La foto de abajo es bastante fea, seguir con el estilo de la portada

Incluir KW aquí. Ejemplo:

¿Quiénes podrán beneficiarse de Innobonos 2024 y qué áreas tecnológicas cubrirá?

Actualizar a 2024: valorar si título, fechas, información

También se puede hacer como la competencia y añadir con bullet point o un emoji o algo "recomendaciones" a seguir. Algo visual. Estaría crema también que se pudiera embeber videos de tiktok o IG

Este anchor no tiene sentido

Durante todo el artículo se pueden añadir capturas de pantalla del perfil de Coco

Ejemplo: https://metricool.com/es/como-crecer-en-tiktok/

Así hacemos promo y a la vez somos un ejemplo como "buena práctica"

Volver a repetir la KW

Competencia:

Cómo crecer en TikTok

Optimizar metas, ampliar título

Author Response

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

eLife assessment

This work provides a valuable contribution and assessment of what it means to replicate a null study finding, and what are the appropriate methods for doing so (apart from a rote p-value assessment). Through a convincing re-analysis of results from the Reproducibility Project: Cancer Biology using frequentist equivalence testing and Bayes factors, the authors demonstrate that even when reducing 'replicability success' to a single criterion, how precisely replication is measured may yield differing results. Less focus is directed to appropriate replication of non-null findings.

Reviewer #1 (Public Review):

Summary:

The goal of Pawel et al. is to provide a more rigorous and quantitative approach for judging whether or not an initial null finding (conventionally with p ≥ 0.05) has been replicated by a second similarly null finding. They discuss important objections to relying on the qualitative significant/non-significant dichotomy to make this judgment. They present two complementary methods (one frequentist and the other Bayesian) which provide a superior quantitative framework for assessing the replicability of null findings.

Strengths:

Clear presentation; illuminating examples drawn from the well-known Reproducibility Project: Cancer Biology data set; R-code that implements suggested analyses. Using both methods as suggested provides a superior procedure for judging the replicability of null findings.

Weaknesses:

The proposed frequentist and the Bayesian methods both rely on binary assessments of an original finding and its replication. I'm not sure if this is a weakness or is inherent to making binary decisions based on continuous data.

For the frequentist method, a null finding is considered replicated if the original and replication 90% confidence intervals for the effects both fall within the equivalence range. According to this approach, a null finding would be considered replicated if p-values of both equivalences tests (original and replication) were, say, 0.049, whereas would not be considered replicated if, for example, the equivalence test of the original study had a p-value of 0.051 and the replication had a p-value of 0.001. Intuitively, the evidence for replication would seem to be stronger in the second instance. The recommended Bayesian approach similarly relies on a dichotomy (e.g., Bayes factor > 1).

Thanks for the suggestions, we now emphasize more strongly in the “Methods for assessing replicability of null results” and “Conclusions” sections that both TOST p-values and Bayes factors are quantitative measures of evidence that do not require dichotomization into “success” or “failure”.

Reviewer #2 (Public Review):

Summary:

The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

Strengths:

The study uses reliable and shareable/open data to demonstrate its findings, sharing as well the code for statistical analysis. The study provides sensitivity analysis for different scenarios of equivalence margin and alfa level, as well as for different scenarios of standard deviations for the prior of Bayes factors and different thresholds to consider. All analysis and code of the work is open and can be replicated. As well, the study demonstrates on a case-by-case basis how the different criteria can diverge, regarding one sample of a field of science: preclinical cancer biology. It also explains clearly what Bayes factors and equivalence tests are.

Weaknesses:

It would be interesting to investigate whether using Bayes factors and equivalence tests in addition to p-values results in a clearer scenario when applied to replication data from other fields. As mentioned by the authors, the Reproducibility Project: Experimental Philosophy (RPEP) and the Reproducibility Project: Psychology (RPP) have data attempting to replicate some original studies with null results. While the RPCB analysis yielded a similar picture when using both criteria, it is worth exploring whether this holds true for RPP and RPEP. Considerations for further research in this direction are suggested. Even if the original null results were excluded in the calculation of an overall replicability rate based on significance, sensitivity analyses considering them could have been conducted. The present authors can demonstrate replication success using the significance criteria in these two projects with initially p < 0.05 studies, both positive and non-positive.

Other comments:

• Introduction: The study demonstrates how inconclusive replications of studies initially with p > 0.05 can be and employs equivalence tests and Bayesian factor approaches to illustrate this concept. Interestingly, the study reveals that achieving a success rate of 11 out of 15, or 73%, as was accomplished with the non-significance criterion from the RPCB (Reproducibility Project: Cancer Biology), requires unrealistic margins of Δ > 2 for equivalence testing.

• Overall picture vs. case-by-case scenario: An interesting finding is that the authors observe that in most cases, there is no substantial evidence for either the absence or the presence of an effect, as evidenced by the equivalence tests. Thus, using both suggested criteria results in a picture similar to the one initially raised by the paper itself. The work done by the authors highlights additional criteria that can be used to further analyze replication success on a case-by-case basis, and I believe that this is where the paper's main contributions lie. Despite not changing the overall picture much, I agree that the p-value criterion by itself does not distinguish between (1) a situation where the original study had low statistical power, resulting in a highly inconclusive non-significant result that does not provide evidence for the absence of an effect and (2) a scenario where the original study was adequately powered, and a non-significant result may indeed provide some evidence for the absence of an effect when analyzed with appropriate methods. Equivalence testing and Bayesian factor approaches are valuable tools in both cases.

Regarding the 0.05 threshold, the choice of the prior distribution for the SMD under the alternative H1 is debatable, and this also applies to the equivalence margin. Sensitivity analyses, as highlighted by the authors, are helpful in these scenarios.

Thank you for the thorough review and constructive feedback. We have added an additional “Appendix C: Null results from the RPP and EPRP” that shows equivalence testing and Bayes factor analyses for the RPP and EPRP null results.

Reviewer #3 (Public Review):

Summary:

The paper points out that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. Also, it can not be considered a "replication success". The main point of the paper is rather obvious. It may be that both studies are underpowered, in which case their non-significance does not prove anything. The absence of evidence is not evidence of absence! On the other hand, statistical significance is a confusing concept for many, so some extra clarification is always welcome.

One might wonder if the problem that the paper addresses is really a big issue. The authors point to the "Reproducibility Project: Cancer Biology" (RPCB, Errington et al., 2021). They criticize Errington et al. because they "explicitly defined null results in both the original and the replication study as a criterion for replication success." This is true in a literal sense, but it is also a little bit uncharitable. Errington et al. assessed replication success of "null results" with respect to 5 criteria, just one of which was statistical (non-)significance.

It is very hard to decide if a replication was "successful" or not. After all, the original significant result could have been a false positive, and the original null-result a false negative. In light of these difficulties, I found the paper of Errington et al. quite balanced and thoughtful. Replication has been called "the cornerstone of science" but it turns out that it's actually very difficult to define "replication success". I find the paper of Pawel, Heyard, Micheloud, and Held to be a useful addition to the discussion.

Strengths:

This is a clearly written paper that is a useful addition to the important discussion of what constitutes a successful replication.

Weaknesses:

To me, it seems rather obvious that non-significance in both the original study and a replication does not ensure that the studies provide evidence for the absence of an effect. I'm not sure how often this mistake is made.

Thanks for the feedback. We do not have systematic data on how often the mistake of confusing absence of evidence with evidence of absence has been made in the replication context, but we do know that it has been made in at least three prominent large-scale replication projects (the RPP, RPEP, RPCB). We therefore believe that there is a need for our article.

Moreover, we agree that the RPCB provided a nuanced assessment of replication success using five different criteria for the original null results. We emphasize this now more in the “Introduction” section. However, we do not consider our article as “a little bit uncharitable” to the RPCB, as we discuss all other criteria used in the RPCB and note that our intent is not to diminish the important contributions of the RPCB, but rather to build on their work and provide constructive recommendations for future researchers. Furthermore, in response to comments made by Reviewer #2, we have added an additional “Appendix B: Null results from the RPP and EPRP” that shows equivalence testing and Bayes factor analyses for null results from two other replication projects, where the same issue arises.

Reviewer #1 (Recommendations For The Authors):

The authors may wish to address the dichotomy issue I raise above, either in the analysis or in the discussion.

Thank you, we now emphasize that Bayes factors and TOST p-values do not need to be dichotomized but can be interpreted as quantitative measures of evidence, both in the “Methods for assessing replicability of null results” and the “Conclusions” sections.

Reviewer #2 (Recommendations For The Authors):

Given that, here follow additional suggestions that the authors should consider in light of the manuscript's word count limit, to avoid confusing the paper's main idea:

2) Referencing: Could you reference the three interesting cases among the 15 RPCB null results (specifically, the three effects from the original paper #48) where the Bayes factor differs qualitatively from the equivalence test?

We now explicitly cite the original and replication study from paper #48.

3) Equivalence testing: As the authors state, only 4 out of the 15 study pairs are able to establish replication success at the 5% level, in the sense that both the original and the replication 90% confidence intervals fall within the equivalence range. Among these 4, two (Paper #48, Exp #2, Effect #5 and Paper #48, Exp #2, Effect #6) were initially positive with very low p-values, one (Paper #48, Exp #2, Effect #4) had an initial p of 0.06 and was very precisely estimated, and the only one in which equivalence testing provides a clearer picture of replication success is Paper #41, Exp #2, Effect #1, which had an initial p-value of 0.54 and a replication p-value of 0.05. In this latter case (or in all these ones), one might question whether the "liberal" equivalence range of Δ = 0.74 is the most appropriate. As the authors state, "The post-hoc specification of equivalence margins is controversial."

We agree that the post hoc choice of equivalence ranges is a controversial issue. The margins define an equivalence region where effect sizes are considered practically negligible, and we agree that in many contexts SMD = 0.74 is a large effect size that is not practically negligible. We therefore present sensitivity analyses for a wide range of margins. However, we do not think that the choice of this margin is more controversial for the mentioned studies with low p-values than for other studies with greater p-values, since the question of whether a margin plausibly encodes practically negligible effect sizes is not related to the observed p-value of a study. Nevertheless, for the new analyses of the RPP and EPRP data in Appendix B, we have added additional sensitivity analyses showing how the individual TOST p-values and Bayes factors vary as a function of the margin and the prior standard deviation. We think that these analyses provide readers with an even more transparent picture regarding the implications of the choice of these parameters than the “project-wise” sensitivity analyses in Appendix A.

4) Bayes factor suggestions: For the Bayes factor approach, it would be interesting to discuss examples where the BF differs slightly. This is likely to occur in scenarios where sample sizes differ significantly between the original study and replication. For example, in Paper #48, Exp #2 and Effect #4, the initial p is 0.06, but the BF is 8.1. In the replication, the BF dramatically drops to < 1/1000, as does the p-value. The initial evidence of 8.1 indicates some evidence for the absence of an effect, but not strong evidence ("strong evidence for H0"), whereas a p-value of 0.06 does not lead to such a conclusion; instead, it favors H1. It would be interesting if the authors discussed other similar cases in the paper. It's worth noting that in Paper #5, Exp #1, Effect #3, the replication p-value is 0.99, while the BF01 is 2.4, almost indicating "moderate" evidence for H0, even though the p-value is inconclusive.

We agree that some of the examples nicely illustrate conceptual differences between p-values and Bayes factors, e.g., how they take into account sample size and effect size. As methodologists, we find these aspects interesting ourselves, but we think that emphasizing them is beyond the scope of the paper and would distract eLife readers from the main messages.

Concerning the conceptual differences between Bayes factors and TOST p-values, we already discuss a case where there are qualitative differences in more detail (original paper #48). We added another discussion of this phenomenon in the Appendix C as it also occurs for the replication of Ranganath and Nosek (2008) that was part of the RPP.

5) p-values, magnitude and precision: It's noteworthy to emphasize, if the authors decide to discuss this, that the p-value is influenced by both the effect's magnitude and its precision, so in Paper #9, Exp #2, Effect #6, BF01 = 4.1 has a higher p-value than a BF01 = 2.3 in its replication. However, there are cases where both p-values and BF agree. For example, in Paper #15, Exp #2, Effect #2, both the original and replication studies have similar sample sizes, and as the p-value decreases from p = 0.95 to p = 0.23, BF01 decreases from 5.1 ("moderate evidence for H0") to 1.3 (region of "Absence of evidence"), moving away from H0 in both cases. This also occurs in Paper #24, Exp #3, Effect #6.

We appreciate the suggestions but, as explained before, think that the message of our paper is better understood without additional discussion of more general differences between p-values and Bayes factors.

6) The grey zone: Given the above topic, it is important to highlight that in the "Absence of evidence grey zone" for the null hypothesis, for example, in Paper #5, Exp #1, Effect #3 with a p = 0.99 and a BF01 = 2.4 in the replication, BF and p-values reach similar conclusions. It's interesting to note, as the authors emphasize, that Dawson et al. (2011), Exp #2, Effect #2 is an interesting example, as the p-value decreases, favoring H1, likely due to the effect's magnitude, even with a small sample size (n = 3 in both original and replications). Bayes factors are very close to one due to the small sample sizes, as discussed by the authors.

We appreciate the constructive comments. We think that the two examples from Dawson et al. (2011) and Goetz et al. (2011) already nicely illustrate absence of evidence and evidence of absence, respectively, and therefore decided not to discuss additional examples in detail, to avoid redundancy.

7) Using meta-analytical results (?): For papers from RPCB, comparing the initial study with the meta-analytical results using Bayes factor and equivalence testing approaches (thus, increasing the sample size of the analysis, but creating dependency of results since the initial study would affect the meta-analytical one) could change the conclusions. This would be interesting to explore in initial studies that are replicated by much larger ones, such as: Paper #9, Exp #2, Effect #6; Goetz et al. (2011), Exp #1, Effect #1; Paper #28, Exp #3, Effect #3; Paper #41, Exp #2, Effect #1; and Paper #47, Exp #1, Effect #5).

Thank you for the suggestion. We considered adding meta-analytic TOST p-values and Bayes factors before, but decided that Figure 3 and the results section are already quite technical, so adding more analyses may confuse more than help. Nevertheless, these meta-analytic approaches are discussed in the “Conclusions” section.

8) Other samples of fields of science: It would be interesting to investigate whether using Bayes factors and equivalence tests in addition to p-values results in a clearer scenario when applied to replication data from other fields. As mentioned by the authors, the Reproducibility Project: Experimental Philosophy (RPEP) and the Reproducibility Project: Psychology (RPP) have data attempting to replicate some original studies with null results. While the RPCB analysis yielded a similar picture when using both criteria, it is worth exploring whether this holds true for RPP and RPEP. Considerations for further research in this direction are suggested. Even if the original null results were excluded in the calculation of an overall replicability rate based on significance, sensitivity analyses considering them could have been conducted. The present authors can demonstrate replication success using the significance criteria in these two projects with initially p < 0.05 studies, both positive and non-positive.

Thank you for the excellent suggestion. We added an Appendix B where the null results from the RPP and EPRP are analyzed with our proposed approaches. The results are also discussed in the “Results” and “Conclusions” sections.

9) Other approaches: I am curious about the potential impact of using an approach based on equivalence testing (as described in https://arxiv.org/abs/2308.09112). It would be valuable if the authors could run such analyses or reference the mentioned work.

Thank you. We were unaware of this preprint. It seems related to the framework proposed by Stahel W. A. (2021) New relevance and significance measures to replace p-values. PLoS ONE 16(6): e0252991. https://doi.org/10.1371/journal.pone.0252991

We now cite both papers in the discussion.

10) Additional evidence: There is another study in which replications of initially p > 0.05 studies with p > 0.05 replications were also considered as replication successes. You can find it here: https://www.medrxiv.org/content/10.1101/2022.05.31.22275810v2. Although it involves a small sample of initially p > 0.05 studies with already large sample sizes, the work is currently under consideration for publication in PLOS ONE, and all data and materials can be accessed through OSF (links provided in the work).

Thank you for sharing this interesting study with us. We feel that it is beyond the scope of the paper to include further analyses as there are already analyses of the RPCB, RPP, and EPRP null results. However, we will keep this study in mind for future analysis, especially since all data are openly available.

11) Additional evidence 02: Ongoing replication projects, such as the Brazilian Reproducibility Initiative (BRI) and The Sports Replication Centre (https://ssreplicationcentre.com/), continue to generate valuable data. BRI is nearing completion of its results, and it promises interesting data for analyzing replication success using p-values, equivalence regions, and Bayes factor approaches.

We now cite these two initiatives as examples of ongoing replication projects in the introduction. Similarly as for your last point, we think that it is beyond the scope of the paper to include further analyses as there are already analyses of the RPCB, RPP, and EPRP null results.

Reviewer #3 (Recommendations For The Authors):

I have no specific recommendations for the authors.

Thank you for the constructive review.

Reviewing Editor (Recommendations For the Authors):

I recognize that it was suggested to the authors by the previous Reviewing Editor to reduce the amount of statistical material to be made more suitable for a non-statistical audience, and so what I am about to say contradicts advice you were given before. But, with this revised version, I actually found it difficult to understand the particulars of the construction of the Bayes Factors and would have appreciated a few more sentences on the underlying models that fed into the calculations. In my opinion, the provided citations (e.g., Dienes Z. 2014. Using Bayes to get the most out of non-significant results) did not provide sufficient background to warrant a lack of more technical presentation here.

Thank you for the feedback. We added a new “Appendix C: Technical details on Bayes factors” that provides technical details on the models, priors, and calculations underlying the Bayes factors.

The meditation led to a significant reduction in anxiety and depression. Both of you have been impacted by anxiety. This result is from just 8 weeks of mindfulness practice.

Both FA and OM are taught by Medito

Painless way to maintain several remotes synced without Premium.

I would pass textual features through a language model encoder in order to represent them as dense vectors (using models such as word2vec, BERT, ...) and concatenate the numerical features to the resulting test embeddings.

We are all so busy nowadays trying to juggle all the stresses of day-to-day life that we often forget to take care of ourselves in the right ways. Sometimes, even the simplest parts of self-care can seem difficult to achieve. But in the long run, it’s crucial that we priorities our own self-care and health essentials.

test

如何确定使用的Stripping line

Triggered, raw data are reconstructed to transform the detector hits into objects such as tracks and clusters

用MC数据来做触发的条件？

Gauss application 的功能： 1. 用于调用由Pythia，POWHEG等提供的不同的MC模拟产生子 2. 用于调控EvtGen和Geant4。EvtGen 用于描述 模拟粒子，而 Geant4 用于模拟传播和 粒子通过检测器并与检测器相互作用。

LHCb中重要的文件类型

microDST的作用

Author response:

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

Reviewer #1 (Public Review):

Summary:

Bendzunas, Byrne et al. explore two highly topical areas of protein kinase regulation in this manuscript. Firstly, the idea that Cys modification could regulate kinase activity. The senior authors have published some standout papers exploring this idea of late, and the current work adds to the picture of how active site Cys might have been favoured in evolution to serve critical regulatory functions. Second, BRSK1/2 are understudied kinases listed as part of the "dark kinome" so any knowledge of their underlying regulation is of critical importance to advancing the field.

Strengths:

In this study, the author pinpoints highly-conserved, but BRSK-specific, Cys residues as key players in kinase regulation. There is a delicate balance between equating what happens in vitro with recombinant proteins relative to what the functional consequence of Cys mutation might be in cells or organisms, but the authors are very clear with the caveats relating to these connections in their descriptions and discussion. Accordingly, by extension, they present a very sound biochemical case for how Cys modification might influence kinase activity in cellular environs.

Weaknesses:

I have very few critiques for this study, and my major points are barely major.

Major points

(1) My sense is that the influence of Cys mutation on dimerization is going to be one of the first queries readers consider as they read the work. It would be, in my opinion, useful to bring forward the dimer section in the manuscript.

We agree that the influence of Cys on BRSK dimerization is a topic of significant interest. Our primary focus was to explore oxidative regulation of the understudied BRSK kinases as they contain a conserved T-loop Cys, and we have previously demonstrated that equivalent residues at this position in related kinases were critical drivers of oxidative modulation of catalytic activity. We have demonstrated here that BRSK1 & 2 are similarly regulated by redox and this is due to oxidative modification of the T+2 Cys, in addition to Cys residues that are conserved amongst related ARKs as well as BRSK-specific Cys. Although we also provide evidence for limited redox-sensitive higher order BRSK species (dimers) in our in vitro analysis, these represent a small population of the total BRSK protein pool (this was validated by SEC-MALs analysis). As such, we do not have strong evidence to suggest that these limited dimers significantly contribute to the pronounced inhibition of BRSK1 & 2 in the presence of oxidizing agents, and instead believe that other biochemical mechanisms likely drive this response. This may result from oxidized Cys altering the conformation of the activation loop. Indeed, the formation of an intramolecular disulfide within the T-loop of BRSK1 & 2, which we detected by MS, is one such regulatory modification. It is noteworthy, that intramolecular disulfide bonds within the T-loop of AKT and MELK have already been shown to induce an inactive state in the kinase, and we posit a similar mechanism for BRSKs.

While we recognize the potential importance of dimerization in this context, our current data from in vitro and cell-based assays do not provide substantial evidence to assert dimerization as a primary regulatory mechanism. Hence, we maintained a more conservative stance in our manuscript, discussing dimerization in later sections where it naturally followed from the initial findings. That being said, we acknowledge the potential significance of dimerization in the regulation of the BRSK T-loop cysteine. We believe this aspect merits further investigation and could indeed be the focus of a follow-up study.

(2) Relatedly, the effect of Cys mutation on the dimerization properties of preparations of recombinant protein is not very clear as it stands. Some SEC traces would be helpful; these could be included in the supplement.

In order to determine whether our recombinant BRSK proteins (and T-loop mutants) existed as monomers or dimers, we performed SDS-PAGE under reducing and non-reducing conditions (Fig 7). This unambiguously revealed that a monomer was the prominent species, with little evidence of dimers under these experimental conditions (even in the presence of oxidizing agents). Although we cannot discount a regulatory role for BRSK dimers in other physiological contexts, we could not produce sufficient evidence to suggest that multimerization played a substantial role in modifying BRSK kinase activity in our assays. We note that our in vitro analysis was performed using truncated forms of the protein, and as such it is entirely possible that regions of the protein that flank the kinase domain may serve additional regulatory functions that may include higher order BRSK conformations. In this regard, although we have not included SEC traces of our recombinant proteins, we have included analytical SEC-MALS of the truncated proteins (Supplementary Figure 6) which we believe to be more informative. We have also now included additional SEC-MALS data for BRSK2 C176A and C183A (Supplementary Figure 6d and e), which supports our findings in Fig 7, demonstrating the presence of limited dimer species under non-reducing conditions.

(3) Is there any knowledge of Cys mutants in disease for BRSK1/2?

We have conducted an extensive search across several databases: COSMIC (Catalogue of Somatic Mutations in Cancer), ProKinO (Protein Kinase Ontology), and TCGA (The Cancer Genome Atlas). These databases are well-regarded for their comprehensive and detailed records of mutations related to cancer and protein kinases. Our analysis using the COSMIC and TCGA databases focused on identifying any reported instances of Cys mutations in BRSK1/2 that are implicated in cancer. Additionally, we utilized the ProKinO database to explore the broader landscape of protein kinase mutations, including any potential disease associations of Cys mutations in BRSK1/2. However, we found no evidence to indicate the presence of Cys mutations in BRSK1/2 that are associated with cancer or disease. This lack of association in the current literature and database records suggests that, as of our latest search, Cys mutations in BRSK1/2 have not been reported as significant contributors to pathogenesis.

(4) In bar charts, I'd recommend plotting data points. Plus, it is crucial to report in the legend what error measure is shown, the number of replicates, and the statistical method used in any tests.

We have added the data points to the bar charts and included statistical methods in figure legends.

(5) In Figure 5b, the GAPDH loading control doesn't look quite right.

The blot has been repeated and updated.

(6) In Figure 7 there is no indication of what mode of detection was used for these gels.

We have updated the figure legend to confirm that the detection method was western blot.

(7) Recombinant proteins - more detail should be included on how they were prepared. Was there a reducing agent present during purification? Where did they elute off SEC... consistent with a monomer of higher order species?

We have added ‘produced in the absence of reducing agents unless stated otherwise’ in the methods section to improve clarity. Although we have not added additional sentences to describe the elution profile of the BRSK proteins by SEC during purification, we believe that the inclusion of analytical SEC-MALS data is sufficient evidence that the proteins are largely monomeric under non-reducing conditions.

Reviewer #2 (Public Review):

Summary:

In this study by Bendzunas et al, the authors show that the formation of intra-molecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys at an unusual CPE motif at the end of the activation segment function as repressive regulatory mechanisms in BSK1 and 2. They observed that mutation of the CPE-Cys only, contrary to the double mutation of the pair, increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide-mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family. Understanding the molecular mechanisms underlying kinase regulation by redox-active Cys residues is fundamental as it appears to be widespread in signaling proteins and provides new opportunities to develop specific covalent compounds for the targeted modulation of protein kinases.

The authors demonstrate that intramolecular cysteine disulfide bonding between conserved cysteines can function as a repressing mechanism as indicated by the effect of DTT and the consequent increase in activity by BSK-1 and -2 (WT). The cause-effect relationship of why mutation of the CPE-Cys only increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells is not clear to me. The explanation given by the authors based on molecular modeling and molecular dynamics simulations is that oxidation of the CPE-Cys (that will favor disulfide bonding) destabilizes a conserved salt bridge network critical for allosteric activation. However, no functional evidence of the impact of the salt-bridge network is provided. If you mutated the two main Cys-pairs (aE-CHRD and A-loop T+2-CPE) you lose the effect of DTT, as the disulfide pairs cannot be formed, hence no repression mechanisms take place, however when looking at individual residues I do not understand why mutating the CPE only results in the opposite effect unless it is independent of its connection with the T+2residue on the A-loop.

Strengths:

This is an important and interesting study providing new knowledge in the protein kinase field with important therapeutic implications for the rationale design and development of next-generation inhibitors.

Weaknesses:

There are several issues with the figures that this reviewer considers should be addressed.

Reviewer #1 (Recommendations for The Authors):

Major points

Page 26 - the discussion could be more concise. There's an element of recapping the results, which should be avoided.

Regarding the conciseness of the discussion section, we have thoroughly revised it to ensure a more succinct presentation, deliberately avoiding the recapitulation of results. The revised discussion now focuses on interpreting the findings and their implications, steering clear of redundancy with the results section.

Figure 1b seems to be mislabeled/annotated. I recommend checking whether the figure legends match more broadly. Figure 1 appears to be incorrectly cited throughout the results.

Thank you for pointing out the discrepancies in the labeling and citation of Figure 1b. We have carefully reviewed and corrected these issues to ensure that all figure labels, legends, and citations accurately reflect the corresponding data and illustrations. We appreciate your attention to detail and the opportunity to improve the clarity and accuracy of our presentation.

Figure 6 - please include a color-coding key in the figure. Further support for these simulations could be provided by supplementary movies or plots of the interaction. Figure 4 colour palette should be adjusted for the spheres in the Richardson diagrams to have greater distinction.

As suggested, we have amended the colour palette in Figure 4 to improve conformity throughout the figure.

Minor points

Figure 2 - it'd be helpful to know what the percentage coverage of peptides is.

We have updated the figure legend to include peptide coverage for both proteins

Some typos - Supp 2 legend "Domians".

Fixed

Figure 6 legend - analyzed by needs a space;

Fixed

Fig 8 legend schematic misspelled.

Fixed

Broadly, if you Google T-loop you get a pot pourri of enzyme answers. Why not just use Activation loop?

The choice of "T-loop" over "Activation loop" in our manuscript was made to maintain consistency with other literature in the field, and in particular our previous paper “Aurora A regulation by reversible cysteine oxidation reveals evolutionarily conserved redox control of Ser/Thr protein kinase activity” where we refer to the activation loop cysteine as T-loop + 2. We acknowledge the varied enzyme contexts in which "T-loop" is used and agree on the importance of clarity. To address this, we made an explicit note in the manuscript that the "T-loop" is also referred to as the "Activation loop", ensuring readers are aware of the interchangeable use of these terms. Additionally, this nomenclature facilitates a more straightforward designation of cysteine residues within the loop (T+2 Cysteine). We believe this approach balances adherence to established conventions with the need for clarity and precision in our descriptions.

Methods - what is LR cloning. Requires some definition. Some manufacturer detail is missing in methods, and referring to prior work is not sufficient to empower readers to replicate.

We agree, and have added the following to the methods section:

“BRSK1 and 2 were sub-cloned into pDest vectors (to encode the expression of N-terminal Flag or HA tagged proteins) using the Gateway LR Clonase II system (Invitrogen) according to the manufacturer’s instructions. pENtR BRSK1/2 clones were obtained in the form of Gateway-compatible donor vectors from Dr Ben Major (Washington University in St. Louis). The Gateway LR Clonase II enzyme mix mediates recombination between the attL sites on the Entry clone and the attR sites on the destination vector. All cloned BRSK1/2 genes were fully sequenced prior to use.”

Page 7 - optimal settings should be reported. How were pTau signals quantified and normalised?

We have added the following to the methods section:

“Two-color Western blot detection method employing infrared fluorescence was used to measure the ratio of Tau phospho serine 262 to total Tau. Total GFP Tau was detected using a mouse anti GFP antibody and visualized at 680 nm using goat anti mouse IRdye 680 while phospho-tau was detected using a Tau phospho serine 262 specific antibody and visualized at 800 nm using goat anti rabbit IRdye 800. Imaging was performed using a Licor Odessey Clx with scan control settings set to 169 μm, medium quality, and 0.0 mm distance. Quantification was performed using Licor image studio on the raw image files. Total Tau to phospho Tau ratio was determined by measuring the ratio of the fluorescence intensities measured at 800 nm (pTau) to those at 680 nm (total tau).”

In the Figure 6g-j legend, the salt bridge is incorrectly annotated as E185-R248 rather than 258.

Fixed

Lines 393-395 provides a repeat statement on BRSKs phosphorylating Tau (from 388-389).

We have removed the repetition and reworded the opening lines of the results section to improve the overall flow of the manuscript.

Supp. Figure 1 is difficult to view - would it be possible to increase the size of the phylogenetic analysis?

We thank the reviewer for this observation. We have rotated (90°) and expanded the figure so that it can be more clearly viewed

Supp. Figure 2 - BRSK1/2 incorrectly spelled.

Fixed

Please check the alignment of labels in Supp. Figure 3e.

Fixed

Reviewer #2 (Recommendations For The Authors):

(1) In Figure 1, current panel b is not mentioned/described in the figure legend and as a consequence, the rest of the panels in the legends do not fit the content of the figure.

Reviewer 1 also noted this error, and we have amended the manuscript accordingly.

What is the rationale for using the HEK293T cells as the main experimental/cellular system? Are there cell lines that express both proteins endogenously so that the authors can recapitulate the results obtained from ectopic overexpression?

The selection of HEK-293T cells was driven by their well-established utility in overexpression studies, which make them ideal for the investigation of protein interactions and redox regulation. This cell line's robust transfection efficiency and well-characterized biology provide a reliable platform for dissecting the molecular mechanisms underlying the redox regulation of proteins. Furthermore, the use of HEK-293T cells aligns with the broader scientific practice, serving as a common ground for comparability with existing literature in the field of BRSK1/2 signaling, protein regulation and interaction studies.

The application of HEK-293T cells as a model system in our study serves as a foundational step towards eventually elucidating the functions of BRSK1/2 in neuronal cells, where these kinases are predominantly expressed and play critical roles. Given the fact that BRSKs are classed as ‘understudied’ kinases, the choice of a HEK-293T co-overexpression system allowed us to analyze the direct effects of BRSK kinase activity (using phosphorylation of Tau as a readout) in a cellular context and in more controlled manner. This approach not only aids in the establishment of a baseline understanding of the redox regulation of BRSK1/2, but also sets the stage for subsequent investigations in more physiologically relevant neuronal models

In current panel d, could the authors recapitulate the same experimental conditions as in current panel c?

Figure 1 panel c shows that both BRSK1 and 2 are reversibly inhibited by oxidizing agents such as H2O2, whilst panels d and e show the concentration dependent activation and inhibition of the BRSKs with increasing concentrations of DTT and H2O2 respectively. The experimental conditions were identical, other than changing amounts of reducing and oxidizing agents, and used the same peptide coupled assays. Data for all experiments were originally collected in ‘real time’ as depicted in Fig 1c (increase in substrate phosphorylation over time). However, to aid interpretation of the data, we elected to present the latter two panels as dose response curves by calculating the change in the rate of enzyme activity (shown as pmol phosphate incorporated into the peptide substrate per min) for each condition. To aid the reader, we now include an additional supplementary figure (new supplementary figure 2) depicting BRSK1 and 2 dependent phosphorylation of the peptide substrate in the presence of different concentrations of DTT and H2O2 in a real time (kinetic) assay. The new data shown is a subset of the unprocessed data that was used to calculate the rates of BRSK activity in Fig 1d & e.

Why did the authors use full-length constructs in these experiments and did not in e.g. Figure 2 where they used KD constructs instead?

In the initial experiments, illustrated in Figure 1, we employed full-length protein constructs to establish a proof of concept, demonstrating the overall behavior and interactions of the proteins in their full-length form. This confirmed that BRSK1 & 2, which both contain a conserved T + 2 Cys residue that is frequently prognostic for redox sensitivity in related kinases, displayed a near-obligate requirement for reducing agents to promote kinase activity.  

Subsequently, in Figure 2, our focus shifted towards delineating the specific regions within the proteins that are critical for redox regulation. By using constructs that encompass only the kinase domain, we aimed to demonstrate that the redox-sensitive regulation of these proteins is predominantly mediated by specific cysteine residues located within the kinase domain itself. This strategic use of the kinase domain of the protein allowed for a more targeted investigation. Furthermore, in our hands these truncated forms of the protein were more stable at higher concentrations, enabling more detailed characterization of the proteins by DSF and SEC-MALS. We predict that the flanking disordered regions of the full-length protein (as predicted by AlphaFold) contribute to this effect.

(2) In Figure 2, Did the authors try to do LC/MS-MS in the same experimental conditions as in Figure 1 (e.g. buffer minus/plus DTT, H2O2, H2O2 + DTT)?

We would like to clarify that the mass spectrometry experiments were conducted exclusively on proteins purified under native (non-reducing) conditions. We did not extend the LC/MS-MS analyses to include proteins treated with various buffer conditions such as minus/plus DTT, H2O2, or H2O2 + DTT as used in the experiments depicted in Figure 1. Given that we could readily detect disulfides in the absence of oxidizing agents, we did not see the benefit of additional treatment conditions as peroxide treatment of protein samples can frequently complicate interpretation of MS data. However, it should be noted that prior to MS analysis, tryptic peptides were subjected to a 50:50 split, with one half alkylated in the presence of DTT (as described in the methods section) to eliminate disulfides and other transiently oxidized Cys forms. Comparative analysis between reduced and non-reduced tryptic peptides improved our confidence when assigning disulfide bonds (which were eliminated in identical peptides in the presence of DTT).

On panel b, why did the authors show alphafold predictions and not empiric structural information (e.g. X-ray, EM,..)?

The AlphaFold models were primarily utilized to map the general locations of redox-sensitive cysteine pairs within the proteins of interest. Although we have access to the crystal structure of mouse BRSK2, they do not fully capture the active conformation seen in the Alphafold model of the human version. The use of AlphaFold models for human proteins in this study aids in consistently tracking residue numbering across the manuscript, offering a useful framework for understanding the spatial arrangement of these critical cysteine pairs in their potentially active-like states. This approach facilitates our analysis and discussion by providing a reference for the structural context of these residues in the human proteins.

What was the rationale for using the KD construct and not the FL as in Figure 1?

The rationale to use the kinase domain was primarily based on the significantly lower confidence in the structural predictions for regions outside the kinase domain (KD). Our experimental focus was to investigate the role of conserved cysteine residues within the kinase domain, which are critical for the protein's function and regulation. This targeted approach allowed us to concentrate our analyses on the most functionally relevant and structurally defined portion of the protein, thereby enhancing the precision and relevance of our findings. As is frequently the case, truncated forms of the protein, consisting only of the kinase domain, are much more stable than their full length counterparts and are therefore more amenable to in vitro biochemical analysis. In our hands this was true for both BRSK1 and 2, and as such much of the data collected here was generated using kinase-domain (KD) constructs. Simulations using the KD structures are therefore much more representative of our original experimental setup.

