In David Gerrold's The Trouble with Tribbles: The Story Behind Star Trek's Most Popular Episode, he describes how he used a 12-pitch Selectric to type the 1967 episode. When the studio retyped it in pica (10-pitch) it came out to 90 pages and had to be cut down significantly to fit the show's running time.

The difference amounts to approximately 3 words per page and about 50 words per page.

The November 1952 issue of Boys Life had an advertisement for contest for a gold-plated Royal Quiet De Luxe typewriter.

timestamp

I compared Twitter (now X) and Instagram post views. Both immediately allow likes, comments, and sharing. One step away, Twitter offers retweets and quoting, while Instagram allows saving posts. Two steps away, Twitter gives options like adding to lists, and Instagram provides reporting. Both focus on easy engagement but differ in extra features like lists vs. post saving.

For a social media site focused on collaborative learning (like a mix of Reddit and Khan Academy), I'd design a profile page showing posts, achievements, and study interests. Immediate actions: create posts, comment, upvote. One or two steps away: start discussions, follow users. Not allowed: deleting others' posts, editing achievements.

consumption linked to sexual activity

body of the economy (national body) considereds alongside Anna's body -- the cacao is designed to enter both and subsequently transform it (by creolization or bodily transformation, respectively)

https://oldbobsoldtypewriters.com/

Scott Drudge is the proprietor<br /> Second generation typewriter repair as his dad Bob was the original namesake of Old Bob's Old Typewriters.

Taking a sabbatical in 2024 and expected back in late 2024.

I also chose this quote because i feel like it has alot of weight when talking about the current impact redlining has and the impact it has silently had in our society for decades. It also helps us dive into what "The new Deal is" and how the creators had ill intentions with it. It also helps describe the impact this bill had on the citizens of the united states.

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.

As a Chinese student, I was shocked to read this text, I did not think that in the 1960s and 1970s, there were already E-mail boxes in the world. In my opinion, the 1960s and 1970s seemed to be the period when China vigorously developed industry and agriculture, and such things as E-mail and computers seemed very remote to China at that time.

This is an interesting example of how social media doesn't have to depend on technology, in fact some notes; Graffiti walls; Bulletin boards and other things that can be used as carriers of information transmission can also be called "social media". From this perspective, technology only increases its functions and improves the efficiency of information transmission for social media, and its basic form has been finalized before the emergence of software and smart phones.

It's interesting how we are back in the age of rumors and theories. Back then, people didn't have the tools to easily fact check. In modern times, people don't have the attention span to fact check what they see on the internet. Those short, half truth rumors spread like wildfire now.

I'm not quite clear how confusion relates to the idea above. Are you focusing on the feelings of being outside the home and having to find a hidden key?

To some extent you miss Ruberg's critique of empathy games that led her to this conclusion. Can you rework the summary to show how Ruberg is suggesting alternatives?

more detail needed to explain how the example works

awesome point and it works to help clear up the paraphrase--some backwards work witll help.

how does the example follow from the last claim?

a stronger connection to the ideas of the summary is needed. One could perhaps note that GH questions ideas of empathy in the spirit of Ruberg

The 2024 Phoenix Type-In by [[Joe Van Cleave]]

Platen shrinkage

• most typewriters are 6 lines per inch
• 6.5 lines per inch based on actual measurement per JVC on one of his machines
• 2mm shrinkage??
• Per Bob/Typewriter Muse 1.1

Bob had a machine that was supposed to be 1.27 but was measured at 1.259 when pulled off. So shrinkage of platens can be roughly fifteen hundredths of an inch (0.015" or about 0.4mm)

Bob at Typewriter Muse custom tunes platens to the typewriter. Only place doing platens outside of JJ Short.

JVC's partner took him to the Phoenix Type-in for her birthday.

Bill Wahl of Mesa Typewriter Exchange

grandfather started in the 40s<br /> bill started in 73<br /> part time help to 92 and now by himself<br /> does his benchwork after hours and chats during the day

Ted Munk

adding machine database consideration

looking for service manuals for: - royal portables 50-59<br /> - skyriter 40s / 50s<br /> - sm9 service manual

Royal Mercury manual is a clear, well-written manual. The Smith-Corona series 5 typewriter manuals are great too, though a bit more dense.

Brian Goode and Christy organized this year's Phoenix Type-In.

strong point --is this kind of blending of experience what you see gone home as doing?

I wonder if the summary gets at this important claim or idea in Ruberg's passage?

!!!

inescapability of the desire taht any kind of storytelling that will by narrative turn them into something useful/instructive

what danger/risk are there associated w turning these inventoried people from the past into characters form which we extract meaning

"even if I tell stories, is that still doing the same thing history is doing? is there a way out of that? -- trying to make meaning out of the past that respects an ethics of responsibility toward the subjects of the past"

foot note like slavehold -- place where names are kept and held under the body of the text

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

don't have to enter in the amount of water.

