Reviewer #2 (Public review):

Summary:

This study genetically identifies two key enzymes involved in the biosynthesis of glycosphingolipids, GlcT and Egh, act as tumor suppressors in the adult fly gut. Detailed genetic analysis indicates that a deficiency in Mactosyl-ceramide (Mac-Cer) is causing tumor formation. Analysis of a Notch transcriptional reporter further indicates that the lack of Mac-Ser is associated with reduced Notch activity in the gut, but not in other tissues.

Addressing how a change in the lipid composition of the membranes might lead to defective Notch receptor activation, the authors studied the endocytic trafficking of Delta and claimed that internalized Delta appeared to accumulate faster into endosomes in the absence of Mac-Cer. Further analysis of Delta steady state accumulation in fixed samples suggested a delay in the endosomal trafficking of Delta from Rab5+ to Rab7+ endosomes, which was interpreted to suggest that the inefficient, or delayed, recycling of Delta might cause a loss in Notch receptor activation.

Finally, the histological analysis of mouse guts following the conditional knock-out of the GlcT gene suggested that Mac-Cer might also be important for proper Notch signaling activity in that context.

Strengths:

The genetic analysis is of high quality. The finding that a Mac-Cer deficiency results in reduced Notch activity in the fly gut is important and fully convincing.

The mouse data, although preliminary, raised the possibility that the role of this specific lipid may be conserved across species.

Reviewer #2 (Public review):

Summary:

The authors investigated whether the total DNA concentration in gastric fluid (gfDNA), collected via routine esophagogastroduodenoscopy (EGD), could serve as a diagnostic and prognostic biomarker for gastric cancer. In a large patient cohort (initial n=1,056; analyzed n=941), they found that gfDNA levels were significantly higher in gastric cancer patients compared to non-cancer, gastritis, and precancerous lesion groups. Unexpectedly, higher gfDNA concentrations were also significantly associated with better survival prognosis and positively correlated with immune cell infiltration. The authors proposed that gfDNA may reflect both tumor burden and immune activity, potentially serving as a cost-effective and convenient liquid biopsy tool to assist in gastric cancer diagnosis, staging, and follow-up.

Strengths:

This study is supported by a robust sample size (n=941) with clear patient classification, enabling reliable statistical analysis. It employs a simple, low-threshold method for measuring total gfDNA, making it suitable for large-scale clinical use. Clinical confounders, including age, sex, BMI, gastric fluid pH, and PPI use, were systematically controlled. The findings demonstrate both diagnostic and prognostic value of gfDNA, as its concentration can help distinguish gastric cancer patients and correlates with tumor progression and survival. Additionally, preliminary mechanistic data reveal a significant association between elevated gfDNA levels and increased immune cell infiltration in tumors (p=0.001).

Weaknesses:

The study has several notable weaknesses. The association between high gfDNA levels and better survival contradicts conventional expectations and raises concerns about the biological interpretation of the findings. The diagnostic performance of gfDNA alone was only moderate, and the study did not explore potential improvements through combination with established biomarkers. Methodological limitations include a lack of control for pre-analytical variables, the absence of longitudinal data, and imbalanced group sizes, which may affect the robustness and generalizability of the results. Additionally, key methodological details were insufficiently reported, and the ROC analysis lacked comprehensive performance metrics, limiting the study's clinical applicability.

Reviewer #3 (Public review):

Summary:

This study concerns how macaque visual cortical area MT represents stimuli composed of more than one speed of motion.

Strengths:

The study is valuable because little is known about how the visual pathway segments and preserves information about multiple stimuli. The study presents compelling evidence that (on average) MT neurons shift from faster-speed-takes-all at low speeds to representing the average of the two speeds at higher speeds. An additional strength of the study is the inclusion of perceptual reports from both humans and one monkey participant performing a task in which they judged whether the stimuli involved one vs two different speeds. Ultimately, this study raises intriguing questions about how exactly the response patterns in visual cortical area MT might preserve information about each speed, since such information is potentially lost in an average response as described here.

Reviewing Editor comment on revised version:

The remaining concern was resolved.

Reviewer #2 (Public review):

Summary:

This revised study provides a clearer and more mechanistically grounded explanation of how lipid metabolic imbalance contributes to EMT-associated chemoresistance in renal cancer. In this study, the authors discovered that chemoresistance in RCC cell lines correlates with the expression levels of ABCA1 and the EMT-related transcription factor Snail. They demonstrate that Snail induces ABCA1 expression and chemoresistance, and that inhibition of ABCA1-associated pathways can counteract this resistance. The study also suggests that Snail disrupts the cholesterol-sphingomyelin balance by repressing enzymes involved in VLCFA-sphingomyelin synthesis, leading to excess free cholesterol and activation of the LXR-ABCA1 axis. Importantly, inhibiting cholesterol esterification, which renders free cholesterol inert, selectively suppresses growth of a xenograft model of Snail-positive kidney cancer. These findings provide potential lipid metabolism-targeting strategies for cancer therapy. The revised version includes additional quantitative analyses and new experiments addressing lipid balance and ABCA1 localization, further strengthening the overall mechanistic model.

Strengths:

This revised manuscript provides a more comprehensive and convincing mechanistic explanation for how Snail-driven EMT induces chemoresistance through altered lipid homeostasis. The study presents a novel concept in which the Chol/SM balance, rather than individual lipid levels, shapes therapeutic vulnerability. The potential for targeting cholesterol detoxification pathways in Snail-positive cancer cells remains a significant therapeutic implication. In the revised version, the authors provide additional quantitative analyses and complementary experiments - including ABCA1 localization, restoration of VLCFA-SM levels by supplementation with C22:0 ceramide, and membrane-order assays - which further strengthen the mechanistic interpretation and address key concerns raised in earlier reviews.

Weaknesses:

The revised version includes new experiments showing that restoring sphingomyelin levels suppresses ABCA1 expression, thereby strengthening the causal link between altered lipid balance and ABCA1 induction. However, the evidence that ABCA1 is directly required for chemoresistance remains somewhat limited, as the phenotype was not reproduced by ABCA1 knockout or knockdown, and CsA may affect additional targets beyond ABCA1.

Reviewer #2 (Public review):

Modulating the UPR by pharmacological targeting of its sensors (or regulators) provides mostly uncharted opportunities in diseases associated with protein misfolding in the secretory pathway. Spearheaded by the Kelly and Wiseman labs, ATF6 modulators were developed in previous years that act on ER PDIs as regulators of ATF6. However, hurdles in their medicinal chemistry have hampered further developments. In this study, the authors provide evidence that the small molecule AA263 also targets and covalently modifies ER PDIs with the effect of activating ATF6. Importantly, AA263 turned out to be amenable to chemical optimization while maintaining its desired activity. Building on this, the authors show that AA263 derivatives can improve aggregation, trafficking and function of two disease-associated mutants of secretory pathway proteins. Together, this study provides compelling evidence for AA263 (and its derivatives) being interesting modulators of ER proteostasis. Mechanistic details of its mode of action will need more attention in future studies that can now build on this.

In detail, the authors provide strong evidence that AA263 covalently binds to ER PDIs, which will inhibit the protein disulfide isomerase activity. ER PDIs regulate ATF6, and thus their finding provides a mechanistic interpretation of AA263 activating the UPR. It should be noted, however, that AA263 shows broad protein labeling (Fig. 1G) which may suggest additional targets, beyond the ones defined as MS hits in this study. Also, a further direct analysis of the IRE1 and PERK pathways (activated or not by AA263) may be an interesting future directions, as e.g. PDIA1, a target of AA263, directly regulates IRE1 (Yu et al., EMBOJ, 2020) and other PDIs also act on PERK and IRE1. The authors interpret modest activation of IRE1/PERK target genes (Fig. 2C) as an effect on target gene overlap, indeed the most likely explanation based on their selective analyses on IRE1 (ERdj4) and PERK (CHOP) downstream genes, but direct activation due to the targeting of their PDI regulators is also a possible explanation. Further key findings of this paper are the observed improvement of AAT behavior and GABAA trafficking and function. Further strength to the mechanistic conclusion that ATF6 activation causes this could be obtained by using ATF6 inhibitors/knockouts in the presence of AA263 (as the target PDIs may directly modulate behavior of AAT and/or GABAA). Along the same line, it also warrants further investigation in future studies why the different compounds, even if all were used at concentrations above their EC50, had different rescuing capacities on the clients.

Together, the study now provides a strong basis for such in-depth mechanistic analyses.

Reviewer #2 (Public review):

Summary:

This manuscript analyzes the contribution of Traf4 to the fate of epithelial cells in the developing wing imaginal disc tissue. The manuscript is direct and concise and suggests an interesting and valuable hypothesis with dual functions of Traf4 in JNK pathway activation and cell delamination. However, the text is partially speculative, and the evidence is incomplete as the main claims are only partially supported. Some results require validation to support the conclusions.

Strengths:

(1) The manuscript is direct and concise, with a well-written and precise introduction.

(2) It presents an interesting and valuable hypothesis regarding the dual role of Traf4 in JNK pathway activation and cell delamination.

(3) The study addresses a relevant biological question in epithelial tissue development using a genetically tractable model.

(4) The use of newly generated Traf4 mutants adds novelty to the experimental approach.

(5) The manuscript includes multiple experimental strategies, such as genetic manipulation and imaging, to explore Traf4 function.

Weaknesses:

(1) The evidence supporting key claims is incomplete, and some conclusions are speculative.

(2) The use of GFP-tagged Traf4 lacks validation regarding its functional integrity.

(3) Orthogonal views and additional imaging data are needed to confirm changes in apicobasal localization and cell delamination.

(4) Experimental conditions and additional methods should be further detailed.

(5) The interaction between Traf4 and E(spl)m4 remains speculative in Drosophila.

(6) New mutants require deeper analysis and validation.

(7) The elimination of Traf4 mutant clones may be due to cell competition, which requires further experimental clarification.

(8) The role of Traf4 in cell competition is contradictory and needs to be resolved.

Reviewer #2 (Public review):

Tanja Nielsen et al. presents a novel strategy for identification of candidate genes in Congenital Heart Disease (CHD). Their methodology, which is based on comprehensive experiments across cell models, drosophila and zebrafish models, represents an innovative, refreshing and very useful set of tools for identification of disease genes, in a field which are struggling with exactly this problem.

The authors have applied their methodology to investigate the pathomechanisms of Hypoplastic Left Heart Syndrome (HLHS) - a severe and rare subphenotype in the large spectrum of CHD malformations. Their data convincingly implicates ribosomal proteins (RPs) in growth and proliferation defects of cardiomyocytes, a mechanism which is suspected to be associated with HLHS.

By whole genome sequencing analysis of a small cohort of trios (25 HLHS patients and their parents) the authors investigated a possible association between RP encoding genes and HLHS.

Although the possible association between defective RPs and HLHS needs to be verified, the results suggest a novel disease mechanism in HLHS, which is a potentially substantial advance in our understanding of HLHS and CHD. The conclusions of the paper are based on solid experimental evidence from appropriate high- to medium-throughput models, while additional genetic results from an independent patient cohort is needed to verify an association between RP encoding genes and HLHS in patients.

Reviewer #2 (Public review):

Summary

The authors aimed to evaluate whether total DNA concentration in gastric fluid (gfDNA) collected during routine endoscopy could serve as a diagnostic and prognostic biomarker for gastric cancer. Using a large cohort (n=941), they reported elevated gfDNA in gastric cancer patients, an unexpected association with improved survival, and a positive correlation with immune cell infiltration.

Strengths

The study benefits from a substantial sample size, clear patient stratification, and control of key clinical confounders. The method is simple and clinically feasible, with preliminary evidence linking gfDNA to immune infiltration.

Weaknesses

(1) While the study identifies gfDNA as a potential prognostic tool, the evidence remains preliminary. Unexplained survival associations and methodological gaps weaken support for the conclusions.

(2) The paradoxical association between high gfDNA and better survival lacks mechanistic validation. The authors acknowledge but do not experimentally distinguish tumor vs. immune-derived DNA, leaving the biological basis speculative.

(3) Pre-analytical variables were noted but not systematically analyzed for their impact on gfDNA stability.

Comments on revisions:

To enhance the completeness and credibility of this research, it is essential to clarify the biological origin of gastric fluid DNA and validate these preliminary findings through a prospective, longitudinal study design.

Reviewer #2 (Public review):

Summary:

This paper considers the effects of cognitive load (using an n-back task related to font color), predictability, and age on reading times in two experiments. There were main effects of all predictors, but more interesting effects of load and age on predictability. The effect of load is very interesting, but the manipulation of age is problematic, because we don't know what is predictable for different participants (in relation to their age). There are some theoretical concerns about prediction and predictability, and a need to address literature (reading time, visual world, ERP studies).

There is a major concern about the effects of age. See the results (155-190): this depends what is meant by word predictability. It's correct if it means the predictability in the corpus. But it may or may not be correct if it refers to how predictable a word is to an individual participant. The texts are unlikely to be equally predictable to different participants, and in particular to younger vs. older participants, because of their different experience. To put it informally, the newspaper articles may be more geared to the expectations of younger people. But there is also another problem: the LLM may have learned on the basis of language that has largely been produced by young people and so its predictions are based on what young people are likely to say. Both of these possibilities strike me as extremely likely. So it may be that older adults are affected more by words that they find surprising, but it is also possible that the texts are not what they expect, or the LLM predictions from the text are not the ones that they would make. In sum, I am not convinced that the authors can say anything about the effects of age unless they can determine what is predictable for different ages of participants. I suspect that this failure to control is an endemic problem in the literature on aging and language processing and needs to be systematically addressed.

Overall, I think the paper makes enough of a contribution with respect to load to be useful to the literature. But for discussion of age, we would need something like evidence of how younger and older adults would complete these texts (on a word-by-word basis) and that they were equally predictable for different ages. I assume there are ways to get LLMs to emulate different participant groups, but I doubt if we could be confident about their accuracy without a lot of testing. But without something like this, I think making claims about age would be quite misleading.

The authors respond to my summary comment by saying that prediction is individual and that they account for age-related effects in their models. But these aren't my concerns. Rather:

(1) The texts (these edited newspaper articles) could be more predictable for younger than older adults. If so, effects with older adults could simply be because people are less likely to predict less than more predictable words.

(2) The GPT-2 generated surprisal scores may correspond more closely to younger than older adult responses -- that is, its next word predictions may be more younger- than older-adult-like.

In my view, the authors have two choices: they could remove the discussion of age-related effects, or they could try to address BOTH (1) and (2).

As an aside, consider what we would conclude if we drew similar conclusions from a study in which children and adults read the same (children's) texts, but we didn't test what was predictable to each of them separately.

The paper is really strong in other respects and if my concern is not addressed, the conclusions about age might be generally accepted.

Reviewer #2 (Public review):

Streptococcus pyogenes, or group A streptococci (GAS) can cause diseases ranging skin and mucosal infections, plasma invasion, and post-infection autoimmune syndromes. M proteins are essential GAS virulence factors that include an N-terminal hypervariable region (HVR). M proteins are known to bind to numerous human proteins; a small subset of M proteins were reported to bind collagen, which is thought to promote tissue adherence. In this paper, authors characterize M3 interactions with collagen and its role in biofilm formation. Specifically, they screened different collagen type II and III variants for full-length M3 protein binding using an ELISA-like method, detecting anti-GST antibody signal. By statistical analysis, hydrophobic amino acids and hydroxyproline found to positively support binding, whereas acidic residues and proline negatively impacted binding. The authors applied X-ray crystallography to determine the structure of the N-terminal domain (42-151 amino acids) of M3 protein (M3-NTD). M3-NTD dimmer (PDB 8P6K) forms a T-shaped structure with three helices (H1, H2, H3), which are stabilized by a hydrophobic core, inter-chain salt bridges and hydrogen bonds on H1, H2 helices, and H3 coiled coil. The conserved Gly113 serves as the turning point between H2 and H3. The M3-NTD is co-crystalized with a 24-residue peptide, JDM238, to determine the structure of M3-collagen binding. The structure (PDB 8P6J) shows that two copies of collagen in parallel bind to H1 and H2 of M3-NTD. Among the residues involved binding, conserved Try96 is shown to play a critical role supported by structure and isothermal titration calorimetry (ITC). The authors also apply a crystal-violet assay and fluorescence microscopy to determine that M3 is involved in collagen type I binding, but not M1 or M28. Tissue biopsy staining indicates that M3 strains co-localize with collagen IV-containing tissue, while M1 strains do not. The authors provide generally compelling evidence to show that GAS M3 protein binds to collagen, and plays a critical role in forming biofilms, which contribute to disease pathology. This is a very well-executed study and a well-written report relevant to understanding GAS pathogenesis and approaches to combatting disease; data are also applicable to emerging human pathogen Streptococcus dysgalactiae. One caveat that was not entirely resolved is if/how different collagen types might impact M3 binding and function. Due to the technical constrains, the in vitro structure and other binding assays use type II collagen whereas in vivo, biofilm formation assays and tissue biopsy staining use type I and IV collagen; it was unclear if this difference is significant. One possibility is that M3 has an unbiased binding to all types of collagens, only the distribution of collagens leads to the finding that M3 binds to type IV (basement membrane) and type I (varies of tissue including skin), rather than type II (cartilage).

Comments on revisions:

We are glad to see that the authors addressed our prior comments on M3 binding to different types of collagens in discussion section; adding a prediction of M3 binding to type I collagen (Figure 8-figure supplement 1B and 1C) is helpful to fill in the gap. Although it would be nice to experimentally fill in the gap by putting all types of collagens into one experiment (For example, like Figure 9A, use different types of human collagens to test biofilm formation; or Figure 10, use different types of human collagens to compete for biofilm formation), this appears to be beyond the scope of this paper. Meanwhile, the changes they have made are constructive.

The authors have addressed the majority of our prior comments.

Reviewer #2 (Public review):

Summary:

In this paper, the authors describe a novel function involving the cell cycle protein kinase CDK2, which binds to TBK1 (an essential component of the innate immune response) leading to its degradation in a ubiquitin/proteasome-dependent manner. Moreover, the E3 ubiquitin ligase, Dtx4, is implicated in the process by which CDK2 increases the K48-linked ubiquitination of TBK1. This paper presents intriguing findings on the function of CDK2 in lower vertebrates, particularly its regulation of IFN expression and antiviral immunity.

Strengths:

(1) The research employs a variety of experimental approaches to address a single question. The data are largely convincing and appear to be well executed.

(2) The evidence is strong and includes a combination of in vivo and in vitro experiments, including knockout models, protein interaction studies, and ubiquitination analyses.

(3) This study significantly impacts the field of immunology and virology, particularly concerning the antiviral mechanisms in lower vertebrates. The findings provide new insights into the regulation of IFN expression and the broader role of CDK2 in immune responses. The methods and data presented in this paper are highly valuable for the scientific community, offering new avenues for research into antiviral strategies and the development of therapeutic interventions targeting CDK2 and its associated pathways.

Reviewer #2 (Public review):

This work sought to explore antibody responses in the context of hemorrhagic fever with renal syndrome (HFRS) - a severe disease caused by Hantaan virus infection. Little is known about the characteristics or functional relevance of IgG Fc glycosylation in HFRS. To address this gap, the authors analyzed samples from 65 patients with HFRS spanning the acute and convalescent phases of disease via IgG Fc glycan analysis, scRNAseq, and flow cytometry. The authors observed changes in Fc glycosylation (increased fucosylation and decreased bisection) coinciding with a 4-fold or greater increased in Haantan virus-specific antibody titer. The study also includes exploratory analyses linking IgG glycan profiles to glycosylation-related gene expression in distinct B cell subsets, using single-cell transcriptomics. Overall, this is an interesting study that combines serological profiling with transcriptomic data to shed light on humoral immune responses in an underexplored infectious disease. The integration of Fc glycosylation data with single-cell transcriptomic data is a strength.

Reviewer #2 (Public review):

Summary:

The authors aim to provide an overview of the D. traunsteineri rhizosphere microbiome on a taxonomic and functional level, through 16S rRNA amplicon analysis and shotgun metagenome analysis. The amplicon sequencing shows that the major phyla present in the microbiome belong to phyla with members previously found to be enriched in rhizospheres and bulk soils. Their shotgun metagenome analysis focused on producing metagenome assembled genomes (MAGs), of which one satisfies the MIMAG quality criteria for high-quality MAGs and three those for medium-quality MAGs. These MAGs were subjected to functional annotations focusing on metabolic pathway enrichment and secondary metabolic pathway biosynthetic gene cluster analysis. They find 1741 BGCs of various categories in the MAGs that were analyzed, with the high-quality MAG being claimed to contain 181 SM BGCs. The authors provide a useful, albeit superficial, overview of the taxonomic composition of the microbiome, and their dataset can be used for further analysis.

The conclusions of this paper are not well-supported by the data, as the paper only superficially discusses the results, and the functional interpretation based on taxonomic evidence or generic functional annotations does not allow drawing any conclusions on the functional roles of the orchid microbiota.

Weaknesses:

The authors only used one individual plant to take samples. This makes it hard to generalize about the natural orchid microbiome.

The authors use both 16S amplicon sequencing and shotgun metagenomics to analyse the microbiome. However, the authors barely discuss the similarities and differences between the results of these two methods, even though comparing these results may be able to provide further insights into the conclusions of the authors. For example, the relative abundance of the ASVs from the amplicon analysis is not linked to the relative abundances of the MAGs.

Furthermore, the authors discuss that phyla present in the orchid microbiome are also found in other microbiomes and are linked to important ecological functions. However, their results reach further than the phylum level, and a discussion of genera or even species is lacking. The phyla that were found have very large within-phylum functional variability, and reliable functional conclusions cannot be drawn based on taxonomic assignment at this level, or even the genus level (Yan et al. 2017).

Additionally, although the authors mention their techniques used, their method section is sometimes not clear about how samples or replicates were defined. There are also inconsistencies between the methods and the results section, for example, regarding the prediction of secondary metabolite biosynthetic gene clusters (BGCs).

The BGC prediction was done with several tools, and the unusually high number of found BGCs (181 in their high-quality MAG) is likely due to false positives or fragmented BGCs. The numbers are much higher than any numbers ever reported in literature supported by functional evidence (Amos et al, 2017), even in a prolific genus like Streptomyces (Belknap et al., 2020). This caveat is not discussed by the authors.

The authors have generated one high-quality MAG and three medium-quality MAGs. In the discussion, they present all four of these as high-quality, which could be misleading. The authors discuss what was found in the literature about the role of the bacterial genera/phyla linked to these MAGs in plant rhizospheres, but they do not sufficiently link their own analysis results (metabolic pathway enrichment and biosynthetic gene cluster prediction) to this discussion. The results of these analyses are only presented in tables without further explanation in either the results section or the discussion, even though there may be interesting findings. For example, the authors only discuss the class of the BGCs that were found, but don't search for experimentally verified homologs in databases, which could shed more light on the possible functional roles of BGCs in this microbiome.

In the conclusions, the authors state: "These analyses uncovered potential metabolic capabilities and biosynthetic potentials that are integral to the rhizosphere's ecological dynamics." I don't see any support for this. Mentioning that certain classes of BGCs are present is not enough to make this claim, in my opinion. Any BGC is likely important for the ecological niche the bacteria live in. The fact that rhizosphere bacteria harbour BGCs is not surprising, and it doesn't tell us more than is already known.

References:

Belknap, Kaitlyn C., et al. "Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria." Scientific reports 10.1 (2020): 2003

Amos GCA, Awakawa T, Tuttle RN, Letzel AC, Kim MC, Kudo Y, Fenical W, Moore BS, Jensen PR. Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci U S A. 2017 Dec 26;114(52):E11121-E11130.

References:

Belknap, Kaitlyn C., et al. "Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria." Scientific reports 10.1 (2020): 2003

Amos GCA, Awakawa T, Tuttle RN, Letzel AC, Kim MC, Kudo Y, Fenical W, Moore BS, Jensen PR. Comparative transcriptomics as a guide to natural product discovery and biosynthetic gene cluster functionality. Proc Natl Acad Sci U S A. 2017 Dec 26;114(52):E11121-E11130.

Yan Yan, Eiko E Kuramae, Mattias de Hollander, Peter G L Klinkhamer, Johannes A van Veen, Functional traits dominate the diversity-related selection of bacterial communities in the rhizosphere, The ISME Journal, Volume 11, Issue 1, January 2017, Pages 56-66

Reviewer #2 (Public review):

Summary:

The study expands existing analytical tools originally developed for randomized controlled trials with dichotomous outcomes to assess the potential impact of missing data, adapting them for meta-analytical contexts. These tools evaluate how missing data may influence meta-analyses where p-value distributions cluster around significance thresholds, often leading to conflicting meta-analyses addressing the same research question. The approach quantifies the number of recodings (adding events to the experimental group and/or removing events from the control group) required for a meta-analysis to lose or gain statistical significance. The author developed an R package to perform fragility and redaction analyses and to compare these methods with a previously established approach by Atal et al. (2019), also integrated into the package. Overall, the study provides valuable insights by applying existing analytical tools from randomized controlled trials to meta-analytical contexts.

Strengths:

The author's results support his claims. Analyzing the fragility of a given meta-analysis could be a valuable approach for identifying early signs of fragility within a specific topic or body of evidence. If fragility is detected alongside results that hover around the significance threshold, adjusting the significance cutoff as a function of sample size should be considered before making any binary decision regarding statistical significance for that body of evidence. Although the primary goal of meta-analysis is effect estimation, conclusions often still rely on threshold-based interpretations, which is understandable. In some of the examples presented by Atal et al. (2019), the event recoding required to shift a meta-analysis from significant to non-significant (or vice versa) produced only minimal changes in the effect size estimation. Therefore, in bodies of evidence where meta-analyses are fragile or where results cluster near the null, it may be appropriate to adjust the cutoff. Conducting such analyses-identifying fragility early and adapting thresholds accordingly-could help flag fragile bodies of evidence and prevent future conflicting meta-analyses on the same question, thereby reducing research waste and improving reproducibility.

Weaknesses:

It would be valuable to include additional bodies of conflicting literature in which meta-analyses have demonstrated fragility. This would allow for a more thorough assessment of the consistency of these analytical tools, their differences, and whether this particular body of literature favored one methodology over another. The method proposed by Atal et al. was applied to numerous meta-analyses and demonstrated consistent performance. I believe there is room for improvement, as both the EOI and ROAR appear to be very promising tools for identifying fragility in meta-analytical contexts.

I believe the manuscript should be improved in terms of reporting, with clearer statements of the study's and methods' limitations, and by incorporating additional bodies of evidence to strengthen its claims.

Reviewer #3 (Public review):

This important study by Bohorquez et al examines the determinants necessary for concentrating the spatial modulator of cell division, MinD, at the future site of division and the cell poles. Proper localization of MinD is necessary to bring the division inhibitor, MinC, in proximity to the cell membrane and cell poles where it prevents aberrant assembly of the division machinery. In contrast to E. coli, in which MinD oscillates from pole-to-pole courtesy of a third protein MinE, how MinD localization is achieved in B. subtilis-which does not encode a MinE analog-has remained largely a mystery. The authors present compelling data indicating that MinD dimerization is dispensable for membrane localization but required for concentration at the cell poles. Dimerization is also important for interactions between MinD and MinC, leading to the formation of large protein complexes. Computational modeling, specifically a Monte Carlo simulation, supports a model in which differences in diffusion rates between MinD monomers and dimers lead to concentration of MinD at cell poles. Once there, interaction with MinC increases the size of the complex, further reinforcing diffusion differences. Notably, interactions with MinJ-which has previously been implicated in MinCD localization, are dispensable for concentrating MinD at cell poles although MinJ may help stabilize the MinCD complex at those locations.

