Reviewer #1 (Public review):

Summary:

In this manuscript, Matar et al. introduce Mespilia globulus, the tuxedo sea urchin, as a new genomically-enabled model for echinoderm developmental biology. The authors establish a closed life-cycle culture system in a land-locked aquarium facility, demonstrate that key experimental techniques (hybridization chain reaction labelling and CRISPR/Cas9 gene knockout) are tractable in this species, and report chromosome-scale genome assemblies for two colour morphs and both sexes. Using these resources, they compare genome architecture and gene family evolution across sea urchin species, and investigate the genomic basis of sex determination.

Strengths:

The central motivation for this work is well justified: the long larval and juvenile periods of established sea urchin models such as Strongylocentrotus purpuratus have long limited the study of post-metamorphosis and adult biology, and M. globulus reaches metamorphosis in around two weeks and sexual maturity within four to six months, a substantial acceleration. The husbandry and life-cycle data are thorough, and the demonstration that hybridization chain reaction staining and CRISPR/Cas9 knockout both work as expected in this species convincingly establishes its experimental tractability. The two chromosome-scale genome assemblies are of high quality (BUSCO completeness above 99%, 21 chromosome-scale scaffolds consistent with other sea urchins), and the comparative synteny and gene family analyses are carefully constructed, drawing on a solid phylogenomic framework (CAFE-based gene family turnover analysis across six echinoderm species). The authors' finding that M. globulus has fewer duplicated genes in the gene repertoire relative to other camarodont urchins is a genuinely useful observation for researchers choosing a model system for functional genetics, since fewer paralogues should simplify interpretation of knockout phenotypes.

Weaknesses:

Some claims in the manuscript would benefit from additional supporting detail.

(1) The efficiency of the CRISPR/Cas9 knockout is illustrated qualitatively, but no sample size or penetrance value is reported, making it difficult for readers to judge how robust or reproducible this result is.

(2) The gene annotation is reported to have complete PFAM domain coverage for only 75% of predicted genes, but no independent completeness metric (such as BUSCO scored against the annotated gene set rather than the assembly) is provided, leaving open whether the remaining genes are genuinely novel, partial models, or annotation artefacts.

(3) Finally, at the time of review the NCBI BioProject accession cited for the genome and sequencing data (PRJNA1477966) could not be located, and it is not clear from the text whether this accession, once available, will include the gene annotation and RNA-seq datasets in addition to the raw genomic sequencing reads.

In summary, the authors achieve their stated aim of establishing M. globulus as a tractable, fast-developing echinoderm model, and the genomic and experimental resources presented support this conclusion. The comparative genomic conclusions - conservation of ancestral chromosome linkage groups, absence of a heteromorphic sex chromosome, and a comparatively low rate of gene family expansion - are well supported by the data shown, though some of the finer-grained claims (knockout efficiency, annotation completeness) require some clarification. Given the scarcity of tractable models for post-metamorphosis and adult echinoderm biology, this resource is likely to be of real value to the field, provided the genomic and transcriptomic data are made fully and clearly accessible to the community.

Reviewer #2 (Public review):

This manuscript introduces the tuxedo sea urchin, Mespilia globulus, as a new experimental model for developmental, reproductive and genomic biology. The authors establish culture methods that permit completion of the life cycle in a landlocked aquarium facility, demonstrate the applicability of developmental biology tools including HCR-FISH and CRISPR/Cas9-mediated gene disruption, generate chromosome-scale genome assemblies from two color morphs and both sexes, investigate potential sex determination mechanisms, and compare genome organization and gene family evolution with other sea urchin models. The authors conclude that M. globulus combines a relatively rapid life cycle with genomic tractability and therefore represents a valuable addition to the growing repertoire of genetically accessible sea urchin model systems.

Overall, I found this to be a strong and timely contribution that is well suited for the Tools and Resources category of eLife. The authors provide a comprehensive suite of resources, including husbandry protocols, genomic resources, developmental staging information, and proof-of-principle functional manipulations. The manuscript appropriately places M. globulus in the context of established sea urchin models, particularly Lytechinus pictus, and clearly argues that the new species is complementary rather than a replacement for existing systems. Given the increasing importance of genetically tractable echinoderm models, the development of an additional species that can be maintained and bred in closed aquarium systems is of considerable value to the field.

The evidence supporting the establishment of this model system is convincing, with multiple complementary datasets including life-cycle culture methods, genome assemblies, gene expression analyses, and gene-editing experiments.

My concerns primarily relate to two broader issues that should be addressed, followed by several specific comments.

(1) Genetic Background and Aquarium Trade Populations: A central argument of the manuscript is that M. globulus is attractive as a laboratory model because it is widely cultured in the aquarium trade and may exhibit reduced genetic variability due to captive propagation.

The manuscript states:

"M. globulus is a popular species in the aquarium industry and has excellent properties in tropical aquariums where it has been bred for many years in farming operations that reduce genomic heterogeneity..." (lines 96-98) and later:

"Captive breeding may also lower genetic variability compared to wild-caught individuals..." (lines 389-390).

However, the manuscript does not provide sufficient information to evaluate these claims. Several important questions remain unresolved:

(1) How genetically representative are the sequenced individuals relative to natural populations?

(2) What is known about the provenance and breeding history of the aquarium trade stocks used in this study?

(3) Are these animals derived from a small number of founder populations?

(4) Is there evidence for substantial inbreeding or genetic bottlenecks within commercial brood stocks?

(5) How similar are commercially available animals from different vendors and geographic sources?

These questions are important for both practical and biological reasons. From a practical perspective, researchers wishing to adopt M. globulus need to know whether animals purchased from aquarium suppliers are expected to resemble those analyzed here. From a biological perspective, reduced diversity or founder effects could influence genome assembly characteristics, heterozygosity estimates, gene family analyses, developmental traits, or responses to experimental manipulation.

Even if little information is currently available, the manuscript should explicitly discuss these uncertainties and provide available information regarding stock origin, aquaculture practices, and potential differences between captive and natural populations. A clear discussion of potential limitations would significantly strengthen the manuscript.

(2) Presentation and Interpretation of HCR and Phalloidin Data: Although the HCR and phalloidin experiments are not central to the major conclusions of the paper, they serve as important demonstrations of experimental tractability. At present, however, the presentation of these data is not fully convincing.

The HCR images show detectable signal, but the expression domains are only minimally documented. The manuscript states that expression patterns are consistent with known functions of Nodal and Notch signaling, yet the figures do not sufficiently guide readers to these conclusions (especially readers not familiar with sea urchin development). The signal is relatively diffuse and weak in some panels, and there is little annotation explaining exactly which embryonic territories are expressing the genes of interest. For readers without extensive sea urchin developmental biology expertise, it can be difficult to assess the validity and biological significance of the observed expression patterns.

Similarly, the phalloidin-labeled images provide limited anatomical information because the larvae are largely not labeled. I recommend:

(1) Adding labels identifying relevant embryonic regions and structures.

(2) Including arrows or overlays indicating key expression domains.

(3) Providing higher-magnification insets of relevant regions.

(4) Including selected optical sections rather than relying exclusively on 3D projections.

(5) Identifying known larval muscle groups in the phalloidin images.

(6) Improving image contrast and figure annotation where possible.

These changes would substantially strengthen the claim that established developmental biology methods are readily transferable to M. globulus.

Reviewer #3 (Public review):

Summary:

Omar Matar and colleagues describe how they successfully closed the life cycle of the tropical tuxedo urchin Mespilia globulus in a small, closed aquarium system. Its capacity to flourish under closed culturing conditions sets this sea urchin apart from most echinoderms and indeed most marine invertebrates, which require high-quality flow-through seawater (i.e. coastal access and a flow-through aquarium system). As M. globulus reaches sexual maturity in captivity in 4-6 months, which is shorter than other sea urchins, it opens the potential for transgenerational studies.

Matar et al. have developed a suite of molecular and genomic techniques and resources, including Cas9-mediated gene knockdown and chromosome-scale genome assemblies for both sexes and colour morphs. These strong aquaculture and genomics platforms suggest that M. globulus can provide insights into aspects of the sea urchin life cycle and history that would be difficult to study in other sea urchin models, which historically have been focused on embryogenesis.

Strengths:

This manuscript announces M. globulus as a novel, genome-enabled echinoderm model that can be cultured in a closed system with a few hundred litres of 23/24oC artificial seawater. This allows for experimental analysis of parts of the sea urchin life cycle that are not particularly tractable in other sea urchins, including the developmental biology of metamorphosis, symbiont interactions and immunity through the life cycle, post-settlement biomineralisation, and sex determination. The capacity to knock out embryonic/larval genes using CRISPR/Cas9 and visualise localised embryonic and larval gene expression using HCR are consistent with claims M. globulus can contribute novel insights into basic and applied (aquaculture) biology of sea urchins and echinoderms.

Weaknesses:

The general weakness of this manuscript is that the authors do not explain aspects of their study in enough detail (e.g. a single figure - Figure 2 - presents results of analysis of normal development, HCR and Cas9 knockdowns). This manuscript provides limited methodological detail about the culture system and the analysis of gene expression. Here are a few suggestions on how to improve the manuscript:

First, the authors should provide a thorough description of the methods used to cultivate and maintain M. globulus. This should include further details about the closed aquarium system; a schematic of the system would be insightful. Basic details about husbandry are needed, including (i) stocking densities of adults, embryos/larvae, postlarvae/juveniles; (ii) frequencies of level and water changes/top-ups; (iii) feeding regime at all phases of the life cycle (amount/sea urchin, post-feeding cleaning, etc.). These and other details are essential for the uptake of this model system. This documentation would provide the foundation for future improvements, which include shortening the time to acquire larval competence and sexual maturity, and improving and standardising larval settlement.

Second, the description of the procurement and analysis of mRNA is brief, unreferenced and reads as protocols used for an established model species (e.g. what is PFA in this case - the concentration of paraformaldehyde and the buffer can vary markedly between organisms and life stages). Even the RNA extraction protocols can vary between and within species. For instance, highly pigmented tissues tend to be more difficult to procure useable RNA. The HCR analysis, which is also scantily described, is restricted to embryonic and larval stages. Given the emphasis on the capacity of the M. globulus system to analyse all phases of the life cycle, it would be good to know if HCR can be performed on settled postlarvae, juveniles and adult tissues.

Third, the authors should consider dividing Figure 2, which consists of confocal images of normal development, HCR results and CRISPR/Cas9 knockout results, into three separate figures that explore these studies separately. A figure on normal development could, for instance, include documentation of metamorphosis, with a suite of images of postlarval stages. A figure documenting HCR could be expanded to include more stages, higher magnification images and other genes. A figure on the Cas9 knockdown of a PKS gene can provide details on the normal expression of this gene using HCR and possibly qRT-PCR.

Fourth, there should be consideration of providing more characterisation about the protein-coding genes comprising the chromosomal region (Chr. 4) that has marked differences between sexes. This could go beyond Supplementary Table 4 and Supplementary Figure 5B, and include analysis of expression in adult tissues (this would be enhanced by having matching male and female tissues), and KEGG pathways and GO enrichments.

Overall, this is an exciting development in the study of echinoids and echinoderms. This manuscript can be improved by providing the reader with more details. Given the exciting prospect of being able to study M. globulus settlement and metamorphosis in detail, the authors may consider providing more information about this part of the life cycle.

Reviewer #1 (Public review):

Summary:

This article taps into the very interesting phylogeographic situation of two sympatric species of clingfishes sharing the same distribution and environment around Crete and the island of Cythera. Basically, it shows that the population structures of these fishes are influenced in a parallel manner by seascape, low dispersal, and potentially drift or selection despite a different phylogeographic history. This parallelism is looked after in a detailed manner at the genome level. I am very enthusiastic about this extremely well-constructed and very cleverly designed study of this natural "common garden" evolutionary duplicate situation, something sufficiently rare to be underlined.

The authors have produced complete genomes for the two species and their five population samples, from which they are able to conduct up-to-date data analyses. The text is clearly written, without too much jargon, and the options chosen for the various analyses and bioinformatic pipelines are sufficiently detailed so it is rather easy to follow what they've precisely done, something which is alas not that frequent in comparable studies.

Strengths:

The structural part of their study is really very convincing, with results showing that despite very small differences, the population structures of the two species conform quite well with what could be inferred from larval dispersal modeled according to passive particle drift. The parallelism is striking, despite minute differences, and despite quite different population sizes for the two species.

Weaknesses:

After that, the authors tried to identify a set of outlier loci whose distribution doesn't conform to the main population differentiation. This search for outliers is made according to classical methods based on Fst or its derivates, like the program PBS which compares the Fst values in trios on sliding windows along the genome. The study is well conducted, namely taking into account false positives and false discovery rates in a conservative manner.