Don't include the equation in the methods section, only in the introduction.

This should say "Figure 1," and the y-axis should be density, not fluorescence.

This should be volume of the sucrose standard.

No mention of identifying the metal.

This switched from passive to imperative writing.

Don't say "the" the first time you mention a piece of equipment.

this section may be important for the writing

Observation: Two options of protecting shipping interests from the barbary States which was buila navy to rival from barbary states or pay them protection money.

Interpretation It's only two ways to give exchange to Barbary States which was build a navy to rival that of the Barbary States or pay them protection money which our country decided to pay protection money

Observation: The Government of the United States is not founded on the Christian Religion

Interpretation The Government is not founded on specific religion.

Observation: There a firm and perpetual peace and friendship between the united states of America and the bey.

Interpretation There is a peaceful agreement with the united states of america and the bey.

Insert Stuff >> Video Note

Kwalitatief: informatie verzamelen over cultuur waarmee voor het eerst te maken is, om theoretische modellen op te bouwen en hypotheses te genereren. Kwantitatief: voor hypothesetoetsing; wat?

Minder bias=betere data. Betere data vergelijking wereldwijd=hogere equivalentie.

Does not specify what kind of rod

The graph needs a title in the caption: "Figure 1".

Specify what data was included in the graph, and refer to it as "Figure 1."

The mass was found, not the weight.

Again, don't mention the equipment beforehand.

This should be the difference in volumes between the initial and final

They should mention using equation 1, and should specify how they got the volume to use in the equation. It wasn't just the final volume of the water and rod that was measured.

No need to mention extra info about using the balance. Just say the mass of the metal rod measured and recorded.

Don't mention the materials needed before discussing using them.

This demonstrates Biard's observations and awareness that Mi'kmaq communities operated differently from French ones (both in France itself as well as Nouvelle France). He notes that the Mi'kmaq or Canadians are nomadic and thus their lifestyle is not conducive to traditional Christian practices (mass, sermons, sacraments, etc.), this highlights how important it is for missionaries to acclimate to Mi'kmaq culture and communities by living and traveling with them, learning their language, etc. By building these relationships and trust with the Mi'kmaq it becomes easier to facilitate their conversion to the the Catholic faith.

Author response:

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

Reviewer 1

Overall, this work is quite comprehensive and is logically and rigorously designed. The phenotypic and functional data on 2C are strong.

Thank you for your positive feedback on our findings!

(1) Comment from Reviewer 1 suggesting the mechanistic insights of 2C are primarily derived from transcriptomic and genomic datasets without experimental verification. 

Thank you for emphasizing the importance of experimental validation to support our transcriptomic and genomic findings. We acknowledge the gap in direct experimental evidence for the mechanistic insights of section 2C and recognize the value of such validation in strengthening our conclusions. While we recognize the importance of such validation, our current dataset lacks the comprehensive preliminary results necessary for inclusion in the supplemental material. We believe that the mechanistic insights presented offer a substantial foundation for the future research, where we aim to explore these aspects in depth with targeted experimental approaches.

Reviewer 2

Together their data may suggest a regenerative effect of 2C both in vitro and in vivo settings. If confirmed, this study might unlock therapeutic strategy for cardiac regeneration.

Thank you for your positive comment on the significance of our findings and the valuable therapeutic potential of 2C in cardiac regeneration!

(1) Comment from Reviewer 2 pointing out the the main hypothesis (line 50) that Isl1 cells have regenerative properties is not extremely novel. 

We agree with the reviewer that Isl1-positive cells possess regenerative properties. Following the reviewer’s suggestion, we have revised the original wording (line 46 in the revised manuscript).

(2) Comment from Reviewer 2 asking for providing a rationale for this 20x reduction of A-485 concentration? It would be useful to get a titration of this compound for the effects tested. 

As suggested by the reviewer, we have added the titration results of A-485 in Figure 1—figure supplement 1F-G.

(3) Comment from Reviewer 2 confusing to clearly understand what proportion of CMs dedifferentiate to become RCCs. The lineage tracing data suggests only 0.6%-1.5% of cells undergo this transition. It is difficult to understand how such a small fraction can have wide effects in their different experimental settings. This is specifically true when the author quantified nuclear and cytosolic area on brightfield pictures - would the same effect on nuclear/cytosolic area be observed in Isl1 KO cells. 

We appreciate the reviewer's insightful observation on the proportion of CMs undergoing dedifferentiation into RCCs and the potential impact of this subset on our experimental outcomes. The lineage tracing data indicating that only 0.6%-1.5% of CMs transition to RCCs indeed reflects a modest proportion. This observation raises valid questions regarding the broader implications of such a limited fraction in the context of cardiac regeneration and the experimental effects reported. It's important to note that while the proportion of CMs dedifferentiating into RCCs is small, the biological significance and potential impact of these RCCs could be disproportionately large. Emerging evidence suggests that even a minimal number of stem or progenitor cells can exert significant effects on tissue repair and regeneration, possibly through paracrine mechanisms or by acting as key signaling centers within the tissue microenvironment (Fernandes et al., 2015). Regarding the specific question about 2C’s effects on nuclear/cytosolic area in Isl1 knockout (KO) cells, we appreciate the suggestion and consider that such comparative studies would provide valuable insights for future comprehensively understanding the significant impact of 2C-induced RCCs in future search. In addition, ISL1 KO cells are also described in detail in the article published in eLife in 2018 by Quaranta et al.

