced conformational change or through conformational selection and structural snapshots of the starting point and the end point cannot offer any valid insight into which of these mechanisms is at play.

Point accepted. We have revised our manuscript to use conformational differences instead of conformational changes to describe the differences between the apo and ligand-bound states (see the last paragraph of the introduction section and the third paragraph of the discussion section).

Reviewer #2 (Public Review):

Comments and questions to the manuscripts:

Comment 1: I'm quite impressed with the protein purification and structure determination, but I think some functional characterization of the purified proteins should be included in the manuscript. The activity of enzymes should be the foundation of all structures and other speculations based on structures.

We appreciate this comment. However, since we purified the endogenous BDCs and the sample we obtained was a mixture of four BDCs, the enzymatic activity of this mixture cannot accurately reflect the catalytic activity of PCC or MCC holoenzyme. We have revised the manuscript and acknowledged this limitation in the first paragraph of the results section: 

“We did not characterize the enzyme activities of the mixed BDCs because the current methods used to evaluate the carboxylase activities of BDCs, such as measuring the ATP hydrolysis or incorporation of radio-labeled CO2, are unable to differentiate the specific carboxylase activity of each BDC.”

Comment 2: In Figure 1B, the structure of MCC is shown as two layers of beta units and two layers of alpha units, while there is only one layer of alpha units resolved in the density maps. I suggest the authors show the structures resolved based on the density maps and show the complete structure with the docked layer in the supplementary figure.

We appreciate this comment. We have shown the cryo-EM maps of the PCC and MCC holoenzymes in fig. S8 to indicate the unresolved regions in these structures. The BC domains in one layer of MCCα in the MCC-apo structure were not resolved. However, we think it would be better to show a complete structure in Fig. 1 to provide an overall view of the MCC holoenzyme. We have revised Fig. 1B and the figure legend to clearly point out which domains were not resolved in the cryo-EM map and were built in the structure through docking. We have also revised the main text to clearly describe which parts of the holoenzymes were not resolved in the cryo-EM maps and how the complete structures were built.

Comment 3: In the introduction, I suggest the author provide more information about the previous studies about the structure and reaction mechanisms of BDCs, what is the knowledge gap, and what problem you will resolve with a higher resolution structure. For example, you mentioned in line 52 that G437 and A438 are catalytic residues, are these residues reported as catalytic residues or this is based on your structures? Has the catalytic mechanism been reported before? Has the role of biotin in catalytic reactions revealed in previous studies?

Point accepted. It was reported that G419 and A420 in Streptomyces coelicolor PCC, corresponding to G437 and A438 in human PCCβ, were the catalytic residues for the secondstep carboxylation reaction (PMID: 15518551). The same study also reported the catalytic mechanism of the carboxyl transfer reaction. The role of biotin in the BDC-catalyzed carboxylation reactions has been extensively studied (PMIDs: 22869039, 28683917). We have revised the manuscript to introduce the catalytic mechanisms of BDCs elucidated through the investigation of prokaryotic BDCs in the fourth paragraph of the introduction section. 

Comment 4: In the discussion, the authors indicate that the movement of biotin could be related to the recognition of acyl-CoA in BDCs, however, they didn't observe a change in the propionyl-CoA bound MCC structure, which is contradictory to their speculation. What could be the explanation for the exception in the MCC structure?

We appreciate this comment. We do not have a good explanation for why we did not observe a change in the propionyl-CoA bound MCC structure. It is noteworthy that neither acetyl-CoA nor propionyl-CoA is the natural substrate of MCC. Recently, a cryo-EM structure of the human MCC holoenzyme in complex with its natural substrate, 3-methylcrotonyl-CoA, has been resolved (PDB code: 8J4Z). In this structure, the binding site of biotin and the conformation of the CT domain closely resemble that in our acetyl-CoA-bound MCC structure. Therefore, the movement of biotin induced by acetyl-CoA binding mimics that induced by the binding of MCC's natural substrate, 3-methylcrotonyl-CoA, indicating that in comparison with propionylCoA, acetyl-CoA is closer to 3-methylcrotonyl-CoA regarding its ability to bind to MCC. We have discussed this possibility in the last paragraph of the discussion section. We have also added a supplementary figure (fig. S11) to compare the structures of human MCC holoenzyme in complex with acetyl-CoA and 3-methylcrotonyl-CoA.

Comment 5: In the discussion, the authors indicate that the selectivity of PCC to different acyl-CoA is determined by the recognition of the acyl chain. However, there are no figures or descriptions about the recognition of the acyl chain by PCC and MCC. It will be more informative if they can show more details about substrate recognition in Figures 3 and 4.

We appreciate this comment. Unfortunately, in the cryo-EM maps of the PCC holoenzymes, the acyl groups were not resolved (fig. S6), so we were unable to analyze the specific interactions between the acyl-CoAs and PCC. We have revised the manuscript and acknowledged this limitation in the second paragraph of the discussion section: 

“In the cryo-EM maps of the PCC holoenzymes, the acyl groups of acetyl-CoA and propionylCoA were not resolved (fig. S6), limiting the analysis of the interactions between the acyl groups and PCC. Nevertheless, the PCC-PCO and PCC-ACO structures determined in our study demonstrate that the conformations of the acyl-CoA binding pockets in the two structures are almost identical (Fig. 3F, fig. S7, B and C). In addition, the well resolved CoA groups of propionyl-CoA and acetyl-CoA bind at the same position in human PCC holoenzyme (Fig. 3F). These findings indicate that propionyl-CoA and acetyl-CoA bind to PCC with a similar binding mode.”

Comment 6: How are the solved structures compared with the latest Alphafold3 prediction?

Since AlphaFold3 was not released when our manuscript was submitted, we did not compare the solved structures with the AlphaFold3 predictions. We have now carried out the predictions using Alphafold3. Due to the token limitation of the AlphaFold3 server, we can only include two α and six β subunits of human PCC or MCC in the prediction. The overall assembly patterns of the Alphafold3-predicted structures are similar to that of the cryo-EM structures. The RMSDs between PCCα, PCCβ, MCCα, and MCCβ in the apo cryo-EM structures and those in the AlphaFold3-predicted structures are 7.490 Å, 0.857 Å, 7.869 Å, and 1.845 Å, respectively. The PCCα and MCCα subunits adopt an open conformation in the cryo-EM structures but adopt a closed conformation in the AlphaFold-3 predicted structures, resulting in large RMSDs.

Fortunato is pretty impulsive. He hears wine, he's in. He stops participating in the carnival he's dressed for, he the narrator kinda tries to stop him from leaving, and he isn't even turned away by how cold it will be.

Mans dressed like a jester

luck. They got those 1k injuries by chance?

I actually did further research and I believe it's just the characters name

the act of killing yourself or someone else, or of destroying something, usually by burning. Oh lord.

to set right. Does this mean the person/thing who sets it right?

Author response:

The following is the authors’ response to the original reviews.

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

DMS-MaP is a sequencing-based method for assessing RNA folding by detecting methyl adducts on unpaired A and C residues created by treatment with dimethylsulfate (DMS). DMS also creates methyl adducts on the N7 position of G, which could be sensitive to tertiary interactions with that atom, but N7-methyl adducts cannot be detected directly by sequencing. In this work, the authors adopt a previously developed method for converting N7-methyl-G to an abasic site to make it detectable by sequencing and then show that the ability of DMS to form an N7-methyl-G adduct is sensitive to RNA structural context. In particular, they look at the G-quadruplex structure motif, which is dense with N7-G interactions, is biologically important, and lacks conclusive methods for in-cell structural analysis. 

Strengths: 

- The authors clearly show that established methods for detecting N7-methyl-G adducts can be used to detect those adducts from DMS and that the formation of those adducts is sensitive to structural context, particularly G-quadruplexes. 

- The authors assess the N7-methyl-G signal through a wide range of useful probing analyses, including standard folding, adduct correlations, mutate-and-map, and single-read clustering. 

- The authors show encouraging preliminary results toward the detection of G-quadruplexes in cells using their method. Reliable detection of RNA G-quadruplexes in cells is a major limitation for the field and this result could lead to a significant advance. 

- Overall, the work shows convincingly that N7-methyl-G adducts from DMS provide valuable structural information and that established data analyses can be adapted to incorporate the information. 

We thank the reviewer for their time and appreciate the reviewer for their positive assessment as well as for their suggestions which we have addressed below.

Weaknesses: 

- Most of the validation work is done on the spinach aptamer and it is the only RNA tested that has a known 3D structure. Although it is a useful model for validating this method, it does not provide a comprehensive view of what results to expect across varied RNA structures. 

Thank you for your insightful comments. We agree that a more comprehensive view of BASH MaP involves probing a larger variety of RNAs with known 3D-structures beyond Spinach and the poly-UG RNA. Although outside the scope of this publication, more work is needed to reveal the determinants of N7G reactivity to DMS.

- It's not clear from this work what the predictive power of BASH-MaP would be when trying to identify G-quadruplexes in RNA sequences of unknown structure. Although clusters of G's with low reactivity and correlated mutations seem to be a strong signal for G-quadruplexes, no effort was made to test a range of G-rich sequences that are known to form G-quadruplexes or not. Having this information would be critical for assessing the ability of BASH-MaP to identify G-quadruplexes in cells. 

- Although the authors present interesting results from various types of analysis, they do not appear to have developed a mature analysis pipeline for the community to use. I would be inclined to develop my own pipeline if I were to use this method. 

Thank you for your suggestion. We have more clearly annotated the python scripts and GitHub repository which contain all custom scripts used for analyzing BASH MaP data. These changes will enable researchers to more easily utilize our developed pipelines.

- There are various aspects of the DAGGER analysis that don't make sense to me: <br /> (1) Folding of the RNA based on individual reads does not represent single-molecule folding since each read contains only a small fraction of the possible adducts that could have formed on that molecule. As a result, each fold will largely be driven by the naive folding algorithm. I recommend a method like DREEM that clusters reads into profiles representing different conformations. 

(2) How reliable is it to force open clusters of low-reactivity G's across RNA's that don't already have known G-quadruplexes? 

(3) By forcing a G-quadruplex open it will be treated as a loop by the folding algorithm, so the energetics won't be accurate. 

(4) It's not clear how signals on "normal" G's are treated. In Figure 5C some are wiped to 0 but others are kept as 1. 

Thank you for your keen observations regarding the conceptual frameworks utilized in DAGGER. We have included a complimentary analysis to DAGGER utilizing Spinach BASH MaP data with DANCE, an algorithm which shares an underlying architecture with DREEM, and found that DANCE analysis gave similar results to those found with DAGGER. However, we have not benchmarked DAGGER’s performance on a range of RNAs and compared the results with expectation-maximization algorithms like DREEM and DANCE.

To minimize the effects of artificially creating loops with tertiary folding constraints, we utilized the RNA folding algorithm CONTRAfold which relies less on direct energetic calculations than other commonly used RNA folding algorithms such as RNAstructure.

We have updated the main text to more clearly indicate how DAGGER handles signals at G’s in a range of conditions. The main text now better clarifies the specific logic used for determining which G’s contain either a 0 or a 1 in the bitvector encoding used in DAGGER analysis.

Reviewer #2 (Public Review): 

Summary: 

The manuscript introduces BASH MaP and DAGGER, innovative tools for analyzing RNA tertiary structures, specifically focusing on the G-quadruplexes. Traditional methods have struggled to detect and analyze these structures due to their reliance on interactions on the Hoogsteen face of guanine, which are not readily observable through conventional probing that targets Watson-Crick interactions. BASH MaP employs dimethyl sulfate and potassium borohydride to enhance the detection of N7-methylguanosine by converting it into an abasic site, thereby enabling its identification through misincorporation during reverse transcription. This method provides higher precision in identifying G-quadruplexes and offers deeper insights into RNA's structural dynamics and alternative conformations in both vitro and cellular contexts. Overall, the study is well-executed, demonstrating robust signal detection of N7-Gs with some compelling positive controls, thorough analysis, and beautifully presented figures. 

Strengths: 

The manuscript introduces a new method to detect G-quadruplexes (G-qs) that simplifies and potentially enhances the robustness and quantification compared to previous methods relying on reverse transcription truncations. The authors provide a strong positive control, demonstrating a 70% misincorporation at endogenous N7-G within the 18S rRNA, which illustrates BASH MaP's high signal-to-noise ratio. The data concerning the detection of positive control G-qs is particularly compelling. 

Weaknesses: 

Figure 3E shows considerable variability in the correlations among guanosines, suggesting that the methods may struggle with specificity in determining guanosine participation within and between different quadruplexes. There is no estimation of the methods false positive discovery rate.

Thank you for your positive assessment and for your time to come up with suggestions to improve this publication. We have addressed your specific comments in the “Recommendations For The Authors” section below.

Reviewer #3 (Public Review): 

Summary: 

In this study, the authors aim to develop an experimental/computational pipeline to assess the modification status of an RNA following treatment with dimethylsulfate (DMS). Building upon the more common DMS Map method, which predominantly assesses the modification status of the Watson-Crick-Franklin face of A's and C's, the authors insert a chemical processing step in the workflow prior to deep sequencing that enables detection of methylation at the N7 position of guanosine residues. This approach, termed BASH MaP, provides a more complete assessment of the true modification status of an RNA following DMS treatment and this new information provides a powerful set of constraints for assessing the secondary structure and conformational state of an RNA. In developing this work, the authors use Spinach as a model RNA. Spinach is a fluorogenic RNA that binds and activates the fluorescence of a small molecule ligand. Crystal structures of this RNA with ligand bound show that it contains a G-quadruplex motif. In applying BASH MaP to Spinach, the authors also perform the more standard DMS MaP for comparison. They show that the BASH MaP workflow appears to retain the information yielded by DMS MaP while providing new information about guanosine modifications. In Spinach, the G-quadruplex G's have the least reactive N7 positions, consistent with the engagement of N7 in hydrogen bonding interactions at G's involved in quadruplex formation. Moreover, because the inclusion of data corresponding to G increases the number of misincorporations per transcript, BASH MaP is more amenable to analysis of co-occurring misincorporations through statistical analysis, especially in combination with site-specific mutations. These co-occurring misincorporations provide information regarding what nucleotides are structurally coupled within an RNA conformation. By deploying a likelihood-ratio statistical test on BASH MaP data, the authors can identify Gs in G-quadruplexes, deconvolute G-G correlation networks, base-triple interactions and even stacking interactions. Further, the authors develop a pipeline to use the BASH MaP-derived G-modification data to assist in the prediction of RNA secondary structure and identify alternative conformations adopted by a particular RNA. This seems to help with the prediction of secondary structure for Spinach RNA. 

Strengths: 

The BASH Map procedure and downstream data analysis pipeline more fully identify the complement of methylations to be identified from the DMS treatment of RNA, thereby enriching the information content. This in turn allows for more robust computational/statistical analysis, which likely will lead to more accurate structure predictions. This seems to be the case for the Spinach RNA. 

Weaknesses: 

The authors demonstrate that their method can detect G-quadruplexes in Spinach and some other RNAs both in vitro and in cells. However, the performance of BASH MaP and associated computational analysis in the context of other RNAs remains to be determined. 

We thank the reviewer for their time spent analyzing this manuscript, for their positive assessment and for their suggestions on improving this publication. We have addressed your specific comments in the “Recommendations For The Authors” section below.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors): 

Although the text is clear and coherent, the overall flow of the manuscript comes across as "here's a bunch of stuff I tried." Maybe you're looking to get this out quickly, but it would have been much more impactful (and enjoyable to read) a description of a more polished final product. 

Thank you for your highlighting the strengths and weaknesses of this manuscript. We have changed parts of the main text to enhance the overall flow of the manuscript and increase reader enjoyability.

Reviewer #2 (Recommendations For The Authors): 

I have only a few comments: 

Major: 

(1) Analysis of Guanosine Correlations in Figure 3E: In Figure 3E, there is a lot of variability in the correlations among guanosines. For example, G46 shows a strong correlation with G93 (within the same quadruplex) but also correlates with G91, G95 (in different quadruplexes), and G97 (not part of any quadruplex as per the model in Figure 3C). Contrarily, G86 exhibits weak correlations, and G50 along with G89 shows no significant correlations. These findings imply that BASH MaP followed by RING MaP analysis struggles to accurately distinguish between guanosines within the same or different quadruplexes in Spinach. Perhaps there are some opportunities to enhance the specificity in determining guanosine participation within quadruples, a great point for the authors to discuss. 

Thank you for your comments and careful analysis of the pattern of correlations produced by BASH MaP. We agree that BASH MaP followed by RING MaP analysis is unable to unambiguously distinguish between guanosines within the same or different quadruplex layers. This finding was a surprise as we initially assumed that quadruplex layers would behave in a manner like Watson-Crick base pairs and produce specific signals in the corresponding RING MaP heatmaps.  We suspect that this may be due to mutations in specific G’s being associated with altered conformations which allow other G’s to form different interactions that affect DMS reactivity.  This may be unique to the highly complex structure in Spinach.  However, we think BASH-MaP clearly provides signals that point to key residues within the G-quadruplex, even if it does not clearly identify all of them.

This idea is supported by experiments described in Figure 4, which show that mutation of a single guanosine residue causes a complete breakdown of the hydrogen-bonding network throughout all quadruplex layers. Additionally, DMS methylation of an N7G in a quadruplex is likely to disrupt base stacking interactions in and around the quadruplex. The compounding effects of a dynamic G-quadruplex and DMS-induced changes to local base stacking properties explains both the strong correlations with G97, which is base-stacked with the quadruplex, and the inability to specifically identify the guanosines which comprise specific quadruplex quartets. We have further emphasized this point in an updated discussion section.

(2) Potential Consolidation of Figures 3 and 4: Figure 4 appears quite similar to Figure 3 but employs M2-seq instead of relying on spontaneous mutations. It might be beneficial to merge these figures to demonstrate that M2-seq can more effectively identify correlations between guanosines in quadruplexes. 

We agree that Figures 3 and 4 appear quite similar but there is an important distinction to be made between RING MaP and M2-seq analysis. We suspect that the mechanism causing correlations between guanosines in quadruplexes for RING MaP as “RNA breathing” in contrast to the spontaneous T7 RNA polymerase-induced mutation model proposed in Cheng et al. PNAS 2017, https://doi.org/10.1073/pnas.1619897114. To determine whether correlations between guanosines in Spinach BASH MaP experiments rely on spontaneous mutations, we compared the fraction of reads containing misincorporations at pairs of quadruplex guanosines over a range of DMS concentrations.  The spontaneous mutation model predicts a linear dependence between quadruplex guanosine signals and DMS dose while an “RNA breathing” or double-DMS hit model predicts a quadratic dependence on DMS dose (Cheng et al. PNAS 2017, https://doi.org/10.1073/pnas.1619897114). Our data may support a quadratic dependence on DMS dose for multiple pairs of G-quadruplex guanosines, while they demonstrate a linear dependence between helical G’s (Supplementary Data Fig. 9). Together, these data suggest that BASH MaP followed by RING MaP analysis detects double-DMS modification events for pairs of quadruplex guanosines. Therefore, BASH MaP and RING MaP analysis provide a complimentary approach to M2 BASH MaP and reveal guanosine correlations in contexts where pre-installed mutations are incompatible such as the study of endogenously expressed RNAs.

(3) Estimation of False Positive Rates: An estimation of the false positive rate for G-quadruplex identification would be invaluable. Since identification currently depends on the absence of DMS modification, it's important to consider how other factors like solvent inaccessibility or library generation might affect the detection and be misinterpreted as G-quadruplexes. Although this could be a subject of future work, some discussion by the authors would enhance the manuscript. 

We have added a table summarizing sensitivity, positive predictive value, and false positive rate for different G-quadruplex identification schemes.  See Supplementary Table 1.

Minor: 

(4) Line 273 Reference Correction: Please adjust the reference in line 273 to accurately reflect that the G-quadruplex experiments compare potassium with lithium, not sodium. 

In cellulo G-quadruplex reverse transcriptase (RT) stop assays as described by Guo and Bartel (https://www.science.org/doi/10.1126/science.aaf537) compared RT stops between DMS treated mRNA refolded in potassium and sodium buffers. We have clarified in the text that traditionally, G-quadruplex RT stop assays compare potassium with lithium.

(5) Consistency in Figure 1 (Panels F and G): Aligning BASH MaP (170 mM DMS) as the y-axis in both panels F and G would visually align the data points and enhance the graphical coherence across these panels. 

Thank you for noticing the subtleties in our data presentation and for the suggestion on how to improve our graphical coherence across panels. We specifically choose not to align BASH MaP (170 mM DMS) as the y-axis for panels F and G because we did not want the reader to mistakenly assume that the data for BASH MaP (170 mM DMS) presented in panels F and G is the same data. In panel F, BASH MaP was performed under standard DMS probing buffer conditions which utilized a pH 7.5 bicine buffer. The purpose of panel F is to show the reproducibility of BASH MaP under various DMS concentrations. In panel G, BASH MaP was performed under DMS probing buffer conditions which promote the formation of m3U using a pH 8.3 bicine buffer. The purpose of panel G is to show that the borohydride treatment and depurination steps in BASH MaP do not react with DMS-derived m1A, m3C, and m3U in a manner which prevents their measurement through cDNA misincorporation. Together, these experimental differences cause the data points for BASH MaP (170 mM DMS) to vary between panels F and G which would lead to more confusion for the reader and detract from the intended message we are trying to convey through panels F and G. 

(6) Statistical Detail in Figure 1E: Incorporating a confidence interval or a P-value in Figure 1E would enrich the statistical depth and provide readers with a clearer understanding of the data's significance. 

Thank you for the suggestion of including a p-value in Figure 1E to provide the readers with a clearer understanding of the data’s significance. The effect of combining DMS treatment and borohydride reduction on the misincorporation rate of G’s in Spinach is so dramatic that the raw data sufficiently provides the readers a clear understanding of its significance.

(7) Reevaluation of Figure 2B: Considering the small number of Gs in single-stranded regions and base triples, it might be more informative to move Figure 2B to supplementary information. Focusing on Figure 2C, which consolidates non-quadruplex categories, could provide more impactful insights. 

Thank you for your suggestion. It is important to initially provide an overall characterization of N7G DMS reactivity for G’s in a variety of structural contexts before more specifically looking at G-quadruplexes. Panel B is an important part of figure 2 for the following two reasons:

First, a reader’s first question upon seeing the N7G chemical reactivity for Spinach as showed in Figure 2A is likely to ask whether base-paired G’s and single-stranded G’s have similar or different DMS reactivities. Figure 2, panel B shows that generally, single-stranded G’s appear to have higher DMS reactivity than base-paired G’s except for 2 G’s which display hyper-reactivity. The basis for this hyper-reactivity is addressed in Figure 4.

Second, panel B highlights the wide range in N7G DMS reactivities. Since the G-quadruplex G’s display a dramatically lower DMS reactivity as compared to single-stranded G’s and hyper-reactive base-paired G’s, the dynamic range of DMS reactivities was difficult to capture in a single panel. Panel C does not convey these dynamics appropriately as a stand-alone figure.

(8) Enhancements to Figure 2G: Improving the visibility of mutation rates in this figure would help. Suggestions include coloring bars by nucleotide type for intuitive visual comparison and adjusting the y-axis to a logarithmic scale to better represent near-zero mutation rates. Additionally, employing histograms or box plots could directly compare DMS reactivities and provide a clearer analysis. 

Thank you for your suggestions on enhancing the presentation of BASH MaP applied to an mRNA. The main purpose of figure 2G was to validate whether BASH MaP could detect G’s engaged in a G-quadruplex in a cell. In-cell G-quadruplex folding measurements as performed by Guo and Bartel (https://www.science.org/doi/10.1126/science.aaf537) only identified a few G-quadruplexes which were folded and only the 3’ end of the G-quadruplex was detected. We therefore reasoned that the 3’ most G’s of these select set of G-quadruplexes were the only validated G’s engaged in a G-quadruplex in cells. In the instance of the AKT2 mRNA, Guo and Bartel found that 4 G’s appeared to be folded in a G-quadruplex in cells (Supplementary figure 2E). These G’s are indicated at the bottom of the plot with black bars and the label “In-cell G-quadruplex guanosines”. Therefore, we hypothesized that these G’s would display low DMS reactivity with BASH MaP while other G’s in the AKT2 mRNA would display higher chemical reactivities. We followed a standard convention in displaying chemical reactivities used extensively in the field where black bars indicate low reactivity, yellow bars indicate moderate reactivity, and red bars indicate high reactivity. The data in Fig 2G directly supports Guo and Bartel’s prediction of an in-cell folded G-quadruplex in the AKT2 mRNA because the 4 G’s predicted to be engaged in a G-quadruplex all displayed near zero DMS reactivities.

We agree that adjusting the y-axis to a logarithmic scale would better represent near-zero mutations rates. However, the purpose of figure 2G is not to compare all positions with near-zero mutation rates. Instead, our use of standard conventions in displaying chemical reactivities is sufficient for the purpose of displaying BASH MaP’s ability to validate in-cell G-quadruplex G’s.

Later in the paper, we go a step further and create a better criterion than simple N7G DMS reactivity for identifying G’s engaged in a G-quadruplex. For further analysis of G’s with near zero DMS reactivities, see Figure 3 and Supplementary figure 4 which utilizes RING Mapper to identify lowly-reactive G’s which produce co-occurring misincorporations.

(9) Scale Consistency in Figure 3: Ensuring that the correlation scales are uniform across Panels A, B, D, and E would facilitate easier comparison of the data, enhancing the overall coherence of the findings. Using raw correlation values could also improve clarity and interpretation. 

Thank you for the suggestions to facilitate easier comparisons of data in Figure 3. We have ensured the correlation scales are uniform across panels A, B, D, and E to enhance the coherence of these findings. We initially visualized the data in Figure 3 by plotting raw correlation values, but we found these values differed between DMS MaP and BASH MaP datasets, likely because of the low-level background mutations introduced by the borohydride reduction step of BASH (see Supplementary figure 3A). However, performing a global normalization of correlation strength values computed by RING mapper enabled clear comparisons between DMS MaP and BASH MaP RING heatmaps and revealed structural domains consistent with the crystal structure of Spinach.

(10) Correction on Line 506: Please update the reference to M2 BASH MaP for accuracy. 

Thank you. We have updated the main text to incorporate this comment.

Reviewer #3 (Recommendations For The Authors): 

The paper describes multiple applications and multiple methods of analysis of the BASH Map data, which collectively make the manuscript more difficult to follow. The manuscript would become more readable and user-friendly if there were some overview figures to describe the sequencing pipeline and the various computational workflows that the BASH MaP data are fed into (e.g. RING Mapper, DAGGER, M2 BASH MaP, Co-occurring Misincorporations, Secondary Structure Prediction). One or more summary schemes that provide an overview would strongly assist with the clarity and overall content of the paper. 

Thank you for your suggestions. We have incorporated a summary scheme of the various computational workflows and their use cases in Fig 7.

Line 165. Here, misincorporation rates for all four nucleotides are discussed, but m3U is not mentioned until from the following paragraph. It would be appropriate and clearer to mention this sooner. 

Thank you for your suggestion. We have restructured this section to introduce the DMS modification m3U in an earlier paragraph to increase clarity for readers.

Line 506: spelling of DAGGER. 

Thank you. We have updated the main text to incorporate this comment.

Line 645: I found this paragraph difficult to follow, especially the line starting 649. I thought the logic was to exclude G's involved in tertiary interactions from base-paring in the secondary structure prediction. Some clarification would be helpful. 

Thank you for your comments. We have restructured the paragraph to emphasize that DAGGER only applies tertiary folding constraints to sequencing reads without misincorporations at G’s engaged in tertiary interactions. We reasoned that sequencing reads with a misincorporation at a G engaged in a tertiary interaction likely come from an RNA molecule which is in an alternative tertiary conformational state. In this specific circumstance, a tertiary folding constraint may impose incorrect restrictions on the folding of RNA molecules due to distinct tertiary conformations.

Line 817. "Ability to". 

Thank you. We have updated the main text to incorporate this comment.

Figure 6F. Mistake in the axis description. 

Thank you. We have updated the main text to incorporate this comment.

Consider combining the paragraphs at lines 850 and 903. 

Thank you for the suggestion. We rearranged paragraphs in the discussion to improve clarity.

Line 1546. The final conc of DMS would be nice to see here.

Thank you. We have updated the main text to incorporate this comment.

eLife Assessment

This important work substantially advances our understanding of RNA structure analysis by introducing an innovative method that extends DMS probing to include guanosine residues, thereby enhancing our ability to detect complex tertiary interactions. The evidence supporting the conclusions is compelling, with detailed analyses demonstrating the method's capacity to differentiate structural contexts and improve RNA structure predictions. This work will be of broad interest to RNA structural biology, biochemistry, and biophysics researchers.

Reviewer #1 (Public review):

Summary:

DMS-MaP is a sequencing-based method for assessing RNA folding by detecting methyl adducts on unpaired A and C residues created by treatment with dimethylsulfate (DMS). DMS also creates methyl adducts on the N7 position of G, which could be sensitive to tertiary interactions with that atom, but N7-methyl adducts cannot be detected directly by sequencing. In this work, the authors adopt a previously developed method for converting N7-methyl-G to an abasic site to make it detectable by sequencing and then show that the ability of DMS to form an N7-methyl-G adduct is sensitive to RNA structural context. In particular, they look at the G-quadruplex structure motif, which is dense with N7-G interactions, is biologically important, and lacks conclusive methods for in-cell structural analysis.

Strengths:

- The authors clearly show that established methods for detecting N7-methyl-G adducts can be used to detect those adducts from DMS and that the formation of those adducts is sensitive to structural context, particularly G-quadruplexes.

- The authors assess the N7-methyl-G signal through a wide range of useful probing analyses, including standard folding, adduct correlations, mutate-and-map, and single-read clustering.

- The authors show encouraging preliminary results toward the detection of G-quadruplexes in cells using their method. Reliable detection of RNA G-quadruplexes in cells is a major limitation for the field and this result could lead to a significant advance.

- Overall, the work shows convincingly that N7-methyl-G adducts from DMS provide valuable structural information and that established data analyses can be adapted to incorporate the information.

Weaknesses:

- Most of the validation work is done on the spinach aptamer and it and polyUG RNA are the only RNAs tested that have a known 3D structure. Although it is a useful model for validating this method, it does not provide a comprehensive view of what results to expect across varied RNA structures.

- It's not clear from this work what the predictive power of BASH-MaP would be when trying to identify G-quadruplexes in RNA sequences of unknown structure. Although clusters of G's with low reactivity and correlated mutations seem to be a strong signal for G-quadruplexes, no effort was made to test a range of G-rich sequences that are known to form G-quadruplexes or not. Having this information would be critical for assessing the ability of BASH-MaP to identify G-quadruplexes in cells.