Assuming that some environmental variables differ between the five locations where they have samples, the authors hypothesized from this that similar environmental pressures give similar patterns, potentially affecting pro parte similar places in the genome of the two species. However, there is a blind spot in their analysis inasmuch as it seems that recombination and linkage are not taken into account. It is well known that recombination rates are very variable along the chromosomes, going from recombination hot spots to stretches of very low levels of crossovers. It is well known as well that a variety of phenomena like background, purifying, and sweep selection are quite sensitive to the recombination rates, this having important bearings on local variation of a series of variables like Fst, D, Pi... . Hence, their conclusions about a direct action of environmental pressures may largely be challenged, especially when it is to look for functionality of tightly linked genes, and should be taken as the last hypothesis to be retained when the others can be ruled out.

There are probably sufficient levels of conservation and synteny in teleost fish and a sufficient number of species where recombination maps exist so that the authors can reconstruct a map for their species, at least partially, permitting to use methods explicitly taking recombination rate variation along the genome into consideration (like for instance DILS: Demographic inferences with linked selection 2021 Mol Ecol Res) to challenge their adaptationist conclusions, all the more given the fact that the question of the eventual nature of differential environmental pressures cannot be addressed with extant data.

(3) Moreover, there is now a considerable amount of literature which deals with what is coined "islands of differentiation" or "islands of speciation" or "barriers loci". These genomic segments coincide very often with low recombination regions, and some of them are quite often shared in multiple pairs of closely related species. It seems that their experimental set up (several closely related species) is ideal to easily derive the landscape of genomic architecture of divergence in the genus, this permitting to see where the conserved islands of differentiation stand, how much they are conserved or not in the different species, and how this matches or not with their PBS peaks, and by the way, allowing a more direct comparison with similar landscapes published in other species. They have everything at hand, and this will be a very valuable addition to this article that could hence become a more fascinating paper.

Reviewer #2 (Public review):

Summary:

The authors analyzed genetic population structure of two clingfish species in the eastern Mediterranean Sea. They used a genome-wide DNA sequence dataset representing several populations of both species and found general patterns of isolation that agree with likely patterns of dispersal and described parallel signatures suggesting genomic adaptation. The results support that similar species follow the same evolutionary trajectories when they evolve in the same ecological and geographical context and when meta -populations are subject to the same constraints with respect to dispersal.

Strengths:

The findings as such include a population genetic analysis of taxa for which data are lacking. Conclusions on population subdivision as well as genomic divergence suggestive of genomic adaptation are well supported. The analysis of the genetic data is according to established standards and useful.

Weaknesses:

The idea to apply drift simulations to study dispersal in pelagic fish larvae makes sense; I do however, wonder to what extent the neutral drift scenario applies to the species under study, as an earlier paper by the authors ( J Fish Biol 2020 Nov 3; 98(1): 64-88) emphasizes a strong near-coastal retention of larvae. Accordingly, the drift simulations are in agreement with the observed population structure, but I note that a simpler isolation-by-distance model and dispersal primarily along coastlines would equally agree with the data. A demonstration that drift simulations contribute to a refined model of population subdivision would require a denser sampling of populations and measures of drift between these. Ideally, this should include a demonstration that areas where drift is reduced coincide with genetic discontinuity in the absence of deeper areas of the sea. This is not to say that the approach as such is not interesting, but the conclusions towards this goal are not very well supported by data.

One aspect in the study should be clarified: between-species gene flow is common between closely related species of fish. If this occurs, this would dramatically affect the interpretation of parallelism and convergent evolution at the genomic level. Hybridization should be ruled out or discussed. The two focal taxa are not sister taxa according to a phylogenetic tree (Figure 6) based on only a few genetic loci. Even if a more complete dataset is missing for most relevant taxa to recalculate this phylogeny, I would like to see an assessment of the degree of separation between the two taxa at a genome-wide level. The authors mention that the genetic variants that are subject to parallel evolution are not identical. This is promising and should be highlighted more in case hybridization is likely.

Reviewer #3 (Public review):

Summary:

This manuscript asks whether biogeographic patterns are similarly predictable across temporal scales in two sympatric clingfishes (Gouania). By integrating oceanographic dispersal simulations, population genomics, mtDNA, and demographic inference, the authors find broadly concordant contemporary connectivity between species but less consistent deeper phylogeographic and demographic histories. The study addresses an interesting question, although several aspects of the genomic analyses and their interpretation need further attention.

Strengths:

The manuscript has a strong comparative design and an interesting biological system. Comparing sympatric species provides a useful framework for asking how consistently shared environmental processes translate into similar evolutionary patterns. The integration of oceanographic, population-genomic, phylogeographic, and demographic evidence across temporal scales is a particular strength. The most convincing result is that contemporary connectivity appears more predictable across species than deeper phylogeographic and demographic history.

Weaknesses:

The main new dataset is whole-genome resequencing of 85 individuals (46 G. orientalis, 39 G. hofrichteri) from five localities on Crete and Kythira. These reads were mapped to the chromosome-level Gouania willdenowi assembly (fGouWil2; publicly labeled as G. willdenowi but referred to throughout as the G. adriatica reference) produced by the Vertebrate Genomes Project (Rhie et al. 2021). No new reference genome was generated here, which limits the genomic contribution. Ideally, each focal species would have its own reference.

Mapping both species to a third congener also creates an important reference-bias issue. Figure 6a places G. orientalis closer to the reference lineage than G. hofrichteri, so the more distant species is expected to map less well and yield fewer callable sites. That is the direction observed: G. hofrichteri yields nearly half as many called variants (3.17 M vs 5.82 M). This could reflect real diversity, differential mapping, or both. Per-species mapping rates, missingness, and callable-site counts should therefore be reported, and outlier comparisons repeated using sites callable in both species.

Coverage is also low and uneven: 69 individuals were targeted at 5X and 16 at 15X. This is probably adequate for broad population structure, but more problematic for heterozygosity- and frequency-based statistics, as hard calls at ~5X can bias heterozygosity, nucleotide diversity, FIS, and nearly fixed variants. The single 15X G. orientalis from NNE-Mades, which has unusually high diversity and affects FST, illustrates the issue. Key results should therefore be checked using genotype likelihoods, common-depth downsampling, or the higher-coverage subset. Table S1 should also report realized depth and missingness and clarify the discrepancy with the Methods, which state that two individuals per population were sequenced at 15X. Agreement among PCA, admixture, and FST is not independent reassurance because all use the same hard-called genotype matrix (see Lou et al. 2021; Helmkampf et al. 2025).

Much of the remaining dataset comes from previous studies or public resources: the COI sequences, four of five MSMC2 genomes, the VGP genome, and Copernicus currents. Thus, the main new contribution is the Crete-Kythira population-genomic dataset. The strongest result is that contemporary connectivity is broadly concordant between species, whereas deeper phylogeographic and demographic histories are less predictable. The geographic mismatch among datasets, however, limits direct comparisons across scales.

The least secure result is parallel genomic divergence, which is emphasized in the title. The null model for parallel divergence is problematic. The enrichment test treats 29,039 windows as independent even though 60-kb windows overlap by 30 kb. Adjacent windows are therefore not independent, and both species also share the same reference architecture. The significance of 8 shared windows among 397 and 220 outliers may consequently be inflated. This should be tested with a null model that preserves genomic autocorrelation, such as non-overlapping blocks or permutations of larger genomic segments. Otherwise, the parallelism claim should be softened, particularly in the title.

The gene-level analysis raises the same concern and also contains several inconsistencies. The background is 23,789 genes in the Methods, but 21,274 in Table S3; the Methods specify {plus minus}30 kb around window midpoints whereas Table S6 appears to use 120 kb; and the nearly fixed-variant analysis uses 45 and 8 genes in the Methods versus 52 and 14 in the Results/Table S3. These numbers need to be reconciled. I would also avoid placing much weight on a single shared tuba gene without an appropriate null model.

The MSMC2 analysis uses one diploid genome per species but is interpreted as species-level demographic history. Because these genomes come from different localities and the manuscript itself shows substantial within-species structure, species and locality are confounded. These results should be framed as exploratory histories of the sampled genomes/populations unless additional individuals are analyzed.

The link between oceanography and genomic connectivity is also mainly visual. Because this is a central aim, it should be tested quantitatively, for example by comparing a Lagrangian connectivity matrix with genetic distance while accounting for geographic distance. Similarly, the correlation between pairwise FST values across species should use a matrix-based permutation test rather than a standard Spearman p-value based on 10 non-independent comparisons. The Methods explicitly state that correlations between oceanography and population structure are tested, but no such analysis is reported.

A few additional points need attention. The NNE-Mades G. orientalis is excluded from some analyses but retained in others despite strongly affecting results. The particle-drift model assumes passive 2D advection and omits larval behavior and vertical movement, which should be stated. Mitochondrial-nuclear discordance could also reflect stochasticity, introgression, or sex-biased dispersal. Finally, several inconsistencies need correction, including duplicate Figure S6/missing S7, four versus five populations in the Figure 2 caption, the ENA accession range, and several typos.

Reviewer #1 (Public review):

Summary:

In this paper, the authors combine a well-controlled decision-making task with a secondary probe task in order to understand how covert attention is shaped and how it influences the ongoing decision process. The authors report that the likelihood of overtly attending an alternative is shaped both by its decision relevance and its decision value. Further, covert attentional allocation comes at the expense of overt attentional allocation and attenuates the impact that covert gazes have on choice. Importantly, covert attentional allocation is dissociable from pre-saccadic activity. This paper sheds new light on the role of covert attention in decision-making. From an experimental aspect, the authors make excellent use of behavioural and process-tracing methods, presenting an exemplary paradigm that could be valuable to researchers working in related fields.

Strengths:

(1) The paper utilises a very rich and clever experimental design, which allows for probing covert attention at the level of a single trial. Extending the paradigm to ternary choices was an excellent addition. The decision task is also well-controlled. Overall, the results are very clearly presented, and the paper is very well written.

(2) The paper addresses important yet overlooked questions in decision neuroscience: what influences covert attention during decision-making and what is the functional relevance of covert attentional shifts. It is impressive that the authors are able to tackle these questions using behavioural and eye-tracking data alone.

(3) The authors thoroughly check that the secondary probe task can indeed be used as a proxy for covert attention. Checking that covert attentional allocation is dissociable from pre-saccadic activity was an excellent control.

Weaknesses:

(1) It is not clear why the decision task is described as "value-guided" instead of "perceptual". Participants receive momentary reward on the basis of their overall accuracy, but this is common practice in perceptual tasks. A value-based analogue of this task would provide trial-by-trial reward as a function of the perceptual magnitude (decision value) of the chosen stimulus. On a related note, the secondary task was not incentivised. The authors should further justify this choice.

(2) The authors do a great job in describing the determinants of covert attention. However, the relevant analyses are rather "phenomenological". It would be useful to try and dig further into the data in order to understand at a deeper, causal level these determinants. I suggest doing so by utilising in full the rich behavioural and overt attention data this paradigm offers. Specifically, the authors show that the higher the value of an alternative, the higher the likelihood this alternative is covertly attended. Decision values, however, could impact aspects of saccadic behaviour that directly influence covert attentional allocation (saccadic speed, dwell times, locus of gaze). At a more global level, decision value and/ or value difference could affect sampling behaviour (frequency of switching) or decision times, which can manifest in probe accuracy. Overall: a) overt sampling behaviour is at present reduced to the presence of saccades; but saccadic behaviour could be decomposed into richer metrics, b) although the task is "free-response", decision times are not analysed. Metrics based on a) and b) could be tested as mediating factors, enabling the authors to better understand the causal determinants of covert attention.

(3) The authors claim that covert attention attenuates: a) the impact of the last fixation on choice, b) the "time advantage" of the alternative that was overtly attended for longer. To further qualify these claims as functional/causal, further analyses are required. A few suggestions follow below. On trials where the "unattended" probe letter was successfully reported, the last fixation may exhibit different characteristics, which could explain away its reduced impact. For example, it may differ in duration, or it might correspond to a "switching" (rather than "staying" on the same alternative) saccade. These potential covariates need to be further examined. Additionally, correctly reporting unattended probes could come at the expense of decision accuracy due to dual task demands. If that is the case, then the reported attenuation of the impact of the last fixation could just be due to noisier responses. Similar points can be raised about the "time advantage", especially given that decision times do not feature in any of the analyses. More difficult decisions may lead to higher probe accuracy but also to prolonged decision times. The authors quantify the "time advantage" using cumulative fixation time, but perhaps relative metrics (e.g., relative fixation time or cumulative fixation time normalised by decision time) are better suited for this analysis.