Comments on revisions:

I believe the authors put respectable effort into revisions and addressing reviewer comments, particularly those that focused on the strengths of the original conclusions. The language in the current version of the manuscript is more precise and the overall product is stronger.

Reviewer #2 (Public review):

Summary:

The authors report describes a novel vaccine platform derived from a newly discovered organelle called a migrasome. First, the authors address a technical hurdle for using migrasomes as a vaccine platform. Natural migrasome formation occurs at low levels and is labor intensive, however, by understanding the molecular underpinning of migrasome formation, the authors have designed a method to make engineered migrasomes from cultures cells at higher yields utilizing a robust process. These engineered migrasomes behave like natural migrasomes. Next, the authors immunized mice with migrasomes that either expressed a model peptide or the SARS-CoV-2 spike protein. Antibodies against the spike protein were raised that could be boosted by a 2nd vaccination and these antibodies were functional as assessed by an in vitro pseudoviral assay. This new vaccine platform has the potential to overcome obstacles such as cold chain issues for vaccines like messenger RNA that require very stringent storage conditions.

Strengths:

The authors present very robust studies detailing the biology behind migrasome formation and this fundamental understanding was used to from engineered migrasomes, which makes it possible to utilize migrasomes as a vaccine platform. The characterization of engineered migrasomes is thorough and establishes comparability with naturally occurring migrasomes. The biophysical characterization of the migrasomes is well done, including thermal stability and characterization of the particle size (important characterizations for a good vaccine).

Weaknesses:

With a new vaccine platform technology, it would be nice to compare them head-to-head against a proven technology. The authors would improve the manuscript if they made some comparisons to other vaccine platforms such as a SARS-CoV-2 mRNA vaccine or even an adjuvanted recombinant spike protein. This would demonstrate a migrasome based vaccine could elicit responses comparable to a proven vaccine technology. Additionally, understanding the integrity of the antigens expressed in their migrasomes could be useful. This could be done by looking at functional monoclonal antibody binding to their migrasomes in a confocal microscopy experiment.

Updates after revision:

The revised manuscript has additional experiments that I believe improve the strength of evidence presented in the manuscript and address the weaknesses of the first draft. First, they provide a comparison to the antibody responses induced by their migrasome based platform to recombinant protein formulated in an adjuvant and show the response is comparable. Second, they provide evidence that the spike protein incorporated into their migrasomes retains structural integrity by preserving binding to monoclonal antibodies. Together, these results strengthen the paper significantly and support the claims that the novel migrasome based vaccine platform could be a useful in the vaccine development field.

Reviewer #2 (Public review):

Summary:

Sennesh and colleagues analyzed LFP data from 6 regions of rodents while they were habituated to a stimulus sequence containing a local oddball (xxxy) and later exposed to either the same (xxxY) or a deviant global oddball (xxxX). Subsequently, they were exposed to a controlled random sequence (XXXY) or a controlled deterministic sequence (xxxx or yyyy). From these, the authors looked for differences in spectral properties (both oscillatory and aperiodic) between three contrasts (only for the last stimulus of the sequence).

(1) Deviance detection: unpredictable random (XXXY) versus predictable habituation (xxxy)

(2) Global oddball: unpredictable global oddball (xxxX) versus predictable deterministic (xxxx), and

(3) "Stimulus-specific adaptation:" locally unpredictable oddball (xxxY) versus predictable deterministic (yyyy).

They found evidence for an increase in gamma (and theta in some cases) for unpredictable versus predictable stimuli, and a reduction in alpha/beta, which they consider evidence towards the "predictive routing" scheme.

While the dataset and analyses are well-suited to test evidence for predictive coding versus alternative hypotheses, I felt that the formulation was ambiguous, and the results were not very clear. My major concerns are as follows:

(1) The authors set up three competing hypotheses, in which H1 and H2 make directly opposite predictions. However, it must be noted that H2 is proposed for spatial prediction, where the predictability is computed from the part of the image outside the RF. This is different from the temporal prediction that is tested here. Evidence in favor of H2 is readily observed when large gratings are presented, for which there is substantially more gamma than in small images. Actually, there are multiple features in the spectral domain that should not be conflated, namely (i) the transient broadband response, which includes all frequencies, (ii) contribution from the evoked response (ERP), which is often in frequencies below 30 Hz, (iii) narrow-band gamma oscillations which are produced by large and continuous stimuli (which happen to be highly predictive), and (iv) sustained low-frequency rhythms in theta and alpha/beta bands which are prominent before stimulus onset and reduce after ~200 ms of stimulus onset. The authors should be careful to incorporate these in their formulation of PC, and in particular should not conflate narrow-band and broadband gamma.

(2) My understanding is that any aspect of predictive coding must be present before the onset of stimulus (expected or unexpected). So, I was surprised to see that the authors have shown the results only after stimulus onset. For all figures, the authors should show results from -500 ms to 500 ms instead of zero to 500 ms.

(3) In many cases, some change is observed in the initial ~100 ms of stimulus onset, especially for the alpha/beta and theta ranges. However, the evoked response contributes substantially in the transient period in these frequencies, and this evoked response could be different for different conditions. The authors should show the evoked responses to confirm the same, and if the claim really is that predictions are carried by genuine "oscillatory" activity, show the results after removing the ERP (as they had done for the CSD analysis).

(4) I was surprised by the statistics used in the plots. Anything that is even slightly positive or negative is turning out to be significant. Perhaps the authors could use a more stringent criterion for multiple comparisons?

(5) Since the design is blocked, there might be changes in global arousal levels. This is particularly important because the more predictive stimuli in the controlled deterministic stimuli were presented towards the end of the session, when the animal is likely less motivated. One idea to check for this is to do the analysis on the 3rd stimulus instead of the 4th? Any general effect of arousal/attention will be reflected in this stimulus.

(6) The authors should also acknowledge/discuss that typical stimulus presentation/attention modulation involves both (i) an increase in broadband power early on and (ii) a reduction in low-frequency alpha/beta power. This could be just a sensory response, without having a role in sending prediction signals per se. So the predictive routing hypothesis should involve testing for signatures of prediction while ruling out other confounds related to stimulus/cognition. It is, of course, very difficult to do so, but at the same time, simply showing a reduction in low-frequency power coupled with an increase in high-frequency power is not sufficient to prove PR.

(7) The CSD results need to be explained better - you should explain on what basis they are being called feedforward/feedback. Was LFP taken from Layer 4 LFP (as was done by van Kerkoerle et al, 2014)? The nice ">" and "<" CSD patterns (Figure 3B and 3F of their paper) in that paper are barely observed in this case, especially for the alpha/beta range.

(8) Figure 4a-c, I don't see a reduction in the broadband signal in a compared to b in the initial segment. Maybe change the clim to make this clearer?

(9) Figure 5 - please show the same for all three frequency ranges, show all bars (including the non-significant ones), and indicate the significance (p-values or by *, **, ***, etc) as done usually for bar plots.

(10) Their claim of alpha/beta oscillations being suppressed for unpredictable conditions is not as evident. A figure akin to Figure 5 would be helpful to see if this assertion holds.

(11) To investigate the prediction and violation or confirmation of expectation, it would help to look at both the baseline and stimulus periods in the analyses.

Reviewer #2 (Public review):

Summary:

Mark and colleagues test the hypothesis that entorhinal cortical representations may contain abstract structural information that facilitates generalization across structurally similar contexts. To do so, they use a method called "subspace generalization" designed to measure abstraction of representations across different settings. The authors validate the method using hippocampal place cells and entorhinal grid cells recorded in a spatial task, then show perform simulations that support that it might be useful in aggregated responses such as those measured with fMRI. Then the method is applied to an fMRI data that required participants to learn relationships between images in one of two structural motifs (hexagonal grids versus community structure). They show that the BOLD signal within an entorhinal ROI shows increased measures of subspace generalization across different tasks with the same hexagonal structure (as compared to tasks with different structures) but that there was not evidence for the complementary result (ie. increased generalization across tasks that share community structure, as compared to those with different structures). Taken together, this manuscript describes and validates a method for identifying fMRI representations that generalize across conditions and applies it to reveal that entorhinal representations that emerge across specific shared structural conditions.

Strengths:

I found this paper interesting both in terms of its methods and its motivating questions. The question asked is novel and the methods employed are new - and I believe this is the first time that they have been applied to fMRI data. I also found the iterative validation of the methodology to be interesting and important - showing persuasively that the method could detect a target representation - even in the face of random combination of tuning and with the addition of noise, both being major hurdles to investigating representations using fMRI.

Weaknesses:

The primary weakness of the paper in terms of empirical results is that the representations identified in EC had no clear relationship to behavior, raising questions about their functional importance.

The method developed is a clearly valuable tool that can serve as part of a larger battery of analysis techniques, but a small weakness on the methodological side is that for a given dataset, it might be hard to determine whether the method developed here would be better or worse than alternative methods.

Reviewer #2 (Public review):

This is an excellent paper. The ability to measure the immune response to multiple viruses in parallel is a major advancement for the field, that will be relevant across pathogens (assuming the assay can be appropriately adapted). I only had a few comments, focused on maximising the information provided by the sera. These concerns were all addressed in the revised paper.

Reviewer #2 (Public review):

Summary:

The results presented here are a useful extension of two of their previous papers (Colquitt et al 2021, Colquitt et al 2023), where they used single-cell transcriptomics to characterize the inhibitory and excitatory cell types and gene expression patterns of the song circuit, comparing them to mammalian and reptilian brains, and characterized the effect of deafening on these gene expression patterns. In this paper, they focus on the differential expression of various neuropeptidergic systems in the songbird brain. They discover a role for the CRHBP gene in song performance and causally show its influence on song variability.

Strengths:

The authors leverage the advantages of the 'nucleated' structure of the songbird neural circuitry and use a robust approach to compare neuropeptidergic gene expression patterns in these circuits. Their analysis of the expression patterns of the CRHBP gene in different cell types supports their conclusion that interneurons are particularly amenable to this modulation. Their use of a knockdown strategy along with pharmacological manipulation provides strong support for a causal role of neuropeptidergic modulation on song behaviour. These results have important implications as they bring into focus neuropeptide modulation of the song-motor circuit and pave the way for future studies focussing on how this signalling pathway regulates plasticity during song learning and maintenance.

Weaknesses:

While the results demonstrating the bidirectional modulation of CRH and CRHBP on song performance shed light on their role in song plasticity, it would be important to show this in juvenile finches during sensorimotor learning. We also don't get a clear picture of the 'causal' role of this signalling pathway on the song pre-motor area, HVC, as the knockdown and pharmacological manipulation studies were done in RA, whereas we see a modulation of CRHBP expression during deafening and song learning in both RA and HVC. Given the role of interneurons in the HVC in song acquisition (e.g., Vallentin et al. 2016, Science), it would have been interesting to see the results of HVC-specific manipulation of this neuropeptidergic pathway and/or how it affects the song learning process. Perhaps a short discussion of this would help to give the readers some perspective. Finally, a more direct demonstration of the neurophysiological effect of the signalling pathway would also strengthen our understanding of precisely how these modulate the song circuit plasticity, which I understand might be beyond the scope of this study.

Technical/minor:

In the Methods section, several clarifications would be beneficial. For instance, the description of the design matrices would benefit from being presented in a more general statistical form (e.g., linear model equations) rather than using R syntax. This would make the modeling approach more accessible to readers unfamiliar with software-specific syntax. In addition, while some variables (e.g., cdr_scale, frac_mito_scale) are briefly defined, others (e.g., tags, cut3,nsongs_last_two_days_cut3) could be more clearly described. This applies to the descriptions of both the gene set enrichment analysis and the neuropeptide-receptor analysis, which rely heavily on package-specific terminology (e.g., fgseaMultilevel, computeCommunProb), making it difficult for readers to understand the conceptual or statistical basis of the analyses. It would improve clarity if the authors provided a complete list of variable definitions, types (categorical or continuous), and any scaling/transformations applied would enhance clarity and reproducibility.

Reviewer #2 (Public review):

Summary:

In this manuscript, He et al. set out to investigate the mechanisms behind Kupffer Cell death in MASLD. As has been previously shown, they demonstrate a loss of resident KCs in MASLD in different mouse models. They then go on to show that this correlates with alterations in genes/metabolites associated with glucose metabolism in KCs. To investigate the role of glucose metabolism further, they subject isolated KCs in vitro to different metabolic treatments and assess cleaved caspase 3 staining, demonstrating that KCs show increased Cl. Casp 3 staining upon stimulation of glycolysis. Finally, they use a genetic mouse model (Chil1KO) where they have previously reported that loss of this gene leads to increased glycolysis and validate this finding in BMDMs (KO). They then remove this gene specifically from KCs (Clec4fCre) and show that this leads to increased macrophage death compared with controls.

Strengths:

As we do not yet understand why KCs die in MASLD, this manuscript provides some explanation for this finding. The metabolomics is novel and provides insight into KC biology. It could also lead to further investigation; here, it will be important that the full dataset is made available.

Weaknesses:

Different diets are known to induce different amounts of KC loss, yet here, all models examined appear to result in 60% KC death. One small field of view of liver tissue is shown as representative to make these claims, but this is not sufficient, as anything can be claimed based on one field of view. Rather, a full tissue slice should be included to allow readers to really assess the level of death. Additionally, there is no consistency between the markers used to define KCs and moMFs, with CLEC4F being used in microscopy, TIM4 in flow, while the authors themselves acknowledge that moKCs are CLEC4F+TIM4-. As moKCs are induced in MASLD, this limits interpretation. Additionally, Iba1 is referred to as a moMF marker but is also expressed by KCs, which again prevents an accurate interpretation of the data. Indeed, the authors show 60% of KCs are dying but only 30% of IBA1+ moMFs, as KCs are also IBA1+, this would mean that KCs die much more than moMFs, which would then limit the relevance of the BMDM studies performed if the phenotype is KC specific. Therefore, this needs to be clarified. The claim that periportal KCs die preferentially is not supported, given that the majority of KCs are peri-portal. Rather, these results would need to be normalised to KC numbers in PP vs PC regions to make meaningful conclusions. Additionally, KCs are known to be notoriously difficult to keep alive in vitro, and for these studies, the authors only examine cl. Casp 3 staining. To fully understand that data, a full analysis of the viability of the cells and whether they retain the KC phenotype in all conditions is required. Finally, in the Cre-driven KO model, there does not seem to be any death of KCs in the controls (rather numbers trend towards an increase with time on diet, Figure 6E), contrary to what had been claimed in the rest of the paper, again making it difficult to interpret the overall results. Additionally, there is no validation that the increased death observed in vivo in KCs is due to further promotion of glycolysis.

Reviewer #2 (Public review):

The authors in this manuscript studied the role of Candida albicans in Colorectal cancer progression. The authors have undertaken a thorough investigation and used several methods to investigate the role of Candida albicans in Colorectal cancer progression. The topic is highly relevant, given the increasing burden of colon cancer globally and the urgent need for innovative treatment options.

However, there are some inconsistencies in the figures and some missing details in the figures, including:

(1) The authors should clearly explain in the results section which patient samples are shown in Figure 1B.

(2) What do a, ab, b, b written above the bars in Figure 1F represent? Maybe authors should consider removing them, because they create confusion. Also, there is no explanation for those letters in the figure legend.

(3) The authors should submit all the raw images of Western blot with appropriate labels to indicate the bands of protein of interest along with molecular weight markers.

(4) The authors should do the quantification of data in Figure 2d and include it in the figure.

(5) In Figure 2h, the authors should indicate if the quantification represents VEGF expression after 6h or 12h of C. albicans co-culture with cells.

(6) In Figure 2i, quantification of VEGF should be done and data from three independent experiments should be submitted. The authors should also mention the time point.

Reviewer #2 (Public review):

Summary:

A study that furthers the molecular definition of PPGL (where prognosis is variable) and provides a wide range of sub-experiments to back up the findings. One of the key premises of the study is that identification of driver mutations in PPGL is incomplete and that compromises characterisation for prognostic purposes. This is a reasonable starting point on which to base some characterisation based on different methods.

Strengths:

The cohort is a reasonable size, and a useful validation cohort in the form of TCGA is used. Whilst it would be resource-intensive (though plausible given the rarity of the tumour type) to perform RNAseq on all PPGL samples in clinical practice, some potential proxies are proposed.

Weaknesses:

Performance of some of the proxy markers for transcriptional subtype is not presented.

Limited prognostic information available.

Comments on revisions:

Having reviewed the responses to my comments and associated revisions, I am satisfied that they have been addressed.

Reviewer #2 (Public review):

Summary

The current study seeks to understand the neural mechanisms underlying geometric reasoning. Using fMRI with both children and adults, the authors found that contrasting simple geometric shapes with naturalistic images (faces, tools, houses) led to responses in the dorsal visual stream, rather than ventral regions that are generally thought to represent shape properties. The author's followed up on this result using computational modeling and MEG to show that geometric properties explain distinct variance in the neural response than what is captured by a CNN.

Strengths

These findings contribute much-needed neural and developmental data to the ongoing debate regarding shape processing in the brain and offer additional insights into why CNNs may have difficulty with shape processing. The motivation and discussion for the study is appropriately measured, and I appreciate the authors' use of multiple populations, neuroimaging modalities, and computational models in explore this question.

Weaknesses

The presence of activation in aIPS led the authors to interpret their results to mean that geometric reasoning draws on the same processes as mathematical thinking. However, there is only weak and indirect evidence in the current study that geometric reasoning, as its tested here, draws on the same circuits as math.

Reviewer #2 (Public review):

Summary:

The valuable study investigates how statistical learning may facilitate a target detection task and whether the facilitation effect is related to statistical learning of word boundaries. Solid evidence is provided that target detection and word segmentation rely on different statistical learning mechanisms.

Strengths:

The study is well designed, using the contrast between the learning of words of uniform length and words of variable length to dissociate general statistical learning effects and effects related to word segmentation.

Weaknesses:

The study relies on the contrast between word length effects on target detection and word learning. However, the study only tested the target detection condition and did not attempt to replicate the word segmentation effect. It is true that the word segmentation effect has been replicated before but it is still worth reviewing the effect size of previous studies.

The paper seems to distinguish prediction, anticipation, and statistical learning, but it is not entirely clear what each terms refers to.

Comments on revisions:

The authors did not address my concerns...they only replied to reviewer 1.

Reviewer #2 (Public review):

I enjoyed this paper and its examination of the relationship between overall density and age polyethism to reduce the computational complexity required to match nest size with population. I had some questions about the requirement that growth is infinite in such a solution, but these have been addressed by the authors in the responses and updated manuscript. I also enjoyed the discussion of whether collective behaviour is an appropriate framework in systems in which agents (or individuals) differ in the behavioural rules they employ, according to age, location, or information state. This is especially important in a system like social insects, typically held as a classic example of individual-as-subservient to whole, and therefore most likely to employ universal rules of behaviour. The current paper demonstrates a potentially continuous age-related change in target behaviour (excavation), and suggests an elegant and minimal solution to the requirement for building according to need in ants, avoiding the invocation of potentially complex cognitive mechanisms, or information states that all individuals must have access to in order to have an adaptive excavation output.

The authors have addressed questions I had in the review process and the manuscripts is now clear in its communication and conclusions.

The modelling approach is compelling, also allowing extrapolation to other group sizes and even other species. This to me is the main strength of the paper, as the answer to the question of whether it is younger or older ants that primarily excavate nests could have been answered by an individual tracking approach (albeit there are practical limitations to this, especially in the observation nest setup, as the authors point out). The analysis of the tunnel structure is also an important piece of the puzzle, and I really like the overall study.

Reviewer #2 (Public review):

Summary:

In the present manuscript, Cordeiro et al. show that α-mangostin, a xanthone obtained from the fruit of the Garcinia mangostana tree, behaves as an agonist of the BK channels. The authors arrive at this conclusion through the effect of mangostin on macroscopic and single-channel currents elicited by BK channels formed by the α subunit and α + β1sununits, as well as αβ1 channels coexpressed with voltage-dependent Ca2+ (CaV1,2) channels. The single-channel experiments show that α-mangostin produces a robust increase in the probability of opening without affecting the single-channel conductance. The authors contend that α-mangostin activation of the BK channel is state-independent and molecular docking and mutagenesis suggest that α-mangostin binds to a site in the internal cavity. Importantly, α-mangostin (10 μM) alleviates the contracture promoted by noradrenaline. Mangostin is ineffective if the contracted muscles are pretreated with the BK toxin iberiotoxin.

Strengths:

The set of results combining electrophysiological measurements, mutagenesis, and molecular docking reveals α-mangostin as a potent activator of BK channels and the putative location of the α-mangostin binding site. Moreover, experiments conducted on aortic preparations from mice suggest that α-mangostin can aid in developing drugs to treat a myriad of diverse diseases involving the BK channel.

Weaknesses:

Major:

(1) Although the results indicate that α-mangostin is modifying the closed-open equilibrium, the conclusion that this can be due to a stabilization of the voltage sensor in its active configuration may prove to be wrong. It is more probable that, as has been demonstrated for other activators, the α-mangostin is increasing the equilibrium constant that defines the closed-open reaction (L in the Horrigan, Aldrich allosteric gating model for BK). The paper will gain much if the authors determine the probability of opening in a wide range of voltages, to determine how the drug is affecting (or not), the channel voltage dependence, the coupling between the voltage sensor and the pore, and the closed-open equilibrium (L).

(2) Apparently, the molecular docking was performed using the truncated structure of the human BK channel. However, it is unclear which one, since the PDB ID given in the Methods (6vg3), according to what I could find, corresponds to the unliganded, inactive PTK7 kinase domain. Be as it may, the apo and Ca2+ bound structures show that there is a rotation and a displacement of the S6 transmembrane domain. Therefore, the positions of the residues I308, L312, and A316 in the closed and open configurations of the BK channel are not the same. Hence, it is expected that the strength of binding will be different whether the channel is closed or open. This point needs to be discussed.

Minor:

(1) From Figure 3A, it is apparent that the increase in Po is at the expense of the long periods (seconds) that the channel remains closed. One might suggest that α-mangostin increases the burst periods. It would be beneficial if the authors measured both closed and open dwell times to test whether α-mangostin primarily affects the burst periods.

(2) In several places, the authors make similarities in the mode of action of other BK activators and α-mangostin; however, the work of Gessner et al. PNAS 2012 indicates that NS1619 and Cym04 interact with the S6/RCK linker, and Webb et al. demonstrated that GoSlo-SR-5-6 agonist activity is abolished when residues in the S4/S5 linker and in the S6C region are mutated. These findings indicate that binding of the agonist is not near the selectivity filter, as the authors' results suggest that α-mangostin binds.

(3) The sentence starting in line 452 states that there is a pronounced allosteric coupling between the voltage sensors and Ca2+ binding. If the authors are referring to the coupling factor E in the Horrigan-Aldrich gating model, the references cited, in particular, Sun and Horrigan, concluded that the coupling between those sensors is weak.

Reviewer #2 (Public review):

Summary:

The manuscript by Freier et al examines the impact of deletion of the glycine cleavage system (GCS) GcvPAB enzyme complex in the facultative intracellular bacterial pathogen Listeria monocytogenes. GcvPAB mediates the oxidative decarboxylation of glycine as a first step in a pathway that leads to the generation of N5, N10-methylene-Tetrahydrofolate (THF) to replenish the 1-carbon THF (1C-THF) pool. 1C-THF species are important for the biosynthesis of purines and pyrimidines as well as for the formation of serine, methionine, and N-formylmethionine, and the authors have previously demonstrated that gcvPAB is important for bacterial replication within macrophages. A significant defect for growth is observed for the gcvPAB deletion mutant in defined media, and this growth defect appears to stem from the sensitivity of the mutant strain to excess glycine, which is hypothesized to further deplete the 1C-THF pool. Selection of suppressor mutations that restored growth of gcvPAB deletion mutants in synthetic media with high glycine yielded mutants that reversed stop codon inactivation of the formate-tetrahydrofolate ligase (fhs) gene, supporting the premise that generation of N10-formyl-THF can restore growth. Mutations within the folk, codY, and glyA genes, encoding serine hydroxymethyltransferase, were also identified, although the functional impact of these mutations is somewhat less clear. Overall, the authors report that their work identifies three pathways that feed the 1C-THF pool to support the growth and virulence of L. monocytogenes and that this work represents the first example of the spontaneous reactivation of a L. monocytogenes gene that is inactivated by a premature stop codon.

Strengths:

This is an interesting study that takes advantage of a naturally existing fhs mutant Listeria strain to reveal the contributions of different pathways leading to 1C-THF synthesis. The defects observed for the gcvPAB mutant in terms of intracellular growth and virulence are somewhat subtle, indicating that bacteria must be able to access host sources (such as adenine?) to compensate for the loss of purine and fMet synthesis. Overall, the authors do a nice job of assessing the importance of the pathways identified for 1C-THF synthesis.

Weaknesses:

(1) Line 114 and Figure 1: The authors indicate that the gcvPAB deletion forms significantly fewer plaques in addition to forming smaller plaques (although this is a bit hard to see in the plaque images). A reduction in the overall number of plaques sounds like a bacterial invasion defect - has this been carefully assessed? The smaller plaque size makes sense with reduced bacterial replication, but I'm not sure I understand the reduction in plaque number.

(2) Do other Listeria strains contain the stop codon in fhs? How common is this mutation? That would be interesting to know.

(3) Based on the observation that fhs+ ΔgcvPAB ΔglyA mutant is only possible to isolate in complex media, and fhs is responsible for converting formate to 1C-THF with the addition of FolD, have the authors thought of supplementing synthetic media with formate and assessing mutant growth?

Reviewer #2 (Public review):

Summary:

In this manuscript by Laham and co-workers, the authors profiled structurally diverse LXR ligands via a coregulator TR-FRET (CRT) assay for their ability to recruit coactivators and kick off corepressors, while identifying coregulator preference and LXR isoform selectivity.

The relative ligand potencies measured via CRT for the two LXR isoforms were correlated with ABCA1 induction or lipogenic activation of SRE, depending on cellular contexts (i.e, astrocytoma or hepatocarcinoma cells). While these correlations are interesting, there is some leeway to improve the quantitative presentation of these correlations. Finally, the CRT signatures were correlated with the structural stabilization of the LXR: coregulator complexes. In aggregate, this study curated a set of LXR ligands with disparate agonism signatures that may guide the design of future nonlipogenic LXR agonists with potential therapeutic applications for cardiovascular disease, Alzheimer's, and type 2 diabetes, without inducing mechanisms that promote fat/lipid production.

Strengths:

This study has many strengths, from curating an excellent LXR compound set to the thoughtful design of the CRT and cellular assays. The design of a multiplexed precision CRT (pCRT) assay that detects corepressor displacement as a function of ligand-induced coactivator recruitment is quite impressive, as it allows measurement of ligand potencies to displace corepressors in the presence of coactivators, which cannot be achieved in a regular CRT assay that looks at coactivator recruitment and corepressor dissociation in separate experiments.

Weaknesses:

I did not identify any major weaknesses.

Reviewer #2 (Public review):

Summary:

Wan, Thurm et al. use a yeast nanobody library that is thought to have diverse binders to isolate those that specifically bind to proteins of their interest. The yeast nanobody library collection in general carries enormous potential, but the challenge is to isolate binders that have specific activity. The authors posit that one reason for this isolation challenge is that the negative binders, in general, dampen the signal from the positive binders. This is a classic screening problem (one that geneticists have faced over decades) and, in general, underscores the value of developing a good secondary screen. Over many years, the authors have developed an elegant platform to carry out high-throughput silencing-based assays, thus creating the perfect secondary screen platform to isolate nanobodies that bind to chromatin regulators.