(4) Comment from Reviewer 2 asking for the effect of CHIR + I-BET-762 alone. 

As suggested by the reviewer, we have added the results of CHIR + T-BET-762 in Figure 1—figure supplement 1H.

(5) Comment from Reviewer 2 suggesting a transparent explaination about the effects of A-485 on acetylation status.

We thank the reviewer for highlighting the confusion regarding the effects of A-485 on the acetylation status of H3K27Ac and H3K9Ac. Upon re-examination of our data and statements, we recognize the need for clarity in our explanation and the inconsistency it may have caused (lines 223-231 on page 8).

Initially, our observations suggested a selective effect of A-485 on H3K27Ac based on early experimental results (Figure 7—figure supplement 1). This conclusion was drawn from preliminary analyses that focused predominantly on this specific histone mark. However, upon further comprehensive examination of our data, including additional replicates and more sensitive detection methods, we observed that A-485 also impacts H3K9Ac levels (Figure 7—figure supplement 1F). This latter finding emerged from expanded datasets that were not initially considered in our preliminary conclusions.

The "further analyses" mentioned referred to these subsequent experimental investigations, which included chromatin immunoprecipitation (ChIP) assays and extended sample sizes, providing a more robust dataset for evaluating the effects of A-485. We understand the importance of transparency and rigor in scientific communication. To address this, we have revised the manuscript to clearly delineate the progression of our analyses and the evidential basis for our revised understanding of A-485's effects. This includes a detailed description of the methodologies employed in our follow-up experiments (line 537 on page 27), the statistical approaches for data analysis (lines 226-227 in supporting information), and how these led to the updated interpretation regarding A-485's impact on histone acetylation (lines232-269).

(6) Comment from Reviewer 2 asking for the difference in the ChIP peaks representation of the y-axis on the ChIP traces.

Thank you for raising this quest. Actually, we did not normalise the sequencing depth and the y-axis represents the number of counts (line 537 on page 27 and lines 226-227 in supporting information).

(7) Comment from Reviewer 2 suggesting the possibility of testing this 2C protocol on mESCs to see if similar changes are subject to and how these mouse RCCs differ transcriptionally from Isl1+ progenitor cells isolated from neonatal mice (P1-P5)?

Thank you for your insightful questions. Testing the 2C protocol on mouse embryonic stem cells (mESCs) to observe if similar changes occur presents an excellent opportunity to further validate the versatility and applicability of our findings across different stem cell models. We agree that such experiments would not only strengthen the current study but also provide valuable insights into the conservation of mechanisms across species. We are currently in the process of setting up experiments to address this very question and anticipate that the results will significantly contribute to our understanding of cardiomyocyte differentiation processes. Regarding the transcriptional comparison between mouse regenerative cardiac cells (RCCs) induced by our 2C protocol and Isl1+ progenitors isolated from neonatal mice (P1-P5), this comparison is indeed crucial for delineating the specific identity and developmental potential of the RCCs generated. However, a comprehensive side-by-side transcriptomic analysis is required to systematically identify these differences and understand their biological implications. We plan to undertake this analysis as part of our future studies, which will include detailed RNA sequencing and comparative gene expression profiling to elucidate the transcriptional similarities and differences between these cell populations. These future directions will enhance our current findings, provide a deeper mechanistic understanding, and confirm the potential of the 2C protocol in regenerative medicine applications. We appreciate the reviewer's suggestions and acknowledge the importance of these experiments in advancing the field.

(8) Comment from Reviewer 2 with a suggestion to have a precise clarification of statistics & data acquisition.

As suggested by the reviewer, we have revised clarifications to make them clearer (lines 228-233 in supporting information and a precise description of each paragraph involving statistical analyses).

Reviewer 3

The findings may have a translation potential. The idea of promoting the regenerative capacity of the heart by reprogramming CMs into RCCs is interesting.

Thank you for your appreciation of the significance and translational potential of our findings!

(1) Comment from Reviewer 3 suggesting the mechanism involved in the 2C-mediated generation of RCCs is unclear and the lead found in the RAN-seq and ChIP-seq are not experimatally validated.