Reviewer #2 (Public review):

Summary:

The authors combine a value-based choice task with a gaze-contingent covert attention paradigm to investigate how covert attention relates to value-guided decisions. This is an important and timely question, as many models of decision-making implicitly equate gaze with attention despite extensive evidence that covert attention can be dissociated from eye position. I particularly appreciated the relatively naturalistic task design, which allows participants to freely explore the options while covert attention is sampled during the decision process. Overall, the manuscript is well written, the experiments are carefully executed, and the analyses are generally appropriate and clearly presented.

My main reservation concerns the strength of some conceptual claims. The data convincingly demonstrate that covert attention can be decoupled from gaze and that probe report is modulated by option value. However, I found the evidence less directly supportive of the stronger conclusions that covert attention dynamically competes with overt attention throughout the decision process and that covert attention itself causally influences subsequent choice. Many of the reported analyses are consistent with these interpretations but, in my view, do not uniquely support them.

Strengths:

The manuscript addresses an important and timely question at the intersection of visual attention and value-based decision making. The experimental paradigm is elegant and relatively naturalistic, allowing covert attention to be sampled during ongoing decision making while participants freely explore the choice display. The experiments are carefully executed, and the analyses clearly demonstrate that covert attention can be dissociated from gaze and is systematically modulated by option value. The control analyses addressing the contribution of presaccadic attention are an important addition that substantially strengthens the manuscript, even though I had questions regarding their interpretation.

Weaknesses:

(1) Interpreting the causal role of covert attention in guiding choice

The manuscript puts forward two central conclusions: first, that covert attention is shaped by decision-relevant factors such as option value; and second, that covert attention, in turn, influences subsequent choice behavior. I found the evidence for the first conclusion compelling. My reservations concern the second conclusion, namely whether the current data uniquely establish a causal influence of covert attention on choice. Throughout the manuscript, the authors conclude that covert attention exerts "downstream consequences for choice behavior" and that an estimate of covert attention "influences the final choice." However, I am not sure that the presented analyses fully disentangle a causal influence of covert attention from a common influence of option value on both covert attention and the eventual decision.

One aspect that illustrates this concern is the interpretation of the last-fixation bias. While the reported association between the final fixation and the chosen option is clear, it is less obvious that the final fixation itself biases the subsequent choice. An equally plausible interpretation is that participants have largely committed to a decision and subsequently direct one final gaze shift toward the option they have already selected before executing the button press. In other words, the relationship may reflect choice influencing gaze rather than gaze influencing choice. Unless the temporal dynamics allow these alternatives to be distinguished, I would encourage the authors to use more neutral language (e.g., an association between last fixation and subsequent choice) or explicitly discuss this alternative interpretation.

More generally, I found myself looking for a more direct demonstration that covert attention biases choice toward the attended option. Most analyses ask whether successful peripheral probe report attenuates established gaze-related choice biases, such as the last-fixation or time-advantage bias. While these are interesting findings, they remain relatively indirect. A particularly compelling demonstration would be to examine situations in which option value cannot explain the relationship between covert attention and choice.

(2) Dynamic competition between covert attention and overt attention

I think one of the key strengths of this manuscript is its explicit attempt to dissociate covert attention from gaze-a distinction that is often overlooked in both empirical studies and computational models of value-based decision making. My reservation concerns the stronger claim that covert attention is dynamically reallocated during decision making and competes with overt attention. The present results clearly show that covert attention can be dissociated from gaze, but I found less direct evidence for the proposed dynamic competition. Throughout the experiments, probe report accuracy remains highest at the currently fixated option, whereas peripheral benefits, although reliable, are comparatively modest (e.g., Figures 2 and 3). This raises the question of how often, and under which circumstances, covert attention is actually reallocated away from the current fixation.

Because the authors possess precise eye-movement timing, I think the manuscript would be substantially strengthened by an analysis of attentional dynamics within individual fixations, to provide more direct support for the proposed dynamic interplay between covert and overt attention.

More generally, I found several interpretations somewhat stronger than the presented evidence. For example, the statement that increased covert attention to higher-valued peripheral options occurs "at the expense of" overt attention at the fixated location seems to imply a direct trade-off that is not explicitly demonstrated. Unless such temporal dynamics can be shown, I would encourage the authors to distinguish more clearly between demonstrating that covert attention can be dissociated from gaze and demonstrating that it dynamically competes with overt attention throughout the decision process.

(3) Dissociating covert from presaccadic attention

The control analyses aimed at dissociating covert from presaccadic attention are an important strength of the manuscript. However, I found the rationale underlying these analyses difficult to follow. The key conclusion-that value modulates probe report even when covert attention is not presaccadic-rests on the distinction illustrated in Figure 6, yet it remained unclear to me exactly how this distinction isolates presaccadic from non-presaccadic covert attention. My understanding is that the authors compare probe performance at previously fixated locations depending on whether those locations are subsequently re-fixated. If this interpretation is correct, a more explicit explanation of why this operationalization isolates presaccadic attention would help readers evaluate this conclusion. Conceptually, I found it more intuitive to think about a dissociation based on probe performance at locations that are subsequently fixated versus not subsequently fixated following the first fixation, when the currently fixated option, the upcoming saccade target, and a third unfixated option are distinct. Such situations would seem to provide the clearest opportunity to separate attentional enhancement associated with the upcoming saccade target from covert attention directed elsewhere.

I also found the interpretation of the time-to-saccade control stronger than the evidence directly supports. The authors argue that a purely presaccadic account predicts a monotonic decline in probe accuracy as a function of time-to-saccade. This assumption seems stronger than supported by the presaccadic attention literature, which primarily characterizes attentional enhancement during approximately the final 100-200 ms before saccade onset. Within this temporal window, the present data actually appear consistent with such an increase (Figure S6). By contrast, I am not aware of theoretical or empirical work predicting a monotonic presaccadic attentional shift extending hundreds of milliseconds, or even a second, before saccade onset.

The observed U-shaped relationship is nevertheless inconsistent with a simple presaccadic-only account, as probe performance remains elevated even when the upcoming saccade is relatively distant. I therefore agree that the findings suggest additional attentional processes. However, I do not think they uniquely establish that probe performance indexes covert attention independently of presaccadic planning.

Reviewer #1 (Public review):

Summary:

The authors introduce ordinal EPR (Dsym) as a novel metric for characterizing tFUS-evoked calcium responses. The concept is interesting and could offer an innovative way of looking at neural responses to neuromodulation more broadly. Their main result, that EPR carries information beyond mean GCaMP amplitude, is compelling, but the manuscript would be strengthened by testing whether it holds against other conventional GCaMP metrics beyond mean amplitude (e.g. decay time). More importantly, the EPR metric requires further validation before its central claim, that it reflects genuine dynamical reorganization of the underlying circuit rather than artifacts of the measurement pipeline (e.g. GCaMP indicator kinetics), can be accepted. A rigorous surrogate/synthetic signal validation would be a very valuable, if not essential, addition to this paper.

Strengths:

This manuscript frames tFUS-evoked activity in a way that is uncommon in the field. Moving beyond amplitude-based readouts to ask how sonication reshapes the temporal organization of neural activity is a novel contribution to the ultrasound neuromodulation literature. The finding that EPR shows a distinct dose-response profile from calcium amplitude and retains dose-related structure after controlling for amplitude, is a promising demonstration that this framework can extract information not visible to conventional measures.

Methods are very detailed and well explained for reproducibility purposes.

Weaknesses:

Major weaknesses:

EPR may carry information beyond mean GCaMP amplitude- but is it carrying information beyond other elements of the GCaMP signal? For the on-target recovery window, the calcium signal has not yet returned to baseline (original data traces, Fig. 2C, Fig. 4A), so the trace still contains a residual decay transient at the time Dsym is computed. This decay rate reflects neuronal activity returning to baseline and will be dependent on things such as calcium indicator kinetics. Would a change in Dsym always accompany this kind of decay, regardless of whether this has anything to do with endogenous dynamics, irreversibility etc.? Would any gradual return to baseline/decay of this kind produce elevated Dsym on its own, independent of underlying stochastic fluctuations/endogenous dynamics? Is it not expected that a system that is not at steady state shows entropy production? Perhaps the decay rate is simply different by dose, which explains the findings? Could this be tested i.e. with synthetic data or by removing the decay? The fact that a change in EPR is measured when there is no significant GCaMP change indicates that the measure is not purely dominated by decay kinetics but it is not clear whether decay kinetics etc. could be confounding this result.

GCaMP's rise and decay kinetics are asymmetric (fast rise, slow decay). Since Dsym is a measure of asymmetry between forward and time-reversed ordinal statistics, could this kinetic asymmetry alone have any impact on "irreversibility", independent of underlying neural dynamics? Could this be tested with synthetic data? The authors note that the GCaMP signal is filtered through an indicator with slow kinetics but don't mention the asymmetry.

When different stimulation periods are used, what impact if any, does this have on computation of the EPR metric?

What impact does having a noisier/lower SNR calcium signal have on the EPR metric, if any?

Minor weaknesses:

The major advantage of TUS as a non-invasive brain stimulation technique is its capacity for spatially focused deep brain stimulation. However, it carries a significant auditory confound, which leads to activation of widespread (not spatially restricted) neuronal networks (Kop et al., 2024; Sato et al., 2018). The data used in this paper does not adequately control for this confound (i.e. deafened animals (Guo et al., 2023; Sato et al., 2018). Whilst this is not the responsibility of the authors of this manuscript, it should be mentioned in the discussion that any of the tFUS-calcium evoked responses could be due to indirect auditory stimulation rather than a direct pressure-mediated effect. The authors may just be measuring EPR in response to the auditory confound, which does not undermine the overall impact of this paper (as it is more focused on an approach to looking at this kind of data), but should be mentioned. I do think that presence of the auditory confound could impact interpretability of the results in the manuscript. Could the authors comment on this? Could auditory mediated arousal or state shift (perhaps activating brain regions not captured by the fiber) explain any of the presented EPR results or affect interpretation?

Guo, H., Salahshoor, H., Wu, D., Yoo, S., Sato, T., Tsao, D. Y., & Shapiro, M. G. (2023). Effects of focused ultrasound in a "clean" mouse model of ultrasonic neuromodulation. iScience, 26(12). https://doi.org/10.1016/j.isci.2023.108372<br /> Kop, B. R., Shamli Oghli, Y., Grippe, T. C., Nandi, T., Lefkes, J., Meijer, S. W., Farboud, S., Engels, M., Hamani, M., Null, M., Radetz, A., Hassan, U., Darmani, G., Chetverikov, A., den Ouden, H. E., Bergmann, T. O., Chen, R., & Verhagen, L. (2024). Auditory confounds can drive online effects of transcranial ultrasonic stimulation in humans. eLife, 12, RP88762. https://doi.org/10.7554/eLife.88762<br /> Sato, T., Shapiro, M. G., & Tsao, D. Y. (2018). Ultrasonic Neuromodulation Causes Widespread Cortical Activation via an Indirect Auditory Mechanism. Neuron, 98(5), 1031-1041.e5. https://doi.org/10.1016/j.neuron.2018.05.009

Reviewer #2 (Public review):

Summary:

The present paper studies the entropy production rate (EPR) before, during, and after thalamic sonication in freely moving mice from a previously published dataset. The motivation is that EPR contains information about the dynamics of neural activity that is not present in the average calcium amplitude. It was observed that the change in EPR reaches a maximum at an intermediate stimulation dosage, in contrast to the change in overall calcium amplitude, which increases monotonically with dose in the on-target condition. The paper further observes a statistically significant relation between the baseline EPR and the change in EPR during stimulation, but not for recovery, as well as a similar relation for the calcium response. The manuscript draws an analogy between the non-monotonic dependence and stochastic resonance.

Overall, these results present an interesting analysis of how acoustic stimulation affects the dynamics of neural activity. In my view, these tools would be quite useful for quantifying changes in neural activity under different perturbations.

Strength:

The study is well motivated by the argument that quantifying neural response requires information about dynamics that is not contained in the average calcium amplitude. EPR or irreversibility has been shown to be a powerful tool in describing out-of-equilibrium biological processes. The paper successfully quantifies irreversibility using an ordinal surrogate of the entropy production rate. The non-monotonic dependence is an interesting result, which demonstrates (with caveats stated in Weakness) that EPR contains more information about neural response than the average calcium amplitude. Furthermore, the paper also clearly states limitations of the approach and performs a robustness check by varying the parameters used in the ordinal EPR estimation.

Weakness:

(1) My main concern, as the authors have touched upon in the Discussion, is that although irreversibility clearly provides a readout of the neuronal dynamics, it remains unclear what its biological significance is. While it is related to susceptibility, the mechanistic link remains weak. I suspect that this interpretability issue will limit the impact of this approach.