- Although the authors present interesting results from various types of analysis, the code currently available on Github lacks the documentation and examples necessary to be useful to the broader community.

- There are aspects of the DAGGER analysis that could limit its robustness or utility for different RNAs:

(1) Folding of the RNA based on individual reads does not represent single-molecule folding since each read contains only a small fraction of the possible adducts that could have formed on that molecule. As a result, each fold will largely be driven by the naive folding algorithm. The DANCE-MaP algorithm that was also used by the authors addresses this concern.<br /> (2) G residues in a loop will have a different impact on RNA folding than those in a G-quadruplex. This difference could reduce the accuracy of CONTRAfold predictions when forcing G-quadruplex residues to be unpaired. That said, predicting secondary structure around G-quadruplexes is a challenge for folding algorithms.<br /> (3) Incorporation of the G mutations requires prior knowledge of the RNA 3D structure, limiting the utility of the method to predicting alternative conformations in structures that are already well characterized.

Reviewer #3 (Public review):

Summary:

In this study the authors aim to develop an experimental/computational pipeline to assess the modification status of an RNA following treatment with dimethylsulfate (DMS). Building upon the more common DMS Map method, which predominantly assesses the modification status of the Watson-Crick-Franklin face of A's and C's, the authors insert a chemical processing step in the workflow prior to deep sequencing that enables detection of methylation at the N7 position of guanosine residues. This approach, termed BASH MaP, provides a more complete assessment of the true modification status of an RNA following DMS treatment, and this new information provides a powerful set of constraints for assessing the secondary structure and conformational state of an RNA. In developing this work, the authors use Spinach as a model RNA. Spinach is a fluorogenic RNA that binds and activates the fluorescence of a small molecule ligand. Crystal structures of this RNA with ligand bound show that it contains a G-quadruplex motif. In applying BASH MaP to Spinach, the authors also perform the more standard DMS MaP for comparison. They show that the BASH MaP workflow appears to retain the information yielded by DMS MaP while providing new information about guanosine modifications. In Spinach, the G-quadruplex G's have the least reactive N7 positions, consistent with the engagement of N7 in hydrogen bonding interactions at G's involved in quadruplex formation. Moreover, because the inclusion of data corresponding to G increases the number of misincorporations per transcript, BASH MaP is more amenable to analysis of co-occurring misincorporations through statistical analysis, especially in combination with site-specific mutations. These co-occurring misincorporations provide information regarding what nucleotides are structurally coupled within an RNA conformation. By deploying a likelihood-ratio statistical test on BASH MaP data, the authors can identify Gs in G-quadruplexes, deconvolute G-G correlation networks, base-triple interactions and even stacking interactions. Further, the authors develop a pipeline to use the BASH MaP-derived G-modification data to assist in the prediction of RNA secondary structure and identify alternative conformations adopted by a particular RNA. This seems to help with the prediction of secondary structure for Spinach RNA.

Strengths:

The BASH Map procedure and downstream data analysis pipeline more fully identifies the complement of methylations to be identified from DMS treatment of RNA, thereby enriching the information content. This in turn allows for more robust computational/statistical analysis, which likely will lead to more accurate structure predictions. This seems to be the case for the Spinach RNA.

Weaknesses:

The authors demonstrate that their method can detect G-quadruplexes in Spinach and some other RNAs both in vitro and in cells. While application to other RNAs is beyond the scope of the current manuscript, the performance of BASH MaP and associated computational analysis in the context of other RNAs remains to be determined.

the commercialisation of hip hop, using hip hop aesthetics; non-hip hop artists adopting elements of the genre; mainstream media reducing hip hop to harmful stereotypes.

This is an approach that, as the outline notes must all be written, is constructive in the sense of Grothendieck's problem solving is. Rather than solve the problem (pump out the work) this strategy advances the understanding in a way that new writings of the same topic can be undirected.

eLife Assessment

This study by Graca et al. explores ethanol metabolism pathways in mycobacteria. The enzyme, MftG, a flavoprotein dehydrogenase, is shown to act as an electron shuttle between an uncommon redox cofactor and the electron transport chain thereby regenerating mycofactocin. Whilst this study was conducted in Mycobacterium smegmatis, the findings are important and have general implications for elucidating broader mycobacterial metabolism. Overall, the data presented are convincing supported by well-designed experiments.

Reviewer #1 (Public review):

Using a knock-out mutant strain, the authors tried to decipher the role of the last gene in the mycofactocin operon, mftG. They found that MftG was essential for growth in the presence of ethanol as the sole carbon source, but not for the metabolism of ethanol, evidenced by the equal production of acetaldehyde in the mutant and wild type strains when grown with ethanol (Fig 3). The phenotypic characterization of ΔmftG cells revealed a growth-arrest phenotype in ethanol, reminiscent of starvation conditions (Fig 4). Investigation of cofactor metabolism revealed that MftG was not required to maintain redox balance via NADH/NAD+, but was important for energy production (ATP) in ethanol. Since mycobacteria cannot grow via substrate-level phosphorylation alone, this pointed to a role of MftG in respiration during ethanol metabolism. The accumulation of reduced mycofactocin points to impaired cofactor cycling in the absence of MftG, which would impact the availability of reducing equivalents to feed into the electron transport chain for respiration (Fig 5). This was confirmed when looking at oxygen consumption in membrane preparations from the mutant and would type strains with reduced mycofactocin electron donors (Fig 7). The transcriptional analysis supported the starvation phenotype, as well as perturbations in energy metabolism, and may be beneficial if described prior to respiratory activity data.<br /> The data and conclusions support the role of MftG in ethanol metabolism.

Reviewer #3 (Public review):

Summary:

The work by Graca et al. describes a GMC flavoprotein dehydrogenase (MftG) in the ethanol metabolism of mycobacteria and provides evidence that it shuttles electrons from the mycofactocin redox cofactor to the electron transport chain.

Strengths:

Overall, this study is compelling, exceptionally well designed and thoroughly conducted. An impressively diverse set of different experimental approaches is combined to pin down the role of this enzyme and scrutinize the effects of its presence or absence in mycobacteria cells growing on ethanol and other substrates. Other strengths of this work are the clear writing style and stellar data presentation in the figures, which makes it easy also for non-experts to follow the logic of the paper. Overall, this work therefore closes an important gap in our understanding of ethanol oxidation in mycobacteria, with possible implications for the future treatment of bacterial infections.

Weaknesses:

I see no major weaknesses of this work, which in my opinion leaves no doubt about the role of MftG.

Reviewer #4 (Public review):

Summary:

The manuscript by Graça et al. explores the role of MftG in the ethanol metabolism of mycobacteria. The authors hypothesise that MftG functions as a mycofactocin dehydrogenase, regenerating mycofactocin by shuttling electrons to the respiratory chain of mycobacteria. Although the study primarily uses M. smegmatis as a model microorganism, the findings have more general implications for understanding mycobacterial metabolism. Identifying the specific partner to which MftG transfers its electrons within the respiratory chain of mycobacteria would be an important next step, as pointed out by the authors.

Strengths:

The authors have used a wide range of tools to support their hypothesis, including co-occurrence analyses, gene knockout and complementation experiments, as well as biochemical assays and transcriptomics studies.<br /> An interesting observation that the mftG deletion mutant grown on ethanol as the sole carbon source exhibited a growth defect resembling a starvation phenotype.<br /> MftG was shown to catalyse the electron transfer from mycofactocinol to components of the respiratory chain, highlighting the flexibility and complexity of mycobacterial redox metabolism.

Weaknesses:

Could the authors elaborate more on the differences between the WT strains in Fig. 3C and 3E? in Fig. 3C, the ethanol concentration for the WT strain is similar to that of WT-mftG and ∆mftG-mftG, whereas the acetate concentration in thw WT strain differs significantly from the other two strains. How this observation relates to ethanol oxidation, as indicated on page 12.<br /> The authors conclude from their functional assays that MftG catalyses single-turnover reactions, likely using FAD present in the active site as an electron acceptor. While this is plausible, the current experimental set up doesn't fully support this conclusions, and the language around this claim should be softened.<br /> The authors suggest in the manuscript that the quinone pool (page 24) may act as the electron acceptor from mycofactocinol, but later in in the discussion section (page 30) they propose cytochromes as the potential recipients. If the authors consider both possibilities valid, I suggest discussing both options in the manuscript.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Using a knock-out mutant strain, the authors tried to decipher the role of the last gene in the mycofactocin operon, mftG. They found that MftG was essential for growth in the presence of ethanol as the sole carbon source, but not for the metabolism of ethanol, evidenced by the equal production of acetaldehyde in the mutant and wild type strains when grown with ethanol (Fig 3). The phenotypic characterization of ΔmftG cells revealed a growth-arrest phenotype in ethanol, reminiscent of starvation conditions (Fig 4). Investigation of cofactor metabolism revealed that MftG was not required to maintain redox balance via NADH/NAD+, but was important for energy production (ATP) in ethanol. Since mycobacteria cannot grow via substrate-level phosphorylation alone, this pointed to a role of MftG in respiration during ethanol metabolism. The accumulation of reduced mycofactocin points to impaired cofactor cycling in the absence of MftG, which would impact the availability of reducing equivalents to feed into the electron transport chain for respiration (Fig 5). This was confirmed when looking at oxygen consumption in membrane preparations from the mutant and would type strains with reduced mycofactocin electron donors (Fig 7). The transcriptional analysis supported the starvation phenotype, as well as perturbations in energy metabolism, and may be beneficial if described prior to respiratory activity data.

We thank the reviewer for their thorough evaluation of our work. We carefully considered whether transcriptional data should be presented before the respirometry data. However, this would disrupt other transitions and the flow of thoughts between sections, so that we prefer to keep the order of sections as is.

While the data and conclusions do support the role of MftG in ethanol metabolism, the title of the publication may be misleading as the mutant was able to grow in the presence of other alcohols (Supp Fig S2).

We agree that ethanol metabolism was the focus of this work and that phenotypes connected to other alcohols were less striking. We, therefore, changed “alcohol” to “ethanol” in the title of the manuscript.

Furthermore, the authors propose that MftG could not be involved in acetate assimilation based on the detection of acetate in the supernatant and the ability to grow in the presence of acetate. The minimal amount of acetate detected in the supernatant but a comparative amount of acetaldehyde could point to disruption of an aldehyde dehydrogenase.

We do not agree that MftG might be involved in acetaldehyde oxidation. According to our hypothesis, the disruption of an acetaldehyde dehydrogenase would lead to the accumulation of acetaldehyde. However, we observed an equal amount of acetaldehyde in cultures of M. smegmatis WT and ∆mftG grown on ethanol as well as on ethanol + glucose. Furthermore, the amount of acetate detected in the supernatants is not “minimal” as the reviewer points out but higher as or comparable to the acetaldehyde concentration (Figure 3 E and F, note that acetate concentration are indicated in g/L, acetaldehyde concentrations in µM). Furthermore, the accumulation of mycofactocinols in ∆mftG mutants grown on ethanol is not in agreement with the idea of MftG being an aldehyde dehydrogenase but very well supports our hypothesis that MftG is involved in cofactor reoxidation.

The link between mycofactocin oxidation and respiration is shown, however the mutant has an intact respiratory chain in the presence of ethanol (oxygen consumption with NADH and succinate in Fig 7C) and the NADH/NAD+ ratios are comparable to growth in glucose. Could the lack of growth of the mutant in ethanol be linked to factors other than respiration?

Indeed, by using NADH and succinate as electron donors we show that the respiratory chain is largely intact in WT and ∆mftG grown on ethanol. Also, when mycofactocinols were used as an electron donor, we observed that respiration was comparable to succinate respiration in the WT. However, respiration was severely hampered in membranes of ∆mftG when mycofactocinols were offered as reducing agent. These findings support our hypothesis very well that MftG is necessary to shuttle electrons from mycofactocin to the respiratory chain, while the rest of the respiratory chain stayed intact. The fact that NADH/NAD+ ratios are comparable between ethanol and glucose conditions are interesting but indirectly support our hypothesis that mycofactocin and not NAD is the major cofactor in ethanol metabolism. Therefore, we do not see any evidence that the lack of growth of the mutant in ethanol is linked to factors other than respiration.

To this end, bioinformatic investigation or other evidence to identify the membrane-bound respiratory partner would strengthen the conclusions.

We generally agree that it is an important next step to identify the direct interaction partners of MftG. However, we are convinced that experimental evidence using several orthogonal approaches is required to unequivocally identify interaction partners of MftG. Nevertheless, we agree that a preliminary bioinformatics study, could guide follow-up studies. We therefore attempted to predict interaction partners of MftG using D-SCRIPT and Alphafold 2. However, our approach did not reveal any meaningful results. Thus, we prefer not to integrate this approach into the manuscript but briefly summarize our methodology here: To predict potential interaction partners of M. smegmatis mc2 155 MftG (MSMEG_1428), D-SCRIPT (Sledzieski et al. 2021, https://doi.org/10.1016/j.cels.2021.08.010) with the Topsy-Turvy model version 1 (Singh et al. 2022, https://doi.org/10.1093/bioinformatics/btac258) was employed to screen every combination of the MSMEG_1428 amino acid sequence with the amino acid sequence of every potential interaction partner from the M. smegmatis mc2 155 predicted total proteome (total 6602 combinations, UniProt UP000000757,  Genome Accession CP000480). Predictions failed for eight potential interaction partners due to size constraints (MSMEG_0019, MSMEG_0400, MSMEG_0402, MSMEG_0408, MSMEG_1252, MSMEG_3715, MSMEG_4727, MSMEG_4757; all amino acids sequences ≥ 2000 AA). Afterward, the top 100 predicted interaction partners, ranked by D-SCRIPT protein-protein-interaction score, were subjected to an Alphafold 2 multimer prediction using ColabFold batch version 1.5.5 (AlphaFold 2 with MMseqs2, Mirdita et al. 2022, https://doi.org/10.1038/s41592-022-01488-1) on a Google Colab T4 GPU with a Python 3 environment and the following parameters (msa_mode: MMseqs2 (UniRef+Environmental), num_models = 1, num_recycles = 3, stop_at_score = 100, num_relax = 0, relax_max_iterations = 200, use_templates = False). As input, the MSMEG_1428 amino acid sequence was used as protein 1 and the amino acid sequence of the potential interaction partner was used as protein 2. In addition, proteins of the electron transport chain and the dormancy regulon (dos regulon) were included as potential interaction partners. In total, 222 unique potential MftG interactions were predicted. The AlphaFold 2 model interface predicted template modelling (ipTM) score peaked at 0.45 for MftG-MftA. This score, however, lies below the threshold of 0.75, which indicates a likely false prediction of interaction (Yin et al. 2022, https://doi.org/10.1002/pro.4379). Nonetheless, the models with the highest ipTM scores (MftG with MftA, MSMEG_3233, MSMEG_4260, MSMEG_0419, MSMEG_5139, MSMEG_5140) were inspected manually using ChimeraX version 1.8 (Meng et al. 2023, https://doi.org/10.1002/pro.4792). However, no reasonable interaction was found.

Reviewer #2 (Public Review):

Summary

Patrícia Graça et al., examined the role of the putative oxidoreductase MftG in regeneration of redox cofactors from the mycofactocin family in Mycolicibacerium smegmatis. The authors show that the mftG is often co-encoded with genes from the mycofactocin synthesis pathway in M. smegmatis genomes. Using a mftG deletion mutant, the authors show that mftG is critical for growth when ethanol is the only available carbon source, and this phenotype can be complemented in trans. The authors demonstrate the ethanol associated growth defect is not due to ethanol induced cell death, but is likely a result of carbon starvation, which was supported by multiple lines of evidence (imaging, transcriptomics, ATP/ADP measurement and respirometry using whole cells and cell membranes). The authors next used LC-MS to show that the mftG deletion mutant has much lower oxidised mycofactocin (MFFT-8 vs MMFT-8H2) compared to WT, suggesting an impaired ability to regenerate myofactocin redox cofactors during ethanol metabolism. These striking results were further supported by mycofactocin oxidation assays after over-expression of MftG in the native host, but also with recombinantly produced partially purified MftG from E. coli. The results showed that MftG is able to partially oxidise mycofactocin species, finally respirometry measurements with M. smegmatis membrane preparations from WT and mftG mutant cells show that the activity of MftG is indispensable for coupling of mycofactocin electron transfer to the respiratory chain. Overall, I find this study to be comprehensive and the conclusions of the paper are well supported by multiple complementary lines of evidence that are clearly presented.

Strengths

The major strengths of the paper are that it is clearly written and presented and contains multiple, complementary lines of experimental evidence that support the hypothesis that MftG is involved in the regeneration of mycofactocin cofactors, and assists with coupling of electrons derived from ethanol metabolism to the aerobic respiratory chain. The data appear to support the authors hypotheses.

We thank the reviewer for their thorough evaluation of our work.

Weaknesses

No major weaknesses were identified, only minor weaknesses mostly surrounding presentation of data in some figures.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

(1) In Fig 6 C and D, would it not be expected that MMFT-2H2 would be decreasing over time as MMFT-2 is increasing?

This is true. MMFT-2H2 is indeed decreasing while MMFT-2 in increasing, however, since the y-axis is drawn in logarithmic scale the visible difference is not proportional to the actual changes. The increase of MMFT-2 against a very low starting point is more clearly visible than the decrease of MMFT-2H2, which was added in high quantities.

(2) It would be beneficial to include rationale regarding the electron acceptors tested and why FAD was not included.

FAD is a prosthetic group of the enzyme and was always a component of the assay. The other electron acceptors were chosen as potential external electron acceptors.

(3) Bioinformatic analysis to capture possible interacting partners of MftG

See our response to the previous review.

Reviewer #2 (Recommendations For The Authors):

Questions:

(1) The co-occurrence analysis showed that one genome encoded mftG, but not mftC - do the authors think that this is a mftG mis-annotation?

This is a good question. We have investigated this case more closely and conclude that this particular mftG is not a misannotation. Instead, it appears that the mftC gene underwent gene loss in this organism. We added on page 8, line 15: “Only one genome (Herbiconiux sp. L3-i23) encoding a bona fide MftG did not harbor any MftC homolog. However, close inspection revealed the presence of mftD, mftF, and a potential mftA gene but a loss of mftB,C and E in this organism.”

(2) Figure 3A - the complemented mutant strain shows enhanced growth on ethanol when compared to the WT strain with the same mftG complementation vector, suggesting that dysregulation from the expression plasmid may not be responsible for this phenotype. Have the authors conducted whole genome sequencing on the mutant/complement isolate to rule out secondary mutations?

This is an interesting point. We have not conducted further investigations into the complement mutant. However, we can confidently state that the complementation was successful in that it restored growth of the ∆mftG mutant on ethanol, thus confirming that the growth arrest of the mutant was due to the lack of mftG activity and not due to any secondary mutation. We also observed that both the complement strain and the overexpression strain, both of which are based on the same overexpression plasmid, exhibited shorter lag phases, faster growth and higher final cell densities compared to the wild type. We interpret these data in a way that overexpression of mftG might lift a growth limited step. Notably, this is only an interpretation, we do not make this claim. What we cannot explain at the moment, is the observation that the complement mutant grew to a higher OD than the overexpression strain. This is indeed interesting, and it might be due to an artefact or due to complex regulatory effects, which are hard to study without an in-depth characterization of the different strains involved. While this goes beyond the scope of this study, we are convinced that our main conclusions are not challenged by this phenomenon.

(3) Figure 4C - could the yellow fluorescence that suggests growth arrest be quantified in these images similar to the size and septa/replication sites?

In principle, this is a good suggestion. However, the amount of yellow fluorescence only differed in the starvation condition between genotypes. Since this condition was not a focus of this study, we preferred not to discuss these differences further.

(4) Figure 4E - the complemented mutant strain has very high error, why is that? Could this phenotype not be complemented?

It is true that the standard deviation (SD) is relatively high in this experiment. This is due to the fact that single-cell analyses based on microscopic images were conducted here - not bulk measurements of the average fluorescence. This means that the high variance partially reflects phenotypic heterogeneity of the population, rather than inefficient complementation. While it is interesting that not all cells behaved equally, a finding that deserves further investigations in the future, we conclude that the mean value is a good representative for the efficiency of the complementation.

(5) While the whole cell extract experiment presented in Figure 6A is very clear, could the authors include SDS page or MS results of their partially purified MftG preparations used for figure B-F in the supplementary data to rule out any confounding factors that may be oxidising mycofactocin species in these preparations?

We did not include SDS-Page or MS results since the enzyme preparations obtained were not pure. This is why we refer to the preparation as “partially purified fraction”. Since we were aware of the risk of confounding factors being potentially present in the preparation, we used two different expression hosts (M. smegmatis ∆mftG and E. coli) and included negative controls, i.e., a reaction using protein preparations from the same host that underwent the exact same purification steps but lacked the mftG gene. For instance, Figure 6A shows the negative control (M. smegmatis ∆mftG) and the verum (M. smegmatis ∆mftG-mftG_His6). Although this control is not shown in panels BCD for more clarity, we can assure that the proposed activity of MftG as never been detected in any extract of _M. smegmatis ∆mftG. Concerning MftG preparations obtained from heterologous expression in E. coli, we also performed empty vector controls and inactivated protein controls. We added a new Supplementary Figure S4 to show one example control. Taken together, the usage of two different expression hosts along with corresponding background controls clearly demonstrates that mycofactocinol oxidation only occurred in protein extracts of bacterial strains that contained the mftG gene. Taken together, these data indicate that the observed mycofactocinol dehydrogenase activity is connected to MftG and not to any background activity.

Recommendations:

• A suggestion - revise sub-titles in the results section to be more 'results-oriented' e.g. rather than 'the role of MftG in growth and metabolism of mycobacteria' consider instead 'MftG is critical for M. smegmatis capacity to utilise ethanol as a sole carbon source for growth' or something similar.

In principle this is a good idea for many manuscripts. However, we have the impression that this approach does not reflect the complexity and additive aspect of the sections of our manuscript.

• For clarity, revise all figures to include p-values in the figure legend rather than above the figures (use asterisks to indicate significance).

We are not sure whether the deletion of p-values in the figures would enhance clarity. We would prefer to leave them within figures.

• Figure 5B -revise colour legend, it is unclear which bar on the graph corresponds to which strain.

The figure legend was enlarged to enhance readability.

• Page 8 - MftG and MftC should be lowercase and italicised as the authors are writing about the co-occurrence of genes encoded in genomes, not proteins.

Good point, we changed some instances of MftG / MftC to mftG / mftC, to more specifically refer to the gene level. However, in some cases, the protein level is more appropriate, for instance, the phylogenies are based on protein sequences. That is why we used the spelling MftG / MftC in these cases.

• Page 9 - for clarity move Figure 3 after first in text citation.

We moved Figure 3.

• Page 17 - for clarity move Figure 5 after first in text citation.

We moved Figure 5. We furthermore reformatted figure legend to fit onto the same page as the figures.

• Page 20, line 17 - 'was attempted' change to 'was performed'. The authors did more than attempt purification, they succeeded!

Since purification of MftG was not successful, we prefer the term “attempted” here. However, activity assays indeed indicate successful production of MftG.

• Page 20, line 19-21 - data showing that the MftG-HIS6 complements ∆mftG could be included in supplementary information.

Complementation was obvious by growth on media containing ethanol as a sole carbon source.

• Page 26 line 25 - 'we also we' delete duplicated we.

Thank you for the hint, we deleted the second instance of “we” in the manuscript.

• Page 26 Line 26 - 'mycofactocinols were oxidised to mycofactocinols', should this read mycofactocinols were oxidised to mycofactocinones?

Correct. We changed “mycofactocinols” to “mycofactocinones”

• Page 28 line 17, huc hydrogenase operon

We added (“huc operon”).

• Page 38 line 24, 'Two' not 'to'.

This is a misunderstanding. “To” is correct

One can derive this as a corollary of BV 3.12 (HW1)

Warning: The $a_i$s are different in these two views.

Warning: The $b_i$s are different in these two views.

FINAL THOUGHTS: This article largely discussed liberalism in international relations. Specifically, it showed the role of how various norms and institutions work to promote cooperation between states. I thought it was interesting when they talked about how Democratic states are less likely to go to war with each other. Two questions I still have are, how do these liberal norms become a norm in regions with different cultural values? Also, is there any other ways international organizations like the UN can encourage more cooperation among resistant states besides leaving them out of their meetings?

Norms guide state behavior.

International institutions contribute to peace by promoting certain behavior between states.

The necessity of power constraints.

Important liberal norms that contribute to political restraint.

Various institutions and norms in limiting aggressive foreign policy.

Wilson’s commitment to presidential authority in foreign policy.

US public sentiment toward interventionism due to Wilson’s policies.

This aligns with liberal principles.

The initial military objectives of limited intervention.

U.S. governance constrained imperial ambitions.

Comparison to assess U.S. imperialism against other nations.

Contradiction between liberal values and imperialistic actions.

Concept of absolute gains where all parties can achieve mutual benefits from cooperation.

Actions can be less direct but still equally effect states.

Role of norms in shaping state behavior.

Economic integration as a central aspect of the liberal order.

Importance of international organizations like the UN.

Both economic and diplomatic consequences of aggressive states.

Connects domestic liberalism with global governance structures.

The limited history of democracies raises questions about their ability to sustain peace.

Democracies are unlikely to engage in war with each other.

Wanting to prevent the abuse of power within liberal democracies.

The liberal challenge of balancing state security with the protection of individual freedoms.

Liberal concerns about imperialism

Military buildup is a threat to civil liberties.

authoritarianism threatening individual freedoms.

Individual rights as a core liberal element.

liberalism is more hopeful than realism.

Liberalism's focus on institutions to reduce state violence.

Link between liberalism and democratic principles like free elections and civil liberties.

Very interesting line when thinking about what we learned on Monday when Donna Bilak came in for a guest lecture. It seems here that Maier is hinting at the fact that there is a 'mystery' that will unfold upon the reading of the book, as well as 'treasures her enclosed'.

This story shows this practice of flyting in the culture.

I don't fully understand the meaning of this passage. If the dragon is rightly handled, then he becomes friendly to men. But he is still malicious? If the dragon has an alchemical meaning, what would that imply in context with this passage?

I'm interested in the connection to alchemy that this passage creates. If Sol represents Sulphur and Luna represents Mercury, what does the dragon represent in connection to alchemy? If there is any connection at all

Should read "each chapter is"

some connection is needed between this section and the last one.

in this summary, I wonder about it's accuracy in conveying Ruberg's claim that the rhetoric of empathy "minimizes the lives and identities of those who are seen as "different or "other'"

in the context of what precedes, I would expect some discussion of the military's exclusion of gay people and the don't ask, don't tell policy. Lonnie is in a difficult position.

why is Katie in a privileged position? Is it because she's outside the action? How does that relate to "unjust power dynamics? A cleaner connection is needed. Maybe you could consider Katie's privilege as being heteronormative.

It seems like even those trained to reduce bloat can still get affected by it.

Its insane how large simple things on websites have gotten to.

how doe this image demonstrate these complicated relationships and the relevance of this game as exploring those relationships?

to some extent this concluding statement should accound for the connection you're making.

Not clear what this means but I think I see the shift you're making to exploring familial relationships

watch for exact language here--the paraphrase should be in your own words. A more precise summary will help direct the connection more deliberately

what about the family portrait speaks to this strife?

Interesting that certain groups are benefiting while others are not

Also concerning that depression at such a young age is linked to this

violence

writing as reparation

as much a memorialization project as an academic essay -- coming through in affect

awareness of what writing can do

Introduction (teaching, location) full of series -- communicating stylistically the "ubiquity" in the abstract

Couldnt this technically lead to some sort of bias? Since the study focuses on books that librarians choose to keep available? Of course a vast majority may be extremely popular novels, I wouldnt be surprised if there are some that have slight preference for popular but lesser known novels or those that dislike a certain author. I could be completely wrong but would be something to take into account.

The researchers primarily speak and read english which will greatly influence what are considered "classic" books. The data is influenced by the creator's language as that is what they have known the whole time. They wouldnt know about classics from Spanish speaking contries or French speaking countries unless they have actively been pushed in english translated versions.

Another great way we are regulation what is being shared on social media

We can’t stop extremism groups on any platform but we also can’t base all of our information on a small population of people

This doesn’t make sense to me because I feel like social media did the opposite. During Covid people couldn’t go outside but the only way to connect with people was through social media.

It is interesting that they just assume people have heard about the concerns

Right from the beginning it lists reasons why social media is a good thing

This is an improvement over Steam Family Sharing.

"Hate crimes against Asians began to rise, especially toward the elderly."

Like the elderly didn't have enough hate already, since COVID started, more Asians have been abused physically or emotionally. This doesn't just affect the elders but almost all ages. I experienced this as I got bullied as soon as Covid started, "thanks for eating the bats."

OMG!!!

!!!!!!!

SO IMPORTANT

!!!!!

!!!!!!

!!!!!!!

I wonder if this is still the same

the attribution of human characteristics/ behavior to a diety, animal, or object.

parallelism

Definition of superlative: of the highest quality or degree

Derived from the greek word oneiros meaning "dream". Oneiric means relating to dreams or dreaming.

so super important

!!!!!

DEFINITION: The skin conductance response (SCR) is a change in the skin’s electrical and sweat gland activity in response to stimuli that are physiologically arousing

!!!!!!

SO SUPER IMPORTANT

Sascha. 2024. “Mindscapes: The Zettelkasten as a Thinking Environment.” Zettelkasten Method. October 9, 2024. https://zettelkasten.de/posts/zettelkasten-thinking-environment/.

Writing is thinking and most of the times when someone thinks its messy.

We should not only teach that how to think throug writing, but then how to edit and revise to present our thinking as argumentation

This political cartoon illustrates the way that Americans who didn't know much about the stock market quickly jumped into it because they seen the experienced investors progressing. The "TNT" and "Dynamite" represent the explosive risk and danger in the stock market.

Near-mystical sweeping assertions like this call to mind the "fairy tales" that the author accuses the "Washington Establishment" of telling later in this paragraph.

eLife Assessment

This important, clearly written, and timely manuscript links the timing of ART with the kinetics of total and intact proviral HIV DNA. The conclusions are interesting and somewhat novel, and the importance of the work is high because the focus is on African women and clade C virus, both of which are understudied in the HIV reservoir field. The strength of the evidence is convincing. Overall, this work will be of very high interest to scientists and clinicians in the HIV cure/persistence fields.