We acknowledge the reviewer's concern regarding the lack of experimental validation for the mechanisms identified through RNA-seq and ChIP-seq analyses in the generation of RCCs from the 2C state. We understand the importance of substantiating these molecular leads with empirical data to strengthen our conclusions. Currently, our findings are based on in-depth bioinformatic analyses, which have provided us with valuable insights and a strong basis for hypothesis generation. Moving forward, we plan to prioritize experimental validation of key pathways and targets identified in our study. This will include designing targeted experiments to elucidate the functional roles of these mechanisms in the 2C-mediated generation of RCCs. We appreciate the opportunity to clarify our approach and future directions, and we are committed to addressing this gap in subsequent work.

(2) Comment from Reviewer 3 considering the very low number of RCCs (0.6%-1.5% of cells) generated cannot protect the heart from MI, and whether 2C affects the the survival or metabolism of existing CM under hypoxia conditions, and what percentage of cells are regenerated by 2C treatment post-MI?

We appreciate the reviewer's insightful queries regarding the protective effects of 2C treatment against myocardial infarction (MI) given the low percentage of RCCs generated. It is our hypothesis that the benefits of 2C treatment extend beyond mere cell numbers. We propose that 2C may enhance the survival and metabolic resilience of existing CMs under hypoxic conditions, thereby contributing to cardiac protection post-MI. Our future investigations will aim to quantify the precise percentage of cells regenerated by 2C treatment post-MI and explore its broader impacts on cardiac tissue survival and repair mechanisms.

(3) Comment from Reviewer 3 suggesting the administration of 2C in mice, as well as whether 2C affects cardiac function under basal conditions and any physiology in mice, and the need to examine cardiac structural and functional parameters after administration of 2C.

We appreciate the reviewer's interest in the potential effects of 2C administration on cardiac function and overall physiology in mice. While we observed a decrease in body weight at P5 compared to controls, our immunofluorescence staining did not indicate any changes in cardiac structure (Figure 4— figure supplement 1E). This suggests that while 2C administration impacts neonatal rat physiology, it does not adversely affect cardiac structure under basal conditions. Further investigations are planned to assess the functional parameters of the heart post-2C administration to comprehensively understand its effects.

(4) Comment from Reviewer 3 suggesting the potential effects of 2C on other cell types of the heart, including fibroblasts and endothelial cells, in vitro and in vivo.

We value the reviewer's suggestion to explore the effects of 2C on various cardiac cell types, including fibroblasts and endothelial cells, both in vitro and in vivo. We acknowledge the importance of understanding the broader impact of 2C treatment across different cell populations within the heart, given its potential protective effects. To address this, we are designing a series of experiments to assess 2C's influence on these cell types, aiming to elucidate any changes in their behavior, proliferation, and function following treatment. This comprehensive approach will allow us to better understand the mechanistic basis of 2C's cardioprotective effects.

(5) Comment from Reviewer 3 suggesting validation the effect of 2C in a dose-dependent manner.

As suggested by the reviewer, we have supplemented the effect of 2C in dose-dependent (Figure 1— figure supplement 1F-G).

(6) Comment from Reviewer 3 suggesting an explanation of how A-485 affects H3K27Ac and H3K9Ac.

We appreciate the reviewer pointing out the discrepancy regarding the effects of A-485 on H3K27Ac and H3K9Ac. Upon re-examination of our data, we realize that our initial interpretation may have overlooked the broader impact of A-485 on histone acetylation patterns. It appears that A-485 does indeed influence both H3K27Ac and H3K9Ac, contrary to our initial statement. This oversight will be corrected in our revised manuscript, where we will provide a more detailed analysis and discussion of A-485's impact on these histone marks, alongside an explanation for the observed effects (lines 223-269 across page 8-9).

(7) Comment from Reviewer 3 with a correction to use "regeneration" at the screeing stage.

As suggested by the reviewer, we have amended the wording in the text (line 66 on page 3).

Reviewer 4

Comment from Reviewer 4 suggesting more information that clarifies and justifies the hypothesis.

As suggested by the reviewer, we added more information to clarify and justify the hypothesis (lines 39-47 on page 3).

(1) Comment from Reviewer 4 pointing out the story line is not well developed.

To address the reviewer’s question, we revised the manuscript to ensure a smooth and coherent logical flow.

(2) Comment from Reviewer 4 pointing out the purpose in choosing to study ISL1-CMs.

As raised by the reviewer, we have clarified the rationale for using ISL1 as a marker to define RCCs in revised manuscript (lines 39-47 on page 3).

(3) Comment from Reviewer 4 pointing out the missing references in row 57-58.

Thank you for pointing this out, we fixed it.

(4) Comment from Reviewer 4 suggesting more explains and show the results of the screening compounds.

As suggested by the reviewer, we added additional explanations in lines 65-73 and showed the screening results in Figure 1—figure supplement 1F-H.

(5) Comment from Reviewer 4 suggesting an in-depth discussion of the findings.

Thank you for the suggestion, we included additional discussion at the end of the article.

(6) Comment from Reviewer 4 suggesting a conclusion should be inculded in the main text.

Thank you for the suggestion, we made a revision.

(7) Comment from Reviewer 4 pointing out the cell viability under different concentrations of 2C.