(2) I wonder how the measured irreversibility is affected by the asymmetric response of GCaMP, which typically rises quickly and decays slowly. It seems possible that this temporal asymmetry, combined with the average calcium response, already leads to a non-monotonic irreversibility curve. The paper should investigate this and other potential contributors to the temporal irreversibility in the readout.

(3) As shown in Fig. 2AB, the baseline EPR already varies considerably with acoustic intensity, by an amount comparable to the change in EPR after stimulation (Fig. 2E). Since the baseline window precedes stimulation, this variation cannot be caused by the sonication. It suggests either that the uncertainty in EPR quantification is larger than the error bars indicate, or that trials at different nominal intensities differ systematically in some other respect. It should be examined whether the non-monotonic trend is statistically significant in light of this baseline fluctuation.

Reviewer #1 (Public review):

Summary:

The manuscript describes a novel mechanism underlying the formation of secondary lesions following treatment-induced injury. Comprehensive analyses were conducted, including bioinformatics, cell culture, and xenograft models, to investigate the role of IL1b/IRAK4 in ovarian cancer. A novel IRAK4 antagonist was designed and tested in these models, demonstrating its effectiveness in reducing metastatic seeding and tumor growth at injury sites.

Strengths:

Mechanistic role of IRAK4 and its small molecule antagonist was demonstrated using several murine and human ovarian cancer cell lines.

Properties of the novel investigational compound UR241-2 were comprehensively assessed.

The data show the effectiveness of UR241-2 in reducing metastatic seeding after injury.

Weaknesses:

An expanded description of the histological types of ovarian cancer used to generate survival curves and demonstration of the expression of total IRAK4 would strengthen the manuscript.

If the information is available, it could be useful to indicate the percentages of different ovarian cancer histotypes analyzed in Figure 1.

Providing panels demonstrating the expression of total IRAK4 in Figure 4 would be informative.

Reviewer #2 (Public review):

This manuscript presents a broad and potentially impactful investigation of inflammation-associated ovarian cancer implantation and identifies IRAK4 as a candidate therapeutic node linking inflammatory signaling to tumor seeding. Major strengths include development of an injury-associated metastasis model, complementary genetic and pharmacological interrogation of IRAK4, extensive characterization of the novel inhibitor UR241-2, and incorporation of both xenograft and immunocompetent models. The observation that genetic or pharmacological disruption of the IL1R1/IRAK4 pathway preferentially affects tumor formation at injured sites rather than generalized omental disease is particularly interesting and potentially novel. However, several conclusions currently exceed the mechanistic evidence. Most importantly, the manuscript does not conclusively demonstrate that the antitumor effects of UR241-2 are mediated through IRAK4, particularly given the concentration differences between pathway inhibition and antiproliferative activity and the compound's measurable off-target kinase activity. In addition, host versus tumor-intrinsic IRAK4 functions are not resolved, the functional contribution of the altered macrophage/neutrophil populations remains unproven, and the needle-injury model should be described more cautiously as a model relevant to rather than fully recapitulating port-site metastasis. Addressing these issues would substantially strengthen the mechanistic foundation and translational significance of the work. The manuscript has potential, particularly if the authors sharpen the central claim and add experiments establishing that UR241-2's phenotypes are actually IRAK4-dependent.

Major concerns:

(1) UR241-2 decreases tumors at the injury site but apparently does not significantly decrease omental tumor burden in the syngeneic MiM model. It argues against simple nonspecific antitumor activity and supports a possible role for IRAK4 specifically within an inflammation/injury-dependent metastatic niche. The authors should make much more of this distinction-but also mechanistically prove it.

(2) The manuscript does not yet establish that UR241-2's antitumor effects are mediated primarily through IRAK4. The compound has measurable activity against additional kinases, including MAP4K2 and LRRK2, and activity against other kinases is reported at higher concentrations. More importantly, there appears to be a substantial concentration disconnect across assays. IRAK4 phosphorylation is inhibited at nanomolar concentrations in some experiments, whereas colony formation/viability phenotypes occur largely in the micromolar range. For example, colony effects are reported at 5-20 µM and viability experiments at 20-60 µM. Thus, are the antiproliferative effects observed at 10-60 µM actually caused by IRAK4 inhibition? The manuscript needs a stronger pharmacological/genetic causality experiment. Ideally, the authors should test UR241-2 in IRAK4-knockdown/knockout cells. If UR241-2 retains essentially identical cytotoxic activity after IRAK4 loss, the mechanistic interpretation would need substantial revision. A rescue experiment with WT versus inhibitor-resistant IRAK4 would be even stronger.

(3) The distinction between host IRAK4 and tumor-cell IRAK4 is insufficiently resolved. The Il1r1 experiments manipulate the host, whereas IRAK4 knockdown manipulates the tumor cell. UR241-2, meanwhile, presumably inhibits IRAK4 in both compartments. Consequently, the current experiments combine at least two mechanistically distinct possibilities: tumor-intrinsic IRAK4 versus host IRAK4. The manuscript would be considerably stronger if these compartments were experimentally separated. For example, IRAK4-deficient tumor cells implanted into WT versus pathway-deficient hosts, or pharmacological treatment of mice bearing IRAK4-deficient tumor cells, could determine how much of UR241-2 efficacy is tumor-intrinsic versus microenvironment-mediated.

(4) The immune conclusions are presently associative. The increase in MHC-II-positive macrophages and neutrophils is interesting, but describing these populations as demonstrating an "antitumor immune response" is stronger than the evidence warrants. MHC-II expression does not itself demonstrate antitumor function. Likewise, neutrophils in ovarian cancer can be either tumor-promoting or tumor-suppressive depending on context. The authors show that UR241-2 changes immune composition/phenotype. They do not yet demonstrate that these cells mediate the therapeutic effect. This could be addressed by macrophage or neutrophil depletion, functional assays, cytokine profiling, T-cell activation measurements, or potentially single-cell profiling.

(5) The drug-development claims are somewhat premature<br /> The ADMET package is useful, but several features deserve more cautious interpretation. The compound shows: very high plasma protein binding, rapid mouse microsomal turnover, evidence of efflux, relatively rapid IV clearance, and measurable off-target kinase activity. The authors report mouse microsomal half-life of only ~8.7 min compared with ~209 min in human microsomes and an efflux ratio of ~4.14. These are not fatal problems for a proof-of-concept molecule, but they make language implying a near-clinical candidate premature. UR241-2 currently looks more convincing as a lead/tool compound demonstrating therapeutic tractability of IRAK4 than as an advanced drug candidate.

(6) Exposure-response relationships need considerably more attention. Analysis of IRAK4 and/or NF-κB pathway in the treated tumors should be examined

(7) Some mechanistic observations need deeper validation. The connections among IRAK4, adhesion, E-cadherin, WNT4 and ECM remodeling are intriguing but currently somewhat descriptive. At present, several pieces of this pathway appear adjacent rather than causally connected.

Reviewer #1 (Public review):

The authors attempted to compare calcium binding properties of wildtype calreticulin with calreticulin deletion mutant (CRTDel52) associated with myeloproliferative neoplasms.

The researchers conducted their study using advanced techniques They found almost no difference in calcium binding between the two proteins and observed no impact on calcium signaling, specifically store-operated calcium entry (SOCE). The study also noted an increase in ER luminal calcium-binding chaperone proteins. Surprisingly, the authors selected flow cytometry as a technique for measurements of ER luminal calcium. Considering limitations of this approach it would be better to use alternative approaches. This is particularly important as previous reports, using cells from MPN patients, indicate reduced ER luminal calcium and effects on SOCE (Blood, 2020). This issue matters because earlier research with MPN patient cells reported reduced ER luminal calcium levels and altered SOCE (Blood, 2020). How do the authors explain the difference between their results and previous findings about lower ER luminal calcium and changed SOCE in MPN patient cells expressing CRTDel52? Other studies have found that unfolded protein responses are activated in MPN cells with CRTDel52 calreticulin (see Blood, 2021), and increased UPR could account for higher levels of some ER resident calcium-binding proteins observed here. Overall, it remains unclear how this work improves our understanding of MPN or clarifies calreticulin's role in MPN pathophysiology.

Comments on revised version.

The authors have addressed the points raised in the original review. However, given the absence of significant differences between the wild-type and mutant proteins, the relevance of this work to MPN pathology remains unclear. The novelty of the study is limited, as calcium has generally not been considered a significant factor in MPN pathology associated with mutant calreticulin.

Reviewer #2 (Public review):

Summary:

Tagoe and colleagues present a thorough analysis of the calcium (Ca2+) binding capacity of calreticulin (CRT), an endoplasmic reticulum (ER) Ca2+-buffer protein, using a mutant version (CRT del52) found in myeloproliferative neoplasms (MPNs). The authors use purified human CRT protein variants, CRT-KO cell lines, and an MPN cell line to elucidate the differing Ca2+ dynamics, both on the level of the protein and on cell-wide Ca2+-governed processes. In sum, the authors provide new insights into CRT that can be applied to both normal and malignant cell biology.

First the authors purify CRT protein and perform isothermal titration calorimetry to quantify the Ca2+ binding capacity of CRT. They use full-length human CRT, CRT del52, and two truncations of CRT (1-339 and 1-351, the former of which should lead to the entire loss of low affinity Ca2+ binding). While CRT del52 has previously been shown to lead to a decrease in Ca2+ binding affinity in other models, the ITC data shows that this is retained in CRT del52.

Next, the authors utilize a CRT-KO cell line with subsequent addition of CRT protein variants to validate these findings with flow cytometric analysis. Cells were transfected with a ratiometric ER Ca2+ probe, and fluorescence indicates that CRT del52 is unable to restore basal ER Ca2+ levels to the same extent as CRT wild-type. To translate these findings to MPNs, the authors perform CRT-KO in a megakaryocytic cell line, where reconstitution with either CRT variant did not cause a difference in cytosolic calcium levels. The authors further test store-operated calcium entry (SOCE), an important process to maintaining ER Ca2+ levels, in these cells, and find that CRT-KO cells have lower SOCE activity, and that this can be slightly recovered with CRT addition.

Finally, the authors ask whether other effects of CRT-KO/reconstitution can affect cellular Ca2+ signaling pathway and levels. RNASeq analysis revealed showed that CRT-KO lead to an increase in various chaperone protein expressions, and that reconstitution with CRT del52 is unable to reduce expression to the same extent as reconstitution with CRT wildtype.

Comments on revised version.

The authors have sufficiently addressed my concerns from the first review.

Reviewer #1 (Public review):

Summary:

This study quantifies the ability of the four isoforms of the calcium-release calcium-activated (CRAC) channel Orai to mediate calcium entry and transcriptional responses. By genetically invalidating each isoform and by separately re-expressing them in Orai-deficient human embryonic kidney cells, the authors show that the rates of calcium entry across the four native Orai calcium channel isoforms (Orai1α/β, Orai2, Orai3) correlate with the degree of NFAT activation. They further show that the two alternatively translated isoforms Orai1α and Orai1β are interchangeable, as their expression in Orai1-deficient primary mouse T cells induces identical cytokine responses and transcriptional programmes, and that individuals bearing frameshift mutations causing a loss of the Orai1α isoform do not exhibit immune, muscular, or dermatologic features and have preserved T cells' Ca2+ and transcriptional responses.

Strengths:

The data are of high quality, relying on clean cell line and mouse knockout models to link calcium entry rates directly to NFAT activation, and human data from homozygous and heterozygous frameshift mutation carriers confirm that Orai1α and Orai1β are functionally redundant in vivo.

Weaknesses:

An acknowledged limitation is that some conclusions depend on transient overexpression experiments. The authors should explicitly address whether Orai1α could possess non-redundant functions under unique physiological environments not captured by these assays.

Reviewer #2 (Public review):

Summary:

The authors aim to assess the differential role of Orai isoforms for mediating SOCE and NFAT1 and/or NFAT4 nuclear translocation primarily in the context of T cells. For this purpose, they have used genetically modified cells and appropriate human genetic conditions. All isoforms were expressed individually (with deletions of other isoforms) at roughly equivalent levels so that data across isoforms could be compared unambiguously. Their experiments convincingly identify Orai1 as the main driver of SOCE and NFAT1/4 translocation in the HEK293 cell line and in primary T cells. The two Orai1 isoforms appear functionally equivalent, and loss of the longer isoform (Orai1α) is compensated in humans by the presence of the shorter isoform (Orai1β).

Strengths:

Overall, their judicious use of appropriate knockouts, mutants and expression constructs allows for unambiguous interpretation of data regarding the key role of Orai1α and Orai1β in T cell physiology. They also demonstrate a role for Orai3 in driving SOCE in a breast cancer cell line.