The BSK1 KD construct appears to be rather inactive and not responsive to DTT treatment. Could the authors comment on the differences observed with the FL construct of Figure 1

It is important to note that BRSK1, in general, exhibits lower intrinsic activity compared to BRSK2. This reduced activity could be attributed to a range of factors, including the need for activation by upstream kinases such as LKB1, as well as potential post-translational modifications (PTMs) that may be absent in the bacterially expressed KD construct. The full-length forms of the protein were purified from Sf21 cells, and as such may have additional modifications that are lacking in the bacterially derived KD counterparts. We also cannot discount additional regulatory roles of the regions that flank the KD, and these may contribute in part to the modest discrepancy observed between constructs.  Despite these differences, it is crucial to emphasize that both the KD and FL constructs of BRSK1 are regulated by DTT, indicating a conserved redox-dependent activation for both of the related BRSK proteins.  

(3) In Figure 4, on panel A wouldn´t the authors expect that mutating on the pairs e.g. C198A in BSK1 would have the same effect as mutating the C191 from the T+2 site? Did they try mutating individual sites of the aE/CHRD pair? The same will apply to BSK2

We appreciate the insightful comment. It's important to clarify that the redox regulation of these proteins is influenced not solely by the formation of disulfide bonds but also by the oxidation state of individual cysteine residues, particularly the T+2 Cys. This nuanced mechanism of regulation allows for a diverse range of functional outcomes based on the specific cysteine involved and its state of oxidation. This aspect forms a key finding of our paper, highlighting the complexity of redox regulation beyond mere disulfide bond formation. For example, AURA kinase activity is regulated by oxidation of a single T+2 Cys (Cys290, equivalent to Cys191 and Cys176 of BRSK1 and 2 respectively), but this regulation can be supplemented through artificial incorporation of a secondary Cys at the DFG+2 position (Byrne et al., 2020). This targeted genetic modification or AURA mirrors equivalent regulatory disulfide-forming Cys pairs that naturally occur in kinases such as AKT and MELK, and which provide an extra layer of regulatory fine tuning (and a possible protective role to prevent deleterious over oxidation) to the T+2 Cys. We surmise that the CPE Cys is also an accessory regulatory element to the T+2 Cys in BRSK1 +2, which is the dominant driver of BRSK redox sensitivity (as judged by the fact that CPE Cys mutants are still potently regulated by redox [Fig 4]), by locking it in an inactive disulfide configuration.

In our preliminary analysis of BRSK1, we observed that mutations of individual sites within the aE/CHRD pair was similarly detrimental to kinase activity as a tandem mutation (see reviewer figure 1). As discussed in the manuscript, we think that these Cys may serve important structural regulatory functions and opted to focus on co-mutations of the aE/CHRD pair for the remainder of our investigation.

Author response image 1.

In vitro kinase assays showing rates of in vitro peptide phosphorylation by WT and Cys-to-Ala (aE/CHRD residues) variants of BRSK1 after activation by LKB1.

In panels C and D, the same experimental conditions should have been measured as in A and B.

Panels A and B were designed to demonstrate the enzymatic activity and the response to DTT treatment to establish the baseline redox regulation of the kinase and a panel of Cys-to-Ala mutant variants. In contrast, panels C and D were specifically focused on rescue experiments with mutants that showed a significant effect under the conditions tested in A and B. These panels were intended to further explore the role of redox regulation in modulating the activity of these mutants, particularly those that retained some level of activity or exhibited a notable response to redox changes.

The rationale for this experimental design was to prioritize the investigation of mutants, such as those at the T+2 and CPE cysteine sites, which provided the most insight into the redox-dependent modulation of kinase activity. Other mutants, which resulted in inactivation, were deprioritized in this context as they offered limited additional information regarding the redox regulation mechanism. This focused approach allowed us to delve deeper into understanding how specific cysteine residues contribute to the redox-sensitive control of kinase function, aligning with the overall objective of elucidating the nuanced roles of redox regulation in kinase activity.

(4) In figure 5: Why did the authors use reduced Glutathione instead of DTT? The authors should have recapitulated the same experimental conditions as in Figure 4 and not focused only on the T+2 or the CPE single mutants but using the double and the aE/CHRD mutants as well, as internal controls and validation of the enzymatic assays using the modified peptide

Regarding the use of reduced glutathione (GSH) instead of DTT in Figure 5, we chose GSH for its well characterized biological relevance as an antioxidant in cellular responses to oxidative stress. Furthermore, while DTT has been widely used in experimental setups, it is also potentially cytotoxic at high concentrations.

Addressing the point on experimental consistency with Figure 4, we appreciate the suggestion and indeed had already conducted such experiments (Previously Supp Fig 3, now changed to current Supp Fig 4). These experiments include analyses of BRSK mutant activity in a HEK-293T model. However, we chose not to focus on inactivating mutants (such as the aE/CHRD mutants which had depleted expression levels possibly as a consequence of compromised structural integrity) or pursue the generation of double mutant CMV plasmids, as these were deemed unlikely to add significant insights into the core narrative of our study. Our focus remained on the mutants that yielded the most informative results regarding the redox regulation mechanisms in the in vitro setting, ensuring a clear and impactful presentation of our findings.

A time course evaluation of the reducing or oxidizing reagents should have been performed. Would we expect that in WT samples, and in the presence of GSH, and also in the case of the CPE mutant, an increment in the levels of Tau phosphorylation as a readout of BSK1-2 activity?

We acknowledge the importance of such analyses in understanding the dynamic nature of redox regulation on kinase activity and have included a time course (Supp Fig 2 e-g). These results confirm a depletion of Tau phosphorylation over time in response to peroxide generated by the enzyme glucose oxidase.

(5) In Figure 6, did the authors look at the functional impact of the residues with which interact the T+2 and the CPE motifs e.g. T174 and the E185-R258 tether?

Our primary focus was on the salt bridges, as this is a key regulatory structural feature that is conserved across many kinases. Regarding the additional interactions mentioned, we have thoroughly evaluated their roles and dynamics through molecular dynamics (MD) simulations but did not find any results of significant relevance to warrant inclusion.

(6) In Figure 7: Did the author look at the oligomerization state of the BSK1-2 multimers under non-reducing conditions? Were they also observed in the case of the FL constructs? What was the stoichiometry?

Our current work indicates that the kinase domain of BRSK1-2 primarily exists in a monomeric state, with some evidence of dimerization or multimer formation under specific conditions. Our SEC-MALS (Supp Fig 6) and SDS-PAGE analysis (Figure 7) clearly demonstrates that monomers are overwhelmingly the dominant species under non-reducing conditions (>90 %). We also conclude that these limited oligomeric species can be removed by inclusion of reducing agents such as DTT (Figure 7), which may suggest a role for a Cys residue(s). Notably, removal of the T+2 Cys was insufficient to prevent multimerization.

We were unable to obtain reliable SEC-MALS data for the full-length forms of the protein, likely due to the presence of disordered regions that flank the kinase domain which results in a highly heterodispersed and unstable preparation (at the concentrations required for SEC-MALS). Although we are therefore unable to comment on the stoichiometry of FL BRSK dimers, we can detect BRSK1 and 2 hetero- and homo-complexes in HEK-293T cells by IP, which supports the existence of limited BRSK1 & 2 dimers (Supp Fig 6a). However, we were unable to detect intermolecular disulfide bonds by MS, although this does not necessarily preclude their existence. The physiological role of BRSK multimerization (if any) and establishing specifically which Cys residues drive this phenomenon is of significant interest to our future investigations.

eLife assessment

This study provides fundamental new knowledge into the role of reversible cysteine oxidation and reduction in protein kinase regulation. The data provide convincing evidence that intra-molecular disulfide bonds serve a repressive regulatory role in the Brain Selective Kinases (BRSK) 1 & 2; part of the as yet understudied 'dark kinome'. The findings will be of broad interest to biochemists, structural biologists, and those interested in the rational design and development of next-generation kinase inhibitors.

Reviewer #1 (Public Review):

Summary:<br /> Bendzunas, Byrne et al. explore two highly topical areas of protein kinase regulation in this manuscript. Firstly, the idea that Cys modification could regulate kinase activity. The senior authors have published some standout papers exploring this idea of late, and the current work adds to the picture of how active site Cys might have been favoured in evolution to serve critical regulatory functions. Second, BRSK1/2 are understudied kinases listed as part of the "dark kinome" so any knowledge of their underlying regulation is of critical importance to advancing the field.

Strengths:<br /> In this study, the author pinpoints highly-conserved, but BRSK-specific, Cys residues as key players in kinase regulation. There is a delicate balance between equating what happens in vitro with recombinant proteins relative to what the functional consequence of Cys mutation might be in cells or organisms, but the authors are very clear with the caveats relating to these connections in their descriptions and discussion. Accordingly, by extension, they present a very sound biochemical case for how Cys modification might influence kinase activity in cellular environs.

Comments on revised version:

The authors have satisfactorily addressed my concerns.

Reviewer #2 (Public Review):

Summary:

In this study by Bendzunas et al, the authors show that the formation of intra-molecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys at an unusual CPE motif at the end of the activation segment function as repressive regulatory mechanisms in BSK1 and 2. They observed that mutation of the CPE-Cys only, contrary to the double mutation of the pair, increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide-mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family. Understanding the molecular mechanisms underlying kinase regulation by redox-active Cys residues is fundamental as it appears to be widespread in signaling proteins and provides new opportunities to develop specific covalent compounds for the targeted modulation of protein kinases.

The authors demonstrate that intramolecular cysteine disulfide bonding between conserved cysteines can function as a repressing mechanism as indicated by the effect of DTT and the consequent increase in activity by BSK-1 and -2 (WT). The cause-effect relationship of why mutation of the CPE-Cys only increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells is not clear to me. The explanation given by the authors based on molecular modeling and molecular dynamics simulations is that oxidation of the CPE-Cys (that will favor disulfide bonding) destabilizes a conserved salt bridge network critical for allosteric activation. However, no functional evidence of the impact of the salt-bridge network is provided. If you mutated the two main Cys-pairs (aE-CHRD and A-loop T+2-CPE) you lose the effect of DTT, as the disulfide pairs cannot be formed, hence no repression mechanisms take place, however when looking at individual residues I do not understand why mutating the CPE only results in the opposite effect unless it is independent of its connection with the T+2residue on the A-loop.

Strengths:

This is an important and interesting study providing new knowledge in the protein kinase field with important therapeutic implications for the rationale design and development of next-generation inhibitors.

Comments on revised version:

I have one remark related to question number 5 (my question was not clear enough). I meant if the authors did look at the functional relevance of the residues implicated in the identified salt-bridge network/tethers. What happens to the proteins functionally when you mutate those residues? (represented on Fig. 8).

Otherwise, the authors have satisfactorily addressed my concerns.

Any correct implementation can be composed with any other (compatible) correct implementation, and it is guaranteed to be correct .

I.e., there is a possible further computation from y to y', as well as from sigma(y) to sigma(y').

I.e., from any TS' computable mapped state y there is a computable mapped state y'.

Any compute in a TS can be performed in an implementing TS TS'.

I.e., any compute in TS maps to compute in TS'.

I.e., any TS compute is translatable to TS'

I.e., any compute in an implementing TS TS' can be performed in TS.

I.e., any compute in TS' maps to compute in TS.

I.e., any TS' compute is translatable to TS.

specification is an implementation of a TS by a TS'.

empty meaning, noop \ self?

I guess any s has such empty transition for it.

Huuh?

?

S3 -> S2 ?

What does * mean?

Author response:

We thank the reviewers for their attention to our study and for their fair and reasonable assessment of the strengths and weaknesses of our work. We believe the reviewers adequately captured both the potential implications of our work as well as its major current limitations. As both reviewers noted, we believe the work presented in this manuscript is an exciting first step in adapting minibinders as antigen sensors for synthetic receptors but many questions remain before these new tools can be widely adopted. We hope that this work will catalyze others to try minibinders as potential antigen sensors when developing novel synthetic receptors, and we hope that future work will more thoroughly test a wide range of linkers to better optimize antigen sensor function across synthetic receptors.

In our future work, we intend to evaluate a greater diversity of minibinders across different relevant therapeutic targets. We are working to test both existing minibinders as well as generate novel minibinders using deep-learning-based de novo protein design methods. We further hope to explore additional linker modifications, especially focusing on modifications that will allow minibinder coupled-synthetic receptors to escape the glycocalyx of engineered cells. We hope to share findings on these topics in either an update to this manuscript or in future manuscripts, depending on the results of our studies in progress.

Finally, reviewers noted a mismatch in the data displayed in Figure 5A and 5C, whereby LCB-CAR-expressing cells induced higher lysis in Figure 5C than in Figure 5A. This is due to figure 5C showing only 24 hours of incubation between effector and target cells, as opposed to the 72 hours of incubation that is quantitated in 5A. These mismatched timepoints were selected because linker-dependent differences in lysis were most readily apparent at 24 hours and were negligible at 72 hours. The full-time course of lysis for this experiment can be seen in Supplemental Figure 2D.

eLife assessment

This study presents a useful investigation to test de novo-designed mini binders against the Spike protein of SARS-CoV-2 within two classes of synthetic receptors (SNIPRs and CARs). The methods and evidence supporting the focused claims are very solid, although the small-scale nature of the investigation (number of modifications, number of minibinders, etc.) makes it difficult to determine how generalizable these results and potential design principles are. This work will be of interest to synthetic biologists and cell engineers as a starting point for systematic, larger-scale analysis and optimization of synthetic receptor designs for cellular therapy and other applications.

Reviewer #1 (Public Review):

Summary:

The authors want to explore how much two known minibinder protein domains against the Spike protein of SARS-CoV-2 can function as a binding domain of 2 sets of synthetic receptors (SNIPR and CAR); the authors also want to know how some modifications of the linkers of these new receptors affect their activation profile.

Major strengths and weaknesses of the methods and results:

- Strengths include: analysis of synthetic receptor function for 2 classes of synthetic receptors, with robust and appropriate assays for both kinds of receptors. The modifications of the linkers are also interesting and the types of modifications that are often used in the field.

- Weaknesses include: none of the data analysis provides statistical interpretation of the results (that I could find). One dataset is confusing: Figures 5A and C, are said to be the same assay with the same constructs, but the results are 30% in A, and 70% in C.

An appraisal of whether the authors achieved their aims, and whether the results support their conclusions:

Given the open-ended nature of the goal (implicit in it being an exploration), it is hard to say if the authors have reached their aims; they have done an exploration for sure; is it big enough an exploration? This reviewer is not sure.

The results are extremely clearly presented, both in the figures and in the text, both for the methods and the results. The claims put forward (with limited exceptions see below) are very solidly supported by the presented data.

A discussion of the likely impact of the work on the field, and the utility of the methods and data to the community:

The work may stimulate others to consider minibinders as potential binding domains for synthetic receptors. The modifications that are presented although not novel, do provide a starting point for larger-scale analysis.

It is not clear how much this is generalizable to other binders (the authors don't make such claims though). The claims are very focused on the tested modifications, and the 2 receptors and minibinder used, a scope that I would define as narrow; the take-home message if one wants to try it with other minibinders or other receptors seems to be: test a few things, and your results may surprise you.

Any additional context you think would help readers interpret or understand the significance of the work:

We are at the infancy stage of synthetic receptors optimization and next-generation derivation; there is a dearth of systematic studies, as most focus is on developing a few ones that work. This work is an interesting attempt to catalyze more research with these new minibinders. Will it be picked up based on this? Not sure.

Reviewer #2 (Public Review):

Summary:

Weinberg et al. show that spike LCB minibinders can be used as the extracellular domain for SynNotch, SNIPR, and CAR. They evaluated their designs against cells expressing the target proteins and live virus.

Strengths:

This is a good fundamental demonstration of alternative use of the minibinder. The results are unsurprising but robust and solid in most cases.

Weaknesses:

The manuscript would benefit from better descriptions of the study's novelty. Given that LCB previously worked in SynNotch, what unexpected finding was uncovered by this study? It is well known that the extracellular domain of CAR is amendable to different types of binding domains (e.g., scFv, nanobody, DARPin, natural ligands). So, it is not surprising that a minibinder also works with CAR. We don't know if the minibinders are more or less likely to be compatible with CAR or SNIPR.

The demonstrations are all done using just 1 minibinder. It is hard to conclude that minibinders, as a unique class of protein binders, are generalizable in different contexts. All it can conclude is that this specific Spike minibinder can be used in synNotch, SNIPR, and CAR. The LCB3 minibinder seems to be much weaker.

The sensing of live viruses is interesting, but the output is very weak. It is difficult to imagine a utility for such a weak response.

Reviewer #3 (Public Review):

Summary:

The authors use in vitro grown cells and mouse xenografts to show that a combination of drugs, Sulfopin and Vorinostat, can impact the growth of cells derived from Diffuse midline gliomas, in particular the ones carrying the H3 K27M-mutations (clinically classified as DMG, H3 K27M-mutant). The authors use gene expression studies, and chromatin profiling to attempt to better understand how these drugs exert an effect on genome regulation. Their main findings are that the drugs reduce cell growth in vitro and in mouse xenografts of patient tumours, that DMG, H3 K27M-mutant tumours are particularly sensitive, identify potential markers of gene expression underlying this sensitivity, and broadly characterize the correlations between chromatin modification changes and gene expression upon treatment, identifying putative pathways that may be affected and underlie the sensitive (and thus how the drugs may affect the tumour cell biology).

Strengths:

It is a neat, mostly to-the-point work without exploring too many options and possibilities. The authors do a good job not overinterpreting data and speculating too much about the mechanisms, which is a very good thing since the causes and consequences of perturbing such broad epigenetic landscapes of chromatin may be very hard to disentangle. Instead, the authors go straight after testing the performance of the drugs, identifying potential markers and characterizing consequences.

Weaknesses:

If anything, the experiments done on Figure 3 could benefit from an additional replicate.

eLife assessment

This is valuable work showing that a combination of drugs can reduce growth of Diffuse midline gliomas (clinically classified as DMG, H3 K27M-mutant) when applied in vitro and in tumor xenografts in mice. It is a significant first step towards understanding how these drugs work, and provides convincing results to encourage future pre-clinical studies. Further rationale on how doses for specific drugs were chosen, directly demonstrating a survival benefit, or implicating the Pin1 pathway components mechanistically, would make the manuscript stronger.

Reviewer #1 (Public Review):

Summary:

This is an interesting study that utilizes a novel epigenome profiling technology (single molecule imaging) in order to demonstrate its utility as a readout of therapeutic response in multiple DIPG cell lines. Two different drugs were evaluated, singly and in combination. Sulfopin, an inhibitor of a component upstream of the MYC pathway, and Vorinostat, an HDAC inhibitor. Both drugs sensitised DIPG cells, but high (>10 micromolar) concentrations were needed to achieve half-maximal effects. The combination seemed to have some efficacy in vivo, but also produced debilitating side-effects that precluded the measurement of any survival benefit.

Strengths:

Interesting use of a novel epigenome profiling technology (single molecule imaging).

Weaknesses:

The use of this novel imaging technology ultimately makes up only a minor part of the study. The rest of the results, i.e. DIPG sensitivity to HDAC and MYC pathway inhibition, have already been demonstrated by others (Grasso Monje 2015; Pajovic Hawkins 2020, among others). The drugs have some interesting opposing effects at the level of the epigenome, demonstrated through CUT&RUN, but this is not unexpected in any way. The drugs evaluated here also didn't have higher efficacy, or efficacy at especially low concentrations, than inhibitors used in previous reports. The combination therapy attempted here also caused severe side effects in mice (dehydration/deterioration), such that an effect on survival could not be determined. I'm not sure this study advances knowledge of targeted therapy approaches in DIPGs, or if it iterates on previous findings to deliver new, or more efficient, mechanistic or therapeutic/pharmaclogic insights. It is a translational report evaluating two drugs singly and in combination, finding that although they sensitise cells in vitro, efficacy in vivo is limited at best, as this particular combination cannot progress to human translation.

Reviewer #2 (Public Review):

Summary:

The study by Algranati et al. introduces an exciting and promising therapeutic approach for the treatment of H3-K27M pediatric gliomas, a particularly aggressive brain cancer predominantly affecting children. By exploring the dual targeting of histone deacetylases (HDACs) and MYC activation, the research presents a novel strategy that significantly reduces cell viability and tumor growth in patient-derived glioma cells and xenograft mouse models. This approach, supported by transcriptomic and epigenomic profiling, unveils the potential of combining Sulfopin and Vorinostat to downregulate oncogenic pathways, including the mTOR signaling pathway. While the study offers valuable insights, it would benefit from additional clarification on several points, such as the rationale behind the dosing decisions for the compounds tested, the specific contributions of MYC amplification and H3K27me3 alterations to the observed therapeutic effects, and the details of the treatment protocols employed in both in-vitro and in-vivo experiments.

Clarification is needed on how doses were selected for the compounds in Figure S2A and throughout the study. Understanding the basis for these choices is crucial for interpreting the results and their potential clinical relevance. IC50s are calculated for specific patient derived lines, but it is not clear how these are used for selecting the dose.

The introduction mentions MYC amplification in high-grade gliomas. It would be beneficial if the authors could delineate whether the models used exhibit varying degrees of MYC amplification and how this factor, alongside differences in H3K27me3, contributes to the observed effects of the treatment.

In Figure 2A, the authors outline an optimal treatment timing for their in vitro models, which appears to be used throughout the figure. It would be helpful to know how this treatment timing was selected and also why Sulfopin is dosed first (and twice) before the vorinostat. Was this optimized?

It should be clarified whether the dosing timeline for the combination drug experiments in Figure 3 aligns with that of Figure 2. This information is also important for interpreting the epigenetic and transcriptional profiling and the timing should be discussed if they are administered sequentially (also shown in Figure 2A).I have the same question for the mouse experiments in Figure 4.

The authors mention that the mice all had severe dehydration and deterioration after 18 days. It would be helpful to know if there were differences in the side effects for different treatment groups? I would expect the combination to be the most severe. This is important in considering the combination treatment.

Minor Points:

(1) For Figure 1F, reorganizing the bars to directly compare the K27M and KO cell lines at each dose would improve readability of this figure.

(2) In Figure 4D, it would be helpful to know how many cells were included (or a minimum included) to calculate the percentages.

Cambiar H2 final, que no sea "Conclusión" en cada artículo sino algo relevante, relacionado con la KW.

Añadir también FAQs para cubrir las preguntas de Google.

Incluir por qué es importante crear un plan de social media en tu empresa (a modo de bullet point o como H).

Todo este H2 me lo cargaba y pasaba directamente a 10 pasos para crear tu plan de social media y presentar la información de forma visible y fácil de entender: bullet points, gráficas, infografías...

Añadir una gráfica o algún elemento visual que explique mejor lo que es. VER https://www.inboundcycle.com/blog-de-inbound-marketing/pasos-plan-de-social-media-plantilla

La competencia va más al grano: ¿Qué vas a aprender con este artículo? Un párrafo introductorio y listo. Ejemplo de la competencia:

En este artículo te explicaré qué es realmente un plan de social media y cómo desarrollarlo de forma fácil con tan solo 10 pasos. Todos ellos son imprescindibles para crear una estrategia completa y sostenible a largo plazo, así que revísalos uno por uno.

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Reviewer #3 (Public Review):

Distant metastasis is the major cause of death in patients with breast cancer. In this manuscript, Liu et al. show that RGS10 deficiency elicits distant metastasis via epithelial-mesenchymal transition in breast cancer. As a prognostic indicator of breast cancer, RGS10 regulates the progress of breast cancer and affects tumor phenotypes such as epithelial-mesenchymal transformation, invasion, and migration. The conclusions of this paper are mostly well supported by data, but some analyses need to be clarified.

(1) Because diverse biomarkers have been identified for EMT, it is recommended to declare the advantages of using RGS10 as an EMT marker.

(2) The authors utilized databases to study the upstream regulatory mechanisms of RSG10. It is recommended to clarify why the authors focused on miRNAs rather than other epigenetic modifications.

(3) The role of miR-539-5p in breast cancer has been described in previous studies. Hence, it is recommended to provide detailed elaboration on how miR-539-5p regulates the expression of RSG10.

(4) To enhance the clarity and interpretability of the Western blot results, it would be advisable to mark the specific kilodalton (kDa) values of the proteins.

eLife assessment

This study presents a valuable finding on the mechanism to promote distant metastasis in breast cancer. The evidence supporting the claims of the authors is convincing. The work will be of interest to medical biologists working on breast cancer.

Reviewer #1 (Public Review):

Strengths

The paper has shown the expression of RGS10 is related to the molecular subtype, distant metastasis, and survival status of breast cancer. The study utilizes bioinformatic analyses, human tissue samples, and in vitro and in vivo experiments which strengthen the data. RGS10 was validated to inhibit EMT through a novel mechanism dependent on LCN2 and miR-539-5p, thereby reducing cancer cell proliferation, colony formation, invasion, and migration. The study elaborated the function of RGS10 in influencing the prognosis and biological behavior which could be considered as a potential drug target in breast cancer.

Weakness<br /> The mechanism by which the miR-539-5p/RGS10/LCN2 axis may be related to the prognosis of cancer patients still needs to be elucidated. In addition, the sample size used is relatively limited. Especially, if further exploration of the related pathways and mechanisms of LCN2 can be carried out by using organoid models, as well as the potential of RGS10 as a biomarker for further clinical translation to verify its therapeutic target effect, which will make the data more convincing.

Reviewer #2 (Public Review):

Liu et al., by focusing on the regulation of G protein-signaling 10 (RGS10), reported that RGS10 expression was significantly lower in patients with breast cancer, compared with normal adjacent tissue. Genetic inhibition of RGS10 caused epithelial-mesenchymal transition, and enhanced cell proliferation, migration, and invasion, respectively. These results suggest an inhibitory role of RGS10 in tumor metastasis. Furthermore, bioinformatic analyses determined signaling cascades for RGS10-mediated breast cancer distant metastasis. More importantly, both in vitro and in vivo studies evidenced that alteration of RGS10 expression by modulating its upstream regulator miR-539-5p affects breast cancer metastasis. Altogether, these findings provide insight into the pathogenesis of breast tumors and hence identify potential therapeutic targets in breast cancer.

The conclusions of this study are mostly well supported by data. However, there is a weakness in the study that needs to be clarified.

In Figure 2A, although some references supported that SKBR3 and MCF-7 possess poorly aggressive and less invasive abilities, examining only RGS10 expression in those cells, it could not be concluded that 'RGS10 acts as a tumor suppressor in breast cancer'. It would be better to introduce a horizontal comparison of the invasive ability of these 3 types of cells using an invasion assay.

Author response:

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

We thank the reviewers for their thorough review of and overall positive comments on our manuscript. We have revised the manuscript to address most of the concerns raised. Below is a point-by-point response to the reviewers’ comments outlining these changes.

The novelty of the study is compromised due to the recently published structure of unliganded PRex1 (Chang et al. 2022). The unliganded and IP4-bound structure of P-Rex1 appear virtually identical, however, no clear comparison is presented in the manuscript. In the same paper, a very similar model of P-Rex1 activation upon binding to PIP3 membranes and Gbeta/gamma is presented.

This comparison has been added as Supplemental Figure 5. Although similar models of activation are presented in our manuscript and in that of Chang et al. 2022, our model is extended to incorporate inhibition by IP4 and other aspects of regulation not previously incorporated, shown in both schematic form (Figure 6B) and including supporting data (Figure 6A). We also point out that in the work by Chang et al. they used domain insertions to stabilize the structure, and here we present the native protein structure. It turns out that they look similar, but our work reduces concerns over possible engineering artifacts. Finally, our model is further informed by HDX-MS measurements of the enzyme bound to PIP3 in liposomes (Figure 6A and Supplemental figure 8), which reveal the regions of the protein subject to higher dynamics and are consistent with a more fully extended conformation.

The authors demonstrate that IP4 binding to P-Rex1 results in catalytic inhibition and increased protection of autoinhibitory interfaces, as judged by HDX. The relevance of this in a cellular setting is not clear and is not experimentally demonstrated. Further, mechanistically, it is not clear whether the biochemical inhibition by IP4 of PIP3 activated P-Rex1 is due to competition of IP4 with activating PIP3 binding to the PH domain of P-Rex1, or due to stabilizing the autoinhibited conformation, or both.

We feel that both occur. IP4 and PIP3 bind to the same site of the PH domain, thus they must be competitive at the very least. We also show that IP4 stabilizes the autoinhibited conformation (based on both our cryo-EM and HDX-MS data). Because PIP3 does not activate either DH/PH or DH/PH-DEP1 (nor does IP4 inhibit, see Sup. Fig. 1), it is not possible for us to tell with this suite of experiments how much the inhibition is due to competition versus stabilization of the autoinhibited conformation.

It is difficult to judge the error in the HDX experiments presented in Sup. data 1 and 2. In the method section, it is stated that the results represent the average from two samples. How is the SD error calculated in Fig.1B-C?

To clarify, the following passages have been revised:

Figure 1 legend – “Graphs show the exchange over time for select regions in the P-Rex1 (B) PH domain and (C) a IP4P region that was disordered in the P-Rex1–Gbg structure. Shown is the average of two experiments with error bars representing the mean ± standard deviation.” Methods section – “Each sample was analyzed twice by HDX-MS, and the data shown in graphs represent the average of these experiments. For each peptide, the average of all five time points was calculated and used to plot the difference data onto the coordinates.”

As mentioned, from the explanations in the manuscript it is difficult to judge the differences between the unliganded and the IP4 bound structure. A superposition, pointing to the main differences, would help. Are there any additional interactions observed that could explain a more stable autoinhibitory conformation?

Added as Supplemental Figure 5. Although there are global shifts in some of the domains, the overall structures are similar to one another. Due to the moderate resolution of both structures (~4.2 Å), accurate placement of sidechains is difficult, in some places more than others. Because of this, we cannot pinpoint many specific sidechain interactions with certainty. There are no obvious interactions observed in our IP4 bound structure compared to that of 7SYF that would explain a more stable autoinhibited conformation, and thus the evidence comes primarily from the HDX-MS data.

The cellular significance of IP4 regulation is not clear. Finding a way to manipulate intracellular IP4 levels and showing that this affects P-Rex1 cellular activity would greatly increase the significance of this finding.

We agree that this would be an informative experiment, but not one that we currently have the means to perform.

From the presented data it is not clear if inhibition by IP4 is due to competition with PIP3 or due to the proposed stabilization of P-Rex1 autoinhibition. Performing a study as shown in Fig.1D, but with the DH/PH construct could resolve this question.

First, please see our response to the similar concern from Reviewer 1 above. It is not possible for us to test the DH/PH construct and assess if there is direct competition with PIP3. To emphasize this point (and to correct the error that we never made a call to Sup. Fig. 1C in the original manuscript), we added the following lines to the first paragraph of the Results.

“Negatively charged liposomes (containing PC/PS), including those that also contain PIP3, unexpectedly inhibit the GEF activity of the DH/PH-DEP1 and DH/PH fragments (Sup. Fig. 1C). Because full-length P-Rex1 is not affected by PC/PS liposomes, it suggests this the observed inhibition represents a non-productive interaction of the DH/PH-DEP1 and DH/PH fragments with negatively charged surfaces in our assay. The lack of activation of DH/PH-DEP1 by PIP3 prevents us from testing whether IP4 can directly inhibit via direct competition with PIP3.”

If I understand correctly, the data shown in Supplementary Data 1 and 2 are averages of 2 measurements, which makes it difficult to judge real signals from outliers. Perhaps, rather than showing the average, the results from the two experiments could be shown. Also, please explain how the SD error is calculated in Fig.1B-C if the data points indeed are averages of 2 measurements.

We are sorry for the confusion. The data shown in Sup. Data 1 and 2 are not averages of two experiments. The Methods section has therefore been modified to read: “Each image in Supplemental Data 1 and 2 shows one experiment (rainbow plots) or a difference analysis from those experiments (red to blue plots). Only one of the two sets of experiments performed for each condition (+/- liposomes or +/- IP4) is shown here.” As described above, text has been added to clarify the SD error calculated in Fig. 1B and 1C.

The authors claim that the data presented in Fig 4B suggests that the salt bridge formed by K207 and E251 is important for autoinhibition. If so, the authors should explain why the K207C mutant is not activated.

Multiple reviewers had problems with this panel, and we now recognize that we misinterpreted the data, which did not help with this. Because this data is largely just supportive of our structure and SAXS data, Figure 4 was moved to the Supplement and this section of the results now reads:

“Flexibility of the hinge in the a6-aN helix of the DH/PH module is important for autoinhibition.

One of our initial goals in this project was to determine a high-resolution structure of the autoinhibited DH/PH-DEP1 core by X-ray crystallography. To this end, we started with the DH/PH-DEP1 A170K variant, which was more inhibited than wild-type but still dynamic, and then introduced S235C/M244C and K207C/E251C double mutants to completely constrain the hinge in the a6-aN helix via disulfide bond formation in a redox sensitive manner. Single cysteine variants K207C and M244C were generated as controls. The S235C/M244C variant performed as expected, decreasing the activity of the A170K variant to nearly background in the oxidized but not the reduced state (Supplemental Fig. 4). However, the M244C single mutant exhibited similar effects, suggesting that it forms disulfide bonds with cysteine(s) other than S235C. Indeed, the side chains of Cys200 and Cys234 are very close to that of M244C. The K207C/E251C mutant was similar to S235C/M244C under oxidized conditions, but ~15-fold more active (similar to WT DH/PH levels, see Fig. 3C) under reducing conditions. The K270C variant, on the other hand, exhibited higher activity than A170K on its own under oxidizing conditions, but similar activity to all the variants except K207C/E251C when reduced. These results suggest that K207C/E251C in a reduced state and K270C in an oxidized state favor a configuration where the DEP1 domain is less able to engage the DH domain and maintain the kinked state. The mechanism for this is not known. Regardless, these data show that perturbation of contacts between the kinked segments of the a6-aN helix can have profound consequences on the activity of the DH/PH-DEP1 core.”

In the low-resolution cryo-EM study, it is mentioned that only a few classes exhibit the extra density that ultimately corresponds to autoinhibited P-Rex1. If so, is this also the case in the high-resolution study and how many of the most populated classes contribute to the autoinhibited structure? It would be informative for the reader to provide this information.

Indeed, only a small subset of the particles are in the autoinhibited conformation in the Krios data set, similar to the Glacios. How many classes these particles partition to is dependent on how many classes are asked for during 2D classification and how many “garbage” particles are present at the different stages of particle stack cleaning during 2D classification. Also, because of the preferred orientation problem, many of the particles in this conformation segregate together during 2D classification. Therefore, in addition to the information show in Sup. Fig. 2, we think a more informative metric to answer the reviewer’s question is the number of particles at the start of data processing compared to at the end, which is shown in Table 1.

Page 10, line 217: "The kink .... is important for autoinhibition". It seems unlikely that there is no kink in the activated state. Perhaps it should say something like "Mobility in the kink is important ..."

Agreed. In fact, the SAXS data we reported on the DH/PH module in Ravala et al. (2020) is most consistent with a DH/PH that exhibits both extended and condensed conformations in solutions.

Fig. 4A: It would help to label helices alpha6 and alphaN.

These helices have now been labeled.

Page 11, lines 223 and 228 are contradictory: In line 223 it is stated that K207C/E251C exhibit reduced GEF activity, while on line 228 it says this has little effect under non-reducing conditions.

We thank the reviewer for this catch. We have modified the text to make it self-consistent.

In Fig.5B, it would help if the authors mention in the legend that a trans-well migration assay was used, in order to know what the increase in stained cells signifies.

The legend has been modified to include this information.

The previous work by Chang et al., 2022 (PMID: 35864164) found that the final DH domain α6 formed the hinge helix (the kink in this manuscript), which undergoes a significant conformational change between closed and opened conformations of P-Rex1. Could the authors discuss the state of the kink in the presence of IP4 and in the P-Rex1 variants A170K and L177E?