As mentioned by the reviewer, have supplemented the cell numbers during different doses of 2C treatment (Figure 2F).

(8) Comment from Reviewer 4 pointing out the missing information in the methods.

Thank you for the suggestion, we made additions.

(9) Comment from Reviewer 4 suggesting more explanations in Figure S3A.

As mentioned by the reviewer, we made a revision in original Fig.S3A (now is Figure 2—figure supplement 1).

(10) Comment from Reviewer 4 pointing out the high variability of mCherry cells (%) in Figure 3J.

Thank you. We made a revision.

(11) Comment from Reviewer 4 suggesting more explanations on the DNA-binding motif of ISL1 in the cells treated with A-485 or 2C.

Thank you for the suggestion, we added additional explanations (lines 270-274 on page 9).

(12) Comment from Reviewer 4 pointing out the unclear labeling in Figure S1B and D.

Thank you for the suggestion, made a revision (lines 240-245 in supporting information).

(13) Comment from Reviewer 4 suggesting a relative quantification of the proteins in Figure 1H.

Thank you for the suggestion. We have quantified the relative expression levels of proteins in original Fig. 1H. As shown in Figure 1F.

(14) Comment from Reviewer 4 suggesting to provide detailed information in the methodology part about the compounds.

Thank you for the suggestion, we made a revision.

(15) Comment from Reviewer 4 pointing out the insufficient explanations on figure legends.

Thank you for the suggestion, we made a revision.

(16) Comment from Reviewer 4 suggesting more independent experiments to reduce the high variations in “ns” between NC and 2C at 60h+3d shown in Figure 2E and F.

Thank you for the suggestion, we made a revision in Figure 2F.

(17) Comment from Reviewer 4 suggesting a limitations should be provided in the text.

Thank you for the suggestion, we have made provide a limitation statement in the revised manuscript (lines 300-311 on page 10).

eLife Assessment

This manuscript offers valuable information on the combinatory effect of small molecules, CHIR99021 and A-485 (2C), during the reprogramming of mature cardiomyocytes into regenerative cardiac cells on stimulating cardiac cell regeneration. Although the study used several hESC lines and an in vivo model of myocardial injury to demonstrate the regenerative potential of cardiac cells, the manuscript is still incomplete as several concerns remain unanswered, including the lack of validation of the conclusions from scRNA-seq. It is still unclear how a small fraction of dedifferentiating cardiac cells can offer such broad effects on regeneration both in vitro and in vivo. If validated, this study might unlock potential therapeutic strategies for cardiac regeneration.

Reviewer #1 (Public review):

The present manuscript by Zhou and colleagues investigates the impact of a new combination of compounds termed CHIR99021 and A-485 on stimulating cardiac cell regeneration. This manuscript fits the journal and addresses an important contribution to scientific knowledge.

Comments on latest version:

The authors have addressed all of our comments.

Reviewer #2 (Public review):

Summary:

This manuscript reports that a combination of two small molecules, 2C (CHIR99027 and A-485) enabled to induce the dedifferentiation of hESC-derived cardiomyocytes (CMs) into regenerative cardiac cells (RCC). These RCCs had disassembled sarcomeric structures and elevated expression of embryonic cardiogenic genes such as ISL1, which exhibited proliferative potential and were able to differentiate into cardiomyocytes, endothelial cells, and smooth muscle cells. Lineage tracing further suggested that RCCs originated from TNNT2+ cells, not pre-existing ISL1+ cells. Furthermore, 2C treatment increased the numbers of RCC cells in neonatal rat and adult mouse hearts, and improves cardiac function post-MI in adult mice. Mechanistically, bulk RNA-seq analysis revealed that 2C led to elevated expression of embryonic cardiogenic genes while down-regulation of CM-specific genes. Single-cell RNA-seq data showed that 2C promoted cardiomyocyte transition into an intermediate state that are marked with ACTA2 and COL1A1, which subsequently transform into RCCs. Finally, ChIP-seq analysis demonstrated that CHIR99027 enhanced H3K9Ac and H3K27Ac modifications in embryonic cardiac genes, while A-485 inhibited these modifications in cardiac-specific genes. These combined alterations effectively induced the dedifferentiation of cardiomyocytes into RCCs. Overall, this is an important work, presenting a putative cardiac regenerative cell types that may represent endogenous cardiac regeneration in regenerative animals. With that said, here are suggestions for the authors:

Strengths:

Overall, this work is quite comprehensive and is logically and rigorously designed. The phenotypic and functional data on 2C are strong.

Weaknesses or suggestions:

(1) In Figure 4, the authors should perform additional experiments on analyzing 2C effect on cardiomyocytes, endothelial cells, and fibroblasts in adult mouse hearts after myocardial infarction.<br /> (2) In Figures 5-7, the mechanistic insights of 2C are primarily derived from transcriptomic and genomic datasets without experimental verification.<br /> (3) The authors should compare transcriptomic profiling of the RCCs with other putative cardiac progenitors from public databases.