Strengths:

Highlights the enormous value of a strong secondary screen when identifying binders that can be isolated from the yeast nanobody library. This insight is generalizable, and I expect that this manuscript should help inspire many others to design such approaches.

Provides new cell-based reagents that can be used to recruit epigenetic activators or repressors to modulate gene expression at target loci.

Weaknesses:

The authors isolate DNMT3A and TET1/2 enzymes directly from cell lysates and bind these proteins to beads. It is not clear what proteins are, in fact, bound to beads at the end of the IP. Epigenetic repressors are part of complexes, and it would be helpful to know if the IP is specific and whether the IP pulls down only DNMT3A or other factors. While this does not change the underlying assumptions about the screen, it does alter the authors' conclusions about whether the nanobody exclusively recruits DNMT3A or potentially binds to other co-factors.

Using IP-MS to validate the pull-down would be a helpful addition to the manuscript, although one could very reasonably make the case that other co-factors get washed away during the course of the selection assay. Nevertheless, if there are co-factors that are structural and remain bound, these are likely to show up in the MS experiment.

Reviewer #2 (Public review):

Summary:

Okell et al. report the incorporation of arterial spin-labeled (ASL) perfusion MRI into the UK Biobank study and preliminary observations of perfusion MRI correlates from over 7000 acquired datasets, which is the largest sample of human perfusion imaging data to date. Although a large literature already supports the value of ASL MRI as a biomarker of brain function, this important study provides compelling evidence that a brief ASL MRI acquisition may lead to both fundamental observations about brain health as manifested in CBF and valuable biomarkers for use in diagnosis and treatment monitoring.

ASL MRI noninvasively quantifies regional cerebral blood flow (CBF), which reflects both cerebrovascular integrity and neural activity, hence serves as a measure of brain function and a potential biomarker for a variety of CNS disorders. Despite a highly abbreviated ASL MRI protocol, significant correlations with both expected and novel demographic, physiological, and medical factors are demonstrated. In many such cases, ASL was also more sensitive than other MRI-derived metrics. The ASL MRI protocol implemented also enables quantification of arterial transit time (ATT), which provides stronger clinical correlations than CBF in some factors. The results demonstrate both the feasibility and the efficacy of ASL MRI in the UK Biobank imaging study, which expects to complete ASL MRI in up to 60,000 richly phenotyped individuals. Although a large literature already supports the value of ASL MRI as a biomarker of brain function, this important study provides compelling evidence that a brief ASL MRI acquisition may lead to both fundamental observations about brain health as manifested in CBF and valuable biomarkers for use in diagnosis and treatment monitoring.

Strengths:

A key strength of this study is the use of an ASL MRI protocol incorporating balanced pseudocontinuous labeling with a background-suppressed 3D readout, which is the current state-of-the-art. To compensate for the short scan time, voxel resolution was intentionally only moderate. The authors also elected to acquire these data across five post-labeling delays, enabling ATT and ATT-corrected CBF to be derived using the BASIL toolbox, which is based on a variational Bayesian framework. The resulting CBF and ATT maps shown in Figure 1 are quite good, especially when combined with such a large and deeply phenotyped sample.

Another strength of the study is the rigorous image analysis approach, which included covariation for a number of known CBF confounds as well as correction for motion and scanner effects. In doing so, the authors were able to confirm expected effects of age, sex, hematocrit, and time of day on CBF values. These observations lend confidence in the veracity of novel observations, for example, significant correlations between regional ASL parameters and cardiovascular function, height, alcohol consumption, depression, and hearing, as well as with other MRI features such as regional diffusion properties and magnetic susceptibility. They also provide valuable observations about ATT and CBF distributions across a large cohort of middle-aged and older adults.

Weaknesses:

This study primarily serves to illustrate the efficacy and potential of ASL MRI as an imaging parameter in the UK Biobank study, but some of the preliminary observations will be hypothesis-generating for future analyses in larger sample sizes. However, a weakness of the manuscript is that some of the reported observations are difficult to follow. In particular, the associations between ASL and resting fMRI illustrated in Figure 7 and described in the accompanying Results text are difficult to understand. It could also be clearer whether the spatial maps showing ASL correlates of other image-derived phenotypes in Figure 6B are global correlations or confined to specific regions of interest. Finally, while addressing partial volume effects in gray matter regions by covarying for cortical thickness is a reasonable approach, the Methods section seems to imply that a global mean cortical thickness is used, which could be problematic given that cortical thickness changes may be localized.

Reviewer #2 (Public review):

Summary:

The work presented by Zhang and coauthors in this manuscript presents the study of the neuropeptide corazonin in modulating the post-mating response of the brown planthopper, with further validation in Drosophila melanogaster. To obtain their results, the authors used several different techniques that orthogonally demonstrate the involvement of corazonin signalling in regulating the female post-mating response in these species.

They first injected synthetic corazonin peptide into female brown planthoppers, showing altered mating receptivity in virgin females and a higher number of eggs laid after mating. The role of corazonin in controlling these post-mating traits has been further validated by knocking down the expression of the corazonin gene by RNA interference and through CRISPR-Cas9 mutagenesis of the gene. Further proof of the importance of corazonin signalling in regulating the female post-mating response has been achieved by knocking down the expression or mutagenizing the gene coding for the corazonin receptor.

Similar results have been obtained in the fruit fly Drosophila melanogaster, suggesting that corazonin signalling is involved in controlling the female post-mating response in multiple insect species.<br /> Notably, the authors also show that corazonin controls gene expression in the male accessory glands and that disruption of this pathway in males compromises their ability to elicit normal post-mating responses in their mates.

Strengths:

The study of the signalling pathways controlling the female post-mating response in insects other than Drosophila is scarce, and this limits the ability of biologists to draw conclusions about the evolution of the post-mating response in female insects. This is particularly relevant in the context of understanding how sexual conflict might work at the molecular and genetic levels, and how, ultimately, speciation might occur at this level. Furthermore, the study of the post-mating response could have practical implications, as it can lead to the development of control techniques, such as sterilization agents.

The study, therefore, expands the knowledge of one of the signalling pathways that control the female post-mating response, the corazonin neuropeptide. This pathway is involved in controlling the post-mating response in both Nilaparvata lugens (the brown planthopper) and Drosophila melanogaster, suggesting its involvement in multiple insect species.

The study uses multiple molecular approaches to convincingly demonstrate that corazonin controls the female post-mating response.

Weaknesses:

The data supporting the main claims of the manuscript are solid and convincing. The statistical analysis of some of the data might be improved, particularly by tailoring the analysis to the type of data that has been collected.

In the case of the corazonin effect in females, all the data are coherent; in the case of CRISPR-Cas9-induced mutagenesis, the analysis of the behavioural trait in heterozygotes might have helped in understanding the haplosufficiency of the gene and would have further proved the authors' point.

Less consistency was achieved in males (Figure 5): the authors show that injection of CRZ and RNAi of crz, or mutant crz, has the same effect on male fitness. However, the CRZ injection should activate the pathway, and crz RNAi and mutant crz should inhibit the pathway, yet they have the same effect. A comment about this discrepancy would have improved the clarity of the manuscript, pointing to new points that need to be clarified and opening new scientific discussion.

Reviewer #2 (Public review):

Summary:

In this manuscript, Malfatti et al. study the role of Chrna2 Martinotti cells (Mα2 cells), a subset of SST interneurons, for motor learning and motor cortex activity. The authors trained mice on a forelimb prehension task while recording neuronal activity of pyramidal cells using calcium imaging with a head-mounted miniscope. While chemogenetically increasing Mα2 cell activity did not affect motor learning, it changed pyramidal cell activity such that activity peaks became sharper and differently timed than in control mice. Moreover, co-active neuronal assemblies become more stable with a smaller spatial distribution. Increasing Mα2 cell activity in previously trained mice did increase performance on the prehension task and led to increased theta and gamma band activity in the motor cortex. On the other hand, genetic ablation of Mα2 cells affected fine motor movements on a pasta handling task while not affecting the prehension task.

Strengths:

The proposed question of how Chrna2-expressing SST interneurons affect motor learning and motor cortex activity is important and timely. The study employs sophisticated approaches to record neuronal activity and manipulate the activity of a specific neuronal population in behaving mice over the course of motor learning. The authors analyze a variety of neuronal activity parameters, comparing different behavior trials, stages of learning, and the effects of Mα2 cell activation. The analysis of neuronal assembly activity and stability over the course of learning by tracking individual neurons throughout the imaging sessions is notable, since technically challenging, and yielded the interesting result that neuronal assemblies are more stable when activating Mα2 cells.

Overall, the study provides compelling evidence that Mα2 cells regulate certain aspects of motor behaviors, likely by shaping circuit activity in the motor cortex.

Weaknesses:

The main limitation of the study lies in its small sample sizes and the absence of key control experiments, which substantially weaken the strength of the conclusions.

Core findings of this paper, such as the lack of effect of Mα2 cell activation on motor learning, as well as the altered neuronal activity, rely ona sample size of n=3 mice per condition, which is likely underpowered to detect differences in behavior and contributes to the somewhat disconnected results on calcium activity, activity timing, and neuronal assembly activity.

More comprehensive analyses and data presentation are also needed to substantiate the results. For example, examining calcium activity and behavioral performance on a trial-by-trial basis could clarify whether closely spaced reaching attempts influence baseline signals and skew interpretation.

The study uses cre-negative mice as controls for hM3Dq-mediated activation, which does not account for potential effects of Cre-dependent viral expression that occur only in Cre-positive mice.

This important control would be necessary to substantiate the conclusion that it is increased Mα2 cell activity that drives the observed changes in behavior and cortical activity.

Reviewer #2 (Public review):

Summary:

This study investigated how the human brain responds to vocalizations from multiple primate species, including humans, chimpanzees, bonobos, and rhesus macaques. The central finding - that subregions of the temporal voice areas (TVA), particularly in the bilateral anterior superior temporal gyrus, show enhanced responses to chimpanzee vocalizations - suggests a potential neural sensitivity to calls from phylogenetically close nonhuman primates.

Strengths:

The authors employed three analytical models to consistently demonstrate activation in the anterior superior temporal gyrus that is specific to chimpanzee calls. The methodology was logical and robust, and the results supporting these findings appear solid.

Weakness:

The interpretation of the findings in this paper regarding the evolutionary continuity of voice processing lacks sufficient evidence. A simple explanation is that the observed effects can be attributed to the similarity in low-level acoustic features, rather than effects specific to phylogenetically close species. The authors only tested vocalizations from three non-human primate species, other than humans. In this case, the species specificity of the effect does not fully represent the specificity of evolutionary relatedness.

Reviewer #2 (Public review):

Summary:

This study uses a coarse-grained model for double stranded DNA, cgNA+, to assess nucleosome sequence affinity. cgNA+ coarse-grains DNA on the level of bases and accounts also explicitely for the positions of the backbone phosphates. It has been proven to reproduce all-atom MD data very accurately. It is also ideally suited to be incorporated into a nucleosome model because it is known that DNA is bound to the protein core of the nucleosome via the phosphates.

It is still unclear whether this harmonic model parametrized for unbound DNA is accurate enough to describe DNA inside the nucleosome. Previous models by other authors, using more coarse-grained models of DNA, have been rather successful in predicting base pair sequence dependent nucleosome behavior. This is at least the case as long as DNA shape is concerned whereas assessing the role of DNA bendability (something this paper focuses on) has been consistingly challenging in all nucleosome models to my knowledge.

It is thus of major interest whether this more sophisticated model is also more successful in handling this issue. As far as I can tell the work is technically sound and properly accounts for not only the energy required in wrapping DNA but also entropic effects, namely the change in entropy that DNA experiences when going from the free state to the bound state. The authors make an approximation here which seems to me to be a reasonable first step.

Of interest is also that the authors have the parameters at hand to study the effect of methylation of CpG-steps. This is especially interesting as this allows to study a scenario where changes in the physical properties of base pair steps via methylation might influence nucleosome positioning and stability in a cell-type specific way.

Overall, this is an important contribution to the questions of how sequence affects nucleosome positioning and affinity. The findings suggest that cgNA+ has something new to offer. But the problem is complex, also on the experimental side, so many questions remain open. Despite of this, I highly recommend publication of this manuscript.

Strengths:

The authors use their state-of-the-art coarse grained DNA model which seems ideally suited to be applied to nucleosomes as it accounts explicitly for the backbone phosphates.

Weaknesses:

The authors introduce penalty coefficients c_i to avoid steric clashes between the two DNA turns in the nucleosome. This requires c_i-values that are so high that standard deviations in the fluctuations of the simulation are smaller than in the experiments.

Reviewer #2 (Public review):

Summary:

In this study, the authors propose that there are two types of letter knowledge: knowledge about letter sound and knowledge about letter shape. Based on previous studies on implicit statistical learning in adults and babies, the authors hypothesized that passive exposure to letters in the environment allows early readers to acquire knowledge of letter shapes even before knowledge of letter-sound association. Children performed a set of experiments that measures letter shape familiarity, letter-sound association performance, visual processing of letters, and a reading-related cognitive skill. The results show that even the children who have little to no knowledge of letter names are familiar with letter shapes, and that this letter shape familiarity is predictive of performance in visual processing of letters.

Strengths:

The authors' hypothesis is based on widely accepted findings in vision science that repeated exposure to certain stimuli promotes implicit learning of, for example, statistical properties of the stimuli. They used simple and well-established tasks in large-scale experiments with a special population (i.e., children). The data analysis is quite comprehensive, accounting for any alternative explanations when needed. The data support at least a part of their hypothesis that the knowledge of letter shapes is distinct from, and precedes, the knowledge of letter-sound association, and is associated with performance in visual processing of the letters. This study shed light on a rather overlooked aspect of letter knowledge, i.e., letter shapes, challenging the idea that letters are learned only through formal instruction and calling for future research on the role of passive exposure to letters in reading acquisition.

Weaknesses:

Although the authors have successfully identified the knowledge of letter shapes as another type of letter knowledge other than the knowledge of letter-sound association, the question of whether it drives the subsequent reading acquisition remains largely unanswered, despite it being strongly implied in the Introduction. The authors collected a RAN score, which is known to robustly predict future reading fluency, but it did not show a significant partial correlation with familiarity accuracy (i.e., familiarity accuracy is not necessary to predict RAN score). The authors discussed that the performance in visual processing of letters might capture unique variance in reading fluency unexplained by RAN scores, but currently, this claim seems speculative.

Since even children without formal literacy instruction were highly familiar with letter shapes, it would be reasonable to assume that they had obtained the knowledge through passive exposure. However, the role of passive exposure was not directly tested in the study.

Given the superimposed straight lines in Figure 2, I assume the authors computed Pearson correlation coefficients. Testing the statistical significance of the Pearson correlation coefficient requires the assumption of bivariate normality (and therefore constant variance of a variable across the range of the other). According to Figure 2, this doesn't seem to be met, as the familiarity accuracy is hitting the ceiling. The ceiling effect might not be critical in Figure 2, since it tends to attenuate correlation, not inflate it. But in Figures 3 and 4, the authors' conclusion depends on the non-significant partial correlation. In fact, the authors themselves wrote that the ceiling effect might lead to a non-significant correlation even if there is an actual effect (line 404).

Reviewer #2 (Public review):

Summary:

This work investigates transcriptional responses to varying levels of transcription factors (TFs). The authors aim for gradual up- and down-regulation of three transcription factors GFI1B, NFE2 and MYB in K562 cells, by using a CRISPRa- and a CRISPRi line, together with sgRNAs of varying potency. Targeted single-cell RNA sequencing is then used to measure gene expression of a set of 90 genes, which were previously shown to be downstream of GFI1B and NFE2 regulation. This is followed by an extensive computational analysis of the scRNA-seq dataset. By grouping cells with the same perturbations, the authors can obtain groups of cells with varying average TF expression levels. The achieved perturbations are generally subtle, not reaching half or double doses for most samples, and up-regulation is generally weak below 1.5-fold in most cases. Even in this small range, many target genes exhibit a non-linear response. Since this is rather unexpected, it is crucial to rule out technical reasons for these observations.

Strengths:

The work showcases how a single dataset of CRISPRi/a perturbations with scRNA-seq readout and an extended computational analysis can be used to estimate transcriptome dose-responses, a general approach that likely can be built upon in the future.<br /> Moreover, the authors highlight tiling of sgRNAs +/-1000bp around TSS as a useful approach. Compared with conventional direct TSS-targeting (+/- 200 bp), the larger sequence window allows placing more sgRNAs. Also it requires little prior knowledge of CREs, and avoids using "attenuated" sgRNAs which would require specialized sgRNA design.

Weaknesses:

The experiment was performed in a single replicate and it would have been reassuring to see an independent validation of the main findings, for example through measuring individual dose-response curves .

Much of the analysis depends on the estimation of log-fold changes between groups of single cells with non-targeting controls and those carrying a guide RNA driving a specific knockdown. Generally, biological replicates are recommended for differential gene expression testing (Squair et al. 2021, https://doi.org/10.1038/s41467-021-25960-2). When using the FindMarkers function from the Seurat package, the authors divert from the recommendations for pseudo-bulk analysis to aggregate the raw counts (https://satijalab.org/seurat/articles/de_vignette.html). Furthermore, differential gene expression analysis of scRNA-seq data can suffer from mis-estimations (Nguyen et al. 2023, https://doi.org/10.1038/s41467-023-37126-3), and different computational tools or versions can affect these estimates strongly (Pullin et al. 2024, https://doi.org/10.1186/s13059-024-03183-0 and Rich et al. 2024, https://doi.org/10.1101/2024.04.04.588111). Therefore it would be important to describe more precisely in the Methods how this analysis was performed, any deviations from default parameters, package versions, and at which point which values were aggregated to form "pseudobulk" samples.

Two different cell lines are used to construct dose-response curves, where a CRISPRi line allows gene down-regulation and the CRISPRa line allows gene upregulation. Although both lines are derived from the same parental line (K562) the expression analysis of Tet2, which is absent in the CRISPRi line, but expressed in the CRISPRa line (Fig. S1F, S3A) suggests clonal differences between the two lines. Similarly, the UMAP in S3C and the PCA in S4A suggest batch effects between the two lines. These might confound this analysis, even though all fold changes are calculated relative to the baseline expression in the respective cell line (NTC cells). Combining log2-fold changes from the two cell lines with different baseline expression into a single curve (e.g. Fig. 3) remains misleading, because different data points could be normalized to different base line expression levels.

The study estimates the relationship between TF dose and target gene expression. This requires a system that allows quantitative changes in TF expression. The data provided does not convincingly show that this condition is met, which however is an essential prerequisite for the presented conclusions. Specifically, the data shown in Fig. S3A shows that upon stronger knock-down, a subpopulation of cells appear, where the targeted TF is not detected any more (drop-outs). Also in Fig. 3B (top) suggests that the knock-down is either subtle (similar to NTCs) or strong, but intermediate knock-down (log2-FC of 0.5-1) does not occur. Although the authors argue that this is a technical effect of the scRNA-seq protocol, it is also possible that this represents a binary behavior of the CRISPRi system. Previous work has shown that CRISPRi systems with the KRAB domain largely result in binary repression and not in gradual down-regulation as suggested in this study (Bintu et al. 2016 (https://doi.org/10.1126/science.aab2956), Noviello et al. 2023 (https://doi.org/10.1038/s41467-023-38909-4)).

One of the major conclusions of the study is that non-linear behavior is common. It would be helpful to show that this observation does not arise from the technical concerns described in the previous points. This could be done for instance with independent experimental validations.

Did the authors achieve their aims? Do the results support the conclusions?:

Some of the most important conclusions, such as the claim that non-linear responses are common, are not well supported because they rely on accurately determining the quantitative responses of trans genes, which suffers from the previously mentioned concerns.

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

Together with other recent publications, this work emphasizes the need to study transcription factor function with quantitative perturbations. The computational code repository contains all the valuable code with inline comments, but would have benefited from a readme file explaining the repository structure, package versions, and instructions to reproduce the analyses, including which input files or directory structure would be needed.

Reviewer #2 (Public review):

Summary:

Li et al. propose TSvelo, a computational framework for RNA velocity inference that models transcriptional regulation and gene-specific splicing using a neural ODE approach. The method is intended to improve trajectory reconstruction and capture dynamic gene expression changes in scRNA-seq data. However, the manuscript in its current form falls short in several critical areas, including rigorous validation, quantitative benchmarking, clarity of definitions, proper use of prior knowledge, and interpretive caution. Many of the authors' claims are not fully supported by the evidence.

Major comments:

(1) Modeling comments

(a) Lines 512-513: How does the U-to-S delay validate the accuracy of pseudotime? Using only a single gene as an example is not sufficient for "validation."

(b) Lines 512-518: The authors propose a strategy for selecting the initial state, but do not benchmark how accurate this selection procedure is, nor do they provide sufficient rationale. While some genes may indeed exhibit U-to-S delay during lineage differentiation, why does the highest U-to-S delay score indicate the correct initiation states? Please provide mathematical justification and demonstrate accuracy beyond using a single gene example. Maybe a simulation with ground truth could help here, too.

(c) Equation (8): The formulation looks to be incorrect. If $$W \in \mathbb{R}^{G\times G}$$ and $$W' - \Gamma' \in \mathbb{R}^{K\times K}$$, how can they be aligned within the same row? Please clarify.

(d) The use of prior knowledge graphs from ENCODE or ChEA to constrain regulation raises concerns. Much of the regulatory information in these databases comes from cell lines. How can such cell-line-based regulation be reliably applied to primary tissues, as is done throughout the manuscript? Additional experiments are needed to test the robustness of TSvelo with respect to prior knowledge.

(e) Lines 579-580: How is the grid search performed? More methodological details are required. If an existing method was used, please provide a citation.

(2) Application on pancreatic endocrine datasets

(a) Lines 140-141: What is the definition of the final pseudotime-fitted time t or velocity pseudotime?

(b) Lines 143-144: The use of the velocity consistency metric to benchmark methods in multi-lineage datasets is incorrect. In multi-lineage differentiation systems, cells (e.g., those in fate priming stages) may inherently show inconsistency in their velocity. Thus, it is difficult to distinguish inconsistency caused by estimation error from that arising from biological signals. Velocity consistency metrics are only appropriate in systems with unidirectional trajectories (e.g., cell cycling). The abnormally high consistency values here raise concerns about whether the estimated velocities meaningfully capture lineage differences.

(c) The improvement of TSvelo over other methods in terms of cross-boundary direction correctness looks marginal; a statistical test would help to assess its significance.

(d) Lines 177-178: Based on the figure, TSvelo does not appear to clearly distinguish cell types. A quantitative metric, such as Adjusted Rand Index (ARI), should be provided.

(e) Lines 179-183: The claim that traditional methods cannot capture dynamics in the unspliced-spliced phase portrait is vague. What specific aspect is not captured-the fitted values or something else? Evidence is lacking. Please provide a detailed explanation and quantitative metrics to support this claim.

(3) Application to gastrulation erythroid datasets

(a) Lines 191-194: The observation that velocity genes are enriched for erythropoiesis-related pathways is trivial, since the analysis is restricted to highly variable genes (HVGs) from an erythropoiesis dataset. This enrichment is expected and therefore not informative.

(b) Lines 227-228: It remains unclear how TSvelo "accurately captures the dynamics." What is the definition of dynamics in this context? Figure 3g shows unspliced/spliced vs. fitted time plots and phase portraits, but without a quantitative definition or measure, the claim of superiority cannot be supported. Visualization of a single gene is insufficient; a systematic and quantitative analysis is needed.

(4) Application to the mouse brain and other datasets

(a) Lines 280-281: The authors cannot claim that velocity streams are smoother in TSvelo than in Multivelo based solely on 2D visualization. Similarly, claiming that one model predicts the correct differentiation trajectory from a 2D projection is over-interpretation, as has been discussed in prior literature see PMID: 37885016.

(b) Lines 304-306: Beyond transcriptional signal estimation, how is regulation inferred solely from scRNA-seq data validated, especially compared with scATAC-seq data? Are there cases where transcriptome-based regulatory inference is supported by epigenomic evidence, thereby demonstrating TSvelo's GRN inference accuracy?

(c) The claim that TSvelo can model multi-lineage datasets hinges on its use of PAGA for lineage segmentation, followed by independent modeling of dynamics within each subset. However, the procedure for merging results across subsets remains unclear.

Reviewer #2 (Public review):

Summary:

This article aims to elucidate the potential roles of P-bodies in yeast adaptation to complex environmental conditions, such as the plant leaf phyllosphere. The authors demonstrated that yeast mutants defective in one of the P-body-localized proteins failed to grow in the Arabidopsis thaliana phyllosphere. They conducted detailed imaging analyses, focusing particularly on the co-localization of P-bodies and mRNAs (DAS1) related to the methanol metabolism pathway under various environmental conditions. The study newly revealed that these mRNAs form dot-like structures that occasionally co-localize with a P-body marker. Furthermore, the authors showed that the number of P-body-labeled dots increases under stress conditions, such as H₂O₂ treatment, and that mRNA dots are more frequently localized to P-body-like structures. Based on these detailed observations, the authors hypothesize that P-bodies function to protect mRNAs from degradation, particularly under stress conditions.

Strengths:

I think the authors' attempt to elucidate the potential roles of P-bodies in yeast under stress conditions is novel, and the imaging data are overall very nice.

Weaknesses:

I believe the authors could make additional efforts to more clearly demonstrate that P-bodies are indeed required for yeast proliferation in the phyllosphere, as described below, since this represents the most novel aspect of the study.

Reviewer #2 (Public review):

Summary:

This work provided experimental evidence on how geomagnetic and visual cues are integrated, and visual cues are indispensable for magnetic orientation in the nocturnal fall armyworm.

Strengths:

Although it has been demonstrated previously that the Australian Bogon moth could integrate global stellar cues with the geomagnetic field for long-distance navigation, the study presented in this manuscript is still fundamentally important to the field of magnetoreception and sensory biology. It clearly shows that the integration of geomagnetic and visual cues may represent a conserved navigational mechanism broadly employed across migratory insects. I find the research very important, and the results are presented very well.

Weaknesses:

The authors developed an indoor experimental system to study the influence of magnetic fields and visual cues on insect orientation, which is certainly a valuable approach for this field. However, the ecological relevance of the visual cue may be limited or unclear based on the current version. The visual cues were provided "by a black isosceles triangle (10 cm high, 10 cm 513 base) made from black wallpaper and fixed to the horizon at the bottom of the arena". It is difficult to conceive how such a stimulus (intended to represent a landmark like a mountain) could provide directional information for LONG-DISTANCE navigation in nocturnal fall armyworms, particularly given that these insects would have no prior memory of this specific landmark. It might be a good idea to make a more detailed explanation of this question.

Reviewer #2 (Public review):

This paper builds on prior work by some of the same authors on how to model fitness landscapes in the presence of epistasis. They have previously shown how simply writing general expansions of fitness in terms of one-body plus two-body plus three-body, etc., terms often fails to generalize to good predictions. They have also previously introduced a Gaussian process regression approach regarding how much epistasis there should be of each order.

This paper contains several main advances:

(1) They implement a more efficient form of the Gaussian process model fitting that uses GPUs and related algorithmic advances to enable better fitting of these models to datasets for larger sequences.

(2) They provide a software package implementing the above.

(3) They generalize the models to allow the extent of epistasis associated with changes in sequence to depend on specific sites, alleles, and mutations.