Weaknesses:

The main shortcoming of this manuscript is its inability to place the findings in a context that would be of interest to a broader audience. It would be helpful to provide a metanalysis from existing public databases (human and/or murine) of the known expression in various cell types and tissues of Orai1α, Orai1β, Orai2 and Orai3. This could suggest possible roles for each Orai isoform in tissues other than immune cells. Further, the physiological relevance of the two NFAT isoforms studied, NFAT1 and NFAT4, needs some elaboration, both in the context of T cells and other tissues.

Reviewer #3 (Public review):

Summary:

The work by Abdelnaby et al. investigated the different Orai isoforms, and also especially Orai1 alpha and beta for NFAT 1 and NFAT 4 translocation, but also its impact in genetically modified T-cells. This is a very well-performed work that manages to monitor NFAT nuclear/cytosol ratio even in a time-dependent manner. Overall, this study has been very well performed, is clearly written and discusses the literature very accurately.

Strengths:

For monitoring NFAT translocation, the authors have managed to observe this pattern even in a time-dependent manner. The authors may like to describe how this analysis was done with more details, as I believe some software assistance was needed to distinguish the nuclear to cytosolic region for a huge number of cells. Clearly, this analysis provides a very clear picture of the time course of translocation and allows for a precise statistical analysis.

Remarkably, NFAT1 and NFAT4 translocation was not substantially different for Orai1 alpha- and Orai1 beta-mediated Ca2+ signals. This has also been observed previously by Zhang et al. for NFAT1 from the same laboratory. Clearly, this is in contrast to the work of reference 38 (Kar et al.). All these publications have been performed with a huge amount of data, and I believe that clearly stating this difference in results from previous work is an additional important aspect of this manuscript.

In line with the similar NFAT translocation efficiency of Orai1 alpha- or beta-containing cells, the authors carefully evaluated differentially expressed genes in CD4+ T cells. They did not find a substantial difference in these cells that were transduced with Orai1 alpha or beta - clear orthogonal evidence for a conserved function of Orai1 alpha and beta for transcriptional activation.

Weaknesses:

This reviewer identified no obvious weaknesses in this work.

Reviewer #4 (Public review):

Summary

Orai1, Orai2 and Orai3 are the pore-forming subunits of CRAC channels, and Orai1 itself exists as two N-terminally distinct translational isoforms, Orai1α and Orai1β. Despite well-documented differences in the biophysical properties of these four proteins (Ca²⁺-dependent inactivation, expression pattern, evolutionary conservation), it has been unclear whether these differences translate into distinct transcriptional outputs through the Ca²⁺-calcineurin-NFAT axis, or whether NFAT responses are simply scaled by the amount of Ca²⁺ that each channel variant lets through. The authors address this using HEK293 cell lines engineered by CRISPR/Cas9 to retain only a single native Orai homologue (OraiDKO lines) or none at all (Orai-TKO, reconstituted at near-native levels with a weak TK promoter), and extend their findings to primary murine CD4⁺ T cells lacking endogenous Orai1, as well as to human primary T cells and population genetic datasets from individuals carrying naturally occurring loss-offunction alleles that selectively eliminate Orai1α while sparing Orai1β. Across these systems, the authors report a consistent rank order of NFAT1/NFAT4 activation (Orai1β {greater than or equal to} Orai1α >> Orai2 > Orai3) that mirrors the rank order of SOCE amplitude, and show that a fast Ca²⁺ chelator (BAPTA) but not a slow one (EGTA) blocks NFAT1 activation, consistent with a requirement for local, channel-proximal Ca²⁺ signals rather than global cytosolic Ca²⁺ elevation. Human individuals homozygous for Orai1αselective null alleles are clinically unaffected and show normal or even enhanced SOCE/NFAT responses, contrasting sharply with the severe CRAC channelopathy phenotype produced by mutations affecting residues shared by both isoforms. Together, the data support a model in which the graded strength of SOCE, rather than isoform-specific coupling machinery, is the principal determinant of NFAT activation and downstream gene expression.

Strengths

The central strength of this study is its genetic strategy. Rather than relying on overexpression of individual Orai/STIM constructs in a background where multiple endogenous Orai paralogues are still present (a common confound in this field), the authors generated HEK293 clones that retain only one native Orai isoform, and separately reconstituted Orai-TKO cells with individual isoforms at nearendogenous expression levels using a weak TK promoter, validated by immunofluorescence and Western blotting. This design substantially reduces the risk that observed differences reflect artifacts of Orai/STIM stoichiometry rather than genuine isoform-intrinsic properties, a concern the authors explicitly raise and address (citing prior work showing that Orai/STIM overexpression itself can alter regulator sensitivity).

The multi-tier validation strategy is unusually thorough for this type of mechanistic question. The same qualitative conclusion, that NFAT activation scales with SOCE magnitude rather than isoform identity, is supported independently by (i) engineered HEK293 lines under both maximal (thapsigargin) and physiological (carbachol) stimulation, (ii) an orthogonal cellular system (MCF7 breast cancer cells natively dominated by Orai3) in which a "weak" channel is shown to support robust NFAT1 activation when sufficiently abundant, (iii) reconstitution of Orai1-deficient primary murine CD4⁺ T cells with matched, near endogenous levels of Orai1α or Orai1β, assessed by SOCE, endogenous NFAT1 localization (ImageStream), cytokine production, and genome-wide RNA-seq, and (iv) human population genetics across four independent cohorts (UK Biobank, gnomAD, Qatar Biobank, All of Us) combined with direct cellular phenotyping of human T cells from individuals with defined Orai1α genotypes. The convergence of cell line, mouse, and human genetic data on a single coherent model considerably strengthens confidence in the conclusions beyond what any single approach could provide.

The chelator experiment (Figure 4) is a clean, well-controlled test of local versus global Ca²⁺ signaling, using the classical BAPTA/EGTA differential kinetic-buffering logic, and the result (BAPTA-sensitive, EGTA-insensitive NFAT1 activation for both isoforms) is internally consistent and clearly presented.

The RNA-seq analysis (Figure 6) is a valuable addition, showing near-identical global transcriptional programs driven by Orai1α and Orai1β (log2 fold-change correlation R ≈ 0.92) and demonstrating that the larger number of nominal differentially expressed genes for Orai1α is attributable to statistical thresholding rather than a qualitatively distinct transcriptional signature. This substantially strengthens the claim that isoform identity has little independent influence on the transcriptional output of SOCE beyond its effect on Ca²⁺ influx magnitude.

Finally, the human genetic component is a genuine strength that elevates the physiological relevance of the paper considerably. Directly testing individuals who are natural "knockouts" for one Orai1 isoform but not the other is a powerful complement to the reductionist cell biology, and the finding that Orai1αnull carriers are clinically well and immunologically not compromised (indeed showing modestly enhanced SOCE/NFAT signaling) provides an unusually direct refutation of a specific published mechanistic model (the AKAP79-Orai1α N-terminus coupling hypothesis).

Weaknesses

Some tension remains between the HEK293/human T cell data, where Orai1β is moderately but consistently more efficient than Orai1α at driving SOCE and NFAT activation, and the murine primary CD4⁺ T cell data, where the two isoforms are functionally indistinguishable. The authors offer a plausible explanation, that retroviral expression levels in T cells were high enough to mask subtle isoform differences, and they partially address this by gating on Amtlow (lower-expressing) cells.

The TK-promoter reconstitution system, while a clear improvement over CMV-driven overexpression and validated as achieving comparable expression across isoforms, still involves ectopic expression in an Orai-null background rather than truly endogenous expression from the native locus. Describing this system as achieving "near-native" levels is reasonable given the Western blot validation shown in the supplement, but readers would benefit from the manuscript being explicit that this is a reconstitution model rather than unperturbed endogenous expression, and from a brief discussion of what residual differences (in, for example, membrane trafficking, promoter-driven transcript stability, or subtle stoichiometric mismatch with STIM) could still confound isoform comparisons.

Physiological cells normally co-express Orai1α and Orai1β at varying ratios (as the authors themselves show in Figure S2 across T helper subsets), and it is not established whether heteromeric Orai1α/Orai1β channels (which have been reported by others to form) behave as a simple functional average of the two homomeric channels or display emergent properties. The current study's conclusions rest entirely on isoform-pure systems, and this leaves open whether the "SOCE magnitude" model generalizes cleanly to the mixed populations of channels present in most native cells.

Several of the human genetic subgroup analyses involve modest sample sizes. The number of homozygous carriers of the two Orai1α-specific truncating variants varies substantially by cohort (for example, only 2 and 0 homozygotes identified in QBB), and the UK Biobank clinical phenotype comparison is based on 24 mutation carriers versus 984 controls. While the overall pattern (absence of enrichment for CRAC channelopathy associated diagnostic codes) is reassuring and consistent across the core infection, ectodermal, and myopathy categories, the confidence intervals in these comparisons are necessarily wide, and the absence of statistically significant differences in a modestly sized cohort should be interpreted as consistent with, rather than definitive proof of, phenotypic equivalence. Likewise, the direct cellular characterization of NFAT translocation and SOCE in human T cells from wild-type, heterozygous, and homozygous Orai1α-null Qatar Genome Project donors (Figure 8) is based on a single individual per genotype, which, although understandable given the rarity of the relevant genotype, limits the ability to distinguish genotype effects from inter-individual variability.

The manuscript proposes that NFAT activation is governed principally by the magnitude of local, channel-proximal Ca²⁺ signals rather than isoform-specific decoding machinery, but does not fully address whether isoform-specific differences in Ca²⁺-dependent inactivation kinetics (which shape the temporal profile, not just the amplitude, of the Ca²⁺ signal) could themselves constitute a form of isoform-specific "coding" that is conceptually distinct from, but difficult to fully disentangle from, simple amplitude scaling. A brief discussion of how the SOCE magnitude and Ca²⁺ signal kinetics/duration are related, and whether they can be cleanly separated in this experimental system, would help readers judge the boundaries of the magnitude-based model.

Reviewer #3 (Public review):

Summary:

Core conclusions are well-supported by data: co-folding outperforms docking in known ligand pose/affinity prediction (validated by RMSD and IC₅₀ correlation), struggles with false positive discrimination in virtual screens (lower AUC values), and is complementary to docking (non-correlated errors, distinct strengths in drug discovery stages).

Strengths:

Unprecedented prospective design with 557 novel Mac1-ligand complexes ensures rigorous, independent evaluation of co-folding methods, provides an unbiased and rigorous benchmark dataset, which contains structures and compounds absent from the co-folding models training sets. Comprehensive comparison of 3 co-folding tools (AlphaFold3, Chai-1, Boltz-2) with DOCK3.7 across diverse targets and metrics enables nuanced performance assessment. The revised results clarify an intriguing finding: co-folding can predict correct ligand poses even when protein formations are mispredicted. The study clearly demonstrates complementary roles of co-folding (superior pose/affinity prediction for known ligands) and docking (better hit prioritization), and addresses deep learning memorization concerns via ligand similarity analysis.

Weaknesses:

The study identifies a major limitation of co-folding-failure to capture rare protein conformational changes, which deserve future investigation. The authors include uncalibrated Boltz-2 affinity data (addressing a prior comment) but note that large-scale free energy perturbation (FEP) comparisons are beyond their capabilities.

Appraisal of Aims Achieved:

The authors successfully achieved their primary aims and the results provide strong, well-supported evidence for their core conclusions. Key conclusions are grounded in the study's unbiased, training-set independent data, ensures the conclusions are not confounded by model memorization and are broadly applicable to the field's use of these co-folding models.

Field Impact:

This study provides a critical reality check for the field: co-folding models are powerful tools for pose prediction but are not yet standalone solutions for virtual screening, a key distinction that will prevent over-reliance on these models and guide more rational tool selection.

Reviewer #1 (Public review):

The authors conducted a comprehensive benchmarking and evaluation of co-folding platforms, including AlphaFold3, Boltz-2, Chai-1, and the docking algorithm Dock3.7, which employs a physics-based scoring function that incorporates van der Waals interactions, electrostatics, and ligand desolvation energies. The system of interest was the SARS-CoV-2 NSP3 macrodomain (Mac1), an increasingly popular antiviral target, and the ligand sets comprised 557 unseen ligand poses (keeping the training for these co-folding platforms in mind). Additionally, the authors investigated whether the co-folding models could distinguish true ligands from non-binding small molecules. The study is thorough, with extensive statistical support and consensus across multiple metrics (chemoinformatics for quantifying ligand similarity and efficacy). The questions that the authors aim to address are whether the co-folding models struggle with memorization, whether they can distinguish between a true and a false binder, whether they replicate experimental binding affinities and efficacy, and how they compare to the physics-based docking algorithm (Dock3.7).

Strengths:

Overall, this is a scientifically solid paper.

The work is highly detailed and well executed, featuring thorough data analysis and statistical assessment.