Reviewer #3 (Public review):

Summary:

The ability of cardiac cells to regenerate has been the object of intense (and sometimes controversial) research in biology. While lower organisms can robustly undergo cardiac regeneration by reactivation of embryonic cardiogenic pathway, this ability is strongly reduced in mice, both temporally and qualitatively. Finding a way to derive precursor cells with regenerative ability from differentiated cells in mammals has been challenging.

Zhou, He and colleagues hypothesized that ISL-1-positive cells would show regenerative capacity and developed a small molecules screen to dedifferentiate cardiomyocytes (CM) to ISL1-positive precursor cells. Using hESC-derived CM, authors found that the combination of both, WNT activation (CHIR99021) and p300 acetyltransferase inhibition (A-485) (named 2C protocol) induces CM dedifferentiation to regenerative cardiac cells (RCCs). RCCs are proliferative and re-express embryonic cardiogenic genes while decreasing expression of more mature cardiac genes, bringing them towards a more precursor-like state. RCCs were able to differentiate to CM, smooth muscle cells and endothelial cells, highlighting their multipotent property. In vivo administration of 2C in rats and mice had protective effects upon myocardial infarction.

Mechanistically, authors report that 2C protocol drives CM-specific transcriptional and epigenetic changes.

Strengths:

The authors made a great effort to validate their data using orthogonal ways, and several hESC lines. The use of lineage tracing convincingly showed a dedifferentiation from CM. They translate their findings into an in vivo model of myocardial injury, and show functional cardiac regeneration post injury. They also showed that 2C could surprisingly be used as preventive treatment. Together their data may suggest a regenerative effect of 2C both in vitro and in vivo settings. If confirmed, this study might unlock therapeutic strategy for cardiac regeneration.

Weaknesses:

Updated General comments:

Experimental design & Interpretation

(1) The titration provided by the author following the first round of revision is puzzling to me. Based on the authors explanation, the initial screen was performed using 10uM of A-485, allowing the authors to choose CHIR + A-485 as a combination of drugs increasing Isl1-positive cells. However, in the titration provided, the combination of CHIR + 10uM of A-485 (used during the screen) shows *no* increase of the percentage of Isl-1-positive cells compared to DMSO control. How is that possible? Can the authors provide a transparent explanation of the experimental design for their screen. How was A-485 isolated from the 4000+ compounds tested if it does not show any effect on the titration? This titration raises significant concerns about the rational of following up with the combination of compounds.

(2) The authors have not really addressed the concern raised earlier. If only ~1% of the cells de-differentiate and become Isl-positive, how can anybody quantify a nuclear/cytosolic ratio at the global population and show statistical significant when only 1% of the cells should be different?

(3) Authors now provide a quantification of the effect of I-BET-762 (Supp 1H). While the authors state " [the combination of CHIR + I-BET-762] was less effective than A-485 in combination with CHIR99021", the figure provided does not test that. A side-by-side comparaison of the effect of A485 and I-BET should have been performed on the same graph. I-BET increases by 4 fold, while A-485 increases by 5-fold, which, based on the variation of their data, will unlikely be statistically different. The rational for disregarding the effect of I-BET-762 is therefore weakened.

(4) Why NR2F2 is statistically significant in one set of experiments (Fig 2 - Fig. supplement 1) and then non-significant in another set (Fig. 1G) using the exact same experiment design (NC vs 2C for 60h) and similar statistical test applied?

Statistics & Data Acquisition

(1) Authors should refrain from deriving statistics from 2 biological repeats (Figure 3G).<br /> (2) Authors still do not state whether the normality of their data was tested.<br /> (3) What is the rational for using a two-way ANOVA for Fig 3G? Authors are only comparing the effect of their treatment for each marker. Same question for most panels from Figure 1, Fig 2C, 2F, and throughout the manuscript. This needs clarification/justification especially because in other experiments, they used multiple unpaired t-test (Fig 2 - Fig. supplement 1).

Others

(1) Authors should try to make their manuscript colorblind-friendly: No modification added following this comment.

The graph shouldn't have any extra space on the X and Y axis. most obvious being the 18% sugar on x axis because there wasn't a 18% standard.

don't mention the lab packet.

The reader doesn't know what this refers to.

should be separated from the text and labeled as, "equation 1"

Not necessary.

This isn't the definition of m in the equation; it is just mass.

There is no mention of the Erlenmeyer flask used to gather the calibration standard.

They didn't mention calculating density or identifying the metal.

Don't mention recording the mass; this is assumed.

I don't think this is necessary to include.

the graph isn't supposed to include guidlines.

This is supposed to be revenge against Fortunato? Why is the narrator insisting he go back? Did he know it wouldn't change Fortunato's mind? Is he doing this to make his character still seem good?