(4) They show modest improvements in prediction and substantial improvements in interpretability with the more generalized models above.

Overall, while this paper is quite technical, my assessment is that it represents a substantial conceptual and algorithmic advance for the above reasons, and I would recommend only modest revisions. The paper seems well-written and clear, given the inherent complexity of this topic.

Reviewer #2 (Public review):

Summary:

Hong et al. present a new method that uses a Wishart process to dramatically increase the efficiency of measuring visual sensitivity as a function of stimulus parameters for stimuli that vary in a multidimensional space. Importantly, they have validated their model against their own hold-out data and against 3 published datasets, as well as against colour spaces aimed at 'perceptual uniformity' by equating JNDs. Their model achieves high predictive success and could be usefully applied in colour vision science and psychophysics more generally, and to tackle analogous problems in neuroscience featuring smooth variation over coordinate spaces.

Strengths:

(1) This research makes a substantial contribution by providing a new method to very significantly increase the efficiency with which inferences about visual sensitivity can be drawn, so much so that it will open up new research avenues that were previously not feasible. Secondly, the methods are well thought out and unusually robust. The authors made a lot of effort to validate their model, but also to put their results in the context of existing results on colour discrimination, transforming their results to present them in the same colour spaces as used by previous authors to allow direct comparisons. Hold-out validation is a great way to test the model, and this has been done for an unusually large number of observers (by the standards of colour discrimination research). Thirdly, they make their code and materials freely available with the intention of supporting progress and innovation. These tools are likely to be widely used in vision science, and could of course be used to address analogous problems for other sensory modalities and beyond.

Weaknesses:

It would be nice to better understand what constraints the choice of basis functions puts on the space of possible solutions. More generally, could there be particular features of colour discrimination (e.g., rapid changes near the white point) that the model captures less well? The substantial individual differences evident in Figure S20 (comparison with Krauskopf and Gegenfurtner, 1992) are interesting in this context. Some observers show radial biases for the discrimination ellipses away from the white point, some show biases along the negative diagonal (with major axes oriented parallel to the blue-yellow axis), and others show a mixture of the two biases. Are these genuine individual differences, or could the model be performing less accurately in this desaturated region of colour space?

Reviewer #2 (Public review):

Summary:

This study investigates whether visuomotor mismatch responses can be detected in humans. By adapting paradigms from rodent studies, the authors report EEG evidence of mismatch responses during visuomotor conditions and compare them to visual-only stimulation and mismatch responses in other modalities.

Strengths:

(1) The authors use a creative experimental design to elicit visuomotor mismatch responses in humans.

(2) The study provides an initial dataset and analytical framework that could support future research on human visuomotor prediction errors.

Weaknesses:

(1) Methodological issues (e.g., volume conduction, channel selection, lack of control for eye movements) make it difficult to confidently attribute the observed mismatch responses to activity in visual cortical regions.

(2) A very large portion of the data was excluded due to motion artefacts, raising concerns about statistical power and representativeness. The criteria for trial inclusion and the number of accepted trials per participant appear arbitrary and not justified with reference to EEG reliability standards.

(3) The comparison across sensory modalities (e.g., auditory vs. visual mismatch responses) is conceptually interesting, but due to the choice of analyzing auditory mismatch responses over occipital channels, it has limited interpretability.

The authors successfully demonstrate that visuomotor mismatch paradigms can, in principle, be applied in human EEG. However, due to the issues outlined above, the current findings are relatively preliminary. If validated with improved methodology, this approach could significantly advance our understanding of predictive processing in the human visual system and provide a translational bridge between rodent and human work.

Reviewer #2 (Public review):

Summary:

In 2014, Wang et al. showed that noninvasive stimulation of a parietal site, connected functionally to the hippocampus, increased resting state connectivity throughout a canonical network associated with episodic memory. It also produced a memory boost, which correlated with the connectivity increase across subjects. Their discovery that an imaging biomarker could be used to target a network (rather than a single cortical site) in individual subjects and provide a scaling measure of target modulation should have revolutionized the noninvasive neuromodulation field. This meta-analysis by members of the same group covers memory effects from noninvasive stimulation of various nodes of the "hippocampal" network.

Strengths:

This is a very timely summary and meta-analysis of this very promising application of TMS. To the limited extent of my expertise in meta-analysis, the methodology seems rigorous, and the central finding, that high-frequency stimulation of nodes in the hippocampal network reproducibly improves event recall, is amply supported. This should provide impetus for larger clinical trials and further quantification of the optimal dose, duration of effect, etc.

Weaknesses:

My critical comments are mainly on the framing and argument:

(1) While the introduction centers on the role of the hippocampus in episodic memory and posits hippocampal neuromodulation by TMS as causative, the true mechanism may be more complex. Clean hippocampal lesions in primates cause focal loss of spatial and place memory, and I am aware of no specific evidence that the hippocampus does more than this in humans. Moreover, there is evidence that lateral parietal TMS also reaches neighboring temporal lobe regions, which contribute to episodic memory. The hippocampus may, therefore, be a reliable deep seed for connectivity-based targeting of the episodic memory network, but might not be the true or only functional target.

(2) The meta-analysis combines studies with confirmation of targeting and target-network engagement from fMRI and studies without independent evidence of having stimulated the putative target (e.g., Koch et al). That seems like a more important methodological distinction than merely the use of any individual targeting method. In my experience, atlas-based estimates are at least as accurate as eyeballing cortical areas in individuals. Hence, entering individual functional targeting as a factor might reveal an effect on efficacy.

(3) The funnel plot and Egger's regression for episodic memory outcomes suggested possible bias, and the average sample size of 23 is small, contributing to the likelihood of false positive results. It would be informative, therefore, to know how many or which studies had formal power estimates and what the predicted effect sizes were.

(4) In the Discussion, the authors might provide a comparison between the effect size for memory improvement found here with those reported for other brain-targeted interventions and behavioral strategies. It may also be worthwhile pointing out that HITS/memory is one of the very few, or perhaps the only, neuromodulatory effects on cognition that has been extensively reproduced and survived rigorous meta-analysis.

(5) The section of the Discussion on specificity compares HITS to transcranial electrical stimulation without specifying an anatomical target or intended outcome. A better contrast might be the enormous variety of cognitive and emotional effects claimed for TMS of the dorsolateral prefrontal cortex.

(6) With reference to why other nodes in the episodic memory network have not been tested, current flow modeling shows TMS of the medial prefrontal cortex is unlikely to be achievable without stronger stimulation of the convexity under the coil, in addition to being uncomfortable. The lateral temporal lobe has been stimulated without undue discomfort.

(7) Finally, a critical question hanging over the clinical applicability of HITS and other neuromodulation techniques is how well they will work on a damaged substrate. Functional and/or anatomical imaging might answer this question and help screen for likely responders. The authors' opinion on this would be informative.

Reviewer #2 (Public review):

Transcranial magnetic stimulation is used in several medical conditions to alter brain activity, probably by induction of synaptic plasticity. The authors pursue the idea to personalise parameters of the stimulation protocol by adapting the stimulation frequency to an individual's brain rhythm. The authors test this approach in a population model connecting the cortex with deeper brain areas, the thalamocortical loop, which includes calcium-dependent plasticity for the connections within and between brain regions. While the authors relate literature-based experimental findings with their results, their results are so far not supported by experimental work.

The authors successfully highlight in their model that personalization of rTMS stimulation frequency to the brain intrinsic frequency has the potential to improve stimulation impact, and they relate this to specific changes in the network. Their arguments that this resonance improves efficacy are intuitive, and their finding that inhibition and excitation are selectively modulated is a good starting point for analysing the underlying mechanism.

As rTMS is used in clinical contexts, and the idea of aligning intrinsic and stimulation frequency is relatively easy to implement, the paper is conceptually of interest for the rTMS community, despite its weak points on the mechanistic explanation. The authors made the simulation code publicly available, which is a useful resource for further studies on the effects of metaplasticity. The same stimulation parameters have been tested in experiments, and a reanalysis of the experimental results following the idea of this paper could be influential for clinical optimisation of stimulation protocols.

A strength of the paper is that it takes into account also deeper brain areas, and their interaction with the cortex. The paper carefully measures system changes in response to different frequency differences between thalamocortical loop and stimulation. By explicitly modelling changes to connections, the authors do start dissect the mechanism underlying the observed effect. Unfortunately, the dissection of the mechanistic underpinning in the current version of the manuscript does not yet fully exploits the possibility of a computational model. Here are a couple of points related to this critique:

(1) The study reports that connections between thalamus and cortex as well as within the thalamus change, but the model is not used to separate the influence of both.

(2) The paper reports that a resonance between stimulation and brain increases stimulation effectiveness. This conclusion is solely based on the observation of strong reactions in the network to subharmonics of the brain's frequency, and lacks further support such as alternative measures of resonance, or an analysis of the role of the phase difference between stimulation and brain oscillation, which is likely changed by the stimulation. For example, for harmonic oscillators, resonance leads to a 90 degree phase difference between driving force and system response, and for rTMS, phase locking has been shown to be relevant.

(3) The authors claim that over-engagement of plasticity for HF-rTMS makes their intermittent protocol more effective. Yet, the study lacks a direct comparison between stimulation protocols that shows over-engagement of plasticity for the HF-protocol. The study also does not explore which time-scale of the plasticity mechanism rules the optimal stimulation protocol. Moreover, the study reports that only few number of pulses per burst show a good effect. This should depend on how strongly a single pulse changes the calcium volume, but this relation was not explored in the model.

(4) The authors report on the frequency spectrum of the cortical excitatory population, with the argument that the power of this population is most closely related to EEG measurements. A report of the other neuronal populations is missing, which might be informative on what is going on in the network.

Statistics:

(1) The authors do not state whether they test for assumptions of the multiple regression analysis, such as whether errors have equal variance or that residuals are normally distributed.

(2) For the statistical analysis, the authors ignore about half of their model simulations for which the change in the power was negligible. It is not clear to me which statistical analysis is meant; whether the figures show all model simulations, whether regression lines where evaluated ignoring them, and whether the multiple regression analysis used only half of the data points.

Reviewer #2 (Public review):

Summary:

This manuscript presents a technically oriented application of UMI-based long-read sequencing to study intra-host diversity in influenza virus populations. The authors aim to minimize sequencing artifacts and improve the detection of rare variants, proposing that this approach may inform predictive models of viral evolution. While the methodology appears robust and successfully reduces sequencing error rates, key experimental and analytical details are missing, and the biological insight is modest. The study includes only four samples, with no independent biological replicates or controls, which limits the generalizability of the findings. Claims related to rare variant detection and evolutionary selection are not fully supported by the data presented.

Strengths:

The study addresses an important technical challenge in viral genomics by implementing a UMI-based long-read sequencing approach to reduce amplification and sequencing errors. The methodological focus is well presented, and the work contributes to improving the resolution of low-frequency variant detection in complex viral populations.

Weaknesses:

The application of UMI-based error correction to viral population sequencing has been established in previous studies (e.g., in HIV), and this manuscript does not introduce a substantial methodological or conceptual advance beyond its use in the context of influenza.

The study lacks independent biological replicates or additional viral systems that would strengthen the generalizability of the conclusions. Potential sources of technical error are not explored or explicitly controlled. Key methodological details are missing, including the number of PCR cycles, the input number of molecules, and UMI family size distributions. These are essential to support the claimed sensitivity of the method.

The assertion that variants at {greater than or equal to}0.1% frequency can be reliably detected is based on total read count rather than the number of unique input molecules. Without information on UMI diversity and family sizes, the detection limit cannot be reliably assessed.

Although genetic variation is described, the functional relevance of observed mutations in HA and NA is not addressed or discussed in the context of known antigenic or evolutionary features of influenza. The manuscript is largely focused on technical performance, with limited exploration of the biological implications or mechanistic insights into influenza virus evolution.

The experimental scale is small, with only four viral populations derived from single particles analyzed. This limited sample size restricts the ability to draw broader conclusions about quasispecies dynamics or evolutionary pressures.

Comments on revisions:

The revised manuscript provides additional methodological detail and clearer presentation, which improves transparency. However, the main limitations persist: the study remains small in scale, lacks independent validation, and relies on theoretical rather than empirical support for its claimed detection sensitivity. As a result, the work represents a modest technical advance rather than a substantive contribution to understanding influenza virus evolution.

Reviewer #2 (Public review):

The authors present a combined experimental and theoretical workflow to study partitioning noise arising during cell division. Such quantifications usually require time-lapse experiments, which are limited in throughput. To bypass these limitations, the authors propose to use flow-cytometry measurements instead and analyse them using a theoretical model of partitioning noise. The problem considered by the authors is relevant and the idea to use statistical models in combination with flow cytometry to boost statistical power is elegant. The authors demonstrate their approach using experimental flow cytometry measurements and validate their results using time-lapse microscopy. The approach focuses on a particular case, where the dynamics of the labelled component depends predominantly on partitioning, while turnover of components is not taken into account. The description of the methods is significantly clearer than in the previous version of the manuscript.

Reviewer #2 (Public review):

Summary:

The authors set out to test whether a TMS-induced reduction in excitability of the left Superior Frontal Sulcus influenced evidence integration in perceptual and value-based decisions. They directly compared behaviour-including fits to a computational decision process model---and fMRI pre and post TMS in one of each type of decision-making task. Their goal was to test domain-specific theories of the prefrontal cortex by examining whether the proposed role of the SFS in evidence integration was selective for perceptual but not value-based evidence.

Strengths:

The paper presents multiple credible sources of evidence for the role of the left SFS in perceptual decision making, finding similar mechanisms to prior literature and a nuanced discussion of where they diverge from prior findings. The value-based and perceptual decision-making tasks were carefully matched in terms of stimulus display and motor response, making their comparison credible.

Weaknesses:

-I was confused about the model specification in terms of the relationship between evidence level and drift rate. While the methods (and e.g. supplementary figure 3) specify a linear relationship between evidence level and drift rate, suggesting, unless I misunderstood, that only a single drift rate parameter (kappa) is fit. However, the drift rate parameter estimates in the supplementary tables (and response to reviewers) do not scale linearly with evidence level.

-The fit quality for the value-based decision task is not as good as that for the PDM, and this would be worth commenting on in the paper.

Reviewer #2 (Public review):

This manuscript explores the mechanisms underlying cerebral cortical folding using a combination of physical modelling, computational simulations, and geometric morphometrics. The authors extend their prior work on human brain development (Tallinen et al., 2014; 2016) to a comparative framework involving three mammalian species: ferrets (Carnivora), macaques (Old World monkeys), and humans (Hominoidea). By integrating swelling gel experiments with mathematical differential growth models, they simulate sulcification instability and recapitulate key features of brain folding across species. The authors make commendable use of publicly available datasets to construct 3D models of fetal and neonatal brain surfaces: fetal macaque (ref. [26]), newborn ferret (ref. [11]), and fetal human (ref. [22]).

Using a combination of physical models and numerical simulations, the authors compare the resulting folding morphologies to real brain surfaces using morphometric analysis. Their results show qualitative and quantitative concordance with observed cortical folding patterns, supporting the view that differential tangential growth of the cortex relative to the subcortical substrate is sufficient to account for much of the diversity in cortical folding. This is a very important point in our field, and can be used in the teaching of medical students.

Brain folding remains a topic of ongoing debate. While some regard it as a critical specialization linked to higher cognitive function, others consider it an epiphenomenon of expansion and constrained geometry. This divergence was evident in discussions during the Strüngmann Forum on cortical development (Silver et al., 2019). Though folding abnormalities are reliable indicators of disrupted neurodevelopmental processes (e.g., neurogenesis, migration), their relationship to functional architecture remains unclear. Recent evidence suggests that the absolute number of neurons varies significantly with position-sulcus versus gyrus-with potential implications for local processing capacity (e.g., https://doi.org/10.1002/cne.25626). The field is thus in need of comparative, mechanistic studies like the present one.

This paper offers an elegant and timely contribution by combining gel-based morphogenesis, numerical modelling, and morphometric analysis to examine cortical folding across species. The experimental design - constructing two-layer PDMS models from 3D MRI data and immersing them in organic solvents to induce differential swelling - is well-established in prior literature. The authors further complement this with a continuum mechanics model simulating folding as a result of differential growth, as well as a comparative analysis of surface morphologies derived from in vivo, in vitro, and in silico brains.

Conclusion:

This is a well-executed and creative study that integrates diverse methodologies to address a longstanding question in developmental neurobiology. While a few aspects-such as regional folding peculiarities, sensitivity to initial conditions, and available human data-could be further elaborated, they do not detract from the overall quality and novelty of the work. I enthusiastically support this paper and believe that it will be of broad interest to the neuroscience, biomechanics, and developmental biology communities.

[Editor's note: The reviewers were satisfied with the authors' response. The eLife Assessment was slightly updated to reflect the author's response.]

Reviewer #2 (Public Review):

Verma et al. provide a short technical report showing that endogenously tagged dynein and dynactin molecules localize to growing microtubule plus-ends and also move processively along microtubules in cells. The data are convincing, and the imaging and movies very nicely demonstrate their claims. I don't have any large technical concerns about the work. It is perhaps not surprising that dynein-dynactin complexes behave this way in cells due to other reports on the topic, but the current data are among some of the nicest direct demonstrations of this phenomenon. It may be somewhat controversial since a separate group has reported that dynein does not move processively in mammalian cells

(https://www.biorxiv.org/content/10.1101/2021.04.05.438428v3).

Reviewer #2 (Public review):

The authors provide convincing data from a whole set of different binding kinetic and thermodynamic experiments to explore whether glutamine binding protein binds glutamine via an induced fit or a conformational selection process.

Weaknesses:

The single-molecule TIRF-smFRET data appear to include spots that may represent more than one molecule, which raises the general issue of how rigorously traces were selected for single photobleaching events.

Reviewer #2 (Public review):

Summary:

In the manuscript by Mahen et al., entitled "Gut Microbe-Derived Trimethylamine Shapes Circadian Rhythms Through the Host Receptor TAAR5," the authors investigate the interplay between a host G protein-coupled receptor (TAAR5), the gut microbiota-derived metabolite trimethylamine (TMA), and the host circadian system. Using a combination of genetically engineered mouse and bacterial models, the study demonstrates a link between microbial signaling and circadian regulation, particularly through effects observed in the olfactory system. Overall, this manuscript presents a novel and valuable contribution to our understanding of host-microbe interactions and circadian biology. The addition of new data following revision adds mechanistic depth to more fully support the authors' conclusions.

Strengths:

(1) The manuscript addresses an important and timely topic in host-microbe communication and circadian biology.

(2) The studies employ multiple complementary models, e.g., Taar5 knockout mice, microbial mutants, which enhances the depth of the investigation.

(3) The integration of behavioral, hormonal, microbial, and transcript-level data provides a multifaceted view of the observed phenotype.

(4) Inclusion of rhythmic analysis of a defined microbial community adds novelty and strength to the overall findings.

(5) The identification of olfactory-linked circadian changes in the context of gut microbes adds a novel perspective to the field.

Weaknesses:

(1) While the authors suggest a causal role for TAAR5 and its ligand in circadian regulation, some of the data remain correlative in this context; however, the authors have appropriately tempered these claims, and mechanistic experiments are proposed to expand upon their compelling findings in future work.

Reviewer #2 (Public review):

This manuscript describes the use of a powerful technique called microfluidics to elucidate the mechanisms explaining how overexpression (OE) of Ssd1 and caloric restriction (CR) in yeast extend replicative lifespan (RLS). Microfluidics measures RLS by trapping cells in chambers mounted to a slide. The chambers hold the mother cell but allow daughters to escape. The slide, with many chambers, is recorded during the entire process, roughly 72 hours, with the video monitored afterwards to count how many daughters each of the trapped mothers produces. The power of the method is what can be done with it. For example, the entire process can be viewed by fluorescence so that GFP and mCherry-tagged proteins can be followed as cells age. The budding yeast is the only model where bona fide replicative aging can be measured, and microfluidics is the only system that allows protein localization and levels to be measured in a single cell while aging. The authors do a wonderful job of showing what this combination of tools can do.

The authors had previously shown that Ssd1, an mRNA-binding protein, extends RLS when overexpressed. This was attributed to Ssd1 sequestering away specific mRNAs under stress, likely leading to reduced ribosomal function. It remained completely unknown how Ssd1 OE extended RLS. The authors observed that overexpressed, but not normally expressed, Ssd1 formed cytoplasmic condensates during mitosis that are resolved by cytokinesis. When the condensates fail to be resolved at the end of mitosis, this signals death.

It has become clear in the literature that iron accumulation increases with age within the cell. The transcriptional programs that activate the iron regulon also become elevated in aging cells. This is thought to be due to impaired mitochondrial function in aging cells, with increased iron accumulation as an attempt at restoring mitochondrial activity. The authors show that Ssd1 OE and CR both reduce the expression of the iron regulon. The data presented indicate that iron accumulation shortens RLS: deletion of iron regulon components extends RLS, and adding iron to WT cells decreases RLS, but not when Ssd1 is overexpressed or when cells are calorically restricted. Interestingly, iron chelation using BPS has no impact on WT RLS, but decreases the elevated RLS in CR cells and cells overexpressing Ssd1. It was not initially clear why iron chelation would inhibit the extended lifespan seen with CR and Ssd1 OE. This was addressed by an experiment where it was shown that the iron regulon is induced (FIT2 induction) when iron is chelated. Thus, the detrimental effects of induction of the iron regulon by BPS and iron accumulation on RLS cannot be tempered by Ssd1 OE and CR once turned on.

Comments on Revised Version:

I am content with the authors' responses to my prior comments.

Reviewer #2 (Public review):

Summary:

This study examines the dynamic interplay between infant attention and hierarchical maternal behaviors from a social information processing perspective. By employing a comprehensive naturalistic framework, the author quantified interactions across both low-level (sensory) and high-level (semantic) features. With correlation analysis with these features, they found that within social contexts, behaviors such as joint attention - shaped by mutual interaction - exhibit patterns distinct from unilateral responding or mimicry. In contrast to traditional semi-structured behavioral observation and coding, the methods employed in this study were designed to consciously and sensitively capture these dynamic features and relate them temporally. This approach contributes to a more integrated understanding of the developmental principles underlying capacities like joint action and communication.

Strengths:

The manuscript's core strength lies in its innovative, dynamic, and hierarchical framework for investigating early social attention. The findings reveal complex adaptive scaffolding strategies: for instance, when infants focus on objects, mothers reduce low-level sensory input, minimising distractions. Furthermore, the results indicate that, even from early development, maternal behaviors are both driven by and predictive of infant attention, confirming that attention involves complex interactive processes that unfold across multiple levels, from salience to semantics.

From a methodological standpoint, the use of unstructured play situations, combined with multi-channel, high-precision time-series analyses, undoubtedly required substantial effort in both data collection and coding. Compared to the relatively two-dimensional analytical approaches common in prior research, this study's introduction of lower-level and higher-level features to explore the hierarchical organization of processing across development is highly plausible. The psychological processes reflected by these quantified physical features span multiple domains - including emotion, motion, and phonetics - and the high temporal sampling rate ensures fine-grained resolution.

Critically, these features are extracted through a suite of advanced machine learning and computational methods, which automate the extraction of objective metrics from audiovisual data. Consequently, the methodological flow significantly enhances data utilization and offers valuable inspiration for future behavioral coding research aiming for high ecological validity.

Weaknesses:

The conclusion of this paper is generally supported by the data and analysis, but some aspects of data analysis need to be clarified and extended.

(1) A more explicit justification for the selection and theoretical categorization of the eight interaction features may be needed. The paper introduces a distinction between "lower-level" and "higher-level" features but does not clearly articulate the criteria underpinning this classification. While a continuum is acknowledged, the practical division requires a principled rationale. For instance, is the classification based on the temporal scale of the features, the degree of cognitive processing required for their integration, or their proximity to sensory input versus semantic meaning?

(2) The claims regarding age-related differences in Predictions 2 are not fully substantiated by the current analyses. The findings primarily rely on observing that an effect is significant in one age group but not the other (e.g., the association between object naming and attention is significant at 15 months but not at 5 months). However, this pattern alone does not constitute evidence about whether the two age groups differ significantly from each other. The absence of a direct statistical comparison (e.g., an interaction test in a model that includes age as a factor) creates an inferential gap. To robustly support developmental change, formal tests of the Age × Feature interaction on infant attention are required.

(3) Another potential methodological issue concerns the potential confounding effect of parents' use of the infant's name. The analysis of "object naming" does not clarify whether utterances containing object words (e.g., "panda") were distinct from those that also incorporated the infant's name (e.g., "Look, Sarah, the panda!"). Given that a child's own name is a highly salient social cue known to robustly capture infant attention, its co-occurrence with object labels could potentially inflate or confound the measured effect of object naming itself. It would be important to know whether and how frequently infants' names were called, whether this variable was analyzed separately, and if its effect was statistically disentangled from that of pure object labeling.

(4) Interpretation of results requires clarification regarding the extended temporal lags reported, specifically the negative correlation between maternal vocal spectral flux and infant attention at 6.54 to 9.52 seconds (Figure 4C). The authors interpret this as a forward-prediction, suggesting that a decrease in acoustic variability leads to increased infant attention several seconds later. However, a lag of such duration seems unusually long for a direct, contingent infant response to a specific vocal feature. Is there existing empirical evidence from infant research to support such a prolonged response latency? Alternatively, could this signal suggest a slower, cyclical pattern of the interaction rather than a direct causal link?

Reviewer #2 (Public review):

Summary:

In Maggi et al., the authors investigated the mechanisms that regulate the dynamics of a specialized junctional structure called junction-based lamellipodia (JBL), which they have previously identified during multicellular vascular tube formation in the zebrafish. They identified the Arp2/3 complex to dynamically localize at expanding JBLs and showed that the chemical inhibition of Arp2/3 activity slowed junctional elongation. The authors therefore concluded that actin polymerization at JBLs pushes the distal junction forward to expand the JBL. They further revealed the accumulation of Myl9a/Myl9b (marker for MLC) at the junctional pole, at interjunctional regions, suggesting that contractile activity drives the merging of proximal and distal junctions. Indeed, chemical inhibition of ROCK activity decreased junctional mergence. With these new findings, the authors added new molecular and cellular details into the previously proposed clutch mechanism by proposing that Arp2/3-dependent actin polymerization provides pushing forces while actomyosin contractility drives the merging of proximal and distal junctions, explaining the oscillatory protrusive nature of JBLs.

Strengths:

The authors provide detailed analyses of endothelial cell-cell dynamics through time-lapse imaging of junctional and cytoskeletal components at subcellular resolution. The use of zebrafish as an animal model system is invaluable in identifying novel mechanisms that explain the organizing principles of how blood vessels are formed. The data is well presented, and the manuscript is easy to read.

Weaknesses:

While the data generally support the conclusions reached, some aspects can be strengthened. For the untrained eye, it is unclear where the proximal and distal junctions are in some images, and so it is difficult to follow their dynamics (especially in experiments where Cdh5 is used as the junctional marker). Images would benefit from clear annotation of the two junctions. All perturbation experiments were done using chemical inhibitors; this can be further supported by genetic perturbations.

Reviewer #2 (Public Review):

Summary:

The authors of this manuscript address an important question regarding how macrophages respond to external stimuli to create different functional phenotypes, also known as macrophage polarization. Although this has been studied extensively, the authors argue that the transcription factors that mediate the change in state in response to a specific trigger remain unknown. They create a "master" human gene regulatory network and then analyze existing gene expression data consisting of PBMC-derived macrophage response to 28 stimuli, which they sort into thirteen different states defined by perturbed gene expression networks. They then identify the top transcription factors involved in each response that have the strongest predicted association with the perturbation patterns they identify. Finally, using S. aureus infection as one example of a stimulus that macrophages respond to, they infect THP-1 cells while perturbing regulatory factors that they have identified and show that these factors have a functional effect on the macrophage response.