Reviewer #1 (Public review):

The authors sought to determine the impact of early antiretroviral treatment on the size, composition, and decay of the HIV latent reservoir. This reservoir represents the source of viral rebound upon treatment interruption and therefore constitutes the greatest challenge to achieving an HIV cure. A particular strength of this study is that it reports on reservoir characteristics in African women, a significantly understudied population, of whom some have initiated treatment within days of acute HIV diagnosis. With the use of highly sensitive and current technologies, including digital droplet PCR and near full-length genome next-generation sequencing, the authors generated a valuable dataset for investigation of proviral dynamics in women initiating early treatment compared to those initiating treatment in chronic infection. The authors confirm previous reports that early antiretroviral treatment restricts reservoir size, but further show that this restriction extends to defective viral genomes, where late treatment initiation was associated with a greater frequency of defective genomes. Furthermore, an additional strength of this study is the longitudinal comparison of viral dynamics post-treatment, wherein early treatment was shown to be associated with a more rapid rate of decay in proviral genomes, regardless of intactness, over a period of one year post-treatment. While it is indicated that intact genomes were not detected after one year following early treatment initiation, sampling depth is noted as a limitation of the study by the authors, and caution should thus be taken with interpretation where sequence numbers are low. Defective genomes are more abundant than intact genomes and are therefore more likely to be sampled. Early treatment was also associated with reduced proviral diversity and fewer instances of polymorphisms associated with cytotoxic T-lymphocyte immune selection. This is expected given that rapid evolution and extensive immune selection are synonymous with HIV infection in the absence of treatment, yet points to an additional benefit of early treatment in the context of immune therapies to restrict the reservoir.

This is one of the first studies to report the mapping of longitudinal intactness of proviral genomes in the globally dominant subtype C. The data and findings from this study therefore represent a much-needed resource in furthering our understanding of HIV persistence and informing broadly impactful cure strategies. The analysis on clonal expansion of proviral genomes may be limited by higher sequence homogeneity in hyperacute infection i.e., cells with different proviral integration sites may have a higher likelihood of containing identical genomes compared to chronic infection.

Overall, these data demonstrate the distinct benefits of early treatment initiation at reducing the barrier to a functional cure for HIV, not only by restricting viral abundance and diversity but also potentially through the preservation of immune function and limiting immune escape. It therefore provides clues to curative strategies even in settings where early diagnosis and treatment may be unlikely.

Reviewer #2 (Public review):

HIV infection is characterized by viral integration into permissive host cells - an event that occurs very early in viral-host encounter. This constitutes the HIV proviral reservoir and is a feature of HIV infection that provides the greatest challenge for eradicating HIV-1 infection once an individual is infected.

This study looks at how starting HIV treatment very early after infection, which substantially reduces the peak viral load detectable (compared to untreated infection), affects the amount and characteristics of the viral reservoir. The authors studied 35 women in South Africa who were at high risk of getting HIV. Some of these women started HIV treatment very soon after getting infected, while others started later. This study is well designed and has as its focus a very well characterized cohort. Comparison groups are appropriately selected to address proviral DNA characterization and dynamics in the context of acute and chronic treated HIV-1. The amount of HIV and various characteristics of the genetic makeup of the virus (intact/defective proviral genome) was evaluated over one year of treatment. Methods employed for proviral DNA characterization are state of the art and provide in-depth insights into the reservoir in peripheral blood.

While starting treatment early didn't reduce the amount of HIV DNA at the outset, it did lead to a gradual decrease in total HIV DNA quantity over time. In contrast, those who started treatment later didn't see much change in this parameter. Starting treatment early led to a faster decrease in intact provirus (a measure of replication-competence), compared to starting treatment later. Additionally, early treatment reduced genetic diversity of the viral DNA and resulted in fewer immune escape variants within intact genomes. This suggests that collectively having a smaller intact replication-competent reservoir, less viral variability, and less opportunity for virus to evade the immune system - are all features that are likely to facilitate more effective clearance of viral reservoir, especially when combined with other intervention strategies.

Major strengths of the study include the cohort of very early treated persons with HIV and the depth of study. These are important findings, particularly as the study was conducted in HIV-1 subtype C infected women (more cure studies have focussed on men and with subtype B infection)- and in populations most affected by HIV and in need of HIV cure interventions. This is highly relevant because it cannot be assumed that any interventions employed for reducing/clearing the HIV reservoir would perform similarly in men and women or across different populations. Other factors also deserve consideration and include age, and environment (e.g. other comorbidities and coinfections).

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public reviews):

(1) Given that this is one of the first studies to report the mapping of longitudinal intactness of proviral genomes in the globally dominant subtype C, the manuscript would benefit from placing these findings in the context of what has been reported in other populations, for example, how decay rates of intact and defective genomes compare with that of other subtypes where known.  

Most published studies are from men living with HIV-1 subtype B and the studies are not from the hyperacute infection phase and therefore a direct head-to-head comparison with the FRESH study is difficult.  However, we can cite/highlight and contrast our study with a few a few examples from acute infection studies as follows.

a. Peluso et. al., JCI, 2020, showed that in Caucasian men (SCOPE study), with subtype B infection, initiating ART during chronic infection virus intact genomes decayed at a rate of 15.7% per year, while defective genomes decayed at a rate of 4% per year.  In our study we showed that in chronic treated participants genomes decreased at a rate of 25% (intact) and 3% (defective) per month for the first 6 months of treatment.

b. White et. al., PNAS, 2021, demonstrated that in a cohort of African, white and mixed-race American men treated during acute infection, the rate of decay of intact viral genomes in the first phase of decay was <0.3 logs copies in the first 2-3 weeks following ART initiation. In the FRESH cohort our data from acute treated participants shows a comparable decay rate of 0.31 log copies per month for virus intact genomes.

c. A study in Thailand (Leyre et. al., 2020, Science Translational Medicine), of predominantly HIV-1 CRF01-AE subtype compared HIV-reservoir levels in participants starting ART at the earliest stages of acute HIV infection (in the RV254/SEARCH 010 cohort) and participants initiating ART during chronic infection (in SEARCH 011 and RV304/SEARCH 013 cohorts). In keeping with our study, they showed that the frequency of infected cells with integrated HIV DNA remained stable in participants who initiated ART during chronic infection, while there was a sharp decay in these infected cells in all acutely treated individuals during the first 12 weeks of therapy.  Rates of decay were not provided and therefore a direct comparison with our data from the FRESH cohort is not possible.

d. A study by Bruner et. al., Nat. Med. 2016, described the composition of proviral populations in acute treated (within 100 days) and chronic treated (>180 days), predominantly male subtype B cohort. In comparison to the FRESH chronic treated group, they showed that in chronic treated infection 98% (87% in FRESH) of viral genomes were defective, 80% (60% in FRESH) had large internal deletions and 14% (31% in FRESH) were hypermutated.  In acute treated 93% (48% in FRESH) were defective and 35% (7% in FRESH) were hypermutated.  The differences frequency of hypermutations could be explained by the differences in timing of infection specifically in the acute treated groups where FRESH participants initiate ART at a median of 1 day after infection.  It is also possible that sex- or race-based differences in immunological factors that impact the reservoir may play a role.  

This study also showed that large deletions are non-random and occur at hotspots in the HIV-1 genome. The design of the subtype B IPDA assay (Bruner et. al., Nature, 2019) is based on optimal discrimination between intact and deleted sequences - obtained with a 5′ amplicon in the Ψ region and a 3′ amplicon in Envelope. This suggest that Envelope is a hotspot for large while deletions in Ψ is the site of frequent small deletions and is included in larger 5′ deletions. In the FRESH cohort of HIV-1

subtype C, genome deletions were most frequently observed between Integrase and Envelope relative to Gag (p<0.0001–0.001).

e. In 2017, Heiner et. al., in Cell Rep, also described genetic characteristics of the latent HIV-1 reservoir in 3 acute treated and 3 chronic treated male study participants with subtype B HIV.  Their data was similar to Bruner et. al. above showing proportions of intact proviruses in participants who initiated therapy during acute/early infection at 6% (94% defective) and chronic infection at 3% (97% defective). In contrast the frequencies in FRESH in acute treated were 52% intact and 48% defective and in chronic infection were 13% intact and 87% defective.  These differences could be attributed to the timing of treatment initiation where in the aforementioned study early treatment ranged from 0.6-3.4 months after infection.

(2) Indeed, in the abstract, the authors indicate that treatment was initiated before the peak. The use of the term 'peak' viremia in the hyperacute-treated group could perhaps be replaced with 'highest recorded viral load'. The statistical comparison of this measure in the two groups is perhaps more relevant with regards to viral burden over time or area under the curve viral load as these are previously reported as correlates of reservoir size. 

We have edited the manuscript text to describe the term peak viraemia in hyperacute treated participants more clearly (lines 443-444). We have now performed an analysis of area under the curve to compare viral burden in the two study groups and found associations with proviral DNA levels after one year. This has been added to the results section (lines 162-163).

Reviewer #2 (Public reviews):

(1) Other factors also deserve consideration and include age, and environment (e.g. other comorbidities and coinfections.)

We agree that these factors could play a role however participants in this study were of similar age (18-23), and information on co-morbidities and coinfections are not known.

Reviewer #3 (Public reviews):

(1) The word reservoir should not be used to describe proviral DNA soon after ART initiation. It is generally agreed upon that there is still HIV DNA from actively infected cells (phase 1 & 2 decay of RNA) during the first 6-12 months of ART. Only after a full year of uninterrupted ART is it really safe to label intact proviral HIV DNA as an approximation of the reservoir. This should be amended throughout.

We agree and where appropriate have amended the use of the word reservoir to only refer to the proviral load after full viral suppression, i.e., undetectable viral load.

(2) All raw, individualized data should be made available for modelers and statisticians. It would be very nice to see the RNA and DNA data presented in a supplementary figure by an individual to get a better grasp of intra-host kinetics.

We will make all relevant data available and accessible to interested parties on request. We have now added a section on data availability (lines 489-491).

(3) The legend of Supplementary Figure 2 should list when samples were taken.

The data in this figure represents an overall analysis of all sequences available for each participant at all time points.  This has now been explained more clearly in the figure legend.

Recommendations for the authors:

Reviewer #1 (Recommendations for The Authors):

(1) It is recommended that the introduction includes information to set the scene regarding what is currently reported on the composition of the reservoir for those not in the immediate field of study i.e., the reported percentage of defective genomes and in which settings/populations genome intactness has been mapped, as this remains an area of limited information.

We have now included summary of other reported findings in the field in the introduction (lines 89-92, 9498) and discussion (lines 345-350).  A more detailed overview has been provided in the response to public reviews.

(2) It may be beneficial to state in the main text of the paper what the purpose of the Raltegravir was and that it was only administered post-suppression. Looking at Table 1, only the hyperacute treatment group received Raltegravir and this could be seen as a confounder as it is an integrase inhibitor. Therefore, this should be explained.

Once Raltegravir became available in South Africa, all new acute infections in the study cohort had an intensified 4-drug regimen that included Raltegravir.  A more detailed explanation has now been included in the methods section (lines 435-437).

(3) Can the authors explain why the viral measures at 6 months post-ART are not shown for chronictreated individuals in Figure 1 or reported on in the text?

The 6 months post-ART time point has been added to Figure 1.

(4) Can the authors indicate in the discussion, how the breakdown of proviral composition compares to subtype B as reported in the literature, for example, are the common sites of deletion similar, or is the frequency of hypermutation similar?

Added to discussion (lines 345-350).

(5) Do the numbers above the bars in Figure 3 represent the number of sampled genomes? If so, this should be stated.

Yes, the numbers above the bars represent the number of sampled genomes. This has been added to the Figure 3 legend.

(6) In the section starting on line 141, the introduction implies a comparison with immunological features, yet what is being compared are markers of clinical disease progression rather than immune responses. This should be clarified/corrected.

This has been corrected (line 153).

(7) Line 170 uses the term 'immediately' following infection, however, was this not 1 -3 days after?

We have changed the word “immediately” to “1-3 days post-detection” (line 181).

(8) Can the sampling time-points for the two groups be given for the longitudinal sequencing analysis?

The sequencing time points for each group is depicted in Figure 2.

(9) Line 183 indicates that intact genomes contributed 65% of the total sequence pool, yet it's given as 35% in the paragraph above. Should this be defective genomes?

Yes, this was a typographical error.  Now corrected to read “defective genomes” (line 193).

(10) The section on decay kinetics of intact and defective genomes seems to overlap with the section above and would flow better if merged.

Well noted, however we choose to keep these sections separate.

(11) Some references in the text are given in writing instead of numbering.

This has been corrected.

(12) In the clonal expansion results section, can it be indicated between which two time-points expansion was measured?

This analysis was performed with all sequences available for each participant at all time points.  We have added this explanation to the respective Figure legend.

Reviewer #2 (Recommendations for The Authors):

(1) The statement on line 384 "Our data showed that early ART...preserves innate immune factors" - what innate immune factors are being referred to?

We have removed this statement.

(2) HLA genotyping methods are not included in the Methods section

Now included and referenced (lines 481-483).

(3) Are CD4:CD8 ratios available for the cohorts? This could be another informative clinical parameter to analyse in relation to HIV-1 proviral load after 1 year of ART – as done for the other variables (peak VL, and the CD4 measures).

Yes, CD4:CD8 ratios are available. We performed the recommended analysis but found no associations with HIV-1 proviral load after 1 year of ART. We have added this to the results section (lines 163-164).

(4) Reference formatting: Paragraph starting at line 247 (Contribution of clonal expansion...) - the two references in this paragraph are not cited according to the numbering system as for the rest of the manuscript. The Lui et al, 2020 reference is missing from the reference list - so will change all the numbering throughout.

This has been corrected.

Reviewer #3 (Recommendations for The Authors):

(1) To allow comparison to past work. I suggest changing decay using % to half-life. I would also mention the multiple studies looking at total and intact HIV DNA decay rates in the intro.

We do not have enough data points to get a good estimate of the half-life and therefor report decay as percentage per month for the first 6 months. 

(2) Line 73: variability is the wrong word as inter-individual variability is remarkably low. I think the authors mean "difference" between intact and total.

We have changed the word variability to difference as suggested.

(3) Line 297: I am personally not convinced that there is data that definitively shows total HIV DNA impacting the pathophysiology of infection. All of this work is deeply confounded by the impact of past viremia. The authors should talk about this in more detail or eliminate this sentence.

We have reworded the statement to read “Total HIV-1 DNA is an important biomarker of clinical outcomes.” (Lines 308-309).

(4) Line 317; There is no target cell limitation for reservoir cells. The vast majority of CD4+ T cells during suppressive ART are uninfected. The mechanism listing the number of reservoir cells is necessarily not target cell limitation.

We agree. The statement this refers to has been reworded as follows: “Considering, that the majority of CD4 T cells remain uninfected it is likely that this does not represent a higher number of target cells, and this warrants further investigation.” (lines 325-326).

(5) Line 322: Some people in the field bristle at the concept of total HIV DNA being part of the reservoir as defective viruses do not contribute to viremia. Please consider rephrasing. 

We acknowledge that there are deferring opinions regarding total HIV DNA being part of the reservoir as defective viruses do not contribute to viremia, however defective HIV proviruses may contribute to persistent immune dysfunction and T cell exhaustion that are associated comorbidities and adverse clinical outcomes in people living with HIV.  We have explained in the text that total HIV-DNA does not distinguish between replication-competent and -defective viruses that contribute to the viral reservoir.

(6) Line 339: The under-sampling statement is an understatement. The degree of under-sampling is massive and biases estimates of clonality and sensitivity for intact HIV. Please see and consider citing work by Dan Reeves on this subject.

We agree and have cited work by Dan Reeves (line 358).

(7) Line 351: This is not a head-to-head comparison of biphasic decay as the Siliciano group's work (and others) does not start to consider HIV decay until one year after ART. I think it is important to not consider what happens during the first year of ART to be reservoir decay necessarily.

Well noted.

(8) Line 366-371: This section is underwritten. In nearly all PWH studies to date, observed reservoirs are highly clonal.

We agree that observed reservoirs are highly clonal but have not added anything further to this section.

(9) It would be nice to have some background in the intro & discussion about whether there is any a priori reason that clade C reservoirs, or reservoirs in South African women, might differ (or not) from clade B reservoirs observed in different study participants.

We have now added this to the introduction (lines 94-103).

(10) Line 248: This sentence is likely not accurate. It is probable that most of the reservoir is sustained by the proliferation of infected CD4+ T cells. 50% is a low estimate due to under-sampling leading to false singleton samples. Moreover, singletons can also be part of former clones that have contracted, which is a natural outcome for CD4+ T cells responding to antigens &/or exhibiting homeostasis. The data as reported is fine but more complex ecologic methods are needed to truly probe the clonal structure of the reservoir given severe under sampling.

Well noted.

eLife Assessment

This study reports an important finding on the mechanism underlying the enhancement of anti-viral immune responses by febrile temperatures, especially the role of the conserved heat-shock factor, HSF-1. The data provide compelling support for the authors' model wherein increased temperature in the shrimp Litopenaeus vannamei activates HSF1, which in turn enhances anti-viral response via up-regulation of the nSWD protein and antibacterial peptides. The work, which will be of interest to virologists, immunologists, and cell biologists, would benefit from more discussion of the function and roles of HSF-1 at 25°C vs. 32°C.

Usage- Repeated socially oriented action,

custom (type of usage)- action based on the fact that it's been repeated for a long time

Self- interest( type of usage)- many people can do the same thing in self-interest as long as everyone gets the same thing out of it.

This sentence, which expresses human feelings through nature, is a perfect example of Romanticism. The lilacs demonstrate how the natural world offers a way to manage and process grief by acting as symbols of both beauty and melancholy. One of the main features of Romanticism is the way in which nature and human emotion are interwoven, highlighting the profound ways in which our surroundings may both influence and mirror our internal emotional landscape.

This line reflects romanticism by using nature to express personal feelings. the lilacs symbolize both beauty and morning, showing how the natural world can help us proceed grief. This connection to nature and emotion is a key aspect of Romanticism, highlighting how our surroundings can deeply influence our inner experiences.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews: 

Reviewer #1 (Public Review): 

Summary: 

The present study's main aim is to investigate the mechanism of how VirR controls the magnitude of MEV release in Mtb. The authors used various techniques, including genetics, transcriptomics, proteomics, and ultrastructural and biochemical methods. Several observations were made to link VirR-mediated vesiculogenesis with PG metabolism, lipid metabolism, and cell wall permeability. Finally, the authors presented evidence of a direct physical interaction of VirR with the LCP proteins involved in linking PG with AG, providing clues that VirR might act as a scaffold for LCP proteins and remodel the cell wall of Mtb. Since the Mtb cell wall provides a formidable anatomical barrier for the entry of antibiotics, targeting VirR might weaken the permeability of the pathogen along with the stimulation of the immune system due to enhanced vesiculogenesis. Therefore, VirR could be an excellent drug target. Overall, the study is an essential area of TB biology.

We thank the reviewer for the kind assessment of our paper.  

Strengths: 

The authors have done a commendable job of comprehensively examining the phenotypes associated with the VirR mutant using various techniques. Application of Cryo-EM technology confirmed increased thickness and altered arrangement of CM-L1 layer. The authors also confirmed that increased vesicle release in the mutant was not due to cell lysis, which contrasts with studies in other bacterial species. 

Another strength of the manuscript is that biochemical experiments show altered permeability and PG turnover in the mutant, which fits with later experiments where authors provide evidence of a direct physical interaction of VirR with LCP proteins. 

Transcriptomics and proteomics data were helpful in making connections with lipid metabolism, which the authors confirmed by analyzing the lipids and metabolites of the mutant. 

Lastly, using three approaches, the authors confirm that VirR interacts with LCP proteins in Mtb via the LytR_C terminal domain. 

Altogether, the work is comprehensive, experiments are designed well, and conclusions are made based on the data generated after verification using multiple complementary approaches.

We are glad that this reviewer finds our study of interest and well designed.   

Weaknesses: 

(1) The major weakness is that the mechanism of VirR-mediated EV release remains enigmatic. Most of the findings are observational and only associate enhanced vesiculogenesis observed in the VirR mutant with cell wall permeability and PG metabolism. The authors suggest that EV release occurs during cell division when PG is most fragile. However, this has yet to be tested in the manuscript - the AFM of the VirR mutant, which produces thicker PG with more pore density, displays enhanced vesiculogenesis. No evidence was presented to show that the PG of the mutant is fragile, and there are differences in cell division to explain increased vesiculogenesis. These observations, counterintuitive to the authors' hypothesis, need detailed experimental verification.

We concur with the reviewer that we do not have direct evidence showing a more fragile PG in the virR mutant and our statement is supported by a compendium of different results. However, this statement is framed in the discussion section as a possible scenario, acknowledging that more experiments are needed to make such connection. Nevertheless, we provide additional data on the molecular characterization of virRmut PG using MS to show a significant increase in the abundance of deacetylated muropeptides, a feature that has been linked to altered lysozyme sensitivity in other unrelated Gram-positive bacteria

(Fig 8 G,H).  

(2.1) Transcriptomic data only adds a little substantial. Transcriptomic data do not correlate with the proteomics data. It remains unclear how VirR deregulates transcription. 

We concur with the reviewer that information provided by transcriptomics and proteomics is a bit fragmented and, taking into consideration the low correlation between both datasets, it does not help to explain the phenotype observed in the mutant. This issue has also been raised by another reviewer so, we have paid special attention to that. 

To refine the biological interpretation of the transcriptomic data we have integrated the complemented strain (virRmut-Comp) in our analyses. This led us to narrow down the virR-dependent transcriptomics signature to the sets of genes that appear simultaneously deregulated in virRmut with respect to both WT and complemented strain in either direction. Furthermore, to identify the transcription factors whose regulatory activity appear disrupted in the mutant strain, we have resorted to an external dataset (Minch et al. 2015) and found a set of 10 transcriptional regulators whose regulons appear significantly impacted in the virRmut strain. While admittedly these improvements do not fully address the question tackled by the reviewer, we found that they contribute to a more precise characterization of the VirR-dependent transcriptional signatures, as well as the regulons, in the genome-wide transcriptional regulatory network of the pathogen that appear altered because of virR disruption. We acknowledge that the lack of correlation between whole-cell lysates proteomics and transcriptomic data is something intriguing, albeit not uncommon in Mycobacterium tuberculosis. However, differences in the protein cargo of the vesicles from different strains share key pathways in common with the transcriptomic analyses, such as the enrichments in cell wall biogenesis and peptidoglycan biosynthesis that are observed both among genes that are downregulated in both cases in virRmut.

(2.2) TLCs of lipids are not quantitative. For example, the TLC image of PDIM is poor; quantitative estimation needs metabolic labeling of lipids with radioactive precursors. Further, change in PDIMs is likely to affect other lipids (SL-1, PAT/DAT) that share a common precursor (propionyl- CoA).

We also agree with the reviewer that TLC, as it is, it is not quantitative. However, we do not have access to radioactive procedures. In the new version of the manuscript, we have run TLCs on all the strains tested to resolve SLs and PAT/DATs (Fig S8). Our results show a reduction in the pool of SL and DATs in the mutant, indicating that part of the methylmalonil pool is diverted to the synthesis of PDIMs. 

(3) The connection of cholesterol with cell wall permeability is tenuous. Cholesterol will serve as a carbon source and contribute to the biosynthesis of methyl-branched lipids such as PDIM, SL-1, and PAD/DAT. Carbon sources also affect other aspects of physiology (redox, respiration, ATP), which can directly affect permeability and import/export of drugs. Authors should investigate whether restoration of the normal level of permeability and EV release is not due to the maintenance of cell wall lipid balance upon cholesterol exposure of the VirR mutant.

We concur with the reviewer that cholesterol as a sole carbon source is introducing many changes in Mtb cells beside permeability. Consequently, we investigated the virRmut lipid profile upon exposure to either cholesterol or TRZ (Fig S8). Both WT and virRmut-Comp strains were included in the analysis. Polar lipid analysis revealed that either cholesterol or TRZ exposure induced a marked reduction in PIMs and cardiolipin (DPG) levels in virRmut relative to WT or complemented strains (Fig S8A). Analysis of apolar lipids indicated that, relative to glycerol MM, virRmut cultured in the presence of cholesterol or TRZ showed reduced levels of TDM and DATs compared to WT and virRmut-Comp strains (Fig S8B). These results suggest a lack of correlation between modulation of cell permeability by cholesterol and TRZ and lipid levels in the absence of VirR.

Furthermore, about this section, we would like to mention that we have modified the reference used for the annotation of the DosR regulon: moving from the definition of the regulon used in the previous submission (coming from Rustad, el at. PLoS One 3(1), e1502 (2008). The enduring hypoxic response of Mycobacterium tuberculosis) to the more recent characterization of the regulon based on CHiPseq data, reported in Minch et al. 2015. This was done to ensure coherence with the transcriptomics analyses in the new figure 4.

(4) Finally, protein interaction data is based on experiments done once without statistical analysis. If the interaction between VirR and LCP protein is expected on the mycobacterial membrane, how the SPLIT_GFP system expressed in the cytoplasm is physiologically relevant. No explanation was provided as to why VirR interacts with the truncated version of LCP proteins and not with the full-length proteins.

We have repeated the experiments and applied statistics (Figure 9). As stated in the manuscript this assay has successfully been applied to interrogate interactions of domains of proteins embedded in the membrane of mycobacteria. Therefore, we believe that this assay is valid to interrogate interactions between Lcp proteins.

Reviewer #2 (Public Review): 

Summary: 

In this work, Vivian Salgueiro et al. have comprehensively investigated the role of VirR in the vesicle production process in Mtb using state-of-the-art omics, imaging, and several biochemical assays. From the present study, authors have drawn a positive correlation between cell membrane permeability and vesiculogenesis and implicated VirR in affecting membrane permeability, thereby impacting vesiculogenesis. 

Strengths: 

The authors have discovered a critical factor (i.e. membrane permeability) that affects vesicle production and release in Mycobacteria, which can broadly be applied to other bacteria and may be of significant interest to other scientists in the field. Through omics and multiple targeted assays such as targeted metabolomics, PG isolation, analysis of Diaminopimelic acid and glycosyl composition of the cell wall, and, importantly, molecular interactions with PG-AG ligating canonical LCP proteins, the authors have established that VirR is a central scaffold at the cell envelope remodelling process which is critical for MEV production. 

We thank the reviewer for the kind assessment of the paper.

Weaknesses: 

Throughout the study, the authors have utilized a CRISPR knockout of VirR. VirR is a non-essential gene for the growth of Mtb; a null mutant of VirR would have been a better choice for the study. 

According to Tn mutant databases and CRISPR databases, virR is a non-essential gene. However, we have tried to interrupt this gene using the allelic exchange substitution approach via phages many times with no success. So far there is no precedent of a clean KO mutant in this gene. White et al., generated a virR mutant consisting of deletion of a large fragment of the c-terminal part of the protein, pretty much replicating the effect of the Tn insertion site in the virR Tn mutant. These precedents made us to switch to CRISPR technology.  

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors): 

(1) The authors monitored cell lysis by measuring the release of a cytoplasmic iron-responsive protein (IdeR). Since EV release is regulated by iron starvation, which is directly sensed by IdeR, another control (unrelated to iron) is needed. A much better approach would be to use hydrophobic/hydrophilic probes to measure changes in the cell wall envelope.

Does the VirR complemented strain have a faint IdeR band in the supernatant? The authors need to clarify. Also, it's unclear whether the complementation restored normal VirR levels or not. 

We thank the reviewer for this recommendation. Consequently, we have complemented these studies by an alternative approach based on serially diluted cultures spotted on solid medium. These results align very well with that of western blot using IdeR levels in the supernatant as a surrogate of cell lysis.

We also noticed the presence of a faint IdeR band in the supernatant of the complemented strain and suggestive of a possible cell lysis. However, as shown in other section this was not translated into increased levels of vesiculation. As previously shown in a previous paper describing VirR as a genetic determinant of vesiculogenesis, VirR levels in the complemented strains are not just restored but increased considerably. This overexpression could explain the potential artifact of a leaky phenotype in the complemented strain. In addition to that previous study, the proteomic data included in this paper clearly shows a restoration of VirR levels relative to the WT strains.

(2) Figure 2C: The data are weak; I don't see any difference in incorporating FDAAs in MM media. Even in the 7H9 medium, differences appear only at the last time point (20 h). What happens at the time point after 20 h (e.g., 48 h)? How do we differentiate between defective permeability or anabolism leading to altered PG? No statistical analysis was performed.

We apologize for the incomplete assessment of the results in this figure. First, this figure just shows differential incorporation of FDAAs in the different strains in different media. As per previous studies (Kuru et al (2017) Nat. Protocols), these probes can freely enter into cells and may be incorporated into PG by at least three different mechanisms, depending on the species: through the cytoplasmic steps of PG biosynthesis and via two distinct transpeptidation reactions taking place in the periplasm. Consequently, the differential labeling observed in virRmut relative to WT strain may be a consequence of the enlarge PG observe din the mutant. We have repeated the experiment and created new data. First, we have cultured strains with a blue FDAA (HADA) for 48 to ensure full labeling. Then, we washed cells and cultured in the presence of a second FDAA, this time green (FDL) for 5 h. The differential incorporation of FDL relative to HADA was then measured under the fluorescence microscope. This experiment showed a virRmut incorporate more FDL that the other strains, suggesting an altered PG remodeling.  modified the figure to make clearer the early and late time points of the time-course and applied statistics.

(3) Many genes (~ 1700) were deregulated in the mutant. Since these transcriptional changes do not correlate at the protein level in WCL, it's important to determine VirR-specificity. RNA-Seq of VirR complemented strain is important.

We think this was an extremely important point, and we thank the reviewer for pointing this out. Following their suggestion, we have analyzed and integrated data from the complemented strain, which we have added to the GEO submission, to conclude that, in fact, differences in expression between the complemented strain and either the WT, or virRmut are also common and highly significant. Albeit this is not completely unexpected, given the nature of our mutants and the fact that the complemented strains show significantly higher levels of expression of VirR -both at the RNA and protein levels- than the WT, it motivated us to narrow down our definition of VirR-dependent genes to adopt a combined criterium that integrated the complemented strain. Following this approach, we considered the set of genes upregulated (downregulated) in virRmut as those whose expression in that strain is, at the same time, significantly higher (lower) than in WT as well as in virRmut-Comp. Working with this integrated definition, the genes considered -399 upregulated and 502 downregulated genes- are those whose observed expression changes are more likely to be genuinely VirR-dependent rather than any non-specific consequence of the mutagenesis protocols. Despite the lower number of genes in these sets, the repetition of all our functional enrichment analyses based on this combined criterium leads us to conclusions that are largely compatible with those presented in the first version of the paper.

(4) Transcriptome data provide no clues about how VirR could mediate expression deregulation. Is there an overlap with the regulations/regulons of any Mtb transcription factors? One clue is DosR; however, DosR only regulates 50-60 genes in Mtb. 