We have now included an alignment of our structure in the presence of IP4 with the Chang et al., 2022 structure (Supplemental Figure 5). There is very little difference in the kink region. Because the A170K variant exhibits reduced GEF activity and a smaller Dmax, it could be speculated that the kink might be further stabilized as compared to wild-type. The L177E variant exhibited activity similar to that of DH/PH alone, implying a relief of the kink. This interpretation is supported by our SAXS analysis of A170K and L177E in Fig. 3.

I am a bit confused about the set of experiments with the intended DH-DEP1 interface disruptive mutation A170K, which later turned out to enhance P-Rex1 activity inhibition. The authors explained that the DH K170 salt bridges with DEP1 Glu411 stabilize the DH-DEP1 interaction. Next, the authors used P-Rex1 A170K mutant as the backbone for the introduction of disulfide bonds to block the closed configuration of the DH-PH hinge region by creating some mutants S235C/M244C and K207C/E251C. The first intended C235-C244 disulfide bond did not show any effect on the GEF activity because C235 is so close to the native C234 for a potential disulfide bond. I would recommend putting the data of S235C/M244C into a supplemental figure. Also, I am wondering if the GEF activity measurements in Fig 4B could be performed in the presence or absence of IP4 to see whether the IP4-induced autoinhibition form is distinct from the natural autoinhibitory once the kink was unblocked by reducing agent DTT.

The confusion was warranted by our poor analysis of this data, rectified as discussed above.

With regards to experiments plus/minus IP4, due to the absence of the IP4P domain, IP4 had no inhibitory effect on the activity of DH/PH or DH/PH-DEP1 (Supplemental Figure 1A and 1B) and as such this experiment would not likely be informative (or at best very hard to interpret).

For the IP4 versus PIP3 activity assays, the authors indicated that P-Rex1 inhibition is dependent on the Inositol 3-phosphate. Have the authors tested and could they test with either Ins (1,3,4)P3 or Ins(1,3,5)P3?

In these assays (Figure 1D), we show that inhibition does not occur with Ins(1,4,5)P3. Based on previous structures of IP4 bound to the PH domain and supporting biochemical assays (Cash et al., 2016, Structure), the 3- and 4-phosphates are the most highly coordinated and the next most thermostabilizing headgroup other than IP4 was Ins(1,3,4)P3. Therefore, we would anticipate that Ins(1,3,4)P3 might stabilize the autoinhibited state, perhaps at higher concentrations, but we have not directly tested this.

The authors should provide the electron density maps of the P-REX1-IP4 complex in the supplemental figure and highlight the maps for two key interactions between DEP1 and DH and between PH and IP4P 4-helix bundle subdomain.

The Coulomb potential map of this complex is shown in Figure 2A. Due to the moderate resolution of the reconstruction, side chain details cannot be unambiguously modeled at these interfaces, which is why we do not highlight any observed, specific interactions between sidechains.

The manuscript was written very well and there is only one typing error in the legend of Supplemental Figure 1.

Thank you for this catch.

Details of EM density at significant domain interfaces and at the IP4 binding site should be provided as supplementary material.

Beyond our comment about interfaces above, we have now provided the map representing the bound IP4 as Figure 4B.

Line 123: It is difficult to discern in Figure 2A the "severe bend" in the helix that connects the DH and PH domains. It was not apparent (to me, at least) where this helix is located until eventually encountering Figure 4. It would be helpful to highlight or label (maybe with an asterisk) the bend site in Fig 2A.

This has been labeled in Figure 2A.

Line 125-126: likewise, It would be helpful to the reader to highlight the GTPase binding site in the DH domain.

This has been labeled in Figure 2A.

Line 159. Consider adding a supplementary figure showing a superposition of the two pREX-1 regulatory interfaces in the present structure and in 7SYF.

A superposition of the two structures has now been added as Supplemental Figure 5. Because both structures are of moderate resolution, it is difficult to place side chains with a high degree of certainty. Thus, we did not think it wise to draw conclusions from comparisons between the details of these interfaces.

Is the positioning of IP4 dictated by the EM density, prior knowledge from high-resolution structures, or both? A rendering of the EM density over the stick model as a supplementary figure would be helpful.

This was modeled based on both. This image has now been added as Figure 4B.

It should be emphasized that the jackknife model is similar to the hinge model proposed by Chang et al (2022).

Mention of similarity between our model and the model proposed by Chang et al., 2022 occurs twice in the manuscript.

Reviewer #1 (Public Review):

Summary:

The authors perform a multidisciplinary approach to describe the conformational plasticity of P-Rex1 in various states (autoinhibited, IP4 bound and PIP3 bound). Hydrogen-deuterium exchange (HDX) is used to reveal how IP4 and PIP3 binding affect intramolecular interactions. While IP4 is found to stabilize autoinhibitory interactions, PIP3 does the opposite, leading to deprotection of autoinhibitory sites. Cryo-EM of IP4 bound P-Rex1 reveals a structure in the autoinhibited conformation, very similar to the unliganded structure reported previously (Chang et al. 2022). Mutations at observed autoinhibitory interfaces result in a more open structure (as shown by SAXS), reduced thermal stability and increased GEF activity in biochemical and cellular assays. Together their work portrays a dynamic enzyme that undergoes long-range conformational changes upon activation on PIP3 membranes. The results are technically sound and the conclusions are justified. The main drawback is the limited novelty due to the recently published structure of unliganded P-Rex1, which is virtually identical to the IP4 bound structure presented here. Novel aspects suggest a regulatory role for IP4, but the exact significance and mechanism of this regulation has not been explored.

Strengths:

The authors use a multitude of techniques to describe the dynamic nature and conformational changes of P-Rex1 upon binding to IP4 and PIP3 membranes. The different approaches together fit well with the overall conclusion that IP4 binding negatively regulates P-Rex1, while binding to PIP3 membranes leads to conformational opening and catalytic activation. The experiments are performed very thoroughly and are technically sound. The results are clear and support the conclusions.

Weaknesses:

(1) The novelty of the study is compromised due to the recently published structure of unliganded P-Rex1 (Chang et al. 2022). The unliganded and IP4 bound structure of P-Rex1 appear virtually identical, however, no clear comparison is presented in the manuscript. In the same paper a very similar model of P-Rex1 activation upon binding to PIP3 membranes and Gbeta-gamma is presented.

(2) The authors demonstrate that IP4 binding to P-Rex1 results in catalytic inhibition and increased protection of autoinhibitory interfaces, as judged by HDX. The relevance of this in a cellular setting is not clear and is not experimentally demonstrated. Further, mechanistically, it is not clear whether the biochemical inhibition by IP4 of PIP3 activated P-Rex1 is due to competition of IP4 with activating PIP3 binding to the PH domain of P-Rex1, or due to stabilizing the autoinhibited conformation, or both.

(3) Fig.1B-C: To give a standard deviation from 2 data points has no statistical significance. In this case it would be better to define as range/difference of the 2 data points.

eLife assessment

This important study contributes insights into the regulatory mechanisms of a protein governing cell migration at the membrane. The integration of approaches revealing protein structure and dynamics provides convincing data for a model of regulation and suggests a new allosteric role for a solubilized phospholipid headgroup. The work will be interesting to researchers focusing on signaling mechanisms, cell motility, and cancer metathesis.

Reviewer #2 (Public Review):

Summary:

In this new paper, the authors used biochemical, structural, and biophysical methods to elucidate the mechanisms by which IP4, the PIP3 headgroup, can induce an autoinhibit form of P-Rex1 and propose a model of how PIP3 can trigger long-range conformational changes of P-Rex1 to relieve this autoinhibition. The main findings of this study are that a new P-Rex1 autoinhibition is driven by an IP4-induced binding of the PH domain to the DH domain active site and that this autoinhibit form stabilized by two key interactions between DEP1 and DH and between PH and IP4P 4-helix bundle (4HB) subdomain. Moreover, they found that the binding of phospholipid PIP3 to the PH domain can disrupt these interactions to relieve P-Rex1 autoinhibition.

Strengths:

The study provides good evidence that binding of IP4 to the P-Rex1 PH domain can make the two long-range interactions between the catalytic DH domain and the first DEP domain, and between the PH domain and the C-terminal IP4P 4HB subdomain that generate a novel P-Rex1 autoinhibition mechanism. This valuable finding adds an extra layer of P-Rex1 regulation (perhaps in the cytoplasm) to the synergistic activation by phospholipid PIP3 and the heterotrimeric Gβγ subunits at the plasma membrane. Overall, this manuscript's goal sounds interesting, the experimental data were carried out carefully and reliably.

Weakness:

The set of experiments with the disulfide bond S235C/M244C caused a bit of confusion for interpretation, it should be moved into the supplement, and the text and Figure 4 were altered accordingly.

Reviewer #3 (Public Review):

Summary:

In this report, Ravala et al demonstrate that IP4, the soluble head-group of phosphatiylinositol 3,4,5 - trisphosphate (PIP3), is an inhibitor of pREX-1, a guanine nucleotide exchange factor (GEF) for Rac1 and related small G proteins that regulate cell cell migration. This finding is perhaps unexpected since pREX-1 activity is PIP3-dependent. By way of Cryo-EM (revealing the structure of the p-REX-1/IP4 complex at 4.2Å resolution), hydrogen-deuterium mass spectrometry and small angle X-ray scattering, they deduce a mechanism for IP4 activation, and conduct mutagenic and cell-based signaling assays that support it. The major finding is that IP4 stabilizes two interdomain interfaces that block access of the DH domain, which conveys GEF activity towards small G protein substrates. One of these is the interface between the PH domain that binds to IP4 and a 4-helix bundle extension of the IP4 Phosphatase domain and the DEP1 domain. The two interfaces are connected by a long helix that extends from PH to DEP1. Although the structure of fully activated pREX-1 has not been determined, the authors propose a "jackknife" mechanism, similar to that described earlier by Chang et al (2022) (referenced in the author's manuscript) in which binding of IP3 relieves a kink in a helix that links the PH/DH modules and allows the DH-PH-DEP triad to assume an extended conformation in which the DH domain is accessible. While the structure of the activated pREX-1 has not been determined, cysteine mutagenesis that enforces the proposed kink is consistent with this hypothesis. SAXS and HDX-MS experiments suggest that IP4 acts by stiffening the inhibitory interfaces, rather than by reorganizing them. Indeed, the cryo-EM structure of ligand-free pREX-1 shows that interdomain contacts are largely retained in the absence of IP4.

Strengths:

The manuscript thus describes a novel regulatory role for IP4 and is thus of considerable significance to our understanding of regulatory mechanisms that control cell migration, particularly in immune cell populations. Specifically, they show how the inositol polyphosphate IP4 controls the activity of pREX-1, a guanine nucleotide exchange factor that controls the activity of small G proteins Rac and CDC42 . In their clearly-written discussion, the authors explain how PIP3, the cell membrane and the Gbeta-gamma subunits of heterotrimeric membranes together localize pREX-1 at the membrane and induce activation. The quality of experimental data is high and both in vitro and cell-based assays of site-directed mutants designed to test the author's hypotheses are confirmatory. The results strongly support the conclusions. The combination of cryo-EM data, that describe the static (if heterogeneous) structures with experiments (small angle x-ray scattering and hydrogen-deuterium exchange-mass spectrometry) that report on dynamics are well employed by the authors

Manuscript revision:

The reviewers noted a number of weaknesses, including error analysis of the HDX data, interpretation of the mutagenesis data, the small fraction of the total number of particles used to generate the EM reconstruction, the novelty of the findings in light of the previous report by Cheng et al, 2022, various details regarding presentation of structural results and questions regarding the interpretation of the inhibition data (Figure 1D). The authors have responded adequately to these critiques. It appears that pREX-1 is a highly dynamic molecule, and considerable heterogeneity among particles might be expected.

While, indeed, the conformation of pREX presented in this report is not novel, the finding that this inactive conformational state is stabilized by IP4 is significant and important. The evidence for this is both structural and biochemical, as indicated by micromolar competition of IP4 with PI3-enriched vesicles resulting in the inhibition of pREX-1 GEF activity.

Reviewer #3 (Public Review):

Summary:

Studying evolutionary trajectories provides important insight in genetic architecture of adaptation and provide potential contribution to evaluating the predictability (or unpredictability) in biological processes involving adaptation. While many papers in the field address adaptation to environmental challenges, the number of studies on how genomic contexts, such as large-scale variation, can impact evolutionary outcomes adaptation is relatively low. This research experimentally evolved a genome-reduced strain for ~1000 generations with 9 replicates and dissected their evolutionary changes. Using the fitness assay of OD measurement, the authors claimed there is a general trend of increasing growth rate and decreasing carrying capacity, despite a positive correlation among all replicates. The authors also performed genomic and transcriptomic research at the end of experimental evolution, claiming the dissimilarity in the evolution at the molecular level.

Strengths:

The experimental evolution approach with a high number of replicates provides a good way to reveal the generality/diversity of the evolutionary routes.

The assay of fitness, genome, and transcriptome all together allows a more thorough understanding of the evolutionary scenarios and genetic mechanisms.

Comments on revised version:

5 in the last round of comments: When the authors mentioned no overlapping in single mutation level, I thought the authors would directly use this statement to support their next sentence about no bias of these mutations. As the author's responded, I was suspecting no overlapping for 65 mutation across the entire genome is likely to be not statistically significant. In the revised version, the authors emphasized and specified their simulation and argument in the following sentences, so I do not have questions on this point anymore.

14 in the last round of comments: As what authors responded, "short-term responses" meant transcriptional or physiological changes within a few hours after environmental or genetic fluctuation. "long-term responses" involve new compensatory mutations and selection. The point was that, the authors found that "the transcriptome reorganization for fitness increase triggered by evolution differed from that for fitness decrease caused by genome reduction." That is short vs long-term responses to genetic perturbation. Some other experimental evolution did short vs long-term responses to environmental perturbation and usually also found that the short-term responses are reverted in the long-term responses (e.g., https://academic.oup.com/mbe/article/33/1/25/2579742). I hope this explanation makes more sense. And I think the authors can make their own decisions on whether they would like to add this discussion or not.

Author response:

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

Response to Reviewer #1:

Thank you for the careful reading and the positive evaluation of our manuscript. As you mentioned, the present study tried to address the question of how the lost genomic functions could be compensated by evolutionary adaptation, indicating the potential mechanism of "constructive" rather than "destructive" evolution. Thank you for the instructive comments that helped us to improve the manuscript. We sincerely hope the revised manuscript and the following point-to-point response meet your concerns.

• Line 80 "Growth Fitness" is this growth rate?

Yes. The sentence was revised as follows.

(L87-88) “The results demonstrated that most evolved populations (Evos) showed improved growth rates, in which eight out of nine Evos were highly significant (Fig. 1B, upper).”

• Line 94 a more nuanced understanding of r/K selection theory, allows for trade-ups between R and K, as well as trade-offs. This may explain why you did not see a trade-off between growth and carrying capacity in this study. See this paper https://doi.org/10.1038/s41396-023-01543-5. Overall, your evos lineages evolved higher growth rates and lower carrying capacity (Figures 1B, C, E). If selection was driving the evolution of higher growth rates, it may have been that there was no selective pressure to maintain high carrying capacity. This means that the evolutionary change you observed in carrying capacity may have been neutral "drift" of the carrying capacity trait, during selection for growth rate, not because of a trade-off between R and K. This is especially likely since carrying capacity declined during evolution. Unless the authors have convincing evidence for a tradeoff, I suggest they remove this claim.

• Line 96 the authors introduce a previous result where they use colony size to measure growth rate, this finding needs to be properly introduced and explained so that we can understand the context of the conclusion.

• Line 97 This sentence "the collapse of the trade-off law likely resulted from genome reduction." I am not sure how the authors can draw this conclusion, what is the evidence supporting that the genome size reduction causes the breakdown of the tradeoff between R and K (if there was a tradeoff)?

Thank you for the reference information and the thoughtful comments. The recommended paper was newly cited, and the description of the trade-off collapse was deleted. Accordingly, the corresponding paragraph was rewritten as follows.

(L100-115) “Intriguingly, a positive correlation was observed between the growth fitness and the carrying capacity of the Evos (Fig. 1D). It was somehow consistent with the positive correlations between the colony growth rate and the colony size of a genome-reduced strain 11 and between the growth rates and the saturated population size of an assortment of genome reduced strains 13. Nevertheless, the negative correlation between growth rate and carrying capacity, known as the r/K selection30,31 was often observed as the trade-off relationship between r and K in the evolution and ecology studies 32 33,34. As the r/K trade-off was proposed to balance the cellular metabolism that resulted from the cost of enzymes involved 34, the deleted genes might play a role in maintaining the metabolism balance for the r/K correlation. On the other hand, the experimental evolution (i.e., serial transfer) was strictly performed within the exponential growth phase; thus, the evolutionary selection was supposed to be driven by the growth rate without selective pressure to maintain the carrying capacity. The declined carrying capacity might have been its neutral "drift" but not a trade-off to the growth rate. Independent and parallel experimental evolution of the reduced genomes selecting either r or K is required to clarify the actual mechanisms.”

• Line 103 Genome mutations. The authors claim that there are no mutations in parallel but I see that there is a 1199 base pair deletion in eight of the nine evo strains (Table S3). I would like the author to mention this and I'm actually curious about why the authors don't consider this parallel evolution.

Thank you for your careful reading. According to your comment, we added a brief description of the 1199-bp deletion detected in the Evos as follows.

(L119-122) “The number of mutations largely varied among the nine Evos, from two to 13, and no common mutation was detected in all nine Evos (Table S3). A 1,199-bp deletion of insH was frequently found in the Evos (Table S3, highlighted), which well agreed with its function as a transposable sequence.”

• Line 297 Please describe the media in full here - this is an important detail for the evolution experiment. Very frustrating to go to reference 13 and find another reference, but no details of the method. Looked online for the M63 growth media and the carbon source is not specified. This is critical for working out what selection pressures might have driven the genetic and transcriptional changes that you have measured. For example, the parallel genetic change in 8/9 populations is a deletion of insH and tdcD (according to Table S3). This is acetate kinase, essential for the final step in the overflow metabolism of glucose into acetate. If you have a very low glucose concentration, then it could be that there was selection to avoid fermentation and devote all the pyruvate that results from glycolysis into the TCA cycle (which is more efficient than fermentation in terms of ATP produced per pyruvate).

Sorry for the missing information on the medium composition, which was additionally described in the Materials and Methods. The glucose concentration in M63 was 22 mM, which was supposed to be enough for bacterial growth. Thank you for your intriguing thinking about linking the medium component to the genome mutation-mediated metabolic changes. As there was no experimental result regarding the biological function of gene mutation in the present study, please allow us to address this issue in our future work.

(L334-337) “In brief, the medium contains 62 mM dipotassium hydrogen phosphate, 39 mM potassium dihydrogen phosphate, 15 mM ammonium sulfate, 15 μM thiamine hydrochloride, 1.8 μM Iron (II) sulfate, 0.2 mM magnesium sulfate, and 22 mM glucose.”

• Line 115. I do not understand this argument "They seemed highly related to essentiality, as 11 out of 49 mutated genes were essential (Table S3)." Is this a significant enrichment compared to the expectation, i.e. the number of essential genes in the genome? This enrichment needs to be tested with a Hypergeometric test or something similar.

• Also, "As the essential genes were known to be more conserved than nonessential ones, the high frequency of the mutations fixed in the essential genes suggested the mutation in essentiality for fitness increase was the evolutionary strategy for reduced genome." I do not think that there is enough evidence to support this claim, and it should be removed.

Sorry for the unclear description. Yes, the mutations were significantly enriched in the essential genes (11 out of 45 genes) compared to the essential genes in the whole genome (286 out of 3290 genes). The improper description linking the mutation in essential genes to the fitness increase was removed, and an additional explanation on the ratio of essential genes was newly supplied as follows.

(L139-143) “The ratio of essential genes in the mutated genes was significantly higher than in the total genes (286 out of 3290 genes, Chi-square test p=0.008). As the essential genes were determined according to the growth35 and were known to be more conserved than nonessential ones 36,37, the high frequency of the mutations fixed in the essential genes was highly intriguing and reasonable.”

• Line 124 Regarding the mutation simulations, I do not understand how the observed data were compared to the simulated data, and how conclusions were drawn. Can the authors please explain the motivation for carrying out this analysis, and clearly explain the conclusions?

Random simulation was additionally explained in the Materials and Methods and the conclusion of the random simulation was revised in the Results, as follows.

(L392-401) “The mutation simulation was performed with Python in the following steps. A total of 65 mutations were randomly generated on the reduced genome, and the distances from the mutated genomic locations to the nearest genomic scars caused by genome reduction were calculated. Subsequently, Welch's t-test was performed to evaluate whether the distances calculated from the random mutations were significantly longer or shorter than those calculated from the mutations that occurred in Evos. The random simulation, distance calculation, and statistic test were performed 1,000 times, which resulted in 1,000 p values. Finally, the mean of p values (μp) was calculated, and a 95% reliable region was applied. It was used to evaluate whether the 65 mutations in the Evos were significantly close to the genomic scars, i.e., the locational bias.”

(L148-157) “Random simulation was performed to verify whether there was any bias or hotspot in the genomic location for mutation accumulation due to the genome reduction. A total of 65 mutations were randomly generated on the reduced genome (Fig. 2B), and the genomic distances from the mutations to the nearest genome reduction-mediated scars were calculated. Welch's t-test was performed to evaluate whether the genomic distances calculated from random mutations significantly differed from those from the mutations accumulated in the Evos. As the mean of p values (1,000 times of random simulations) was insignificant (Fig. 2C, μp > 0.05), the mutations fixed on the reduced genome were either closer or farther to the genomic scars, indicating there was no locational bias for mutation accumulation caused by genome reduction.”

• Line 140 The authors should give some background here - explain the idea underlying chromosomal periodicity of the transcriptome, to help the reader understand this analysis.

• Line 142 Here and elsewhere, when referring to a method, do not just give the citation, but also refer to the methods section or relevant supplementary material.

The analytical process (references and methods) was described in the Materials and Methods, and the reason we performed the chromosomal periodicity was added in the Results as follows.

(L165-172) “As the E. coli chromosome was structured, whether the genome reduction caused the changes in its architecture, which led to the differentiated transcriptome reorganization in the Evos, was investigated. The chromosomal periodicity of gene expression was analyzed to determine the structural feature of genome-wide pattern, as previously described 28,38. The analytical results showed that the transcriptomes of all Evos presented a common six-period with statistical significance, equivalent to those of the wild-type and ancestral reduced genomes (Fig. 3A, Table S4).”

• Line 151 "The expression levels of the mutated genes were higher than those of the remaining genes (Figure 3B)"- did this depend on the type of mutation? There were quite a few early stops in genes, were these also more likely to be expressed? And how about the transcriptional regulators, can you see evidence of their downstream impact?

Sorry, we didn't investigate the detailed regulatory mechanisms of 49 mutated genes, which was supposed to be out of the scope of the present study. Fig. 3B was the statistical comparison between 3225 and 49 genes. It didn't mean that all mutated genes expressed higher than the others. The following sentences were added to address your concern.

(L181-185) “As the regulatory mechanisms or the gene functions were supposed to be disturbed by the mutations, the expression levels of individual genes might have been either up- or down-regulated. Nevertheless, the overall expression levels of all mutated genes tended to be increased. One of the reasons was assumed to be the mutation essentiality, which remained to be experimentally verified.”

• Line 199 onward. The authors used WGCNA to analyze the gene expression data of evolved organisms. They identified distinct gene modules in the reduced genome, and through further analysis, they found that specific modules were strongly associated with key biological traits like growth fitness, gene expression changes, and mutation rates. Did the authors expect that there was variation in mutation rate across their populations? Is variation from 3-16 mutations that they observed beyond the expectation for the wt mutation rate? The genetic causes of mutation rate variation are well understood, but I could not see any dinB, mutT,Y, rad, or pol genes among the discovered mutations. I would like the authors to justify the claim that there was mutation rate variation in the evolved populations.

Thank you for the intriguing thinking. We don't think the mutation rates were significantly varied across the nine populations, as no mutation occurred in the MMR genes, as you noticed. Our previous study showed that the spontaneous mutation rate of the reduced genome was higher than that of the wild-type genome (Nishimura et al., 2017, mBio). As nonsynonymous mutations were not detected in all nine Evos, the spontaneous mutation rate couldn't be calculated (because it should be evaluated according to the ratio of nonsynonymous and synonymous single-nucleotide substitutions in molecular evolution). Therefore, discussing the mutation rate in the present study was unavailable. The following sentence was added for a better understanding of the gene modules.

(L242-245) “These modules M2, M10 and M16 might be considered as the hotspots for the genes responsible for growth fitness, transcriptional reorganization, and mutation accumulation of the reduced genome in evolution, respectively.”

• Line 254 I get the idea of all roads leading to Rome, which is very fitting. However, describing the various evolutionary strategies and homeostatic and variable consequence does not sound correct - although I am not sure exactly what is meant here. Looking at Figure 7, I will call strategy I "parallel evolution", that is following the same or similar genetic pathways to adaptation and strategy ii I would call divergent evolution. I am not sure what strategy iii is. I don't want the authors to use the terms parallel and divergent if that's not what they mean. My request here would be that the authors clearly describe these strategies, but then show how their results fit in with the results, and if possible, fit with the naming conventions, of evolutionary biology.

Thank you for your kind consideration and excellent suggestion. It's our pleasure to adopt your idea in tour study. The evolutionary strategies were renamed according to your recommendation. Both the main text and Fig. 7 were revised as follows.

(L285-293) “Common mutations22,44 or identical genetic functions45 were reported in the experimental evolution with different reduced genomes, commonly known as parallel evolution (Fig. 7, i). In addition, as not all mutations contribute to the evolved fitness 22,45, another strategy for varied phenotypes was known as divergent evolution (Fig. 7, ii). The present study accentuated the variety of mutations fixed during evolution. Considering the high essentiality of the mutated genes (Table S3), most or all mutations were assumed to benefit the fitness increase, partially demonstrated previously 20. Nevertheless, the evolved transcriptomes presented a homeostatic architecture, revealing the divergent to convergent evolutionary strategy (Fig. 7, iii).”

Author response image 1.

• Line 327 Growth rates/fitness. I don't think this should be called growth fitness- a rate is being calculated. I would like the authors to explain how the times were chosen - do the three points have to be during the log phase? Can you also explain what you mean by choosing three ri that have the largest mean and minor variance?

Sorry for the confusing term usage. The fitness assay was changed to the growth assay. Choosing three ri that have the largest mean and minor variance was to avoid the occasional large values (blue circle), as shown in the following figure. In addition, the details of the growth analysis can be found at https://doi.org/10.3791/56197 (ref. 59), where the video of experimental manipulation, protocol, and data analysis is deposited. The following sentence was added in accordance.

Author response image 2.

(L369-371) “The growth rate was determined as the average of three consecutive ri, showing the largest mean and minor variance to avoid the unreliable calculation caused by the occasionally occurring values. The details of the experimental and analytical processes can be found at https://doi.org/10.3791/56197.”

• Line 403 Chromosomal periodicity analysis. The windows chosen for smoothing (100kb) seem big. Large windows make sense for some things - for example looking at how transcription relates to DNA replication timing, which is a whole-genome scale trend. However, here the authors are looking for the differences after evolution, which will be local trends dependent on specific genes and transcription factors. 100kb of the genome would carry on the order of one hundred genes and might be too coarse-grained to see differences between evos lineages.

Thank you for the advice. We agree that the present analysis focused on the global trend of gene expression. Varying the sizes may lead to different patterns. Additional analysis was performed according to your comment. The results showed that changes in window size (1, 10, 50, 100, and 200 kb) didn't alter the periodicity of the reduced genome, which agreed with the previous study on a different reduced genome MDS42 of a conserved periodicity (Ying et al., 2013, BMC Genomics). The following sentence was added in the Materials and Methods.

(L460-461) “Note that altering the moving average did not change the max peak.”

• Figures - the figures look great. Figure 7 needs a legend.

Thank you. The following legend was added.

(L774-777) “Three evolutionary strategies are proposed. Pink and blue arrowed lines indicate experimental evolution and genome reduction, respectively. The size of the open cycles represents the genome size. Black and grey indicate the ancestor and evolved genomes, respectively.”

Response to Reviewer #2:

Thank you for reviewing our manuscript and for your fruitful comments. We agree that our study leaned towards elaborating observed findings rather than explaining the detailed biological mechanisms. We focused on the genome-wide biological features rather than the specific biological functions. The underlying mechanisms indeed remained unknown, leaving the questions as you commented. We didn't perform the fitness assay on reconstituted (single and combinatorial) mutants because the research purpose was not to clarify the regulatory or metabolic mechanisms. It's why the RNA-Seq analysis provided the findings on genome-wide patterns and chromosomal view, which were supposed to be biologically valuable. We did understand your comments and complaints that the conclusions were biologically meaningless, as ALE studies that found the specific gene regulation or improved pathway was the preferred story in common, which was not the flow of the present study.

For this reason, our revision may not address all these concerns. Considering your comments, we tried our best to revise the manuscript. The changes made were highlighted. We sincerely hope the revision and the following point-to-point response are acceptable.

Major remarks:

(1) The authors outlined the significance of ALE in genome-reduced organisms and important findings from published literature throughout the Introduction section. The description in L65-69, which I believe pertains to the motivation of this study, seems vague and insufficient to convey the novelty or necessity of this study i.e. it is difficult to grasp what aspects of genome-reduced biology that this manuscript intends to focus/find/address.

Sorry for the unclear writing. The sentences were rewritten for clarity as follows.

(L64-70) “Although the reduced growth rate caused by genome reduction could be recovered by experimental evolution, it remains unclear whether such an evolutionary improvement in growth fitness was a general feature of the reduced genome and how the genome-wide changes occurred to match the growth fitness increase. In the present study, we performed the experimental evolution with a reduced genome in multiple lineages and analyzed the evolutionary changes of the genome and transcriptome.”

(2) What is the rationale behind the lineage selection described in Figure S1 legend "Only one of the four overnight cultures in the exponential growth phase (OD600 = 0.01~0.1) was chosen for the following serial transfer, highlighted in red."?

The four wells (cultures of different initial cell concentrations) were measured every day, and only the well that showed OD600=0.01~0.1 (red) was transferred with four different dilution rates (e.g., 10, 100, 1000, and 10000 dilution rates). It resulted in four wells of different initial cell concentrations. Multiple dilutions promised that at least one of the wells would show the OD600 within the range of 0.01 to 0.1 after the overnight culture. They were then used for the next serial transfer. Fig. S1 provides the details of the experimental records. The experimental evolution was strictly controlled within the exponential phase, quite different from the commonly conducted ALE that transferred a single culture in a fixed dilution rate. Serial transfer with multiple dilution rates was previously applied in our evolution experiments and well described in Nishimura et al., 2017, mBio; Lu et al., 2022, Comm Biol; Kurokawa et al., 2022, Front Microbiol, etc. The following sentence was added in the Materials and Methods.

(L344-345) “Multiple dilutions changing in order promised at least one of the wells within the exponential growth phase after the overnight culture.”

(3) The measured growth rate of the end-point 'F2 lineage' shown in Figure S2 seemed comparable to the rest of the lineages (A1 to H2), but the growth rate of 'F2' illustrated in Figure 1B indicates otherwise (L83-84). What is the reason for the incongruence between the two datasets?

Sorry for the unclear description. The growth rates shown in Fig. S2 were obtained during the evolution experiment using the daily transfer's initial and final OD600 values. The growth rates shown in Fig. 1B were obtained from the final population (Evos) growth assay and calculated from the growth curves (biological replication, N=4). Fig. 1B shows the precisely evaluated growth rates, and Fig. S2 shows the evolutionary changes in growth rates. Accordingly, the following sentence was added to the Results.

(L84-87) “As the growth increases were calculated according to the initial and final records, the exponential growth rates of the ancestor and evolved populations were obtained according to the growth curves for a precise evaluation of the evolutionary changes in growth.”

(4) Are the differences in growth rate statistically significant in Figure 1B?

Eight out of nine Evos were significant, except F2. The sentences were rewritten and associated with the revised Fig. 1B, indicating significance.

(L87-90) “The results demonstrated that most evolved populations (Evos) showed improved growth rates, in which eight out of nine Evos were highly significant (Fig. 1B, upper). However, the magnitudes of growth improvement were considerably varied, and the evolutionary dynamics of the nine lineages were somehow divergent (Fig. S2).”

(5) The evolved lineages showed a decrease in their maximal optical densities (OD600) compared to the ancestral strain (L85-86). ALE could accompany changes in cell size and morphologies, (doi: 10.1038/s41586-023-06288-x; 10.1128/AEM.01120-17), which may render OD600 relatively inaccurate for cell density comparison. I suggest using CFU/mL metrics for the sake of a fair comparison between Anc and Evo.

The methods evaluating the carrying capacity (i.e., cell density, population size, etc.) do not change the results. Even using CFU is unfair for the living cells that can not form colonies and unfair if the cell size changes. Optical density (OD600) provides us with the temporal changes of cell growth in a 15-minute interval, which results in an exact evaluation of the growth rate in the exponential phase. CFU is poor at recording the temporal changes of population changes, which tend to result in an inappropriate growth rate. Taken together, we believe that our method was reasonable and reliable. We hope you can accept the different way of study.

(6) Please provide evidence in support of the statement in L115-119. i.e. statistical analysis supporting that the observed ratio of essential genes in the mutant pool is not random.

The statistic test was performed, and the following sentence was added.

(L139-141) “The ratio of essential genes in the mutated genes was significantly higher than in the total genes (286 out of 3290 genes, Chi-square test p=0.008).”

(7) The assumption that "mutation abundance would correlate to fitness improvement" described in L120-122: "The large variety in genome mutations and no correlation of mutation abundance to fitness improvement strongly suggested that no mutations were specifically responsible or crucially essential for recovering the growth rate of the reduced genome" is not easy to digest, in the sense that (i) the effect of multiple beneficial mutations are not necessarily summative, but are riddled with various epistatic interactions (doi: 10.1016/j.mec.2023.e00227); (ii) neutral hitchhikers are of common presence (you could easily find reference on this one); (iii) hypermutators that accumulate greater number of mutations in a given time are not always the eventual winners in competition games (doi: 10.1126/science.1056421). In this sense, the notion that "mutation abundance correlates to fitness improvement" in L120-122 seems flawed (for your perusal, doi: 10.1186/gb-2009-10-10-r118).

Sorry for the improper description and confusing writing, and thank you for the fruitful knowledge on molecular evolution. The sentence was deleted, and the following one was added.

(L145-146) “Nevertheless, it was unclear whether and how these mutations were explicitly responsible for recovering the growth rate of the reduced genome.”

(8) Could it be possible that the large variation in genome mutations in independent lineages results from a highly rugged fitness landscape characterized by multiple fitness optima (doi: 10.1073/pnas.1507916112)? If this is the case, I disagree with the notion in L121-122 "that no mutations were specifically responsible or crucially essential" It does seem to me that, for example, the mutations in evo A2 are specifically responsible and essential for the fitness improvement of evo A2 in the evolutionary condition (M63 medium). Fitness assessment of individual (or combinatorial) mutants reconstituted in the Ancestral background would be a bonus.

Thank you for the intriguing thinking. The sentence was deleted. Please allow us to adapt your comment to the manuscript as follows.

(L143-145) “The large variety of genome mutations fixed in the independent lineages might result from a highly rugged fitness landscape 38.”

(9) L121-122: "...no mutations were specifically responsible or crucially essential for recovering the growth rate of the reduced genome". Strictly speaking, the authors should provide a reference case of wild-type E. coli ALE in order to reach definitive conclusions that the observed mutation events are exclusive to the genome-reduced strain. It is strongly recommended that the authors perform comparative analysis with an ALEed non-genome-reduced control for a more definitive characterization of the evolutionary biology in a genome-reduced organism, as it was done for "JCVI-syn3.0B vs non-minimal M. mycoides" (doi: 10.1038/s41586-023-06288-x) and "E. coli eMS57 vs MG1655" (doi: 10.1038/s41467-019-08888-6).