Strengths:

The computational work done to create a "master" hGRN, response networks for each of the 28 stimuli studied, and the clustering of stimuli into 13 macrophage states is useful. The data generated will be a helpful resource for researchers who want to determine the regulatory factors involved in response to a particular stimulus and could serve as a hypothesis generator for future studies.

The streamlined system used here - macrophages in culture responding to a single stimulus - is useful for removing confounding factors and studying the elements involved in response to each stimulus.

The use of a functional study with S. aureus infection is helpful to provide proof of principle that the authors' computational analysis generates data that is testable and valid for in vitro analysis.

[Reviewing Editor comments on revised version: the authors have made minimal changes and we have made a modest modification to the eLife Assessment, without returning the revised version to the original reviewers.]

Reviewer #2 (Public review):

Summary:

Through this study the authors combine a number of innovative technologies including scRNAseq to provide insight into Crohn's disease. Importantly, samples from pediatric patients are included. The authors develop a principled and unbiased tiered clustering approach, termed ARBOL. Through high-resolution scRNAseq analysis the authors identify differences in cell subsets and states during pediCD relative to FGID. The authors provide histology data demonstrating T cell localisation within the epithelium. Importantly, the authors find anti-TNF treatment pushes the pediatric cellular ecosystem towards an adult state.

Strengths:

This study is well presented. The introduction clearly explains the important knowledge gaps in the field, the importance of this research, the samples that are used and study design.<br /> The results clearly explain the data, without overstating any findings. The data is well presented. The discussion expands on key findings and any limitations to the study are clearly explained.

I think the biological findings from and bioinformatic approach used in, this study, will be of interest to many and significantly add to the field.

Weaknesses:

(1) The ARBOL approach for iterative tiered clustering on a specific disease condition was demonstrated to work very well on the datasets generated in this study where there were no obvious batch effects across patients. What if strong batch effects are present across donors where PCA fails to mitigate such effects? Are there any batch correction tools implemented in ARBOL for such cases?

The authors have addressed this comment during review

(2) The authors mentioned that the clustering tree from the recursive sub-clustering contained too much noise, and they therefore used another approach to build a hierarchical clustering tree for the bottom-level clusters based on unified gene space. But in general, how consistent are these two trees?

The authors have addressed this comment during review

Comments on revisions:

I have no additional comments. The authors addressed my previous comments well.

Reviewer #2 (Public review):

Summary:

Dong et al. present a thorough investigation into the potential of repurposing citalopram, an SSRI, for hepatocellular carcinoma (HCC) therapy. The study highlights the dual mechanisms by which citalopram exerts anti-tumor effects: reprogramming tumor-associated macrophages (TAMs) toward an anti-tumor phenotype via C5aR1 modulation and suppressing cancer cell metabolism through GLUT1 inhibition, while enhancing CD8+ T cell activation. The findings emphasize the potential of drug repurposing strategies and position C5aR1 as a promising immunotherapeutic target.

Strengths:

It provides detailed evidence of citalopram's non-canonical action on C5aR1, demonstrating its ability to modulate macrophage behavior and enhance CD8+ T cell cytotoxicity. The use of DARTS assays, in silico docking, and gene signature network analyses offers robust validation of drug-target interactions. Additionally, the dual focus on immune cell reprogramming and metabolic suppression presents a comprehensive strategy for HCC therapy. By highlighting the potential for existing drugs like citalopram to be repurposed, the study also emphasizes the feasibility of translational applications. During revision, the authors experimentally demonstrated that TAM has lower GLUT1, which further strengthens their claim of C5aR1 modulation-dependent TAM improvement for tumor therapy.

Weaknesses:

The authors proposed that CD8+ T cells have an TAM-independent role upon Citalropharm treatment. However, this claim requires further investigation to confirm that the effect is truly "TAM independent".

Reviewer #2 (Public review):

Summary:

This is a well-conducted and clearly written manuscript addressing the link between population receptive fields (pRFs) and visual behavior. The authors test whether developmental prosopagnosia (DP) involves atypical pRFs in face-selective regions, a hypothesis suggested by prior work with a small DP sample. Using a larger cohort of DPs and controls, robust pRF mapping with appropriate stimuli and CSS modeling, and careful in-scanner eye tracking, the authors report no group differences in pRF properties across the visual processing hierarchy. These results suggest that reduced spatial integration is unlikely to account for holistic face processing deficits in DP.

Strengths:

The dataset quality, sample size, and methodological rigor are notable strengths.

Weaknesses:

The primary concern is the interpretation of the results.

(1) Relationship between pRFs and spatial integration

While atypical pRF properties could contribute to deficits in spatial integration, impairments in holistic processing in DPs are not necessarily caused by pRF abnormalities. The discussion could be strengthened by considering alternative explanations for reduced spatial integration, such as altered structural or functional connectivity in the face network, which has been reported to underlie DP's difficulties in integrating facial features.

(2) Beyond the null hypothesis testing framework

The title claims "normal spatial integration," yet this conclusion is based on a failure to reject the null hypothesis, which does not justify accepting the alternative hypothesis. To substantiate a claim of "normal," the authors would need to provide analyses quantifying evidence for the absence of effects, e.g., using a Bayesian framework.

(3) Face-specific or broader visual processing

Prior work from the senior author's lab (Jiahui et al., 2018) reported pronounced reductions in scene selectivity and marginal reductions in body selectivity in DPs, suggesting that visual processing deficits in DPs may extend beyond faces. While the manuscript includes PPA as a high-level control region for scene perception, scene selectivity was not directly reported. The authors could also consider individual differences and potential data-quality confounds (tSNR difference between and within groups, several obvious outliers in the figures, etc). For instance, examining whether reduced tSNR in DPs contributed to lower face selectivity in the DP group in this dataset.

(4) Linking pRF properties to behavior

The manuscript aims to examine the relationship between pRF properties and behavior, but currently reports only one aspect of pRF (size) in relation to a single behavioral measure (CFMT), without full statistical reporting:

"We found no significant association between participants' CFMT scores and mean pRF size in OFA, pFUS, or mFUS."

For comprehensive reporting, the authors could examine additional pRF properties (e.g., center, eccentricity, scaling between eccentricity and pRF size, shape of visual field coverage, etc), additional ROIs (early, intermediate, and category-selective areas), and relate them to multiple behavioral measures (e.g., HEVA, PI20, FFT). This would provide a full picture of how pRF characteristics relate to behavioral performance in DP.

Reviewer #2 (Public review):

Summary:

This work by Prentis and Bakkour examines how predictive memory can become distorted in multidimensional environments and how inductive biases may mitigate these distortions. Using both computational simulations and an original human-robot building task with manipulated semantic congruency, the authors show that spurious observations can amplify noise throughout memory. They hypothesize, and preliminarily support, that humans deploy inductive biases to suppress such spurious information.

Strengths:

(1) The manuscript addresses an interesting and understudied question-specifically, how learning is distorted by spurious observations in high-dimensional settings.

(2) The theoretical modeling and feature-based successor representation analyses are methodologically sound, and simulations illustrate expected memory distortions due to multidimensional transitions.

(3) The behavioral experiment introduces a creative robot-building paradigm and manipulates transitions to test the effect of semantic congruency (more so category part congruency as explained below).

Weaknesses:

(1) The semantic manipulation may be more about category congruence (e.g., body part function) than semantic meaning. The robot-building task seems to hinge on categorical/functional relationships rather than semantic abstraction. Strong evidence for semantic learning would require richer, more genuinely semantic manipulations.

(2) The experimental design remains limited in dimensionality and depth. Simulated higher-dimensional or deeper tasks (or empirical follow-up) would strengthen the interpretation and relevance for real-world memory distortion.

(3) The identification of idiosyncratic biases appears to reflect individual variation in categorical mapping rather than semantic processing. The lack of conjunctive learning may simply reflect variability in assumed builder-target mappings, not a principled semantic effect.

Additional Comments:

(1) It is unclear whether this task primarily probes memory or reinforcement learning, since the graded reward feedback in the current design closely aligns with typical reinforcement learning paradigms.

(2) It may be unsurprising that the feature-based successor model fits best given task structure, so broader model comparisons are encouraged.

(3) Simulation-only work on higher dimensionality (lines 514-515) falls short; an empirical follow-up would greatly enhance the claims.

Reviewer #2 (Public review):

Summary:

This study reports a highly unconventional mechanism by which AGC kinases might undergo reversible activation-loop (T-loop) phosphorylation through an ATP-independent phosphate recycling process that is modulated by alkali metal ions such as Na⁺ and K⁺. The authors propose that these ions trigger phosphate dissociation and subsequent reattachment in the absence of ATP or canonical kinase activity, implying the existence of a novel phosphate-transferring intermediate. If validated, this would represent a radical departure from established models of kinase regulation and signal transduction. I note that this study is personally funded by one of the authors.

Strengths:

The study addresses an important and fundamental question in protein phosphorylation biology. The authors have conducted an impressive number of biochemical experiments spanning cellular and in vitro systems, with multiple orthogonal readouts. The idea of an ATP-independent phosphate recycling mechanism is original and thought-provoking, challenging conventional assumptions and inviting further exploration. The manuscript is well organized and written with considerable technical detail.

Weaknesses:

The central mechanistic claim contradicts extensive existing evidence on AGC kinase regulation derived from decades of biochemical, mechanistic, pharmacological, genetic, and structural studies. The data, while extensive, do not provide sufficiently direct or quantitative evidence to support the existence of ATP-independent phosphate transfer. Alternative explanations, such as low-level residual ATP-dependent re-phosphorylation or assay artifacts, are not fully excluded. They claim that an unidentified factor-x is involved, but do not provide evidence for the existence of this molecule or characterize this. The physiological relevance of the ion concentrations used is unclear, as the conditions far exceed normal intercellular levels. Overall, the findings are not yet convincing enough to support a paradigm shift in our understanding of AGC kinase activation, in my opinion.

Reviewer #2 (Public review):

Summary:

Ji, Ma, and colleagues report the discovery of a mechanism in C. elegans that mediates transcriptional responses to low-intensity light stimuli. They find that light-induced transcription requires a pair of bZIP transcription factors and induces expression of a cytochrome P450 effector. This unexpected light-sensing mechanism is required for physiologically relevant gene expression that controls behavioral plasticity. The authors further show that this mechanism can be co-opted to create light-inducible transgenes.

Strengths:

The authors rigorously demonstrate that ambient light stimuli regulate gene expression via a mechanism that requires the bZIP factors ZIP-2 and CEBP-2. Transcriptional responses to light stimuli are measured using transgenes and using measurements of endogenous transcripts. The study shows proper genetic controls for these effects. The study shows that this light-response does not require known photoreceptors, is tuned to specific wavelengths, and is highly unlikely to be an artifact of temperature-sensing. The study further shows that the function of ZIP-2 and CEBP-2 in light-sensing can be distinguished from their previously reported role in mediating transcriptional responses to pathogenic bacteria. The study includes experiments that demonstrate that regulatory motifs from a known light-response gene can be used to confer light-regulated gene expression, demonstrating sufficiency and suggesting an application of these discoveries in engineering inducible transgenes. Finally, the study shows that ambient light and the transcription factors that transduce it into gene expression changes are required to stabilize a learned olfactory behavior, suggesting a physiological function for this mechanism.

Weaknesses:

The study implies but does not show that the effects of ambient light on stabilizing a learned olfactory behavior are through the described pathway. To show this clearly, the authors should determine whether ambient light has any effect on mutants lacking CYP-14A5, ZIP-2, or CEBP-2. Other minor edits to the text and figures are suggested.

Reviewer #2 (Public review):

Summary:

This important study describes a deep learning framework that analyzes single-cell RNA data to identify tumor-agnostic gene signature associated with brain metastases. The identified signature uncovers key molecular mechanisms like VEGF signaling and highlights its potential therapeutic targets. It also assessed the performance of the gene signature in liquid biopsy and showed that the brain metastases signature yields a robust, metastasis-specific transcriptional signal in circulating platelets, suggesting potential for non-invasive diagnostics.

Strengths:

(1) The approach is multi-cancer, identifying mechanisms shared across diseases beyond tumor-specific constraints.

(2) Robust and explainable deep learning method workflow that utilized scRNA-seq data from various cancer types, demonstrating solid predictive accuracy.

(3) The detection of the BrM signature in tumor-educated platelets (TEPs) indicates a promising avenue for developing liquid biopsy assays, which could significantly enhance early detection capabilities.

Weaknesses:

(1) The paper lacks a thorough comparison with other reported signatures in the literature, which could help contextualize the performance and uniqueness of the authors' findings.

(2) The model training focused solely on epithelial cells, potentially overlooking critical contributions from stromal and immune cell types, which could provide a more comprehensive understanding of the tumor microenvironment.

(3) While the results are promising, there is a need for validation across tumor types not included in the training set to assess the generalizability of the signature.

Achievements:

The authors have made significant progress toward their aims, successfully identifying a transcriptional signature that is associated with brain metastasis across multiple cancer types. The results support their conclusions, showcasing the BrM signature's ability to distinguish between metastatic and primary tumor cells and its potential usability as a non-invasive biomarker.

This study has the potential to make a substantial impact in oncological research and clinical practice, particularly in the management of patients at risk for brain metastasis. The identification of a gene signature applicable across various tumor types could lead to the development of standardized diagnostic tools for early detection. Moreover, the emphasis on non-invasive diagnostic techniques aligns well with the current trends in precision medicine, making the findings highly relevant for the broader medical community.

Reviewer #3 (Public review):

Summary:

The authors examine how distinct cellular environments differentially control Mtb following BCG vaccination. The key findings are that IL17 producing PMNs harbor a significant Mtb load in both wild type and IFNg-/- mice. Targeting IL17, Cox2, and Rorgt, improved disease in combination but not alone and enhances BCG efficacy over 12 weeks and neutrophils/IL17 are associated with treatment failure in humans. The authors suggest that targeting these pathways, especially in MSMD patients may improve disease outcomes.

Strengths:

The experimental approach is generally sound and consists of low dose aerosol infections with distinct readouts including cell sorting followed by CFU, histopathology and RNA sequencing analysis. By combining genetic approaches and chemical/antibody treatments, the authors can probe these pathways effectively.

Understanding how distinct inflammatory pathways contribute to control or worsen Mtb disease is important and thus, the results will be of great interest to the Mtb field.

Uncovering a neutrophil population that is refractory to BCG-mediated control can help to better define key markers for vaccine efficacy

Weaknesses:

Several of the key findings in mice have previously been shown (albeit with less sophisticated experimentation) and human disease and neutrophils are well described - thus the real new finding is how intracellular Mtb in neutrophils are more refractory to BCG-mediated control and modulating IL17 and inflammation can alter this.

There is a lack of direct evidence that the neutrophils are producing IL-17 or showing that specifically removing IL17 neutrophils has an effect on disease. Thus, many of these data are correlative, or have modest phenotypes. For example if blocking IL17 or alone does not impact disease alone the conclusion that these IL17+ neutrophils limits protection as noted in the title is is not fully supported. The inhibitors used are not cell-type specific.

Reviewer #2 (Public review):

Summary:

In this study, the authors studied the synchrony between ripple events in the Hippocampus, cortical spindles, and Locus Coeruleus spiking. The results in this study, together with the established literature on the relationship of hippocampal ripples with widespread thalamic and cortical waves, guided the authors to propose a role for Locus Coeruleus spiking patterns in memory consolidation. The findings provided here, i.e., correlations between LC spiking activity and Hippocampal ripples, could provide a basis for future studies probing the directional flow or the necessity of these correlations in the memory consolidation process. Hence, the paper provides enough scientific advances to highlight the elusive yet important role of Norepinephrine circuitry in the memory processes.

Strengths:

The authors were able to demonstrate correlations of Locus Coeruleus spikes with hippocampal ripples as well as with cortical spindles. A specific strength of the paper is in the demonstration that the spindles that activate with the ripples are comparatively different in their correlations with Locus Coeruleus than those that do not.

Weaknesses:

The claims regarding the roles of these specific interactions were mostly derived from the literature that these processes individually contribute to the memory process, without any evidence of these specific interactions being necessary for memory processes. There are also issues with the description of methods, validation of shuffling procedures, and unclear presentation and the interpretation of the findings, which are described in the points that follow. I believe addressing these weaknesses might improve and add to the strength of the findings.

Reviewer #2 (Public review):

Summary:

This manuscript by Syed et al. presents a detailed investigation of inhibitory interneurons, specifically from the 13A and 13B hemilineages, which contribute to the generation of rhythmic leg movements underlying grooming behavior in Drosophila. After performing a detailed connectomic analysis, which offers novel insights into the organization of premotor inhibitory circuits, the authors build on this anatomical framework by performing optogenetic perturbation experiments to functionally test predictions derived from the connectome. Finally, they integrate these findings into a computational model that links anatomical connectivity with behavior, offering a systems-level view of how inhibitory circuits may contribute to grooming pattern generation.

Strengths:

(1) Performing an extensive and detailed connectomic analysis, which offers novel insights into the organization of premotor inhibitory circuits.

(2) Making sense of the largely uncharacterized 13A/13B nerve cord circuitry by combining connectomics and optogenetics is very impressive and will lay the foundation for future experiments in this field.

(3) Testing the predictions from experiments using a simplified and elegant model.

Weaknesses:

(1) In Figure 4-figure supplement 1, the inclusion of walking assays in dusted flies is problematic, as these flies are already strongly biased toward grooming behavior and rarely walk. To assess how 13A neuron activation influences walking, such experiments should be conducted in undusted flies under baseline locomotor conditions.

(2) Regarding Fig 5: The 70ms on/off stimulation with a slow opsin seems problematic. CsChrimson off kinetics are slow and unlikely to cause actual activity changes in the desired neurons with the temporal precision the authors are suggesting they get. Regardless, it is amazing the authors get the behavior! It would still be important for authors to mention the optogentics caveat, and potentially supplement the data with stimulation at different frequencies, or using faster opsins like ChrimsonR.

Overall, I think the strengths outweigh the weaknesses, and I consider this a timely and comprehensive addition to the field.

Reviewer #2 (Public review):

The work presents a model of dopamine release, diffusion and reuptake in a small (100 micrometer^2 maximum) volume of striatum. This extends previous work by this group and others by comparing dopamine dynamics in the dorsal and ventral striatum and by using a model of immediate dopamine-receptor activation inferred from recent dopamine sensor data. From their simulations the authors report three main conclusions: that ventral and dorsal striatum have consistently different distributions of dopamine; that dorsal striatum does not appear to have a clear "tonic" dopamine -- the sustained, relatively uniform concentration of dopamine driven by the constant 4Hz firing of dopamine neurons; and that D1 receptor activation is able to track rapid increases in dopamine concentration changes D2 receptor activation cannot -- and neither receptor-type's activation tracks pauses in pacemaker firing of dopamine neurons.

The simulations of dorsal striatum will be of interest to dopamine aficionados as they throw doubt on the classic model of "tonic" and "phasic" dopamine actions, further show the disconnect between dopamine neuron firing and consequent release, and thus raise issues for the reward-prediction error theory of dopamine.

There is some careful work here checking the dependence of results on the spatial volume and its discretisation. The simulations of dopamine concentration from pacemaker firing of dopamine neurons are checked over a range of values for key parameters. The model is good, the simulations are well done, and the evidence for robust differences between dorsal and ventral striatum dopamine concentration is good.

There are a couple of weaknesses that suggest further work is needed to support the third conclusion of how DA receptors track dopamine concentration changes, before any strong conclusions are drawn about the implications for the reward prediction error theory of dopamine:

effects of changes in affinity (EC50) are tested, and shown to be robust, but not of the receptors' binding (k_on) and unbinding (k_off) rate constants which are more crucial in setting the ability to track changes in concentration.

bursts of dopamine were modelled as release from a cluster of local release sites (40), which is consistent with induced local release by e.g. cholinergic receptor activation, but the rate of release was modelled as the burst firing of dopamine neurons. Burst firing of dopamine neurons would produce a wide range of release site distributions, and are unlikely to be only locally clustered. Conversely, pauses in dopamine release were seemingly simulated as a blanket cessation of activity at all release sites, which implies a model of complete correlation between dopamine neurons. It would be good to have seen both release scenarios for both types of activity, as well as more nuanced models of phasic firing of dopamine neurons.

That said, in releasing their code openly the authors have made it possible for others to extend this work to test the rate constants, the modelling of dopamine neuron bursting, and more.

Reviewer #2 (Public review):

Summary:

The submitted manuscript aims to characterize the role of mast cells in TB granuloma. The manuscript reports heterogeneity in mast cell populations present within the granulomas of tuberculosis patients. With the help of previously published scRNAseq data, the authors identify transcriptional signatures associated with distinct subpopulations.

Strengths:

(1) The authors have carried out sufficient literature review to establish the background and significance of their study.

(2) The manuscript utilizes a mast cell-deficient mouse model, which demonstrates improved lung pathology during Mtb infection, suggesting mast cells as a potential novel target for developing host-directed therapies (HDT) against tuberculosis.

Weaknesses:

(1) The manuscript requires significant improvement, particularly in the clarity of the experimental design, as well as in the interpretation and discussion of the results. Enhanced focus on these areas will provide better coherence and understanding for the readers.

(2) The results discussed in the paper add only a slight novel aspect to the field of tuberculosis. While the authors have used multiple models to investigate the role of Mast cells in TB, majority of the results discussed in the Figure 1-2 are already known and are re-validation of previous literature.

(3) The claims made in the manuscript are only partially supported by the presented data. However, additional extensive experiments are necessary to strengthen the findings and enhance the overall scientific contribution of the work.

Comments on revisions:

While most of the comments have been addressed by the authors, a few important concerns pertaining to the data interpretation remain unanswered.

(1) The discrepancy between published studies and the current study on function of mast cells during TB remains. The authors could not justify the reason behind differences in results obtained during Mtb infection in humans vs macaques.

(2) To address the concern regarding immune alterations in mast cells deficient mice, the authors carried out adoptive transfer of mast cells to WT mice. However, they do not observe any changes in mycobacterial lung burden and inflammation, diluting their conclusions throughout the study.

(3) Additionally, as the authors propose mast cells as players in LTBI to PTB conversion, the adoptive transfer experiment could be conducted in a low-dosage model of TB. This would aid in assessing its role in TB reactivation.

Reviewer #2 (Public review):

Summary:

Lamothe et al. collected fMRI responses to many voice stimuli in 3 subjects. The authors trained two different autoencoders on voice audio samples and predicted latent space embeddings from the fMRI responses, allowing the voice spectrograms to be reconstructed. The degree to which reconstructions from different auditory ROIs correctly represented speaker identity, gender or age was assessed by machine classification and human listener evaluations. Complementing this, the representational content was also assessed using representational similarity analysis. The results broadly concur with the notion that temporal voice areas are sensitive to different types of categorical voice information.

Strengths:

The single-subject approach that allow thousands of responses to unique stimuli to be recorded and analyzed is powerful. The idea of using this approach to probe cortical voice representations is strong and the experiment is technically solid.

Reviewer #4 (Public review):

Summary:

In this study Tateishi et al. used TnSeq to identify 131 shared essential or growth defect-associated genes in eight clinical MAC-PD isolates and the type strain ATCC13950 of Mycobacterium intracellulare which are proposed as potential drug targets. Genes involved in gluconeogenesis and the type VII secretion system which are required for hypoxic pellicle-type biofilm formation in ATCC13950 also showed increased requirement in clinical strains under standard growth conditions. These findings were further confirmed in a mouse lung infection model.

Strengths:

This study has conducted TnSeq experiments in reference and 8 different clinical isolates of M. intracellulare thus producing large number of datasets which itself is a rare accomplishment and will greatly benefit the research community.

Weaknesses:

(1) Comparative growth study of pure and mixed cultures of clinical and reference strains under hypoxia will be helpful in supporting the claim that clinical strains adapt better to such conditions. This should be mentioned as future directions in the discussion section along with testing the phenotype of individual knockout strains.

(2) Authors should provide the quantitative value of read counts for classifying a gene as "essential" or "non-essential" or "growth-defect" or "growth-advantage". Merely mentioning "no insertions in all or most of their TA sites" or "unusually low read counts" or "unusually high low read counts" is not clear.

(3) One of the major limitations of this study is the lack of validation of TnSeq results with individual gene knockouts. Authors should mention this in the discussion section.

Comments on revisions:

The revised version has satisfactorily addressed my initial comments in the discussion section.

Reviewer #2 (Public review):

This study leverages acute protein degradation of CHD4 to define its role in chromatin and gene regulation. Previous studies have relied on KO and/or RNA interference of this essential protein and, as such, are hampered by adaptation, cell population heterogeneity, cell proliferation, and indirect effects. The authors have established an AID2-based method to rapidly deplete the dMi-2 remodeller to circumvent these problems. CHD4 is gone within an hour, well before any effects on cell cycle or cell viability can manifest. This represents an important technical advance that, for the first time, allows a comprehensive analysis of the immediate and direct effect of CHD4 loss of function on chromatin structure and gene regulation.

Rapid CHD4 degradation is combined with ATAC-seq, CUT&RUN, (nascent) RNA-seq, and single-molecule microscopy to comprehensively characterise the impact on chromatin accessibility, histone modification, transcription, and transcription factor (NANOG, SOX2, KLF4) binding in mouse ES cells.

The data support the previously developed model that high levels of CHD4/NuRD maintain a degree of nucleosome density to limit TF binding at open regulatory regions (e.g., enhancers). The authors propose that CHD4 activity at these sites is an important prerequisite for enhancers to respond to novel signals that require an expanded or new set of TFs to bind.

What I find even more exciting and entirely novel is the finding that CHD4 removes TFs from regions of limited accessibility to repress cryptic enhancers and to suppress spurious transcription. These regions are characterised by low CHD4 binding and have so far never been thoroughly analysed. The authors correctly point out that the general assumption that chromatin regulators act on regions where they seem to be concentrated (i.e., have high ChIP-seq signals) runs the risk of overlooking important functions elsewhere. This insight is highly relevant beyond the CHD4 field and will prompt other chromatin researchers to look into low-level binding sites of chromatin regulators.

The biochemical and genomic data presented in this study are of high quality (I cannot judge single microscopy experiments due to my lack of expertise). This is an important and timely study that is of great interest to the chromatin field.

I have a number of comments that the authors might want to consider to improve the manuscript further:

(1) Figure 2 shows heat maps of RNA-seq results following a time course of CHD4 depletion (0, 1, 2 hours...). Usually, the red/blue colour scale is used to visualise differential expression (fold-difference). Here, genes are coloured in red or blue even at the 0-hour time point. This confused me initially until I discovered that instead of fold-difference, a z-score is plotted. I do not quite understand what it means when a gene that is coloured blue at the 0-hour time point changes to red at a later time point. Does this always represent an upregulation? I think this figure requires a better explanation.

(2) Figure 5D: NANOG, SOX2 binding at the KLF4 locus. The authors state that the enhancers 68, 57, and 55 show a gain in NANOG and SOX2 enrichment "from 30 minutes of CHD4 depletion". This is not obvious to me from looking at the figure. I can see an increase in signal from "WT" (I am assuming this corresponds to the 0 hours time point) to "30m", but then the signals seem to go down again towards the 4h time point. Can this be quantified? Can the authors discuss why TF binding seems to increase only temporarily (if this is the case)?