Again, we would like to thank the reviewer for this recommendation, which we have followed accordingly to generate a new section in the results named “VirR-dependent genes intersect the regulons of key transcriptional regulators of the responses to stress, dormancy, and cell wall remodeling”. As we explain in this new section, we resorted to the regulon annotations reported in (Minch et al. 2015), where ChIP-seq data is collected on binding events between a panel of 143 transcription factors (TFs) and DNA genome-wide. The dataset includes 7248 binding events between regulators and DNA motifs in the vicinity of targets’ promoters. After completing enrichment analyses with the resulting regulons, we identified 10 transcription factors whose intersections with the sets of up and downregulated genes in virRmut were larger than expected by chance (One tailed Fisher exact test, OR>2, FDR<0.1). Those regulators -which, as guessed by the referee, included DevR-, control key pathways related with cell wall remodeling, stress responses, and transition to dormancy.

(5) How many proteins that are enriched or depleted in the EVs of the VirR mutant also affected transcriptionally in the mutant? How does VirR regulate the abundance and transport of protein in EVs? 

While the intersection between genes and proteins that appear upregulated in the virRmut strain both at transcriptional and vesicular protein levels (N=21) was found larger than expected by chance (OR=2.0 p=7.0E-3), downregulated genes and proteins in virRmut (N=14) were not enriched in each other. These results, indicated, at most, a scarce correlation between RNA and protein levels (a phenomenon nonetheless previously observed in Mycobacterium tuberculosis, among other organisms, see Cortés et al. 2013). Admittedly, the compilation of these omics data is insufficient, by itself to pinpoint the specific regulatory mechanisms through which the absence of VirR impacts protein abundance in EVs. For the sake of transparency, this has been acknowledged in the discussion section of the resubmitted version of the manuscript.

(6) The assumption that a depleted pool of methylmalonyl CoA is due to increased utilization for PDIM biosynthesis is problematic. Without flux-based measurement, we don't know if MMCoA is consumed more or produced less, more so because Acc is repressed in the VirR mutant EVs. Further, MMCoA feeds into the TCA cycle and other methyl-branched lipids. Without data on other lipids and metabolism, the depletion of MMCoA is difficult to explain.

The differential expression statistics compiled suggest that both effects may be at place, since we observed, at the same time, a downregulation of enzymes controlling methylmalonyl synthesis from propionyl-CoA (i.e. Acc, at the protein level), as well as an upregulation of enzymes related with its incorporation into DIM/PDIMs (i.e. pps genes). Both effects, combined, would favor an increased rate of methylmalonyl production, and a slower depletion rate, thus contributing to the higher levels observed. We however concur with the reviewer that fluxomics analyses will contribute to shed light on this question in a more decisive manner, and we have acknowledged this in the discussion section too.   

(7) Figure 5: Deregulation of rubredoxins and copper indicates impaired redox balance and respiration in the mutant. The data is complex to connect with permeability as TRZ is mycobactericidal and also known to affect the respiratory chain. The authors need to investigate if, in addition to permeability, the presence of VirR is essential for maintaining bioenergetics.

The data related to rubredoxins and copper has been modified after reanalyzing transcriptomic data including the complemented strain. Nevertheless, we found that some features of the response to stresses may be impaired in the mutant, including the one to oxidative stress. In this regard, we found the enhanced sensitivity of the mutant to H2O2 relative to WT and complemented strains. This piece of data is now included as Fig S3 in the new version of the manuscript.

(8) Differential regulation of DoS regulon and cholesterol growth could also be linked to differences in metabolism, redox, and respiration. What is the phenotype of VirR mutants in terms of growth and respiration in the presence of cholesterol/TRZ? 

We thank the reviewer for this suggestion. Consequently, we have added a new section to Results that suggest that other aspects of mycobacterial physiology may be affected in the virR mutant when cultured in the presence of cholesterol or TRZ: 

“Modulation of EV levels and permeability in virRmut by cholesterol and TRZ. We next wondered about the effect of culturing virRmut on both cholesterol or TRZ could have on cell growth, permeability and EV production. In the case of cholesterol, it has also been shown to affect other aspects of physiology (redox, respiration, ATP), which can directly affect permeability (Lu et al., 2017). We monitored virRmut growth cultured in MM supplemented with either glycerol, cholesterol as a sole carbon source, and TRZ at 3 ug ml-1 for 20 days. While cholesterol significantly enhanced the growth virRmut after 5 days relative to glycerol medium, supplementation of glycerol medium with TRZ restricted growth during the whole time-course (Fig S5A). The study of cell permeability in the same conditions indicated that the enhanced cell permeability observed in glycerol MM was reduced when virRmut when cultured with cholesterol as sole carbon source. Conversely, the presence of TRZ increased cell permeability relative to the medium containing solely glycerol (Fig S5C). As we have previously observed for the WT strain, either condition (Chol or TRZ) also modified vesiculation levels in the mutant accordingly (Fig S5B). These results strongly indicates that other aspects of mycobacterial physiology besides permeability are also affected in the virR mutant and may contribute to the observed enhanced vesiculation.

(9) PDIM TLC is not evident; both DimA and DImB should be clearly shown. It will also be necessary to show other methyl-branched lipids, such as SL-1 and PAT/DAT, because the increase in PDIM can take away methyl malonyl CoA from the biosynthesis of SL-1 and PAT/DAT. Studies have shown that SLI-, PAT/DAT, and PDIM are tightly regulated, where an increase in one lipid pool can affect the abundance of other lipids. Quantitative assays using 14C acetate/propionate are most appropriate for these experiments. 

We apologize for the fact that TLC analysis is not performed in a radioactive fashion. However, we do not have access to this approach. To answer reviewer question about the fact that other methyl-branched lipids may explain the altered flux of methyl malonyl CoA, we have run TLCs on all the strains tested to resolve SLs and PAT/DATs (Fig S8). Notably, we observed a reduction in the level of these lipids (SL1 or PAT/DAT) in virRmut cultured in glycerol relative to WT and complemented strains, suggesting that the excess of PDIM synthesis can take away methyl malonyl CoA from the biosynthesis of SL-1 and PAT/DAT in the absence of VirR (Fig S8B).

(10) Figure 8: Interaction between VirR and Lcp proteins. Since these interactions are happening in the membrane, using a split GFP system where proteins are expressed in the cytoplasm is unlikely to be relevant.

Also, experiments on Figure 8C are performed once, and representation needs to be clarified; split GFP needs a positive control, and negative control (CtpC) is not indicated in the figure.

We have repeated the experiments and applied statistics (Figure 9). As stated in the manuscript this assay has successfully been applied to interrogate interactions of domains of proteins embedded in the membrane of mycobacteria. Therefore, we believe that this assay is valid to interrogate interactions between Lcp proteins.

Reviewer #2 (Recommendations For The Authors):  

(1) Authors should consider making more effort to mine the omics data and integrate them. Given the amount of data that is generated with the omics, they need to be looked at together to find out threads that connect all of them. 

In the resubmitted version of the paper, we have followed reviewer´s recommendation by incorporating new analyses that integrated the virRmut-C strain, and tried to provide context to the differences found in the context of broader transcriptional regulatory networks (new figure 4), as well as in the context of metabolic pathways related with PDIM biosynthesis from methylmalonyl (figure 6I, already present in the first submission). We consider that these additions contribute to a deeper interpretation of the omics data in the line of what was suggested by the reviewer.

(2) The interpretation given by authors in lines 387-390 is an interpretation that does not have sufficient support and, hence should be moved into discussion. 

We thank the reviewer for this recommendation. We believe that these new analyses and integration studies now support the above statement.

eLife Assessment

In this important study, the authors set out to investigate the biogenesis of extracellular vesicles in mycobacteria and provide several observations to link VirR with vesiculogenesis, PG metabolism, lipid metabolism, and cell wall permeability. Whilst some of the evidence provided is convincing, there are still some shortcomings in the revised manuscript where the data to support the proposed mechanism remain incomplete. The work will be of interest to bacteriologists.

Reviewer #1 (Public review):

Summary:

The present study's main aim is to investigate the mechanism of how VirR controls the magnitude of MEV release in Mtb. The authors used various techniques, including genetics, transcriptomics, proteomics, and ultrastructural and biochemical methods. Several observations were made to link VirR-mediated vesiculogenesis with PG metabolism, lipid metabolism, and cell wall permeability. Finally, the authors presented evidence of a direct physical interaction of VirR with the LCP proteins involved in linking PG with AG, providing clues that VirR might act as a scaffold for LCP proteins and remodel the cell wall of Mtb. Since the Mtb cell wall provides a formidable anatomical barrier for the entry of antibiotics, targeting VirR might weaken the permeability of the pathogen along with the stimulation of the immune system due to enhanced vesiculogenesis. Therefore, VirR could be an excellent drug target. Overall, the study is an essential area of TB biology.

Strengths:

The authors have done a commendable job of comprehensively examining the phenotypes associated with the VirR mutant using various techniques. Application of Cryo-EM technology confirmed increased thickness and altered arrangement of CM-L1 layer. The authors also confirmed that increased vesicle release in the mutant was not due to cell lysis, which contrasts with studies in other bacterial species.

Another strength of the manuscript is that biochemical experiments show altered permeability and PG turnover in the mutant, which fits with later experiments where authors provide evidence of a direct physical interaction of VirR with LCP proteins.

Transcriptomics and proteomics data were helpful in making connections with lipid metabolism, which the authors confirmed by analyzing the lipids and metabolites of the mutant.

Lastly, using three approaches, the authors confirm that VirR interacts with LCP proteins in Mtb via the LytR_C terminal domain.

Altogether, the work is comprehensive, experiments are designed well, and conclusions were made based on the data generated after verification using multiple complementary approaches.

Weaknesses:

The major weakness is that the mechanism of VirR-mediated EV release remains enigmatic. Most of the findings are observational and only associate enhanced vesiculogenesis observed in the VirR mutant with cell wall permeability and PG metabolism. Authors suggest that EV release occurs during cell division when PG is most fragile. However, this has yet to be tested in the manuscript - the AFM of the VirR mutant, which produces thicker PG with more pore density, displays enhanced vesiculogenesis. No evidence was presented to show that the PG of the mutant is fragile, and there are differences in cell division to explain increased vesiculogenesis. These observations, counterintuitive to the authors' hypothesis, need detailed experimental verification.

Transcriptomic data only adds a little substantial. Transcriptomic data do not correlate with the proteomics data. It remains unclear how VirR deregulates transcription. TLCs of lipids are not quantitative. For example, the TLC image of PDIM is poor; quantitative estimation needs metabolic labeling of lipids with radioactive precursors. Further, change in PDIMs is likely to affect other lipids (SL-1, PAT/DAT) that share a common precursor (propionyl- CoA).

The connection of cholesterol with cell wall permeability is tenuous. Cholesterol will serve as a carbon source and contribute to the biosynthesis of methyl-branched lipids such as PDIM, SL-1, and PAD/DAT. Carbon sources also affect other aspects of physiology (redox, respiration, ATP), which can directly affect permeability and import/export of drugs. Authors should investigate whether restoration of the normal level of permeability and EV release is not due to the maintenance of cell wall lipid balance upon cholesterol exposure of the VirR mutant.

Finally, protein interaction data is based on experiments done once without statistical analysis. If the interaction between VirR and LCP protein is expected on the mycobacterial membrane, how SPLIT_GFP system expressed in the cytoplasm is physiologically relevant. No explanation was provided as to why VirR interacts with the truncated version of LCP proteins and not with the full-length proteins.

Reviewer #2 (Public review):

Summary:

In this work, Vivian Salgueiro et al. have comprehensively investigated the role of VirR in the vesicle production process in Mtb using state-of-the-art omics, imaging, and several biochemical assays. From the present study, authors have drawn a positive correlation between cell membrane permeability and vasculogenesis and implicated VirR in affecting membrane permeability, thereby impacting vasculogenesis.

Strengths:

The authors have discovered a critical factor (i.e. membrane permeability) that affects vesicle production and release in Mycobacteria, which can broadly be applied to other bacteria and may be of significant interest to other scientists in the field. Through omics and multiple targeted assays such as targeted metabolomics, PG isolation, analysis of Diaminopimelic acid and glycosyl composition of the cell wall, and, importantly, molecular interactions with PG-AG ligating canonical LCP proteins, the authors have established that VirR is a central scaffold at the cell envelope remodelling process which is critical for MEV production.

Weaknesses:

Throughout the study, the authors have utilized a CRISPR knockout of VirR. VirR is a non-essential gene for the growth of Mtb; a null mutant of VirR would have been a better choice for the study.

Comments on the revised version:

Concerns flagged about using CRISPR -guide RNA mediated knockdown of viral has yet to be addressed entirely. I understand that the authors could not get knock out despite attempts and hence they have guide RNA mediated knockdown strategy. However, I wondered if the authors looked at the levels of the downstream genes in this knockdown.

Authors have used the virmut-Comp strain for some of the experiments. However, the materials and methods must describe how this strain was generated. Given the mutant is a CRISPR-guide RNA mediated knockdown. The CRISPR construct may have taken up the L5 loci. Did authors use episomal construct for complementation? If so, what is the expression level of virR in the complementation construct? What are the expression levels of downstream genes in mutant and complementation strains? This is important because the transcriptome analysis was redone by considering complementation strain. The complemented strain is written as virmut-C or virmut-Comp. This has to be consistent.

1. Technological Innovation: Reduces costs and simplifies logistics, facilitating cross-border integration.
2. Growth of International Economic Activity: Fuels the development of global value chains.
3. Liberalization of Economic Policies: Reduces tariffs and barriers, encouraging greater international trade and investment.

RSL_codes

RSL_results

RSL_results

mudança organizacional

mudança organizacional

mudança organizacional

mudança organizacional

need for more studies

adoção

eLife Assessment

This fundamental work advances our understanding of the mechanisms underlying lactation-induced infertility. Compelling evidence supports the notion that prolactin inhibits kisspeptin activity and LH pulsatile release and that loss of this signal results in an early reestablishment of fertility during lactation. This work will be of interest to endocrinologists and reproductive biologists.

Reviewer #1 (Public review):

Summary:

In this paper, Hackwell and colleagues performed technically impressive, long-term, GCaMP fiber photometry recordings from Kiss1 neurons in the arcuate nucleus of mice during multiple reproductive states. The data show an immediate suppression of activity of arc Kiss1 neuronal activity during pregnancy that is maintained during lactation. In the absence of any apparent change in suckling stimulus or milk production, mice lacking prolactin receptors in arcuate Kiss1 neurons regained Kiss1 episodic activity and estrous cyclicity faster than control mice, demonstrating that direct prolactin action on Kiss1 neurons is at least partially responsible for suppressing fertility in this species. The effect of loss of prolactin receptors from CamK2a expressing neurons was even greater, indicating either that prolactin sensitivity in Kiss1 neurons of the RP3V contributes to lactational infertility or that other prolactin-sensitive neurons are involved. These data demonstrate the important role of prolactin in suppressing Kiss1 neuron activity and thereby fertility during the lactational period in the mouse.

Strengths:

This is the first study to monitor activity of the GnRH pulse-generating system across different reproductive states in the same animal. Another strength in the study design is that it isolated the effects of prolactin by maintaining normal lactation and suckling (assessed indirectly using pup growth curves). The study also offers insight into the phenomenon of postpartum ovulation in mice. The results showed a brief reactivation of arcuate Kiss1 activity immediately prior to parturition, attributed to falling progesterone levels at the end of pregnancy. This hypothesis will be of interest to the field and is likely to inspire testing in future studies. With the exceptions mentioned below, the conclusions of the paper are well supported by the data and the aims of the study were achieved. This paper is likely to raise the standard for technical expectations in the field and spark new interest in the direct impact of prolactin on Kiss1 neurons during lactation in other species.

Weaknesses:

A weakness in the approach is the use of genetic models that do not offer complete deletion of the prolactin receptor from targeted neuronal populations. A substantial proportion of Kiss1 neurons in both models retains the receptor. As a result, it is not clear whether the partial maintenance of cyclicity during lactation in the genetic models is due to incomplete deletion or to the involvement of other factors. In addition, results showing no impact of progesterone on LH secretion during lactation are surprising, given the effectiveness of progesterone-containing birth control in lactating women. While the authors assert their findings may reflect an important role for prolactin in lactational infertility in other mammalian species, that remains to be seen. Hyperprolactinemia is known to suppress GnRH release, but its importance in the suppression of cyclicity during the lactation is controversial. Indeed, in several species, the stimulus of suckling is considered to be the main driver of lactational fertility suppression. Data from rats shows that exogenous prolactin was unable to suppress LH release in dams deprived of their pups shortly after birth; both suckling and prolactin were necessary to suppress a post-ovariectomy rise in LH levels. The duration of amenorrhea does not correlate with average prolactin levels in humans, and suckling but not prolactin was required to suppress the postpartum rise in LH in the rhesus monkey. The protocol of this or other studies might result in discordant results; alternatively, mice may be an outlier in their mechanism of cycle suppression.

Comments on revised version:

I remain enthusiastic about this article, which has been substantially improved in this revision. However, I didn't feel the authors responded to any of the points I raised previously in my public review (see Weaknesses), for example by adding to the manuscript's discussion section. These are the larger, conceptual issues that speak to the value of the paper in the context of the existing literature. The authors could also state they feel they have addressed the issues raised sufficiently in the text.

Reviewer #2 (Public review):

Summary:

The overall goal of Eleni et al. is to determine if the suppression of LH pulses during lactation is mediated by prolactin signaling at kisspeptin neurons. To address this, the authors used GCaMP fiber photometry and serial blood sampling to reveal that in vivo episodic arcuate kisspeptin neuron activity and LH pulses are suppressed throughout pregnancy and lactation. The authors further utilized knockout models to demonstrate that the loss of prolactin receptor signaling at kisspeptin cells prevents the suppression of kisspeptin cell activity and results in the early reestablishment of fertility during lactation. The work demonstrates exemplary design and technique, and the outcomes of these experiments are sophistically discussed.

Strengths:

This manuscript demonstrates exceptional skill with powerful techniques and reveals a key role for arcuate kisspeptin neurons in maintaining lactation-induced infertility in mice. In a difficult feat, the authors used fiber photometry to map the activity of arcuate kisspeptin cells into lactation and weaning without disrupting parturition, lactation, or maternal behavior. The authors used a knockout approach to identify if the inhibition of fertility by prolactin is mediated via direct signaling at arcuate kisspeptin cells. Although the model does not perfectly eliminate prolactin receptor expression in all kisspeptin neurons, results from the achieved knockdown support the conclusion that prolactin signaling at kisspeptin neurons is required to maintain lactational infertility. The methods are advanced and appropriate for the aims, the study is rigorously conducted, and the conclusions are thoughtfully discussed.

Comments on the latest version:

All comments and suggestions have been addressed by the authors in this revision.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Recommendations For The Authors):

I recommend being explicit regarding how the animals were habituated to blood sampling.

On lines 109-111 we have added a more detailed explanation of how mice were habituated to blood sampling. This includes details that mice were held and had their tails palpated for approximately 5 minutes per day.

Were any mice excluded due to loss or movement of the implant over time? Any details to allow replication of long-term measurements like this should be included.

No mice lost their cannulas during experimentation so we have added a sentence on this on lines 303 to 304 to this effect.  We have also noted that there was a slight decrease in signal over the months of experimentation. A statement on line 318 has also been added that clarifies two mice lost between the pregnancy and lactation stages of experiment were euthanised due to dystocia.

The text states that synchronized episodic activity reappeared as early as 3 days after birth, citing Figure 6c as evidence. There is no 6c. Figure 6b shows day 5 after birth.

This has been corrected.

The methods state mRNA levels had to be "above background" to be counted as colocalization. At how many fold/what percent above background was a cell considered positive for expression?

Positive hybridisation was scored according to the manufacturer’s protocol and a statement to this effect has been added on line 144.

Please ensure figure titles or the data graphs explicitly give the genotype of the mice in all figures (or state the mice are wildtype).

Genotype has been added to figure titles where possible. Genotypes are always given in figure legends and tables and/or explicitly stated on the figure itself.

Figure 4's title states events are "perfectly" correlated, which is a subjective term. I recommend saying "consistently" or "temporally" correlated, depending on your meaning.

This has been amended to read “consistently correlated”

Reviewer #2 (Recommendations For The Authors):

The comments below aim to clarify the paper's methodology and results but do not detract from my overall enthusiasm for this work.

- Given past studies demonstrating prolactin action in the brain, particularly the MPOA/MPN, is essential for maternal behavior, can the authors please clarify why this behavior is retained in the cam2a prlr knockout mice? The authors mention that prlr in the MPOA is only knocked down 50% compared to WT controls. Is this sufficient to retain maternal behavior?

In our experience 50% Prlr in the MPOA is sufficient to retain normal maternal behaviour in most animals including the ones in this experiment (our original paper describing this showed relatively normal behavior, for example, with a vGAT and vGlut-mediated knockouts, and even a double knockout – it was only when we achieved complete KO with an AAV-Cre that we saw failure of maternal behavior – Brown et al, PNAS 3;114(40):10779-10784 2017). We have added a statement on lines 157-159 regarding this.  We have an additional paper in preparation specifically characterising the maternal behaviour and lactation outcomes in this line of mice, and we find most animals display normal maternal behaviour, with slightly impaired milk production in later lactation.

- Supplementary Figure 1. Can the authors please clarify the criteria for a cell to be positive for prlr? The methods state that the signal must be "above background level." How was the background measurement obtained? In the negative control?

As per above, scoring of positive hydribisation was done according to the manufacturer’s protocol and a statement to this effect has been added on line 144.

- Lines 310-314: This sentence describes RNAscope analysis of prlr knockdown in kisspeptin cells and refers to Extended Figure 3 - but I believe this is in Supplementary Figure 1.

This has been corrected.

- Figure 3-4: When mice return to estrous cycles, the amplitude of episodic kisspeptin neuron activity is the same as 24 hours after weaning, which appears much lower than in virgin females. Does this reach significance? If so, do the authors know why kisspeptin activity is still suppressed, and can they comment on why this may not affect estrous cyclicity?

This does not reach significance – see Supplementary Table 1 (4C) for statistics. Therefore, no further analysis was done. This question would need to be examined with a follow up experiment. Given the 5s on, 15 s off scheduled mode of recording used here, amplitude was not an extremely accurate measure and amplitude has been reported as relative within each mouse. There is also an additional issue of a gradual reduction in amplitude of signal over time in these long-term experiments – although it is true that much larger signals were detected after ovariectomy at the end of the experiment.  At present, we have not tried to interpret whether the changes in amplitude are informative.

- Fiber photometry studies: Please indicate whether a post-mortem examination of GCaMP transfection and fiber photometry placement was conducted, and what region of the ARC was imaged.

Brains from these mice were collected, however postmortem analysis of cannula placement of GCaMP6 transfection was not carried out in all mice. This was based on our experience with this method, in that the quality and characteristic pattern of activity seen, as well as corresponding LH secretion following an SE, was indicative of successful cannula placement and transfection.  Incorrectly placed cannular failed to show SEs. A trial was done with 3 mice and cannula placement was found to be in the caudal ARC (cARC) with GFP (attached to GCaMP) restricted to the cARC. A statement has been added on lines 306-313 regarding this.

- Were male mice removed before birth? Please add to the methods section if not included.

Yes, male mice were removed after a sperm plug was seen and were never present at parturition. We have inserted additional details on line 95 to this effect.

Reviewer #3 (Recommendations For The Authors):

(1) Line 172: n=7-8 per group, yet in Supplementary Figure 2, n=6 per group.

These are referring to different groups of mice. N=7-8 is referring to the group size of mice in Figure 2 that were given mifepristone or vehicle control. In contrast the Supplementary figure 2 n number refers to the mice in the pilot study. Additional n number for the pilot study has been added on line 194.

(2) Line 314: Extended = suppl; Figure 3 = 1.

This has been corrected.

(3) Line 451: Figure 6C, does not exist.

This has been corrected.

Line 590: Reference 23 could be replaced by Ordog T et al 1998 Am J Physiol 274,E665 because it is later and more relevant to the topic.

This reference has been replaced with the suggested reference.

eLife Assessment

In this useful study, Wang and colleagues investigate the potential probiotic effects of Bacillus velezensis in a murine model. They provide convincing evidence that B. velezensis limits the growth of Salmonella typhimurium in lab culture and in mice, together with beneficial effects on the microbiota. The overall presentation of the manuscript has improved and the work will be of interest to infectious disease researchers.

Reviewer #1 (Public review):

Summary:

Wang and colleagues presented an investigation of pig-origin bacteria Bacillus velezensis HBXN2020, for its released genome sequence, in vivo safety issue, probiotic effects in vitro, and protection against Salmonella infection in a murine model. Various techniques and assays are performed; the main results are all descriptive, without new insight advancing the field or a mechanistic understanding of the observed protection.

Strengths:

An extensive study on the probiotic properties of the Bacillus velezensis strain HBXN2020

Weaknesses:

The main results are descriptive without mechanistic insight. Additionally, most of the results and analysis parts are separated without a link or a story-telling way to deliver a concise message.

Now the manuscript has made appropriate and considerable improvements.

Author response:

The following is the authors’ response to the previous reviews.

Reviewer #1 (Public Review):

Summary:

Wang and colleagues presented an investigation of pig-origin bacteria Bacillus velezensis HBXN2020, for its released genome sequence, in vivo safety issue, probiotic effects in vitro, and protection against Salmonella infection in a murine model. Various techniques and assays are performed; the main results are all descriptive, without new insight advancing the field or a mechanistic understanding of the observed protection.

Thank you very much for your reading and comments our manuscript.

Strengths:

An extensive study on probiotic property of the Bacillus velezensis strain HBXN2020

Thank you very much for your reading and comments our manuscript.

Weaknesses:

The main results are descriptive without mechanistic insight. Additionally, most of the results and analysis parts are separated without a link or a story-telling way to deliver a concise message.

Thank you for your comments and suggestions on our manuscript. In later work, we will focus on exploring the antibacterial substances and bactericidal mechanisms of B. velezensis. The manuscript results and analysis sections have been extensively revised. We appreciate your review and feedback.

Reviewer #2 (Public Review):

Summary:

In this study, Wang and colleagues study the potential probiotic effects of Bacillus velezensis. Bacillus species have potential benefit to serve as probiotics due to their ability to form endospores and synthesize secondary metabolites. B. velezensis has been shown to have probiotic effects in plants and animals but data for human use are scarce, particularly with respect to salmonella-induced colitis. In this work, the authors identify a strain of B. velezensis and test it for its ability to control colitis in mice.

Thanks for the constructive comments and the positive reception of the manuscript.

Key findings:

(1) The authors sequence an isolate for B. velezensis - HBXN2020 and describe its genome (roughly 4 mb, 46% GC-content etc).

Thanks for the constructive comments and the positive reception of the manuscript.

(2) The authors next describe the growth of this strain in broth culture and survival under acid and temperature stress. The susceptibility of HBXN2020 was tested against various antibiotics and against various pathogenic bacteria. In the case of the latter, the authors set out to determine if HBXN2020 could directly inhibit the growth of pathogenic bacteria. Convincing data, indicating that this is indeed the case, are presented.

Thanks for the constructive comments and the positive reception of the manuscript.

(3) To determine the safety profile of BHXN2020 (for possible use as a probiotic), the authors infected the strain in mice and monitored weight, together with cytokine profiles. Infected mice displayed no significant weight loss and expression of inflammatory cytokines remained unchanged. Blood cell profiles of infected mice were consistent with that of uninfected mice. No significant differences in tissues, including the colon were observed.

Thanks for the constructive comments and the positive reception of the manuscript.

(4) Next, the authors tested the ability to HBXN2020 to inhibit growth of Salmonella typhimurium (STm) and demonstrate that HBXN2020 inhibits STm in a dose dependent manner. Following this, the authors infect mice with STm to induce colitis and measure the ability of HBXN2020 to control colitis. The first outcome measure was a reduction in STm in faeces. Consistent with this, HBXN2020 reduced STm loads in the ileum, cecum, and colon. Colon length was also affected by HBXN2020 treatment. In addition, treatment with HBXN2020 reduced the appearance colon pathological features associated with colitis, together with a reduction in inflammatory cytokines.

Thanks for the constructive comments and the positive reception of the manuscript.

(5) After noting the beneficial (and anti-inflammatory effects) of HBXN2020, the authors set out to investigate effects on microbiota during treatment. Using a variety of algorithms, the authors demonstrate that upon HXBN2020 treatment, microbiota composition is restored to levels akin to that seen in healthy mice.

Thanks for the constructive comments and the positive reception of the manuscript.

(6) Finally, the authors assessed the effect of using HBXN2020 as prophylactic treatment for colitis by first treating mice with the spores and then infecting with STm. Their data indicate that treatment with HBXN2020 reduced colitis. A similar beneficial impact was seen with the gut microbiota.

Thanks for the constructive comments and the positive reception of the manuscript.

Strengths:

(1) Good use of in vitro and animal models to demonstrate a beneficial probiotic effect.

Thank you very much for your reading and comments our manuscript.

(2) Most observations are supported using multiple approaches.

Thanks for the comments and the positive reception of the manuscript.

(3) Mouse experiments are very convincing.

Thanks for the comments and the positive reception of the manuscript.

Weaknesses:

(1) Whilst a beneficial effect is observed, there no investigation of the mechanism that underpins this.

Thank you for pointing this out. We apologize for any inconvenience caused by the lack of mechanism research of the manuscript. In later work, we will focus on exploring the antibacterial substances and bactericidal mechanisms of B. velezensis. Thank you for your suggestions, and we hope our response has addressed your concerns.

(2) Mouse experiments would have benefited from the use of standard anti-inflammatory therapies to control colitis. That way the authors could compare their approach of using bacillus spores that current gold standard for treatment.

We gratefully appreciate for your valuable comments. The comments improve the quality and depth of manuscript. Based on your suggestion, we have supplemented this in the revised manuscript. We appreciate your review and feedback, and have marked the updated contents in the revised manuscript.

The updated contents were presented in line 198-378 in results section of the revised manuscript.

Reviewer #3 (Public Review):

Summary:

The manuscript by Wang et al. investigates the effects of B. velezensis HBXN2020 in alleviating S. Typhimurium-induced mouse colitis. The results showed that B. velezensis HBXN2020 could alleviate bacterial colitis by enhancing intestinal homeostasis (decreasing harmful bacteria and enhancing the abundance of Lactobacillus and Akkermansia) and gut barrier integrity and reducing inflammation.

Thanks for the comments and the positive reception of the manuscript.

Strengths:

B. velezensis HBXN2020 is a novel species of Bacillus that can produce a great variety of secondary metabolites and exhibit high antibacterial activity against several pathogens. B. velezensis HBXN2020 is able to form endospores and has strong anti-stress capabilities. B. velezensis HBXN2020 has a synergistic effect with other beneficial microorganisms, which can improve intestinal homeostasis.

Thanks for the comments and the positive reception of the manuscript.