Comments on revised version:

The authors have adequately addressed my concerns.

Reviewer #1 (Public review):

Summary:

This study revisits an important and controversial question in brain repair: whether NeuroD1 can convert brain immune cells into nerve cells in vivo. Using a virus-free genetic system, in vivo imaging, injury experiments, and single-cell profiling, the authors provide convincing evidence that NeuroD1-expressing cells do not become nerve cells under the tested conditions. Instead, these cells largely retain their original immune-cell identity, and some appear to undergo cellular stress or loss.

Strengths:

The main strength of the work is that it tests this question with a cleaner genetic strategy, avoiding some of the concerns associated with viral delivery and unintended cell labeling. Although the overall conclusion is consistent with the authors' previous work, the current study adds useful independent evidence, particularly through the virus-free fate-mapping system and live imaging in the brain.

Weaknesses:

The tested time window cannot fully exclude the possibility of very delayed or incomplete neuronal differentiation.

Overall, this is a useful and careful study that supports the conclusion that NeuroD1 does not drive brain immune cells to become nerve cells in the tested settings. It should be valuable for researchers studying brain repair, cell fate conversion, and genetic fate mapping, and it provides a clear caution against overinterpreting reprogramming results based only on viral labeling.

Reviewer #2 (Public review):

Summary:

In vivo glia-to-neuron conversion emerges as a potential regeneration-based therapeutic strategy for neural injuries and diseases. However, controversies exist in this exciting field, largely arising from the non-stringent methods use to analyze in vivo neuronal conversions. The study by Li et al. directly tackled such a controversy on Neurod1-mediated microglia-to-neuron conversion. They took advantage of transgenic mouse lines to specifically express Neurod1 in microglia of adult mouse brains. Results from immunohistology, in vivo live cell imaging, and scRNA-seq convincingly demonstrate that microglia cannot be converted in vivo to neurons by ectopic Neurod1 expression under the specified normal or injury conditions. Instead, it induces microglia death, consistent with their earlier findings. These solid results, though negative, are critical additions to the research field and further support that stringent lineage tracing methods are essential for studying in vivo cell reprogramming. Overall, the studies are rigorously designed and executed.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

The current manuscript characterizes in detail the macrophages in the thymus. The authors identify two distinct populations of thymic macrophages and describe their surface marker expression and transcriptional signatures. They also explore their ontology and kinetics of settling and persistence in the thymus and find that the TIMD4+ macrophages are derived from embryonic progenitors and self-maintain in the thymus, while the TIMD4- macrophages are derived from monocytes. Most importantly, the authors test the functional importance of thymic macrophages for T cell development using an in vitro depletion system, from which they conclude that macrophages are important for one of the earliest selection steps in T cell development - the beta selection.

Strengths:

The authors use state-of-the-art techniques, such as multiple genetically modified mice, multi-color flow cytometry, single-cell RNA sequencing, genetic fate mapping, and fetal thymic organ culture (FTOC) combined with depletion. Their work is in good agreement with prior published studies on the subject, such as Tacke et al. (PMID: 26091486) and Zhou et al. (PMID: 36449334). In addition to reproducing prior knowledge, the authors uncover novel and unexpected facets of thymic macrophage biology, such as their SpiC independence and the fact that TIMD4- thymic macrophages depend on CCR2 (Tacke et al. have shown that the overall thymic macrophage compartment is normal in CCR2-/- mice). Most surprisingly, the authors claim that thymic macrophages control an early checkpoint in T cell development, the beta selection. This has not been reported before, as beta selection is usually considered a cell-autonomous process in thymocytes that does not require input from other cells.

Reviewer #2 (Public review):

This manuscript from Zuniga-Pflucker laboratory describes that thymic macrophages are heterogeneous in flow cytometric and transcriptomic profiles, containing two major populations characterized by TIMD4 and CX3CR1 expression. These macrophage populations are both parenchymal in the thymus but are unequal in developmental ontogeny, Flt3 expression history, and CCR2 dependency. The manuscript further reports the interesting findings that the depletion of thymic macrophages impairs thymocyte development at the DN3 beta-selection checkpoint. These results provide an important advance for further understanding of thymus biology, especially in view of the contribution of heterogenous thymic macrophage subpopulations.

Reviewer #1 (Public review):

Summary:

The authors provide in vivo and in vitro evidence for an interaction between AIRE and AID. This has implications for the dynamics of the germinal center response and autoimmunity related to the APSI disease.

Strengths:

Several both biochemical and in vivo experiments to show interaction and the function of AIREs regulation of AID activity in the GC response.

Comments on revised version.

I believe the manuscript is improved.

Reviewer #2 (Public review):

Summary:

In this study, Zhou et al investigated the expression and function of AIRE in B cells in peripheral lymphoid tissues. First, they found the expression of AIRE protein in mature B cells in the follicles in human tonsils and spleens from healthy donors. Flow cytometry analyses using human samples as well as Aire-reporter mice demonstrated AIRE expression in germinal center B cells. The expression of Aire in B cells was induced by CD40 signals. Then, to investigate the impact of AIRE deficiency on B cell function, the authors used a method of transplanting bone marrow cells from Aire-KO and WT mice into B-cell-deficient mice, comparing B cell development and function reconstituted in the recipient mice. Their results showed that Aire-deficient B cells strongly responded to immunization with antigens, exhibiting enhanced class switching and somatic hypermutation of antibodies compared with WT B cells. The same phenomena were observed in CRISPRed B cell lines lacking Aire. The authors successfully utilized the Aire-deficient B cell line to demonstrate that Aire suppresses antibody class switching and somatic hypermutation via its interaction with AID. Finally, using B cell transfer into B cell-deficient mice demonstrated that mice harboring Aire-deficient B cells produced high levels of autoantibodies against Th17 cytokines and exhibited reduced resistance to Candida infection. This mirrors characteristic symptoms in AIRE-deficient patients. The findings of this study not only reveal an unexpected function of AIRE in B cells but also have the potential to contribute to understanding the pathogenesis of APECED and offering a new direction for developing therapies.

Strengths:

The strength of this study lies in demonstrating the expression of function of AIRE in B cells in both mice and humans. It also revealed the direct interaction between AIRE and AID, along with its binding mode (requiring CARD and NLS domains of AIRE), and showed that this interaction is crucial for AIRE function in B cells. It is also significant that the study demonstrated how B cell-intrinsic dysfunction of AIRE leads to autoantibody production against cytokines.

Comments on revised version.

My previous concerns have been properly addressed.

Reviewer #2 (Public review):

The manuscript reports protection of midlobular hepatocytes from APAP toxicity by activation of Atf4-CHOP (Ddit3)-mediated cell cycle arrest and stress response. The authors acknowledge that their finding is unexpected because CHOP typically induces cell death. Therefore, they functionally validate several aspects of the proposed Atf4-CHOP mechanism. Along these lines, the mitigation of APAP toxicity by AAV expression of Atf4 or Btg2, the latter identified as CHOP effector, is impressive. Whether Atf4 indeed acts through CHOP and whether midlobular hepatocytes are protected because of cell cycle arrest is less clear. These and other criticisms are described in the following.

Major points:

(1) Starting with the basics, one wonders why midlobular hepatocytes manage to mount a defensive response to APAP but PC hepatocytes don't. Is this because midlobular hepatocytes express the relevant Cyps (2e1 but also 1a2 and 3a11) at lower levels, which mitigates toxicity and buys them time? This would be supported by F2A but not by F3B, at least not for the most important Cyp2e1. A moderate difference is shown for Cyp1a2 expression in F3D but is that enough to explain the different fates? Or are additional post-transcriptional effects on these Cyps at work? In the re-revised manuscript, it was clarified in the legends of F2A and F3B that they visualize the same data in different ways.

(2) The evidence presented in support of cell cycle arrest of midlobular hepatocytes is not fully convincing: there is no overt difference in S and G2/M gene scores in F2F; the marker genes used for S phase and G1 to S progression in F2G are unusual. Along these lines, one wonders if spatial transcriptomics confirmed the Ki67 immunostaining results in F1 also for specific zones, not only overall, as shown in F2E? The discussion and abstract of the re-revised manuscript acknowledge that spatial transcriptomics did not independently confirm cell cycle arrest in midlobular hepatocytes.

(3) The authors conclude in line 364 that halting of proliferation by Btg2 favors survival, which raises the question of whether Btg2 knockout causes death in midlobular hepatocytes in F6K. Data addressing this question, that is, localization and extent of tissue necrosis and ALT levels after APAP, are missing. The efficiency of knockout of Btg2 is also not given. Additional Btg2 knockout data support its proposed role in the revised manuscript.

(4) Related to the previous question, the BTG2 immunostaining in F6F is not convincing when compared to F6D. One also wonders if it is necessary to apply APAP to find induction of BTG2 by AAV-Ddit3? The text of the re-revised manuscript reflects that issues with immunostaining did not allow for concluding that APAP promotes nuclear localization of BTG2.

(5) Related to the previous question, the proposed Atf4-Ddit3 axis is challenged by the lack of midlobular induction of Atf4 in the APAP scRNA-seq data published by another group presented in S4F and G. Further analysis of AAV-Atf4 samples generated for F5 could address if it is really Atf4 that acts on Ddit3 in APAP toxicity. The extended list of transcription factors (from 30 to 50) includes Atf4 but direct evidence for an interaction with Ddit3 is missing from the revised manuscript. The re-revised manuscript acknowledges this limitation by referring to a Atf4-Chop (Ddit3) axis and defining that as a functional pathway, not direct interaction of the proteins.

(6) Related to the previous question, the ATF4 immunostaining in F5A doesn't look convincing, with many brown pigments appearing to be outside of the nucleus, which was addressed by adding high-magnification images to F5A of the re-revised manuscript.

(7) It is not ruled out that AAV expression of Atf4 or Btg2 reduces hepatocyte sensitivity to APAP by affecting expression of the Cyps needed for activation. In other words, does AAV-Atf4 or AAV-Btg2 change the expression of any of the Cyps relevant to APAP in the 3 weeks before APAP application (F5B)? S5A of the revised manuscript rules out loss of Cyp2e1 expression as a confounding factor.

(8) It is laudable that the authors tried to extend their findings to human by using snRNA-seq data from a published study (line 391) but it is unclear why they didn't analyze all 10 patients in that study but instead focused on 2 and stated that this small sample number prevented drawing definitive conclusions and could therefore only be mentioned in the discussion. The re-revised manuscript includes analysis of the more substantial snRNA-seq dataset (in addition to the limited spatial transcriptomics) of patients with APAP toxicity in S4-3E, which confirms the midlobular expression of stress-response genes observed in mice but differs from mice in activation of proliferation genes, which may be due to sampling at later stages of the injury response as explained in the text.

Minor points:

(1) What is the functional classification of DEG in F2A based on? GO terms? Clarified in revised manuscript.

(2) The rationale for focusing on CHOP is not clear because Ddit3 is not shown in the spatial transcriptomics in F2A and not significant in F2B, contradicting what is stated in line 206. F2A includes Ddit3 in the revised manuscript and although it is not significant in S1G (former F2B), it is among the most highly expressed transcription factors in F4B and S3B.

(3) The term "redistribution" used in line 197 to describe expression of Cyp2e1 and other Cyps in the midlobular zone seems inappropriate considering that they just continue to be expressed there whereas PC hepatocytes are dying in F3B; the same applies to "Gene Expression Shift" in F3H. Clarified in revised manuscript.

Comments on revised version.

The revised manuscript addressed many of the original points and the re-revised manuscript clearly describes remaining uncertainties, which may be technical in nature such as lack of cell cycle arrest of midlobular hepatocytes in spatial transcriptomics or could be addressed in follow-up studies such as the nature of the interaction between Atf4 and CHOP.

Reviewer #1 (Public review):

Summary:

This manuscript presents an innovative approach combining spatial miRNA profiling with computational analysis to characterize treatment-associated tumor states in a BRCA1-deficient breast cancer model.

Strengths:

(1) The integration of latent Dirichlet allocation-based topic modeling and Structural Similarity Index Measure maps analysis provides a potentially valuable framework for studying tumor heterogeneity.

(2) The innovation is high, both conceptually and on technical aspects. The work is a potentially important technical development as spatial transcriptomics for miRNAs is needed, and an interesting manuscript for a large spectrum of readers.

Weaknesses:

The method analysed a limited set of microRNAs, although all are functionally important and well published.

Reviewer #2 (Public review):

Summary:

The authors apply a hydrogel nanoliter-well in situ microRNA assay to tissue sections from a mouse model of BRCA1-related triple-negative breast cancer, in which tumors had acquired resistance to a PARP inhibitor, and test two drug combinations. They develop a spatial analysis that groups wells into microRNA "topics" and relates these topics to treatment sensitivity and to immune infiltration, aiming to show that the spatial arrangement of microRNAs can report on drug efficacy and stratify tumors by their eventual sensitivity or resistance.