The improper description was deleted in response to comments 7 and 8. The mentioned references were cited in the manuscript (refs 21 and 23). Thank you for the experimental advice. We are sorry that the comparison of wild-type and reduced genomes was not in the scope of the present study and will probably be reported soon in our future work.

(10) L146-148: "The homeostatic periodicity was consistent with our previous findings that the chromosomal periodicity of the transcriptome was independent of genomic or environmental variation" A Previous study also suggested that the amplitudes of the periodic transcriptomes were significantly correlated with the growth rates (doi: 10.1093/dnares/dsaa018). Growth rates of 8/9 Evos were higher compared to Anc, while that of Evo F2 remained similar. Please comment on the changes in amplitudes of the periodic transcriptomes between Anc and each Evo.

Thank you for the suggestion. The correlation between the growth rates and the amplitudes of chromosomal periodicity was statistically insignificant (p>0.05). It might be a result of the limited data points. Compared with the only nine data points in the present study, the previous study analyzed hundreds of transcriptomes associated with the corresponding growth rates, which are suitable for statistical evaluation. In addition, the changes in growth rates were more significant in the previous study than in the present study, which might influence the significance. It's why we did not discuss the periodic amplitude.

(11) Please elaborate on L159-161: "It strongly suggested the essentiality mutation for homeostatic transcriptome architecture happened in the reduced genome.".

Sorry for the improper description. The sentence was rewritten as follows.

(L191-193) “The essentiality of the mutations might have participated in maintaining the homeostatic transcriptome architecture of the reduced genome.”

(12) Is FPKM a valid metric for between-sample comparison? The growing consensus in the community adopts Transcripts Per Kilobase Million (TPM) for comparing gene expression levels between different samples (Figure 3B; L372-379).

Sorry for the unclear description. The FPKM indicated here was globally normalized, statistically equivalent to TPM. The following sentence was added to the Materials and Methods.

(L421-422) “The resulting normalized FPKM values were statistically equivalent to TPM.”

(13) Please provide % mapped frequency of mutations in Table S3.

They were all 100%. The partially fixed mutations were excluded in the present study. The following sentence was added to the caption of Table S3.

(Supplementary file, p 9) “Note that the entire population held the mutations, i.e., 100% frequency in DNA sequencing.”

(14) To my knowledge, M63 medium contains glucose and glycerol as carbon sources. The manuscript would benefit from discussing the elements that impose selection pressure in the M63 culture condition.

Sorry for the missing information on M63, which contains 22 mM glucose as the only carbon source. The medium composition was added in the Materials and Methods, as follows.

(L334-337) “In brief, the medium contains 62 mM dipotassium hydrogen phosphate, 39 mM potassium dihydrogen phosphate, 15 mM ammonium sulfate, 15 μM thiamine hydrochloride, 1.8 μM Iron (II) sulfate, 0.2 mM magnesium sulfate, and 22 mM glucose.”

(15) The RNA-Seq datasets for Evo strains seemed equally heterogenous, just as their mutation profiles. However, the missing element in their analysis is the directionality of gene expression changes. I wonder what sort of biological significance can be derived from grouping expression changes based solely on DEGs, without considering the magnitude and the direction (up- and down-regulation) of changes? RNA-seq analysis in its current form seems superficial to derive biologically meaningful interpretations.

We agree that most studies often discuss the direction of transcriptional changes. The present study aimed to capture a global view of the magnitude of transcriptome reorganization. Thus, the analyses focused on the overall features, such as the abundance of DEGs, instead of the details of the changes, e.g., the up- and down-regulation of DEGs. The biological meaning of the DEGs' overview was how significantly the genome-wide gene expression fluctuated, which might be short of an in-depth view of individual gene expression. The following sentence was added to indicate the limitation of the present analysis.

(L199-202) “Instead of an in-depth survey on the directional changes of the DEGs, the abundance and functional enrichment of DEGs were investigated to achieve an overview of how significant the genome-wide fluctuation in gene expression, which ignored the details of individual genes.”

Minor remarks

(1) L41: brackets italicized "(E. coli)".

It was fixed as follows.

(L40) “… Escherichia coli (E. coli) cells …”

(2) Figure S1. It is suggested that the x-axis of ALE monitor be set to 'generations' or 'cumulative generations', rather than 'days'.

Thank you for the suggestion. Fig. S1 describes the experimental procedure, so the" day" was used. Fig. S2 presents the evolutionary process, so the "generation" was used, as you recommended here.

(3) I found it difficult to digest through L61-64. Although it is not within the job scope of reviewers to comment on the language style, I must point out that the manuscript would benefit from professional language editing services.

Sorry for the unclear writing. The sentences were revised as follows.

(L60-64) “Previous studies have identified conserved features in transcriptome reorganization, despite significant disruption to gene expression patterns resulting from either genome reduction or experimental evolution 27-29. The findings indicated that experimental evolution might reinstate growth rates that have been disrupted by genome reduction to maintain homeostasis in growing cells.”

(4) Duplicate references (No. 21, 42).

Sorry for the mistake. It was fixed (leaving ref. 21).

(5) Inconsistency in L105-106: "from two to 13".

"From two to 13" was adopted from the language editing. It was changed as follows.

(L119) “… from 2 to 13, …”

Response to Reviewer #3:

Thank you for reviewing our manuscript and for the helpful comments, which improved the strength of the manuscript. The recommended statistical analyses essentially supported the statement in the manuscript were performed, and those supposed to be the new results in the scope of further studies remained unconducted. The changes made in the revision were highlighted. We sincerely hope the revised manuscript and the following point-to-point response meet your concerns. You will find all your suggested statistic tests in our future work that report an extensive study on the experimental evolution of an assortment of reduced genomes.

(1) Line 106 - "As 36 out of 45 SNPs were nonsynonymous, the mutated genes might benefit the fitness increase." This argument can be strengthened. For example, the null expectation of nonsynonymous SNPs should be discussed. Is the number of observed nonsynonymous SNPs significantly higher than the expected one?

(2) Line 107 - "In addition, the abundance of mutations was unlikely to be related to the magnitude of fitness increase." Instead of just listing examples, a regression analysis can be added.

Yes, it's significant. Random mutations lead to ~33% of nonsynonymous SNP in a rough estimation. Additionally, the regression is unreliable because there's no statistical significance between the number of mutations and the magnitude of fitness increase. Accordingly, the corresponding sentences were revised with additional statistical tests.

(L123-129) “As 36 out of 45 SNPs were nonsynonymous, which was highly significant compared to random mutations (p < 0.01), the mutated genes might benefit fitness increase. In addition, the abundance of mutations was unlikely to be related to the magnitude of fitness increase. There was no significant correlation between the number of mutations and the growth rate in a statistical view (p > 0.1). Even from an individual close-up viewpoint, the abundance of mutations poorly explained the fitness increase.”

(3) Line 114 - "They seemed highly related to essentiality, as 11 out of 49 mutated genes were essential (Table S3)." Here, the information mentioned in line 153 ("the ratio of essential to all genes (302 out of 3,290) in the reduced genome.") can be used. Then a statistical test for a contingency table can be used.

(4) Line 117 - "the high frequency of the mutations fixed in the essential genes suggested the mutation in essentiality for fitness increase was the evolutionary strategy for reduced genome." What is the expected number of fixed mutations in essential genes vs non-essential genes? Is the observed number statistically significantly higher?

Sorry for the improper and insufficient information on the essential genes. Yes, it's significant. The statistical test was additionally performed. The corresponding part was revised as follows.

(L134-146) “They seemed highly related to essentiality7 (https://shigen.nig.ac.jp/ecoli/pec/genes.jsp), as 11 out of 49 mutated genes were essential (Table S3). Although the essentiality of genes might differ between the wild-type and reduced genomes, the experimentally determined 302 essential genes in the wild-type E. coli strain were used for the analysis, of which 286 were annotated in the reduced genome. The ratio of essential genes in the mutated genes was significantly higher than in the total genes (286 out of 3290 genes, Chi-square test p=0.008). As the essential genes were determined according to the growth35 and were known to be more conserved than nonessential ones 36,37, the high frequency of the mutations fixed in the essential genes was highly intriguing and reasonable. The large variety of genome mutations fixed in the independent lineages might result from a highly rugged fitness landscape 38. Nevertheless, it was unclear whether and how these mutations were explicitly responsible for recovering the growth rate of the reduced genome.”

(5) The authors mentioned no overlapping in the single mutation level. Is that statistically significant? The authors can bring up what the no-overlap probability is given that there are in total x number of fixed mutations observed (either theory or simulation is good).

Sorry, we feel confused about this comment. It's unclear to us why it needs to be statistically simulated. Firstly, the mutations were experimentally observed. The result that no overlapped mutated genes were detected was an Experimental Fact but not a Computational Prediction. We feel sorry that you may over-interpret our finding as an evolutionary rule, which always requires testing its reliability statistically. We didn't conclude that the evolution had no overlapped mutations. Secondly, considering 65 times random mutations happened to a ~3.9 Mb sequence, the statistical test was meaningful only if the experimental results found the overlapped mutations. It is interesting how often the random mutations cause the overlapped mutations in parallel evolutionary lineages while increasing the evolutionary lineages, which seems to be out of the scope of the present study. We are happy to include the analysis in our ongoing study on the experimental evolution of reduced genomes.

(6) The authors mentioned no overlapping in the single mutation level. How about at the genetic level? Some fixed mutations occur in the same coding gene. Is there any gene with a significantly enriched number of mutations?

No mutations were fixed in the same gene of biological function, as shown in Table S3. If we say the coding region, the only exception is the IS sequences, well known as the transposable sequences without genetic function. The following description was added.

(L119-122) “The number of mutations largely varied among the nine Evos, from 2 to 13, and no common mutation was detected in all nine Evos (Table S3). A 1,199-bp deletion of insH was frequently found in the Evos (Table S3, highlighted), which well agreed with its function as a transposable sequence.”

(7) Line 151-156- It seems like the authors argue that the expression level differences can be just explained by the percentage of essential genes that get fixed mutations. One further step for the argument could be to compare the expression level of essential genes with vs without fixed mutations. Also, the authors can compare the expression level of non-essential genes with vs without fixed mutations. And the authors can report whether the differences in expression level became insignificant after the control of the essentiality.

It's our pleasure that the essentiality intrigued you. Thank you for the analytical suggestion, which is exciting and valuable for our studies. As only 11 essential genes were detected here and "Mutation in essentiality" was an indication but not the conclusion of the present study, we would like to apply the recommended analysis to the datasets of our ongoing study to demonstrate this statement. Thank you again for your fruitful analytical advice.

(8) Line 169- "The number of DEGs partially overlapped among the Evos declined significantly along with the increased lineages of Evos (Figure 4B). " There is a lack of statistical significance here while the word "significantly" is used. One statistical test that can be done is to use re-sampling/simulation to generate a null expectation of the overlapping numbers given the DEGs for each Evo line and the total number of genes in the genome. The observed number can then be compared to the distribution of the simulated numbers.

Sorry for the inappropriate usage of the term. Whether it's statistically significant didn't matter here. The word "significant" was deleted as follows.

(L205--206) “The number of DEGs partially overlapped among the Evos declined along with the increased lineages of Evos (Fig. 4B).”

(9) Line 177-179- "In comparison,1,226 DEGs were induced by genome reduction. The common DEGs 177 of genome reduction and evolution varied from 168 to 540, fewer than half of the DEGs 178 responsible for genome reduction in all Evos" Is the overlapping number significantly lower than the expectation? The hypergeometric test can be used for testing the overlap between two gene sets.

There's no expectation for how many DEGs were reasonable. Not all numbers experimentally obtained are required to be statistically meaningful, which is commonly essential in computational and data science.

(10) The authors should give more information about the ancestral line used at the beginning of experimental evolution. I guess it is one of the KHK collection lines, but I can not find more details. There are many genome-reduced lines. Why is this certain one picked?

Sorry for the insufficient information on the reduced genome used for the experimental evolution. The following descriptions were added in the Results and the Materials and Methods, respectively.

(L75-79) “The E. coli strain carrying a reduced genome, derived from the wild-type genome W3110, showed a significant decline in its growth rate in the minimal medium compared to the wild-type strain 13. To improve the genome reduction-mediated decreased growth rate, the serial transfer of the genome-reduced strain was performed with multiple dilution rates to keep the bacterial growth within the exponential phase (Fig. S1), as described 17,20.”

(L331-334) “The reduced genome has been constructed by multiple deletions of large genomic fragments 58, which led to an approximately 21% smaller size than its parent wild-type genome W3110.”

(11) How was the saturated density in Figure 1 actually determined? In particular, the fitness assay of growth curves is 48h. But it seems like the experimental evolution is done for ~24 h cycles. If the Evos never experienced a situation like a stationary phase between 24-48h, and if the author reported the saturated density 48 h in Figure 1, the explanation of the lower saturated density can be just relaxation from selection and may have nothing to do with the increase of growth rate.

Sorry for the unclear description. Yes, you are right. The evolution was performed within the exponential growth phase (keeping cell division constant), which means the Evos never experienced the stationary phase (saturation). The final evolved populations were subjected to the growth assay to obtain the entire growth curves for calculating the growth rate and the saturated density. Whether the decreased saturated density and the increased growth rate were in a trade-off relationship remained unclear. The corresponding paragraph was revised as follows.

(L100-115) “Intriguingly, a positive correlation was observed between the growth fitness and the carrying capacity of the Evos (Fig. 1D). It was somehow consistent with the positive correlations between the colony growth rate and the colony size of a genome-reduced strain 11 and between the growth rates and the saturated population size of an assortment of genome reduced strains 13. Nevertheless, the negative correlation between growth rate and carrying capacity, known as the r/K selection30,31 was often observed as the trade-off relationship between r and K in the evolution and ecology studies 32 33,34. As the r/K trade-off was proposed to balance the cellular metabolism that resulted from the cost of enzymes involved 34, the deleted genes might play a role in maintaining the metabolism balance for the r/K correlation. On the other hand, the experimental evolution (i.e., serial transfer) was strictly performed within the exponential growth phase; thus, the evolutionary selection was supposed to be driven by the growth rate without selective pressure to maintain the carrying capacity. The declined carrying capacity might have been its neutral "drift" but not a trade-off to the growth rate. Independent and parallel experimental evolution of the reduced genomes selecting either r or K is required to clarify the actual mechanisms.”

(12) What annotation of essentiality was used in this paper? In particular, the essentiality can be different in the reduced genome background compared to the WT background.

Sorry for the unclear definition of the essential genes. They are strictly limited to the 302 essential genes experimentally determined in the wild-type E coli strain. Detailed information can be found at the following website: https://shigen.nig.ac.jp/ecoli/pec/genes.jsp. We agree that the essentiality could differ between the WT and reduced genomes. Identifying the essential genes in the reduced genome will be an exhaustedly vast work. The information on the essential genes defined in the present study was added as follows.

(L134-139) “They seemed highly related to essentiality7 (https://shigen.nig.ac.jp/ecoli/pec/genes.jsp), as 11 out of 49 mutated genes were essential (Table S3). Although the essentiality of genes might differ between the wild-type and reduced genomes, the experimentally determined 302 essential genes in the wild-type E. coli strain were used for the analysis, of which 286 were annotated in the reduced genome.”

(13) The fixed mutations in essential genes are probably not rarely observed in experimental evolution. For example, fixed mutations related to RNA polymerase can be frequently seen when evolving to stressful environments. I think the author can discuss this more and elaborate more on whether they think these mutations in essential genes are important in adaptation or not.

Thank you for your careful reading and the suggestion. As you mentioned, we noticed that the mutations in RNA polymerases (rpoA, rpoB, and rpoD) were identified in three Evos. As they were not shared across all Evos, we didn't discuss the contribution of these mutations to evolution. Instead of the individual functions of the mutated essential gene functions, we focused on the enriched gene functions related to the transcriptome reorganization because they were the common feature observed across all Evos and linked to the whole metabolic or regulatory pathways, which are supposed to be more biologically reasonable and interpretable. The following sentence was added to clarify our thinking.

(L268-273) “In particular, mutations in the essential genes, such as RNA polymerases (rpoA, rpoB, rpoD) identified in three Evos (Table S3), were supposed to participate in the global regulation for improved growth. Nevertheless, the considerable variation in the fixed mutations without overlaps among the nine Evos (Table 1) implied no common mutagenetic strategy for the evolutionary improvement of growth fitness.”

(14) In experimental evolution to new environments, several previous literature also show that long-term experimental evolution in transcriptome is not consistent or even reverts the short-term response; short-term responses were just rather considered as an emergency plan. They seem to echo what the authors found in this manuscript. I think the author can refer to some of those studies more and make a more throughput discussion on short-term vs long-term responses in evolution.

Thank you for the advice. It's unclear to us what the short-term and long-term responses referred to mentioned in this comment. The "Response" is usually used as the phenotypic or transcriptional changes within a few hours after environmental fluctuation, generally non-genetic (no mutation). In comparison, long-term or short-term experimental "Evolution" is associated with genetic changes (mutations). Concerning the Evolution (not the Response), the long-term experimental evolution (>10,000 generations) was performed only with the wild-type genome, and the short-term experimental evolution (500~2,000 generations) was more often conducted with both wild-type and reduced genomes, to our knowledge. Previous landmark studies have intensively discussed comparing the wild-type and reduced genomes. Our study was restricted to the reduced genome, which was constructed differently from those reduced genomes used in the reported studies. The experimental evolution of the reduced genomes has been performed in the presence of additional additives, e.g., antibiotics, alternative carbon sources, etc. That is, neither the genomic backgrounds nor the evolutionary conditions were comparable. Comparison of nothing common seems to be unproductive. We sincerely hope the recommended topics can be applied in our future work.

Some minor suggestions

• Figures S3 & Table S2 need an explanation of the abbreviations of gene categories.

Sorry for the missing information. Figure S3 and Table S3 were revised to include the names of gene categories. The figure was pasted followingly for a quick reference.

Author response image 3.

• I hope the authors can re-consider the title; "Diversity for commonality" does not make much sense to me. For example, it can be simply just "Diversity and commonality."

Thank you for the suggestion. The title was simplified as follows.

(L1) “Experimental evolution for the recovery of growth loss due to genome reduction.”

• It is not easy for me to locate and distinguish the RNA-seq vs DNA-seq files in DRA013662 at DDBJ. Could you make some notes on what RNA-seq actually are, vs what DNA-seq files actually are?

Sorry for the mistakes in the DRA number of DNA-seq. DNA-seq and RNA-seq were deposited separately with the accession IDs of DRA013661 and DRA013662, respectively. The following correction was made in the revision.

(L382-383) “The raw datasets of DNA-seq were deposited in the DDBJ Sequence Read Archive under the accession number DRA013661.”

eLife assessment

This is an important study of the recovery of genome-reduced bacterial cells in laboratory evolution experiments, to understand how they regain their fitness. Through the analysis of gene expression and a series of tests, the authors present convincing evidence indicating distinct molecular changes in the evolved bacterial strains, although the precise mechanisms remain uncharacterized. These findings imply that diverse mechanisms are employed to offset the effects of a reduced genome, offering intriguing insights into genome evolution.

Reviewer #1 (Public Review):

In this study, the authors explored how the reduced growth fitness, resulting from genome reduction, can be compensated through evolution. They conducted an evolution experiment with a strain of Escherichia coli that carried a reduced genome, over approximately 1,000 generations. The authors carried out sequencing, and found no clear genetic signatures of evolution across replicate populations. They carry out transcriptomics and a series of analyses that lead them to conclude that there are divergent mechanisms at play in individual evolutionary lineages. The authors used gene network reconstruction to identify three gene modules functionally differentiated, correlating with changes in growth fitness, genome mutation, and gene expression, respectively, due to evolutionary changes in the reduced genome.

I think that this study addresses an interesting question. Many microbial evolution experiments evolve by loss of function mutations, but presumably a cell that has already lost so much of its genome needs to find other mechanisms to adapt. Experiments like this have the potential to study "constructive" rather than "destructive" evolution.

Comments on revised version:

I think the authors have carefully gone through the manuscript and addressed all of my concerns.

Reviewer #2 (Public Review):

This manuscript describes an adaptive laboratory evolution (ALE) study with a previously constructed genome-reduced E. coli. The growth performance of the end-point lineages evolved in M63 medium was comparable to the full-length wild-type level at lower cell densities.

Subsequent mutation profiling and RNA-Seq analysis revealed many changes on the genome and transcriptomes of the evolved lineages. The authors did a great deal on analyzing the patterns of evolutionary changes between independent lineages, such as the chromosomal periodicity of transcriptomes, pathway enrichment analysis, weight gene co-expression analysis, and so on. They observed a striking diversity in the molecular characteristics amongst the evolved lineages, which, as they suggest, reflect divergent evolutionary strategies adopted by the genome-reduced organism.

As for the overall quality of the manuscript, I am rather torn. The manuscript leans towards elaborating observed findings, rather than explaining their biological significance. For this reason, readers are left with more questions than answers. For example, fitness assay on reconstituted (single and combinatorial) mutants was not performed, nor any supporting evidence on the proposed contributions of each mutants provided. This leaves the nature of mutations - be them beneficial, neutral or deleterious, the presence of epistatic interactions, and the magnitude of fitness contribution, largely elusive. Also, it is difficult to tell whether the RNA-Seq analysis in this study managed to draw biologically meaningful conclusions, or instill insight into the nature of genome-reduced bacteria. The analysis primarily highlighted the differences in transcriptome profiles among each lineage based on metrics such as 'DEG counts' and the 'GO enrichment'. However, I could not see any specific implications regarding the biology of the evolved minimal genome drawn. In their concluding remark, 'Multiple evolutionary paths for the reduced genome to improve growth fitness were likely all roads leading to Rome,' the authors observed the first half of the sentence, but the distinctive characteristics of 'all roads' or 'evolutionary paths', which I think should have been the key aspect in this investigation, remains elusive.

Comments on revised version:

I appreciate the author's responses. They responded to most of the comments, but I still think that there is room for improvement. Please refer to the following comments. Quoted below are the author's responses.

"We agree that our study leaned towards elaborating observed findings rather than explaining the detailed biological mechanisms."<br /> - Comment: I doubt if there are scientific merits in merely elaborating observed findings. The conclusion of this study suggests that evolutionary paths in reduced genomes are highly diverse. But if you think about the nature of adaptive evolution, which relies upon the spontaneous mutation event followed by selection, certain degree of divergence is always expected. The problem with current experimental setting is that there are no ways to quantitively assess whether the degree of evolutionary divergence increases as the function of genome reduction, as the authors claimed. In addition, this notion is in direct contradiction to the prediction that genome reduction constraints evolution by reducing the number of solution space. It is more logical to think and predict that genome reduction would, in turn, lead to the loss of evolutionary divergence. We are also interested to know whether solution space to the optimization problem altered in response to the genome reduction. In this regard, a control ALE experiment on non-reduced wild-type seems to be a mandatory experimental control. I highly suggest that authors present a control experiment, as it was done for "JCVI syn3.0B vs non-minimal M. mycoides" (doi: 10.1038/s41586 023 06288 x) and "E. coli eMS57 vs MG1655" (doi: 10.1038/s41467 019 08888 6).<br /> "We focused on the genome wide biological features rather than the specific biological functions."<br /> - Comment: The 'biological features' delivered in current manuscript does not give insight as to which genomic changes translated into strain fitness improvement. Rather than explaining the genotype-phenotype relationships and/or the mechanistic basis of fitness improvement, authors merely elaborated on the observed phenotypes. I question the scientific merits of such 'findings'.<br /> "Although the reduced growth rate caused by genome reduction could be recovered by experimental evolution, it remains unclear whether such an evolutionary improvement in growth fitness was a general feature of the reduced genome and how the genome wide changes occurred to match the growth fitness increase."<br /> - Comment: This response is very confusing to understand. "it remains unclear whether such an evolutionary improvement in growth fitness was a general feature of the reduced genome" - what aspects remain unclear?? What assumption led the authors to believe that reduced genome's fitness cannot be evolutionarily improved?<br /> - Comment: "and how the genome wide changes occurred to match the growth fitness increase" - this is exactly the aspect that authors should deliver, instead of just elaborating the observed findings. Why don't authors select one or two fastest-growing (or the fittest) lineages and specifically analyze underlying adaptive changes (i.e. genotype-phenotype relationships)?

Author response:

eLife assessment

In this valuable study, Kumar et al., provide evidence suggesting that the p130Cas drives the formation of condensates that sprout from focal adhesions to cytoplasm and suppress translation. Pending further substantiation, this study was found to be likely to provide previously unappreciated insights into the mechanisms linking focal adhesions to the regulation of protein synthesis and was thus considered to be of broad general interest. However, the evidence supporting the proposed model was incomplete; additional evidence is warranted to substantiate the relationship between p130Cas condensates and mRNA translation and establish corresponding functional consequences.

We thank the Elife editorial team for their positive assessment of the broad significance of our manuscript. We fully agree that the functional consequences need to be explored in more detail. We feel that many of the criticisms are valid points that are not easily addressed via available tools, thus, should be considered limitations of present approaches. We hope that readers appreciate that identification of a new class of liquid-liquid phase separations calls for much more work to fully explore their characteristics, regulation and function, which will likely advance many areas of cell biology and perhaps even medicine.

Reviewer #1 (Public Review):

Summary:

The authors demonstrated the phenomenon of p130Cas, a protein primarily localized at focal adhesions, and its formation of condensates. They identified the constituents within the condensates, which include other focal adhesion proteins, paxillin, and RNAs. Furthermore, they proposed a link between p130Cas condensates and translation.

Strengths:

Adhesion components undergo rapid exchange with the cytoplasm for some unclear biological functions. Given that p130Cas is recognized as a prominent mechanical focal adhesion component, investigating its role in condensate formation, particularly its impact on the translation process, is intriguing and significant.

We thank the reviewer for recognizing the functional significance of the work.

Weaknesses:

The authors identified the disordered region of p130Cas and investigated the formation of p130Cas condensate. They attempted to demonstrate that p130Cas condensates inhibit translation, but the results did not fully support this assertion. There are several comments below:

(1) Despite isolating p130Cas-GFP protein using GFP-trap beads, the authors cannot conclusively eliminate the possibility of isolating p130Cas from focal adhesions. While the characterization of the GFP-tagged pulls can reveal the proteins and RNAs associated with p130Cas, they need to clarify their intramolecular mechanism of localization within p130Cas droplets. Whether the protein condensates retain their liquid phase or these GFP-p130Cas pulls represent protein aggregate remains uncertain.

We agree, the isolation from cell lysates does not distinguish between focal adhesions and cytoplasmic LLPS. We note that p130Cas in focal adhesions also appears to be in LLPS. But there are no methods available to isolate them separately. We acknowledge this is a limitation of the study.

(2) The authors utilized hexanediol and ammonium acetate to highlight the phenomenon of p130Cas condensates. Although hexanediol is an inhibitor for hydrophobic interactions and ammonium acetate is a salt, a more thorough explanation of the intramolecular mechanisms underlying p130Cas protein-protein interaction is required. Additionally, given that the size of p130Cas condensates can exceed >100um2, classification is needed to differentiate between p130Cas condensates and protein aggregation.

Ammonium acetate, which works by promoting hydrophobic interactions and weak Van der Waals forces, has been widely used in phase separation studies to change ionic strength without altering intracellular pH. Conversely, hexanediol weakens hydrophobic/ Van der Walls interactions that commonly mediate phase separation of IDRs. In the case of p130Cas, the multiple tyrosines and within the scaffolding domain are obvious targets. If the reviewer is asking us to resolve the detailed hydrophobic interactions within the scaffolding domain, this is far beyond the scope of the current paper.

Protein aggregates are defined by their characteristics (e.g irreversibility, departure from spherical) not by size. Older, larger droplets remain circular and show slower but still measurable rates of exchange. Moreover, droplets are essentially absent after trypsinizing and replating cells. All these results argue against aggregates.

(3) The connection between p130Cas condensates and translation inhibition appears tenuous. The data only suggests a correlation between p130Cas expression and translation inhibition. Further evidence is required to bolster this hypothesis.

The optogenetic experiment shows that triggering LLPS by dimerizing p130Cas results in inhibition of translation. This is a causal not a correlative experiment. The reviewer may be thinking that dimerizing p130Cas could stimulate focal adhesion signaling, activating FAK or a src family kinase or other signals. However, none of these signals has been linked to inhibition of cell growth or migration. Thus, we agree that this is a limitation but consider it a low probability mechanism.

Reviewer #2 (Public Review):

Summary:

In this article, Kumar et al., report on a previously unappreciated mechanism of translational regulation whereby p130Cas induces LLPS condensates that then traffic out from focal adhesion into the cytoplasm to modulate mRNA translation. Specifically, the authors employed EGFP-tagged p130Cas constructs, endogenous p130Cas, and p130Cas knockouts and mutants in cell-based systems. These experiments in conjunction with various imaging techniques revealed that p130Cas drives assembly of LLPS condensates in a manner that is largely independent of tyrosine phosphorylation. This was followed by in vitro EGFP-tagged p130Cas-dependent induction of LLPS condensates and determination of their composition by mass spectrometry, which revealed enrichment of proteins involved in RNA metabolism in the condensates. The authors excluded the plausibility that p130Cas-containing condensates co-localize with stress granules or p-bodies. Next, the authors determined mRNA compendium of p130Cas-containing condensates which revealed that they are enriched in transcripts encoding proteins implicated in cell cycle progression, survival, and cell-cell communication. These findings were followed by the authors demonstrating that p130Cas-containing condensates may be implicated in the suppression of protein synthesis using puromycylation assay. Altogether, it was found that this study significantly advances the knowledge pertinent to the understanding of molecular underpinnings of the role of p130Cas and more broadly focal adhesions on cellular function, and to this end, it is likely that this report will be of interest to a broad range of scientists from a wide spectrum of biomedical disciplines including cell, molecular, developmental and cancer biologists.

Strengths:

Altogether, this study was found to be of potentially broad interest inasmuch as it delineates a hitherto unappreciated link between p130Cas, LLPS, and regulation of mRNA translation. More broadly, this report provides unique molecular insights into the previously unappreciated mechanisms of the role of focal adhesions in regulating protein synthesis. Overall, it was thought that the provided data sufficiently supported most of the authors' conclusions. It was also thought that this study incorporates an appropriate balance of imaging, cell and molecular biology, and biochemical techniques, whereby the methodology was found to be largely appropriate.

We thank reviewer for this positive assessment.

Weaknesses:

Two major weaknesses of the study were noted. The first issue is related to the experiments establishing the role of p130Cas-driven condensates in translational suppression, whereby it remained unclear whether these effects are affecting global mRNA translation or are specific to the mRNAs contained in the condensates. Moreover, some of the results in this section (e.g., experiments using cycloheximide) may be open to alternative interpretation. The second issue is the apparent lack of functional studies, and although the authors speculate that the described mechanism is likely to mediate the effects of focal adhesions on e.g., quiescence, experimental testing of this tenet was lacking.

We appreciate the reviewer’s insights. Assessing translational inhibition for specific genes rather than global measurement of translation is an important direction for future work.

Regarding the cycloheximide experiments, we are unsure what the reviewer means. We used it as a control for puromycin labeling but this is a very standard approach. It seems more likely that the question concerns Fig 5G, where we used it to sequester mRNAs on ribosomes to deplete from other pools. In this case, p130cas condensates decrease after 2 minutes. The reviewer may be suggesting that this effect could be due to blocked translation per se and loss of short-lived proteins. We acknowledge that this is possible but given the very rapid effect (2 min), we think it unlikely.

Lastly, we agree with the reviewer that further functional studies in quiescence or senescence are warranted; however, these are extensive, open-ended studies and we will not be able to include them as part of the current paper.

if let - удобна в том случае, когда нужен только один из всех вариантов, enum. остальные он просто будет игнорировать.

Otherwise known as prisoners dilemma and "defect / defect" equilibrium.

(Aside: why invent new terms). It's just classic game theory PD ...

Using the term Reddits to call out the founders.

Author response:

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

eLife assessment

In this valuable study, the authors investigate the transcriptional landscape of tuberculous meningitis, revealing important molecular differences contributed by HIV co-infection. Whilst some of the evidence presented is compelling, the bioinformatics analysis is limited to a descriptive narrative of gene-level functional annotations, which are somewhat basic and fail to define aspects of biology very precisely. Whilst the work will be of broad interest to the infectious disease community, validation of the data is critical for future utility.

We appreciate with eLife’s positive assessment, although we challenge the conclusion that we ‘fail to define aspects of biology very precisely’. Our stated objective was to use bioinformatics tools to identify the biological pathways and hub genes associated with TBM pathogenesis and the eLife assessment affirms we have investigated ‘the transcriptional landscape of tuberculous meningitis’. To more precisely define aspects of the biology will require another study with different design and methods.

Reviewer #1 (Public Review):

Summary:

Tuberculous meningitis (TBM) is one of the most severe forms of extrapulmonary TB. TBM is especially prevalent in people who are immunocompromised (e.g. HIV-positive). Delays in diagnosis and treatment could lead to severe disease or mortality. In this study, the authors performed the largest-ever host whole blood transcriptomics analysis on a cohort of 606 Vietnamese participants. The results indicated that TBM mortality is associated with increased neutrophil activation and decreased T and B cell activation pathways. Furthermore, increased angiogenesis was also observed in HIV-positive patients who died from TBM, whereas activated TNF signaling and down-regulated extracellular matrix organisation were seen in the HIV-negative group. Despite similarities in transcriptional profiles between PTB and TBM compared to healthy controls, inflammatory genes were more active in HIV-positive TBM. Finally, 4 hub genes (MCEMP1, NELL2, ZNF354C, and CD4) were identified as strong predictors of death from TBM.

Strengths:

This is a really impressive piece of work, both in terms of the size of the cohort which took years of effort to recruit, sample, and analyse, and also the meticulous bioinformatics performed. The biggest advantage of obtaining a whole blood signature is that it allows an easier translational development into a test that can be used in the clinical with a minimally invasive sample. Furthermore, the data from this study has also revealed important insights into the mechanisms associated with mortality and the differences in pathogenesis between HIV-positive and HIV-negative patients, which would have diagnostic and therapeutic implications.

Weaknesses:

The data on blood neutrophil count is really intriguing and seems to provide a very powerful yet easy-to-measure method to differentiate survival vs. death in TBM patients. It would be quite useful in this case to perform predictive analysis to see if neutrophil count alone, or in combination with gene signature, can predict (or better predict) mortality, as it would be far easier for clinical implementation than the RNA-based method. Moreover, genes associated with increased neutrophil activation and decreased T cell activation both have significantly higher enrichment scores in TBM (Figure 9) and in morality (Figure 8). While I understand the basis of selecting hub genes in the significant modules, they often do not represent these biological pathways (at least not directly associated in most cases). If genes were selected based on these biologically relevant pathways, would they have better predictive values?

We conducted a sensitivity analysis including blood neutrophil as a potential predictor in the multivariate Cox elastic-net regression model for important predictor selection (Table S14). In this analysis, all six selected important predictors (genes and clinical risk factors) identified in the original analysis (Table S13) were also selected, together with blood neutrophil number. Additionally, we evaluated the predictive value of blood neutrophil alone, which demonstrated poor performance, with an optimism-corrected AUC of 0.63 for all TBM, 0.67 for HIV-negative TBM, and 0.70 for HIV-positive TBM. Even when combined with identified gene signatures, blood neutrophil did not improve the overall performance of predictive model (optimism-corrected AUC of 0.79 for all TBM, 0.76 for HIV-negative TBM, and 0.80 for HIV-positive). These results indicate that identified hub genes exhibit better predictive values compared to blood neutrophil alone or in combination. These findings have been incorporated into our manuscript results.

To test whether pathway representative genes have better predictive values than hub genes, we included all these genes in the analysis for important predictor selection. Pathway representative genes comprised ANXA3 and CXCR2 representing neutrophil activation and IL1b representing acute inflammatory response. We observed that all hub genes (MCEMP1, NELL2, ZNF354C, and CD4) consistently emerged as the most important genes with the highest selection in the models, compared to the rest, in both the HIV-negative TBM and HIV-positive TBM cohorts. Additionally, these identified hub genes were still selected when testing together with other hub genes representing relevant biological pathways associated with TBM mortality, such as CYSTM1 involved in neutrophil activation, TRAF5 involved in NF-kappa B signaling pathway, CD28 and TESPA1 involved in T cell receptor signaling. These results show that selected genes based on known biologically relevant pathways did not give better predictive values than the identified hub genes in the significant modules.