Weaknesses:

Few studies about the clinical application of Bacillus velezensis. Thus, more studies are still needed to explore the effectiveness of Bacillus velezensis before clinical application.

Thanks for your suggestion. This study serves as an exploratory investigation before the application of Bacillus velezensis. The main purpose of this study is to explore the potential of Bacillus velezensis in application. We appreciate your review and feedback and hope that our response adequately addresses your concerns.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Most of my previous comments are well addressed, here are a few examples.<br /> While in my last comment, I requested a Colitis Mouse Model, which will well resemble the diarrhea disease caused by Salmonella in mammals. The available statement is not convincing, please check https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2225501/, https://pubs.rsc.org/en/content/articlelanding/2020/fo/d0fo01017k please replace "colitis" to a normal infection model. The current statement is incorrect.

Thank you for your valuable suggestion. The comments improve the quality of manuscript. We have corrected this in the revised manuscript as suggested. We have marked the updated contents in the revised manuscript.

The updated contents were presented in line 2, 29, 38, 46, 48, 199, 204, 246, 248, 282, 307, 310, 316, 431, 433, 464, 466, 473, 494, 497, 499, 504, 513, 518, 525, 706, 710 and 735 in the revised manuscript.

Certain parts remain to be overestimated, to my knowledge, the language and logical flow should be addressed thoroughly.

Here are suggestions to improve the logical flow of the manuscript.

(1) Probiotic sampling and isolation

(2) in vitro assessment

(3) genomic sequencing and in silico safety assessment (Crit Rev Food Sci Nutr. 2023;63(32):11244-11262), which should be included as a right ref.

(4) in vivo assay for safety evaluation, but not biosafety (it has a different meaning!!)

(5) infection model and protection assay.

We gratefully appreciate for your valuable comments. The comments improve the quality and depth of manuscript. According to your suggestion, we do our best to correct those problems in the revised manuscript. We would like to express our apologies once again and hope that the revised manuscript meets your expectations. We have marked the updated contents in the revised manuscript.

Also, please pay attention to the logical link or transition sentences between each part to connect the dots in each part.

We gratefully appreciate for your valuable comments. The comments improve the quality of manuscript. According to your suggestion, we have corrected this in the revised manuscript. We have marked the updated contents in the revised manuscript. 

Finally, there are also lots of typos and errors, please improve through the text.<br /> For example, Line 521. "Stain", and more...

Thanks for pointing this out. Based on your suggestion, we have corrected in the revised manuscript. We have marked the updated contents in the revised manuscript.

The updated contents were presented in line 753, 1055, 1087 in the revised manuscript.

Reviewer #2 (Recommendations For The Authors):

The revised manuscript by Wang and colleagues attempts to address concerns raised during the first round of review.

All minor comments have been addressed and in general, the major concerns have been partially addressed in the revised manuscript.

The outstanding concerns relate to the mechanistic basis of the observations. The authors made no attempt to address this in a meaningful manner. Secondly, the issue of comparing the responses to what would be standard therapy (such as anti-inflammatories) was also handled in a somewhat dismissive manner, referring to other ongoing/future work. The clinical utility of the findings are hard to ascertain if there is no comparison to the current gold standard therapeutic approach.

I have no further suggestions for the authors, save for those previously made.

Thank you for pointing this out. We apologize for any inconvenience caused by the lack of mechanism research of the manuscript. In later work, we will focus on exploring the antibacterial substances and bactericidal mechanisms of B. velezensis. Thank you for your suggestions, and we hope our response has addressed your concerns.

Secondly, About the comparative trial of oral bacillus spore treatment with the current gold standard for treatment, we have supplemented this in the revised manuscript. We appreciate your review and feedback, and have marked the updated contents in the revised manuscript.

The updated contents were presented in line 198-378 in results section of the revised manuscript.

Reviewer #3 (Recommendations For The Authors):

This is a revision, they have addressed all my concerns, and now it is acceptable.

Thank you very much for your comments and recognition of the manuscript.

A tutoring dashboard is both important for students and teachers, it is a guidance leading students to find information they need, and help them understand tasks better. Also, it can show them separated parts in a visual way.

Somehow, I think it's the one of the most important element in the online course, because it can tell learners the timeline and tasks exactly, which can help them keep things streamlined. And also, it's the basic logic of a course, no matter what kind of course it is, these elements should be there.

With R version 4.2.2 or greater and Stargazer version 5.2.3, this code doesn't work. You have to put all the models in a list first and use the list as the first argument of the stargazer command. all_models <- list(fat_mod1,fat_mod2,fat_mod3,fat_mod4,fat_mod5,fat_mod6,fat_mod7)

stargazer(all_models, digits = 3, header = FALSE, type = "text", se = rob_se, title = "Linear Panel Regression Models of Traffic Fatalities due to Drunk Driving", model.numbers = FALSE, column.labels = c("(1)", "(2)", "(3)", "(4)", "(5)", "(6)", "(7)"))

The logic of this command is not clear. if either "jail" or "service" is "yes", why is the label for punish "no"?

eLife Assessment

This study reports the fundamental discovery of a novel structure in the developing gut that acts as a midline barrier between left and right asymmetries. Some of the evidence supporting the dynamics, composition, and function of this novel basement membrane in the chick is solid, some is even convincing, but investigation of its origin and impact on asymmetric organogenesis remains challenging and is not yet conclusive. This careful work is of broad relevance to patterning mechanisms, the importance of the extracellular matrix, and laterality disorders.

Joint Public Review:

When the left-right asymmetry of an animal body is established, a barrier that prevents the mixing of signals or cells across the midline is essential. Such midline barrier preventing the spreading of asymmetric Nodal signaling during early left-right patterning has been identified. However, midline barriers during later asymmetric organogenesis have remained largely unknown, except in the brain. In this study, the authors discovered an unexpected structure in the midline of the developing midgut in the chick. Using immunofluorescence, they convincingly show the chemical composition of this midline structure as a double basement membrane and its transient existence during the left-right patterning of the dorsal mesentery, that authors showed previously to be essential for forming the gut loop and guiding local vasculogenesis. Labelling experiments demonstrate a physical and chemical barrier function, to cell mixing and signal diffusion in the dorsal mesentery. Cell labelling and graft experiments rule out a cellular composition of the midline from dorsal mesenchyme or endoderm origin and rule out an inducing role by the notochord. Based on laminin expression pattern and Ntn4 resistance, the authors propose a model, whereby the midline basement membrane is progressively deposited by the descending endoderm. Observations of a transient midline basement membrane in the veiled chameleon suggest a conserved mechanism in birds and reptiles.

Laterality defects encompass severe malformations of visceral organs, with a heterogenous spectrum that remains poorly understood, by lack of knowledge of the different players of left-right asymmetry. This fundamental work significantly advances our understanding of left-right asymmetric organogenesis, by identifying an organ-specific and stage-specific midline barrier. The complexities of basement membrane assembly, maintenance and function are of importance in several other contexts, as for example in the kidney and brain. Thus, this original work is of broad interest.

Overall, reviewers refer to a strong and elegant paper discovering a novel midline structure, combining classic but challenging techniques, and well thought tools, to show the dynamics, chemical and physical properties of the midline. Reviewers also indicate that further work will be necessary to conclude on the origin and impact of the midline for asymmetric organogenesis. They acknowledge that this is currently technically challenging and that authors have made several attempts to answer these questions by different means. The article includes an interesting discussion about these points and the mechanism of midline breakdown.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1:

Summary:

Left-right asymmetry in the developing embryo is important for establishing correct lateralisation of the internal organs, including the gut. It has been shown previously that the dorsal mesentery (DM), which supports looping of the endodermal gut tube during development, is asymmetric with sharp delineation of left and right domains prior to gut looping. The authors set out to investigate the nature of the midline barrier that separates the left and right sides of the DM. They identify a transient basement membrane-like structure which is organised into two layers between the notochord and descending endoderm. In the time window when this basement membrane structure exists, there is no diffusion or cell mixing between the left and right sides of the DM, but once this structure starts breaking down, mixing and diffusion occur. This suggests it acts as a barrier, both physical and chemical, between left and right at the onset of gut lateralisation.

Strengths:

The authors identify a new midline structure that likely acts as a barrier to facilitate left and right separation during early organogenesis. This is an interesting addition to the field of laterality, with relevance to laterality-related disorders including heterotaxia, and may represent a gut-specific mechanism for establishing and maintaining early left-right asymmetry. The structure of this midline barrier appears to be an atypical basement membrane, comprising two adjacent basement membranes. The complexities of basement membrane assembly, maintenance, and function are of importance in almost all organismal contexts. Double basement membranes have been previously reported (for example in the kidney glomeruli as the authors note), and increasing evidence suggests that atypical basement membrane organisation or consideration is likely to be more prevalent than previously appreciated. Thus this work is both novel and broadly interesting.

The data presented are well executed, using a variety of well-established methods. The characterisation of the midline barrier at the stages examined is extensive, and the data around the correlation between the presence of the midline barrier and molecular diffusion or cell mixing across the midline are convincing.

Weaknesses:

The study is rather descriptive, and the authors' hypotheses around the origins of the midline barrier are speculative and not experimentally demonstrated. While several potential origins of the midline are excluded raising interesting questions about the timing and cell-type-specific origin of the midline basement membrane, these remain unanswered which limits the scope of the paper.

We extend our appreciation to Reviewer #1 for their thoughtful and comprehensive evaluation of our work, recognizing the considerable time and effort they dedicated to our work. We agree that functional data would significantly strengthen our understanding of the midline barrier and its exact role during LR asymmetric gut development. However, we would like to note that repeated and diligent attempts to perturb this barrier were made using various strategies, such as in vivo laser ablation, diphtheria toxin, molecular disruption (Netrin 4), and enzymatic digestion (MMP2 and MMP9 electroporation) but we observed no significant effect or stable disruption of the midline. We acknowledge and accept this limitation and hope that our discovery will invite future investigations and perturbation of this novel midline structure.

For example, it is unclear whether the two basement membranes originally appear to be part of a single circular/spherical structure (which looks possible from the images) that simply becomes elongated, or whether it is indeed initially two separate basement membranes that extend.

We favor the hypothesis that the elongation of the preexisting small circular structure to an extended double membrane of relatively increased length would be unlikely without continued contribution of new basement membrane components. However, our attempts to label and trace the basement membrane of the endoderm using tagged laminins (LAMB1-GFP, LAMB1-His, and LAMC1-His), and more recently tagged nidogen constructs (NID1-GFP and NID1-mNG) have met with export issues (despite extensive collaboration with experts, Drs. Dave Sherwood and Peter Yurchenco). As such, it remains difficult to differentiate between the two possibilities suggested. We also believe this is an important question and will continue to investigate methods to trace it.

There is a substantial gap between the BMs at earlier stages before the endoderm has descended - is this a lumen, or is it filled with interstitial matrix?

Our preliminary studies indicate that the gap enclosed by the basement membranes in the early midline structure does have extracellular matrix present, such as fibrillin-2 (see Author response image 1). Also, the electron microscopy shown in Fig. 2 C’’ supports that the space between the notochord and endoderm has fibrillar matrix.

Author response image 1.

The authors show where this basement membrane does not originate from, but only speculate on its origin. Part of this reasoning is due to the lack of Lama1-expressing cells either in the early midline barrier before it extends, or in the DM cells adjacent to it. However, the Laminin observed in the midline could be comprised of a different alpha subtype for example, that wasn't assessed (it has been suggested that the Laminin antibody used in this study is not specific to the alpha-1 subunit, see e.g. Lunde et al, Brain Struct Funct, 2015).

We appreciate this comment and have tried other laminin RNA probes that showed similar lack of midline expression (Lama1, lama3, lama5). Importantly, the laminin alpha 1 subunit is a component of the laminin 111 heterotrimer, which along with laminin 511 is the first laminin to be expressed and assemble in embryonic basement membranes, as reviewed in Yurchenco 2011. Laminin 111 is particularly associated with embryonic development while laminins 511/521 become the most widespread in the adult (reviewed in Aumailley 2013). It is likely that the midline contains laminin 111 based on our antibody staining and the accepted importance and prevalence of laminin 111 in embryonic development. However, it is indeed worth noting that most laminin heterotrimers contain beta 1, gamma 1, or both subunits, and due to this immunological relation laminin antibody cross reactivity is certainly known (Aumailley 2013). As such, while laminin 511 remains a possibility as a component of the midline BM, our lama5 in situs have shown no differential expression at the midline of the dorsal mesentery (see Author response image 2), and as such we are confident that our finding of no local laminin transcription is accurate. Additionally, we will note that the study referenced by the Reviewer observed cross reactivity between the alpha 1 and alpha 2 subunits. Laminin 211/221 is an unlikely candidate based on the embryonic context, and because they are primarily associated with muscle basement membranes (Aumailley 2013). In further support, we recently conducted a preliminary transcriptional profile analysis of midline cells isolated through laser capture microdissection (LCM), which revealed no differential expression of any laminin subunit at the midline. Please note that these data will be included as part of a follow-up story and falls beyond the scope of our initial characterization.

Author response image 2.

Similarly, the authors show that the midline barrier breaks down, and speculate that this is due to the activity of e.g. matrix metalloproteinases, but don't assess MMP expression in that region.

This is an important point, as the breakdown of the midline is unusually rapid. Our MMP2 RNA in situ hybridization at HH21, and ADAMTS1 (and TS9) at HH19-21 indicates no differential activity at the midline (see Author response images 3 and 4). Our future focus will be on identifying a potential protease that exhibits differential activity at the midline of the DM.

Author response image 3.

Author response image 4.

The authors suggest the (plausible) hypothesis that the descent of the endoderm pulls or stretches the midline barrier out from its position adjacent to the notochord. This is an interesting possibility, but there is no experimental evidence to directly support this. Similarly, while the data supporting the barrier function of this midline is good, there is no analysis of the impact of midline/basement membrane disruption demonstrating that it is required for asymmetric gut morphogenesis. A more functional approach to investigating the origins and role of this novel midline barrier would strengthen the study.

Yes, we fully agree that incorporating functional data would immensely advance our understanding of the midline barrier and its crucial role in left-right gut asymmetry. However, our numerous efforts to perturb this barrier have encountered technical obstacles. For instance, while perturbing the left and right compartments of the DM is a routine and well-established procedure in our laboratory, accessing the midline directly through similar approaches has been far more challenging. We have made several attempts to address this hurdle using various strategies, such as in vivo laser ablation, diphtheria toxin, molecular disruption (Netrin 4), and enzymatic digestion (MMP2 and MMP9 electroporation). Despite employing diverse approaches, we have yet to achieve effective and interpretable perturbation of this resilient structure. We acknowledge this limitation and remain committed to developing methods to disrupt the midline in our current investigations. We again thank Reviewer #1 for the detailed feedback on our manuscript, guidance, and the time taken to provide these comments.

Recommendations For The Authors:

Using Laminin subunit-specific antibodies, or exploring the mRNA expression of more laminin subunits may support the argument that the midline does not derive from the notochord, endoderm, or DM.

As mentioned above, RNA in situ hybridization for candidate genes and a preliminary RNA-seq analysis of cells isolated from the dorsal mesentery midline revealed no differential expression of any laminin subunits.

Similarly, expression analysis of Laminin-degrading MMPs, and/or application of an MMP inhibitor and assessment of midline integrity could strengthen the authors' hypothesis that the BM is actively and specifically broken down.

Our MMP2 RNA in situ hybridization at HH21, and ADAMTS1 at HH19-21shows no differential expression pattern at the midline of the DM (see Author response image 3). We have not included these data in the revision, but future work on this topic will aim at identifying a protease that is differentially active at the midline of the DM.

Functionally testing the role of barrier formation in regulating left-right asymmetry or the role of endoderm descent in elongating the midline barrier would be beneficial. Regarding the former, the authors show that Netrin4 overexpression is insufficient to disrupt the midline, but perhaps overexpression of e.g. MMP9 prior to descent of the endoderm would facilitate early degradation of the midline, and the impact of this on gut rotation could be assessed.

Unfortunately, MMP9 electroporation has produced little appreciable effect. We acknowledge that the lack of direct evidence for the midline’s role in regulating left-right asymmetry is a shortcoming, but current work on this subject aims to define the midline’s function to LR asymmetric morphogenesis.

Reviewer #2:

When the left-right asymmetry of an animal body is established, the barrier that prevents the mixing of signals or cells across the midline is essential. The midline barrier that prevents the mixing of asymmetric signals during the patterning step has been identified. However, a midline barrier that separates both sides during asymmetric organogenesis is unknown. In this study, the authors discovered the cellular structure that seems to correspond to the midline in the developing midgut. This midline structure is transient, present at the stage when the barrier would be required, and composed of Laminin-positive membrane. Stage-dependent diffusion of dextran across the midline (Figure 6) coincides with the presence or absence of the structure (Figures 2, 3). These lines of indirect evidence suggest that this structure most likely functions as the midline barrier in the developing gut.

We extend our gratitude to Reviewer #2 for their thoughtful assessment of our research and for taking the time to provide these constructive comments. We are excited to report that we have now included additional new data on midline diffusion using BODIPY and quantification method to further support our findings on the midline's barrier function. While our data on dextran and now BODIPY both indirectly suggests barrier function, we aspire to perturb the midline directly to assess its role in the dorsal mesentery more conclusively. However, our numerous efforts to perturb this barrier have encountered technical obstacles. For instance, while perturbing the left and right compartments of the DM is a routine and well-established procedure in our laboratory, accessing the midline directly through similar approaches has been far more challenging. We have made several attempts to address this hurdle using various strategies, such as in vivo laser ablation, diphtheria toxin, molecular disruption (Netrin 4), and enzymatic digestion (MMP2 and MMP9 electroporation). Despite employing diverse approaches, we have yet to achieve effective and interpretable perturbation of this resilient structure. Moving forward, our focus is on identifying an effective means of perturbation that can offer direct evidence of barrier function.

Recommendations For The Authors:

(1) It would be much nicer if the requirement of this structure for asymmetric morphogenesis was directly tested. However, experimental manipulations such as ectopic expression of Netrin4 or transplantation of the notochord were not able to influence the formation of this structure (these results, however, suggested the mechanism of the midline formation in the gut dorsal mesentery). Therefore, it seems not feasible to directly test the function of the structure, and this should be the next issue.

We fully agree that the midline will need to be perturbed to fully elucidate its role in asymmetric gut morphogenesis. As noted, multiple attempts were ineffective at perturbing this structure. Extensive current work on this topic is dedicated to finding an effective perturbation method.

(2) Whereas Laminin protein was present in the double basement membrane at the midline, Laminin mRNA was not expressed in the corresponding region (Fig. 4A-C). It is necessary to discuss (with experimental evidence if available) the origin of Laminin protein.

As we have noted, the source of laminin and basement membrane components for the midline remains unclear - no local transcription and the lack of sufficiency of the notochord to produce a midline indicates that the endoderm to be a likely source of laminin, as we have proposed in our zippering endoderm model. We will note that Fig. 4A-C indicate that laminin is in fact actively transcribed in the endoderm. Currently, attempts to trace the endodermal basement membrane using tagged laminins (LAMB1-GFP, LAMB1-His, and LAMC1-His), and more recently tagged nidogen constructs (NID1-GFP and NID1-mNG) have met with export issues (despite extensive collaboration with experts, Drs. Dave Sherwood and Peter Yurchenco). Confirmation of our proposed endodermal origin model is a goal of our ongoing work.

(3) Figure 4 (cell polarity from GM130 staining): addition of representative GM130 staining images for each Rose graph (Figure 4E) would help. They can be shown in Supplementary Figures. Also, a graph for the right coelomic epithelium in Fig. 4E would be informative.

We have added the requested GM130 images in our Supplemental Figures (please refer to Fig. S4ABB’) and modified the main Fig. 4E to include a rose graph for the polarity of the right coelomic epithelium.

(4) Histological image of HH19 DM shown in Fig. 2J looks somehow different from that shown in Fig. 3F. Does Fig. 2J represent a slightly earlier stage than Fig. 3F?

Figure 2J and Figure 3F depict a similar stage, although the slight variation in the length of the dorsal mesentery is attributed to the pseudo time phenomenon illustrated in Figure 3J-J’’’. This implies that the sections in Figure 2J and Figure 3F might originate from slightly different positions along the anteroposterior axis. Nonetheless, these distinctions are minimal, and based on the dorsal mesentery's length in Figure 2J, the midline is likely extremely robust regardless of this minor pseudo time difference.

Reviewer #3:

Summary:

The authors report the presence of a previously unidentified atypical double basement membrane (BM) at the midline of the dorsal mesentery (DM) during the establishment of left-right (LR) asymmetry. The authors suggest that this BM functions as a physical barrier between the left and the right sides of the DM preventing cell mixing and ligand diffusion, thereby establishing LR asymmetry.

Strengths:

The observation of the various components in the BM at the DM midline is clear and convincing. The pieces of evidence ruling out the roles of DM and the notochord in the origin of this BM are also convincing. The representation of the figures and the writing is clear.

Weaknesses:

The paper's main and most important weakness is that it lacks direct evidence for the midline BM's barrier and DM LR asymmetry functions.

We thank Reviewer #3 for their thoughtful and comprehensive evaluation of our work, recognizing the considerable time and effort they dedicated to assessing our study. We fully agree that incorporating functional data would immensely advance our understanding of the midline barrier and its crucial role in left-right gut asymmetry. However, several distinct attempts at perturbing this barrier have encountered technical obstacles. While our laboratory routinely perturbs the left and right compartments of the DM via DNA electroporation and other techniques, directly perturbing the midline using these methods is far more challenging. We have made diligent attempts to address this using various strategies, such as in vivo laser ablation, diphtheria toxin, molecular disruption (Netrin 4), and enzymatic digestion (MMP2 and MMP9 electroporation). However, we have not yet been able to identify a means of producing consistent and interpretable perturbation of the midline. We acknowledge this limitation and remain committed to developing methods to disrupt the midline in our current investigations.

Recommendations For The Authors:

Major:

(1) We suggest the authors test their hypotheses i.e., physical barrier and proper LR asymmetry establishment by the midline BM, by disrupting it using techniques such as physical ablation, over-expression of MMPs, or treatment with commercially available enzymes that digest the BM.

As above, efforts involving physical ablation and MMP overexpression have not yielded significant effects on the midline thus far. Moving forward, investigating the midline's role in asymmetric morphogenesis will necessitate finding a method to perturb it effectively. In pursuit of progress on this critical question, we recently conducted laser capture microdissection (LCM) and RNA-sequencing of the midline to unravel the mechanisms underlying its formation and potential disruption. This work shows promise but it is still in its early stages; validating it will require significant time and effort, and it falls outside the scope of the current manuscript.

(2) Lefty1's role in the midline BM was ruled out by correlating lack of expression of the gene at the midline during HH19 when BM proteins expression was observed. Lefty1 may still indirectly or directly trigger the expression of these BM proteins at earlier stages. The only way to test this is by inhibiting lefty1 expression and examining the effect on BM protein localization.

We have added a section to discuss the potential of Lefty1 inhibition as a future direction. However, similar to perturbing global Nodal expression, interpreting the results of Lefty1 inhibition could be challenging. This is because it may not specifically target the midline but could affect vertebrate laterality as a whole. Despite this complexity, we acknowledge the value of such an experiment and consider it worth pursuing in the future.

(3) Using a small dextran-based assay, the authors conclude that diffusible ligands such as cxcl2 and bmp4 do not diffuse across the midline (Figure 6). However, dextran injection in this system seems to label the cells, not the extracellular space. The authors measure diffusion, or the lack thereof, by counting the proportion of dextran-labeled cells rather than dextran intensity itself. Therefore, This result shows a lack of cell mixing across the midline (already shown in Figure 2 ) rather than a lack of diffusion.

We should emphasize that the dextran-injected embryos shown in Fig. 6 D-F were isolated two hours post-injection, a timeframe insufficient for cell migration to occur across the DM (Mahadevan et al., 2014). We also collected additional post-midline stage embryos ten minutes after dextran injections - too short a timeframe for significant cellular migration (Mahadevan et al., 2014). Importantly, the fluorescent signal in those embryos was comparable to that observed in the embryos in Fig. 6. Thus, we believe the movement of fluorescent signal across the DM when the barrier starts to fragment (HH20-HH23) is unlikely to represent cell migration. More than a decade of DNA electroporation experiments of the left vs. right DM by our laboratory and others have never indicated substantial cell migration across the midline (Davis et al., 2008; Kurpios et al., 2008; Welsh et al., 2013; Mahadevan et al., 2014; Arraf et al. 2016; Sivakumar et al., 2018; Arraf et al. 2020; and Sanketi et al., 2022). This is also shown in our current GFP/RFP double electroporation data in Fig. 2 G-H, and DiI/DiO labeling data in Fig. 2 E-G. Collectively, our experiments suggest that the dextran signal we observed at HH20 and HH23 is likely not driven by cell mixing.

To further strengthen this argument, we now have additional new data on midline diffusion using BODIPY diffusion and quantification method to support our findings on the midline's function against diffusion (please refer to New Fig. 6H-M). Briefly, we utilized a BODIPY-tagged version of AMD3100 (Poty et al., 2015) delivered via soaked resin beads surgically inserted into the left coelomic cavity (precursor to the DM). The ratio of average AMD3100-BODIPY intensity in the right DM versus the left DM was below 0.5 when the midline is intact (HH19), indicating little diffusion across the DM (Fig. 6J). At HH21 when no midline remains, this ratio significantly rises to near one, indicating diffusion of the drug is not impeded when the midline basement membrane structure is absent. Collectively, these data suggest that the basement membrane structure at the midline forms a transient functional barrier against diffusion.

(4) Moreover, in a previous study (Mahadevan et al., Dev Cell., 2014), cxcl2 and bmp4 expression was observed on both the left and right side before gut closure (HH17, when midline BM is observed). Then their expression patterns were restricted on the left or right side of DM at around HH19-20 (when midline BM is dissociated). The authors must explain how the midline BM can act as a barrier against diffusible signals at HH-17 to 19, where diffusible signals (cxcl12 and bmp4) were localized on both sides.

We appreciate the Reviewer's invitation to clarify this crucial point. Early in dorsal mesentery (DM) formation, genes like Cxcl12 (Mahadevan et al., Dev Cell 2014) and Bmp4 (Sanketi et al., Science 2021) exhibit symmetry before Pitx2 expression initiates on the left (around ~HH18, Sanketi et al., 2021). Pitx2 then inhibits BMP4 (transcription) and maintains Cxcl12 (mRNA) expression on the left side. The loss of Cxcl12 mRNA on the right is due to the extracellular matrix (ECM), particularly hyaluronan (Sivakumar et al., Dev Cell 2018). Our hypothesis is that during these critical stages of initial DM asymmetry establishment, the midline serves as a physical barrier against protein diffusion to protect this asymmetry during a critical period of symmetry breaking. Although some genes, such as Pitx2 and Cxcl12 continue to display asymmetric transcription after midline dissolution (Cxcl12 becomes very dynamic later on – see Mahadevan), it's crucial to note that the midline's primary role is preventing protein diffusion across it, akin to an insurance policy. Thus, the absence of the midline barrier at HH21 does not result in the loss of asymmetric mRNA expression. We think its primary function is to block diffusible factors from crossing the midline at a critical period of symmetry breaking. We acknowledge that confirming this hypothesis will necessitate experimental disruption of the midline and observing the consequent effects on asymmetry in the DM. This remains central to our ongoing research on this subject.

(5) On page 11, lines 15-17, the authors mention that "We know that experimentally mixing left and right signals is detrimental to gut tilting and vascular patterning-for example, ectopic expression of pro-angiogenic Cxcl12 on the right-side results in an aberrant vessel forming on the right (Mahadevan et al., Dev Cell., 2014)". In this previous report from the author's laboratory, the authors suggested that ectopic expression of cxcl12 on the right side induced aberrant formation of the vessel on the right side, which was formed from stage HH17, and the authors also suggested that the vessel originated from left-sided endothelial cells. If the midline BM acts as a barrier against the diffusible signal, how the left-sided endothelial cells can contribute to vessel formation at HH17 (before midline BM dissociation)?

To address this point, we suggest directing the Reviewer to previously published supplemental movies of time-lapse imaging, which clearly illustrate the migration path of endothelial cells from left to right DM (Mahadevan et al., Dev Cell 2014). While the Reviewer correctly notes that ectopic induction of Cxcl12 on the right induces left-to-right migration, it's crucial to highlight that these cells never cross the midline. Instead, they migrate immediately adjacent to the tip of the endoderm (please also refer to published Movies S2 and S3). We observe this migration pattern even in wild-type scenarios during the loss of the endogenous right-sided endothelial cords, where some endothelial cells from the right begin slipping over to the left around HH19-20 (over the endoderm), as the midline is beginning to fragment, but never traverse the midline. We attribute this migration pattern to a dorsal-to-ventral gradient of left-sided Cxcl12 expression, as disrupting this pattern perturbs the migration trajectory (Mahadevan).

6) It is unclear how continuous is the midline BM across the anterior-posterior axis across the relevant stages. Relatedly, it is unclear how LR segregated the cells are, across the anterior-posterior axis across the relevant stages.

We refer the reviewer to Fig. 3J-K, in which the linear elongation of the midline basement membrane structure is shown and measured at HH19 in three embryos from the posterior of the embryo to the anterior point at which the midline is fragmented and ceases to be continuous. Similarly, Fig. S2 shoes the same phenomenon in serial sections along the length of the anterior-posterior (AP) axis at HH17, also showing the continuity of the midline. All our past work at all observed sections of the AP axis has shown that cells do not move across the midline as indicated by electroporation of DNA encoding fluorescent reporters (Davis et al. 2008, Kurpios et al. 2008, Welsh et al. 2013, Mahadevan et al. 2014, Sivakumar et al. 2018, Sanketi et al. 2022), and is shown again in Fig. 2 E-H. As noted previously, very few endothelial cells cross the midline at a point just above the endoderm (image above) when the right endothelial cord remodels (Mahadevan et al. 2014), but this is a limited phenomenon to endothelial cells and cells of the left and right DM are fully segregated as previously established.

Minor comments:

(1) The authors found that left and right-side cells were not mixed with each other even after the dissociation of the DM midline at HH21 (Fig2 H). And the authors also previously mentioned that N-cadherin contributes to cell sorting for left-right DM segregation (Kurpios et al., Proc Natl Acad Sci USA., 2008). It could be a part of the discussion about the difference in tissue segregation systems before or after the dissociation of DM midline.

We appreciate this thoughtful suggestion. N-cadherin mediated cell sorting is key to the LR asymmetry of the DM and gut tilting, and we believe it underlies the observed lack of cell mixing from left and right DM compartments after the midline fragments. We have added a brief section to the discussion concerning the asymmetries in N-cadherin expression that develop after the midline fragments.