Strengths:

(1) The in vivo combination-therapy experiments are technically careful, and the finding that adding Poly(I:C) to olaparib improves antitumor activity is new.

(2) The data and the analysis code are openly deposited on Zenodo.

(3) Whether the spatial organization of microRNAs carries treatment-relevant information remains a worthwhile question.

Weaknesses:

(1) It is not clear what the spatial measurement adds. The discrimination of sensitive vs resistant tumors was already reported in the authors' prior work, and in this dataset the separation reduces to the relative amount of two microRNAs, let-7a and miR-21, that the bulk analysis had already nominated.

(2) The platform is on the well-level rather than single-cell, and the effective spatial resolution (well size and the number of cells per well) is not stated, so the meaning of "spatial" is unclear, and the sensitivity and specificity of the assay are not established in this work.

(3) The sensitive vs resistant separation is an in-sample description of labels that were fixed in advance, on roughly 21 tumors with about three per treatment arm and nothing held out; the model is refit for each analysis rather than frozen, so it cannot be evaluated as a classifier.

(4) The headline association of a let-7a topic with resistance is correlative, unvalidated, and runs opposite to the canonical roles of let-7 as a tumor suppressor and miR-21 as an oncomiR, and it may reflect the abundance ratio of the two dominant probes.

(5) The topic model is simplistic, collapses to two informative topics, and does not use the existing morphology or H&E information already available on the same sections; the co-localization analysis relies on an image-quality metric that is not appropriate for this purpose and lacks a null.

(6) The conclusions are dependent on a single mouse model at a single timepoint with no human data, but the framing attempts to extend to patients.

Reviewer #3 (Public review):

Summary:

This manuscript investigates strategies to overcome resistance to PARP inhibitors (olaparib) in a mouse model of BRCA1-related triple-negative breast cancer. They test whether combining olaparib with a PI3K inhibitor (alpelisib) or with an immune-stimulating agent (Poly(I:C)) can improve outcomes in both drug-sensitive and drug-resistant tumors, and find that both combinations extend survival in sensitive tumors, while only the PI3K combination partially overcomes established resistance. To understand the biological basis for these differences, the authors apply a previously developed hydrogel-based assay that measures seven microRNAs directly within tumor tissue sections, preserving their spatial location. They then build a set of computational tools-based on a topic-modeling method called latent Dirichlet allocation (LDA), principal component analysis (PCA), and an image-similarity measure called SSIM-to interpret these spatial microRNA patterns and relate them to tumor drug sensitivity, treatment type, and the surrounding immune cell environment.

Strengths:

(1) The in vivo survival experiments are well powered and rigorously analyzed, with appropriate statistical testing (log-rank tests) clearly supporting the central efficacy claims: both combination therapies benefit sensitive tumors, and PI3K inhibition (but not Poly(I:C)) partially rescues resistant tumors.

(2) The spatial microRNA measurement technology, while previously published, is thoughtfully applied here to an earlier treatment timepoint (10 days) than prior work, which is a reasonable and useful extension aimed at capturing biology before advanced tumor changes complicate interpretation.

(3) The core finding that a microRNA topic dominated by miR-21 associates with drug sensitivity, while a topic dominated by let-7a associates with resistance, is supported by a formal statistical test (a Mann-Whitney U test comparing principal component scores between sensitive and resistant tumors), giving reasonable confidence in this specific result.

(4) The idea of layering an immune-infiltration similarity map (SSIM) onto the microRNA topic maps is a creative and potentially broadly useful way to connect molecular spatial patterns with tissue architecture, and could be adapted to other spatial biomarker studies beyond this one.

Weaknesses:

(1) Several of the paper's central spatial and immune-colocalization findings are supported only by visual inspection of small numbers of samples (commonly three tumors per treatment group) rather than by formal statistical comparison. This applies to the treatment-type separation shown in Figure 3B.iii and to the immune-microRNA co-localization patterns shown in Figure 4B.ii, both of which are described narratively without accompanying statistical tests.

(2) The claim that Poly(I:C) fails to alter the immune composition of resistant tumors, unlike PI3K inhibition, is stated qualitatively ("little difference") without a quantitative comparison, which weakens confidence in this specific interpretation.

(3) All spatial analyses derive from a single mouse model at a single treatment timepoint, with no independent tumor cohort used to test whether the identified microRNA topics and their treatment/sensitivity associations generalize. This is an appropriate scope for an initial proof-of-concept study but means the biomarker potential of the approach remains unproven outside this specific dataset.

Overall, the authors achieve their stated aims, and the evidence broadly supports the paper's central conclusions distinguishing drug-sensitive from drug-resistant tumors. The additional analyses linking treatment regimen and immune infiltration to spatial microRNA patterns are plausible and consistent with the survival data, though they rely on small sample sizes and, in places, qualitative rather than statistical comparisons, and would benefit from further validation. The analytical framework itself - particularly the SSIM-based integration of molecular and cellular spatial data - is a useful and creative contribution with potential utility for other groups working on spatial biomarker discovery.

Reviewer #1 (Public review):

Summary:

This paper is a comprehensive review of perturbation studies, and the state-dependence of the brain's response to perturbation at the circuit, mesoscale, and macroscale level.

Strengths:

The strengths of the paper are the thorough description of many perturbation studies at different levels of organization, and the integration of both experimental and modeling studies. The review clearly communicates the need to consider 1) brain or local-population state, and 2) multiple levels of organization, in order to understand perturbation responses. Another major strength is the ability for the reader to reproduce figures using the EBRAINS platform.

Weaknesses:

The major weakness is that the review does not include a significant integration across scales, and as a result reads like three separate (though comprehensive) reviews. Currently, the only integration across the scales is in a brief conclusion paragraph. I would recommend adding an additional section, in which the overarching picture is discussed. (i.e. a unifying view of state dependence, and what is learned by considering across scales), and more prefacing in the introduction of the overarching message and framework to the review.

Reviewer #2 (Public review):

Summary:

In this review article, the authors discuss the whole brain activity changes induced by brain stimulation. They review the literature on how these activity changes depend on the cognitive state of the brain and divide the results by the scale of the change being induced, from microscale changes across small groups of neurons, up to macroscale changes across the entire brain. Finally, they describe attempts to model these changes using computational models.

Strengths:

The review provides an overview of the results within this sub-field of neuroscience, and the authors are able to discuss a lot of prior results. The framing of the changes in neuronal activity in terms of computational changes is also a helpful approach.

We thank the authors for the updates that they have made in response to our original comments. Their attempts to address many of the comments that we raised have greatly improved the paper. We believe that there are two major points that still require some additional changes:

(1) We raised the concern that the results within each of the three spatial scales did not join together into a cohesive single framework. The authors responded by updating the conclusion section to provide a more conceptual picture linking the different spatial scales. This is much appreciated. However, by placing this framework at the end of the paper, it prevents the reader from using this understanding to building a conceptual model as they progress through the paper. We would ask that the authors intersperse this conceptual picture within the main text, and to then re-emphasize it in the conclusions. This would frame each section in terms of the findings that led directly to it and, therefore, allow the reader to build a conceptual understanding within each section. As one example, we note that the authors have made no changes to the mesoscale processing section. Therefore, when reading that section, it is completely unclear how any of the results seen in the microscale may relate to the changes observed at the mesoscale.

(2) The authors have greatly improved their explanation of the complexity metrics. However, the paper still lacks a conceptual understanding for why "perturbation-based complexity metrics" are a reasonable way to study the state-dependent dynamics? What does studying perturbations provide that studying the spontaneous activity in different states alone, would not provide? Why is this the preferred way to study such dynamical systems? Such a justification would strongly support the analyses reviewed in the paper and would increase the reader's understanding of the methodology.

Reviewer #1 (Public review):

Summary:

The authors identify and investigate a specific population of PVNOT neurons (oxytocin neurons of the paraventricular hypothalamus) that seem to be involved in both behavioral and autonomic thermoregulation. These cells are activated by social thermoregulatory behaviors, but can influence thermoregulation in both social and social contexts, specifically during transitions and when mice are at low core body temperature (Tb).

Comments on revised version.

The authors have addressed my concerns with clear and reasonable explanations and altered the text accordingly. This has improved the paper, but it still feels in some parts like a patchwork of nice work and discoveries stitched together. Further changes to format, analysis, and some experimental work could hugely improve the manuscript. I see that will surely come from future work, and this is the authors' choice.

Regarding the lack of behavioral analysis, I think it's fair for them to keep it for future studies.

I am happy to see they take and expand the opto inhibition suggestion. Again, that experiment would be nice for this paper, but not crucial.

Regarding discussing Raam et al 2026. It is good that they detail the practical decision of using females. What I meant was that, given that both papers study calcium dynamics around the time when mice engage in social thermoregulatory behaviour, they could have speculated on potential dmPFC-PVN functional connectivity, for example. Or the fact that Raam found that females showed fewer huddling behaviour than males at 5{degree sign}C (however, Vandendoren tested 15{degree sign}C, not 5{degree sign}C). Discussion of these features would be welcome, but maybe all of the current scope.

Overall, this is a very strong paper.

Reviewer #2 (Public review):

This is a very interesting study from Vandendoren and colleagues examining the role of PVN oxytocin neurons during thermoregulatory behaviors, in particular during thermoregulatory huddling. The findings are important and have implications for the thermoregulation field as well as the social/naturalistic behavior field. The findings are compelling and use a combination of state-of-the-art tools (photometry, optogenetics, automated behavior tracking, thermal imaging, and core body temperature measurement), often in combination with each other, to produce a rigorous and high-dimensional dataset.

Comments on revised version.

I appreciate the effort the authors have put into addressing all of my questions, and I have no remaining concerns.

Reviewer #3 (Public review):

Summary:

This study investigates how the activity of hypothalamic paraventricular oxytocin (PVNOT) neurons relates to physiological states in female mice, with a particular focus on behavioral states and thermogenic sympathetic activity. To address this question, the authors combined automated video-based behavioral classification with calcium imaging of PVNOT neuron activity. Sympathetic thermogenesis was inferred from surface temperature changes measured by infrared thermography, and the authors have made their custom analysis scripts available. The authors report that strong, pulsatile activation of PVNOT neurons was "occasionally" observed immediately before transitions from resting to active states. This observation suggests that PVNOT neuronal activity may facilitate the transition from rest to activity. This phenomenon was observed in both pair-housed and individually housed animals. Taken together, these findings raise the possibility that the oxytocinergic system contributes to naturalistic behavior transitions even in the absence of social interactions. However, concerns regarding the selectivity of GCaMP expression in oxytocin-expressing neurons call into question the validity of the recorded PVNOT neuronal activity. The revised manuscript improves the presentation and interpretation of the data. Nevertheless, because the authors have not provided additional experiments or analyses addressing the major methodological concerns, the evidence supporting the central conclusions remains essentially unchanged.

Strengths:

The oxytocinergic neural system is believed to subserve a wide range of physiological functions. Elucidating these roles requires monitoring PVNOT neuronal activity under diverse behavioral contexts, as well as manipulating this activity to establish causal relationships. In this study, the authors present a technically sound experimental framework that integrates behavioral tracking in both individually and group-housed mice with the monitoring and manipulation of PVNOT neuron activity. This setup represents a valuable methodological resource for researchers investigating the physiological functions of oxytocin.

Weaknesses:

(1) Immunohistochemical validation of selective GCaMP expression in oxytocin-expressing neurons showed that only 24-51% of GCaMP-positive neurons expressed oxytocin. As an alternative approach, the authors argue that the similarity between calcium dynamics recorded in virgin and lactating animals supports the identity of the recorded neurons as oxytocin neurons. While this physiological comparison is interesting, it does not constitute direct evidence for cell-type specificity of GCaMP expression. The revised manuscript now acknowledges that in situ hybridization targeting oxytocin mRNA would provide a more reliable validation, but such validation has not been performed. Therefore, uncertainty regarding the identity of the recorded neurons remains, limiting confidence in the interpretation of the calcium imaging data.

(2) Although the authors' interpretation is generally consistent with the data presented, their main conclusions rely heavily on observational findings. Moreover, optogenetic stimulation of PVNOT neurons failed to robustly recapitulate behavioral state transitions (Figs. 6D and S5B). Further interventional experiments remain necessary to rigorously test the authors' interpretation and establish a causal relationship between PVNOT activity and rest-to-active transitions. In particular, loss-of-function approaches targeting the PVNOT system, such as OXTR antagonism, inhibitory optogenetics, or cell-type-specific ablation, remain essential to determine whether perturbation of this system alters behavioral state transitions. Although the authors expanded the Discussion to acknowledge this limitation, the revised manuscript provides no additional experimental evidence addressing it.