Reviewer #2 (Public Review):

Summary:

This manuscript describes the analysis of blood transcriptomic data from patients with TB meningitis, with and without HIV infection, with some comparison to those of patients with pulmonary tuberculosis and healthy volunteers. The objectives were to describe the comparative biological differences represented by the blood transcriptome in TBM associated with HIV co-infection or survival/mortality outcomes and to identify a blood transcriptional signature to predict these outcomes. The authors report an association between mortality and increased levels of acute inflammation and neutrophil activation, but decreased levels of adaptive immunity and T/B cell activation. They propose a 4-gene prognostic signature to predict mortality.

Strengths:

Biological evaluations of blood transcriptomes in TB meningitis and their relationship to outcomes have not been extensively reported previously.

The size of the data set is a major strength and is likely to be used extensively for secondary analyses in this field of research.

Weaknesses:

The bioinformatic analysis is limited to a descriptive narrative of gene-level functional annotations curated in GO and KEGG databases. This analysis cannot be used to make causal inferences. In addition, the functional annotations are limited to 'high-level' terms that fail to define biology very precisely. At best, they require independent validation for a given context. As a result, the conclusions are not adequately substantiated. The identification of a prognostic blood transcriptomic signature uses an unusual discovery approach that leverages weighted gene network analysis that underpins the bioinformatic analyses. However, the main problem is that authors seem to use all the data for discovery and do not undertake any true external validation of their gene signature. As a result, the proposed gene signature is likely to be overfitted to these data and not generalisable. Even this does not achieve significantly better prognostic discrimination than the existing clinical scoring.

As explained in response to the eLife assessment, our objective was to use bioinformatics tools to identify the biological pathways and hub genes associated with TBM pathogenesis. We agree that ‘This analysis cannot be used to make causal inferences’: that would require different study design and approaches. The proposed gene signature has higher AUC values than the existing clinical model alone or in combination with clinical risk factors (Table 4). We agree that independent validation of the gene signature will be a crucial next step for future utility. We have performed qPCR in another sample set, and have added these results in the revision (Table 4 and supplementary figure S8)

Reviewer #1 (Recommendations For The Authors):

I have a few additional comments most of which are relatively minor:

(1) Can the authors please clarify if all the PTB cases are also HIV-negative?

This has been added to the methods section.

(2) For Table 1, can the authors please list the total number of patients with microbiologically confirmed TB regardless of the methods used? And for the two TBM groups, was the positive microbiology based on CSF findings?

The total number of patients with microbiologically confirmed TB was presented in Table 2 in definite TBM group, which was microbiologically confirmed TB diagnosed using microscopy, culture, and Xpert testing in cerebrospinal fluid (CSF) samples. We have updated the note in Table 2 to provide clarity on the definition.

(3) How was the discovery and validation set selected? Was it based on randomisation?

We randomly split TBM data into two datasets, a discovery cohort (n=142) and a validation cohort (n=139) with a purpose to ensure reproducibility of data analysis. We described this in the methods section.

(4) Line 107 can be better clarified by stating that the overall 3-month mortality rate is 21.7% for TBM regardless of HIV status.

Thank you, we have restated this sentence in the results section.

(5) The authors stated that samples were collected at enrolment when patients would have received less than 6 days of anti-tubercular treatment. Is there information on the median and IQR on the number of days that the patients would have received Rx, especially between the groups? Did the authors control for this variable when analysing for DEGs?

One of criteria to enroll participants in LAST-ACT and ACT-HIV trials is that they must receive less than 6 consecutive days of two or more drugs active against M. tuberculosis. However, the information of the days that the patients would have received Rx was not recorded and we could not control this variable when performing differential expression analysis for DEGs. This has been clarified further in the methods section: ‘The samples were taken at enrollment, when patients could not have received more than 6 consecutive days of two or more drugs active against M. tuberculosis.’

(6) I am a little bit concerned with the reads mapping accuracy (57%) to the human genome, which is fairly low. Did the authors investigate the reasons behind this low accuracy?

Thank you. It was indeed a typo. We have corrected it in the results section.

(7) On Tables S2-S4, can the authors please clarify what the last column (labelled as "B") shows?

Tables S2-S4 now have been changed to S3-S5. We have updated the legend of these tables to provide clarification regarding the meaning of the last column.

Reviewer #2 (Recommendations For The Authors):

If the authors wish to revise their manuscript, I suggest the following amendments:

(1) Provide a consort diagram for the selection of samples included in the present analysis (from parent study cohorts), allocation to test and validation splits for bioinformatics analysis, and outcomes.

We have provided our consort diagram in supplementary Figure S10.

(2) Provide details of inclusion criteria for pulmonary TB cohort, and how samples from this cohort were selected for inclusion in the present analysis. Please clarify whether this cohort excluded HIV-positive participants by design or by chance.

The inclusion criteria for the pulmonary TB cohort were described in the methods section. Due to the very low prevalence of HIV in this prospective observational study, HIV-positive participants were excluded. We have clarified in the amended manuscript that the pulmonary TB cohort only included HIV-negative participants.

(3) Baseline characteristics of HIV-positive participants (Table 1) should include CD4 count, HIV viral load, and whether anti-retroviral therapy was naïve or experienced.

We have included pre-treatment CD4 cell count, information on anti-retroviral therapy, and HIV viral load data in Table 1, as well as described these information in the results section.

(4) I note that the TBM samples were derived from RCTs of adjunctive steroid therapy, but not stratified in the present analysis by treatment arm allocation. Clearly, this may affect the survival/mortality outcomes that are the central focus of this manuscript. Therefore, they should be included in the models for differential gene expression analysis and prognostic signature discovery. To do so, the authors may need to wait until they are able to unblind the trial metadata.

With permission from the trial investigators, we were able to adjust the analyses for treatment with corticosteroids. The investigators remained blind to the allocation and we have not reported any direct effects of corticosteroids on outcome – such an analysis could only be done once the LAST-ACT trial has been reported (which won’t be until the end of 2024). Treatment outcome and effect were blinded by extracting only the fold change difference between survival and death in the linear regression model, in which gene expression was outcome and survival and treatment were covariates.

(5) I understood from the methods (lines 460-461) that batch correction of the RNAseq data was necessary. However, it is not clear how the samples were batched. PCA of the transcriptomes before and after batch correction with batch and study group labels should be provided. I would also advocate for a sensitivity analysis to check the robustness of the main findings without batch correction. I assume Fig2A represents batch-corrected data, but this is not clear.

We have now added information about the RNA sequencing batch and the batch correction approach, analyses and data visualizations utilized batch-corrected data in the methods section. We have also updated results related to batch correction in Fig. 2A and Supplementary Figure S9.

(6) I would encourage the authors to include a differential gene expression analysis to directly compare the transcriptome of TBM to that of pulmonary TB. I think it would add additional value to their focus on describing the transcriptome in TBM.

We thank for reviewer’s suggestion. Conducting differential gene expression analysis to compare the transcriptome of TBM with that of PTB is beyond the scope of this manuscript and we will examine this question separately.

(7) I don't really understand the purpose of splitting their data set into test and validation for the purposes of showing that WGCNA analysis is mostly reproduced in the two halves of the data. I would advocate that they scrap this approach to maximise the statistical power of their analysis in the descriptive work.

As mentioned in response to reviewer #1 in question #3, the purpose of splitting data is to ensure the reproducibility of the data analysis as suggested by Langfelder et al. (PMID: 21283776). This approach served two purposes: (i) to affirm the existence of functional modules in an independent cohort and (ii) to validate the association of interested modules or their hub genes with survival outcomes.

(8) The authors should soften the confidence in their interpretation of the GO/KEGG annotations of WGCNA modules. At least, they should include a paragraph that explicitly details the limitations of their analyses, including (i) the accuracy GO/KEGG annotations are not validated in this context (if at all), (ii) that none of the data can be used to make causal inferences and (iii) that peripheral blood assessments that are obviously impacted by changes in cellular composition of peripheral blood do not necessarily reflect immunopathogenesis at the site of disease - in fact if circulating cells are being recruited to the site of disease or other immune compartments, then quite the opposite interpretations may be true.

We appreciate the reviewer's comment. (i) In our analysis, we initially confirmed the existence of Weighted Gene Co-expression Network Analysis (WGCNA) modules in discovery cohort and validated the association of these modules with mortality outcomes in validation cohort. We then applied GO/KEGG annotations to define the biological functions involved in WGCNA modules. Finally, we performed Qusage analysis to directly test the association of top-hit pathways of each WGCNA module with mortality outcomes (see supplementary S6). This analysis approach helped to identify and validate modules and biological pathways associated with TBM mortality in this context, avoiding potential false positives in GO/KEGG annotations of WGCNA modules. (ii) We agree with the assessment that 'This analysis cannot be used to make causal inferences,' as that would require a different study design and approach. (iii) The focus of this study is to investigate the pathogenesis of TBM in the systemic immune system. We have highlighted this focus in the title and the aim of the manuscript.

(9) For the prognostic signature discovery and validation, I strongly recommend the authors include more robust validation. For example, to undertake an 80:20 split for sequential discovery (for feature selection and derivation of a prognostic model), followed by validation of a 'locked' model in data that made no contribution to discovery. In two separate sensitivity analyses. I also suggest they split their dataset (i) by treatment allocation in the RCT and (ii) by HIV status. In addition, their method for feature selection has to be clearer- precisely how they select hub genes from their WGCNA analysis as candidate predictors is not explained. Since this is such a prominent output of their manuscript, the results of this analysis should really be included in the main manuscript, and all performance metrics for discrimination should include confidence intervals.

Employing an 80:20 split for training and testing models is a good approach for an internal validation. However, we addressed the issue of overestimating the performance of a prognostic model by bootstrapping sampling approach proposed by Steyerberg et al. (PMID: 11470385). This approach has been proven to provide stable estimates with low bias. The overall model performance for discrimination, reported in our manuscript, was corrected for “optimism” to ensure internal validity. This adjustment was achieved through a 1000-times bootstrapping approach, which effectively accounted for estimation uncertainty. As such, there is no need to present confidence intervals for these metrics.

Moreover, in our revision, to confirm prognostic signatures independently, we have evaluated the predictive value of identified gene signatures using qPCR in another set of samples. The results have been added in Table 4, supplementary Figure S8 and the results section.

For the reasons given above (comment 4), we are unable to split our dataset by treatment allocation in this analysis. But as described, we have adjusted the analysis for corticosteroid treatment. Once the primary results of the LAST ACT trial have been published, we will examine the impact of corticosteroids on TBM pathophysiology and outcomes, seeking to better understand the mechanisms by which steroids have their therapeutic effects.

Given the difference in pathogenesis and immune response by HIV-coinfection, we stratified our analysis by HIV status. As the reviewer’s suggestion, we have provided additional details in the methods section regarding the selection of hub genes from associated WGCNA modules and the feature selection process for predictive modeling.

eLife assessment

In this valuable study, the authors investigate the transcriptional landscape of tuberculous meningitis. They reveal potentially significant molecular differences contributed by HIV co-infection, and derive a prognostic model to predict mortality combining a gene expression signature with clinical parameters. Whilst some of the evidence presented is compelling, the bioinformatics analysis remains limited and cannot be used to make causal inferences and conclusions about immunopathogenesis for tuberculous meningitis. The work will be of broad interest to the infectious disease community however, further validation of the findings is critical for future utility.

Reviewer #1 (Public Review):

Summary:

Tuberculous meningitis (TBM) is one of the most severe form of extrapulmonary TB. TBM is especially prevalent in people who are immunocompromised (e.g. HIV-positive). Delays in diagnosis and treatment could lead to severe disease or mortality. In this study, the authors performed the largest ever host whole blood transcriptomics analysis on a cohort of 606 Vietnamese participants. The results indicated that TBM mortality is associated with increased neutrophil activation and decreased T and B cell activation pathways. Furthermore, increased angiogenesis was also observed in HIV-positive patients who died from TBM, whereas activated TNF signaling and down-regulated extracellular matrix organisation were seen in the HIV-negative group. Despite similarities in transcriptional profiles between PTB and TBM compared to healthy controls, inflammatory genes were more active in HIV-positive TBM. Finally, 4 hub genes (MCEMP1, NELL2, ZNF354C and CD4) were identified as strong predictors of death from TBM.

Strengths:

This is a really impressive piece of work, both in terms of the size of the cohort which took years of effort to recruit, sample and analyse and also the meticulous bioinformatics performed. The biggest advantage of obtaining a whole blood signature is that it allows an easier translational development into test that can be used in the clinical with a minimally invasive sample. Furthermore, the data from this study has also revealed important insights in the mechanisms associated with mortality and the differences in pathogenesis between HIV-positive and HIV-negative patients, which would have diagnostic and therapeutic implications.

Weaknesses:

The authors have addressed all the weaknesses in the revised version.

Reviewer #2 (Public Review):

Summary:

This manuscript describes the analysis of blood transcriptomic data from patients with TB meningitis, with and without HIV infection, with some comparison to those of patients with pulmonary tuberculosis and healthy volunteers. The objectives were to describe the comparative biological differences represented by the blood transcriptome in TBM associated with HIV co-infection or survival/mortality outcomes, and to identify a blood transcriptional signature to predict these outcomes. The authors report an association between mortality and increased levels of acute inflammation and neutrophil activation, but decreased levels of adaptive immunity and T/B cell activation. They propose a 4-gene prognostic signature to predict mortality.

Strengths:

Biological evaluations of blood transcriptomes in TB meningitis and their relationship to outcomes have not been extensively reported previously.<br /> The size of the data set is a major strength and is likely to be used extensively for secondary analyses in this field of research.<br /> The addition of a new validation cohort to evaluate the generalisability of their prognostic model in the revised manuscript is welcome.

Weaknesses:

The bioinformatic analysis is limited to a descriptive narrative of gene-level functional annotations curated in GO and KEGG databases. This analysis cannot be used to make causal inferences. In addition the functional annotations are limited to 'high-level' terms that fail to define the biology very precisely. As a result, the conclusions about the immunopathogenesis of TBM are not adequately substantiated.<br /> The lack of AUROC confidence intervals and direct comparison to the reference prognostic model in the validation cohort undermines confidence in their conclusion that their new prognostic model combing gene expression data and clinical variables performs better than the reference model.

Author response:

The following is the authors’ response to the previous reviews

We extend our sincere gratitude for the invaluable comments provided by the reviewers and yourself, along with the constructive suggestions to enhance the quality of our manuscript. In response to this invaluable feedback, we have diligently revised and resubmitted our paper as an article, introducing five primary figures, seven supplementary figures, and two supplementary data files. Importantly, this work represents a significant contribution to the field, presenting novel findings for the first time without any prior publication.

Within the enclosed document, we have provided a comprehensive response to the editor and reviewer comments, addressing each point meticulously and specifically. We extend our heartfelt thanks to the reviewers and yourself for your diligent examination of our manuscript and for offering insightful recommendations.

In our latest revision, we have taken great care to address every comment, ensuring that we clarify the manuscript and provide robust evidence where required. We have meticulously highlighted the modifications within the manuscript in yellow for your convenience, while also including the modifications made in response to each specific comment. The primary focus of these revisions was to provide additional context regarding the relationship between PARP-1 and mono-methylated histones. Substantial modifications were made to our discussion section to address this point.

Another concern raised was regarding the discrepancy in the relationship of PR-SET7 and PARP-1 between our study and the recent study by Estève et al. (PMID: 36434141). We have revised the results and discussion sections to discuss this concern.

Addressing Reviewer 2’s concern about the potential indirect role of PARP1 in the regulation of some metabolic genes despite its direct binding to loci coding for metabolic genes we revised the discussion section to highlight this possibility.

Enclosed, you will find a detailed, point-by-point response to each of the editor’s and reviewers' comments, showcasing our commitment to addressing their concerns with precision.

We firmly believe that our revisions successfully resolve all the concerns raised by the editor and the reviewers, and we are confident that this improved version of our manuscript contributes significantly to the scientific discourse. Once again, we thank you for considering our work, and please feel free to contact me if you require any additional information.

In the revised manuscript, most of the concerns raised by the reviewers have been addressed satisfactorily. However, as suggested by reviewer#2, it would have been more significant, if the PARP1-mediated reading of global mono-methylation of histone could be addressed. At least the mechanisms of selectivity of PARP1 need further convincing discussion.

We thank the editor for their valuable comments. We have extended our discussion section to discuss in more detail the relationship between PARP1 and mono-methylated histones. In our refined Discussion section, we have endeavored to articulate more clearly how PARP-1 may be selectively recruited to active chromatin domains through its interaction with mono-methylated histone marks. We propose a model wherein PARP-1 actively participates in the turnover process, contributing to the maintenance of an active chromatin environment. This mechanism entails PARP-1 selectively binding to mono-methylated active histone marks associated with highly transcribed genes. Upon activation, PARP-1 undergoes automodification, leading to its release from chromatin and facilitating the reassembly of nucleosomes carrying the mono-methylated marks. Subsequently, the enzymatic action of Poly(ADP)-ribose glycohydrolase (PARG) cleaves pADPr, enabling the restoration of PARP-1's binding affinity to mono-methylated active histone marks. This proposed hypothesis is consistent with existing research across various model organisms and aligns with the known association of PARP-1 with highly expressed genes, as well as its role in mediating nucleosome dynamics and assembly.

Our modified Discussion section unfolds as follows:

"Finally, highly transcribed genes have been reported to present a high turnover of mono-methylated modifications, maintaining a state of low methylation (50). Moreover, our previous study revealed that PARP1 preferentially binds to highly active genes (34).  Consequently, our findings suggest an active involvement of PARP-1 in the turnover process to maintain an active chromatin environment. This proposed mechanism unfolds in the following steps: 1) PARP-1 selectively binds to mono-methylated active histone marks associated with highly transcribed genes. 2) Upon activation, PARP-1 undergoes automodification and subsequently disengages from chromatin, facilitating the reassembly of nucleosomes carrying the mono-methylated marks. 3) The enzymatic action of Poly(ADP)-ribose glycohydrolase (PARG) cleaves pADPr, restoring PARP-1's binding affinity to mono-methylated active histone marks. This proposed hypothesis is consistent with existing research conducted across various model organisms, including mice, Drosophila, and Humans (7, 24, 30, 51-53). Notably, previous studies have consistently demonstrated that PARP-1 predominantly associates with highly expressed genes and plays a crucial role in mediating nucleosome dynamics and assembly. Thus, our proposed model provides a molecular framework that may contribute to understanding the relationship between PARP-1 and the epigenetic regulation of gene expression."

We trust that these revisions effectively address the editor’s comment and enhance the overall strength and clarity of our manuscript.

Furthermore, recent developments in the area are omitted, as an important publication hasn't been discussed anywhere in the work (PMID: 36434141).

We appreciate the editor's thorough review of our revised manuscript and the responses to the previous reviewer's comments. To address this important concern, we have carefully investigated the levels of PR-SET7 in parp1 hypomorphic conditions.

Supplemental Fig. S4 and S5 demonstrate that in the absence of Parp1, there were no significant changes observed in PR-SET7 RNA or protein levels, respectively. This finding supports the conclusion that Parp1 is not directly involved in the regulation of PR-SET7 in Drosophila contrasting with the findings of Estève et al.'s study (PMID: 36434141). This discrepancy may arise from differing relationships between PARP-1 and PR-SET7, which could cooperate in the context of Drosophila development while playing antagonistic roles in specific cell lines or under particular conditions.

We have updated the Results section to explicitly mention this observation:

"Interestingly, in the absence of PARP-1, neither PR-SET7 RNA nor protein levels were affected (Supplemental Fig.S4-5), indicating that PARP-1 is not directly implicated in the regulation of pr-set7. This finding contrasts with recent evidence demonstrating PARP1-induced degradation of PR-SET7/SET8 in human cells (16)."

Furthermore, we have modified the discussion section to address this discrepancy:

"A recent study demonstrated that in human cells overexpressing PARP-1, PR-SET7/SET8 is degraded, whereas depletion of PARP-1 leads to an increase in PR-SET7/SET8 levels (16). However, in our study involving parp-1 mutant in Drosophila third-instar larvae revealed a nuanced scenario: we detected a minor but not significant reduction in both PR-SET7 RNA and protein levels (Supplemental Fig.S4 and S5). This outcome stands in stark contrast to the previous study's findings. The discrepancy could be due to the distinct experimental approaches used: the previous research focused on mammalian cells and in vitro experiments, whereas our study examined the functions of PARP-1 in whole Drosophila third-instar larvae during development. Consequently, while PARP-1 may cooperate with PR-SET7 in the context of Drosophila development, it could exhibit antagonistic roles against PR-SET7 in specific cell lines and under certain biological or developmental conditions."

We believe that these modifications effectively address the raised concern and provide a more comprehensive understanding of the relationship between PARP1 and PR-SET7 in our study. We hope these clarifications enhance the overall robustness and clarity of our findings.

Reviewer #2 (Public Review):

Summary:

This study from Bamgbose et al. identifies a new and important interaction between H4K20me and Parp1 that regulates inducible genes during development and heat stress. The authors present convincing experiments that form a mostly complete manuscript that significantly contributes to our understanding of how Parp1 associates with target genes to regulate their expression.

Strengths:

The authors present 3 compelling experiments to support the interaction between Parp1 and H4K20me, including:

(1) PR-Set7 mutants remove all K4K20me and phenocopy Parp mutant developmental arrest and defective heat shock protein induction.

(2) PR-Set7 mutants have dramatically reduced Parp1 association with chromatin and reduced poly-ADP ribosylation.

(3) Parp1 directly binds H4K20me in vitro.

Weaknesses:

(1) The RNAseq analysis of Parp1/PR-Set7 mutants is reasonable, but there is a caveat to the author's conclusion (Line 251): "our results indicate H4K20me1 may be required for PARP-1 binding to preferentially repress metabolic genes and activate genes involved in neuron development at co-enriched genes." An alternative possibility is that many of the gene expression changes are indirect consequences of altered development induced by Parp1 or PR-Set7 mutants. For example, Parp1 could activate a transcription factor that represses metabolic genes. The authors counter this model by stating that Parp1 directly binds to "repressed" metabolic genes. While this argument supports their model, it does not rule out the competing indirect transcription factor model. Therefore, they should still mention the competing model as a possibility.

We appreciate Reviewer 2's insightful comments during both rounds of revision, which have significantly enriched the quality of our manuscript. The binding of PARP1 to loci encoding metabolic genes indeed suggests a direct role of PARP1 in their regulation. However, we acknowledge Reviewer 2's point that some of these targets might be regulated indirectly, with PARP1 potentially modulating the expression of intermediary transcription factors.

To address this possibility, we have revised the discussion section of our manuscript accordingly:

"Remarkably, our observations indicate a notable affinity of PARP-1 for binding to the gene bodies of these metabolic genes (34), suggesting a direct involvement of PARP1 in their regulation. Nonetheless, it remains plausible that certain genes may be indirectly regulated by PARP1 through intermediary transcription factors."

We trust that this modification adequately addresses Reviewer 2's concern.

(2) The section on inducibility of heat shock genes is interesting but missing an important control that might significantly alter the author's conclusions. Hsp23 and Hsp83 (group B genes) are transcribed without heat shock, which likely explains why they have H4K20me without heat shock. The authors made the reasonable hypothesis that this H4K20me would recruit Parp-1 upon heat shock (line 270). However, they observed a decrease of H4K20me upon heat shock, which led them to conclude that "H4K20me may not be necessary for Parp1 binding/activation" (line 275). However, their RNA expression data (Fig4A) argues that both Parp1 and H40K20me are important for activation. An alternative possibility is that group B genes indeed recruit Parp1 (through H4K20me) upon heat shock, but then Parp1 promotes H3/H4 dissociation from group B genes. If Parp1 depletes H4, it will also deplete H4K20me1. To address this possibility, the authors should also do a ChIP for total H4 and plot both the raw signal of H4K20me1 and total H4 as well as the ratio of these signals. The authors could also note that Group A genes may similarly recruit Parp1 and deplete H3/H4 but with different kinetics than Group B genes because their basal state lacks H4K20me/Parp1. To test this possibility, the authors could measure Parp association, H4K20methylation, and H4 depletion at more time points after heat shock at both classes of genes.

We sincerely appreciate Reviewer 2 for their insightful comment on our manuscript. Your hypothesis regarding the potential induction of H3/H4 dissociation from group B genes by PARP-1, leading to a reduction in H4K20me1, offers a thought-provoking perspective. However, our findings suggest an alternative interpretation.

Our data indicate that while H4K20me1 is indeed present under normal conditions at group B genes, its reduction following heat shock does not seem to impede PARP-1's role in transcriptional activation (Fig. 4A, C, and E). Instead, we propose that this decrease in H4K20me1 might signify a regulatory shift in chromatin structure, facilitating transcriptional activation during heat shock, with PARP-1 playing an independent facilitating role. Moreover, existing studies have highlighted the dual role of H4K20me1, acting as a promoter of transcription elongation in certain contexts and as a repressor in others.

The elevated enrichment of H4K20me1 in group B genes under normal conditions may indeed indicate a repressive state that requires alleviation for transcriptional activation. Additionally, we cannot discount the possibility of unique regulatory functions associated with PR-SET7, extending beyond its recognized role as a histone methylase. Non-catalytic activities and potential interactions with non-histone substrates might contribute to the nuanced control exerted by PR-SET7 on group B genes during heat stress.

Furthermore, our exploration of pr-set720 and ParpC03256 mutants reveals distinct roles for PARP-1 and H4K20me1 in modulating gene expression (Fig 3E). This reinforces the notion that the interplay between PR-SET7 and PARP-1 involves a multifaceted regulatory mechanism.

To address these points, we have revised the discussion section of our manuscript accordingly:

"Another plausible explanation could be that the recruitment of PARP-1 to group B genes loci promotes H4 dissociation and then leads to a reduction of H4K20me1. However, our findings suggest an alternative interpretation: the decrease in H4K20me1 at group B genes during heat shock does not seem to impede PARP-1's role in transcriptional activation, (Fig.4A, C and E). Rather than disrupting PARP-1 function, we propose that this reduction in H4K20me1 may signify a regulatory shift in chromatin structure, priming these genes for transcriptional activation during heat shock, with PARP-1 playing an independent facilitating role. Moreover, existing studies have highlighted the dual role of H4K20me1, acting as a promoter of transcription elongation in certain contexts and as a repressor in others (13, 26, 39, 40, 42-46). The elevated enrichment of H4K20me1 in group B genes under normal conditions may indicate a repressive state that requires alleviation for transcriptional activation. Additionally, we cannot discount the possibility of unique regulatory functions associated with PR-SET7, extending beyond its recognized role as a histone methylase. Non-catalytic activities and potential interactions with non-histone substrates might contribute to the nuanced control exerted by PR-SET7 on group B genes during heat stress (47, 48). Furthermore, our exploration of pr-set720 and parp-1C03256 mutants reveals distinct roles for PARP-1 and H4K20me1 in modulating gene expression (Fig 3E). This reinforces the notion that the interplay between PR-SET7 and PARP-1 involves a multifaceted regulatory mechanism. Understanding the intricate relationship between these molecular players is crucial for elucidating the complexities of gene expression modulation under heat stress conditions."

We believe that this modification enhances the clarity of our conclusions and adequately addresses Reviewer 2's concerns regarding the intricate relationship between PARP-1, H4K20me1, and PR-SET7 in transcriptional regulation under heat stress conditions.

eLife assessment

This valuable study presents convincing evidence for an association between PARP-1 and H4K20me1 in transcriptional regulation, supported by biochemical and ChIP-seq analyses. The work contributes significantly to our understanding of how Parp1 associates with target genes to regulate their expression.

Reviewer #2 (Public Review):

Summary:

This study from Bamgbose et al. identifies a new and important interaction between H4K20me and Parp1 that regulates inducible genes during development and heat stress. The authors present convincing experiments that form a mostly complete manuscript that significantly contributes to our understanding of how Parp1 associates with target genes to regulate their expression.

Strengths:

The authors present 3 compelling experiments to support the interaction between Parp1 and H4K20me, including:

(1) PR-Set7 mutants remove all K4K20me and phenocopy Parp mutant developmental arrest and defective heat shock protein induction.

(2) PR-Set7 mutants have dramatically reduced Parp1 association with chromatin and reduced poly-ADP ribosylation.

(3) Parp1 directly binds H4K20me in vitro.

: 聽說了嗎？那家公司被指控做Uncook the books。 : 真的嗎？這太糟糕了，他們的信譽會受到很大損害。 《Uncook the book(s)》 是「作假帳」，這裡的the book(s)指的是帳本而非書本。做假帳就是在原本帳目上做點手腳，好像煮飯菜的時候要一點想像力，加一些調味料，因此cook the book(s)就是所謂的作假帳。 【範例】 ★He lives his life uncooking the books for criminal organizations. 他專門幫犯罪組織查假帳，並靠此維生。 ★The company was accused of uncooking the books. 那家公司被指控做假帳。

It can't be true that "cook the book" and "UNcook the book" both mean 作假帳.

The mention of the No Child Left Behind Act in 2002 underscores the ongoing national concern about closing achievement gaps, particularly among minority and non-minority students. This legislative focus highlights the persistent importance and urgency of addressing educational disparities on a broad scale.

This paragraph introduces an interesting exploration of academic achievement gaps at Alhambra High School through the perspective of student Robin Zhou. It raises thought-provoking questions about the underlying reasons behind disparities among student groups and highlights cultural perceptions and parental influences on academic performance.

This passage captivates me due to its exploration of the internalization and questioning of the “Asian” cultural script within education. Both Gary Wong and Paul Pham’s experiences highlight a complex interaction between cultural expectations and individual experiences in academic achievement. It’s enlightening to see examples of Asian Americans who recognize and deviate from the stereotypical educational pressures often associated with their communities. This deviation challenges the monolithic view of Asian American educational values and shows the diversity of experiences and expectations within the community.

The discussion around the model minority stereotype and its implications for Asian American students at Alhambra High is deeply engaging because it exposes how cultural stereotypes can shape educational expectations and experiences. It resonates with me as it highlights the pressure and unrealistic standards that can arise from essentializing cultural traits, such as hard work and academic excellence, to an entire ethnic group. This reinforces the need for a more nuanced understanding of individual and community dynamics that go beyond simplistic and often harmful stereotypes.

The discussion on the racialization of academic achievement, especially in light of historical and ongoing legislative efforts like the No Child Left Behind Act, strikes a chord with me because it underscores the complexity of addressing educational disparities. The fact that older racial biases are often veiled under cultural explanations today highlights the subtle ways systemic racism perpetuates. This prompts me to think critically about how societal structures shape educational outcomes and the importance of addressing these issues from a systemic rather than an individualistic perspective. It’s essential to explore more profound, structural changes that go beyond mere symptom treatment.

The transition from ethnically mixed groups in junior high to more racially homogeneous groups in high school at Alhambra highlights a troubling yet significant trend in educational environments. The divide becomes particularly stark with the separation into different academic tracks, exacerbating the racialized “achievement gap.” This segregation in schooling interests me because it reflects broader societal issues and challenges the ideal of educational equity. It is concerning how institutional structures, such as tracking, can reinforce and perpetuate these divisions, impacting students’ academic and social lives.

The dynamic at Alhambra High, as described by Nancy and Paul, where ethnic identity deeply influences social categorization and interaction, provides a clear example of how racial and ethnic perceptions shape student experiences in diverse settings. This portrayal is intriguing because it reveals the nuanced ways students navigate their identities in a predominantly Asian and Latina/o environment, challenging the simplistic racial binaries often prevalent in less diverse areas. It emphasizes the complexity of identity in multicultural settings and the role of schools as spaces where these identities are continuously negotiated and redefined.

This passage captivates me with its deep dive into the complex role schools play in shaping societal norms and structures. It emphasizes how schools not only reflect but actively construct social realities, perpetuating hierarchies under the guise of neutrality. The idea that schools are arenas for both maintaining and challenging societal norms is particularly compelling, illustrating the dual role of education as both a tool for social reproduction and a potential catalyst for change. This dual role suggests that while schools can reinforce inequalities, they also hold the power to dismantle them, making education a critical field for social justice efforts.

The incident at Alhambra High, spurred by Robin’s column, caught my attention because it highlights the powerful role schools play in reflecting and challenging societal norms, particularly around issues of race and achievement. The controversy not only exposed underlying racial tensions but also prompted a broader conversation about equality, meritocracy, and the complex ways in which race influences educational outcomes. It is a vivid example of how educational settings can become battlegrounds for larger societal debates, revealing the deep-seated ideologies that shape our understanding of race and success.

The passage reflects on the profound role schools play in shaping societal norms under the guise of neutrality, which intrigues me due to the dual nature of educational institutions as both upholders and challengers of societal structures. Schools not only propagate certain social and racial orders but also provide a platform for challenging these hegemonies. This perspective is vital as it prompts a deeper examination of educational practices and their impact on societal inequalities. It emphasizes the need for critical awareness in educational settings to foster a more equitable society.

This is insanity; to say turtl is the only 'content creation platform' that's 'backed by data' is complete hogwash.

This is marketing fluff at its worst: a lie.

This is marketing fluff and hyperbole; I'll believe this claim when I see proof that they've examined every single 'content creation platform'.

For example, Microsoft Office apps could be considered part of a 'content creation platform'. They're partly built via UX research and feedback via people who are trained in psychology. This simple fact shows turtl as unreliable.

Van Ausdale and Feagin's research highlights how children absorb and reflect adult racial biases, using stereotypes to navigate social interactions and enhance their status among peers.

This is so terrible. No one should be attack by no reason. Leave education on the side, discrimination to any people should be shameful

The descriptions of how racial harassment is often met with silence and the inadequate responses from educational systems are particularly striking. This resonates with me because it underscores the pervasive nature of racial discrimination and the complicity of silence in perpetuating oppression. Josh’s and his sister’s reactions, along with the historical context of African Americans being taught to suppress their reactions to racism, highlight a harmful cycle where non-confrontation leads to unresolved trauma and mental health issues. It’s disheartening to see that despite more attention to mental health in schools, there remains a significant gap in culturally competent counseling.

The passage discussing Eve’s school experiences as a multiethnic individual caught my attention due to its nuanced depiction of identity and isolation in predominantly white educational settings. It illustrates the complexity of racial identity and how individuals often internalize societal perceptions, attributing social difficulties to personal quirks rather than racial dynamics. This reflection deepens my understanding of the subtle ways racism can manifest and influence self-perception, highlighting the importance of addressing racial issues openly in educational environments to foster a more inclusive atmosphere.

This passage sheds light on the dual-edged sword of the model minority stereotype and its impact on Asian American students. It piques my interest because it reveals how positive stereotypes can mask the underlying racial discrimination and social isolation experienced by Asian American students. The narrative challenges the notion that racial teasing is just a part of growing up, emphasizing its damaging effect on students’ social interactions and self-perception. This discourse prompts me to reflect on the deeper societal changes needed to address such ingrained prejudices in educational institutions.

The incident at South Philadelphia High School, where Asian American students were targeted and bullied, is deeply troubling and highlights systemic racism’s pervasive influence in educational settings. It underscores the urgent need for schools to understand and actively address the dynamics of racial tensions. The media’s failure to delve into how the “model minority” stereotype may have contributed to misunderstandings and hostility in this environment is particularly disconcerting. This situation reminds us that stereotypes can have dangerous implications and stresses the importance of fostering a culturally aware and inclusive school climate.

This is true.

eLife assessment

Using new cannabinoid receptor (CNR1 and CNR2) knockout mouse models, this important paper shows how dysregulation of the endocannabinoid system is involved in endometriosis progression. The transcriptomic evidence is solid, but a major limitation of the work is the absence of detailed measurements of lesion size and burden by histopathology.

Reviewer #1 (Public Review):

Summary:

The endocannabinoid system (ECS) components are dysregulated within the lesion microenvironment and systemic circulation of endometriosis patients. Using endometriosis mouse models and genetic loss of function approaches, Lingegowda et al. report that canonical ECS receptors, CNR1 and CNR2, are required for disease initiation, progression, and T-cell dysfunction.