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?

could have been worded better, like: Then repeat the following procedure with the cranberry juice and root beer.

volume of the metal rod, after calculating it using the graduated cylinder.

Don't mention where you got the calibration standard averages (from the class).

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.

eLife Assessment

This valuable article represents a significant body of work that addresses some novel aspects of the biology of lung cancer, the overall influence of CHIP and its impacts on responses to therapy. While a high clonal hematopoiesis (CHIP) burden was previously linked with an inflammatory phenotype in other disease settings, the authors demonstrate with solid evidence that this is also true for lung cancer. CHIP is complex and more data will be required to substantiate more evidence with regard perhaps to specific mutations in certain situations and how this might influence therapy choices.

Reviewer #1 (Public review):

Summary:

The study investigates the impact of Clonal Hematopoiesis of Indeterminate Potential (CHIP) on Immune Checkpoint Inhibitor (ICI) therapy outcomes in NSCLC patients, analyzing blood samples from 100 patients pre- and post-ICI therapy for CHIP, and conducting single-cell RNA sequencing (scRNA-seq) of PBMCs in 63 samples, with validation in 180 more patients through whole exome sequencing. Findings show no significant CHIP influence on ICI response, but a higher CHIP prevalence in NSCLC compared to controls and a notable CHIP burden in squamous cell carcinoma. Severely affected CHIP groups showed NF-kB pathway gene enrichment in myeloid clusters.

Strengths:

The study is commendable for analyzing a significant cohort of 100 patients for CHIP and utilizing scRNA-seq on 63 samples, showcasing the use of cutting-edge technology.

The study tackles the vital clinical question of predicting ICI therapy outcomes in NSCLC.

Weaknesses:

The study groups, comprising NSCLC patients and healthy controls, exhibit notable differences in sex distribution and smoking status. Given that smoking is a well-established factor influencing CHIP status, this introduces potential confounding variables that may impact the study's conclusions. The authors have appropriately acknowledged these disparities and provided a transparent discussion of their implications.

Comments on revised submission:

The authors thoroughly addressed all my concerns. Thank you very much for your additional work.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The study investigates the impact of Clonal Hematopoiesis of Indeterminate Potential (CHIP) on Immune Checkpoint Inhibitor (ICI) therapy outcomes in NSCLC patients, analyzing blood samples from 100 patients pre- and post-ICI therapy for CHIP, and conducting single-cell RNA sequencing (scRNA-seq) of PBMCs in 63 samples, with validation in 180 more patients through whole exome sequencing. Findings show no significant CHIP influence on ICI response, but a higher CHIP prevalence in NSCLC compared to controls, and a notable CHIP burden in squamous cell carcinoma. Severely affected CHIP groups showed NF-kB pathway gene enrichment in myeloid clusters.

Strengths:

The study is commendable for analyzing a significant cohort of 100 patients for CHIP and utilizing scRNA-seq on 63 samples, showcasing the use of cutting-edge technology. The study tackles the vital clinical question of predicting ICI therapy outcomes in NSCLC.

Weaknesses:

The manuscript's comparison of CHIP prevalence between NSCLC patients and healthy controls could be strengthened by providing more detailed information on the control group. Specifically, details such as sex, smot king status, and comorbidities are needed to ensure the differences in CHIP are attributable to lung cancer rather than other factors. Including these details, along with a comparative analysis of demographics and comorbidities between both groups and clarifying how the control group was selected, would enhance the study's credibility and conclusions.

Reviewer #2 (Public Review):

Summary:

The authors used a large cohort of patients with metastatic lung cancer pre- and 1-3 weeks post-immunotherapy. The goal was to investigate whether immunotherapy results in changes in CHIP clones (using targeted sequencing and whole exome sequencing) as well as to investigate whether patients with CHIP changed their response to immunotherapy (single-cell RNA sequencing).

Strengths:

This represents a large cohort of patients, and comprehensive assays - including targeted sequencing, whole exome sequencing, and single-cell RNA sequencing.

Weaknesses:

Findings are not necessarily unexpected. With regards to clonal dynamics, it would be very unlikely to see any changes within a few weeks' time frame. Longer follow-up to assess clonal dynamics would realistically be necessary.

We truly appreciate constructive comments by the reviewers and editors. We agree with these comments and did our best to address them to improve the paper. Please see the following pages.

Reviewer #1 (Recommendations For The Authors):

Comment 1-1. In Figure 3B, the changes in frequency are challenging to discern. Consider employing connected line plots or another visual representation to enhance clarity and interpretation.

Thank you for the suggestion. We modified Figure 3B to efficiently visualize the changes in cell proportion. Please note that the proportional changes in cell populations were not statistically significant by treatment, pathology, or clonal hematopoiesis (CH) severity.

Comment 1-2. On page 13, Figure 3D is mentioned before Figure 3C. Please re-order to follow the correct sequence.

We corrected the sequence of the figure and revised the text accordingly.