(2) Please add the time point on the images (Fig3 C, D, Fig 6A and B)

We have updated these figures to provide the requested stage information.

(3) The authors suggested that the endoderm might be responsible for making the DM BM midline because the endoderm links to DM midlines and have the same resistance to NTN4. The authors mentioned that the midline and endoderm might have basement membranes of the same "flavor." However, perlecan expression was strongly expressed in the midline BM compared with the endodermal BM. It could be a part of the discussion about the difference in the properties of the BM between the endoderm and DM midline.

Perlecan does indeed localize strongly to the endoderm as well as the midline. The HH18 image included in prior Fig. S3 B’, B’’ appears to show atypically low antibody staining in the endoderm for all membrane components. Perlecan is an important component for general basement membrane assembly, and the bulk of our HH18 and HH19 images indicate strong staining for perlecan in both midline and endoderm. Perlecan staining at the very earliest stages of midline formation also indicate perlecan in the endoderm as well, supporting the endoderm as a potential source for the midline basement membrane. We have updated Fig. S3 to include these images in our revision.

(4) The authors investigated whether the midline BM originates from the notochord or endoderm, but did not examine a role for endothelial cells and pericytes surrounding the dorsal aorta (DA). In Fig S1, Fig S2, and FigS3, the authors showed that DA is very close to the DM midline basement membrane, so it is worth checking their roles.

We fully agree that the dorsal aorta and the endothelial cords that originate from the dorsal aorta may interact with the midline in important ways. However, accessing the dorsal aorta for electroporation or other perturbation is extremely difficult. Additionally, the basement membrane of vascular endothelial cells has a distinct composition from a non-vascular basement membrane. Vascular endothelial cells produce only alpha 4 and alpha 5 laminin subunits but contain no alpha 1 subunit in any known species (reviewed in DiRusso et al., 2017). Thus, endothelial cell-derived basement membranes would not contain the alpha 1 laminin subunit that we used in our studies as a robust marker of the midline basement membrane. Additionally, no fibronectin is found in the midline basement membrane, while it is enriched in the dorsal aorta (see Supplemental Figure 3CC’C’’). We will briefly note that our preliminary data in quail tissue indicates that QH1+ cord cells (i.e. endothelial cells) sometimes exhibit striking contact with the midline along the dorso-ventral length of the DM, suggesting not an origin but an important interaction.

Reviewer #4 (Recommendations For The Authors):

Major comments:

(1) The descending endoderm zippering model for the formation of the midline lacks evidence.

We have attempted to address this issue by introducing several tagged laminin constructs (LAMB1-GFP, LAMB1-His, LAMC1-His), and more recently tagged nidogen plasmids (NID1-GFP and NID1-mNG) to the endoderm via DNA electroporation to try to label the source of the basement membrane. Production of the tagged components occurred but no export was observed in any case (despite extensive collaboration with experts in this area, Drs. Dave Sherwood and Peter Yurchenco). This experiment was further complicated by the necessary large size of these constructs at 10-11kb due to the size of laminin subunit genes, resulting in low electroporation efficiency. We also believe this is an important question and are continuing to investigate methods to trace it.

The midline may be Ntn4 resistant until it is injected in the source cells.

Ntn4 has been shown to disrupt both assembling and existing basement membranes (Reuten et al. 2016). Thus, we feel that the midline and endodermal basement membranes’ resistance to degradation is not determined by stage of assembly or location of secretion.

Have you considered an alternative origin from the bilateral dorsal aorta or the paraxial mesoderm, which would explain the double layer as a meeting of two lateral tissues? The left and right paraxial mesoderm seem to abut in Fig. S1B-C and S2E, and is laminin-positive in Fig 4A'. What are the cells present at the midline (Fig.4D-E)? Are they negative for the coelomic tracing, paraxial or aortic markers?

We fully agree that alternate origins of the midline basement membrane cannot be ruled out from our existing data. We agree and have considered the dorsal aorta and even the endothelial cords that originate from the dorsal aorta. However, accessing the dorsal aorta for electroporation or other perturbation is extremely difficult. Importantly, the basement membrane of vascular endothelial cells has a distinct composition from a non-vascular basement membrane. Vascular endothelial cells produce only alpha 4 and alpha 5 laminin subunits but contain no alpha 1 subunit in any known species (reviewed in Hallmann et al. 2005). Thus, endothelial cell-derived basement membranes would not contain the alpha 1 laminin subunit that we used in our studies as a robust marker of the midline basement membrane. Note in Fig. 3 E-H that our laminin alpha 1 antibody staining does not label the aortae. Additionally, no fibronectin is found in the midline basement membrane, while it is enriched in the dorsal aorta (see Supplemental Figure 3CC’C’’). We will briefly note that our preliminary data in quail tissue indicates that QH1+ cord cells (i.e. endothelial cells) sometimes exhibit striking contact with the midline along the dorso-ventral length of the DM, suggesting not an origin but an important interaction. Moreover, at the earliest stages of midline basement membrane emergence, the dorsal aortae are distant from the nascent basement membrane, as are the somites, which have not yet undergone any epithelial to mesenchymal transition. Fig. S2G provides an example of an extremely early midline basement membrane without dorsal aorta or somite contact. S2G is from a section of the embryo that is fairly posterior in the embryo, it is thus less developed in pseudo-time and gives a window on midline formation in very early embryos.

(2) The importance of the midline is inferred from previously published data and stage correlations but will require more direct evidence. Can the midline be manipulated with Hh signaling or MMPs?

We agree that direct evidence in the form of midline perturbation will be critically required. As previously noted, our numerous efforts to perturb this barrier have encountered technical obstacles. For instance, while perturbing the left and right compartments of the DM is a routine and well-established procedure in our laboratory, accessing the midline directly through similar approaches has been far more challenging. We have made several attempts to address this hurdle using various strategies, such as in vivo laser ablation, diphtheria toxin, molecular disruption (Netrin 4), and enzymatic digestion (MMP2 and MMP9 electroporation). Despite employing diverse approaches, we have yet to achieve effective and interpretable perturbation of this resilient structure. Targeting Hh signaling between the endoderm and notochord is a good idea and we will continue these efforts. Thanks very much.

Minor comments:

- Please add the species in the title.

We have altered the title as follows: “An atypical basement membrane forms a midline barrier during left-right asymmetric gut development in the chicken embryo.”

- The number of observations in Fig2, Fig3A-B, 4A-C, G-H, S1, S3 is lacking.

We have added the requested n numbers of biological replicates to the legends of the specified figures.

- Please annotate Fig 3J to show what is measured in K.

We have modified Fig. 3J to include a dashed bar indicating the length measurements in Fig. 3K.

- Please provide illustrations of Fig 4E.

We have added a representative image of GM130 staining to the supplement.

- If laminin gamma is the target of Ntn4, its staining would help interpret the results of Ntn4 manipulation. Is laminin gamma present in different proportions in the different types of basement membranes, underlying variations in sensitivity?

Laminin is exported as a heterotrimer consisting of an alpha, beta, and gamma subunit. Laminin gamma is therefore present in equal proportions to other laminins in all basement membranes with a laminin network. Several gamma isoforms do exist, but only laminin gamma 1 will bind to laminin alpha 1, which we use throughout this paper to mark the midline as well as nearby basement membranes that are sensitive to Ntn4 disruption. Thus, gamma laminin proportions or isoforms are unlikely to underlie the resistance of the midline and endodermal basement membranes to Ntn4 (reviewed in Yurchenco 2011).

- Please comment: what is the red outline abutting the electroporated DM on the left of Fig5B?

The noted structure is the basement membrane of the nephric duct – we added this information to Fig. 5B image and legend.

- The stage in Fig 6A-B is lacking.

We have added the requested stage information to Fig. 6.

- Please comment on whether there is or is not some cell mixing Fig 2H, at HH21 after the midline disappearance. Is it consistent with Fig. 6E-F which labels cells?

More than a decade of DNA electroporation experiments of the left vs. right DM by our laboratory and others have never indicated dorsal mesentery cell migration across the midline (Davis et al., 2008; Kurpios et al., 2008; Welsh et al., 2013; Mahadevan et al., 2014; Arraf et al. 2016; Sivakumar et al., 2018; Arraf et al. 2020; and Sanketi et al., 2022). This is also shown in our current GFP/RFP double electroporation data in Fig. 2 G-H, and DiI/DiO labeling data in Fig. 2 E-G. Cell mixing does not occur even after midline disappearance, most likely due to asymmetric N-cadherin expression on the left side of the DM (Kurpios et al., 2008). The sparse, green-labeled cells observed on the right side in Fig. 2H are likely a result of DNA electroporation - the accuracy of this process relies on the precise injection of the left (or right) coelomic cavity (precursor to the gut mesenchyme including the DM) and subsequent correct placement of the platinum electrodes.

Based on these data, we strongly feel that cellular migration is not responsible for the pattern of dextran observed in Fig. 6E-F, especially in light of the N-cadherin mediated segregation of left and right. We will also note that there is no significant difference between dextran diffusion at HH19 and HH20, only a trend towards significance. Additionally, we would like to note that the dextran-injected embryos were isolated two hours post-injection, which we do not believe is sufficient time for any cell migration to occur across the DM. We also collected additional post-midline stage embryos ten minutes after dextran injections (data not shown), too short a timeframe for significant cellular migration, and the fluorescent signal in those embryos was comparable to that represented in the embryos in Fig. 6. Thus, we believe the movement of fluorescent signal across the DM observed when the barrier starts to fragment at HH20 and HH23 is unlikely to represent movement of cells.

To further strengthen this argument, we now have additional new data on midline diffusion using BODIPY and quantification method to support our findings on the midline's function against diffusion (please refer to New Fig. 6H-M). Briefly, we utilized a BODIPY-tagged version of AMD3100 (Poty et al., 2015) delivered via soaked resin beads surgically inserted into the left coelomic cavity (precursor to the DM). The ratio of average AMD3100-BODIPY intensity in the right DM versus the left DM was below 0.5 when the midline is intact (HH19), indicating little diffusion across the DM (Fig. 6J). At HH21 when no midline remains, this ratio significantly rises to near one, indicating diffusion of the drug is not impeded when the midline basement membrane structure is absent. Collectively, these data suggest that the basement membrane structure at the midline forms a transient functional barrier against diffusion.

- 'independent of Lefty1': rephrase or show the midline phenotype after lefty1 inactivation.

We agree with this comment and have rephrased this section to indicate the midline is present “at a stage when Lefty1 is no longer expressed at the midline.”

We again would like to extend our sincere gratitude to our reviewers and the editors at eLife for their dedicated time and thorough evaluation of our paper. Their meticulous attention to detail and valuable insights have strengthened our data and provided further support for our findings.

While it would not have been realised fully at the time, overreliance on generative art, be it text, music, pictures or videos, is harmful for the the electronic literature as a whole. As we know, even present day AI is unable to create something new, it only replicates what is already present using the tools it has, whcih are limited by it's design, That ties into the modern theory of the Dead Interent, which, despite being conspirology for the most part, does have some reasons to exist. Over-saturation with generated imagery, text and video-files creates a closed loophole, with the same material being reused ad nauseam.

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eLife Assessment

This potentially useful study introduces an orthogonal approach for detecting RNA modification, without chemical modification of RNA, which often results in RNA degradation and therefore loss of RNA molecules. While the authors have improved the work compared to a previous version, uncertainty regarding false positive and false negative rates leave the evidence for the broad applicability of the method incomplete. If properly validated, the approach might be of particular interest for sites where modifications are rare.

Reviewer #2 (Public review):

The fledgling field of epitranscriptomics has encountered various technical roadblocks with implications as to the validity of early epitranscriptomics mapping data. As a prime example, the low specificity of (supposedly) modification-specific antibodies for the enrichment of modified RNAs, has been ignored for quite some time and is only now recognized for its dismal reproducibility (between different labs), which necessitates the development of alternative methods for modification detection.

Furthermore, early attempts to map individual epitranscriptomes using sequencing-based techniques are largely characterized by the deliberate avoidance of orthogonal approaches aimed at confirming the existence of RNA modifications that have been originally identified.

Improved methodology, the inclusion of various controls, and better mapping algorithms as well as the application of robust statistics for the identification of false-positive RNA modification calls have allowed revisiting original (seminal) publications whose early mapping data allowed making hyperbolic claims about the number, localization and importance of RNA modifications, especially in mRNA. Besides the existence of m6A in mRNA, the detectable incidence of RNA modifications in mRNAs has drastically dropped.

As for m5C, the subject of the manuscript submitted by Zhou et al., its identification in mRNA goes back to Squires et al., 2012 reporting on >10.000 sites in mRNA of a human cancer cell line, followed by intermittent findings reporting on pretty much every number between 0 to > 100.000 m5C sites in different human cell-derived mRNA transcriptomes. The reason for such discrepancy is most likely of a technical nature. Importantly, all studies reporting on actual transcript numbers that were m5C-modified relied on RNA bisulfite sequencing, an NGS-based method, that can discriminate between methylated and non-methylated Cs after chemical deamination of C but not m5C. RNA bisulfite sequencing has a notoriously high background due to deamination artifacts, which occur largely due to incomplete denaturation of double-stranded regions (denaturing-resistant) of RNA molecules. Furthermore, m5C sites in mRNAs have now been mapped to regions that have not only sequence identity but also structural features of tRNAs. Various studies revealed that the highly conserved m5C RNA methyltransferases NSUN2 and NSUN6 do not only accept tRNAs but also other RNAs (including mRNAs) as methylation substrates, which in combination account for most of the RNA bisulfite-mapped m5C sites in human mRNA transcriptomes. Is m5C in mRNA only a result of the Star activity of tRNA or rRNA modification enzymes, or is their low stoichiometry biologically relevant?<br /> In light of the short-comings of existing tools to robustly determine m5C in transcriptomes, other methods, like DRAM-seq, allowing to map m5C independently of ex situ RNA treatment with chemicals, are needed to arrive at a more solid "ground state", from which it will be possible to state and test various hypotheses as to the biological function of m5C, especially in lowly abundant RNAs such as mRNA.

Importantly, the identification of >10.000 sites containing m5C increases through DRAM-Seq, increases the number of potential m5C marks in human cancer cells from a couple of 100 (after rigorous post-hoc analysis of RNA bisulfite sequencing data) by orders of magnitude. This begs the question, whether or not the application of these editing tools results in editing artefacts overstating the number of actual m5C sites in the human cancer transcriptome.

Remaining comments after resubmission:

(1) The use of two m5C reader proteins is likely a reason for the high number of edits introduced by the DRAM-Seq method. Both ALYREF and YBX1 are ubiquitous proteins with multiple roles in RNA metabolism including splicing and mRNA export. It is reasonable to assume that both ALYREF and YBX1 bind to many mRNAs that do not contain m5C.<br /> To substantiate the author's claim that ALYREF or YBX1 binds m5C-modified RNAs to an extent that would allow distinguishing its binding to non-modified RNAs from binding to m5C-modified RNAs, it would be recommendable to provide data on the affinity of these, supposedly proven, m5C readers to non-modified versus m5C-modified RNAs. To do so, this reviewer suggests performing experiments as described in Slama et al., 2020 (doi: 10.1016/j.ymeth.2018.10.020). Mind you that using dot blots like in so many published studies to show modification-specific antibody or protein binding, is insufficient as an argument because no antibody, nor protein encounters nanograms to micrograms of a specific RNA identity in a cell. This issue remains a major caveat in all studies using so-called RNA modification reader proteins as bait for detecting RNA modifications in epitranscriptomics research and becomes a pertinent problem, if used as a platform for base-editing similar to the work presented in this manuscript.

(2) Using sodium arsenite treatment of cells as a means to change the m5C status of transcripts through the downregulation of the two major m5C writer proteins NSUN2 and NSUN6 is problematic and the conclusions from these experiments are not warranted. Sodium arsenite is a chemical that poisons every protein containing thiol groups. Not only do NSUN proteins contain cysteines but also the base editor fusion proteins. Arsenite will inactivate these proteins, hence the editing frequency will drop, as observed in the experiments shown in Figure 5, which the authors explain with fewer m5C sites to be detected by the fusion proteins.

(3) The authors should move high-confidence editing site data contained in Supplementary Tables 2 and 3 into one of the main Figures to substantiate what is discussed in Figure 4A. However, the data needs to be visualized in another way then excel format. Furthermore, Supplementary Table 2 does not contain a description of the columns, while Supplementary Table 3 contains a single row with letters and numbers.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1:

In this manuscript, Zhou et al describe a deaminase and reader protein-assisted RNA m5C sequencing method. The general strategy is similar to DART-seq for m6A sequencing, but the difference is that in DART-seq, m6A sites are always followed by C which can be deaminated by fused APOBEC1 to provide a high resolution of m6A sites, while in the case of m5C, no such obvious conserved motifs for m5C sites exist, therefore, the detection resolution is much lower. In addition, the authors used two known m5C binding proteins ALYREF and YBX1 to guide the fused deaminases, but it is not clear whether these two binding proteins can bind most m5C sites and compete with other m5C binding proteins.

Thank you for your kind suggestion. RNA affinity chromatography and mass spectrometry analyses using biotin-labelled oligonucleotides with or without m5C were performed in previous reports (doi:10.1038/cr.2017.55 and doi: 10.1038/s41556-019-0361-y), and the results showed that ALYREF and YBX1 had a more prominent binding ability to m5C -modified oligonucleotides. Moreover, these two m5C -binding proteins are also responsible for mRNA m5C binding, so we chose to use their ability to bind targeted m5C to construct a DRAM detection system in anticipation of transcriptome-wide m5C detection. We hope to propose a suitable detection strategy for RNA m5C, and there will certainly be room for optimization of the DRAM system in the future with more in-depth studies of m5C binding proteins. We have discussed the above issue in lines 75-82 and 315-318.

It is well known that two highly modified m5C sites exist in 28S RNA and many m5C sites exist in tRNA, the authors should validate their methods first by detecting these known m5C sites and evaluate the possible false positives in rRNA and tRNA.

Thank you for your kind suggestion. We attempted PCR amplification of sequences flanking m5C sites 3782 and 4447 on 28S rRNA, as well as multiple m5C sites on tRNA, including m5C48 and m5C49 on tRNAVal, m5C48 and m5C49 on tRNAAsp, and m5C48 on tRNALys.

However, Sanger sequencing revealed no valid mutations, which was implemented in Figure S3. We believe this outcome indicates that the DRAM system is more suited for transcriptome-wide m5C detection of mRNAs. This is supported by current reports that ALYREF and YBX1 are responsible for the m5C-binding proteins of mRNAs (doi:10.1038/cr.2017.55 and doi: 10.1038/s41556-019-0361-y). The above results and descriptions were added to lines 136-143.

In mRNA, it is not clear what is the overlap between the technical replicates. In Figures 4A and 4C, they detected more than 10K m5C sites, and most of them did not overlap with sites uncovered by other methods. These numbers are much larger than expected and possibly most of them are false positives.

Thank you for your kind suggestion. We observed significant overlap between the technical repeats by comparing the data across biological repeats, as shown in Figure S4C and described in lines 174-175. We considered m5C modification in a region only when editing events were detected in at least two biological replicates, ensuring a high-stringency screening process (details seen in the revised method in lines 448-455 and Figure 3F). With more in-depth research into m5C readers, we aim to achieve more accurate detection in the future.

Besides, it is not clear what is the detection sensitivity and accuracy since the method is neither single base resolution nor quantitative.

Thank you for your suggestion. As shown in Figure 3G, we found that the editing window of the DRAM system exhibited enrichment of approximately 20 bp upstream and downstream of the m5C site. Previous reports identified Type I m5C sites, which tend to have a downstream "NGGG" motif, and Type II m5C sites, which often contain a downstream "UCCA" motif. However, these m5C motifs do not fully characterize all m5C sites, and their presence downstream of an m5C site is not guaranteed (doi: 10.1038/s41594-019-0218-x). This limitation complicates single-base resolution analysis by the DRAM system. Nevertheless, we believe that with further exploration of m5C sequence features, precise single-base resolution detection can be achieved in the future. This point is also discussed in lines 314-322.

Regarding the quantitative level of the assay, we conducted additional experiments by progressively reducing the expression levels of the fusion proteins. Sanger sequencing revealed that the editing efficiency of A-to-G and C-to-U within the m5C region significantly decreased as fusion protein expression diminished (Figure S9). These findings suggest that the DRAM system's transfection efficiency is concentration-dependent and that the ratio of editing efficiency to transfection efficiency could aid in the quantitative analysis of m5C using the DRAM system. The relative results were supplemented in Figure S9 and discussed in lines 263-271.

There are no experiments to show that the detected m5C sites are responsive to the writer proteins such as NSUN2 and NSUN6, and the determination of the motifs of these writer proteins.

Thank you for your kind suggestion. We have performed a motif enrichment analysis based on the sequences spanning 10 nt upstream and downstream of DRAM-editing sites. The relative results of this analysis were supplemented in Figure S4D and lines 168-171. Unfortunately, we did not identify any clear sequence preferences for the m5C sites catalyzed by the methyltransferases NSUN2 and NSUN6, which have previously been associated with “G”-rich sequences and the “CUCCA” motif. This limitation is mainly due to the DRAM detection system’s inability to achieve single-base resolution for m5C detection, which is also explained in the above response.

Reviewer #2:

(1) The use of two m5C reader proteins is likely a reason for the high number of edits introduced by the DRAM-Seq method. Both ALYREF and YBX1 are ubiquitous proteins with multiple roles in RNA metabolism including splicing and mRNA export. It is reasonable to assume that both ALYREF and YBX1 bind to many mRNAs that do not contain m5C.

To substantiate the author's claim that ALYREF or YBX1 binds m5C-modified RNAs to an extent that would allow distinguishing its binding to non-modified RNAs from binding to m5C-modified RNAs, it would be recommended to provide data on the affinity of these, supposedly proven, m5C readers to non-modified versus m5C-modified RNAs. To do so, this reviewer suggests performing experiments as described in Slama et al., 2020 (doi: 10.1016/j.ymeth.2018.10.020). However, using dot blots like in so many published studies to show modification of a specific antibody or protein binding, is insufficient as an argument because no antibody, nor protein, encounters nanograms to micrograms of a specific RNA identity in a cell. This issue remains a major caveat in all studies using so-called RNA modification reader proteins as bait for detecting RNA modifications in epitranscriptomics research. It becomes a pertinent problem if used as a platform for base editing similar to the work presented in this manuscript.

We thank the reviewer for the valuable suggestion. Previous studies have shown that while ALYREF and YBX1 can bind mRNAs without the m5C modification, their binding affinity for m5C-modified oligonucleotides is significantly higher than for unmethylated controls. This has been demonstrated through experiments such as in vitro tractography, electrophoretic mobility shift assay (EMSA) (doi:10.1038/cr.2017.55), and UHPLC-MRM-MS/MS. Additionally, isothermal titration calorimetry measurements and PAR-CLIP experiments have shown that mutations in the key amino acids responsible for m5C binding in ALYREF and YBX1 result in a significant reduction in their ability to m5C (doi: 10.1038/s41556-019-0361-y).

Although Me-RIP analysis was unsuccessful in our laboratory, likely due to the poor specificity of the m5C antibody, we alternatively performed RNA pulldown experiments. These experiments verified that the ability of DRAMmut-expressing proteins to bind RNA with m5C modification was virtually absent compared to DRAM-expressing proteins, while their binding ability with non-modified RNA was not significantly affected. The relative RNA pulldown results were supplemented in Figure S1E, S1F and lines 110-111. Therefore, we believe that by integrating DRAMmut group, our DRAM system could effectively exclude the false-positive mutations caused by unspecific binding of DRAM’s reader protein to non-m5C-modified mRNAs.

(2) Since the authors use a system that results in transient overexpression of base editor fusion proteins, they might introduce advantageous binding of these proteins to RNAs. It is unclear, which promotor is driving construct expression but it stands to reason that part of the data is based on artifacts caused by overexpression. Could the authors attempt testing whether manipulating expression levels of these fusion proteins results in different editing levels at the same RNA substrate?

Thank you for pointing this out. To investigate how different expression levels of these proteins influence A-to-G and C-to-U editing within the same m5C region, we conducted a gradient transfection using plasmid concentrations of 1500 ng, 750 ng and 300 ng. This approach allowed us to progressively reduce the expression levels of the fusion proteins. Sanger sequencing revealed that the editing efficiency of A-to-G and C-to-U within the m5C region significantly decreased as fusion protein expression diminished. These findings suggest that the transfection efficiency of the DRAM system is concentration-dependent and that the ratio of editing efficiency to transfection efficiency may assist in the quantitative analysis of m5C using the DRAM system. The relative results and hypotheses were added and discussed in Figure S9 and lines 263-271 of the revised manuscript.

(3) Using sodium arsenite treatment of cells as a means to change the m5C status of transcripts through the downregulation of the two major m5C writer proteins NSUN2 and NSUN6 is problematic and the conclusions from these experiments are not warranted. Sodium arsenite is a chemical that poisons every protein containing thiol groups. Not only do NSUN proteins contain cysteines but also the base editor fusion proteins. Arsenite will inactivate these proteins, hence the editing frequency will drop, as observed in the experiments shown in Figure 5, which the authors explain with fewer m5C sites to be detected by the fusion proteins.

Thank you for pointing this out. We used bisulfite sequencing PCR to determine that the m5C levels in RPSA and AP5Z1 were significantly reduced after sodium arsenite treatment. This was followed by a significant decrease in editing frequency detected by the DRAM system in sodium arsenite-treated samples compared to untreated samples. This reduction aligns with the decreased editing efficiency observed in methyltransferase-deficient cells (as shown in Figures 2G and 2H), which initially convinced us that these results reflected the DRAM system's ability to monitor dynamic changes in m5C levels.

However, as the reviewer pointed out, sodium arsenite treatment could potentially inactivate the fusion proteins, leading to the observed reduction in editing efficiency. This possibility has not been conclusively ruled out in our current experiments. Optimizing this validation may require the future development of more specific m5C inhibitors. In light of this, we have revised our previous results and conclusions in lines 235-244, and discussed these points in lines 308-315.

(4) The authors should move high-confidence editing site data contained in Supplementary Tables 2 and 3 into one of the main Figures to substantiate what is discussed in Figure 4A. However, the data needs to be visualized in another way than an Excel format. Furthermore, Supplementary Table 2 does not contain a description of the columns, while Supplementary Table 3 contains a single row with letters and numbers.

Thank you for your kind suggestion. We have visualized the data from Supplementary Tables 2 and 3 into Figure 3F, presenting it as a screening flowchart for high-confidence editing sites. In Supplementary Table 3, we have displayed only the DRAM-mutated genes, which is why it contains a single row with letters and numbers. As requested, we have included descriptions of each column and reorganized the Supplementary table 2 and 3 accordingly.

(5) The authors state that "plotting the distribution of DRAM-seq editing sites in mRNA segments (5'UTR, CDS, and 3'UTR) highlighted a significant enrichment near the initiation codon (Figure 3F).", which is not true when this reviewer looks at Figure 3F.

Thank you for your kind suggestion, and we replaced the expression of " near the initiation codon" with "in the CDS" in lines 192-193.

(6) The authors state that "In contrast, cells expressing the deaminase exhibited a distinct distribution pattern of editing sites, characterized by a prevalence throughout the 5'UTR.", which is not true when this reviewer looks at Figure 3F.

Thank you for your kind suggestion. This distribution was actually characterized by a prevalence throughout the "3'UTR", but not "5'UTR". We have also made the necessary changes in lines 193-195.

(7) The authors claim in the final conclusion: "In summary, we developed a novel deaminase and reader protein assisted RNA m5C methylation approach...", which is not what the method entails. The authors deaminate As or Us close to 5mC sites based on the binding of a deaminase-containing protein.

Thank you for your kind suggestion, and we have made the necessary changes in lines 331-334.

(8) The authors claim that "The data supporting the findings of this study are available within the article and its Supplementary Information." However, no single accession number for the deposited sequencing data can be found in the text or the supplementary data. Without the primary data, none of the claims can be verified.

Thank you for pointing this out. The sequencing data from this study has already been deposited to the GEO database (GEO assession number: GSE254194, GEO token：ororioukbdqtpcn), and we will ensure it is made publicly available in a timely manner.

(a) To underscore point (1), a recent publication (https://doi.org/10.1038/s41419-023-05661-y) reported: "To further identify the potential mRNAs regulated by ALYREF, we performed RNA-seq analysis in control or ALYREF knockdown T24 cells. After knockdown of ALYREF, 143 mRNAs differentially expressed, including 94 downregulated mRNAs (NC reads >100, |Fold change | >1.5, P-value <0.05). Functional enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that regulated mRNAs by ALYREF are chiefly enriched in canonical cancer-related pathways (Fig. S4A), including TGF-β signaling, MAPK signaling, and NF-κB signaling, strongly supporting the oncogenic function of ALYREF in tumor progression. Among these 94 downregulated genes, 11 mRNA showed a significant reduction in m5C methylation after NUSN2 silencing in T24 cells, combined with previously transcriptome-wide RNA-BisSeq data of T24 cells [21] (Fig. 4A)."

These results translate into 94 mRNAs are regulated by ALYREF in bladder cancer-derived cells. From those, very few (11) mRNA identities respond to NSUN2-dependent RNA methylation mediated by ALYREF binding.The question then arises, is that number sufficient to claim that ALYREF is a m5C-binding protein?

And if so, how does the identification of 10.000+ edits by DRAM-Seq compare with the 94 mRNAs that are regulated by ALYREF? Were these 94 mRNAs identified by DRAM-Seq.

Thank you for your kind suggestion. Previous reports by Yang et al. ( doi: 10.1038/cr.2017.55), including the literature you refer to, have detailed the close relationship between ALYREF and m5C modification, and the ALY/REF export factor (ALYREF) was identified as the first nuclear m5C reader, and it was demonstrated that many mRNAs are regulated by ALYREF, and is therefore considered to be an m5C-binding protein.

As required, by comparing the DRAM-edited mRNAs with the reported 94 mRNAs, we found that only 55.32% of the 94 mRNAs regulated by ALYREF could be detected by the DRAM system. This indicates that the DRAM system specifically targets certain mRNAs, as illustrated in Figure S4E. The relevant results were described and discussed in lines 175-179.

(b) Line 123:

"The deep sequencing results showed that the deamination rates of RPSA and SZRD1 were 75.5% and 27.25%, respectively. (Fig. 2A, B)."

The Figure shows exactly the opposite of bisulfite-mediated deamination. These are the cytosines that were not deaminated by the chemical treatment and therefore can be sequenced as cytosines and not thymidines. Hence, the term deamination rate is wrong.

Thank you for your kind suggestion. We have made the necessary change in lines 129-130 to change the deamination rates to m⁵C fraction.