Strengths:

The approach uses genetic approaches to establish in vivo causal relationships between dysregulated ECS and endometriosis pathogenesis. The experimental design incorporates bulk RNAseq approaches, as well as imaging mass spectrometry to characterize the mouse lesions. The identification of immune-related and T-cell-specific changes in the lesion microenvironment of CNR1 and CNR2 knockout (KO) mice represents a significant advance

Weaknesses:

Although the mouse phenotypic analyses involve a detailed molecular characterization of the lesion microenvironment using genomic approaches, detailed measurements of lesion size/burden and histopathology would provide a better understanding of how CNR1 or CNR2 loss contributes to endometriosis initiation and progression. The cell or tissue-specific effects of the CNR1 and CNR2 are not incorporated into the experimental design of the studies. Although this aspect of the approach is recognized as a major limitation, global CNR1 and CNR2 KO may affect normal female reproductive tract function, ovarian steroid hormone levels, decidualization response, or lead to preexisting alterations in host or donor tissues, which could affect lesion establishment and development in the surgically induced, syngeneic mouse model of endometriosis.

Reviewer #2 (Public Review):

Summary:

The endocannabinoid system (ECS) regulates many critical functions, including reproductive function. Recent evidence indicates that dysregulated ECS contributes to endometriosis pathophysiology and the microenvironment. Therefore, the authors further examined the dysregulated ECS and its mechanisms in endometriosis lesion establishment and progression using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. The authors presented differential gene expressions and altered pathways, especially those related to the adaptive immune response in CNR1 and CNR2 ko lesions. Interstingly, the T-cell population was dramatically reduced in the peritoneal cavity lacking CNR2, and the loss of proliferative activity of CD4+ T helper cells. Imaging mass cytometry analysis provided spatial profiling of cell populations and potential relationships among immune cells and other cell types. This study provided fundamental knowledge of the endocannabinoid system in endometriosis pathophysiology.

Strengths:

Dysregulated ECS and its mechanisms in endometriosis pathogenesis were assessed using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. Not only endometriotic lesions, but also peritoneal exudate (and splenic) cells were analyzed to understand the specific local disease environment under the dysregulated ECS.

Providing the results of transcriptional profiles and pathways, immune cell profiles, and spatial profiles of cell populations support altered immune cell population and their disrupted functions in endometriosis pathogenesis via dysregulation of ECS.

In line 386: Role of CNR2 in T cells. The finding that nearly absent CD3+ T cells in the peritoneal cavity of CNR2 ko mice is intriguing.

The interpretation of the results is well-described in the Discussion.

Weaknesses:

The study was terminated and characterized 7 days after EM induction surgery without the details for selecting the time point to perform the experiments.

The authors also mentioned that altered eutopic endometrium contributes to the establishment and progression of endometriosis. This reviewer agrees with lines 324-325. If so, DEGs are likely identified between eutopic endometrium (with/without endometriosis lesion induction) and ectopic lesions. It would be nice to see the data (even though using publicly available data sets).

Figure 7 CDEF. The results of the statistical analyses and analyzed sample numbers should be added. Lines 444-450 cannot be reviewed without them.

This reviewer agrees with lines 498-500. In contrast, retrograded menstrual debris is not decidualized. The section could be modified to avoid misunderstanding.

Author response:

Reviewer #1 (Public Review):

Summary:

The endocannabinoid system (ECS) components are dysregulated within the lesion microenvironment and systemic circulation of endometriosis patients. Using endometriosis mouse models and genetic loss of function approaches, Lingegowda et al. report that canonical ECS receptors, CNR1 and CNR2, are required for disease initiation, progression, and T-cell dysfunction.

Strengths:

The approach uses genetic approaches to establish in vivo causal relationships between dysregulated ECS and endometriosis pathogenesis. The experimental design incorporates bulk RNAseq approaches, as well as imaging mass spectrometry to characterize the mouse lesions. The identification of immune-related and T-cell-specific changes in the lesion microenvironment of CNR1 and CNR2 knockout (KO) mice represents a significant advance

Weaknesses:

Although the mouse phenotypic analyses involve a detailed molecular characterization of the lesion microenvironment using genomic approaches, detailed measurements of lesion size/burden and histopathology would provide a better understanding of how CNR1 or CNR2 loss contributes to endometriosis initiation and progression. The cell or tissue-specific effects of the CNR1 and CNR2 are not incorporated into the experimental design of the studies. Although this aspect of the approach is recognized as a major limitation, global CNR1 and CNR2 KO may affect normal female reproductive tract function, ovarian steroid hormone levels, decidualization response, or lead to preexisting alterations in host or donor tissues, which could affect lesion establishment and development in the surgically induced, syngeneic mouse model of endometriosis.

We appreciate the reviewer's thoughtful and constructive feedback. We agree that the additional measurements of lesion size/burden and histopathology would provide valuable insights into the specific contributions of CNR1 and CNR2 to endometriosis progression. However, the focus of this study was on assessing the alterations in complex immune microenvironment due to the absence of CNR1 and CNR2, given their close relation in regulating immune cell populations. We will plan to incorporate these measurements in future studies to further strengthen the understanding of the disease pathogenesis. Regarding the potential effects of global knockout, the reviewer raises a valid concern. To address this, we will explore cell and/or tissue-specific knockout models in future experiments to better isolate the direct effects of CNR1 and CNR2 on the disease process, while minimizing potential confounding factors from systemic alterations.

Reviewer #2 (Public Review):

Summary:

The endocannabinoid system (ECS) regulates many critical functions, including reproductive function. Recent evidence indicates that dysregulated ECS contributes to endometriosis pathophysiology and the microenvironment. Therefore, the authors further examined the dysregulated ECS and its mechanisms in endometriosis lesion establishment and progression using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. The authors presented differential gene expressions and altered pathways, especially those related to the adaptive immune response in CNR1 and CNR2 ko lesions. Interestingly, the T-cell population was dramatically reduced in the peritoneal cavity lacking CNR2, and the loss of proliferative activity of CD4+ T helper cells. Imaging mass cytometry analysis provided spatial profiling of cell populations and potential relationships among immune cells and other cell types. This study provided fundamental knowledge of the endocannabinoid system in endometriosis pathophysiology.

Strengths:

Dysregulated ECS and its mechanisms in endometriosis pathogenesis were assessed using two different endometrial sources of mouse models of endometriosis with CNR1 and CNR2 knockout mice. Not only endometriotic lesions, but also peritoneal exudate (and splenic) cells were analyzed to understand the specific local disease environment under the dysregulated ECS.

Providing the results of transcriptional profiles and pathways, immune cell profiles, and spatial profiles of cell populations support altered immune cell population and their disrupted functions in endometriosis pathogenesis via dysregulation of ECS.

In line 386: Role of CNR2 in T cells. The finding that nearly absent CD3+ T cells in the peritoneal cavity of CNR2 ko mice is intriguing.

The interpretation of the results is well-described in the Discussion.

Weaknesses:

The study was terminated and characterized 7 days after EM induction surgery without the details for selecting the time point to perform the experiments.

The authors also mentioned that altered eutopic endometrium contributes to the establishment and progression of endometriosis. This reviewer agrees with lines 324-325. If so, DEGs are likely identified between eutopic endometrium (with/without endometriosis lesion induction) and ectopic lesions. It would be nice to see the data (even though using publicly available data sets).

Figure 7 CDEF. The results of the statistical analyses and analyzed sample numbers should be added. Lines 444-450 cannot be reviewed without them.

This reviewer agrees with lines 498-500. In contrast, retrograded menstrual debris is not decidualized. The section could be modified to avoid misunderstanding.

We would like to thank the reviewer for insightful comments, suggestions and acknowledging the importance of the work presented in this manuscript.

Regarding 7-day time point, we have provided rationale in lines 479-481, but agree that it isn’t sufficient and hence we have provided additional details on the selection of the 7-day time point for the experiments in methods section (Mouse model of EM). We have also noted the suggestion on providing comparison of differentially expressed genes in the eutopic endometrium vs ectopic lesions. Since there are publications comparing the eutopic vs ectopic gene expression patterns (PMIDs: 33868805 and 18818281), including a study exploring the ECS genes in the endometrium throughout different menstrual cycles (PMID: 35672435), we believe additional analysis using the same dataset may not yield new information. However, we see the value in reviewer’s comment, and we will look at the gene expression patterns in the uterine vs endometriosis like lesions in our future studies with tissue or cell specific CNR1 and CNR2 knockout models to understand functional relevance of ECS in endometriosis initiation.

Since the IMC study was exploratory for proof of concept, we did not have enough biological replicates for meaningful statistical validation (n = 2-3). We have clarified this information in the methods, results, and figure legends for appropriately representing the limitations of the current setup.

Finally, we appreciate the feedback on the section discussing retrograded menstrual debris. Even though the menstrual debris may not be decidualized, some endometriotic lesions have the ability to decidualize based on their response to estrogen and progesterone in a cycling manner (PMID: 26450609), similar to the endometrium in the uterine cavity. We have clarified this in the revised MS.

This seems like unrelated to the education topic, but I can feel the panic. I'm really wondering what is going on and how could it lead to the Asian American oppression. It's a very interesting beginning

Perhaps you should also begin with something about "Structure and semantics". See Simon Mellins article about accessibility and publishing and some of the possible approaches to AI being made by the publishing industry.

Author response:

We kindly thank the senior editor, the reviewing editor, and the esteemed reviewers for their invaluable insights in enhancing our manuscript. The assessment and feedback, particularly on the role of directly released bacterial ATP versus OMV-delivered bacterial ATP and its role on neutrophils, addressing study limitations, and discussing our models is highly appreciated.

The points you raised let us critically rethink our approach, our results, and our conclusions. Furthermore, it gave us the chance to elaborate on some critical aspects that you mentioned. With your help, we will make clarifications throughout the manuscript, and we will add the data about neutrophil numbers in the different organs (reviewer #1, weaknesses #3).

eLife assessment

This fundamental study advances our understanding of the role of bacterial derived extracellular ATP in the pathogenesis of sepsis. The evidence supporting the conclusions is solid, particularly with the analysis of E. coli mutants to address different aspects of bacterial release of ATP. The work will be of broad interest to researchers on microbiology and infectious diseases.

Reviewer #1 (Public Review):

Summary:

Extracellular ATP represents a danger-associated molecular pattern associated to tissue damage and can act also in an autocrine fashion in macrophages to promote proinflammatory responses, as observed in a previous paper by the authors in abdominal sepsis. The present study addresses an important aspect possibly conditioning the outcome of sepsis that is the release of ATP by bacteria. The authors show that sepsis-associated bacteria do in fact release ATP in a growth dependent and strain-specific manner. However, whether this bacterial derived ATP play a role in the pathogenesis of abdominal sepsis has not been determined. To address this question, a number of mutant strains of E. coli has been used first to correlate bacterial ATP release with growth and then, with outer membrane integrity and bacterial death. By using E. coli transformants expressing the ATP-degrading enzyme apyrase in the periplasmic space, the paper nicely shows that abdominal sepsis by these transformants results in significantly improved survival. This effect was associated with a reduction of peritoneal macrophages and CX3CR1+ monocytes, and an increase in neutrophils. To extrapolate the function of bacterial ATP from the systemic response to microorganisms, the authors exploited bacterial OMVs either loaded or not with ATP to investigate the systemic effects devoid of living microorganisms. This approach showed that ATP-loaded OMVs induced degranulation of neutrophils after lysosomal uptake, suggesting that this mechanism could contribute to sepsis severity.

Strengths:

A strong part of the study is the analysis of E. coli mutants to address different aspects of bacterial release of ATP that could be relevant during systemic dissemination of bacteria in the host.

Weaknesses:

As pointed out in the limitations of the study whether ATP-loaded OMVs provide a mechanistic proof of the pathogenetic role of bacteria-derived ATP independently of live microorganisms in sepsis is interesting but not definitively convincing. It could be useful to see whether degranulation of neutrophils is differentially induced by apyrase-expressing vs control E. coli transformants. Also, the increase of neutrophils in bacterial ATP-depleted abdominal sepsis, which has better outcomes than "ATP-proficient" sepsis, seems difficult to correlate to the hypothesized tissue damage induced by ATP delivered via non-infectious OMVs. Are the neutrophils counts affected by ATP delivered via OMVs? A comparison of cytokine profiles in the abdominal fluids of E. coli and OMV treated animals could be helpful in defining the different responses induced by OMV-delivered vs bacterial-released ATP. The analyses performed on OMV treated versus E. coli infected mice are not closely related and difficult to combine when trying to draw a hypothesis for bacterial ATP in sepsis. Also it was not clear why lung neutrophils were used for the RNAseq data generation and analysis.

Reviewer #2 (Public Review):

Summary:

In their manuscript "Released Bacterial ATP Shapes Local and Systemic Inflammation during Abdominal Sepsis", Daniel Spari et al. explored the dual role of ATP in exacerbating sepsis, revealing that ATP from both host and bacteria significantly impacts immune responses and disease progression.

Strengths:<br /> The study meticulously examines the complex relationship between ATP release and bacterial growth, membrane integrity, and how bacterial ATP potentially dampens inflammatory responses, thereby impairing survival in sepsis models. Additionally, this compelling paper implies a concept that bacterial OMVs act as vehicles for the systemic distribution of ATP, influencing neutrophil activity and exacerbating sepsis severity.

Weaknesses:

(1) The researchers extracted and cultivated abdominal fluid on LB agar plates, then randomly picked 25 colonies for analysis. However, they did not conduct 16S rRNA gene amplicon sequencing on the fluid itself. It is worth noting that the bacterial species present may vary depending on the individual patients. It would be beneficial if the authors could specify whether they've verified the existence of unculturable species capable of secreting high levels of Extracellular ATP.

(2) Do mice lacking commensal bacteria show a lack of extracellular ATP following cecal ligation puncture?

(3) The authors isolated various bacteria from abdominal fluid, encompassing both Gram-negative and Gram-positive types. Nevertheless, their emphasis appeared to be primarily on the Gram-negative E. coli. It would be beneficial to ascertain whether the mechanisms of Extracellular ATP release differ between Gram-positive and Gram-negative bacteria. This is particularly relevant given that the Gram-positive bacterium E. faecalis, also isolated from the abdominal fluid, is recognized for its propensity to release substantial amounts of Extracellular ATP.

(4) The authors observed changes in the levels of LPM, SPM, and neutrophils in vivo. However, it remains uncertain whether the proliferation or migration of these cells is modulated or inhibited by ATP receptors like P2Y receptors. This aspect requires further investigation to establish a convincing connection.

(5) Additionally, is it possible that the observed in vivo changes could be triggered by bacterial components other than Extracellular ATP? In this research field, a comprehensive collection of inhibitors is available, so it is desirable to utilize them to demonstrate clearer results.

(6) Have the authors considered the role of host-derived Extracellular ATP in the context of inflammation?

(7) The authors mention that Extracellular ATP is rapidly hydrolyzed by ectonucleotases in vivo. Are the changes of immune cells within the peritoneal cavity caused by Extracellular ATP released from bacterial death or by OMVs?

(8) In the manuscript, the sample size (n) for the data consistently remains at 2. I would suggest expanding the sample size to enhance the robustness and rigor of the results.

Legal certainty usually means, for individuals to be able to foresee any legal consequences of their actions Contains certain subprincipals: 1. Clarity of law - law needs to be clear and understandable and simple, however, sometimes complex provisions are necessary to clear up grey areas

1. Constancy of the law, should not change too often

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Reply to the reviewers

__Below is our point-by-point reply to the reviewer's comments __

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

PNKP is one of critical end-processing enzymes for DNA damage repair, mainly base excision & single strand break repair, and double strand break repair to a certain extent. This protein has dual enzyme function: 3' phosphatase and 5' kinase to make DNA ends proper for ligation. It has been demonstrated that PTM of PNKP (e.g., S114, S126), particularly phosphorylation by either ATM or DNAPK, is important for PNKP function in DNA damage repair. The authors found a new phosphorylation site, T118, of PNKP which might be modified by CDK1 or 2 during S phase. This modification of phosphorylation is involved in maintenance and stability of the lagging strand, particularly Okazaki fragments. Loss of this phosphorylation could result in increased single strand gaps, accelerated speed of fork progression, and eventually genomic instability. And for this process, PNKP enzyme activity is not that important. And the authors concluded that PNKP T118 phosphorylation is important for lagging strand stability and DNA damage repair.

Major comments

In general, enzymes have protein interactions with its/their substrates. If PNKP is phosphorylated by either/both CDK1/2, the protein interaction between these would be expected. However, the authors did not provide any protein interactions in PNKP and CDKs. *Thank you for your suggestion. We will perform GFP-pulldown assays using cell extracts from HEK293 cells expressing GFP-WT-PNKP, GFP-T118A-PNKP. And then to confirm the interaction of PNKP and CDK1/2, we will blot with CDK1 and CDK2 antibodies. *

It is not clear how T118 phosphorylation is involved in DNA damage repair itself as the authors suggested. The data presenting the involvement of T118 phosphorylation in this mechanism are limited. This claim opens more questions than answers. CDK1/2 still phosphorylates T118 in this DNA damage repair process? What would happen to DNA damage repair in which PNKP involves outside of S phase in terms of T118 phosphorylation?

Thank you for your comment. We have investigated how T118 phosphorylation is important in DNA damage repair by several experiments. In figure S8, we tested SSB and DSB repair abilities of PNKP KO cells expressing PNKP T118A mutant, in which PNKP T118 phosphorylation has critical roles in both SSB and DSB repair pathways. Interestingly, the result of SSB repair assay (figure S8A & B) may indirectly indicate that T118 phosphorylation is important for SSB repair throughout cell cycle as these SSBs are instantly induced by IR exposure and recovered only for 30 mins that is presumably not enough time for cells to go through cell cycle. Along with the repair abilities, we also analyzed a recruitment kinetics/ability to DNA damage in PNKP T118A and T118D mutants using laser micro-irradiation assay in figure S9. This result indicates that the phosphorylation of PNKP at T118 is controlling its recruitment to at least laser-induced DNA damage sites. Moreover, we have analyzed recruitment of PNKP to a single-strand DNA gap structure, which mimics intermediates of some DNA repair pathways and incomplete Okazaki fragment maturation, using cell extracts from PNKP KO cells expressing PNKP T118A and T118D mutants and biochemical assay in figure 4H. This assay is much cleaner and shows that loss of T118 phosphorylation impairs PNKP recruitment to the ssDNA gap structure. We believe that these data sufficiently support our model that the phosphorylation of T118 on PNKP is involved in DNA repair in general. However, we agree with that we have not yet directly tested DNA repair ability of PNKP T118A in outside of S-phase. Therefore, in addition to these data, we will perform H2O2-induced SSB and IR-induced DSB repair assay using EdU (S phase) pulse labelling in PNKP KO cells expressing PNKP T118A mutant, then we will measure the ADP-ribose intensity and pH2AX foci in EdU negative cells (outside of S phase as the reviewer suggested).

Along the same line with #1/2 comments, the recruitment of PNKP to the damage sites is XRCC1 dependent. Is not clear whether PNKP recruitment to gaps on the lagging strand is XRCC1 independent or dependent. It might be interesting to examine (OPTIONAL)

*Thank you for an important suggestion. XRCC1 acts as a scaffold of PNKP and is required for recruitment of PNKP for canonical SSB repair, although we propose that PNKP is involved in two pathways in DNA replication: PARP1-XRCC1-dependent ssDNA gap filling pathway and Okazaki fragment maturation pathway working with FEN1. It is still important to address how XRCC1 is required for PNKP recruitment to the single-strand gaps on nascent DNA. Therefore, we will perform iPOND analysis in XRCC1 knock down + GFP-WT-PNKP expressed HEK293 cells. *

Minor comments

In results: 'Generation of PNKP knock out U2OS cell line' - In figure S2A; There are no data regarding diminishing the phosphorylation of g-H2AX.

Thank you for your suggestion. We will add pH2AX blot data in fig S2A (all reviewers requested).

• By showing data in figure S2B/C/D/E, the authors describe 'PNKP KO cells impaired the SSBs repair activity'. However, as the authors mentioned in this manuscript, PNKP could bind to either XRCC1 or XRCC4. Also for this experiment, IR had been applied, which induces DNA double strand breaks. Therefore, it is not certain that the authors' description is fully supported by these data presented. Perhaps, SSB inducing reagents should be used instead of IR.

In figure S2B/C/D/E, we used gamma-ray as IR source, which classified as low energy transfer irradiation. which mainly act as indirect effect to the DNA. It is estimated gamma-ray induce DNA damage as 60-80% SSBs and 20-40 % DSBs. We believe our results are reasonable. In addition to these results, we will perform poly-ADP-ribose assay with H2O2 treatment to more specifically assess SSBs repair activity.

• Is there any FACS analysis data to support the description of the last sentence 'especially the phosphorylation of PNKP T118, is required for S phase progression and proper cell proliferation'?

Thank you for your suggestion. We will add the FACS analysis data of cell cycle profiles in PNKP KO cells expressing GFP, GFP-PNKP WT, T118A.

In results: 'CDKs phosphorylate T118 of PNKP ~~~ replication forks'

• In figure 3A, Is there any change in total PNKP (both GFP-tagged & endogenous) level?

*Thank you for your suggestion. We agree with your comment. We will add the PNKP expression analysis in different cell cycle population in asynchronized and synchronized cells (G1, S, G2/M samples). *

In results: 'Phosphorylation of PNKP at T118 ~~~ between Okazaki fragments'

• In figure 4D, What happens in the ADP-ribose level, when T118D PNKP is expressed?

*Thank you for your suggestion. This is interesting question. We will perform ADP-ribosylation assay in PNKP KO cells and PNKP KO cells expressing PNKP WT and T118D, and add data of ADP-ribose levels in those cells. *

In results: 'PNKP is involved in postreplicative single-strand DNA gap-filling pathway'

• The description regarding data presented in figure 6 is not clear enough. These data might suggest that wildtype U2OS does not have SSB which is a substrate for S1 nuclease (except under FEN1i and PARPi treatment), whereas PNKP KO has SSB during both IdU and CIdU incorporation, so that S1 nuclease treatment dramatically reduces the speed of fork formation in PNKP KO cells. Also In figure 6B/C/D, adding an experimental group of PNKP KO with S1 nuclease + PARPi might help to understand the role of PNKP during replication better. Also these additional data could support the description in discussion 'Furthermore, PNKP is required for the PARP1-dependent single-strand gap-filling pathway ~~~ DNA gap structure'.

• *

*We agree with reviewer's comment and suggestion. Since this point is also raised by reviewer 3, we will add the rationale of the experiment and more detailed description about the results, which would substantially improve this manuscript. We will also revise our representation in text followed by the comment. In addition to revising the text, we will add experiment groups of PNKP KO with S1 nuclease with/without PARPi as the reviewer suggested. *

In results: 'Phosphorylation of PNKP at T118 is essential for genome stability'

• In figure S8C, Did you measure g-H2AX foci disappearance for later time point, such as 24 hrs after DNA damage? Is not clear whether non-phosphorylated PNKP at T118 inhibit DNA damage repair or make it slower? How does T114A-PNKP behave in this experimental condition? T114 is well known target of ATM/DNAPK for DDR & DSB repair.

Thank you for your suggestion. We agree with your point. It is very important to analyze whether T118A mutant shows delayed or total loss of DSB repair ability. We will add the measurement of pH2AX foci at 24 hrs after IR in PNKP KO cells expressing GFP, WT-PNKP, T118A-PNKP. Although the analysis of pS114 PNKP is previously reported (Segal-Raz et al., EMBO reports, 2011 and Zolner et al., Nucleic Acids Research, 2011), we will also perform pH2AX assay in PNKP KO cells expressing S114A-PNKP as a control.

The result shown in figure S9 should be described in the result section, not in the discussion section.

Thank you for your suggestion. This is a point also raised by Reviewer 3. Since we are going to re-consider the layout of the manuscript upon the planned revision (as reviewer 3 suggested), we will move these points to the appropriate result section from the discussion.

**Referees cross-commenting**

I could see a similar degree of positive tendency toward the manuscript. I agree with the comments and suggestions in additional experiments made by reviewers 2 and 3. Those suggestions will improve an impact of the manuscript in the DNA damage repair field.

Reviewer #1 (Significance (Required)):

Significance

The authors discovered new phosphorylation site (T118) of PNKP which is an important DNA repair protein. This modification seems to play a role in maintenance of the lagging strand stability in S phase. This discovery is something positive in DNA repair field to expand the canonical and non-canonical functions of DNA repair factors.

The data presented to support PNKP functions and T118 phosphorylation in S phase seem solid in general, yet it is not sure how much PNKP is critical in the Okazaki fragment maturation process which is known that several end processing enzymes (like FEN1, EXO1, DNA2 etc which leave clean DNA ends.) are involved.

These finding might draw good attentions from researchers interested broadly in cell cycle, DNA damage repair, replication, and possibly new tumor treatment.

My field and research interest: DNA damage response (including cell cycle arrest and programmed cell death), DNA damage repair (including BER, SSBR, DSBR)

Thank you very much for your positive comment. As you mentioned, there are several other end processing enzymes that seem to be involved in Okazaki fragment maturation, however, none of those enzymes is reported as a protein involved in the gap-filling pathway as well. Therefore, the role(s) of PNKP in DNA replication are very outstanding as PNKP could be involved in two separate pathways, Okazaki fragment maturation and a back-up gap-filling repair process. As you suggested, we will add several experiments such as iPOND experiments using XRCC1-depleted cells, analysis of DNA repair ability of PNKP T118A mutant throughout cell cycle and S1 nuclease DNA fiber assays in PNKP KO cells with/without PARP inhibitor treatment, to reveal how much PNKP is critical in the Okazaki fragment maturation. We believe that performing those experiments makes the conclusion and this manuscript more solid and convincing.

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

Polynucleotide kinase phosphatase (PNPK) participates in multiple DNA repair processes, where it acts on DNA breaks to generate 5'-phosphate and 3'-OH ends, facilitating the downstream activities of DNA ligases or polymerases.

This manuscript identifies a CDK-dependent phosphorylation site on threonine 118 in PNKP's linker region. The authors provide some convincing evidence that this modification is important to direct the activity of PNPK towards ssDNA gaps between Okazaki fragments during DNA replication. The authors monitored protein expression levels, enzymatic activity, the growth rate and replication fork speed, as well as the presence of ssDNA damage to make a comprehensive overview of the features of PNKP necessary for its function.

Overall, the conclusions are sufficiently supported by the results and this manuscript is relevant and of general interest to the DNA repair and genome stability fields. Some level of revision to the experimental data and text would help strengthen its message and conclusions.

Major points:

In an iPOND experiment the authors detect the wt PNKP and the T118 phosphorylated form at the forks and conclude that this phosphorylation promotes interaction with nascent DNA (Figure 3E). An informative sample to include here would have been the T118A mutant. Based on the model proposed, the prediction would be that it would not be associated with the forks, or at least, associated at reduced levels compared to the wt. *Thank you for your suggestion. We agree with your comment. We will add the iPOND analysis in PNKP KO cells expressing T118A mutant to confirm that pT118 is important for recruitment of PNKP at nascent DNA. *

The quality of the gels showing the phosphatase and kinase assays in Figure 5 could be improved to facilitate quantification of the results. The gel showing the phosphatase activity has a deformed band corresponding to K378A mutant. The gel showing the kinase activity seems to be hitting the detection limits, and the overall high background might influence the quantification of D171A mutant in the area of interest. The authors should provide a better quality of these gels, focusing on better separation (running them longer, eventually with a slightly increased electric current) and higher signal of the analyzed bands (longer incubation phosphatase/kinase prior to quenching or loading higher amount of DNA).

We agree with your suggestion. This phosphatase and kinase assay could be improved. We will perform this assay again followed by reviewer's suggestions.

The authors sometimes make statements like: "a slight increase, slightly increased, relatively high" without an evaluation of the statistical significance for the presented data. An example of such a statement is: "T118A mutant-expressing cells exhibited a marked delay in cell growth, which was not observed for S114A, although T122A, S126A, and S143A were slightly delayed," based on the figure 2E. A similar comment applies also to figures 4A, 5A, 5E. Whenever possible, the authors should include also an evaluation of the statistical significance in the statement.

Thank you for your suggestion. We will check manuscript and revise representation as reviewer's suggestion.

Minor revisions:

I could not find a gH2AX blot for figure S2A.

Thank you for your suggestion. We will add pH2AX blot data in fig S2A.

The authors established two PNKP-/- clones and supported it with sequencing and several functional observations However, the C-terminal antibody appears to detect lower-intensity bands (Figure 1A). Can authors comment on those bands?

Thank you for your comment. One possibility of this band is artificially recognized bands. To improve this problem, we will try electrophoresis for longer time to separate this band.

Why the S1 nuclease data on DNA fibers do not show the same level of epistasis with the Fen1i, as do those on ADP-ribosylation?

Because FEN1 dependent Okazaki fragment maturation and PARP1-XRCC1 dependent gap-filling pathway are different pathways, FEN1i and PARPi treatment resulted in an additive effect in S1 nuclease data in PNKP WT cells. To facilitate better understanding, we will add graphical scheme in figure 6 (a similar problem was raised by Reviewer 3 below) and revise the description of the result.

**Referees cross-commenting**

I agree with all the comments from the reviewers 1 and 3.

Reviewer #2 (Significance (Required)):

Significance:

The manuscript identifies a CDK phosphorylation site in a relevant DNA repair protein. The experiments on this part are elegant and convincing. It seems that this phosphorylation is important during DNA replication and there is some supporting evidence in this point, although not as robust, meaning that it is not clear whether this phosphorylation is controlling specifically the recruitment to Okazaki fragments, or a general role in DNA repair. Maybe if they see a reduced recruitment of the T118A mutant to the forks (iPOND experiment) this would further increase the impact.

This work will be relevant to the basic research, especially in the fields of DNA repair and DNA replication.

My expertise: DNA replication, genome stability, telomere biology.

Thank you very much for your positive comment. As you suggested, we will perform an iPOND assay using PNKP T118A mutant. In addition of the T118A iPOND assay, we will also analyze the DNA repair function of PNKP T118A mutant throughout cell cycle as reviewer 1 suggested. We believe that results of these experiments will pin down whether the phosphorylation of PNKP on T118 is controlling its recruitment to Okazaki fragments specifically or single-strand DNA gaps in general, and solidify the conclusion of the manuscript.

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

Tsukada and colleagues studied the role of PNKP phosphorylation in processing single-strand DNA gaps and its link to fork progression and processing of Okazaki fragments.

They generated two PNKP KO human clonal cell lines and described defects in cell growth, accumulation in S-phase, and faster fork progression. With some elegant experiments, they complement the KO cell lines with deletion and point mutants for PNKP, identifying a critical phosphorylation site (T118) in the linker regions, which is important for cell growth and DNA replication.

They show that phosphorylation of PNKP peaks in the mid-S phase. CDK1 and CDK2/ with Cyclin A2 are the two main CDK complexes responsible for this modification. With the IPOND experiment, the author shows that PNKP is recruited at nascent DNA during replication.

They described increased parylation activity in PNKP KO cells, and by using HU and emetin, they concluded that this increased activity depends on replication and synthesis of Okazaki fragments.

Interfering with Okazaki fragment maturation by FEN1 inhibition is epistatic with PNKP KO (and T118A) in influencing parylation activity in the S phase and fork progression. The authors try to understand by mutant complementation which of the two functions (Phosphatase vs Kinase) is important in processing OF, and they propose a primary role for the phosphatase activity of PNKP. They also show that T118 is important in controlling genome stability following different genotoxic stress. Finally, by coupling the measurement of fork progression with PARP/FEN1 inhibitors and S1 treatment, they propose a role of PNKP in the post-replicative repair of single-strand gaps due to unligated OF.

Here are my major points:

The authors use a poly ADP ribose deposition measurement to estimate SSB nick/gap formation. Even if PARP activity is strictly linked to SSB repair, ADP ribosylation does not directly estimate SSB/nick gap formation. In addition, in Figs S2A, B, and C, the authors use IR and PARG inhibition to measure poly-ADP ribosylation in WT and PNKP KO cells. IR produces both SSB and DSB. A better and cleaner experiment would be to directly measure SSB formation (with alkaline comet assay, for example) in combination with treatments that are known to mainly cause SSB (H2O2, or low doses of bleomycin). Thank you for your suggestion. The main purpose of this manuscript is to clarify the potential role of PNKP in DNA replication. Therefore, we generated PNKP KO human cells and figure S2 showed confirmation of function of established role of PNKP in SSBs and DSBs repair. In addition, previous our report published in EMBO Journal (Shimada et al., 2015), we showed SSBs and DSBs repair defect in PNKP KO MEF with comet assay (both alkaline and neutral) after IR and H2O2 treatment. In addition to those observations, we will also perform BrdU incorporation assay in PNKP WT and KO cells treated with H2O2. BrdU staining under an undenatured condition has now been commonly used and is a more direct method to detect ssDNA nick/gap formation. We believe that the importance of PNKP in SSB repair is sufficiently supported by all data such as previous comet assays in PNKP KO MEF cells and two SSB repair assays in human cells using ADP-ribose staining or BrdU incorporation, which will be provided in the revised manuscript.

The manuscript would benefit from substantially restructuring the figures' order and panels. Before starting the T118 part, the authors could create several figures to explain the main consequences of the loss of PNKP. A figure could be focused on DSB-driven genome instability (fig1 + fig S8 and S9). Then, a figure for the single-strand break and link to the S-phase. For example, by using data from Figure 6 and showing only WT vs PNKP KO +- Nuclease S1 (without FEN1 or PARP inhibitors), the authors could easily convince the readers that loss of PNKP leads to the accumulation of single-strand gaps. Only in the second part of the manuscript could they introduce all the T118 parts. Thank you for your suggestion. The layout of this manuscript makes reviewers feeling confusing. After performing all planned experiments, we will carefully re-consider the total layout of the revised manuscript.

I understand the use of a FEN1 inhibitor to link the PNKP KO phenotype to OF processing, but this drug does not either rescue or exacerbate any of the phenotypes described by the authors. It seems to have just an epistatic effect everywhere. So, what other conclusion can we have if not that PNKO has a similar effect to FEN1? I think that the presence of this inhibitor in many plots complicates the digestion of several figures a little bit. Maybe clustering the data in a different way (DMSO on one side FEN1i on the other) would help. Thank you for your suggestion. We agree that this data set is complicate. To facilitate better understanding, we will change organization of the data according to your suggestion and add graphical scheme in figure 6.

In terms of the other conclusion we can have from those experiments, the other conclusion is that PNKP might plays two important roles in DNA replication: Okazaki fragment maturation, which seems an epistatic effect with FEN1, and PARP1-XRCC1 dependent single-strand gap filling pathway, which is required for repairing single-strand gaps between Okazaki fragments when Okazaki fragment maturation pathway does not work properly (e.g., loss of FEN1 or PNKP). In figure 6D, we show that a double treatment of FEN1i and PARPi in PNKP WT cells with S1 nuclease treatment shows extensive amount of digested DNA fibers, although a single treatment of either FEN1i or PARPi in PNKP WT cells with S1 nuclease treatment leads to only limited amount of digested DNA fibers, which indicates that two pathways regulated by FEN1 or PARP are coordinately required for preventing eruption of ssDNA gaps in DNA replication. On the other hand, PNKP KO cells with S1 nuclease treatment cause extensive amount of digested DNA fibers even without FEN1i and PARP1i treatments, also it is not further increased by FEN1i and PARPi treatment. Those results indicate that PNKP itself is involved in two pathways mentioned above. Therefore, loss of PNKP has a similar phenotype with loss of FEN1 in terms of Okazaki fragment maturation, but also there is an additional effect in repairing ssDNA nicks/gaps, which is created in FEN1 loss condition, but FEN1 seems not dealing with it.