(3) The is no real discussion of HOW CHD4/NuRD counteracts TF binding (i.e. by what molecular mechanism). I understand that the data does not really inform us on this. Still, I believe it would be worthwhile for the authors to discuss some ideas, e.g., local nucleosome sliding vs. a direct (ATP-dependent?) action on the TF itself.

Reviewer #2 (Public review):

Summary:

This study by Dong et al. characterizes the roles of highly-expressed Rab GTPases Rab5, Rab7, and Rab11 in the development and wiring of olfactory projection neurons in Drosophila. This convincing descriptive study provides complementary approaches to Rab expression and localization profiling, conventional dominant-negative mutants, and clonal loss-of-function mutants to address the roles of different endosomal trafficking pathways across circuit development. They show distinct distributions and phenotypes for different Rabs. Overall, the study sets the stage for future mechanistic studies in this well-defined central neuron.

Strengths:

Beautiful imaging in central neurons demonstrates differential roles of 3 key Rab proteins in neuronal morphogenesis, as well as interesting patterns of subcellular endosome distribution. These descriptions will be critical for future mechanistic studies. The cell biology is well-written and explanatory, very accessible to a wide audience without sacrificing technical accuracy.

Weaknesses:

The Drosophila manipulations require more explanation in the main text to reach a wide audience.

Reviewer #2 (Public review):

Summary:

In "Spatially heterogeneous inhibition projects sequential activity onto unique neural subspaces", Lehr et al. address the question of how neural circuits generate distinct low-dimensional, sequential neural dynamics that can shift to different neural subspaces on fast, behaviorally relevant timescales.

Lehr et al. propose a circuit architecture in which spatially heterogeneous inhibition constrains network dynamics to sequential activity on distinct neural subspaces and allows top-down sequence selection on fast timescales. Two types of inhibitory interneurons play separate roles. One class of interneuron balances excitation and contributes to sequence propagation. The second class of interneuron forms spatially heterogeneous, clustered inhibition that projects onto the sequence-generating portion of the circuit and suppresses all but a subset of the sequential activity, thus driving sequence selection. Due to the random nature of the inhibitory projections from each inhibitory cluster, the selected sequences exist on well-separated neural subspaces, provided the 'selection' inhibition is sufficiently dense. Lehr et al. use mathematical analysis and computational modeling to study this type of circuit mechanism in two contexts: a 1D ring network and a 2D, locally connected, spiking network. This work connects to previous literature, which considers the role of selective inhibition in shaping and restructuring sequential dynamics.

Strengths:

(1) This study makes testable predictions about the connectivity patterns for the two types of interneurons contributing to sequence generation and sequence selection.

(2) This study proposes a relatively simple circuit motif that can generate many distinct, low-dimensional neural sequences that can vary dynamically on fast, behaviorally relevant timescales. The authors make a clear analytical argument for the stability and structure of the dynamics of the sub-sequences.

(3) This study applies the inhibitory selection mechanisms in two different model network contexts: a 1D rate model and a 2D spiking model. Both settings have local connectivity patterns and two inhibitory pools but differ in several significant ways, which supports the generality of the proposed mechanism.

Weaknesses:

(1) Scaling synaptic weights to match the original sequence dynamics is a complex requirement for this mechanism. In the 2D network, the solution to this scaling issue is the saturation of single-unit firing rates. It is unclear if this is in a biologically relevant dynamical regime or to what degree the saturation dynamics of the sequences themselves are altered by the density of selective inhibition.

(2) In the 2D model, although the sequence-generating circuit is quite general, the heterogenous interneuron population requires a tuned connectivity structure paired with matched external inputs. In particular, the requirement that inhibitory pools project to shared but random excitatory neurons would benefit from a discussion about the biological feasibility of this architecture.

Reviewer #2 (Public review):

Summary:

Wang et al. engineered an optimized ACE2 mutant by introducing two mutations (T92Q and H374N) and fused this ACE2 mutant to human IgG1-Fc (B5-D3). Experimental results suggest that B5-D3 exhibits broad-spectrum neutralization capacity and confers effective protection upon intranasal administration in SARS-CoV-2-infected K18-hACE2 mice. Transcriptomic analysis suggests that B5-D3 induces early immune activation in lung tissues of infected mice. Fluorescence-based bio-distribution assay further indicates rapid accumulation of B5-D3 in the respiratory tract, particularly in airway macrophages. Further investigation shows that B5-D3 promotes viral phagocytic clearance by macrophages via an Fc-mediated effector function, namely antibody-dependent cellular phagocytosis (ADCP), while simultaneously blocking ACE2-mediated viral infection in epithelial cells. These results provide insights into improving decoy treatments against SARS-CoV-2 and other potential respiratory viruses.

Strengths:

The protective effect of this ACE2-Fc fusion protein against SARS-CoV-2 infection has been evaluated in a quite comprehensive way.

Weaknesses:

(1) The paper lacks an explanation regarding the reason for the combination of mutations listed in Supplementary Figure 2b. For example, for the mutations that enhance spike protein binding, B2-B6 does not fully align with the mutations listed in Table S1 of Reference 4, yet no specific criteria are provided. Second, for the mutations that abolished enzymatic activity, while D1 and D2, D3, D4, and D5 are cited from References 12, 11, and 33, respectively, the reason for combining D3 and D4 into A2, and D1 and D2 into A3 remains unexplained. It is also unclear whether some of these other possible combinations have been tested. Furthermore, for the B5-derived mutations, only double-mutant combinations with D1-D5 are tested, with no attempt made to evaluate triple mutations involving A2 or A3.

(2) Figures 1b, 1d, and 1e lack statistical analyses, making it difficult to determine whether B5 and D3 exhibit significant advantages. For Wuhan-Hu-1 strain, B2 and B5 are similar, and for D614G strain, B2, B3, B4, B5, and B6 display comparable results. However, only the glycosylation-related single mutant B5 is chosen for further combinatorial constructs. Moreover, for VOC/VOI strains, B5 is superior to B5-D3; for the Alpha strain, B5-D4 and B5-D5 are superior to B5-D3; and for the Delta and Lambda strains, B5-D5 is superior to B5-D3. These observations further highlight the need for a clearer explanation of the selection strategy.

(3) Figure 1e does not specify the construct form of the control hIgG1, namely whether it is an hIgG1 Fc fragment or a full-length hIgG1 protein. If the full-length form is used, the design of its Fab region should be clarified to ensure the accuracy and comparability of the experimental control.

(4) In Figure 2a, all three PBS control mice died, whereas in Figure 2f, three out of five PBS control mice died, with the remaining showing gradual weight recovery. This discrepancy may reflect individual immune variations within the control groups, and it is necessary to clarify whether potential autoimmune factors could have affected the comparability of the results. Also, the mouse experiments suffer from insufficient sample sizes, which affects the statistical power and reliability of the results. In Figure 2a, each group contains only 4 replicates, one of which was used for lung tissue sampling. As a result, body weight monitoring data is derived from only 3 mice per group (the figure legend indicating n=4 should be corrected to n=3). Such a small sample size limits the robustness of the conclusions. Similarly, in Figure 2f, although each group has 5 replicates, body weight data are presented for only 4 mice, with no explanation provided for the exclusion of the fifth mouse. Furthermore, the lung tissue experiments in Figure 3a include only 3 replicates, which is also inadequate.

(5) Compared to 6 hours, intranasal administration of B5-D3 at 24 hours before viral infection results in reduced protective efficacy. However, only survival and body weight data are provided, with no supporting evidence from virological assays such as viral titer measurement. Therefore, the long-term effectiveness lacks sufficient experimental validation.

(6) In Figures 3b and 3c, viral spike (S) and nucleocapsid (N) RNA relative expression levels are quantified by qPCR. The results show significant individual variation within the B5-D3-LALA treatment group: one mouse exhibits high S and N expression, while the other two show low expression. Viral load levels are also inconsistent: two mice have high viral loads, and one has a low viral load. Due to this variability, the available data are insufficient to robustly support the conclusion.

(7) Figure 3e: "H&E staining indicated alveolar thickening in all groups," including the Mock group. Since the Mock group did not receive virus or active drug treatment, this observed change may result from local tissue reaction induced by the intranasal inoculation procedure itself, rather than specific immune activation. A control group (no manipulation) should be set to rule out potential confounding effects of the experimental procedure on tissue morphology, thereby allowing a more accurate assessment of the drug's effects.

(8) In Supplementary Figure 11b, a considerable number of alveolar macrophages (AMs) are observed in both the PBS and B5-D3 groups. This makes it difficult to determine whether the observed accumulation is specifically induced by B5-D3.

(9) In the flow cytometry experiment shown in Figure 5, the PBS control group is not labeled with AF750, which necessarily results in a value of zero for "B5-D3+ cells" on the y-axis. An appropriate control (e.g., hIgG1-Fc labeled with AF750) should be included.

(10) The Methods section: a more detailed description of the experimental procedures involving HIV p24 and SARS-CoV-2 should be included.

Reviewer #2 (Public review):

Summary:

In this manuscript, Fan, Cohen, and Dam et al. conducted a follow-up study to their prior work on the ESCRT- and ALIX-binding region (EABR) mRNA vaccine platform that they developed. They tested in mice whether vaccines made in this format will have improved binding/neutralization antibody capacity over conventional antigens when used as a booster. The authors tested this in both monovalent (Wu1 only) or bivalent (Wu1 + BA.5) designs. The authors found that across both monovalent and bivalent designs, the EABR antigens had improved antibody titers than conventional antigens, although they observed dampened titers against Omicron variants, likely due to immune imprinting. Deep mutational scanning experiments suggested that the improvement of the EABR format may be due to a more diversified antibody response. Finally, the authors demonstrate that co-expression of multiple spike proteins within a single cell can result in the formation of heterotrimers, which may have potential further usage as an antigen.

Strengths:

(1) The experiments are conducted well and are appropriate to address the questions at hand. Given the significant time that is needed for testing of pre-existing immunity, due to the requirement of pre-vaccinated animals, it is a strength that the authors have conducted a thorough experiment with appropriate groups.

(2) The improvement in titers associated with EABR antigens bodes well for its potential use as a vaccine platform.

Weaknesses:

As noted above, this type of study requires quite a bit of initial time, so the authors cannot be blamed for this, but unfortunately, the vaccine designs that were tested are quite outdated. BA.5 has long been replaced by other variants, and importantly, bivalent vaccines are no longer used. Testing of contemporaneous strains as well as monovalent variant vaccines would be desirable to support the study.

Reviewer #2 (Public review):

Summary:

The authors combined behavioral experiments, computational modeling, and functional magnetic resonance imaging (fMRI) to investigate the psychological and neural mechanisms underlying guilt, shame, and the altruistic behaviors driven by these emotions. The results revealed that guilt is more strongly associated with harm, whereas shame is more closely linked to responsibility. Compared to shame, guilt elicited a higher level of altruistic behavior. Computational modeling demonstrated how individuals integrate information about harm and responsibility. The fMRI findings identified a set of brain regions involved in representing harm and responsibility, transforming responsibility into feelings of shame, converting guilt and shame into altruistic actions, and mediating the effect of trait guilt on compensatory behavior.

Strengths:

This study offers a significant contribution to the literature on social emotions by moving beyond prior research that typically focused on isolated aspects of guilt and shame. The study presents a comprehensive examination of these emotions, encompassing their cognitive antecedents, affective experiences, behavioral consequences, trait-level characteristics, and neural correlates. The authors have introduce a novel experimental task that enables such a systematic investigation and holds strong potential for future research applications. The computational modeling procedures were implemented in accordance with current field standards. The findings are rich and offer meaningful theoretical insights. The manuscript is well written, and the results are clearly and logically presented.

Weaknesses:

In this study, participants' feelings of guilt and shame were assessed retrospectively, after they had completed all altruistic decision-making tasks. This reliance on memory-based self-reports may introduce recall bias, potentially compromising the accuracy of the emotion measurements.

In many behavioral economic models, self-interest plays a central role in shaping individual decision-making, including moral decisions. However, the model comparison results in this study suggest that models without a self-interest component (such as Model 1.3) outperform those that incorporate it (such as Model 1.1 and Model 1.2). The authors have not provided a satisfactory explanation for this counterintuitive finding.

The phrases "individuals integrate harm and responsibility in the form of a quotient" and "harm and responsibility are integrated in the form of a quotient" appear in the Abstract and Discussion sections. However, based on the results of the computational modeling, it is more accurate to state that "harm and the number of wrongdoers are integrated in the form of a quotient." The current phrasing misleadingly suggests that participants represent information as harm divided by responsibility, which does not align with the modeling results. This potentially confusing expression should be revised for clarity and accuracy.

In the Discussion, the authors state: "Since no brain region associated social cognition showed significant responses to harm or responsibility, it appears that human brain encodes a unified measure integrating harm and responsibility (i.e., the quotient) rather than processing them as separate entities when both are relevant to subsequent emotional experience and decision-making." However, this interpretation overstates the implications of the null fMRI findings. The absence of significant activation in response to harm or responsibility does not necessarily imply that the brain does not represent these dimensions separately. Null results can arise from various factors, including limitations in the sensitivity of fMRI. It is possible that more fine-grained techniques, such as intracranial electrophysiological recordings, could reveal distinct neural representations of harm and responsibility. The interpretation of these null findings should be made with greater caution.

For the revised manuscript, the authors have provided additional evidence and clarified expressions. all the comments were responded. I have no further comments.

Reviewer #2 (Public review):

Summary:

The manuscript is a timely and comprehensive review of how the extracellular matrix (ECM), particularly the vascular basement membrane, regulates leukocyte extravasation, migration, and downstream immune function. It integrates molecular, mechanical, and spatial aspects of ECM biology in the context of inflammation, drawing from recent advances. The framing of ECM as an active instructor of immune cell fate is a conceptual strength.

Strengths:

• Comprehensive synthesis of ECM functions across leukocyte extravasation and post-transmigration activity.
• Incorporation of recent high-impact findings alongside classical literature.
• Conceptually novel framing of ECM as an active regulator of immune function.
• Effective integration of molecular, mechanical, and spatial perspectives.

Weaknesses:

• Some sections remain dense with signalling detail.
• Figure readability could be improved through simplified labeling.

Appraisal and Impact:

The authors have achieved their aim of presenting an integrated view of ECM-immune interactions. The review provides conceptual and visual clarity on a complex topic.

Reviewer #2 (Public review):

Summary:

This article examines reviewer coercion in the form of requesting citations to the reviewer's own work as a possible trade for acceptance and shows that, under certain conditions, this happens.

Strengths:

The methods are well done and the results support the conclusions that some reviewers "request" self-citations and may be making acceptance decisions based on whether an author fulfills that request.

Weakness:

I thank the author for addressing my comments about the original version.

Reviewer #2 (Public review):

To fuse, differentiated muscle cells must rearrange their cytoskeleton and assemble actin-enriched cytoskeletal structures. These actin foci are proposed to generate mechanical forces necessary to drive close membrane apposition and the fusion pore formation. While the study of these actin-rich structures has been conducted mainly in drosophila and in vertebrate embryonic development, the present manuscript present clear evidence this mechanism is necessary for fusion of adult muscle stem cells in vivo, in mice. The data presented here clearly demonstrate that ARP2/3 and SCAR/WAVE complexes are required for differentiating satellite cells fusion into multinucleated myotubes, during skeletal muscle regeneration.

Reviewer #2 (Public review):

Summary:

In this paper, the authors report on the genomic correlates of the transition to the pathogenic lifestyle in Sordariomycetes. The pathogenic lifestyle was found to be better explained by the number of genes, and in particular effectors and tRNAs, but this was modulated by the type of interacting host (insect or not insect) and the ability to be vectored by insects.

Strengths:

The main strengths of this study lie in (i) the size of the dataset, and the potentially high number of lifestyle transitions in Sordariomycetes, (ii) the quality of the analyses and the quality of the presentation of the results, (iii) the importance of the authors' findings.

Weaknesses:

The weakness is a common issue in most comparative genomics studies in fungi, but it remains important and valid to highlight it. Defining lifestyles is complex because many fungi go through different lifestyles during their life cycles (for instance, symbiotic phases interspersed with saprotrophic phases). In many fungi, the lifestyle referenced in the literature is merely the sampling substrate (such as wood or dung), which does not necessarily mean that this substrate is a key part of the life cycle. The authors discuss this issue, but they do not eliminate the underlying uncertainties.

[Editors' note: this version was assessed by the editors, without involving the reviewers again.]

Reviewer #2 (Public review):

Summary:

The authors propose that bidirectional translocation of actomyosin drives tissue invagination in Ciona siphon tube formation. They suggest a two-stage model where actomyosin first accumulates apically to drive a slow initial invagination, followed by translocation to lateral domains to accelerate the invagination process through cell shortening. They have shown that actomyosin activity is important for invagination - modulation of myosin activity through expression of myosin mutants altered the timing and speed of invagination; furthermore, optogenetic inhibition of myosin during the transition of the slow and fast stages disrupted invagination. The authors further developed a vertex model to validate the relationship between contractile force distribution and epithelial invagination.

Strengths:

(1) The authors employed various techniques to address the research question, including optogenetics, the use of MRLC mutants, and vertex modelling.

(2) The authors provide quantitative analyses for a substantial portion of their imaging data, including cell and tissue geometry parameters as well as actin and myosin distributions. The sample sizes used in these analyses appear appropriate.

(3) The authors combined experimental measurements with computer modeling to test the proposed mechanical models, which represents a strength of the study. It provides a framework to explore the mechanical principles underlying the observed morphogenesis.

Weaknesses:

(1) The concept of coordinated and sequential action of apical and lateral actomyosin in support of epithelial folding has been documented through a combination of experimental and modeling approaches in other contexts, such as ascidian endoderm invagination (PMID: 20691592) and gastrulation in Drosophila (PMIDs: 21127270, 22511944, 31273212). While the manuscript addresses an important question, related findings have been reported in these previous studies. This overlap reduces the degree of novelty, and it remains to be clarified how their work advances beyond these prior contributions.

(2) One of the central statements made by the authors is that the translocation of actomyosin between the apical and lateral domains mediates invagination. The use of the term "translocation" infers that the same actomyosin structures physically move from one location to another location, which is not demonstrated by the data. Given the time scale of the process (several hours), it is also possible that the observed spatiotemporal patterns of actomyosin intensity result from sequential activation/assembly and inactivation/disassembly at specific locations on the cell cortex, rather than from the physical translocation of actomyosin structures over time.

(3) Some aspects of the data on actomyosin localization require further clarification. (1) The authors state that actomyosin translocation is bidirectional, first moving from the lateral domain to the apical domain; however, the reduction of the lateral actomyosin at this step was not rigorously tested. (2) During the slow invagination stage, it is unclear whether myosin consistently localizes to the apical cell-cell borders or instead relocalizes to the medioapical domain, as suggested by the schematic illustration presented in Figure 2C. (3) It is unclear how many cells along the axis orthogonal to the furrow accumulate apical and lateral myosin.

(4) The overexpression of MRLC mutants appears to be rather patchy in some cases (e.g., in Figure 3A, 17.0 hpf, only cells located at the right side of the furrow appeared to express MRLC T18ES19E). It is unclear how such patchy expression would impact the phenotype.

(5) In the optogenetic experiment, it appears that after one hour of light stimulation, the apical side of the tissue underwent relaxation (comparing 17 hpf and 16 hpf in Figure 4B). It is therefore unclear whether the observed defect in invagination is due to apical relaxation or lack of lateral contractility, or both. Therefore, the phenotype is not sufficient to support the authors' statement that "redistribution of myosin contractility from the apical to lateral regions is essential for the development of invagination".

(6) The vertex model is designed to explore how apical and lateral tensions contribute to distinct morphological outcomes. While the authors raise several interesting predictions, these are not further tested, making it unclear to what extent the model provides new insights that can be validated experimentally. In addition, modeling the epithelium as a flat sheet and not accounting for cell curvature is a simplification that may limit the model's accuracy. Finally, the model does not fully recapitulate the deeply invaginated furrow configuration as observed in a real embryo (comparing 18 hpf in Figure 5D and 18 hpf in Figure 1A) and does not fully capture certain mutant phenotypes (comparing 18 hpf in Figure 5F and 18 hpf in Figure 3B right panel).

Reviewer #2 (Public review):

Summary:

This ambitious study introduced 22 mutations corresponding to amino acid substitution mutations known to induce cancer in human Notch1, located within the Negative Regulatory Region, into the Drosophila Notch gene. It comprehensively examined their effects on activity, intracellular transport, protein levels, and stability. The results revealed that the impact of amino acid substitutions within the Negative Regulatory Region can be grouped based on their location, differing between the Heterodimerization Domain and the Lin12/Notch Repeat. These findings provide important insights into elucidating the mechanisms by which amino acid substitution mutations in human Notch1 cause leukemia and cancer.

Strengths:

In this study, the authors successfully measured the activity of amino acid-substituted Notch with high precision by effectively leveraging the advantages of their previously established experimental system. Furthermore, they clearly demonstrated ligand-dependent and Deltex-dependent properties.

Weaknesses:

Amino acid substitution mutations exhibit interesting effects depending on their position, so interest naturally turns to the mechanisms generating these differences. Unfortunately, however, elucidating these mechanisms will require considerable time in the future. Therefore, it is reasonable to conclude that questions regarding the mechanism fall outside the scope of this paper.

Reviewer #2 (Public review):

Summary:

Van der Linden et al. describe the addition of the T203Y mutation to their previously described fluorescence lifetime calcium sensor Tq-Ca-FLITS to shift the fluorescence to green emission. This mutation was previously described to similarly red-shift the emission of green and cyan FPs. Tq-Ca-FLITS_T203Y behaves as a green calcium sensor with opposite polarity compared with the original (lifetime goes down upon calcium binding instead of up). They then screen a library of variants at two linker positions and identify a variant with slightly improved lifetime contrast (Tq-Ca-FLITS_T203Y_V27A_N271D, named G-Ca-FLITS). The authors then characterize the performance of G-Ca-FLITS relative to Tq-Ca-FLITS in purified protein samples, in cultured cells, and in the brains of fruit flies.

Strengths:

This work is interesting as it extends their prior work generating a calcium indicator scaffold for fluorescent protein-based lifetime sensors with large contrast at a single wavelength, which is already being adopted by the community for production of other FLIM biosensors. This work effectively extends that from cyan to green fluorescence. While the cyan and green sensors are not spectrally distinct enough (~20-30nm shift) to easily multiplex together, it at least shifts the spectra to wavelengths that are more commonly available on commercial microscopes.

The observations of organellar calcium concentrations were interesting and could potentially lead to new biological insight if followed up.

Reviewer #2 (Public review):

Summary:

The manuscript describes various conformational states and structural dynamics of the Insulin degrading enzyme (IDE), a zinc metalloprotease by nature. Both open and closed state structures of IDE have been previously solved using crystallography and cryo-EM which reveal a dimeric organization of IDE where each monomer is organized into N and C domains. C-domains form the interacting interface in the dimeric protein while the two N-domains are positioned on the outer sides of the core formed by C-domains. It remains elusive how the open state is converted into the closed state but it is generally accepted that it involves large-scale movement of N-domains relative to the C-domains. Authors here have used various complementary experimental techniques such as cryo-EM, SAXS, size-exclusion chromatography and enzymatic assays to characterize the structure and dynamics of IDE protein in the presence of substrate protein insulin whose density is captured in all the structures solved. The experimental structural data from cryo-EM suffered from high degree of intrinsic motion amongst the different domains and consequently, the resultant structures were moderately resolved at 3-4.1 Å resolution. Total five structures were generated in the originally submitted manuscript using cryo-EM. Another cryo-EM reconstruction (sixth) at 5.1Å resolution was mentioned after first revision which was obtained using time-resolved cryo-EM experiments. Authors have extensively used Molecular dynamics simulation to fish out important inter-subunit contacts which involves R668, E381, D309, etc residues. In summary, authors have explored the conformational dynamics of IDE protein using experimental approaches which are complimented and analyzed in atomic details by using MD simulation studies. The studies are meticulously conducted and lay ground for future exploration of protease structure-function relationship.

Comments after first peer-review:

The authors have addressed all my concerns, and have added new data and explanations in terms of time-resolved cryo-EM (Fig. 7) and upside simulations (Fig. 8) which in my opinion have strengthened the merit of the manuscript.

Reviewer #2 (Public review):

The authors addressed the question how mitochondrial proteins that are dually localized or only to a minor fraction localized to mitochondria can be visualized. For this they used an established and previously published method called BiG split-GFP, in which GFP strands 1-10 are encoded in the mitochondrial DNA and fused the GFP11 strand C-terminally to the yeast ORFs using the C-SWAT library. The generated library was imaged under different growth and stress conditions and yielded positive mitochondrial localization for approximately 400 proteins. The strength of this method is the detection of proteins that are dually localized with only a minor fraction within mitochondria, which was so far has hampered due to strong fluorescent signals from other cellular localizations. The weakness of this method is that due to the localization of the GFP1-10 in the mitochondrial matrix, only matrix proteins and IM protein with their C-termini facing the matrix can be detected. In addition, The C-terminal GFP11 might impact on assembly of proteins into multimeric complexes or interfere with biogenesis trapping the tagged protein in an unproductive transport intermediate. Taken these limitations into consideration, the authors provide a new library that can help in identification of eclipsed protein distribution within mitochondria, thus further increasing our knowledge on the complete mitochondrial proteome. The approach of global tagging of the yeast genome is the logical consequence after the successful establishment of the BiG split-GFP for mitochondria. The authors also propose that their approach can be applied to investigate the topology of inner membrane proteins, however, for this the inherent issue remains that even the small GFP11 tag can impact on protein biogenesis and topology. Thus, the approach will not overcome the need to assess protein topology via biochemical approaches detecting endogenous untagged proteins.

Comments on revisions:

The first sentence of the abstract should be changed as the statement that "The majority of the mitochondrial proteins (...) often lack clear targeting signals" is in particular for the here analysed IM and matrix protein not correct: Several N-proteomics analysis have defined N-terminal cleavable targeting signals in great detail.

Also the statement in the title that the assay illuminates protein targeting routes should be reconsidered as experimental evidence for this statement is still scarce.

Reviewer #2 (Public review):

Summary:

The paper describes new insights into the role of adenosine deaminase-related growth factor (adgf), an enzyme that catalyses the breakdown of adenosine into ammonia and inosine, in tip formation during Dictyostelium development. The adgf null mutant has a pre-tip mound arrest phenotype, which can be rescued by external addition of ammonia. Analysis suggests that the phenotype involves changes in cAMP signaling possibly involving a histidine kinase dhkD, but details remain to be resolved.

Strengths:

The generation of an adgf mutant showed a strong mound arrest phenotype and successful rescue by external ammonia. Characterisation of significant changes in cAMP signaling components, suggesting low cAMP signaling in the mutant and identification of the histidine kinase dhkD as a possible component of the transduction pathway. Identification of a change in cell-type differentiation towards prestalk fate

Comments on previous version:

The revised version of the paper has improved significantly in terms of structure and clarity. The additional data on rescue of total cAMP production by ammonia (Fig. 7C) in the adgf- mutant and the 5-fold increased prespore expression of adgf RNA compared to prestalk cells (Fig 9) are useful data additions.

The link between changes in cAMP signaling (lower aca expression) and wave geometry (concentric waves rather than spiral waves) remains speculative.

I noted that Fig 6 contains different images than the previous version (Fig 7).