(c) Line 157:

"DRAM-seq analysis further confirmed that DRAM was detected in an m5C-dependent manner, with minimal mutations in AP5Z1 and RPSA mRNAs in methyltransferase knockout cells compared to wild-type cells (Fig. 3C, D)."

There is no indication of what the authors mean by minimal mutation in these Figures. The term "minimal mutation" should be reconsidered as well.

Thank you for your kind suggestion. We intended to express that "Mutations in AP5Z1 and RPSA mRNA are reduced in methyltransferase-deficient cells." There was an issue with the initial formulation, and we have made the necessary changes in lines 165-167.

(d) Line 167:

"To further delineate the characteristics of the DRAM-seq data, we compared the distribution of DRAM-seq editing sites within the gene structure, specifically examining their occurrences in the 5'untranslated region (5'UTR), 3' untranslated region (3'UTR), CDS and ncRNA."

Which part of a coding RNA is meant by "ncRNA"?

Thank you for pointing this out. This was actually the Intergenic or Intron region, but not ncRNA. We have also corrected this labelling in Figure 3G and lines 186-189 of the revised manuscript.

(e) Line 189:

"Subsequently, we assessed the capacity of DRAM-seq to detect m5C on a transcriptome-wide scale, comparing its performance to BS-seq that have been previously reported with great authority."

The term "great authority" is not a scientific term. Please, remove adulation to senior authors.

Thank you for your kind suggestion. We removed this unsuitable expression and made the necessary changes in lines 207-208.

(f) Line 233:

"Several experiments have highlighted the requirement of 100-500 ng of RNA for m5C-RIP-seq, while BS-seq necessitates an even more demanding 500-750 μg of RNA21,25,61."

This reviewer doubts that RNA bisulfite sequencing required half to one mg of RNA input. Please, check these references.

Thank you for your kind suggestion. According to the references, we corrected μg to ng and made the necessary changes in lines 251-252.

(g) Line 247:

"Several experiments have highlighted the requirement of 100-500 ng of RNA for m5C-RIP-seq, while BS-seq necessitates an even more demanding 500-750 μg of RNA21,25,61."

This reviewer doubts that RNA bisulfite sequencing requires half to one mg of RNA input. Please, check these references.

Thank you for your kind suggestion. According to the references, we corrected μg to ng and made the necessary changes in lines 251-252.

(h) Line 292:

"Since m5C lacks a fixed motif, DRAM has an apparent limitation in achieving single-base resolution for detecting m5C."

m5C deposition by NSUN2 and NSUN6 occurs in particular motifs that were coined Type I and II motifs. Hence, this statement is not correct.

Thank you for your kind suggestion. Previous reports identified Type I m5C sites, which tend to have a downstream "NGGG" motif, and Type II m5C sites, which often contain a downstream "UCCA" motif. However, these m5C motifs do not fully characterize all m5C sites, and their presence downstream of an m5C site is not guaranteed (doi: 10.1038/s41594-019-0218-x ). Therefore, we have corrected the expression “fixed motif” to “fixed base composition for characterizing all m5C modification sites” in lines 317.

(i) Line 390:

"1 μl of total cellular RNA was used for sequencing library gene..."

1 uL does not allow us to deduce which RNA mass was used for cDNA synthesis.

Thank you for your kind suggestion. According to our cDNA synthesis protocol, we corrected “1μl” to “1μg” in lines 422-423.

(j) Line 405:

"...was assessed on the Agilent 5400 system (Agilent, USA) and quantified by QPCR (1.5 nM)"

What does the 1.5 nM refer to in this sentence?

Thank you for your kind suggestion. Here, "1.5nM" means that the concentration of the constructed library should be no less than 1.5nM. We have also revised this expression in the methods in lines 436-438.

eLife Assessment

This interesting study focuses on a previously reported positive correlation between translational efficiency and protein noise. This is unexpected as typically noise is inversely related to expression and increasing translation efficiency would increase the protein expression and thus be expected to reduce noise in gene expression. Using mathematical modeling and analysis of experimental data the authors argue that this phenomenon arises due to ribosomal demand. However, the work appears incomplete, with the reviewers having raised questions regarding the validity of the assumptions used in the mathematical model as well as the clarity of the presentation.

Reviewer #1 (Public review):

Summary:

The authors use analysis of existing data, mathematical modelling, and new experiments, to explore the relationship between protein expression noise, translation efficiency, and transcriptional bursting.

Strengths:

The analysis of the old data and the new data presented is interesting and mostly convincing.

Weaknesses:

(1) My main concern is the analysis presented in Figure 4. This is the core of mechanistic analysis that suggests ribosomal demand can explain the observed phenomenon. I am both confused by the assumptions used here and the details of the mathematical modelling used in this section. Firstly, the authors' assumption that the fluctuations of a single gene mRNA levels will significantly affect ribosome demand is puzzling. On average the total level of mRNA across all genes would stay very constant and therefore there are no big fluctuations in the ribosome demand due to the burstiness of transcription of individual genes. Secondly, the analysis uses 19 mathematical functions that are in Table S1, but there are not really enough details for me to understand how this is used, are these included in a TASEP simulation? In what way are mRNA-prev and mRNA-curr used? What is the mechanistic meaning of different terms and exponents? As the authors use this analysis to argue ribosomal demand is at play, I would like this section to be very much clarified.

(2) Overall, the paper is very long and as there are analytical expressions for protein noise (e.g. see Paulsson Nature 2004), some of these results do not need to rely on Gillespie simulations. Protein CV (noise) can be written as three terms representing protein noise contribution, mRNA expression contribution, and bursty transcription contribution. For example, the results in panel 1 are fully consistent with the parameter regime, protein noise is negligible compared to transcriptional noise.

Reviewer #2 (Public review):

This work by Pal et al. studied the relationship between protein expression noise and translational efficiency. They proposed a model based on ribosome demand to explain the positive correlation between them, which is new as far as I realize. Nevertheless, I found the evidence of the main idea that it is the ribosome demand generating this correlation is weak. Below are my major and minor comments.

Major comments:

(1) Besides a hypothetical numerical model, I did not find any direct experimental evidence supporting the ribosome demand model. Therefore, I think the main conclusions of this work are a bit overstated.

(2) I found that the enhancement of protein noise due to high translational efficiency is quite mild, as shown in Figure 6A-B, which makes the biological significance of this effect unclear.

(3) The captions for most of the figures are short and do not provide much explanation, making the figures difficult to read.

(4) It would be helpful if the authors could define the meanings of noise (e.g., coefficient of variation?) and translational efficiency in the very beginning to avoid any confusion. It is also unclear to me whether the noise from the experimental data is defined according to protein numbers or concentrations, which is presumably important since budding yeasts are growing cells.

(5) The conclusions from Figures 1D and 1E are not new. For example, the constant protein noise as a function of mean protein expression is a known result of the two-state model of gene expression, e.g., see Equation (4) in Paulsson, Physics of Life Reviews 2005.

(6) In Figure 4C-D, it is unclear to me how the authors changed the mean protein expression if the translation initiation rate is a function of variation in mRNA number and other random variables.

(7) If I understand correctly, the authors somehow changed the translation initiation rate to change the mean protein expression in Figures 4C-D. However, the authors changed the protein sequences in the experimental data of Figure 6. I am not sure if the comparison between simulations and experimental data is appropriate.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors use analysis of existing data, mathematical modelling, and new experiments, to explore the relationship between protein expression noise, translation efficiency, and transcriptional bursting.

Strengths:

The analysis of the old data and the new data presented is interesting and mostly convincing.

Thank you for the constructive suggestions and comments. We address the individual comments below.

Weaknesses:

(1) My main concern is the analysis presented in Figure 4. This is the core of mechanistic analysis that suggests ribosomal demand can explain the observed phenomenon. I am both confused by the assumptions used here and the details of the mathematical modelling used in this section. Firstly, the authors' assumption that the fluctuations of a single gene mRNA levels will significantly affect ribosome demand is puzzling. On average the total level of mRNA across all genes would stay very constant and therefore there are no big fluctuations in the ribosome demand due to the burstiness of transcription of individual genes. Secondly, the analysis uses 19 mathematical functions that are in Table S1, but there are not really enough details for me to understand how this is used, are these included in a TASEP simulation? In what way are mRNA-prev and mRNA-curr used? What is the mechanistic meaning of different terms and exponents? As the authors use this analysis to argue ribosomal demand is at play, I would like this section to be very much clarified.

Thank you for raising two important points. Regarding the first point, we agree that the overall ribosome demand in a cell will remain more or less the same even with fluctuations in mRNA levels of a few genes. However, what we refer to in the manuscript is the demand for ribosomes for translating mRNA molecules of a single gene. This demand will vary with the changes in the number of the mRNA molecules of that gene. When the mRNA copy number of the gene is low, the number of ribosomes required for translation is low. At a subsequent timepoint when the mRNA number of the same gene goes up rapidly due to transcriptional bursting, the number of ribosomes required would also increase rapidly. The process of allocation of ribosomes for translation of these mRNA molecules will vary between cells, and this process can lead to increased expression variation of that gene among cells.

Regarding the second point, each of the 19 mathematical functions was individually tested in the TASEP model and stochastic simulation. The parameters ‘mRNA-curr’ and ‘mRNA-prev’ are the mRNA copy numbers at the current time point and the previous time point in the stochastic simulation, respectively. These numbers were calculated from the rate of production of mRNA, which is influenced by the burst frequency and the burst size, as well as the rate of mRNA removal. We would expand this section with explanation for all parameters and terms in the revised manuscript.

(2) Overall, the paper is very long and as there are analytical expressions for protein noise (e.g. see Paulsson Nature 2004), some of these results do not need to rely on Gillespie simulations. Protein CV (noise) can be written as three terms representing protein noise contribution, mRNA expression contribution, and bursty transcription contribution. For example, the results in panel 1 are fully consistent with the parameter regime, protein noise is negligible compared to transcriptional noise.

Thank you for referring to the paper on analytical expressions for protein noise. We introduced translational bursting and ribosome demand in our model, and these are linked to stochastic fluctuations in mRNA and ribosome numbers. In addition, our model couples transcriptional bursting with translational bursting and ribosome demand. Since these processes are all stochastic in nature, we felt that the stochastic simulation would be able to better capture the fluctuations in mRNA and protein expression levels originating from these processes. For consistency, we used stochastic simulations throughout even when the coupling between transcription and translation were not considered.

Reviewer #2 (Public review):

This work by Pal et al. studied the relationship between protein expression noise and translational efficiency. They proposed a model based on ribosome demand to explain the positive correlation between them, which is new as far as I realize. Nevertheless, I found the evidence of the main idea that it is the ribosome demand generating this correlation is weak. Below are my major and minor comments.

Thank you for your helpful suggestions and comments. We note that the direct experimental support required for the ribosome demand model would need experimental setups that are beyond the currently available methodologies. We address the individual comments below.

Major comments:

(1) Besides a hypothetical numerical model, I did not find any direct experimental evidence supporting the ribosome demand model. Therefore, I think the main conclusions of this work are a bit overstated.

Direct experimental evidence of the hypothesis would require generation of ribosome occupancy maps of mRNA molecules at the level of single cells and at time intervals that closely match the burst frequency of the genes. This is beyond the currently available methodologies. However, there are other evidences that support our model. For example, earlier work in cell-free systems have showed that constraining cellular resources required for transcription or translation can increase expression heterogeneity (Caveney et al., 2017). In addition, genome-wide analysis of expression noise in yeast also revealed that the association between protein noise and translational efficiency was highest in the group of genes with the most bursty transcription (Supplementary fig. S20).

(2) I found that the enhancement of protein noise due to high translational efficiency is quite mild, as shown in Figure 6A-B, which makes the biological significance of this effect unclear.

Although we agree with the reviewer’s comment that the effect of translational efficiency on protein noise may not be as substantial as the effect of transcriptional bursting, it has been observed in studies across bacteria, yeast and Arabidopsis (Ozbudak et al., 2003; Blake et al., 2003; Wu et al., 2022). In addition, the relationship between translational efficiency and protein noise is in contrast with the inverse relationship observed between mean expression and noise (Newman et al., 2006; Silander et al., 2012). We also note that the goal of the manuscript was not to evaluate the strength of the association, but to understand the basis of the influence of translational efficiency on protein noise.

(3) The captions for most of the figures are short and do not provide much explanation, making the figures difficult to read.

We will revise the figure captions to include more details as per the reviewer’s suggestion.

(4) It would be helpful if the authors could define the meanings of noise (e.g., coefficient of variation?) and translational efficiency in the very beginning to avoid any confusion. It is also unclear to me whether the noise from the experimental data is defined according to protein numbers or concentrations, which is presumably important since budding yeasts are growing cells.

For all published datasets where we had measurements from a large number of genes/promoters, we used the measures of adjusted noise (for mRNA noise) and Distance-to-median (DM, for protein noise). For experiments that we performed on a limited number of promoters, we used the measure of coefficient of variation (CV) to quantify noise, as calculation of adjusted noise or DM was not possible. Translational efficiency refers to translation rate which is determined by both the translation initiation rate and the translation elongation rate. The noise at the protein level was quantified from the signal intensity of GFP tagged proteins, which was proportional to protein numbers without considering cell volume. For quantification of noise at the mRNA level, single-cell RNA-seq data was used, which provided mRNA numbers in individual cells.

(5) The conclusions from Figures 1D and 1E are not new. For example, the constant protein noise as a function of mean protein expression is a known result of the two-state model of gene expression, e.g., see Equation (4) in Paulsson, Physics of Life Reviews 2005.

Yes, they are not new, but we included these results for setting the baseline for comparison with simulation results that appear in the later part of the manuscript where we included translational bursting and ribosome demand in our models.

(6) In Figure 4C-D, it is unclear to me how the authors changed the mean protein expression if the translation initiation rate is a function of variation in mRNA number and other random variables.

The translation initiation rate varied from a baseline initiation rate depending on the mRNA numbers and other variables. We changed the baseline initiation rate to alter the mean protein expression levels. We will elaborate this section in the revised manuscript.

(7) If I understand correctly, the authors somehow changed the translation initiation rate to change the mean protein expression in Figures 4C-D. However, the authors changed the protein sequences in the experimental data of Figure 6. I am not sure if the comparison between simulations and experimental data is appropriate.

It is an important observation. Even though we changed the translation initiation rate to change the mean expression (Fig. 4C-D), we noted in the description in the model (Fig. 3D) that the changes in the translation initiation rate was also linked with changes in the translation elongation rate. The translation initiation rate can only increase if the ribosomes already bound to the mRNA traverse quicker through the mRNA. This means that an increase in the translation initiation rate will occur only if the translation elongation rate is also increased, which will lead to lower traversal time of the ribosomes through the mRNA (Fig. 3D). Similarly, an increase in the translation elongation rate will allow more ribosomes to initiate translation. Thus, the parameters translation initiation rate and translation elongation rate are interconnected. This has also been observed in an experimental study by Barrington et al. (2023). Having said that, however, the models can also be expressed in terms of the translation elongation rate, instead of the translation initiation rate, and this modification will not change the results of the simulations due to interconnectedness of the initiation rate and the elongation rate.  

References

C. L. Barrington, G. Galindo, A. L. Koch, E. R. Horton, E. J. Morrison, S. Tisa, T. J. Stasevich, O. S. Rissland. Synonymous codon usage regulates translation initiation. Cell Rep. 42, 113413 (2023).

W. J. Blake, M. Kaern, C. R. Cantor, J. J. Collins, Noise in eukaryotic gene expression. Nature 422, 633-637 (2003).

P. M. Caveney, S. E. Norred, C. W. Chin, J. B. Boreyko, B. S. Razooky, S. T. Retterer, C. P. Collier, M. L. Simpson, Resource Sharing Controls Gene Expression Bursting. ACS Synth Biol. 6, 334-343 (2017)

J. R. Newman, S. Ghaemmaghami, J. Ihmels, D. K. Breslow, M. Noble, J. L. DeRisi, J. S. Weissman, Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature, 441, 840-846 (2006).

E. M. Ozbudak, M. Thattai, I. Kurtser, A. D. Grossman, A. van Oudenaarden, Regulation of noise in the expression of a single gene. Nat Genet. 31, 69-73 (2002).

O. K. Silander, N. Nikolic, A. Zaslaver, A. Bren, I. Kikoin, U. Alon, M. Ackermann, A genome-wide analysis of promoter-mediated phenotypic noise in Escherichia coli. PLoS Genet. 8, e1002443 (2012).

H. W. Wu, E. Fajiculay, J. F. Wu, C. S. Yan, C. P. Hsu, S. H. Wu, Noise reduction by upstream open reading frames. Nat Plants. 8, 474-480 (2022).

The hashtag #HaryanaElectionResult is trending on Twitter due to the recent assembly elections in Haryana, which have garnered significant public interest and engagement. Here are some key reasons for the trend:

Today, we all lost our hero Ratan Tata sir at the age of 86 🥲 I was just doing my work and some friend told me that see the news that Ratan Tata sir is not more.

A few days ago, Ratan Tata had denied reports of him being admitted to ICU.

Ratan Tata Death Latest News Today: In a shocking development, the business tycoon Ratan Tata has passed away on Wednesday, several reports claimed on the Internet.

According to information, Ratan Tata took his last breath at the age of 86.

Author response:

Public Reviews:

Reviewer #1 (Public review)

Summary:

Numerous mechanism and structural studies reported the cooperative role of Oct4 and Sox2 during the establishment of pluripotency during reprogramming. Due to the difficulty in sample collection and RNA-seq with low-number cells, the precise mechanisms remain in early embryos. This manuscript reported the role of OCT4 and SOX2 in mouse early embryos using knockout models with low-input ATAC-seq and RNA-seq. Compared to the control, chromatin accessibility and transcriptome were affected when Oct4 and Sox2 were deleted in early ICM. Specifically, decreased ATAC-seq peaks showed enrichment of Motifs of TF such as OCT, SOX, and OCT-SOX, indicating their importance during early development. Moreover, by deep analysis of ATAC-seq and RNA-seq data, they found Oct4 and Sox2 target enhancer to activate their downstream genes. In addition, they also uncovered the role of OS during development from the morula to ICM, which provided the scientific community with a more comprehensive understanding.

Strengths:

On the whole, the manuscript is innovative, and the conclusions of this paper are mostly well supported by data, however, there are some issues that need to be addressed.

Weaknesses:

Major Points:

(1) In Figure 1, a more detailed description of the knockout strategy should be provided to clarify itself. The knockout strategy in Fig1 is somewhat obscure, such as how is OCT4 inactivated in Oct4mKO2 heterozygotes. As shown in Figure 1, the exon of OCT4 is not deleted, and its promoter is not destroyed. Therefore, how does OCT4 inactivate to form heterozygotes?

Thank you for your kind suggestions. We will add a detailed description of the knockout strategy in the legends for Figure 1A and 1B, as shown below:

Figure 1A. Schemes of mKO2-labeled Oct4 KO (Oct4mKO2) and Oct4 flox alleles. In the Oct4mKO2 allele, a PGK-pac∆tk-P2A-mKO2-pA cassette was inserted 3.6 kb upstream of the Oct4 transcription start site (TSS) and a promoter-less FRT-SA-IRES-hph-P2A-Venus-pA cassette was inserted into Oct4 intron 1. The inclusion of a stop codon followed by three sets of polyadenylation signal sequences (pA) after the Venus cassette ensures both transcriptional and translational termination, effectively blocking the expression of Oct4 exons 2–5.

Figure 1B. Schemes of EGFP-labeled Sox2 KO (Sox2EGFP) and Sox2 flox alleles. In the Sox2EGFP allele, the 5’ untranslated region (UTR), coding sequence and a portion of the 3’ UTR of Sox2 were deleted and replaced with a PGK-EGFP-pA cassette. Notably, 1,023 bp of the Sox2 3’UTR remaine intact.

(2) Is ZP 3-Cre expressed in the zygotes? Is there any residual protein?

Thank you for the question. While we have not directly tested for ZP3-Cre expression in zygotes, the published transcriptome and proteomics data shows that ZP3 is present at both the transcriptional and protein levels in wild-type zygotes (Deng et al., Science, 2014; Gao et al., Cell Reports, 2017). This suggests that ZP3-Cre could potentially be expressed in zygotes as well.

(3) What motifs are enriched in the rising ATAC-seq peaks after knocking out of OCT4 and SOX2?

Thank you for the question. The enriched motifs in the rising ATAC-seq peaking in Oct4 KO and Sox2 KO ICMs are the GATA, TEAD, EOMES and KLF motifs, as shown in Figure 4A and Figure supplement 7.

(4) The ordinate of Fig4c is lost.

Thank you for the question. The y-axis is average normalized signals (reads per million-normalized pileup signals). We will add it in the revised version.

(5) Signals of H3K4me1, H3K27ac, and so on are usually used to define enhancers, and the loci of enhancers vary greatly in different cells. In the manuscript, the authors defined ATAC-seq peaks far from the TSS as enhancers. The definition in this manuscript is not strictly an enhancer.

Thank you for this insightful comment. We will search for and analyze published omics data on H3K4me1 and H3K27ac in early embryos or mouse embryonic stem cells to conduct this analysis.

(6) If Oct4 and Sox2 truly activate sap 30 and Uhrf 1, what effect does interfering with both genes have on gene expression and chromatin accessibility?

Thank you for the interesting question. Unfortunately, we have not conducted this specific experiment, so we do not have direct results. However, Sap30 is a key component of the mSin3A corepressor complex, while Uhrf1 regulates the establishment and maintenance of DNA methylation. Both proteins are known to function as repressors. Therefore, we hypothesize that interfering with these two genes could alleviate repression of some genes, such as trophectoderm markers, similar to what we have observed in Oct4 KO and Sox2 KO ICMs.

Reviewer #2 (Public review):

In this manuscript, Hou et al. investigate the interplay between OCT4 and SOX2 in driving the pluripotent state during early embryonic lineage development. Using knockout (KO) embryos, the authors specifically analyze the transcriptome and chromatin state within the ICM-to-EPI developmental trajectory. They emphasize the critical role of OCT4 and the supportive function of SOX2, along with other factors, in promoting embryonic fate. Although the paper presents high-quality data, several key claims are not well-supported, and direct evidence is generally lacking.

Major Points:

(1) Although the authors claim that both maternal KO and maternal KO/zygotic hetero KO mice develop normally, the molecular changes in these groups appear overestimated. A wildtype control is recommended for a more robust comparison.

Thank you for your valuable feedback. However, I’m unclear on what is meant by “the molecular changes in these groups appear overestimated.” Could the reviewer kindly provide more details or clarify which specific aspects of the molecular changes they are referring to? This would help us better address the concern.

(2) The authors assert that OCT4 and SOX2 activate the pluripotent network via the OCT-SOX enhancer. However, the definition of this enhancer is based solely on proximity to TSSs, which is a rough approximation. Canonical enhancers are typically located in intronic and intergenic regions and marked by H3K4me1 or H3K27ac. Re-analyzing enhancer regions with these standards could be beneficial. Additionally, the definitions of "close to" or "near" in lines 183-184 are unclear and not defined in the legends or methods.

Thank you for this insightful comment. We will search for and analyze published omics data on H3K4me1 and H3K27ac in early embryos or mouse embryonic stem cells to address the concern of “enhancer”.

The definition of "close to" or "near" in lines 183-184 is in the legend of Figure 2E and methods. In the GSEA analysis, Ensembl protein-coding genes with TSSs located within 10 kb of ATAC-seq peak centers were included.

(3) There is no evidence that the decreased peaks/enhancers could be the direct targets of Oct4 and Sox2 throughout this manuscript. Figures 2 and 4 show only minimal peak annotations related to OCT and SOX motifs, and there is a lack of chromatin IP data. Therefore, claims about direct targets are not substantiated and should be appropriately revised.

Thank you for the comment. In Figure Supplement 3C, we analyzed published Sox2 CUT&RUN data from E4.5 ICMs (Li et al., Science, 2023), which demonstrates that the reduced ATAC-seq peaks in our Sox2 KO ICMs are enriched with Sox2 CUT&RUN signals. This data suggests that decreased peaks/enhancers could be the direct targets of Sox2. Unfortunately, we did not to find similar published data for Oct4 in embryos.

(4) Lines 143-146 lack direct data to support the claim. Actually, the main difference in cluster 1, 11 and 3, 8, 14 is whether the peak contains OCT-SOX motif. However, the reviewer cannot get any information of peaks activated by OCT4 rather than SOX2 in cluster 1, 11.

Thank you for the comment. As the reviewer pointed out, we agree that clusters 3, 8, 14 is more enriched with OCT-SOX motifs than clusters 1/11. However, this is consistent with our observation that the accessibility of peaks in clusters 1 and 11 mainly relies on Oct4, while the accessibility of clusters 3, 8, 14 relies on both Oct4 and Sox2. Probably the word “activate” is not accurate. We will rearrange the texts as below:

“Notably, compared to the peaks dependent on Oct4 but not Sox2 (Figure 2B, clusters 1 and 11), those reliant on both Oct4 and Sox2 show greater enrichment of the OCT-SOX motif (Figure 2B, clusters 3, 8 and 14). The former group tended to be already open in the morula, while the latter group became open in the ICM. “

Minor Points:

(1) Lines 153-159: The figure panel does not show obvious enrichment of SOX2 signals or significant differences in H3K27ac signals across clusters, thus not supporting the claim.

Thank you for the comments.

Line 153-159 reference two datasets:  Figure supplement 3C and 3D.

In Figure supplement 3C, the average plots above the heatmaps show that the decreased ATAC-seq peaks exhibited higher enrichment with Sox2 CUT&RUN signals compared to the increased or unchanged peaks.

Regarding Figure supplement 3D, we agree that the H3K27ac signal is only slightly more enriched on the decreased peaks than the unchanged peaks, However, it's important to note that only the top 57,512 strongest of the 142,096 unchanged peaks were included in the analysis. We excluded the weaker unchanged peaks because they are less informative. but if included, they could reduce the average H3K27ac signal for the unchanged peaks.

(2) Lines 189-190: The term "identify" is overstated for the integrative analysis of RNA-seq and ATAC-seq, which typically helps infer TF targets rather than definitively identifying them.

Thank you for the suggestion. We will replace “identify” with “infer”. The revised version is as below:

“In addition, integration of the ATAC-seq and RNA-seq data allowed us to infer previously unknown targets of Oct4 and Sox2, such as Sap30 and Uhrf1, which are essential for somatic cell reprogramming and embryonic development.”

(3) The Discussion is lengthy and should be condensed.

Thank you for the suggestion. We will shorten it.

eLife Assessment

This work presents a valuable finding on how the interplay between transcription factors SOX2 and OCT4 establishes the pluripotency network in early mouse embryos. Despite the high quality of the data, the evidence supporting the claims of the authors is currently incomplete and would benefit from more omics analysis such as H3K4me1 and H3K27ac CUT&Tag. The work will be of interest to biologists working on embryonic development.

Reviewer #1 (Public review):

Summary:

Numerous mechanism and structural studies reported the cooperative role of Oct4 and Sox2 during the establishment of pluripotency during reprogramming. Due to the difficulty in sample collection and RNA-seq with low-number cells, the precise mechanisms remain in early embryos. This manuscript reported the role of OCT4 and SOX2 in mouse early embryos using knockout models with low-input ATAC-seq and RNA-seq. Compared to the control, chromatin accessibility and transcriptome were affected when Oct4 and Sox2 were deleted in early ICM. Specifically, decreased ATAC-seq peaks showed enrichment of Motifs of TF such as OCT, SOX, and OCT-SOX, indicating their importance during early development. Moreover, by deep analysis of ATAC-seq and RNA-seq data, they found Oct4 and Sox2 target enhancer to activate their downstream genes. In addition, they also uncovered the role of OS during development from the morula to ICM, which provided the scientific community with a more comprehensive understanding.

Strengths:

On the whole, the manuscript is innovative, and the conclusions of this paper are mostly well supported by data, however, there are some issues that need to be addressed.

Weaknesses:

Major Points:

(1) In Figure 1, a more detailed description of the knockout strategy should be provided to clarify itself. The knockout strategy in Fig1 is somewhat obscure, such as how is OCT4 inactivated in Oct4mKO2 heterozygotes. As shown in Figure 1, the exon of OCT4 is not deleted, and its promoter is not destroyed. Therefore, how does OCT4 inactivate to form heterozygotes?

(2) Is ZP 3-Cre expressed in the zygotes? Is there any residual protein?

(3) What motifs are enriched in the rising ATAC-seq peaks after knocking out of OCT4 and SOX2?

(4) The ordinate of Fig4c is lost.

(5) Signals of H3K4me1, H3K27ac, and so on are usually used to define enhancers, and the loci of enhancers vary greatly in different cells. In the manuscript, the authors defined ATAC-seq peaks far from the TSS as enhancers. The definition in this manuscript is not strictly an enhancer.

(6) If Oct4 and Sox2 truly activate sap 30 and Uhrf 1, what effect does interfering with both genes have on gene expression and chromatin accessibility？

Reviewer #2 (Public review):

In this manuscript, Hou et al. investigate the interplay between OCT4 and SOX2 in driving the pluripotent state during early embryonic lineage development. Using knockout (KO) embryos, the authors specifically analyze the transcriptome and chromatin state within the ICM-to-EPI developmental trajectory. They emphasize the critical role of OCT4 and the supportive function of SOX2, along with other factors, in promoting embryonic fate. Although the paper presents high-quality data, several key claims are not well-supported, and direct evidence is generally lacking.

Major Points:

(1) Although the authors claim that both maternal KO and maternal KO/zygotic hetero KO mice develop normally, the molecular changes in these groups appear overestimated. A wildtype control is recommended for a more robust comparison.

(2) The authors assert that OCT4 and SOX2 activate the pluripotent network via the OCT-SOX enhancer. However, the definition of this enhancer is based solely on proximity to TSSs, which is a rough approximation. Canonical enhancers are typically located in intronic and intergenic regions and marked by H3K4me1 or H3K27ac. Re-analyzing enhancer regions with these standards could be beneficial. Additionally, the definitions of "close to" or "near" in lines 183-184 are unclear and not defined in the legends or methods.

(3) There is no evidence that the decreased peaks/enhancers could be the direct targets of Oct4 and Sox2 throughout this manuscript. Figures 2 and 4 show only minimal peak annotations related to OCT and SOX motifs, and there is a lack of chromatin IP data. Therefore, claims about direct targets are not substantiated and should be appropriately revised.

(4) Lines 143-146 lack direct data to support the claim. Actually, the main difference in cluster I, 11 and 3, 8, 14 is whether the peak contains OCT-SOX motif. However, the reviewer cannot get any information of peaks activated by OCT4 rather than SOX2 in cluster I, 11.

Minor Points:

(1) Lines 153-159: The figure panel does not show obvious enrichment of SOX2 signals or significant differences in H3K27ac signals across clusters, thus not supporting the claim.