Fig S9 should be removed from the discussion. Additionally, the authors should consider whether they want to keep that piece of data in a manuscript that is already pretty dense. Why should we focus on additional linker residues and microirradiation data at the end of this manuscript? *Thank you for your suggestion. This is a point also raised by Reviewer 1. Since we are going to re-consider the layout of the manuscript upon the planned revision, we will move these points to the appropriate result section from the discussion. *

I suggest using a free AI writing assistant. I think this manuscript would substantially benefit from one. As a non-native English speaker, I personally use one of them and find it extremely useful. Thank you for your suggestion. Our manuscript was revised by a native speaker from an English correction company. However, for revised manuscript, we will discuss with native speakers as well as use a free AI writing assistant to improve the quality of the manuscript.

Minor points:

In Figure S1A, the author refers to P-H2AX, but I do not see this marker in the western blot. Thank you for your suggestion. We will add pH2AX blot data in fig S2A.

**Referees cross-commenting**

I agree with all comments from reviewer 1 and 2.

Reviewer #3 (Significance (Required)):

This is an interesting paper with generally solid data and proper statistical analysis. The figures are pretty straightforward. Unfortunately, the manuscript is dry, and the reader needs help to follow the logical order and the rationale of the experiments proposed. This is also complicated by the enormous amount of data the authors have generated. The authors should improve their narrative, explaining better why they are performing the experiment and not simply referring to a previous citation. Reordering panels and figures would help in this regard. Overall, with some new experiments, tone-downs over strong claims and a better explanation of the rationale behind experiments the authors could create a fascinating paper.

Thank you very much for your positive comment about the data/analysis and the logic behind the experiments provided in the manuscript. We agree with that a manner and a structure of the manuscript could be improved by reordering figures, cutting down some redundant experiments, adding better explanation of the rationale behind experiments, and toning-down some claims. With rewriting the manuscript as stated above and performing several additional experiments suggested by the reviewers, we believe that the revised manuscript will be more convincing and fascinating.

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

Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. If no revisions have been carried out yet, please leave this section empty.

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Reviewer #1:

Minor comments

• Is there any difference (except for PARGi exposure time?!) between figure S2B/C and S2D/E? Both data show increased ADP ribose after IR. It seems redundancy. Also it is hard to imagine that there is absolutely no sign of ADP ribose after IR w/o PARGi treatment (figure S2D).

Figure S2B/C show spontaneous single strand DNA breaks (SSBs) in PNKP KO cells, on the other hand, figure 2S/E show ectopic SSBs induced by IR exposure in PNKP KO cells. We believe these data help for readers to understand the effect of endo or exo damage in PNKP KO cells. Poly-ADP ribosylations are immediately removed from SSB sites after repair as demonstrated previously (Tsukada, et al., PLoS One 2019, Kalasova et al., Nucleic Acids Research, 2020), although not zero (low level), it is very difficult to detect without PARGi treatment.

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Legend for figure S3 - typo!

Thank you for your suggestion about typo. The legend for figure S3 is corrected as "Protein expression of PNKP mutants in U2OS cells".

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• In figure S3A/B, it is quite interesting that the PNKP antibody used for this analysis can detect all truncated and alanine substituted PNKP proteins. It might be helpful to indicate for other researchers which antibody used (Novus; epitope - 57aa to 189 aa or Abcam; epitope not revealed).

In S3A/B, Novus PNKP antibody was used for all blots. We indicated this in the figure legend as "PNKP antibody (Novus: NBP1-87257) was used for comparing expression levels of endogenous and exogenous PNKP".

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In results: 'PNKP phosphorylation, especially of T118 ~~~ proliferation'

• In the fork progression experiment (figure 2C), is there any statistical difference between D2 and D3/4 expressing cells?

*Thank you for your suggestion. We performed statistical analysis as the reviewer suggested. Statistical analysis shows that there are no significant differences between D2 and D3/D4. Meanwhile, there are significant differences between WT and D3(P- What is the basis of the description 'Since the linker region of PNKP is considered to be involved in fork progression'? Any reference?

This sentence was considered based on the above sentences "Furthermore, D2 mutant-expressing cells also showed an increased speed of the replication fork compared to WT and D1 mutant-expressing cells, although D3 and D4 showed mildly high-speed fork progression.". The D2 mutant lacks a whole linker region, which shows increased speed of DNA fiber in figure 2C. Therefore, we originally explained as the sentence above. We have revised the sentence to "Since these results may indicate the linker region of PNKP is involved in proper fork progression".

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• In figure 3B: pS114-PNKP (also pS15-p53) is DNA damage inducible. In this experiment, was DNA damage introduced? Roscovitine could hinder DNA repair process, but not inducing DNA damage itself.

Thank you for your suggestion. DNA damage induction was not applied in this experiment. We agree that this panel makes confusing. We think that endogenously S114-PNKP (also S15-p53) might be phosphorylated slightly but not significant, although this is not the scope of this manuscript. This result showing that phosphorylated-T118 is reduced by Roscovitine treatment maybe redundant as we also have a result of in vitro phosphorylation assay using several combinations of CDKs and Cyclin proteins, which is a cleaner experiment to prove which CDK/Cyclin complex is directly controlling the T118 phosphorylation. Since the manuscript already contains enough amount of data to support the conclusion (as reviewer 3 also stated), we removed those blots result from the panel to avoid complicating the conclusion.

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In results: 'Phosphatase activity of PNKP is ~~~ of Okazaki fragments'

• In figure 5C, any statistical analysis between WT-PNKP KO vs D171A-PNKP KO or K378A-PNKP KO has been done?

Thank you for your comment. Statistical analysis shows P *

In discussion, 'In contrast, the T118A mutants showed the absence of both SSBs and DSBs repair (Fig. S7) : figure S7 does not indicate what the authors describe.

Thank you for pointing out this. This should refer to figure S8 instead of figure S7. We have corrected this error.

In addition, the same sentence in discussion: No evidence demonstrate that 'the absence of both SSBs and DSBs repair', and the following sentence is not clear.

*This is same point with above. We have corrected this mis-referencing and revised the sentence to "In contrast, the T118A mutants showed the impaired abilities of both SSBs and DSBs repair (Fig. S8).". We also revised the following sentence to "However, residual SSBs due to impaired SSB repair ability (e.g., in PARPi-treated cells and T118A cells) sometimes cause DNA replication-coupled DSBs formation in S phase, and the phenotype in DSB repair assay of the T118A mutant may be caused by an accumulated formation of DNA replication-coupled DSBs. Future works will be needed to distinguish whether the T118 phosphorylation directly regulate PNKP recruitment to DSBs as well as SSBs." for better explanation of the result. *

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In discussion, 'Because both CDK1/cyclin A2 and CDK2/cyclin A2 are involved in PNKP phosphorylation, cyclin A2 is likely important for these activities': It is not clear what this description intends? Is 'cyclin A2' important in what stance?

This description is coming from Fig3C observation. Since both CDK1 and CDK2 activities are cyclin A2 dependent, we speculated cyclin A2 is important for CDK1/CDK2 dependent PNKP T118 phosphorylation. We revised the description to "Since both CDK1/Cyclin A2 and CDK2/Cyclin A2 phosphorylate T118 of PNKP, we speculated that PNKP T118 is phosphorylated in S phase to G2 phase in CDK1/Cyclin A2- and CDK2/Cyclin A2-dependent manner (Fig. 3B and C)".

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In discussion, 'This may be explained by the fact that mutations in the phosphorylated residue in the linker region are embryonic lethal': any reference to support this embryonic lethality?

Thank you for your suggestion. We agree with that this sentence is overwriting. We revise the sentence to "This observation may indicate that mutations in the phosphorylated residue (T118) in the linker region are potentially embryonic lethal due to the importance of T118 in DNA replication, which is revealed in the present study.".

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Reviewer #2:

Minor comments

Sometimes there are incorrect references to the figures in the discussion (e.g. FigS9A, B, and C, are called out instead of E, F and G), a similar issue is found 4 lines below in the same page.

Thank you for pointing out these errors. We checked the references in the discussion and corrected to the appropriate references.

Based on the data in Figure 3A the authors suggest that pT118-PNKP follows Cyclin A2 levels, but this does not appear very clearly in the gel, especially for the last point. Even though the results are convincing, the authors should rephrase the conclusions of Figure 3A to reflect better the results.

Thank you for your suggestion. We agree that this phrase is overwriting. We revised the conclusion to "pT118-PNKP was detected in asynchronized cells but increased particularly in the S phase, similar to Cyclin A2 expression levels, although the reduction of pT118, possibly dephosphorylation of T118, seems not as robust as the reduction of the Cyclin A2 expression level at the 12 hours time point. However, this effect was very weak during mitosis, suggesting that T118 phosphorylation plays a specific role in the S phase.".

I did not find a reference to what seems to be a relevant work in this topic: PMID: 22171004

Thank you for your suggestion. We have added the ref (Coquelle et al., PNAS, 2011) in Introduction section.

Reviewer #3:

Major comments

The authors should consider and discuss the potential role of PNKP KO outside of the S-phase. In Figure 4C, while it is clear that poly ADP ribosylation is higher in S-phase, the effects of PNKP KO and complementation by WT or T118A are equally present. This would be more immediate if comparison, fold change, and statistical significance calculation were done within the same cell cycle phase instead of between cell stages. This is also clear by IF in Figure 4B. How do the authors explain this? Thank you for your suggestion. We agree with reviewer's suggestion. We compared intensities of ADP-ribose between cell lines in same cell cycle rather than between different cell cycles in a same cell line and added the respective statistics in figure 4C. Also, we agree with that poly ADP-ribose intensity is changed outside of S phase between WT and T118A PNKP expressing PNKP KO cells. As shown in figure S8, PNKP pT118 is also involved in DNA repair. These results might reflect of PNKP function outside of S phase. We have added the sentence "Of note, PNKP−/−*cells and PNKP T118A cells showed markedly higher ADP-ribose intensity in outside the S phase as well, which indicate that PNKP and T118 may have an endogenous role to prevent SSBs formation in outside the S phase. Since FEN1 has been reported to function in R-loop processing, PNKP could also be involved in this process. Future studies of a role of PNKP in different cell cycle will be able to address this question." to discuss about the function of PNKP outside the S phase. We have added the ref (Cristini et al., Cell Reports, 2019, and Laverde et al., Genes, 2022). *

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In connection with the previous point, can the author provide the same quantification in Figure 4E also for G2/M and not only the S phase? This should give an estimate of the activity of FEN1 outside the S-phase. This is important because FEN1 has other functions apart from OF maturation, such as R loop processing (Cristini 2019; Laverde 2023) Thank you for your suggestion. Here attached is the data of ADP-ribose intensity in cells outside the S phase as you suggested. FEN1i treatment still induces increased ADP-ribose intensity in outside the S phase as well, although the difference between with/without FEN1i treatment is much smaller than that in S phase, indicating that FEN1 has other functions outside the S phase. This finding is very interesting. However, the function of FEN1 in outside the S phase is outside the scope of this manuscript. Therefore, we would like to not put this data in the manuscript to avoid complicating the conclusion (as reviewer 3 also suggested).

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Why does FEN1 inhibition induce a faster fork progression in Fig4 but not in Fig5 and Fig6? Yes, it does in figure 4 and figure 5. In PNKP WT cells, FEN1i-treated fibers (CldU) show an increased speed of forks compared to non-treated fibers (IdU). However, loss of PNKP and T118 phosphorylation themselves cause a faster fork progression even if without FEN1i treatment, therefore the difference of speeds of forks before/after FEN1i treatment in PNKP KO and T118A cells is disappeared as both fibers grow faster than intact fibers in normal cells. In regard to figure 6, as you mentioned in a latter comment about figure 6, the title of vertical axis of the graph showing CldU length should not be speeds of replication forks as those DNA fibers are potentially digested by S1 nuclease, which is modified in the revised manuscript. Even so, DNA fibers from FEN1i-treated cells (CldU) with S1 nuclease shows similar length with fibers from untreated cells with S1 nuclease, whereas FEN1 inhibitor treatment accelerates a speed of forks in general (figure 4 and figure 5, assays without S1 nuclease), indicating that FEN1i treatment induces remaining of some ssDNA nicks/gaps which are substrates of S1 nuclease.

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How do the authors explain the impaired DNA gap binding activity of the phospho-mimetic T118D? Thank you for your suggestion. We think that the appropriate timing of phosphorylation of PNKP T118 is important, while the phosphor-mimetic mutant T118D mimics consecutively phosphorylated situation that may result in incomplete complementation of PNKP function.

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I would like to see a representative fiber image from Fig 6. Additionally, in Figure 6, the author should not label the y-axis as CldU-fork speed. Nuclease S1 treatment destroys single-strand gaps (in vitro) and does not affect the fork speed (in vivo) Thank you for your suggestion. We have added a representative fiber image. We also agree with that CldU fork speed is not a right label of y-axis as CldU fibers are potentially digested by S1 nuclease. We changed the y-axis label to "CldU tract length [kb/min]" in figure 6.

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Figure 5E: both mutants (kinase vs phosphatase) increase polyADP ribose intensity, while the title of this figure only emphasizes the phosphatase activity. We agree with your comment. We have changed this subtitle to "Enzymatic activities of PNKP is important for the end-processing of Okazaki fragments".

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Minor comments

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The authors refer to Hoch Nature 2017 when referring to polyADP ribose IF + PARG inhibition. Should they not refer to Hanzlikova Mol Cell 2018?

Thank you for your suggestion. We have added the ref (Hanzlikova et al., Mol Cell 2018).

Statistical analysis should be performed on the cell cycle profile in Figure 1B * *

We performed statistical analysis to check whether there are significant differences of S phase population between WT and PNKP KO cells. There were significant differences between WT vs PNKP KO C1 (PThe authors should not refer to fork degradation or protection as a given fact without assessing it in these conditions. Thank you for your suggestion. We assume that this comment refers to the result section of figure 1 and figure 4. We have added a sentence "although future studies will be needed to investigate whether PNKP−/− cells has the fork protection phenotype" in the result section of figure 1. We have changed representation in the section according to the reviewer's suggestion in the result section of figure 4.*

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Referee #3

Evidence, reproducibility and clarity

Tsukada and colleagues studied the role of PNKP phosphorylation in processing single-strand DNA gaps and its link to fork progression and processing of Okazaki fragments.

They generated two PNKP KO human clonal cell lines and described defects in cell growth, accumulation in S-phase, and faster fork progression. With some elegant experiments, they complement the KO cell lines with deletion and point mutants for PNKP, identifying a critical phosphorylation site (T118) in the linker regions, which is important for cell growth and DNA replication.

They show that phosphorylation of PNKP peaks in the mid-S phase. CDK1 and CDK2/ with Cyclin A2 are the two main CDK complexes responsible for this modification. With the IPOND experiment, the author shows that PNKP is recruited at nascent DNA during replication.

They described increased parylation activity in PNKP KO cells, and by using HU and emetin, they concluded that this increased activity depends on replication and synthesis of Okazaki fragments.

Interfering with Okazaki fragment maturation by FEN1 inhibition is epistatic with PNKP KO (and T118A) in influencing parylation activity in the S phase and fork progression. The authors try to understand by mutant complementation which of the two functions (Phosphatase vs Kinase) is important in processing OF, and they propose a primary role for the phosphatase activity of PNKP. They also show that T118 is important in controlling genome stability following different genotoxic stress. Finally, by coupling the measurement of fork progression with PARP/FEN1 inhibitors and S1 treatment, they propose a role of PNKP in the post-replicative repair of single-strand gaps due to unligated OF.

Here are my major points:

• The authors use a poly ADP ribose deposition measurement to estimate SSB nick/gap formation. Even if PARP activity is strictly linked to SSB repair, ADP ribosylation does not directly estimate SSB/nick gap formation. In addition, in Figs S2A, B, and C, the authors use IR and PARG inhibition to measure poly-ADP ribosylation in WT and PNKP KO cells. IR produces both SSB and DSB. A better and cleaner experiment would be to directly measure SSB formation (with alkaline comet assay, for example) in combination with treatments that are known to mainly cause SSB (H2O2, or low doses of bleomycin).
• The manuscript would benefit from substantially restructuring the figures' order and panels. Before starting the T118 part, the authors could create several figures to explain the main consequences of the loss of PNKP. A figure could be focused on DSB-driven genome instability (fig1 + fig S8 and S9). Then, a figure for the single-strand break and link to the S-phase. For example, by using data from Figure 6 and showing only WT vs PNKP KO +- Nuclease S1 (without FEN1 or PARP inhibitors), the authors could easily convince the readers that loss of PNKP leads to the accumulation of single-strand gaps. Only in the second part of the manuscript could they introduce all the T118 parts.
• The authors should consider and discuss the potential role of PNKP KO outside of the S-phase. In Figure 4C, while it is clear that poly ADP ribosylation is higher in S-phase, the effects of PNKP KO and complementation by WT or T118A are equally present. This would be more immediate if comparison, fold change, and statistical significance calculation were done within the same cell cycle phase instead of between cell stages. This is also clear by IF in Figure 4B. How do the authors explain this?
• In connection with the previous point, can the author provide the same quantification in Figure 4E also for G2/M and not only the S phase? This should give an estimate of the activity of FEN1 outside the S-phase. This is important because FEN1 has other functions apart from OF maturation, such as R loop processing (Cristini 2019; Laverde 2023)
• I understand the use of a FEN1 inhibitor to link the PNKP KO phenotype to OF processing, but this drug does not either rescue or exacerbate any of the phenotypes described by the authors. It seems to have just an epistatic effect everywhere. So, what other conclusion can we have if not that PNKO has a similar effect to FEN1? I think that the presence of this inhibitor in many plots complicates the digestion of several figures a little bit. Maybe clustering the data in a different way (DMSO on one side FEN1i on the other) would help.
• Why does FEN1 inhibition induce a faster fork progression in Fig4 but not in Fig5 and Fig6?
• How do the authors explain the impaired DNA gap binding activity of the phospho-mimetic T118D?
• Fig S9 should be removed from the discussion. Additionally, the authors should consider whether they want to keep that piece of data in a manuscript that is already pretty dense. Why should we focus on additional linker residues and microirradiation data at the end of this manuscript?
• I would like to see a representative fiber image from Fig 6. Additionally, in Figure 6, the author should not label the y-axis as CldU-fork speed. Nuclease S1 treatment destroys single-strand gaps (in vitro) and does not affect the fork speed (in vivo)
• Figure 5E: both mutants (kinase vs phosphatase) increase polyADP ribose intensity, while the title of this figure only emphasizes the phosphatase activity.
• I suggest using a free AI writing assistant. I think this manuscript would substantially benefit from one. As a non-native English speaker, I personally use one of them and find it extremely useful.

Minor points:

• In Figure S1A, the author refers to P-H2AX, but I do not see this marker in the western blot.
• The authors refer to Hoch Nature 2017 when referring to polyADP ribose IF + PARG inhibition. Should they not refer to Hanzlikova Mol Cell 2018?
• Statistical analysis should be performed on the cell cycle profile in Figure 1B
• The authors should not refer to fork degradation or protection as a given fact without assessing it in these conditions.

Referees cross-commenting

I agree with all comments from reviewer 1 and 2.

Significance

This is an interesting paper with generally solid data and proper statistical analysis. The figures are pretty straightforward. Unfortunately, the manuscript is dry, and the reader needs help to follow the logical order and the rationale of the experiments proposed. This is also complicated by the enormous amount of data the authors have generated. The authors should improve their narrative, explaining better why they are performing the experiment and not simply referring to a previous citation. Reordering panels and figures would help in this regard. Overall, with some new experiments, tone-downs over strong claims and a better explanation of the rationale behind experiments the authors could create a fascinating paper.

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Referee #2

Evidence, reproducibility and clarity

Polynucleotide kinase phosphatase (PNPK) participates in multiple DNA repair processes, where it acts on DNA breaks to generate 5'-phosphate and 3'-OH ends, facilitating the downstream activities of DNA ligases or polymerases.

This manuscript identifies a CDK-dependent phosphorylation site on threonine 118 in PNKP's linker region. The authors provide some convincing evidence that this modification is important to direct the activity of PNPK towards ssDNA gaps between Okazaki fragments during DNA replication. The authors monitored protein expression levels, enzymatic activity, the growth rate and replication fork speed, as well as the presence of ssDNA damage to make a comprehensive overview of the features of PNKP necessary for its function.

Overall, the conclusions are sufficiently supported by the results and this manuscript is relevant and of general interest to the DNA repair and genome stability fields. Some level of revision to the experimental data and text would help strengthen its message and conclusions.

Major points:

1. In an iPOND experiment the authors detect the wt PNKP and the T118 phosphorylated form at the forks and conclude that this phosphorylation promotes interaction with nascent DNA (Figure 3E). An informative sample to include here would have been the T118A mutant. Based on the model proposed, the prediction would be that it would not be associated with the forks, or at least, associated at reduced levels compared to the wt.
2. The quality of the gels showing the phosphatase and kinase assays in Figure 5 could be improved to facilitate quantification of the results. The gel showing the phosphatase activity has a deformed band corresponding to K378A mutant. The gel showing the kinase activity seems to be hitting the detection limits, and the overall high background might influence the quantification of D171A mutant in the area of interest. The authors should provide a better quality of these gels, focusing on better separation (running them longer, eventually with a slightly increased electric current) and higher signal of the analyzed bands (longer incubation phosphatase/kinase prior to quenching or loading higher amount of DNA).
3. The authors sometimes make statements like: "a slight increase, slightly increased, relatively high" without an evaluation of the statistical significance for the presented data. An example of such a statement is: "T118A mutant-expressing cells exhibited a marked delay in cell growth, which was not observed for S114A, although T122A, S126A, and S143A were slightly delayed," based on the figure 2E. A similar comment applies also to figures 4A, 5A, 5E. Whenever possible, the authors should include also an evaluation of the statistical significance in the statement.

Minor revisions:

1. I could not find a gH2AX blot for figure S2A.
2. Sometimes there are incorrect references to the figures in the discussion (e.g. FigS9A, B, and C, are called out instead of E, F and G), a similar issue is found 4 lines below in the same page.
3. The authors established two PNKP-/- clones and supported it with sequencing and several functional observations However, the C-terminal antibody appears to detect lower-intensity bands (Figure 1A). Can authors comment on those bands?
4. Based on the data in Figure 3A the authors suggest that pT118-PNKP follows Cyclin A2 levels, but this does not appear very clearly in the gel, especially for the last point. Even though the results are convincing, the authors should rephrase the conclusions of Figure 3A to reflect better the results.
5. Why the S1 nuclease data on DNA fibers do not show the same level of epistasis with the Fen1i, as do those on ADP-ribosylation?
6. I did not find a reference to what seems to be a relevant work in this topic: PMID: 22171004

Referees cross-commenting

I agree with all the comments from the reviewers 1 and 3.

Significance

The manuscript identifies a CDK phosphorylation site in a relevant DNA repair protein. The experiments on this part are elegant and convincing. It seems that this phosphorylation is important during DNA replication and there is some supporting evidence in this point, although not as robust, meaning that it is not clear whether this phosphorylation is controlling specifically the recruitment to Okazaki fragments, or a general role in DNA repair. Maybe if they see a reduced recruitment of the T118A mutant to the forks (iPOND experiment) this would further increase the impact.

This work will be relevant to the basic research, especially in the fields of DNA repair and DNA replication.

My expertise: DNA replication, genome stability, telomere biology.

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Referee #1

Evidence, reproducibility and clarity

Summary

PNKP is one of critical end-processing enzymes for DNA damage repair, mainly base excision & single strand break repair, and double strand break repair to a certain extent. This protein has dual enzyme function: 3' phosphatase and 5' kinase to make DNA ends proper for ligation. It has been demonstrated that PTM of PNKP (e.g., S114, S126), particularly phosphorylation by either ATM or DNAPK, is important for PNKP function in DNA damage repair. The authors found a new phosphorylation site, T118, of PNKP which might be modified by CDK1 or 2 during S phase. This modification of phosphorylation is involved in maintenance and stability of the lagging strand, particularly Okazaki fragments. Loss of this phosphorylation could result in increased single strand gaps, accelerated speed of fork progression, and eventually genomic instability. And for this process, PNKP enzyme activity is not that important. And the authors concluded that PNKP T118 phosphorylation is important for lagging strand stability and DNA damage repair.

Major comments

1. In general, enzymes have protein interactions with its/their substrates. If PNKP is phosphorylated by either/both CDK1/2, the protein interaction between these would be expected. However, the authors did not provide any protein interactions in PNKP and CDKs.
2. It is not clear how T118 phosphorylation is involved in DNA damage repair itself as the authors suggested. The data presenting the involvement of T118 phosphorylation in this mechanism are limited. This claim opens more questions than answers. CDK1/2 still phosphorylates T118 in this DNA damage repair process? What would happen to DNA damage repair in which PNKP involves outside of S phase in terms of T118 phosphorylation?
3. Along the same line with #1/2 comments, the recruitment of PNKP to the damage sites is XRCC1 dependent. Is not clear whether PNKP recruitment to gaps on the lagging strand is XRCC1 independent or dependent. It might be interesting to examine (OPTIONAL)

Minor comments

1. In results: 'Generation of PNKP knock out U2OS cell line'
   • In figure S2A; There are no data regarding diminishing the phosphorylation of g-H2AX.
   • Is there any difference (except for PARGi exposure time?!) between figure S2B/C and S2D/E? Both data show increased ADP ribose after IR. It seems redundancy. Also it is hard to imagine that there is absolutely no sign of ADP ribose after IR w/o PARGi treatment (figure S2D).
   • By showing data in figure S2B/C/D/E, the authors describe 'PNKP KO cells impaired the SSBs repair activity'. However, as the authors mentioned in this manuscript, PNKP could bind to either XRCC1 or XRCC4. Also for this experiment, IR had been applied, which induces DNA double strand breaks. Therefore, it is not certain that the authors' description is fully supported by these data presented. Perhaps, SSB inducing reagents should be used instead of IR.
2. Legend for figure S3 - typo!
   • In figure S3A/B, it is quite interesting that the PNKP antibody used for this analysis can detect all truncated and alanine substituted PNKP proteins. It might be helpful to indicate for other researchers which antibody used (Novus; epitope - 57aa to 189 aa or Abcam; epitope not revealed).
3. In results: 'PNKP phosphorylation, especially of T118 ~~~ proliferation'
   • In the fork progression experiment (figure 2C), is there any statistical difference between D2 and D3/4 expressing cells?
   • What is the basis of the description 'Since the linker region of PNKP is considered to be involved in fork progression'? Any reference?
   • Is there any FACS analysis data to support the description of the last sentence 'especially the phosphorylation of PNKP T118, is required for S phase progression and proper cell proliferation'?
4. In results: 'CDKs phosphorylate T118 of PNKP ~~~ replication forks'
   • In figure 3A, Is there any change in total PNKP (both GFP-tagged & endogenous) level?
   • In figure 3B: pS114-PNKP (also pS15-p53) is DNA damage inducible. In this experiment, was DNA damage introduced? Roscovitine could hinder DNA repair process, but not inducing DNA damage itself.
5. In results: 'Phosphorylation of PNKP at T118 ~~~ between Okazaki fragments'
   • In figure 4D, What happens in the ADP-ribose level, when T118D PNKP is expressed?
6. In results: 'Phosphatase activity of PNKP is ~~~ of Okazaki fragments'
   • In figure 5C, any statistical analysis between WT-PNKP KO vs D171A-PNKP KO or K378A-PNKP KO has been done?
7. In results: 'PNKP is involved in postreplicative single-strand DNA gap-filling pathway'
   • The description regarding data presented in figure 6 is not clear enough. These data might suggest that wildtype U2OS does not have SSB which is a substrate for S1 nuclease (except under FEN1i and PARPi treatment), whereas PNKP KO has SSB during both IdU and CIdU incorporation, so that S1 nuclease treatment dramatically reduces the speed of fork formation in PNKP KO cells. Also In figure 6B/C/D, adding an experimental group of PNKP KO with S1 nuclease + PARPi might help to understand the role of PNKP during replication better. Also these additional data could support the description in discussion 'Furthermore, PNKP is required for the PARP1-dependent single-strand gap-filling pathway ~~~ DNA gap structure'.
8. In results: 'Phosphorylation of PNKP at T118 is essential for genome stability'
   • In figure S8C, Did you measure g-H2AX foci disappearance for later time point, such as 24 hrs after DNA damage? Is not clear whether non-phosphorylated PNKP at T118 inhibit DNA damage repair or make it slower? How does T114A-PNKP behave in this experimental condition? T114 is well known target of ATM/DNAPK for DDR & DSB repair.
9. The result shown in figure S9 should be described in the result section, not in the discussion section.
10. In discussion, 'In contrast, the T118A mutants showed the absence of both SSBs and DSBs repair (Fig. S7) : figure S7 does not indicate what the authors describe.
11. In addition, the same sentence in discussion: No evidence demonstrate that 'the absence of both SSBs and DSBs repair', and the following sentence is not clear.
12. In discussion, 'Because both CDK1/cyclin A2 and CDK2/cyclin A2are involved in PNKP phosphorylation, cyclin A2 is likely important for these activities': It is not clear what this description intends? Is 'cyclin A2' important in what stance?
13. In discussion, 'This may be explained by the fact that mutations in the phosphorylated residue in the linker region are embryonic lethal': any reference to support this embryonic lethality?

Referees cross-commenting

I could see a similar degree of positive tendency toward the manuscript. I agree with the comments and suggestions in additional experiments made by reviewers 2 and 3. Those suggestions will improve an impact of the manuscript in the DNA damage repair field.

Significance

The authors discovered new phosphorylation site (T118) of PNKP which is an important DNA repair protein. This modification seems to play a role in maintenance of the lagging strand stability in S phase. This discovery is something positive in DNA repair field to expand the canonical and non-canonical functions of DNA repair factors.

The data presented to support PNKP functions and T118 phosphorylation in S phase seem solid in general, yet it is not sure how much PNKP is critical in the Okazaki fragment maturation process which is known that several end processing enzymes (like FEN1, EXO1, DNA2 etc which leave clean DNA ends.) are involved. These finding might draw good attentions from researchers interested broadly in cell cycle, DNA damage repair, replication, and possibly new tumor treatment.

My field and research interest: DNA damage response (including cell cycle arrest and programmed cell death), DNA damage repair (including BER, SSBR, DSBR)

It would be interesting to see a gender breakdown for this as well.

eLife assessment

This important article presents the results of a large screen for non-genetic transgenerational effects that may influence gene expression and other phenotypes in mice. An extraordinary amount of mouse breeding, phenotyping, and RNA sequencing data provide compelling evidence that, for the phenotypes and genomic regions interrogated in these mouse strains, non-genetic transgenerational effects of appreciable magnitude are likely to be extremely rare. This paper will be of broad interest to geneticists and of particular interest to those studying epigenetic inheritance.

Reviewer #1 (Public Review):

Summary:

This paper explores the contribution of transgenerational effects to phenotypic variation in twenty-five phenotypes and transcript variation in the heart, liver, pituitary, whole embryo, and placenta. The authors use a powerful design, exploiting the use of consomics, and argue that there are no observable changes attributable to the differences in the parental origin of the four chromosomes they examine.

Strengths:<br /> It's good to see a use for consomics. This is a powerful and useful design to address the problem they are tackling.

Weaknesses:<br /> The difficulty faced by the authors is that they have interrogated only a small portion of the genome, using bulk RNA sequencing and a set of correlated phenotypes, thus restricting the conclusions they can draw from the absence of significant findings.

Reviewer #2 (Public Review):

Summary:

In this study, Gularte-Merida et al investigate the occurrence of transgenerational effects of non-transmitted parental alleles outside of the well-described effect of "genetic nurture." To achieve this they employed consomic male mice to generate an N2 and N3 population, allowing for the observation of effects due to non-transmitted paternal alleles while controlling for maternal care by using isogenic B6 dams. The authors conduct RNAseq, qPCR validation, and anatomical phenotyping measures to investigate the presence of non-genetic nurture TGE. The author's findings challenge the frequency of non-genetic nurture TGE, a meaningful contribution to the field. Overall, this is an ambitious study with important negative data. The authors are to be commended on this. This greatly strengthens the negative findings within the paper.

The paper, however, is written extremely technically, with little detail, and is not currently suitable for the lay audience. The authors need to greatly increase the clarity of the writing and data presentation.

Strengths:

Elegant experimental design using consomic mouse populations.

The use of a second replication cohort using the same genetic founders as the first study.

Weaknesses:

While much of the explanation of the methods is understandable by geneticists, the paper has implications outside of the genetics field. Overall, I suggest expanding the explanation and language for non-geneticists. This will allow the paper to reach a wider audience.

Reviewer #3 (Public Review):

Summary:

Gularte-Mérida and colleagues took advantage of the existence of so-called consomic strains in the mouse, which result from the substitution of one of their chromosomes by that of another strain, to ask through appropriate crosses whether information carried by this substitution chromosome impacts progeny that do not inherit it. With one exception, the authors did not detect any significant effect for any of the four non-transmitted chromosomes tested. Given these results, the authors conclude that such effects, if they exist, must be extremely rare in the mouse.

Strengths:

This is a very convincing and impressive study, with effects assessed in almost 2500 mice. The negative results obtained should put to rest once and for all the notion that intergenerational, let alone transgenerational, non-DNA sequence-based inheritance via the male germline could be substantial in the mouse.

Weaknesses:

The terminology used (epigenetics, nurture-independent TGE, etc. ) is somewhat confusing and unnecessary.

eLife assessment

In this useful study, the authors show that N-acetylation of synuclein increases clustering of synaptic vesicles in vitro and that this effect is mediated by enhanced interaction with lysophosphatidylcholine. While the evidence for enhanced clustering is largely solid, the biological significance remains unclear.

Reviewer #1 (Public Review):

⍺-synuclein (syn) is a critical protein involved in many aspects of human health and disease. Previous studies have demonstrated that post-translational modifications (PTMs) play an important role in regulating the structural dynamics of syn. However, how post-translational modifications regulate syn function remains unclear. In this manuscript, Wang et al. reported an exciting discovery that N-acetylation of syn enhances the clustering of synaptic vesicles (SVs) through its interaction with lysophosphatidylcholine (LPC). Using an array of biochemical reconstitution, single vesicle imaging, and structural approaches, the authors uncovered that N-acetylation caused distinct oligomerization of syn in the presence of LPC, which is directly related to the level of SV clustering. This work provides novel insights into the regulation of synaptic transmission by syn and might also shed light on new ways to control neurological disorders caused by syn mutations.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors provide evidence that posttranslational modification of synuclein by N-acetylation increases clustering of synaptic vesicles in vitro. When using liposomes the authors found that while clustering is enhanced by the presence of either lysophosphatidylcholine (LPC) or phosphatidylcholine in the membrane, N-acetylation enhanced clustering only in the presence of LPC. Enhancement of binding was also observed when LPC micelles were used, which was corroborated by increased intra/intermolecular cross-linking of N-acetylated synuclein in the presence of LPC.

Strengths:

It is known for many years that synuclein binds to synaptic vesicles but the physiological role of this interaction is still debated. The strength of this manuscript is clearly in the structural characterization of the interaction of synuclein and lipids (involving NMR-spectroscopy) showing that the N-terminal 100 residues of synuclein are involved in LPC-interaction, and the demonstration that N-acetylation enhances the interaction between synuclein and LPC.

Weaknesses:

Lysophosphatides form detergent-like micelles that destabilize membranes, with their steady-state concentrations in native membranes being low, questioning the significance of the findings. Oddly, no difference in binding between the N-acetylated and unmodified form was observed when the acidic phospholipid phosphatidylserine was included. It remains unclear to which extent binding to LPC is physiologically relevant, particularly in the light of recent reports from other laboratories showing that synuclein may interact with liquid-liquid phases of synapsin I that were reported to cause vesicle clustering.

eLife assessment

This manuscript reports important data on the interaction of Rev7 with the Rad50-Mre11-Xrs2 complex in budding yeast providing evidence that a 42 amino acid region of Rev7 is necessary and sufficient for interaction. Rev7 is found to inhibit the Rad50 ATPase and the Mre11 nuclease activities, with the exception of the ssDNA exonuclease activity. Overall, the study is incomplete: controls are lacking, there is little evidence to support the conclusion about DSB repair pathway usage, and the work on the role of Mre11 in G4 metabolism is underdeveloped.