Comment 1-3. Supplementary Figure 9 reveals an intriguing observation: the hypoxia and TNF signaling pathways appear to be regulated in opposite directions between CHIP-negative subjects and those with a Variant Allele Frequency (VAF) greater than 0.1. It would be insightful if the authors could delve into the potential implications or interpretations of this finding.

We appreciate the reviewer's insightful comment. In the GSEA results presented in Supplementary Figure 9 and Figure 3C, we specifically focused on TNF signaling in monocytes and cDCs. Our subsequent analysis revealed that the adaptation of inflammatory signals is enriched in the myeloid cells in the CHIP-severe patients (Supplementary Fig. S12). Following the reviewer’s comment, we found that the leading-edge genes were shared between the TNF signaling and hypoxia pathways in most clusters (Supplementary Fig. S15). Suggested core genes, such as FOS, DUSP1, JUN, and PPP1R15A, play critical roles in the inflammatory phenotypes of myeloid lineages. Based on this finding, we added a paragraph in the Discussion section to address the implications of these shared signatures as follows (lines 340-348):

“Our GSEA results specifically indicated the enrichment of TNF signaling and hypoxia pathways in most clusters of patients with severe CH (Supplementary Fig. S9). The leading-edge genes from GSEA results showed core genes such as FOS, DUSP1, JUN, and PPP1R15A, which are known to play critical roles in the inflammatory phenotypes of immune cells, were shared between the TNF signaling and hypoxia pathways in all significant clusters. (Supplementary Fig. S15). Furthermore, gene regulatory network analysis using SCENIC indicated a higher enrichment of inflammatory signatures in myeloid lineages (Supplementary Fig. S9), highlighting the pronounced inflammatory phenotype of CH clones in these cell lineages.”

Comment 1-4. The plots in Supplementary Figure 12 would benefit from enlargement to improve legibility and facilitate a better understanding of the data presented.

We improved resolutions and enlarged Supplementary Figure S12.

Reviewer #2 (Recommendations For The Authors):

Comment 2-1. The authors state that CHIP is seen at a higher prevalence in the metastatic lung (44/100) vs controls (5/42), however, no in-depth info other than age is given about the normal cohort (Table S2). It would be important to make sure the cohorts are matched with regards to smoking hx, age range, etc before making the claim that CHIP is more frequent in the metastatic lung cancer group.

Thank you for the comment. To provide additional information of control cohort including current smoking habits and their sex information, we added columns in Table S2. While we tried to match the age distributions between the control group without a history of solid cancer and the lung cancer cohort, we observed that the lung cancer cohort had slightly older ages (mean ages: 58.9 vs. 64.1 years), a higher prevalence of smoking (current smokers: 11/42 vs. 37/100), and a higher proportion of males (male/female: 18/24 vs. 91/9).  Age and smoking are well-known epidemiological contributors to lung cancer and could influence the prevalence of clonal hematopoiesis (CH).

However, previous studies have reported similar prevalence rates of CH in NSCLC patients, which aligned with our findings (Bolten et al., 2020 Nat Genet; Hong et al., 2022 Cancer Res). Moreover, our most prevalent CH mutations, including DNMT3A, TET2, and PPM1D, were marginally affected by smoking, and this trend has been consistently observed in healthy populations (Levin et al., 2022 Sci Rep). We have acknowledged these factors as major limitations of our study in the Discussion section as follows (lines 379-390):

“Also, the distinct characteristics of our cohort can be confounders for our results. Compared to control patients, our cohort was biased toward slightly older ages, higher prevalence of smoking habits, and with a higher proportion of males (mean age: 64.1 vs. 58.9; current smokers: 37/100 vs. 11/42; male/female: 91/9 vs. 18/24 Supplementary Figures S1 and S3). However, previous studies have reported similar prevalence rates of clonal hematopoiesis in NSCLC patients, aligned with our findings (9,51). Moreover, our most prevalent CH mutations, including DNMT3A, TET2, and PPM1D, were marginally affected by smoking, and this trend has been consistently observed in both healthy populations and NSCLC patients (10,51,52).”

Comment 2-2. Figure 1 - 1A states there were 100 CHIP and CHIP-PD mutations identified, but in 1B, C, and D there are < 100 bars and/or dots shown. How were the mutations in 1A then triaged to be shown in 1B-D?

It appears that our poor annotation caused this misunderstanding. In Figure 1A, we showed the number of samples in each study group but did not provide detailed information in the legend. We found 67 mutations among the 100 patients and presented the mutational statistics in Figures 1B–D. Accordingly, we have revised the Figure 1 legend to clarify this sentence “The numbers indicate sample counts in each group.” (lines 426-427).

Comment 2-3. Table S4 - would be helpful to have # of variant reads and # of total reads as columns (and also calculate VAF for an additional column).

Thank you for the comment. We added columns revealing the total number of reads and the number of variant reads in Table S4. Also, we calculated the VAF and included it as a new column as suggested by the reviewer.

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.

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

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

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.