The statement "Interestingly, Klebsiella pneumoniae physically separated from the Dictyostelium adgf mutants in a partitioned dish, also rescues the mound arrest phenotype suggesting a cross-kingdom interaction that drives development" in the summary is rather overdone. All experiments were performed with axenic strains (no bacteria).

as is the sentence "Remarkably, in higher vertebrates, adgf expression is elevated during gastrulation and thus adenosine deamination may be a conserved process driving organizer development in different organisms"

The data supporting this in the supplementary information is hardly legible and poorly presented. What is shown is ADA expression in different tissues, not at different stages. I would suggest taking these figures out and concentrating the summary on the key mechanistic findings of the paper. (The authors have now done this.)

Reviewer #2 (Public review):

This study conducted by Lu et al. explores the molecular underpinnings of sexual dimorphism in antiviral immunity in zebrafish, with a particular emphasis on the male-biased gene cyp17a2. The authors demonstrate that male zebrafish exhibit stronger antiviral responses than females, and they identify a teleost-specific gene cyp17a2 as a key regulator of this dimorphism. Utilizing a combination of in vivo and in vitro methodologies, they demonstrate that Cyp17a2 potentiates IFN responses by stabilizing STING via K33-linked polyubiquitination and directly degrades the viral P protein via USP8-mediated deubiquitination. The work challenges conventional views of sex-based immunity and proposes a novel, hormone- and sex chromosome-independent mechanism.

Strengths:

(1) The following constitutes a novel concept, sexual dimorphism in immunity can be driven by an autosomal gene rather than sex chromosomes or hormones represents a significant advance in the field, offering a more comprehensive understanding of immune evolution.

(2) The present study provides a comprehensive molecular pathway, from gene expression to protein-protein interactions and post-translational modifications, thereby establishing a link between Cyp17a2 and both host immune enhancement (via STING) and direct antiviral activity (via viral protein degradation).

(3) In order to substantiate their claims, the authors utilize a wide range of techniques, including transcriptomics, Co-IP, ubiquitination assays, confocal microscopy, and knockout models.

(4) The utilization of a singular model is imperative. Zebrafish, which are characterized by their absence of sex chromosomes, offer a clear genetic background for the dissection of autosomal contributions to sexual dimorphism.

Weaknesses:

(1) Limited discussion on whether this mechanism extends beyond Cyprinidae and its implications for teleost adaptation.

Comments on revisions:

The authors successfully achieved their primary aim, which was to identify and characterize a male-biased gene governing antiviral sexual dimorphism in fish. The data provide robust support for the conclusion that Cyp17a2 enhances antiviral immunity through dual mechanisms, STING stabilization and viral protein degradation, independent of classical sex-determining pathways. The findings are consistent across a range of experimental setups and are statistically robust. The revisions have significantly enhanced the clarity, depth, and overall quality of the manuscript. The authors have addressed each concern meticulously, resulting in a much-improved and robust article. No further suggestions are offered.

Reviewer #2 (Public review):

Summary:

The ADP-ribosyltransferase tankyrase controls many biological processes, many of which are relevant to human disease. This includes Wnt/beta-catenin signalling, which is dysregulated in many cancers, most notably colorectal cancer. Tankyrase is a positive regulator of Wnt/beta-catenin signalling in that it counters the activity of the beta-catenin destruction complex (DC). Catalytic inhibition of tankyrase not only blocks PAR-dependent ubiquitylation and degradation of AXIN1/2, the central scaffolding protein in the DC, but also tankyrase itself. As a result, blocking tankyrase gives rise to tankyrase accumulation, which may accentuate its non-catalytic functions, which have been proposed to drive Wnt/beta-catenin signalling. Most tankyrase catalytic inhibitors have shown limited efficacy and substantial toxicity in vivo. By developing tankyrase-directed PROTACs, the authors aim to block both catalytic and non-catalytic functions of tankyrase, aspiring to achieve a more complete inhibition of Wnt/beta-catenin signalling. The successfully developed PROTAC, based on the existing catalytic inhibitor IWR1, IWR1-POMA, induces the degradation of both TNKS and TNKS2, blocks beta-catenin-dependent transcription without stabilising the DC in puncta/degradasomes, and inhibits cancer cell growth in vitro. Mechanistically, this points to a scaffolding role of tankyrase in the DC, at least under conditions of tankyrase catalytic inhibition, in line with previous proposals.

Strengths:

The study clearly illustrates the incentive for developing a tankyrase degrader, namely, to abolish both catalytic and non-catalytic functions of tankyrase. By and large, the study achieves these ambitions, and the findings support the main conclusions, although the statement that a more complete inhibition of the pathway is achieved requires corroboration. The proteomics studies are powerful. IWR1-POMA constitutes a very useful tool to re-evaluate targeting of tankyrase in oncogenic Wnt/beta-catenin signalling. The paired compounds will benefit investigations of tankyrase scaffolding functions across many different biological systems controlled by tankyrase. The findings are exciting.

Weaknesses:

Although the results are promising and mostly compelling, the claim that the PROTACs provide "a deeper suppression of the WNT/β-catenin pathway activity" requires further corroboration, particularly at endogenous tankyrase levels.

There are also some other points that, if considered, would further improve the manuscript, as detailed below.

(1) Abstract and line 62: Many catalytic tankyrase inhibitors tend to display toxicity, which is likely on-target (e.g., 10.1177/0192623315621192; 10.1158/0008-5472). This constitutes the main limiting factor for these compounds. An incomplete inhibition of Wnt/beta-catenin signalling may contribute to the challenges, but this does not appear to be the dominant problem. A more prominent introduction to this important challenge is probably expected by the field.

(2) The authors do a good job in setting the scene for the need for tankyrase degraders. Their observations relating to the formation of puncta (degradasomes) being tankyrase-dependent are compatible with a previous study by Martino-Echarri et al. 2016 (10.1371/journal.pone.0150484): simultaneous silencing of TNKS and TNKS2 by RNAi abolishes degradasome formation. The paper is cited as reference 17, but only in passing, and deserves more prominence. (It includes an entire paragraph titled "Expression of tankyrases 1 and 2 is required for TNKSi-induced formation of axin puncta").

(3) Moreover, the scaffolding concept has been discussed comprehensively in other studies: 10.1111/bph.14038 and more recently 10.1042/BCJ20230230. There are also a few studies that focus on targeting the ankyrin repeat clusters of tankyrase to disengage substrates (10.1038/s41598-020-69229-y; 10.1038/s41598-019-55240-5) that illustrate the concept of blocking the scaffolding function. In that sense, the hypotheses are mature, and it is interesting to see some of them supported in this study. The authors could improve how they set their work into the context of these other efforts and proposals.

(4) In several places in the manuscript, the DC is referred to as "biomolecular condensate", at times even as a "classic example", implying that it operates through phase separation. This has not been demonstrated. In fact, super-resolution microscopy indicates that the puncta are not droplet-like (10.7554/eLife.08022), which would argue against the condensate hypothesis.

(5) It is beautiful to be able to use IWR1 and IWR1-POMA at identical concentrations for direct comparisons. However, this requires the two compounds to bind to tankyrase similarly well and reach the target to a comparable extent. How sure are authors that target engagement is comparable? Has this been evaluated?

(6) Figure 1F: It is not immediately apparent how IWR1-POMA shows more complete containment of Wnt/beta-catenin signalling. Most Wnt/beta-catenin targets lie close to the perfect diagonal, so I do not see how the statement "that IWR1-POMA controlled WNT/β-catenin signaling more effectively than IWR1" (in the legend of Figure 1F) is supported. Minimally, an expanded explanation would benefit the reader. Providing the colour-coding legend directly in the figure would help improve clarity. Also, the panel is very small and may benefit from a different presentation in the figure.

(7) Figure 2: The conclusion of a "deeper suppression" of signalling relies on overexpression of tankyrase in an otherwise tankyrase-null background. Have the authors attempted to measure reporter activity or endogenous gene expression without tankyrase overexpression, in Wnt3a-stimulated cells (in the context of a normal Wnt/beta-catenin pathway) or CRC cells at the basal level? Non-catalytic activity in a similar assay has previously been observed upon tankyrase overexpression (10.1016/j.molcel.2016.06.019). Whether or not there is a substantial scaffolding effect at endogenous tankyrase levels after tankyrase inhibition remains unconfirmed, and the PROTAC is a valuable tool to address this important question. The findings presented in Figure S7C and D go some way towards answering this question - these data could be presented more prominently, and similar assays could be performed in other cell systems.

(8) Line 237/238: "TNKS accumulation negatively impacts the catalytic activity of the DC (Figure 5D)" - the data do not show this. Beta-catenin levels are a surrogate readout for DC function (phosphorylation and ubiquitylation). Minimally, this requires rewording, with reference to beta-catenin levels.

(9) Line 303-304: Beta-catenin is thought to exchange at beta-catenin degradasomes; this is clear from previous FRAP assays and the observation that phospho-beta-catenin accumulates in degradasomes upon proteasome inhibition (10.1158/1541-7786.MCR-15-0125). However, degradasome size hasn't, to my knowledge, been related to activity. Can this be clarified, please?

(10) There are previous hypotheses/proposals that the sensitivity of CRC cells to tankyrase inhibition correlates with APC truncation or PIK3CA status (10.1158/1535-7163.MCT-16-0578; 10.1038/s41416-023-02484-8). Have the authors considered expanding their cell line panel (Figure S7) to sample a wider range of cell lines, including some that are wild-type with regard to APC or Wnt/beta-catenin signalling in general? This would be a valuable addition to the work. Quantitated colony formation data could be moved to the main body of the manuscript.

(11) The manuscript only mentions toxicity (i.e., therapeutic window) in the last sentence of the Discussion section. As this is THE main challenge with tankyrase inhibitors (as mentioned above), can the authors expand their discussion of this aspect? Is there an expectation that PROTACs may be less toxic?

(12) Figures 3, 4, 5A: For fluorescence microscopy experiments, can these be quantified, and can repeat data be included?

(13) Figure 4, S6: An additional channel illustrating the distribution of cells (e.g., nuclei, cytoskeleton, or membrane) would be helpful for orientation and context for the AXIN1 signal.

(14) How were cytosolic fractions of cells prepared to assess cytosolic beta-catenin levels? This detail is missing from the methods.

Reviewer #2 (Public review):

Summary:

This study focuses on the genomic privacy risks associated with Genome-Wide Association Study (GWAS) summary statistics, employing a three-tiered demonstration framework of "theoretical derivation - simulation experiments - real-data validation". The research finds that when GWAS summary statistics are combined with high-dimensional phenotypic data, genotype recovery and individual re-identification can be achieved using linear programming methods. It further identifies key influencing factors such as the effective phenotype-to-sample size ratio (R/N) and minor allele frequency (MAF). These findings provide practical reference for improving data governance policies in genomic research, holding certain real-world significance.

Strengths:

This study integrates theoretical analysis, simulation validation, and the application of real-world datasets to construct a comprehensive research framework, which is conducive to understanding and mitigating the risk of private information leakage in genomic research.

Weaknesses:

(1) Limited scope of variant types covered:

The analysis is conducted solely on Single Nucleotide Polymorphisms (SNPs), omitting other crucial genomic variant types such as Copy Number Variations (CNVs), Insertions/Deletions (InDels), and chromosomal translocations/inversions. From a genomic structure perspective, variants like CNVs and InDels are also core components of individual genetic characteristics, and in some disease-related studies, association signals for these variants can be even more significant than those for SNPs. From the perspective of privacy risk logic, the genotypes of these variants (e.g., copy number for CNVs, base insertion/deletion status for InDels) can also be quantified and could theoretically be inferred backwards using the combination of "summary statistics + high-dimensional phenotypes". Their privacy leakage risks might differ from those of SNPs (for instance, rare CNVs might be more easily re-identified due to higher genetic specificity).

(2) Bias in data applicability scope:

Both the simulation experiments and real-data validation in the study primarily rely on European population samples (e.g., 489 European samples from the 1000 Genomes Project; the genetic background of whole blood tissue samples from the GTEx project is not explicitly mentioned regarding non-European proportions). It only briefly notes a higher risk for African populations in the individual re-identification risk assessment, without conducting systematic analyses for other populations, such as East Asian, South Asian, or admixed American populations. Significant differences in genetic structure (e.g., MAF distribution, linkage disequilibrium patterns) exist across different populations. This may result in the R/N threshold and the relationship between MAF and recovery accuracy identified in the study not being fully applicable to other populations

Hence, addressing the aforementioned issues through supplementary work would enhance the study's scientific rigor and application value, potentially providing more comprehensive theoretical and technical support for "privacy protection" in genomic data sharing.

Reviewer #2 (Public review):

Summary:

In this paper, Shukla, Cross, Kish, and colleagues investigate how binding of a cargo-adaptor mimic (KinTag) to the TPR domains of the kinesin-1 light chain, or disruption of the TPR docking site (TDS) on the kinesin-1 heavy chain, triggers release of the TPR domains from the holoenzyme. This dislocation provides a plausible mechanism for transition out of the autoinhibited lambda-particle toward the open and active conformation of kinesin-1. Using a combination of negative-stain electron microscopy, AlphaFold modeling, biochemical assays, hydrogen-deuterium exchange mass spectrometry (HDX-MS), and other methods, the authors show how TPR undocking propagates conformational changes through the coiled-coil stalk to the motor domains, increasing their mobility and enhancing interactions with the microtubule-bound cofactor MAP7. Together, they propose a model in which the TDS on CC1 of the heavy chain forms a "shoulder" in the compact, autoinhibited state. Cargo-adaptor binding, mimicked here by KinTag, dislodges this shoulder, liberating the motor domains and promoting MAP7 association, driving kinesin-1 activation.

Strengths:

Throughout the study, the authors use a clever construct design - e.g., delta-Elbow, ElbowLock, CC-Di, and the high-affinity KinTag - to test specific mechanisms by directly perturbing structural contacts or affecting interactions. The proposed mechanism of releasing autoinhibition via adaptor-induced TPR undocking is also interrogated with a number of complementary techniques that converge on a convincing model for activation that can be further tested in future studies. The paper is well-written and easy to follow, though some more attention to figure labels and legends would improve the manuscript (detailed in recommendations for the authors).

Weaknesses:

These reflect limits of what the current data can establish rather than flaws in execution. It remains to be tested if the open state of kinesin-1 initiated by TPR undocking is indeed an active state of kinesin-1 capable of processive movement and/or cargo transport. It also remains to be determined what the mechanism of motor domain undocking from the autoinhibited conformation is, and perhaps this could have been explored more here. The authors have shown by HDX-MS that the motor domains become more mobile on KinTag binding, but perhaps molecular dynamics would also be useful for modelling how that might occur.

Reviewer #2 (Public review):

Summary:

In this study, the authors follow up on a previous suppressor screen of a temperature-sensitive allele of mis4 (mis4-G1487D), the cohesin loading factor in S. pombe, and identify additional suppressor alleles tied to the S. pombe TORC1 complex. Their analysis suggests that these suppressor mutations attenuate TORC1 activity, while enhanced TORC1 activity is deleterious in this context. Suppression of TORC1 activity also ameliorates chromosome segregation and spindle defects observed in the mis4-G1487D strain, although some more subtle effects are not reconstituted. The authors provide evidence that this genetic suppression is also tied to the reconstitution of cohesin loading. Moreover, disrupting TORC1 also enhances Mis4/cohesin association with chromatin (likely reflecting enhanced loading) in WT cells, while rapamycin treatment can enhance the robustness of chromosome transmission. These effects likely arise directly through TORC1 or its downstream effector kinases, as TORC1 co-purifies with Mis4 and Rad21; these factors are also phosphorylated in a TORC1-dependent fashion. Disrupting Sck2, a kinase downstream of TORC1, also suppresses the mis4-G1487D allele while simultaneous disruption of Sck1 and Sck2 enhances cohesin association with chromatin, albeit with differing effects on phosphorylation of Mis4 and Psm1/Scm1. Phosphomutants of Mis4 and Psm1 that mimic observed phosphorylation states identified by mass spectrometry that are TORC1-dependent also suppressed phenotypes observed in the mis4-G1487D background. Last, the authors provide evidence that the mis4-G1487D background and TORC1 mutant backgrounds display an overlap in the dysregulation of genes that respond to environmental conditions, particularly in genes tied to meiosis or other "stress".

Overall, the authors provide compelling evidence from genetics, biochemistry, and cell biology to support a previously unknown mechanism by which nutrient sensing regulates cohesin loading with implications for the stress response. The technical approaches are generally sound, well-controlled, and comprehensive.

Specific Points:

(1) While the authors favor the model that the enhanced cohesin loading upon diminished TORC1 activity helps cells to survive harsh environmental conditions, as starvation of S. pombe also drives commitment to meiosis, it seems as plausible that enhanced cohesin loading is related to preparing the chromosomes to mate.

(2) Related to Point 1, the lab of Sophie Martin previously published that phosphorylation of Mis4 characterizes a cluster of phosphotargets during starvation/meiotic induction (PMID: 39705284). This work should be cited, and the authors should interrogate how their observations do or do not relate to these prior observations (are these the same phosphosites?).

(3) It would be useful for the authors to combine their experimental data sets to interrogate whether there is a relationship between the regions where gene expression is altered in the mis4-G1487D strain and changes in the loading of cohesin in their ChIP experiments.

(4) Given that the genes that are affected are predominantly sub-telomeric while most genes are not affected in the mis4-G1487D strain, one possibility that the authors may wish to consider is that the regions that become dysregulated are tied to heterochromatic regions where Swi6/HP1 has been implicated in cohesin loading.

(5) It would be helpful to show individual data points from replicates in the bar graphs - it is not always clear what comprises the data sets, and superplots would be of great help.

Reviewer #2 (Public review):

Summary:

King et al. present several sets of experiments aimed to address the potential impact of UV irradiation on human mitochondrial DNA as well as the possible role of mitochondrial TFAM protein in handling UV-irradiated mitochondrial genomes. The carefully worded conclusion derived from the results of experiments performed with human HeLa cells, in vitro small plasmid DNA, with PCR-generated human mitochondrial DNA, and with UV-irradiated small oligonucleotides is presented in the title of the manuscript: "UV irradiation alters TFAM binding to mitochondrial DNA". The authors also interpret results of somewhat unconnected experimental approaches to speculate that "TFAM is a potential DNA damage sensing protein in that it promotes UVC-dependent conformational changes in the [mitochondrial] nucleoids, making them more compact." They further propose that such a proposed compaction triggers the removal of UV-damaged mitochondrial genomes as well as facilitates replication of undamaged mitochondrial genomes.

Strengths:

(1) The authors presented convincing evidence that a very high dose (1500 J/m2) of UVC applied to oligonucleotides covering the entire mitochondrial DNA genome alleviates sequence specificity of TFAM binding (Figure 3). This high dose was sufficient to cause UV lesions in a large fraction of individual oligonucleotides. The method was developed in the lab of one of the corresponding authors (reference 74) and is technically well-refined. This result can be published as is or in combination with other data.

(2) The manuscript also presents AFM evidence (Figure 4) that TFAM, which was long known to facilitate compaction of the mitochondrial genome (Alam et al., 2003; PMID 12626705 and follow-up citations), causes in vitro compaction of a small pUC19 plasmid and that approximately 3 UVC lesions per plasmid molecule result in a slight, albeit detectable, increase in TFAM compaction of the plasmid. Both results can be discussed in line with a possible extrapolation to in vivo phenomena, but such a discussion should include a clear statement that no in vivo support was provided within the set of experiments presented in the manuscript.

Weaknesses:

Besides the experiments presented in Figures 3 and 4, other results do not either support or contradict the speculation that TFAM can play a protective role, eliminating mitochondrial genomes with bulky lesions by way of excessive compaction and removing damaged genomes from the in vivo pool.

To specify these weaknesses:

(1) Figure 1 - presents evidence that UVC causes a reduction in the number of mitochondrial spots in cells. The role of TFAM is not assessed.

(2) Figure 2 - presents evidence that UVC causes lesions in mitochondrial genomes in vivo, detectable by qPCR. No direct assessment of TFAM roles in damage repair or mitochondrial DNA turnover is assessed despite the statements in the title of Figure 2 or in associated text. Approximately 2-fold change in gene expression of TFAM and of the three other genes does not provide any reasonable support to suggestion about increased mitochondrial DNA turnover over multiple explanations on related to mitochondrial DNA maintenance.

(3) Figure 5. Shows that TFAM does not protect either mitochondrial nucleoids formed in vitro or mitochondrial DNA in vivo from UVC lesions as well as has no effect on in vivo repair of UV lesions.

(4) Figure 6: Based on the above analysis, the model of the role of TFAM in sensing mtDNA damage and elimination of damaged genomes in vivo appears unsupported.

(5) Additional concern about Figure 3 and relevant discussion: It is not clear if more uniform TFAM binding to UV irradiated oligonucleotides with varying sequence as compared to non-irradiated oligonucleotides can be explained by just overall reduced binding eliminating sequence specific peaks.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors combined coarse-grained structure-based model simulation, optical tweezer experiments, and AI-based analysis to assess the knotting behavior of the TrmD-Tm1570 protein. Interestingly, they found that while the structure-based model can fold the single knot from TrmD and Tm1570, the double-knot protein TrmD-Tm1570 cannot form a knot itself, suggesting the need for chaperone proteins to facilitate this knotting process. This study has strong potential to understand the molecular mechanism of knotted proteins, supported by many experimental and simulation evidence. However, there are a few places that appear to lack sufficient details, and more clarification in the presentation is needed.

Strengths:

A combination of both experimental and computational studies.

Weaknesses:

There is a lack of detail to support some statements.

(1) The use of the AI-based method, SOM, can be emphasized further, especially in its analysis of the simulated unfolding trajectories and discovery of the four unfolding/folding pathways. This will strengthen the statistical robustness of the discovery.

(2) The manuscript would benefit from a clearer description of the correlation between the simulation and experimental results. The current correlation, presented in the paragraph starting from Line 250, focuses on measured distances. The authors could consider providing additional evidence on the order of events observed experimentally and computationally. More statistical analyses on the experimental curves presented in Figure 4 supplement would be helpful.

(3) How did the authors calibrate the timescale between simulation and experiment? Specifically, what is the value \tau used in Line 270, and how was it calculated? Relevant information would strengthen the connection between simulation and experiment.

(4) In Line 342, the authors comment that whether using native contacts or not, they cannot fold double-knotted TrmD-Tm1570. Could the authors provide more details on how non-native interactions were analyzed?

(5) It appears that the manuscript lacks simulation or experimental evidence to support the statement at Line 343: While each domain can self-tie into its native knot, this process inhibits the knotting of the other domain. Specifically, more clarification on this inhibition is needed.

Reviewer #2 (Public review):

Summary:

Ptbp1 has been proposed as a key regulator of neuronal fate through its role in repressing neurogenesis. In this study, the authors conditionally inactivated Ptbp1 in mouse retinal progenitor cells using the Chx10-Cre line. While RNA-seq analysis at E16 revealed some changes in gene expression, there were no significant alterations in retinal cell type composition, and only modest transcriptional changes in the mature retina, as assessed by immunofluorescence and scRNAseq. Based on these findings, the authors conclude that Ptbp1 is not essential for cell fate determination during retinal development.

Strengths:

Despite some effects of Ptbp1 inactivation (initiated around E11.5 with the onset of Chx10-Cre activity) on gene expression and splicing, the data convincingly demonstrate that retinal cell type composition remains largely unaffected. This study is highly significant since it challenges the prevailing view of Ptbp1 as a central repressor of neurogenesis and highlights the need to further investigate, or re-evaluate, its role in other model systems and regions of the CNS.

Weaknesses:

A limitation of the study is the use of the Chx10-Cre driver, which initiates recombination around E11. This timing does not permit assessment of Ptbp1 function during the earliest phases of retinal development, if expressed at that time.

Comments on revisions:

The authors have thoroughly and satisfactorily addressed all my previous comments.

Reviewer #2 (Public review):

Summary:

This manuscript presents compelling evidence for a novel anti-inflammatory function of glycoprotein non-metastatic melanoma protein B (GPNMB) in chondrocyte biology and osteoarthritis (OA) pathology. Through a combination of in vitro, ex vivo, and in vivo models, including the destabilization of the medial meniscus (DMM) surgery in mice, the authors demonstrate that GPNMB expression is upregulated in OA-affected cartilage and that recombinant GPNMB treatment reduces the expression of key catabolic markers (MMPs, Adamts-4, and IL-6) without impairing anabolic gene expression. Notably, DBA/2J mice lacking functional GPNMB exhibit exacerbated cartilage degradation post-injury. Mechanistically, GPNMB appears to mitigate inflammation via the MAPK/ERK pathway. Overall, the work is thorough, methodologically sound, and significantly advances our understanding of GPNMB as a protective modulator in osteoarthritic joint disease. The findings could open pathways for therapeutic development.

Strengths:

(1) Clear hypothesis addressing a well-defined knowledge gap.

(2) Robust and multi-modal experimental design: includes human, mouse, cell-line, explant, and surgical OA models.

(3) Elegant use of DBA/2J GPNMB-deficient mice to mimic endogenous loss-of-function.

(4) Mechanistic insight provided through MAPK signaling analysis.

(5) Statistical analysis appears rigorous and the figures are informative.

Weaknesses:

(1) Clarify the strain background of the DBA/2J GPNMB+ mice: While DBA/2J GPNMB+ is described as a control, it would help to explicitly state whether these are transgenically rescued mice or another background strain. Are they littermates, congenic, or a separate colony?

(2) Provide exact sample sizes and variance in all figure legends: Some figures (e.g., Figure 2 panels) do not consistently mention how many replicates were used (biological vs. technical) for each experimental group. Standardizing this across all panels would improve reproducibility.

(3) Expand on potential sex differences: The DMM model is applied only in male mice, which is noted in the methods. It would be helpful if the authors added 1-2 lines in the discussion acknowledging potential sex-based differences in OA progression and GPNMB function.

(4) Visual clarity in schematic (Figure 7): The proposed mechanism is helpful but the text within the schematic is somewhat dense and could be made more readable with spacing or enlarged font. Also, label the MAPK/ERK pathway explicitly in panel B.

Comments on revisions:

The authors have addressed all the concerns raised in the initial review.

Reviewer #2 (Public review):

In the presented manuscript, Teplenin and colleagues use both electrical pacing and optogenetic stimulation to create a reproducible, controllable source of ectopy in cardiomyocyte monolayers. To accomplish this, they use a careful calibration of electrical pacing characteristics (i.e., frequency, number of pulses) and illumination characteristics (i.e., light intensity, surface area) to show that there exists a "sweet spot" where oscillatory excitations can emerge proximal to the optogenetically depolarized region following electrical pacing cessation, akin to pacemaker cells. Furthermore, the authors demonstrate that a high-frequency electrical wave-train can be used to terminate these oscillatory excitations. The authors observed this oscillatory phenomenon both in vitro (using neonatal rat ventricular cardiomyocyte monolayers) and in silico (using a computational action potential model of the same cell type). These are surprising findings and provide a novel approach for studying triggered activity in cardiac tissue.

The study is extremely thorough and one of the more memorable and grounded applications of cardiac optogenetics in the past decade. One of the benefits of the authors' "two-prong" approach of experimental preps and computational models is that they could probe the number of potential variable combinations much deeper than through in vitro experiments alone. The strong similarities between the real-life and computational findings suggest that these oscillatory excitations are consistent, reproducible, and controllable.

Triggered activity, which can lead to ventricular arrhythmias and cardiac sudden death, has been largely contributed to sub-cellular phenomena, such as early or delayed afterdepolarizations, and thus to date has largely been studied in isolated single cardiomyocytes. However, these findings have been difficult to translate to tissue- and organ-scale experiments, as well-coupled cardiac tissue has notably different electrical properties. This underscores the significance of the study's methodological advances: use of a constant depolarizing current in a subset of (illuminated) cells to reliably result in triggered activity could facilitate the more consistent evaluation of triggered activity at various scales. An experimental prep that is both repeatable and controllable (i.e., both initiated and terminated through the same means) is a boon for further inquiry.