Reviewer #1 (Public Review):

Summary:

The mammalian Shieldin complex consisting of REV7 (aka MAD2L2, MAD2B) and SHLD1-3 affects pathway usage in DSB repair favoring non-homologous endjoining (NHEJ) at the expense of homologous recombination (HR) by blocking resection and/or priming fill-in DNA synthesis to maintain or generate near blunt ends suitable for NHEJ. While the budding yeast Saccharomyces cerevisiae does not have homologs to SHLD1-3, it does have Rev7, which was identified to function in conjunction with Rev3 in the translesion DNA polymerase zeta. Testing the hypothesis that Rev7 also affects DSB resection in budding yeast, the work identified a direct interaction between Rev7 and the Rad50-Mre11-Xrs2 complex by two-hybrid and direct protein interaction experiments. Deletion analysis identified that the 42 amino acid C-terminal region was necessary and sufficient for the 2-hybrid interaction. Direct biochemical analysis of the 42 aa peptide was not possible. Rev7 deficient cells were found to be sensitive to HU only in synergy with G2 tetraplex forming DNA. Importantly, the 42 aa peptide alone suppressed this phenotype. Biochemical analysis with full-length Rev7 and a C-terminal truncation lacking the 42 aa region shows G4-specific DNA binding that is abolished in the C-terminal truncation and with a substrate containing mutations to prevent G4 formation. Rev7 lacks nuclease activity but inhibits the dsDNA exonuclease activity of Mre11. The C-terminal truncation protein lacking the 42 aa region also showed some inhibition suggesting the involvement of additional binding sites besides the 42 aa region. Also, the Mre11 ssDNA endonuclease activity is inhibited by Rev7 but not the degradation of linear ssDNA. Rev7 does not affect ATP binding by Rad50 but inhibits in a concentration-dependent manner the Rad50 ATPase activity. The C-terminal truncation protein lacking the 42 aa region also showed some inhibition but significantly less than the full-length protein.

Using an established plasmid-based NHEJ assay, the authors provide strong evidence that Rev7 affects NEHJ, showing a four-fold reduction in this assay. The mutations in the other Pol zeta subunits, Rev3 and Rev1, show a significantly smaller effect (~25% reduction). A strain expressing only the Rev7 C-terminal 42 aa peptide showed no NHEJ defect, while the truncation protein lacking this region exhibited a smaller defect than the deletion of REV7. The conclusion that Rev7 supports NHEJ mainly through the 42 aa region was validated using a chromosomal NHEJ assay. The effect on HR was assessed using a plasmid:chromosome system containing G4 forming DNA. The rev7 deletion strain showed an increase in HR in this system in the presence and absence of HU. Cells expressing the 42 aa peptide were indistinguishable from the wild type as were cells expressing the Rev7 truncation lacking the 42 aa region. The authors conclude that Rev7 suppresses HR, but the context appears to be system-specific and the conclusion that Rev7 abolished HR repair of DSBs is unwarranted and overly broad.

Strength:

This is a well-written manuscript with many well-executed experiments that suggest that Rev7 inhibits MRX-mediated resection to favor NEHJ during DSB repair. This finding is novel and provides insight into the potential mechanism of how the human Shieldin complex might antagonize resection.

Weaknesses:

The nuclease experiments were conducted using manganese as a divalent cation, and it is unclear whether there is an effect with the more physiological magnesium cation. Additional controls for the ATPase and nuclease experiments to eliminate non-specific effects would be helpful. Evidence for an effect on resection in cells is lacking. The major conclusion about the role of Rev7 in regulating the choice between HR and NHEJ is not justified, as only a highly specialized assay is used that does not warrant the broad conclusion drawn. Specifically, the results that the Rev7 C-terminal truncation lacking the 42 aa region still suppresses HR is unexpected and unexplained. The effect of Rev7 on G4 metabolism is underdeveloped and distracts from the main results that Rev7 modulated MRX activity. The authors should consider removing this part and develop a more complete story on this later.

Reviewer #2 (Public Review):

In this study, Badugu et al investigate the Rev7 roles in regulating the Mre11-Rad50-Xrs2 complex and in the metabolism of G4 structures. The authors also try to make a conclusion that REV7 can regulate the DSB repair choice between homologous recombination and non-homologous end joining.

The major observations of this study are:

(1) Rev7 interacts with the individual components of the MRX complex in a two-hybrid assay and in a protein-protein interaction assay (microscale thermophoresisi) in vitro.<br /> (2) Modeling using AlphaFold-Multimier also indicated that Rev7 can interact with Mre11 and Rad50.<br /> (3) Using a two-hybrid assay, a 42 C terminal domain in Rev7 responsible for the interaction with MRX was identified.<br /> (4) Rev7 inhibits Mre11 nuclease and Rad50 ATPase activities in vitro.<br /> (5) Rev 7 promotes NHEJ in plasmid cutting/relegation assay.<br /> (6) Rev7 inhibits recombination between chromosomal ura3-1 allele and plasmid ura3 allele containing G4 structure.<br /> (7) Using an assay developed in V. Zakian's lab, it was found that rev7 mutants grow poorly when both G4 is present in the genome and yeast are treated with HU.<br /> (8) In vitro, purified Rev7 binds to G4-containing substrates.

In general, a lot of experiments have been conducted, but the major conclusion about the role of Rev7 in regulating the choice between HR and NHEJ is not justified.

(1) Two stories that do not overlap (regulation of MRX by Rev7 and Rev7's role in G4 metabolism) are brought under one umbrella in this work. There is no connection unless the authors demonstrate that Rev7 inhibits the cleavage of G4 structures by the MRX complex.

(2) The authors cannot conclude based on the recombination assay between G4-containing 2-micron plasmid and chromosomal ura3-1 that Rev7" completely abolishes DSB-induced HR". First of all, there is no evidence that DSBs are formed at G4. Why is there no induction of recombination when cells are treated with HU? Second, as the authors showed, Rev7 binds to G4, therefore it is not clear if the observed effects are the result of Rev7 interaction with G4 or its impact on HR. The established HO-based assays where the speed of resection can be monitored (e.g., Mimitou and Symington, 2010) have to be used to justify the conclusion that Rev7 inhibits MRX nuclease activity in vivo.

Reviewer #3 (Public Review):

Summary:

REV7 facilitates the recruitment of Shieldin complex and thereby inhibits end resection and controls DSB repair choice in metazoan cells. Puzzlingly, Shieldin is absent in many organisms and it is unknown if and how Rev7 regulates DSB repair in these cells. The authors surmised that yeast Rev7 physically interacts with Mre11/Rad50/Xrs2 (MRX), the short-range resection nuclease complex, and tested this premise using yeast two-hybrid (Y2H) and microscale thermophoresis (MST). The results convincingly showed that the individual subunits of MRX interact robustly with Rev7. AlphaFold Multimer modelling followed by Y2H confirmed that the carboxy-terminal 42 amino acid is essential for interaction with MR and G4 DNA binding by REV7. The mutant rev7 lacking the binding interface (Rev7-C1) to MR shows moderate inhibition to the nuclease and the ATPase activity of Mre11/Rad50 in biochemical assays. Deletion of REV7 also causes a mild reduction in NHEJ using both plasmid and chromosome-based assays and increases mitotic recombination between chromosomal ura3-01 and the plasmid ura3 allele interrupted by G4. The authors concluded that Rev7 facilitates NHEJ and antagonizes HR even in budding yeast, but it achieves this by blocking Mre11 nuclease and Rad50 ATPase.

Weaknesses:

There are many strengths to the studies and the broad types of well-established assays were used to deduce the conclusion. Nevertheless, I have several concerns about the validity of experimental settings due to the lack of several key controls essential to interpret the experimental results. The manuscript also needs a few additional functional assays to reach the accurate conclusions as proposed.

(1) AlphaFold model predicts that Mre11-Rev7 and Rad50-Rev7 binding interfaces overlap and Rev7 might bind only to Mre11 or Rad50 at a time. Interestingly, however, Rev7 appears dimerized (Figure 1). Since the MR complex also forms with 2M and 2R in the complex, it should still be possible if REV7 can interact with +-*both M and R in the MR complex. The author should perform MST using MR complex instead of individual MR components. The authors should also analyze if Rev7-C1 is indeed deficient in interaction with MR individually and with complex using MST assay.

(2) The nuclease and the ATPase assays require additional controls. Does Rev7 inhibit the other nuclease or ATPase non-specifically? Are these outcomes due to the non-specific or promiscuous activity of Rev7? In Figure 6, the effect of REV7 on the ATP binding of Rad50 could be hard to assess because the maximum Rad50 level (1 uM) was used in the experiments. The author should use the suboptimal level of Rad50 to check if REV7 still does not influence ATP binding by Rad50.

(3) The moderate deficiency in NHEJ using plasmid-based assay in REV7 deleted cells can be attributed to aberrant cell cycle or mating type in rev7 deleted cells. The authors should demonstrate that rev7 deleted cells retain largely normal cell cycle patterns and the mating type phenotypes. The author should also analyze the breakpoints in plasmid-based NHEJ assays in all mutants, especially from rev7 and rev7-C1 cells.

(4) It is puzzling why the authors did not analyze end resection defects in rev7 deleted cells after a DSB. The author should employ the widely used resection assay after a HO break in rev3, rev7, and mre11 rev7 cells as described previously.

(5) Is it possible that Rev7 also contributes to NHEJ as the part of TLS polymerase complex? Although NHEJ largely depends on Pol4, the authors should not rule out that the observed NHEJ defect in rev7 cells is due at least partially to its TLS defect. In fact, both rev3 or rev1 cells are partially defective in NHEJ (Figure 7). Rev7-C1 is less deficient in NHEJ than REV7 deletion. These results predict that rev7-C1 rev3 should be as defective as the rev7 deletion. Additionally, the authors should examine if Rev7-C1 might be deficient in TLS. In this regard, does rev7-C1 reduce TLS and TLS-dependent mutagenesis? Is it dominant? The authors should also check if Rev3 or Rev1 are stable in Rev7 deleted or rev7-C1 cells by immunoblot assays.

(6) Due to the G4 DNA and G4 binding activity of REV7, it is not clear which class of events the authors are measuring in plasmid-chromosome recombination assay in Figure 9. Do they measure G4 instability or the integrity of recombination or both in rev7 deleted cells? Instead, the effect of rev7 deletion or rev7-C1 on recombination should be measured directly by more standard mitotic recombination assays like mating type switch or his3 repeat recombination.

eLife assessment

This important study investigates, from Drosophila to mammals, the role of the Forkhead box O (FoxO) transcription factors in airway epithelial cells' response to stressors including hypoxia, temperature variations, and oxidative stress. The findings suggest a conserved role of FoxO in maintaining airway homeostasis across species. However, limitations in the specificity and concerns with the loss-of-function experiments render the evidence presented incomplete. Nonetheless, this study highlights FoxO's potential relevance in respiratory diseases like asthma and offers insights into potential therapeutic targets for conditions affecting airway health.

Joint Public Review

This work investigates the evolutionary conservation and functional significance of FoxO transcription factors in the response of airway epithelia to diverse stressors, ranging from hypoxia to temperature fluctuations and oxidative stress. Utilizing a comprehensive approach encompassing Drosophila, murine models, and human samples, the study investigates FoxO's role across species. The authors demonstrate that hypoxia triggers a dFOXO-dependent immune response in Drosophila airways, with subsequent nuclear localization of dFOXO in response to various stressors. Transcriptomic analysis reveals differential regulation of crucial gene categories in respiratory tissues, highlighting FoxO's involvement in metabolic pathways, DNA replication, and stress resistance mechanisms.

The study underscores FoxO's importance in maintaining homeostasis by revealing reduced stress resistance in dFOXO Drosophila mutants, shedding light on its protective role against stressors. In mammalian airway cells, FoxO exhibits nuclear translocation in response to hypoxia, accompanied by upregulation of cytokines with antimicrobial activities. Intriguingly, mouse models of asthma show FoxO downregulation, which is also observed in sputum samples from human asthma patients, implicating FoxO dysregulation in respiratory pathologies.

Overall, the manuscript suggests that FoxO signaling plays a critical role in preserving airway epithelial cell homeostasis under stress conditions, with implications for understanding and potentially treating respiratory diseases like asthma. By providing compelling evidence of FoxO's involvement across species and its correlation with disease states, the study underscores the importance of further exploration into FoxO-mediated mechanisms in respiratory health.

Strengths

(1) This study shows that FoxO transcription factors are critical for regulating immune and inflammatory responses across species, and for orchestrating responses to various stressors encountered by airway epithelial cells, including hypoxia, temperature changes, and oxidative stress. Understanding the intricate regulation of FoxO transcription factors provides insights into modulating immune and inflammatory pathways, offering potential avenues for therapeutic interventions against respiratory diseases and other illnesses.

(2) The work employs diverse model systems, including Drosophila, murine models, and human samples, thereby establishing a conserved role for FoxOs in airway epithelium and aiding translational relevance to human health.

(3) The manuscript establishes a strong correlation between FoxO expression levels and respiratory diseases such as asthma. Through analyses of both murine models of asthma and asthmatic human samples, the study demonstrates a consistent reduction in FoxO expression, indicating its potential involvement in the pathogenesis of respiratory disorders. This correlation underscores the clinical relevance of FoxO dysregulation and opens avenues for developing treatments for respiratory conditions like asthma, COPD, and pulmonary fibrosis, addressing significant unmet clinical needs.

(4) The study unveils intriguing mechanistic details regarding FoxO regulation and function. Particularly noteworthy is the observation of distinct regulatory mechanisms governing dFOXO translocation in response to different stressors. The independence of hypoxia-induced dFOXO translocation from JNK signaling adds complexity to our understanding of FoxO-mediated stress responses. Such mechanistic insights deepen our understanding of FoxO biology and pave the way for future investigations into the intricacies of FoxO signaling pathways in airway epithelial cells.

Weaknesses

(1) The manuscript does not distinguish between FoxO expression levels and FoxO activation status. While FoxO nuclear localization is observed in Drosophila and murine models, it remains unclear whether this reflects active FoxO signaling or merely FoxO expression, limiting the mechanistic understanding of FoxO regulation.

(2) The manuscript utilizes various stressors across different experiments without providing a clear rationale for their selection. This lack of coherence in stressor choice complicates the interpretation of results and diminishes the ability to draw meaningful comparisons across experiments.

(3) The manuscript frequently refers to "FoxO signaling" without providing specific signaling readouts. This ambiguity undermines the clarity of the conclusions drawn from the data and hinders the establishment of clear cause-and-effect relationships between FoxO activation and cellular responses to stress.

(4) Many conclusions drawn in the manuscript rely heavily on the quantification of immunostaining images for FoxO nuclear localization. While this is an important observation, it does not provide a sufficient mechanistic understanding of FoxO expression or activation regulation.

(5) The primary weakness in the Drosophila experiments is the analysis of dFoxO in homozygous dFoxO mutant animals, which precludes determining the specific role of dFoxO in airway cells. Despite available tools for tissue-specific gene manipulation, such as tissue-specific RNAi and CRISPR techniques, these approaches were not employed, limiting the precision of the findings.

(6) In mammalian experiments, the results are primarily correlative, lacking causal evidence. While changes in FoxO expression are observed under pathological conditions, the absence of experiments on FoxO-deficient cells or tissues precludes establishing a causal relationship between FoxO dysregulation and respiratory pathologies.

(7) Although the evidence suggests a critical role for FoxO in airway tissues, the precise nature of this role remains unclear. With gene expression changes analyzed only in Drosophila, the extent of conservation in downstream FoxO-mediated pathways between mammals and Drosophila remains uncertain. Additionally, the functional consequences of FoxO deficiency in airway cells were not determined, hindering comparisons between species and limiting insights into FoxO's functional roles in different contexts.

eLife assessment

This fundamental study provides insights into how pathogens respond, on a systemic level including several gene targets and clusters, to selected antimicrobial molecules. Compelling evidence is provided, through multi-omics and functional approaches, that very similar molecules originally designed to target the same bacterial protein act differently within the context of the whole set of cellular transcripts, expressed proteins, and pre-lethal metabolic changes. Given the incredibly fast accumulation of omics data to date and the much slower capacity of extracting biologically relevant insights from big data, this work exemplifies how the development of sensitive data analysis is still a major necessity in modern research.

Reviewer #1 (Public Review):

In this manuscript, entitled " Merging Multi-OMICs with Proteome Integral Solubility Alteration Unveils Antibiotic Mode of Action", Dr. Maity and colleagues aim to elucidate the mechanisms of action of antibiotics through combined approaches of omics and the PISA tool to discover new targets of five drugs developed against Helicobacter pylori.

Strengths:

Using transcriptomics, proteomic analysis, protein stability (PISA), and integrative analysis, Dr. Maity and colleagues have identified pathways targeted by five compounds initially discovered as inhibitors against H. pylori flavodoxin. This study underscores the necessity of a global approach to comprehensively understanding the mechanisms of drug action. The experiments conducted in this paper are well-designed and the obtained results support the authors' conclusions.

Weaknesses:

This manuscript describes several interesting findings. A few points listed below require further clarification:

(1) Compounds IVk exhibits markedly different behavior compared to the other compounds. The authors are encouraged to discuss these findings in the context of existing literature or chemical principles.

(2) The incubation time for treating H. pylori with the drugs was set at 4 hours for transcriptomic and proteomic analyses, compared to 20 min for PISA analysis. The authors need to explain the reason for these differences in treatment duration.

(3) The PISA method facilitates the identification of proteins stabilized by drug treatment. DnaJ and Trigger factor (tig), well-known molecular chaperones, prevent protein aggregation under stress. Their enrichment in the soluble fraction is expected and does not necessarily indicate direct stabilization by the drugs. The possibility that their stabilization results from binding to other proteins destabilized by the drugs should be considered. To prevent any misunderstanding, the authors should clarify that their methodology does not solely identify direct targets. Instead, the combination of their findings sheds light on various pathways affected by the treatment.

(4) At the end of the manuscript, the authors conclude that four compounds "strongly interact with CagA". However, detailed molecule/protein interaction studies are necessary to definitively support this claim. The authors should exercise caution in their statement. As the authors mentioned, additional research (not mandated in the scope of this current paper) is necessary to determine the drug's binding affinity to the proposed targets.

(5) The authors should clarify the PISA-Express approach over standard PISA. A detailed explanation of the differences between both methods in the main text is important.

Reviewer #2 (Public Review):

Summary:

This work has an important and ambitious goal: understanding the effects of drugs, in this case antimicrobial molecules, from a holistic perspective. This means that the effect of drugs on a group of genes and whole metabolic pathways is unveiled, rather than its immediate effect on a protein target only. To achieve this goal the authors successfully implement the PISA-Express method (Protein Integral Solubility Alteration), using combined transcriptomics, proteomics, and drug-induced changes in protein stability to retrieve a large number of genes and proteins affected by the used compounds. The compounds used in the study (compound IVa, IVb, IVj, and IVk) were all derived from the precursors compound IV, they are effective against Helicobacter pylori, and their mode of action on clusters of genes and proteins has been compared to the one of the known pylori drug metronidazole (MNZ). Due to this comparison, and confirmed by the diversity of responses induced by these very similar compounds, it can be understood that the approach used is reliable and very informative. Notably, although all compound IV derivatives were designed to target pylori Flavodoxin (Fld), only one showed a statistically significant shift of Fld solubility (compound IVj, FIG S11). For most other compounds, instead, the involvement of other possible targets affecting diverse metabolic pathways was also observed, notably concerning a series of genes with other important functions: CagA (virulence factor), FtsY/FtsA (cell division), AtpD (ATP-synthase complex), the essential GTPase ObgE, Tig (protein export), as well as other proteins involved in ribosomal synthesis, chemotaxis/motility and DNA replication/repairs. Finally, for all tested molecules, in vivo functional data have been collected that parallel the omics predictions, comforting them and showing that compound IV derivatives differently affect cellular generation of reactive oxygen species (ROS), oxygen consumption rates (OCR), DNA damage, and ATP synthesis.

Strengths:

The approach used is very potent in retrieving the effects of chemically active molecules (in this case antimicrobial ones) on whole cells, evidencing protein and gene networks that are involved in cell sensitivity to the studied molecules. The choice of these compounds against H. pylori is perfect, showcasing how different the real biological response is, compared to the hypothetical one. In fact, although all molecules were retrieved based on their activity on Fld, the authors unambiguously show that large unexpected gene clusters may, and in fact are, affected by these compounds, and each of them in different manners.

Impact:

The present work is the first report relying on PISA-Express performed on living bacterial cells. Because of its findings, this work will certainly have a high impact on the way we design research to develop effective drugs, allowing us to understand the fine effects of a drug on gene clusters, drive molecule design towards specific metabolic pathways, and eventually better plan the combination of multiple active molecules for drug formulation. Beyond this, however, we expect this article to impact other related and unrelated fields of research as well. The same holistic approaches might also allow gaining deep, and sometimes unexpected, insight into the cellular targets involved in drug side effects, drug resistance, toxicity, and cellular adaptation, in fields beyond the medicinal one, such as cellular biology and environmental studies on pollutants.

eLife assessment

This important study reveals how Drosophila may be used to investigate the role of missense variants in the gene PLCG1 related to human disease in case studies. The evidence that most of these variants have a gain-of-function effect in the fly is convincing and supportive of their pathogenic effect. With some additional control experiments to assess overexpression toxicity, this work would be of relevance to human and Drosophila geneticists alike.

Reviewer #1 (Public Review):

Summary:

This manuscript provides an initial characterization of three new missense variants of the PLCG1 gene associated with diverse disease phenotypes, utilizing a Drosophila model to investigate their molecular effects in vivo. Through the meticulous creation of genetic tools, the study assesses the small wing (sl) phenotype - the fly's ortholog of PLCG1 - across an array of phenotypes from longevity to behavior in both sl null mutants and variants. The findings indicate that the Drosophila PLCG1 ortholog displays aberrant functions. Notably, it is demonstrated that overexpression of both human and Drosophila PLCG1 variants in fly tissue leads to toxicity, underscoring their pathogenic potential in vivo.

Strengths:

The research effectively highlights the physiological significance of sl in Drosophila. In addition, the study establishes the in vivo toxicity of disease-associated variants of both human PLCG1 and Drosophila sl.

Weaknesses:

The study's limitations include the human PLCG1 transgene's inability to compensate for the Drosophila sl null mutant phenotype, suggesting potential functional divergence between the species. This discrepancy signals the need for additional exploration into the mechanistic nuances of PLCG1 variant pathogenesis, especially regarding their gain-of-function effects in vivo.

Overall:

The study offers compelling evidence for the pathogenicity of newly discovered disease-related PLCG1 variants, manifesting as toxicity in a Drosophila in vivo model, which substantiates the main claim by the authors. Nevertheless, a deeper inquiry into the specific in vivo mechanisms driving the toxicity caused by these variants in Drosophila could significantly enhance the study's impact.

Reviewer #2 (Public Review):

The manuscript by Ma et al. reports the identification of three unrelated people who are heterozygous for de novo missense variants in PLCG1, which encodes phospholipase C-gamma 1, a key signaling protein. These individuals present with partially overlapping phenotypes including hearing loss, ocular pathology, cardiac defects, abnormal brain imaging results, and immune defects. None of the patients present with all of the above phenotypes. PLCG1 has also been implicated as a possible driver for cell proliferation in cancer.

The three missense variants found in the patients result in the following amino acid substitutions: His380Arg, Asp1019Gly, and Asp1165Gly. PLCG1 (and the closely related PLCG2) have a single Drosophila ortholog called small wing (sl). sl-null flies are viable but have small wings with ectopic wing veins and supernumerary photoreceptors in the eye. As all three amino acids affected in the patients are conserved in the fly protein, in this work Ma et al. tested whether they are pathogenic by expressing either reference or patient variant fly or human genes in Drosophila and determining the phenotypes produced by doing so.

Expression in Drosophila of the variant forms of PLCG1 found in these three patients is toxic; highly so for Asp1019Gly and Asp1165Gly, much more modestly for His380Arg. Another variant, Asp1165His which was identified in lymphoma samples and shown by others to be hyperactive, was also found to be toxic in the Drosophila assays. However, a final variant, Ser1021Phe, identified by others in an individual with severe immune dysregulation, produced no phenotype upon expression in flies.

Based on these results, the authors conclude that the PLCG1 variants found in patients are pathogenic, producing gain-of-function phenotypes through hyperactivity. In my view, the data supporting this conclusion are robust, despite the lack of a detectable phenotype with Ser1021Phe, and I have no concerns about the core experiments that comprise the paper.

Figure 6, the last in the paper, provides information about PLCG1 structure and how the different variants would affect it. It shows that the His380, Asp1019, and Asp1165 all lie within catalytic domains or intramolecular interfaces and that variants in the latter two affect residues essential for autoinhibition. It also shows that Ser1021 falls outside the key interface occupied by Asp1019, but more could have been said about the potential effects of Ser1021Phe.

Overall, I believe the authors fully achieved the aims of their study. The work will have a substantial impact because it reports the identification of novel disease-linked genes, and because it further demonstrates the high value of the Drosophila model for finding and understanding gene-disease linkages.

Reviewer #3 (Public Review):

Summary:

The paper attempts to model the functional significance of variants of PLCG2 in a set of patients with variable clinical manifestations.

Strengths:

A study attempting to use the Drosophila system to test the function of variants reported from human patients.

Weaknesses:

Additional experiments are needed to shore up the claims in the paper. These are listed below.

Major Comments:

(1) Does the pLI/ missense constraint Z score prediction algorithm take into consideration whether the gene exhibits monoallelic or biallelic expression?

(2) Figure 1B: Include human PLCG2 in the alignment that displays the species-wide conserved variant residues.

(3) Figure 4A:<br /> Given that<br /> (i) sl is predicted to be the fly ortholog for both mammalian PLCγ isozymes: PLCG1 and PLCG2 [Line 62]<br /> (ii) they are shown to have non-redundant roles in mammals [Line 71] and<br /> (iii) reconstituting PLCG1 is highly toxic in flies, leading to increased lethality.<br /> This raises questions about whether sl mutant phenotypes are specifically caused by the absence of PLG1 or PLCG2 functions in flies. Can hPLCG2 reconstitution in sl mutants be used as a negative control to rule out the possibility of the same?

(4) Do slT2A/Y; UAS-PLCG1Reference flies survive when grown at 22{degree sign}C? Since transgenic fly expressing PLCG1 cDNA when driven under ubiquitous gal4s, Tubulin and Da, can result in viable progeny at 22{degree sign}C, the survival of slT2A/Y; UAS-PLCG1Reference should be possible.<br /> and similarly<br /> Does slT2A flies exhibit the phenotypes of (i) reduced eclosion rate (ii) reduced wing size and ectopic wing veins and (iii) extra R7 photoreceptor in the fly eye at 22{degree sign}C?<br /> If so, will it be possible to get a complete rescue of the slT2A mutant phenotypes with the hPLCG1 cDNA at 22{degree sign}C? This dataset is essential to establish Drosophila as an ideal model to study the PLCG1 de novo variants.

(5) Localisation and western blot assays to check if the introduction of the de novo mutations can have an impact on the sub-cellular targeting of the protein or protein stability respectively.

(6) Analysing the nature of the reported gain of function (experimental proof for the same is missing in the manuscript) variants:<br /> Instead of directly showing the effect of introducing the de novo variant transgenes in the Drosophila model especially when the full-length PLCG1 is not able to completely rescue the slT2A phenotype;<br /> (i) Show that the gain-of-function variants can have an impact on the protein function or signalling via one of the three signalling outputs in the mammalian cell culture system: (i) inositol-1,4,5-trisphosphate production, (ii) intracellular Ca2+ release or (iii) increased phosphorylation of extracellular signal-related kinase, p65, and p38.<br /> OR<br /> (ii) Run a molecular simulation to demonstrate how the protein's auto-inhibited state can be disrupted and basal lipase activity increased by introducing D1019G and D1165G, which destabilise the association between the C2 and cSH2 domains. The H380R variant may also exhibit characteristics similar to the previously documented H335A mutation which leaves the protein catalytically inactive as the residue is important to coordinate the incoming water molecule required for PIP2 hydrolysis.

(7) Clarify the reason for carrying out the wing-specific and eye-specific experiments using nub-gal4 and eyless-gal4 at 29˚C despite the high gal4 toxicity at this temperature.

(8) For the sake of completeness the authors should also report other variants identified in the genomes of these patients that could also contribute to the clinical features.

įjungtas RA ON ir mažinu srovę iki 1,2W. Labai svarbu tai padaryti dabar, nes vėliau apertūros užstos ir nežinorime kokia galia šviečia.

سلام اینجا داره افراق میکنه

시민왕 파리에 적게 개입

시민왕

지구. 외곽이려나? 팽창? 이거는 확인 필요하다

1930년대 인구 80만 찍고, 비위생적인 곳에는 노동자가 개인 주도의 현대적 구획 -> 중산층

• 루이18세 때는 토목건축보다는 개조에 초점
• 아케이드 증가

루이18세 시기의 센 지사 - 시 재정 회복과 부채 청산이 목표

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.왕정복고에서 할 수 있던 일

왕정복고 후 지출 제한

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제1제정 몰락, 루이18세 왕정복고

1802 공공 위생에 대한 관심과 보건 관련 기관의 설립. 나무의 중요성이 부각되는 기초

(이후) 19세기 후반 서구의 위생 및 공중보건학 발달. 상하수도 체계 확립(안전한 식수 공급, 콜레라, 이질 등 예방), 주택 청결, 해충 박멸 등 목표

동전의 양면 - 회복과 안정 - 인구의 증가

1809년 나폴레옹1세 시기에 나중에 나폴레옹 4세와 오스만이 구현할 도시개조에 대한 요구가 있었음. 이미 -> 하지만 제국의 몰락

튈르리의 입구이자 전망 닫기

중요 나폴레옹 1세의 도시 건설 프로젝트 "파리의 장식" embellishment

기존 시스템 시장, 지역구에도 대표가 있고, 경찰청장이 있어 충돌

중요. 센 강 지사의 권력이 컸다. 총리에 버금가나? 일종의 장관

시장? 센 강 지사 -> 정확한 표현 확인 - 제정과 행정시스템의 출범

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행정적 지리. 이거 중요 원문확인

행정적으로 운영되는 지역 단위

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확장하는 제국 프랑스의 수도로서 파리, 유럽의 수도로

혼란에 지친 시민들에 대한 증언

이전 왕실의 장소들이 입법부, 상원, 황제 등등 자리를 내줌

중요 혁명은 파괴했지만 건설한 것은 별로 없었따. 인용하기 너무 좋다. 좋은 문장

• 1789-1799 내전, 외부전쟁을 동반한 경제 및 식량 위기로 인구 10만 줄은 듯 원문확인

왕정주의 진압한 장군 나폴레옹 보나파르트 , 그는 황제가 된다. 제정으로

왕실의 재산은 어떻게 되었나? 샹젤리제, 쿠르라헨 등

오 명칭의 변화. 시민!

루이15세의 광장이 혁명의 광장으로

튈르리 침공의 상징성. 샹젤리제까지도 민중의 승리를 의미하는 공간이 될 수 있겠다.

튈르리 공원? park? 입법부는 로열에게 충성햇으나 파리의 민중들이 왕을 몰락시켰다

산책로? 프롬미나드?

루이 16세 참수 전 튈르리/파리로 소환

혁명 후 첫 파리 시장

청산

Version 2 of this preprint has been peer-reviewed and recommended by Peer Community in Ecology.<br /> See the peer reviews and the recommendation.

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Eine extreme Hitzewelle hat in der Sahelzone Hunderte, wahrscheinlich Tausende Menschenleben gefordert. World Weather Attribution zufolge ist die Höhe der Temperaturen eindeutig auf die globale Erhitzung durch Treibhausgase zurückzuführen. https://www.theguardian.com/environment/2024/apr/18/lethal-heatwave-in-sahel-worsened-by-fossil-fuel-burning-study-finds

Zur Studie: https://www.worldweatherattribution.org/extreme-sahel-heatwave-that-hit-highly-vulnerable-population-at-the-end-of-ramadan-would-not-have-occurred-without-climate-change/

This passage highlights the critical issue of misunderstanding and misjudging parental actions based on cultural and socioeconomic differences. The story of David’s mother, who despite her unconventional appearance, demonstrated her deep care and commitment by organizing a birthday party, illustrates the quick judgments educators often make. This resonates with me because it underscores the importance of empathy and understanding in education, especially towards parents from diverse backgrounds. Recognizing the intent behind actions, rather than just the actions themselves, could foster a more supportive and inclusive school environment.

The cultural nuances affecting educational assessments, particularly in Latino and Native American communities, captivate me due to their profound implications on equitable teaching practices. The Latino girls’ hesitance to showcase their knowledge in mixed-gender settings and the Native American students’ struggle with traditional academic tasks like summarizing, due to cultural norms against speaking for others, underline the necessity for culturally responsive education. These examples drive home the importance of educators understanding and adapting to the diverse cultural backgrounds of their students to foster an inclusive and effective learning environment.

The segment discussing the interaction between the cultural backgrounds of students and teachers caught my attention because it highlights how easily a student’s capabilities can be misunderstood due to cultural differences. Marti’s example, where her use of language was misinterpreted by her teacher, showcases the need for educators to have a deeper understanding and appreciation of linguistic diversity. This resonates with me as it underlines the importance of cultural competence in education, where recognizing and valuing diverse forms of expression can enrich the learning experience and better support all students.

This passage on the dynamics of teacher-student interaction across different cultural and ethnic backgrounds highlights the significant impact of communication styles in education. The differentiation in how teachers from diverse backgrounds express authority and set expectations resonates with me because it showcases how cultural misunderstandings can hinder effective teaching and learning. It emphasizes the need for culturally responsive teaching strategies that acknowledge and adapt to the varied backgrounds of students to enhance educational outcomes and mutual respect.

This is interesting because it's about more than just cultural differences. It includes how societal expectations and norms influence behavior, not just for boys more than girls, but for everyone.

I didn't realize before that the way people talk can influence who they become friends with. But it makes sense that if people speak similarly, they're more likely to connect and become friends.

I agree with this idea. Every child is unique and should be seen as their own person. It's difficult to shape them or tell them how to behave when they are still learning everything.

是打击打击的成都市

https://shopgoodwill.com/item/196139225

Nebo is a Mac app for handwritten notes. Its OCR claims to do English plus one of 66 other languages both. First time I've seen that. Q remains: does it do so simultaneously in a single note, or as selected per note? My e-ink device allows a range of languages but not at the same time, I need to switch the setting, and applies one language to one note. This clashes with the fact that multilingual users will use multiple languages inside their notes at the same time. n:: [[Multilingual is not multiple monolingual 20191019072010]] obv https://www.zylstra.org/blog/2019/10/adding-better-language-support-ii/

The discussion of “educación” in this text strongly resonates with me as it broadens the conventional definition of education beyond mere academic achievement to include moral and ethical development. It challenges the impersonal, test-driven approach prevalent in many educational systems today and emphasizes the importance of nurturing a holistic sense of responsibility and care towards others. This approach aligns with my belief that education should foster not only intellectual but also personal growth, encouraging students to become compassionate and responsible citizens.

The concept of “subtractive schooling” is a powerful lens through which to view the impact of educational policies on minority students. It effectively captures how assimilationist approaches can strip students of their linguistic and cultural identities, rather than enriching their educational experience with their native heritage. This resonates with me as it challenges the conventional perspective on bilingual education and emphasizes the need for more inclusive and affirming educational practices that recognize and build upon the diverse backgrounds of students.

The dynamics within Seguin High School, where educational challenges are compounded by high dropout rates and low parental education levels, are reflective of broader systemic issues in education. It’s concerning to see how the blame for educational failures often falls on students and their families rather than addressing systemic inadequacies. This reinforces my belief in the need for a holistic approach to educational reform that includes community engagement and reevaluation of educational policies and practices. The entrenched nature of these issues at Seguin highlights the difficulty of effecting meaningful change in such settings.

address and phone numbers for Henry Dreyfuss, the industrial designer responsible for the The Western Electric model 500 telephone series and the later princess phone.

South Pasadena City Directory, 1961-1962<br /> by California Directory Publishing Co. https://archive.org/details/csp_000062/page/n21/mode/2up?view=theater