(2) Lines 189-190: The term "identify" is overstated for the integrative analysis of RNA-seq and ATAC-seq, which typically helps infer TF targets rather than definitively identifying them.

(3) The Discussion is lengthy and should be condensed.

eLife Assessment

This valuable study provides a detailed picture of the synapse distributions for a set of visual projection neurons and their downstream partners, in combination with multi-compartmental modelling fitted to electrophysiological data. The model reveals interesting consequences of synapse topography for neuronal computation. The analysis, however, seems incomplete as the authors only analyze passive models of these spiking neurons, and do not attempt to connect their analysis to the bigger picture at the behavioral level.

Reviewer #1 (Public review):

Summary:

This study makes use of the EM reconstruction of the fly brain to investigate the morphology and topography of the synapses between retinotopic, loom-sensitive visual projection neurons (VPNs) and downstream descending neurons (DNs). The authors analyzed the distribution of synapses on the dendritic trees of DNs and performed multi-compartmental modelling to study the implications of the synaptic arrangements for neuronal integration of input signals.

Until recently, it has been unclear how spatial information is passed from retinotopic loom-sensitive neurons to descending neurons because the axons of the VPNs terminate in small optic glomeruli with no apparent topographic organization. It has recently been shown that synaptic weight gradients of VPNs connecting to DNs are the main mechanisms that allow for directed behavioral output (Dombrovski et al.). This study now goes one step further to determine if precise synapse location on the dendritic tree contributes further to the information processing. The study suggests that (1) none of the VPNs investigated show a retinotopic organization of synapses on DN dendrites. (2) Synapses of single VPNs are locally clustered. (3) Initial EPSPs at the synaptic location have, as expected, varying amplitudes but the amplitudes are passively normalized and only cover a small range when measured at the SIZ. (4) A near random distribution of synapses allows for linear integration of synaptic inputs when only a few VPNs are activated.

Strengths:

This study provides a detailed picture of the synapse distribution for a set of VPN and DN pairs, in combination with multi-compartmental modelling fitted to electrophysiological data. The data and methods are clear. The findings are overall interesting. The computational pipeline, which should ideally be made publicly available, will allow the community to make similar analyses on different neuronal classes, which will facilitate the detection of more general mechanisms of dendritic computation.

Weaknesses:

- In my opinion, we need more detail on the electrophysiological data and the fitting of the multi-compartmental model, which is the foundation of large parts of the study.<br /> - The study shows that the synapses of an individual VPN are locally clustered and suggests this as evidence for clustering of synapses of similar tuning (as has been shown previously in other systems). I am not fully convinced by the arguments here, since synapses of a single neuron are by necessity not randomly distributed in space.<br /> - As written, it was in parts unclear to me what the main hypotheses and conclusions were - e.g., how would a retinotopic distribution of synapses on dendritic trees contribute to information processing? Are the model predictions in line with the presumed behavioural role of these neurons?

Reviewer #2 (Public review):

Summary:

This article investigates the distribution of synapses on the dendritic arbors of descending neurons in the looming circuit of the fly visual system. The authors use publicly available EM reconstruction data of the adult fly brain to identify the positions of synapses from several types of visual projection neuron (VPN) to descending neuron (DN) connections. VPN dendrites are retinotopically organized, and axons from different VPN populations innervate distinct optic glomeruli. Yet the authors did not find any retinotopic organization of the synapses in the VPN-DN pairs they analyzed. They then constructed passive electrical models of the DNs with their structures extracted from the EM reconstructions. They focused on two specific DNs and parameterized their models by conducting whole-cell recordings within a voltage range below spiking threshold. Simulation of these passive models showed that irrespective of the location of a synapse, EPSPs became very similar at the spike initiation zone. This is consistent with the idea of synaptic democracy where EPSPs at far away synapses have higher amplitude compared to those nearer to the spike initiation zone so that they all attenuate to similar amplitudes while reaching there. The authors found that activating synapses from individual VPNs have the same effect as activating a random set of synapses. They conclude that despite some clustering of VPN synapses at small scale, they are distributed randomly over the dendritic arbor of DNs so that their EPSP amplitude encode the number of activated synapses, avoiding sublinearity from shunting effect.

Strengths:

- Experimental confirmation of the location of the spike initiation zone in the DN arbors is interesting and may provide better understanding of signal processing in these neurons.<br /> - Passive parameters obtained through electrophysiological recordings are useful.<br /> - These morphologically detailed single neuron models, if made available publicly, will be beneficial for building more complete models to understand the fly visual circuit.<br /> - The authors have complemented the work of Dombrovski et al by analyzing the distribution of synapses in more detail from EM data for a different set of neurons.

Weaknesses:

DNs are upstream of motorneurons, and one would expect, as demonstrated by Dombrovski et al, that specific DNs being activated by input from specific regions of the visual field will activate motoneurons so that the fly moves away from a looming object.

The current work analyzed the synapse distribution on two DNs that do not seem to have such role, and emphasize the lack of retinotopy. However, it is not clear why one would expect retinotopy in synapse location on the dendritic arbor. The comparison with mammalian visual circuits is not appropriate because those layers are extracting more and more complex visual features, whereas Drosophila DNs are supposed to drive motoneurons to generate suitable escape behavior.

- The authors do not suggest the functional roles of these DNs in controlling the movement of the fly. They argue that the synapse distribution and the passive electrotonic structure of these neurons are optimized to make the composite EPSP encode the number of activated synapses, but do not explain why this is important.

- Although DNs are spiking neurons, the authors limit their work to the subthreshold passive domain. If the EPSP at the spike initiation zone crosses spiking threshold, will encoding the number of synapses in EPSP amplitude still matter? Will it matter either if the composite EPSP remains subthreshold?

- The temporal aspect of the input has been ignored by the authors in their simulations. First, it is not clear all the synapses from a single VPN should get activated together. One would expect a spike in a VPN to arrive at different synapses with different time delays depending on their electrotonic distance from the spike initiation zone and the signal propagation speed in the neurites.

A looming stimulus should be expanding with time, but from the description of the simulations it does not seem that the authors have tried to incorporate this aspect in their design of the synaptic activation.

- The suggestion in the abstract that linear encoding of synapse number is default strategy which is then tuned by active properties and plasticity seems strange. Developmentally active properties do not get inserted into passive neurons.

- Much of the analysis (Figures 4, 5, 12) show relationships with physical distance along dendrite. In studying passive neurons it is more informative to use electrotonic distance which provides better insight.

Author response:

We thank the editors and reviewers for their valuable feedback and are committed to addressing their suggestions in a revised manuscript. We appreciate the reviewers’ recognition of the value of our findings, including the insights into the consequences of synaptic topography and the investigation of spike initiation zones in DNs, which further advance our understanding of signal processing. Our studies offer broader insights into synaptic organization and its significance for dendritic integration in an ethologically relevant context.

We particularly appreciate the reviewer's suggestion to elaborate on the electrophysiological properties of DNs and to consider the electrotonic distance in our analysis. We also thank the reviewers for highlighting points that need clarification. In short, our models suggest that DNs effectively distribute synapses to maintain linear encoding of synapse numbers when multiple synapses are coactivated. This supports the results of an earlier study suggesting that synapse number gradients encode the location of an approaching stimulus in these neurons (Dombrovski et al., 2023).

We also agree with the reviewers that the temporal activation of synapses is highly relevant for this system. However, we have focused on synaptic topography because the characterization of temporal patterns of VPN activity is currently lacking in the field. A more detailed investigation of temporal dynamics is therefore beyond the scope of this study.

With the publication of the reviewed preprint, we have now made the computational pipeline and models available on GitHub (https://github.com/AusbornLab/VPN-DN-synapse-normalization).

Reference

Dombrovski M, Peek MY, Park J-Y, Vaccari A, Sumathipala M, Morrow C, Breads P, Zhao A, Kurmangaliyev YZ, Sanfilippo P, Rehan A, Polsky J, Alghailani S, Tenshaw E, Namiki S, Zipursky SL, Card GM. 2023. Synaptic gradients transform object location to action. Nature 613:534–542. doi:10.1038/s41586-022-05562-8

eLife Assessment

This valuable study on strategies used by Pseudomonas to subvert hots immunity identifies a new immune evasion strategy. The study presents solid evidence on the cleavage of VgrG2B by Caspase 11 and the generation of fragments that inhibit activity of the NLRP3 inflammasome. This work should be of interest to immunologists and microbiologists.

Reviewer #1 (Public review):

In the manuscript entitled "A VgrG2b fragment cleaved by caspase-11/4 promotes Pseudomonas aeruginosa infection through suppressing the NLRP3 inflammasome", Qian et al. found an activation of the non-canonical inflammasome, but not the downstream NLRP3 inflammasome, during the infection of macrophage by P. aeruginosa, which is in sharp contrast to that by E. coli (Figure 1). In realizing that the suppression of the NLRP3 inflammasome is Caspase-11 dependent, the authors performed a screening among P. aeruginosa proteins and identified VgrG2b being a major substrate of Caspase-11 (Figure 2). Next, the authors mapped the cleavage site on VgrG2b to D883, and demonstrated that cleavage of VgrG2b by Caspase-11 is essential for the suppression of the NLRP3 inflammasome (Figure 3). Furthermore, they found that a binding between the C-terminal fragment of the cleaved VgrG2b and NLRP3 existed (Figure 4), which was then proved to block the association of NLRP3 with NEK7 (Figure 5). Finally, the authors demonstrated that blocking of VgrG2b cleavage, by either mutation of the D883 or administration of a designed peptide, effectively improved the survival rate of the P. aeruginosa-infected mice (Figure 6). This is a well-designed and executed study, with the results clearly presented and stated.

Reviewer #2 (Public review):

Summary:

In their manuscript, Quian and colleagues identified a novel mechanism by which Pseudomonas control inflammatory responses upon inflammasome activation. They identified a caspase-11 substrate (VgrG2b) which, upon cleavage, binds and inhibits the NLRP3 to reduce the production of pro-inflammatory cytokines. This is a unique mechanism that allows for the tailoring of the innate immune response upon bacterial recognition.

Strengths:

The authors are presenting here a novel conceptual framework in host-pathogen interactions. Their work is supported by a range of approaches (biochemical, cellular immunology, microbiology, animal models), and their conclusions are supported by multiple independent evidences. The work is likely to have an important impact on the innate immunity field and host-pathogen interactions field and may guide the development of novel inhibitors.

Weaknesses:

Although quite exhaustive, a few of the authors' conclusions are not fully supported (e.g., caspase-11 directly cleaving VgrG2b, the unique affinity of VgrG2b-C for NLRP3) and would require complementary approaches to validate their findings fully. This is minimal.

eLife Assessment

Wang et al's study addresses an important critical gap in our understanding of de novo epithelial polarization using MDCK cell doublets surrounded by ECM, providing convincing evidence through imaging and depletion studies on the role of conserved polarity proteins and the centrosome during this process. While the authors propose a clear hierarchical model, there is a need for further exploration of how microtubule organization contributes to this process. Specifically, live cell imaging of microtubules under mutants and their included ECM conditions, along with a more precise temporal mapping of microtubule dynamics in relation to proteins like Gp135, would strengthen the study's conclusions.

Reviewer #1 (Public review):

Summary:

Wang, Po-Kai, et al., utilized the de novo polarization of MDCK cells cultured in Matrigel to assess the interdependence between polarity protein localization, centrosome positioning, and apical membrane formation. They show that the inhibition of Plk4 with Centrinone does not prevent apical membrane formation, but does result in its delay, a phenotype the authors attribute to the loss of centrosomes due to the inhibition of centriole duplication. However, the targeted mutagenesis of specific centrosome proteins implicated in the positioning of centrosomes in other cell types (CEP164, ODF2, PCNT, and CEP120) did not affect centrosome positioning in 3D cultured MDCK cells. A screen of proteins previously implicated in MDCK polarization revealed that the polarity protein Par-3 was upstream of centrosome positioning, similar to other cell types.

Strengths:

The investigation into the temporal requirement and interdependence of previously proposed regulators of cell polarization and lumen formation is valuable to the community. Wang et al., have provided a detailed analysis of many of these components at defined stages of polarity establishment. Furthermore, the generation of PCNT, p53, ODF2, Cep120, and Cep164 knockout MDCK cell lines is likely valuable to the community.

Weaknesses:

Additional quantifications would highly improve this manuscript, for example it is unclear whether the centrosome perturbation affects gamma tubulin levels and therefore microtubule nucleation, it is also not clear how they affect the localization of the trafficking machinery/polarity proteins. For example, in Figure 4, the authors measure the intensity of Gp134 at the apical membrane initiation site following cytokinesis, but there is no measure of Gp134 at the centrosome prior to this.

Reviewer #2 (Public review):

Summary:

The authors decoupled several players that are thought to contribute to the establishment of epithelial polarity and determined their causal relationship. This provides a new picture of the respective roles of junctional proteins (Par3), the centrosome, and endomembrane compartments (Cdc42, Rab11, Gp135) from upstream to downstream.<br /> Their conclusions are based on live imaging of all players during the early steps of polarity establishment and on the knock-down of their expression in the simplest ever model of epithelial polarity: a cell doublet surrounded by ECM.

The position of the centrosome is often taken as a readout for the orientation of the cell polarity axis. There is a long-standing debate about the actual role of the centrosome in the establishment of this polarity axis. Here, using a minimal model of epithelial polarization, a doublet of daugthers MDCK cultured in Matrigel, the authors made several key observations that bring new light to our understanding of a mechanism that has been studied for many years without being fully explained:

(1) They showed that centriole can reach their polarized position without most of their microtubule-anchoring structures. These observations challenge the standard model according to which centrosomes are moved by the production and transmission of forces along microtubules.

(2) (However) they showed that epithelial polarity can be established in the absence of centriole.

(3) (Somehow more expectedly) they also showed that epithelial polarity can't be established in the absence of Par3.

(4) They found that most other polarity players that are transported through the cytoplasm in lipid vesicles, and finally fused to the basal or apical pole of epithelial cells, are moved along an axis which is defined by the position of centrosome and orientation of microtubules.

(5) Surprisingly, two non-daughters cells that were brought in contact (for 6h) could partially polarize by recruiting a few Par3 molecules but not the other polarity markers.

(6) Even more surprisingly, in the absence of ECM, Par 3 and centrosomes could move to their proper position close to the intercellular junction after cytokinesis but other polarity markers (at least GP135) localized to the opposite, non-adhesive, side. So the polarity of the centrosome-microtubule network could be dissociated from the localisation of GP135 (which was believed to be transported along this network).

Strengths:

(1) The simplicity and reproducibility of the system allow a very quantitative description of cell polarity and protein localisation.

(2) The experiments are quite straightforward, well-executed, and properly analyzed.

(3) The writing is clear and conclusions are convincing.

Weaknesses:

(1) The simplicity of the system may not capture some of the mechanisms involved in the establishment of cell polarity in more physiological conditions (fluid flow, electrical potential, ion gradients,...).

(2) The absence of centriole in centrinone-treated cells might not prevent the coalescence of centrosomal protein in a kind of MTOC which might still orient microtubules and intracellular traffic. How are microtubules organized in the absence of centriole? If they still form a radial array, the absence of a centriole at the center of it somehow does not conflict with classical views in the field.

(3) The mechanism is still far from clear and this study shines some light on our lack of understanding. Basic and key questions remain:<br /> a) How is the centrosome moved toward the Par3-rich pole? This is particularly difficult to answer if the mechanism does not imply the anchoring of MTs to the centriole or PCM.<br /> b) What happens during cytokinesis that organises Par3 and intercellular junction in a way that can't be achieved by simply bringing two cells together? In larger epithelia cells have neighbours that are not daughters, still, they can form tight junctions with Par3 which participates in the establishment of cell polarity as much as those that are closer to the cytokinetic bridge (as judged by the overall cell symmetry). Is the protocol of cell aggregation fully capturing the interaction mechanism of non-daughter cells?

Reviewer #3 (Public review):

Here, Wang et al. aim to clarify the role of the centrosome and conserved polarity regulators in apical membrane formation during the polarization of MDCK cells cultured in 3D. Through well-presented and rigorous studies, the authors focused on the emergence of polarity as a single MDCK cell divided in 3D culture to form a two-cell cyst with a nascent lumen. Focusing on these very initial stages, rather than in later large cyst formation as in most studies, is a real strength of this study. The authors found that conserved polarity regulators Gp135/podocalyxin, Crb3, Cdc42, and the recycling endosome component Rab11a all localize to the centrosome before localizing to the apical membrane initiation site (AMIS) following cytokinesis. This protein relocalization was concomitant with a repositioning of centrosomes towards the AMIS. In contrast, Par3, aPKC, and the junctional components E-cadherin and ZO1 localize directly to the AMIS without first localizing to the centrosome. Based on the timing of the localization of these proteins, these observational studies suggested that Par3 is upstream of centrosome repositioning towards the AMIS and that the centrosome might be required for delivery of apical/luminal proteins to the AMIS.

To test this hypothesis, the authors generated numerous new cell lines and/or employed pharmacological inhibitors to determine the hierarchy of localization among these components. They found that removal of the centrosome via centrinone treatment severely delayed and weakened the delivery of Gp135 to the AMIS and single lumen formation, although normal lumenogenesis was apparently rescued with time. This effect was not due to the presence of CEP164, ODF2, CEP120, or Pericentrin. Par3 depletion perturbed the repositioning of the centrosome towards the AMIS and the relocalization of the Gp135 and Rab11 to the AMIS, causing these proteins to get stuck at the centrosome. Finally, the authors culture the MDCK cells in several ways (forced aggregation and ECM depleted) to try and further uncouple localization of the pertinent components, finding that Par3 can localize to the cell-cell interface in the absence of cell division. Par3 localized to the edge of the cell-cell contacts in the absence of ECM and this localization was not sufficient to orient the centrosomes to this site, indicating the importance of other factors in centrosome recruitment.

Together, these data suggest a model where Par3 positions the centrosome at the AMIS and is required for the efficient transfer of more downstream polarity determinants (Gp135 and Rab11) to the apical membrane from the centrosome. The authors present solid and compelling data and are well-positioned to directly test this model with their existing system and tools. In particular, one obvious mechanism here is that centrosome-based microtubules help to efficiently direct the transport of molecules required to reinforce polarity and/or promote lumenogenesis. This model is not really explored by the authors except by Pericentrin and subdistal appendage depletion and the authors do not test whether these perturbations affect centrosomal microtubules. Exploring the role of microtubules in this process could considerably add to the mechanisms presented here. In its current state, this paper is a careful observation of the events of MCDK polarization and will fill a knowledge gap in this field. However, the mechanism could be significantly bolstered with existing tools, thereby elevating our understanding of how polarity emerges in this system.

eLife Assessment

This important study shows that Toxoplasma gondii uses paracrine mechanisms, in addition to cell-intrinsic methods, to evade the host immune system, with MYR1 playing a key role in transporting effector molecules into host cells. The authors present convincing evidence that in vivo, MYR1-deficient parasites can be rescued by wild-type parasites, revealing a limitation in pooled CRISPR screens, where such paracrine effects may obscure the identification of key parasite pathways involved in immune evasion.

Reviewer #1 (Public review):

Previous studies have highlighted some of these paracrine activities of Toxoplasma - and Rasogi et al (mBio, 2020) used a single cell sequencing approach of cells infected in vitro with the WT or MYR KO parasites - and one of their conclusions was that MYR-1 dependent paracrine activities counteract ROP-dependent processes. Similarly, Chen et al (JEM 2020) highlighted that a particular rhoptry protein (ROP16) could be injected into uninfected macrophages and move them to an anti-inflammatory state that might benefit the parasite.

There are caveats around immunity and as yet no insight into how this works. In Figure 2 there is a marked defect in the ability of the parasites to expand at day 2 and day 5. Together, these data sets suggest that this paracrine effect mediated by MYR-1 works early - well before the development of adaptive responses.

Reviewer #2 (Public review):

Summary:

In this manuscript by Torelli et al., the authors propose that the major function of MYR1 and MYR1-dependent secreted proteins is to contribute to parasite survival in a paracrine manner rather than to protect parasites from cell-autonomous immune response. The authors conclude that these paracrine effects rescue ∆MYR1 or knockouts of MYR1-dependent effectors within pooled in vivo CRISPR screens.

Strengths:

The authors raised a more general concern that pooled CRISPR screens (not only in Toxoplasma but also other microbes or cancers) would miss important genes by "paracrine masking effect". Although there is no doubt that pooled CRISPR screens (especially in vivo CRISPR screens) are powerful techniques, I think this topic could be of interest to those fields and researchers.

Weaknesses:

In this version, the reviewer is not entirely convinced of the 'paracrine masking effect' because the in vivo experiments should include appropriate controls (see major point 2).

(1) It is convincing that co-infection of WT and ∆MYR1 parasites could rescue the growth of ∆MYR1 in mice shown by in vivo luciferase imaging. Also, this is consistent with ∆MYR1 parasites showing no in vivo fitness defect in the in vivo CRISPR screens conducted by several groups. Meanwhile, it has been reported previously and shown in this manuscript that ∆MYR1 parasites have an in vitro growth defect; however, ∆MYR1 parasites show no in vitro fitness defect the in vitro pooled CRISPR screen. The authors show that the competition defect of ∆MYR1 parasites cannot be rescued by co-infection with WT parasites in Figure 1c, which might indicate that no paracrine rescue occurred in an in vitro environment. The authors seem not to mention these discrepancies between in vitro CRISPR screens and in vitro competition assays. Why do ∆MYR1 parasites possess neutral in vitro fitness scores in in vitro CRISPR screens? Could the authors describe a reasonable hypothesis?

(2) The authors developed a mixed infection assay with an inoculum containing a 20:80 ratio of ΔMYR1-Luc parasites with either WT parasites or ΔMYR1 mutants not expressing luciferase, showing that the in vivo growth defect of ∆MYR1 parasites is rescued by the presence of WT parasites. Since this experiment lacks appropriate controls, interpretation could be difficult. Is this phenomenon specific to MYR1? If a co-inoculum of ∆GRA12-Luc with either WT parasites or GRA12 parasites not expressing luciferase is included, the data could be appropriately interpreted.

(3) In the Discussion part, the authors argue that the rescue phenotype of mixed infection is not due to co-infection of host cells (lines 307-310). This data is important to support the authors' paracrine hypothesis and should be shown in the main figure.

(4) In the Discussion part, the authors assume that the rescue phenotype is the result of multiple MYR1-dependent effectors. I admit that this hypothesis could be possible since a recently published paper described the concerted action of numerous MYR1-dependent or independent effectors contributing to the hypermigration of infected cells (Ten Hoeve et al., mBio, 2024). I think this paragraph would be kind of overstated since the authors did not test any of the candidate effectors. Since the authors possess ∆IST parasites, they can test whether IST is involved in the "paracrine masking effect" or not to support their claim.

eLife Assessment

This important study reports a detailed quantification of the population dynamics of Salmonella enterica serovar Typhimurium in mice. Bacterial burden and founding population sizes across various organs were quantified, revealing pathways of dissemination and reseeding of the gastrointestinal tract from systemic organs. Using various techniques, including genetic distance measurements, the authors present compelling evidence to support their conclusions, thus presenting new knowledge that will be of broad interest to scientists focusing on infectious diseases.

Reviewer #1 (Public review):

Hotinger et al. explore the population dynamics of Salmonella enterica serovar Typhimurium in mice using genetically tagged bacteria. In addition to physiological observations, pathology assessments, and CFU measurements, the study emphasizes quantifying host bottleneck sizes that limit Salmonella colonization and dissemination. The authors also investigate the genetic distances between bacterial populations at various infection sites within the host.

Initially, the study confirms that pretreatment with the antibiotic streptomycin before inoculation via orogastric gavage increases the bacterial burden in the gastrointestinal (GI) tract, leading to more severe symptoms and heightened fecal shedding of bacteria. This pretreatment also significantly reduces between-animal variation in bacterial burden and fecal shedding. The authors then calculate founding population sizes across different organs, discovering a severe bottleneck in the intestine, with founding populations reduced by approximately 10^6-fold compared to the inoculum size. Streptomycin pretreatment increases the founding population size and bacterial replication in the GI tract. Moreover, by calculating genetic distances between populations, the authors demonstrate that, in untreated mice, Salmonella populations within the GI tract are genetically dissimilar, suggesting limited exchange between colonization sites. In contrast, streptomycin pretreatment reduces genetic distances, indicating increased exchange.

In extraintestinal organs, the bacterial burden is generally not substantially increased by streptomycin pretreatment, with significant differences observed only in the mesenteric lymph nodes and bile. However, the founding population sizes in these organs are increased. By comparing genetic distances between organs, the authors provide evidence that subpopulations colonizing extraintestinal organs diverge early after infection from those in the GI tract. This hypothesis is further tested by measuring bacterial burden and founding population sizes in the liver and GI tract at 5 and 120 hours post-infection. Additionally, they compare orogastric gavage infection with the less injurious method of infection via drinking, finding similar results for CFUs, founding populations, and genetic distances. These results argue against injuries during gavage as a route of direct infection.

To bypass bottlenecks associated with the GI tract, the authors compare intravenous (IV) and intraperitoneal (IP) routes of infection. They find approximately a 10-fold increase in bacterial burden and founding population size in immune-rich organs with IV/IP routes compared to orogastric gavage in streptomycin-pretreated animals. This difference is interpreted as a result of "extra steps required to reach systemic organs."

While IP and IV routes yield similar results in immune-rich organs, IP infections lead to higher bacterial burdens in nearby sites, such as the pancreas, adipose tissue, and intraperitoneal wash, as well as somewhat increased founding population sizes. The authors correlate these findings with the presence of white lesions in adipose tissue. Genetic distance comparisons reveal that, apart from the spleen and liver, IP infections lead to genetically distinct populations in infected organs, whereas IV infections generally result in higher genetic similarity.

Finally, the authors investigate GI tract reseeding, identifying two distinct routes. They observe that the GI tracts of IP/IV-infected mice are colonized either by a clonal or a diversely tagged bacterial population. In clonally reseeded animals, the genetic distance within the GI tract is very low (often zero) compared to the bile population, which is predominantly clonal or pauciclonal. These animals also display pathological signs, such as cloudy/hardened bile and increased bacterial burden, leading the authors to conclude that the GI tract was reseeded by bacteria from the gallbladder bile. In contrast, animals reseeded by more complex bacterial populations show that bile contributes only a minor fraction of the tags. Given the large founding population size in these animals' GI tracts, which is larger than in orogastrically infected animals, the authors suggest a highly permissive second reseeding route, largely independent of bile. They speculate that this route may involve a reversal of known mechanisms that the pathogen uses to escape from the intestine.

The manuscript presents a substantial body of work that offers a meticulously detailed understanding of the population dynamics of S. Typhimurium in mice. It quantifies the processes shaping the within-host dynamics of this pathogen and provides new insights into its spread, including previously unrecognized dissemination routes. The methodology is appropriate and carefully executed, and the manuscript is well-written, clearly presented, and concise. The authors' conclusions are well-supported by experimental results and thoroughly discussed. This work underscores the power of using highly diverse barcoded pathogens to uncover the within-host population dynamics of infections and will likely inspire further investigations into the molecular mechanisms underlying the bottlenecks and dissemination routes described here.

Major point:

Substantial conclusions in the manuscript rely on genetic distance measurements using the Cavalli-Sforza chord distance. However, it is unclear whether these genetic distance measurements are independent of the founding population size. I would anticipate that in populations with larger founding population sizes, where the relative tag frequencies are closer to those in the inoculum, the genetic distances would appear smaller compared to populations with smaller founding sizes independent of their actual relatedness. This potential dependency could have implications for the interpretation of findings, such as those in Figures 2B and 2D, where antibiotic-pretreated animals consistently exhibit higher founding population sizes and smaller genetic distances compared to untreated animals.

Reviewer #2 (Public review):

In this paper, Hotinger et. al. propose an improved barcoded library system, called STAMPR, to study Salmonella population dynamics during infection. Using this system, the authors demonstrate significant diversity in the colonization of different Salmonella clones (defined by the presence of different barcodes) not only across different organs (liver, spleen, adipose tissues, pancreas, and gall bladder) but also within different compartments of the same gastrointestinal tissue. Additionally, this system revealed that microbiota competition is the major bottleneck in Salmonella intestinal colonization, which can be mitigated by streptomycin treatment. However, this has been demonstrated previously in numerous publications. They also show that there was minimal sharing between populations found in the intestine and those in the other organs. Upon IV and IP infection to bypass the intestinal bottleneck, they were able to demonstrate, using this library, that Salmonella can renter the intestine through two possible routes. One route is essentially the reverse path used to escape the gut, leading to a diverse intestinal population; while the other, through the bile, typically results in a clonal population. Although the authors showed that the STAMPR pipeline improved the ability to identify founder populations and their diversity within the same animal during infections, some of the conclusions appear speculative and not fully supported.

(1) It's particularly interesting how the authors, using this system, demonstrate the dominant role of the microbiota bottleneck in Salmonella colonization and how it is widened by antibiotic treatment (Figure 1). Additionally, the ability to track Salmonella reseeding of the gut from other organs starting with IV and IP injections of the pathogen provides a new tool to study population dynamics (Figure 5). However, I don't think it is possible to argue that the proximal and distal small intestine, Peyer's patches (PPs), cecum, colon, and feces have different founder populations for reasons other than stochastic variations. All the barcoded Salmonella clones have the same fitness and the fact that some are found or expanded in one region of the gastrointestinal tract rather than another likely results from random chance - such as being forced in a specific region of the gut for physical or spatial reasons-and subsequent expansion, rather than any inherent biological cause. For example, some bacteria may randomly adhere to the mucus, some may swim toward the epithelial layer, while others remain in the lumen; all will proliferate in those respective sites. In this way, different founder populations arise based on random localization during movement through the gastrointestinal tract, which is an observation, but it doesn't significantly contribute to understanding pathogen colonization dynamics or pathogenesis. Therefore, I would suggest placing less emphasis on describing these differences or better discussing this aspect, especially in the context of the gastrointestinal tract.

(2) I do think that STAMPR is useful for studying the dynamics of pathogen spread to organs where Salmonella likely resides intracellularly (Figure 3). The observation that the liver is colonized by an early intestinal population, which continues to proliferate at a steady rate throughout the infection, is very interesting and may be due to the unique nature of the organ compared to the mucosal environment. What is the biological relevance during infection? Do the authors observe the same pattern (Figures 3C and G) when normalizing the population data for the spleen and mesenteric lymph nodes (mLN)? If not, what do the authors think is driving this different distribution?

(3) Figure 6: Could the bile pathology be due to increased general bacterial translocation rather than Salmonella colonization specifically? Did the authors check for the presence of other bacteria (potentially also proliferating) in the bile? Do the authors know whether Salmonella's metabolic activity in the bile could be responsible for gallbladder pathology?