The authors also substantially explored phase space and single cell analyses to document how this "hidden" bi-stable phenomenon can be uncovered during emergent collective tissue behavior. Calibration and testing of different aspects (e.g.: light intensity, illuminated surface area, electrical pulse frequency, electrical pulse count) and other deeper analyses, as illustrated in Figures S3-S8 and Video S1, are significant and commendable.

Given the study is computational, it is surprising that the authors did not replicate their findings using well-validated adult ventricular cardiomyocyte action potential models, such ten Tusscher 2006 or O'Hara 2011. This may have felt out-of-scope, given the nice alignment of rat cardiomyocyte data between in vitro and in silico experiments. However, it would have been helpful peace-of-mind validation, given the significant ionic current differences between neonatal rat and adult ventricular tissue. It is not fully clear whether the pulse trains could have resulted in the same bi-stable oscillatory behavior, given the longer APD of humans relative to rats. The observed phenomenon certainly would be frequency-dependent and would have required tedious calibration for a new cell type, albeit partially mitigated by the relative ease of in silico experiments.

There are likely also mechanistic differences between this optogenetically-tied oscillatory behavior and triggered activity observed in other studies. This is because the constant light-elicited depolarizing current is disrupting the typical resting cardiomyocyte state, thereby altering the balance between depolarizing ionic currents (such as Na+ and Ca2+) and repolarizing ionic currents (such as K+ and Ca2+). The oscillatory excitations appear to later emerge at the border of the illuminated region and non-stimulated surrounding tissue, which is likely an area of high source-sink mismatch. The authors appear to acknowledge differences in this oscillatory behavior and previous sub-cellular triggered activity research in their discussion of ectopic pacemaker activity, which are canonically observed in genetic, pharmacologic, or pathological ionic conditions. Regardless, it is exciting to see new ground being broken in this difficult-to-characterize experimental space, even if the method illustrated here may not necessarily be broadly applicable.

Comments on revisions:

I have read the authors' rebuttal to our earlier comments and do not have any further questions or comments. Thank you for implementing the minor improvements to Figure visualizations and for creating Video S1 to accompany the article.

Reviewer #2 (Public review):

Summary:

Based on extensive live cell assays, SEC, and NMR studies of reconstituted complexes, these authors explore the roles of clathrin and the AP2 protein in facilitating clathrin mediated endocytosis via activated arrestin-2. NMR, SEC, proteolysis, and live cell tracking confirm a strong interaction between AP2 and activated arrestin using a phosphorylated C-terminus of CCR5. At the same time a weak interaction between clathrin and arrestin-2 is observed, irrespective of activation.

These results contrast with previous observations of class A GPCRs and the more direct participation by clathrin. The results are discussed in terms of the importance of short and long phosphorylated bar codes in class A and class B endocytosis.

Strengths:

The 15N,1H and 13C,methyl TROSY NMR and assignments represent a monumental amount of work on arrestin-2, clathrin, and AP2. Weak NMR interactions between arrestin-2 and clathrin are observed irrespective of activation of arrestin. A second interface, proposed by crystallography, was suggested to be a possible crystal artifact. NMR establishes realistic information on the clathrin and AP2 affinities to activated arrestin with both kD and description of the interfaces.

Weaknesses:

This reviewer has identified only minor weaknesses with the study.

(1) I don't observe two overlapping spectra of Arrestin2 (1-393) +/- CLTC NTD in Supp Figure 1

(2) Arrestin-2 1-418 resonances all but disappear with CCR5pp6 addition. Are they recovered with Ap2Beta2 addition and is this what is shown in Supp Fig 2D

(3) I don't understand how methyl TROSY spectra of arrestin2 with phosphopeptide could look so broadened unless there are sample stability problems?

(4) At one point the authors added excess fully phosphorylated CCR5 phosphopeptide (CCR5pp6). Does the phosphopeptide rescue resolution of arrestin2 (NH or methyl) to the point where interaction dynamics with clathrin (CLTC NTD) are now more evident on the arrestin2 surface?

(5) Once phosphopeptide activates arrestin-2 and AP2 binds can phosphopeptide be exchanged off? In this case, would it be possible for the activated arrestin-2 AP2 complex to re-engage a new (phosphorylated) receptor?

(6) I'd be tempted to move the discussion of class A and class B GPCRs and their presumed differences to the intro and then motivate the paper with specific questions.

(7) Did the authors ever try SEC measurements of arrestin-2 + AP2beta2+CCR5pp6 with and without PIP2, and with and without clathrin (CLTC NTD? The question becomes what the active complex is and how PIP2 modulates this cascade of complexation events in class B receptors.

Reviewer #2 (Public review):

Summary:

In this paper, the authors defined the "channelome," consisting of 419 predicted human ion channels as well as 48,000 ion channel orthologs from other organisms. Using this information, the ion channels were clustered into groups, which can potentially be used to make predictions about understudied ion channels in the groups. The authors then focused on the CALHM ion channel family, mutating conserved residues and assessing channel function.

Strengths:

The curation of the channelome provides an excellent resource for researchers studying ion channels. Supplemental Table 1 is well organized with an abundance of useful information.

Comments on revisions:

The authors have thoroughly addressed my concerns and the manuscript is substantially improved. I have just a few suggestions regarding wording/clarification.

In Supplemental Figure 4, the Western blots (n=3) were quantitated, but the surface biotinylation was not. While I suppose that it is fine to just show one representative experiment for the biotinylation assay, the authors should indicate in the legend how many times this was done. It is essential to know whether these data in Supplemental Figure 4E, F are reproducible as they are absolutely critical for interpretation of all of the data in Figure 5.

Reviewer #2 (Public review):

Summary:

Shimogawa et al. studied the effect of lysine acetylation at different sites in the alpha-synuclein (aS) sequence on the protein-membrane affinity, seeding capacity in the test tube and in cells, and on the structure of fibrils, using a range of biophysical methods. They use non-canonical amino acid (ncAA) mutagenesis to prepare aS lysine acetylated variant at different sites.

Strengths:

The major strength of this paper is the approach used for the production of site-specific lysine acetylated variants of aS using ncAA mutagenesis, as well as the combination of a range of biophysical methods together with cellular assays and structure biology to decipher the effect of lysine acetylation on aS-membrane binding, seeding propensity, and fibril structure. This approach allowed the author to find that lysine acetylation at positions 12, 43, and 80 led to lower seeding capacity of aS in the test tube and in cells, but only acetylation at lysine 80 did not affect aS-membrane interaction. These results suggest that lysine acetylation at position 80 may be protective against aggregation without perturbing the proposed functional role of aS in synaptic plasticity.

Weaknesses:

SDS is not a good membrane model to investigate the effect of lysine acetylation on aS membrane-binding because it is a harsh detergent and solubilizes membranes. Negatively charged vesicles or vesicles made of a mixture of lipids mimicking the lipid composition of synaptic vesicles are more accepted in the field to study aS-membrane interactions. The authors used such vesicles for the FCS experiments, and they could be used for the initial screening of the 12 lysine acetylated variants of aS.

It would help the reader to have the experimental details (e.g., buffer, protein/lipid concentrations) for the different assays written in the figure legend.

The authors use an assay consisting of mixing 10% fibrils + 90% monomer to investigate the effect of lysine acetylation on aS. However, the assay only probes fibril elongation and/or secondary processes. The current wording can be misleading, and the term aggregation could be replaced by seeding capacity for clarity. For example, the authors state that lysine acetylation at sites 12, 43, and 80 each inhibits aggregation, but this statement is not supported by the data. Instead, the data show that the acetylation at these sites slows down the fibril elongation and thus decreases the seeding capacity of aS fibrils. In order to state that lysine acetylation has an effect on aS aggregation, fibril formation, the author should use an assay where the de novo formation of fibrils is assessed, such as in the presence of lipid vesicles or under shaking conditions.

It is not clear from the EM data that the structures of the different lysine acetylated variants are different, unlike what is stated in the text.

Reviewer #2 (Public review):

This study by Jaykumar and colleagues seeks to expand the field's appreciation of insulin responses in the brain, specifically by implicating WNK kinase function in various neuronal responses, ranging from behavioral / memory changes to GLUT4 trafficking to the cell surface with subsequent glucose uptake. This revised study is now comprehensive and presents a logical and reasonably documented cascade of molecular interactions responsible in part for GLUT4 trafficking under the regulation of WKK and insulin. Additional data allow the authors to dissect a plausible WNK/OSR1/SPAK-sortilin pathway for the modulation of GLUT4 trafficking, in part by capitalizing on a overlay of various techniques and systems. The data - much of it in vivo or ex vivo - showing a potential role for WNK function in brain glucose utilization remains a compelling part of the story, with the dissection of the signaling cascade and a potential role for sortilin in mediating WNK function via effects on GLUT4 cellular localization now more convincing.

Initially, the group shows that oral WNK463 treatment - an inhibitor of WNKs broadly - in mice augments a number of memory readouts. These findings fit within the context of the overall story the authors present: that WNK function is critical to brain glucose utilization, which impacts learning. Multiple approaches are used to show that WNK463 treatment, i.e. inhibition of WNKs, increases glucose uptake, including labeled 2-deoxyglucose uptake in vivo in the brain and in isolated synaptosome, and uptake in ex vivo hippocampal slices. These findings are solid and consistent. With the exception of some relatively minor comments regarding the data presentation made to the authors and now fully addressed, the findings showing that WNK463 treatment increases GLUT4-mediated glucose uptake and surface localization of GLUT4 are reasonable, with the hippocampal slice data being particularly relevant.

While the details of the WNK signaling cascade is dense, in the revised application one clearly appreciates the molecular interrogation and interactions the group is dissecting, supported by the use of multiple models. With the additional findings, these systems and the data now reinforce each other, presenting a strongly documented overall story.

A limitation of the study with the initial submission was the authors' reliance upon a single pharmacological tool (WNK463) to inhibit WNK kinases. WNK463 apparently has substantial specificity for WNKs and WNK463 treatment lessened OSR1 phosphorylation (a WNK substrate). Nevertheless, the cohesiveness of the findings in terms of the broader pathway engagement (GLUT4 trafficking, glucose uptake) is consistent with the author's proposed mechanisms and conclusions. The authors have additionally addressed this concern in the revised manuscript with more information supporting the specificity of WNK463 as well as the multiple approaches to confirm the effect of WNK463 on the WNK signaling pathway of interest.

The final few paragraphs of the discussion that weave the author's findings into the field more broadly, including Sortilin function and neurological disorders, are appreciated. Additional clarity in the Methods section is also helpful.

Reviewer #2 (Public review):

A summary of what the authors were trying to achieve.

The authors aim to determine whether the gene Hsb17b7 is essential for hair cell function and, if so, to elucidate the underlying mechanism, specifically the HSB17B7 metabolic role in cholesterol biogenesis. They use animal, tissue, or data from zebrafish, mouse, and human patients.

Strengths:

(1) This is the first study of Hsb17b7 in the zebrafish (a previous report identified this gene as a hair cell marker in the mouse utricle).

(2) The authors demonstrate that Hsb17b7 is expressed in hair cells of zebrafish and the mouse cochlea.

(3) In zebrafish larvae, a likely KO of the Hsb17b7 gene causes a mild phenotype in an acoustic/vibrational assay, which also involves a motor response.

(4) In zebrafish larvae, a likely KO of the Hsb17b7 gene causes a mild reduction in lateral line neuromast hair cell number and a mild decrease in the overall mechanotransduction activity of hair cells, assayed with a fluorescent dye entering the mechanotransduction channels.

(5) When HSB17B7 is overexpressed in a cell line, it goes to the ER, and an increase in Cholesterol cytoplasmic puncta is detected. Instead, when a truncated version of HSB17B7 is overexpressed, HSB17B7 forms aggregates that co-localize with cholesterol.

(6) It seems that the level of cholesterol in crista and neuromast hair cells decreases when Hsb17b7 is defective (but see comment below).

Weakness:

(1) The statement that HSD17B7 is "highly" expressed in sensory hair cells in mice and zebrafish seems incorrect for zebrafish:

(a) The data do not support the notion that HSB17B7 is "highly expressed" in zebrafish. Compared to other genes (TMC1, TMIE, and others), the HSB17B7 level of expression in neuromast hair cells is low (Figure 1F), and by extension (Figure 1C), also in all hair cells. This interpretation is in line with the weak detection of an mRNA signal by ISH (Figure 1G I"). On this note, the staining reported in I" does not seem to label the cytoplasm of neuromast hair cells. An antisense probe control, along with a positive control (such as TMC1 or another), is necessary to interpret the ISH signal in the neuromast.

(b) However, this is correct for mouse cochlear hair cells, based on single-cell RNA-seq published databases and immunostaining performed in the study. However, the specificity of the anti-HSD17B7 antibody used in the study (in immunostaining and western blot) is not demonstrated. Additionally, it stains some supporting cells or nerve terminals. Was that expression expected?

(2) A previous report showed that HSD17B7 is expressed in mouse vestibular hair cells by single-cell RNAseq and immunostaining in mice, but it is not cited:

Spatiotemporal dynamics of inner ear sensory and non-sensory cells revealed by single-cell transcriptomics.

Jan TA, Eltawil Y, Ling AH, Chen L, Ellwanger DC, Heller S, Cheng AG.

Cell Rep. 2021 Jul 13;36(2):109358. doi: 10.1016/j.celrep.2021.109358.

(3) Overexpressed HSD17B7-EGFP C-terminal fusion in zebrafish hair cells shows a punctiform signal in the soma but apparently does not stain the hair bundles. One limitation is the consequence of the C-terminal EGFP fusion to HSD17B7 on its function, which is not discussed.

(4) A mutant Zebrafish CRISPR was generated, leading to a truncation after the first 96 aa out of the 340 aa total. It is unclear why the gene editing was not done closer to the ATG. This allele may conserve some function, which is not discussed.

(5) The hsd17b7 mutant allele has a slightly reduced number of genetically labeled hair cells (quantified as a 16% reduction, estimated at 1-2 HC of the 9 HC present per neuromast). On a note, it is unclear what criteria were used to select HC in the picture. Some Brn3C:mGFP positive cells are apparently not included in the quantifications (Figure 2F, Figure 5A).

(6) The authors used FM4-64 staining to evaluate the hair cell mechanotransduction activity indirectly. They found a 40% reduction in labeling intensity in the HCs of the lateral line neuromast. Because the reduction of hair cell number (16%) is inferior to the reduction of FM4-64 staining, the authors argue that it indicates that the defect is primarily affecting the mechanotransduction function rather than the number of HCs. This argument is insufficient. Indeed, a scenario could be that some HC cells died and have been eliminated, while others are also engaged in this path and no longer perform the MET function. The numbers would then match. If single-cell staining can be resolved, one could determine the FM4-64 intensity per cell. It would also be informative to evaluate the potential occurrence of cell death in this mutant. On another note, the current quantification of the FM4-64 fluorescence intensity and its normalization are not described in the methods. More importantly, an independent and more direct experimental assay is needed to confirm this point. For example, using a GCaMP6-T2A-RFP allele for Ca2+ imaging and signal normalization.

(7) The authors used an acoustic startle response to elicit a behavioral response from the larvae and evaluate the "auditory response". They found a significative decrease in the response (movement trajectory, swimming velocity, distance) in the hsd17b7 mutant. The authors conclude that this gene is crucial for the "auditory function in zebrafish".

This is an overstatement:

(a) First, this test is adequate as a screening tool to identify animals that have lost completely the behavioral response to this acoustic and vibrational stimulation, which also involves a motor response. However, additional tests are required to confirm an auditory origin of the defect, such as Auditory Evoked Potential recordings, or for the vestibular function, the Vestibulo-Ocular Reflex.

(b) Secondly, the behavioral defects observed in the mutant compared to the control are significantly different, but the differences are slight, contained within the Standard Deviation (20% for velocity, 25% for distance). To this point, the Figure 2 B and C plots are misleading because their y-axis do not start at 0.

(8) Overexpression of HSD17B7 in cell line HEI-OC1 apparently "significantly increases" the intensity of cholesterol-related signal using a genetically encoded fluorescent sensor (D4H-mCherry). However, the description of this quantification (per cell or per surface area) and the normalization of the fluorescent signal are not provided.

(9) When this experiment is conducted in vivo in zebrafish, a reduction in the "DH4 relative intensity" is detected (same issue with the absence of a detailed method description). However, as the difference is smaller than the standard deviation, this raises questions about the biological relevance of this result.

(10) The authors identified a deaf child as a carrier of a nonsense mutation in HSB17B7, which is predicted to terminate the HSB17B7 protein before the transmembrane domain. However, as no genetic linkage is possible, the causality is not demonstrated.

(11) Previous results obtained from mouse HSD17B7-KO (citation below) are not described in sufficient detail. This is critical because, in this paper, the mouse loss-of-function of HSD17B7 is embryonically lethal, whereas no apparent phenotype was reported in heterozygotes, which are viable and fertile. Therefore, it seems unlikely that heterozygous mice exhibit hearing loss or vestibular defects; however, it would be essential to verify this to support the notion that the truncated allele found in one patient is causal.

Hydroxysteroid (17beta) dehydrogenase 7 activity is essential for fetal de novo cholesterol synthesis and for neuroectodermal survival and cardiovascular differentiation in early mouse embryos.

Jokela H, Rantakari P, Lamminen T, Strauss L, Ola R, Mutka AL, Gylling H, Miettinen T, Pakarinen P, Sainio K, Poutanen M.<br /> Endocrinology. 2010 Apr;151(4):1884-92. doi: 10.1210/en.2009-0928. Epub 2010 Feb 25.

(12) The authors used this truncated protein in their startle response and FM4-64 assays. First, they show that contrary to the WT version, this truncated form cannot rescue their phenotypes when overexpressed. Secondly, they tested whether this truncated protein could recapitulate the startle reflex and FM4-64 phenotypes of the mutant allele. At the homozygous level (not mentioned by the way), it can apparently do so to a lesser degree than the previous mutant. Again, the differences are within the Standard Deviation of the averages. The authors conclude that this mutation found in humans has a "negative effect" on hearing, which is again not supported by the data.

(13) The authors looked at the distribution of the HSB17B7 in a cell line. The WT version goes to the ER, while the truncated one forms aggregates. An interesting experiment consisted of co-expressing both constructs (Figure S6) to see whether the truncated version would mislocalize the WT version, which could be a mechanism for a dominant phenotype. However, this is not the case.

(14) Through mass spectrometry of HSB17B7 proteins in the cell line, they identified a protein involved in ER retention, RER1. By biochemistry and in a cell line, they show that truncated HSB17B7 prevents the interaction with RER1, which would explain the subcellular localization.

Hydroxysteroid (17beta) dehydrogenase 7 activity is essential for fetal de novo cholesterol synthesis and for neuroectodermal survival and cardiovascular differentiation in early mouse embryos.

Jokela H, Rantakari P, Lamminen T, Strauss L, Ola R, Mutka AL, Gylling H, Miettinen T, Pakarinen P, Sainio K, Poutanen M.<br /> Endocrinology. 2010 Apr;151(4):1884-92. doi: 10.1210/en.2009-0928. Epub 2010 Feb 25.

(15) Information and specificity validation of the HSB17B7 antibody are not presented. It seems that it is the same used on mice by IF and on zebrafish by Western. If so, the antibody could be used on zebrafish by IF to localize the endogenous protein (not overexpression as done here). Secondly, the specificity of the antibody should be verified on the mutant allele. That would bring confidence that the staining on the mouse is likely specific.

Reviewer #2 (Public review):

Summary:

In this study, Davis et al. embarked on the quest for the molecular elements responsible for the regulation of lymphatic phasic contractile activity in response to variation of transmural pressure, a mechanism (termed pressure-induced lymphatic chronotropy by the authors) critical for drainage of interstitial fluid from the tissue and transport of lymph back to the blood circulation. Their aim was to investigate the mechanism(s) involved in the pressure-induced regulation of lymphatic pumping, and test whether activation of cation channels, shown in other systems to play mechanosensitive roles are directly at play, and/or whether mechano-activation of GNAQ/GNA11-coupled GPCRs is necessary to generate second messengers to activate those channels, as it has been suggested for the regulation of myogenic tone in arteries. To achieve their goal, the authors used their well-described, highly reliable protocols of mouse lymphatic vessel isolation, pressure myography, and data acquisition to obtain frequency-pressure relationships and other contractile function parameters from transgenic mice where specific channels or molecular elements of interest have been ablated. They combined these data with scRNAseq analysis of these gene targets to determine their respective role and levels of expression in lymphatic muscle cells. Their conclusion is that none of the exhaustive list of tested ion channels was critical, except ANO1 Cl channels, part of the contractile pacemaker mechanism, but that transmural pressure activates GNAQ/GNA11-coupled GPCRs, which generate IP3 to induce SR Ca2+ release through IP3R1 and activate ANO1-mediated depolarization.

Strengths:

The manuscript's strengths reside primarily in very robust, clean, and unequivocal pressure myography data and analysis. The research team is mastering these techniques they developed more than a decade ago and have implemented in mouse lymphatics to study their contractile properties, with consistent and convincing outcomes. They also provide data from an impressive list of transgenic mice in order to determine the role of the targeted gene in pressure-induced lymphatic chronotropy, relying on pharmacological small molecule inhibitors only when necessary. Finally, the use of scRNAseq analysis they gathered from previously published datasets brings novelty with respect to the expression of the genes of interest in all populations of cells comprising the lymphatic vessels, but more critically, to validate or contrast the potential impact of genetic alteration of the given gene on the ability of lymphatic muscles to respond to a change in pressure.

Weaknesses:

The main weakness may reside in the fact that while the authors provide a convincing demonstration that GNAQ/GNA11 are involved in the regulation of the F-P relationship, they give little evidence of the involvement of "upstream" receptors. Indeed, inhibition of AT1R, shown to be involved in myogenic regulation of arteries (a phenomenon the authors rightfully compare to pressure-induced lymphatic chronotropy), didn't lead toa similar effect (decrease in F-P) in lymphatic vessels. Arguably, other GPCRs might be involved in lymphatic vessels, but as such information is not provided in the manuscript, the author's conclusions should be dampened. More in-depth discussion would be required. In fact, it can be argued that the discussion is very restricted with respect to the amount of data and information the manuscript provides.

Overall, the authors convincingly achieved their aim by performing an impressive number of technically challenging experiments, leading to solid datasets. While these support their main conclusions, a more elaborate discussion might be required to refine them.

This study is likely to have an important impact on the field as it provides some answers to the lingering question of how lymphatic vessels regulate their contractile activity to variation in transmural pressure and certainly proposes an experimental means to further explore and address that question.

Reviewer #2 (Public review):

This study by Anttonen, Christensen-Dalsgaard, and Elemans describes the development of hearing thresholds in an altricial songbird species, the zebra finch. The results are very clear and along what might have been expected for altricial birds: at hatch (2 days post-hatch), the chicks are functionally deaf. Auditory evoked activity in the form of auditory brainstem responses (ABR) can start to be detected at 4 days post-hatch, but only at very loud sound levels. The study also shows that ABR response matures rapidly and reaches adult-like properties around 25 days post-hatch. The functional development of the auditory system is also frequency dependent, with a low-to-high frequency time course. All experiments are very well performed. The careful study throughout development and with the use of multiple time-points early in development is important to further ensure that the negative results found right after hatching are not the result of the experimental manipulation. The results themselves could be classified as somewhat descriptive, but, as the authors point out, they are particularly relevant and timely. Since 2016, there have been a series of studies published in high-profile journals that have presumably shown the importance of prenatal acoustic communication in altricial birds, mostly in zebra finches. This early acoustic communication would serve various adaptive functions. Although acoustic communication between embryos in the egg and parents has been shown in precocial birds (and crocodiles), finding an important function for prenatal communication in altricial birds came as a surprise. Unfortunately, none of those studies performed a careful assessment of the chicks' hearing abilities. This is done here, and the results are clear: zebra finches at 2 and 6 days post-hatch are functionally deaf. Since it is highly improbable that the hearing in the egg is more developed than at birth, one can only conclude that zebra finches in the egg (or at birth) cannot hear the heat whistles. The paper also ruled out the detection on egg vibrations as an alternative path. The prior literature will have to be corrected, or further studies conducted to solve the discrepancies. For this purpose, the "companion" paper on bioRxiv that studies the bioacoustical properties of heat calls from the same group will be particularly useful. Researchers from different groups will be able to precisely compare their stimuli.

Beyond the quality of the experiments, I also found that the paper was very well written. The introduction was particularly clear and complete (yet concise).

Weaknesses:

My only minor criticism is that the authors do not discuss potential differences between behavioral audiograms and ABRs. Optimally, one would need to repeat the work of Okanoya and Dooling with your setup and using the same calibration. The ~20dB difference might be real, or it might be due to SPL measured with different instruments, at different distances, etc. Either way, you could add a sentence in the discussion that states that even with the 20 dB difference in audiogram heat whistles would not be detected during the early days post-hatch. But adding a (novel) behavioral assay in young birds could further resolve the issue.

More Minor Points:

(1) As mentioned in the main text, the duration of pips (from pips to bursts) affects the effective bandwidth of the stimulus. I believe that the authors could give an estimate of this effective bandwidth, given what is known from bird auditory filters. I think that this estimate could be useful to compare to the effective bandwidth of the heat-call, which can now also be estimated.

(2) Figure 5b. Label the green and pink areas as song and heat-call spectrum. Also note that in the legend the authors say: "Green and red areas display the frequency windows related to the best hearing sensitivity of zebra finches and to heat calls, respectively". I don't think this is what they meant. I agree that 1-4 kHz is the best frequency sensitivity of zebra finches, but they probably meant green == "song frequency spectrum" and pink == "heat call spectrum". In either case, the figure and the legend need clarification.

(3) Figure 5c. Here also, I would change the song and heat-call labels to "song spectrum", "heat call spectrum". The authors would not want readers to think that they used song and heat calls in these experiments (maybe next time?). For the same reason, maybe in 5a you could add a cartoon of the oscillogram of a frequency sweep next to your speaker.

(4) Methods. In the description of the stimulus, the authors describe "5ms long tone bursts", but these are the tone pips in the main part of the manuscript. Use the same terms.

Reviewer #2 (Public review):

Summary:

This study provides novel insights into the neurotransmitter release mechanisms employed by two distinct subclasses of dopaminergic neurons in the olfactory bulb (OB). The findings suggest that anaxonic neurons primarily release neurotransmitters through their dendrites, whereas axon-bearing neurons predominantly release neurotransmitters via their axons. Furthermore, the study reveals that anaxonic neurons exhibit self-inhibitory behavior, indicating that closely related neuronal subclasses may possess specialized roles in sensory processing.

Strengths:

This study introduces a novel and significant concept, demonstrating that two closely related neuron subclasses can exhibit distinct patterns of neurotransmitter release. Therefore, this finding establishes a valuable framework for future investigations into the functional diversity of neuronal subclasses and their contributions to sensory processing. Furthermore, these findings offer fundamental insights into the neural circuitry of the olfactory bulb, enhancing our understanding of sensory information processing within this critical brain region.

Weaknesses:

The reliance on synaptophysin-based presynaptic structures raises minor concerns about whether these structures represent functional synapses.

Comments on revisions:

Most of the concerns have been addressed by the authors, and there are no further comments about this manuscript.