Comments on revised version.

I appreciate the authors' efforts to clarify the manuscript and to discuss the limitations more explicitly. Nevertheless, because my major concerns have been addressed primarily through revised interpretation rather than new evidence, my overall assessment of the scientific support for the principal conclusions remains unchanged.

Reviewer #1 (Public review):

The manuscript from Zhu et al. identifies microbial riboflavin-derived MR1 ligands as potent pharmacological activators of human MAIT cells and provides evidence that MR1 ligand stimulation can enhance MAIT-mediated tumor killing across multiple solid tumor models. The study is conceptually interesting and supported by a broad combination of human primary samples, tumor cell lines, 3D models, SC transcriptomics, and xenograft experiments. Overall, the data largely support the central conclusion that MR1 ligand stimulation can strongly activate human MAIT cells and enhance anti-tumor cytotoxicity. However, the broader conclusions concerning endogenous MAIT mobilization, tumor specificity, and translational potential are not yet fully supported by the current data and should either be moderated or addressed with additional experiments.

Comments:

(1) The authors use one-way ANOVA throughout the manuscript, but this may not be appropriate for some analyses, particularly when multiple experimental factors are present and their interaction effects need to be considered. For example, Figure 3f appears to involve multiple factors, for which a two-way ANOVA may be more appropriate. Similar issues may apply to other panels.

(2) In Figure 3f, the authors show data from patients #1 and #2 and state that the experiment is representative of three experiments. What does the reported "n=4" represent in this figure?

(3) There appears to be a discrepancy between Figure 3f and Supplementary Figure 3b. The two panels appear to use the same treatment conditions and the same label, and both appear to use patient #1 samples, yet the reported values are different. Please clarify the experimental design and explain the reason for this discrepancy.

In addition, the gating strategy used to define live tumor cells should be clearly described in the figure legend and/or Methods. The authors define "live tumor cells" as MR1/5-OP-RU tetramer-CD45- cells. However, in primary liver tumor samples, the CD45-/tetramer- population may contain other non-hematopoietic cells, such as fibroblasts, and therefore may not exclusively represent tumor cells. The authors should clarify whether additional tumor-specific markers or other criteria were used. The gating strategies for the relevant flow cytometry experiments should be provided in the Supplementary figures.

(4) I have some concerns regarding the claims of "selective activation of anti-tumor inflammatory pathways rather than generalized cytokine release" and "avoiding induction of tumor-supportive mediators." The authors show that MAIT cells stimulated with 5-OP-RU can substantially reduce tumor cell viability. Therefore, the cellular composition of the co-culture is likely to change considerably during the assay, which may affect the absolute levels of cytokines and other soluble mediators detected. For example, reduced tumor cell numbers could lead to lower production of tumor-derived factors such as VEGF, potentially confounding the interpretation that these mediators are not induced by MAIT activation. The authors should consider whether cytokine measurements have been normalized to viable cell numbers or otherwise account for differences in tumor cell abundance.

(5) The in vivo tumor models may show substantial variability between independent experiments. Rather than presenting a single representative experiment, the authors should consider showing pooled data from all independent experiments, with the total number of mice clearly indicated.

(6) Why did the authors use an MR1-overexpressing tumor cell line for the in vivo studies rather than the parental cells with endogenous MR1 expression, together with MR1-KO cells as a negative control? The authors demonstrate that MR1 is detectable across multiple tumor cell lines and that endogenous MR1 expression is sufficient to support MAIT-mediated killing in vitro. Moreover, MR1 overexpression substantially enhances tumor cell susceptibility to MAIT-mediated killing. Therefore, it is unclear whether the strong therapeutic efficacy observed in vivo reflects physiologically relevant MR1 expression or is driven by artificially elevated MR1 expression. An in vivo comparison using parental and MR1-KO tumor cells would substantially strengthen the translational relevance and establish whether the therapeutic effect can be achieved at endogenous levels of MR1.

(7) How is tumor specificity of MAIT achieved ? The authors propose that MAIT-cell activation by MR1 ligands provides an antigen-independent approach for tumor targeting. However, MR1 is broadly expressed and is not tumor specific. While the relative sparing of T and B cells in Figure 7B provides some evidence of cell-type selectivity, this does not establish tumor versus normal tissue specificity. It remains unclear whether activated MAIT cells can discriminate tumor cells from other normal MR1-expressing cells and tissues. This raises an important question regarding the potential systemic toxicity of MAIT cells activated by systemic administration of 5-OP-RU. In particular, could other MR1-expressing cells be targeted when a large number of MAIT cells are simultaneously activated? The authors should consider assessing systemic toxicity in vivo, for example by examining serum ALT/AST levels and tissue pathology, and/or by evaluating the effects of MAIT + 5-OP-RU in tumor-free animals. At least, the potential specificity and safety limitations of systemic MR1 agonism should be discussed.

Reviewer #2 (Public review):

The manuscript by Zhu et al. describes MAIT cell activation by riboflavin metabolites presented by MR1. The authors provide solid evidence for this activation and anti-cancer functional consequence using an array of selected cell lines, primary ex vivo and engineered xenograft models. Broadly, the results are thorough and well controlled, and provide a highly informative insight into the metabolite-MAIT-cancer cell interactions. However, the majority of this work is undertaken using models that preferentially express key targets, and whilst still useful, the (current) broader implications of this research are overstated. Additionally, the suggested MAIT modulation of the tumor microenvironment requires clarification.

Major Comments:

(1) In Figures 2b-d, the authors suggest microbial metabolite stimulation of PBMC cultures increased MAIT cell frequency up to 60%. Whilst their flow data is compelling, the frequency of one population can be influenced by changes in other populations. A form of absolute or relative-to-total count should be used.

(2) The statements regarding cytokine induction in Figure 4e are too strong; many of those inflammatory cytokines are not automatically and consistently tumour-suppressive. The line 299 '...were not induced' may just reflect death of tumor cells. It would be useful to include tumour cell-only controls in Figure 4.

(3) Figure 7 is interesting, but the authors' conclusion that MAIT+5-OP-RU controls the tumor microenvironment is not robustly supported by their evidence.

a) It is not clear how CD14+ cells established a sustained suppressive environment.

b) It is not clear how the peritoneal addition of microbial metabolites 'significantly enhanced MAIT-mediated tumor control'. The authors show that the addition of 5-OP-RU reduced the number of GFP-expressing tumour cells present in peritoneal lavage fluid. There is limited evidence to suggest this occurs through MAIT cells or MR1 in this figure.

c) It is difficult to draw conclusions from peritoneal lavage flow when some experimental groups received cells IP, but then all groups were equally assessed for key populations, and all data are presented as frequencies. The authors should use absolute counts (or similar) to appropriately show changes in cell populations to account for varying total/live/cd45+ cell compartments.

d) It would be necessary at a minimum to include 5-OP-RU-only controls, and ideally include MR1 blocking or the cancer line with MR1 removed. Alongside this, the authors should substantially reduce the strength of their statements on microbial metabolite-MAIT suppression of the tumor microenvironment.

Reviewer #1 (Public review):

Summary:

Lee et al. investigate how parallel retinal pathways respond to a common loss of photoreceptor input. The authors induce partial cone loss in adult mice and compare the functional responses of sustained OFF alpha (sOFFa) and transient OFF alpha (tOFFa) ganglion cells, together with changes in their presynaptic circuits. Using targeted patch-clamp recordings, linear-nonlinear analyses, pharmacological dissection of inhibitory inputs, and quantitative synaptic imaging, they show that the two pathways do not respond uniformly to cone loss. tOFFa ganglion cells exhibit more extensive changes in spatiotemporal receptive fields than sOFFa ganglion cells, with contributions from excitatory transmission, presynaptic glycinergic inhibition, direct GABAergic and glycinergic inhibition, and intrinsic properties. At the same time, transformations between synaptic input and spike output partially preserve ganglion cell signaling despite the loss of cones.

Strengths:

This is a technically careful and high-quality study. The comparison of two well-defined ganglion cell types and their dominant bipolar-cell pathways provides an unusually detailed view of where circuit modifications arise following a shared perturbation. The combination of recordings at successive stages of signal processing, pharmacological manipulations, and synaptic imaging is a particular strength. The use of partial stimulation in control retina also helps distinguish the immediate consequence of reduced input from subsequent circuit changes. The resulting conclusion that common photoreceptor loss produces pathway-specific forms of remodeling rather than a uniform retinal response is interesting and well supported. The work adds to our understanding of the diversity and circuit specificity of responses to retinal degeneration.

Weaknesses:

The principal limitations concern the precision of some mechanistic interpretations rather than the central observation of pathway-specific remodeling. First, the framework used to classify effects as compensation or circuit change sometimes treats the absence of a statistically significant difference as evidence that two conditions are equivalent. Second, the numbers of animals and retinas contributing to the main physiological and anatomical comparisons are not consistently reported, making it difficult to evaluate the independence of measurements obtained from multiple cells, images, or synaptic puncta. Finally, the consequences of the observed remodeling for the visual signals carried by these pathways remain unclear. This is particularly relevant for tOFFa ganglion cells, which have been implicated in responses to looming or approaching dark objects. The altered temporal filtering, center-surround organization, and input-output transformation could preserve, degrade, or otherwise transform such signals. These issues qualify the mechanistic and functional interpretation but do not substantially weaken the main conclusion that the two pathways respond differently to partial cone loss.

Reviewer #2 (Public review):

Summary:

This is an elegant, rigorous, and thought-provoking study that examines how different neural circuits are altered in response to loss of a common sensory input. To study this question, the authors use the mouse retina as a model system to investigate how downstream retinal circuits undergo modifications following a well-controlled partial loss of cone photoreceptors.

Strengths:

The experiments were conducted with a high degree of rigor, and the authors carefully considered and implemented appropriate controls throughout the study. Multiple parameters were tested, including pharmacological approaches to assess responses from different ganglion cell types. In addition, the authors complemented their functional data with confocal imaging to further support their findings. Overall, this is a well-written paper that provides a thorough analysis demonstrating how two similar ganglion cell types undergo distinct adaptations (i.e., compensation versus remodeling) in response to the loss of the same sensory input.

Weaknesses:

No additional experiments are needed. However, the authors may wish to consider the following points:

(1) Do the differences in compensation versus remodeling observed in ganglion cells reflect changes in the OPL? Different bipolar types may remodel their dendrites and form aberrant contacts with rods in the absence of cones. However, this would be challenging to test because there are currently no good markers for different bipolar types.

(2) It would be interesting to determine whether these functional changes can be detected at the transcriptomic level or whether they are mediated primarily through post-translational modifications.

Reviewer #1 (Public review):

In this manuscript, the authors explore whether GPCR signaling in astrocytes affects the production of TNF by astrocytes and, to a lesser extent, microglia. Unfortunately, the method used by the authors to acquire astrocyte-enriched cultures is known to result in meaningful rates of contamination by myeloid cells (microglia and others), oligodendrocyte-lineage cells, and neurons. Alternative methods of generating highly enriched astrocyte cultures, as well as purifying astrocytes with little to no neuronal or myeloid contamination across age and brain regions, have shown no evidence of TNF expression by astrocytes (Zhang et al., J Neurosci, 2014; Zhang et al., Neuron, 2016; Clarke et al., PNAS, 2018). In fact, the paper cited by the authors as demonstrating differences between human and rodent astrocytes found no evidence of TNF expression in immature or mature human astrocytes (Zhang et al., Neuron, 2016). The idea that the majority of the observed TNF transcriptomic signal, at least in culture, comes from myeloid or neuronal contamination also aligns with the authors' observation that myeloid-enriched cultures act identically to astrocyte-enriched cultures.

The authors also use a GFAP virus to drive GPCR signaling in astrocytes and neuronal progenitor cells in their cultures, but, given that these cultures are known to have meaningful contamination by other cell types, such signaling could be due to astrocyte → microglia/neuron signaling or other multicellular pathways that cannot be excluded. Similar concerns mean that we cannot assume the effect of DREADD activation of astrocytes in vivo (Figure 6) reflects a bulk change in TNF expression driven by astrocyte-specific changes rather than by multicellular signaling.

The most compelling evidence for their claim of astrocyte TNF expression comes from the human-induced astrocytes. However, their antibody staining is not sufficient to claim these cells are truly astrocyte-like. Antibody staining is highly prone to non-specificity, as highlighted by the fact that their ALDH1L1 antibody staining appears perfectly nuclear despite ALDH1L1 being a cytoplasmic protein.

To address both the purity concerns of the astrocyte-enriched cultures and the concerns about the astrocyte identity of the induced astrocytes, the authors should perform RNA sequencing. By profiling gene expression in these cultures at the genome-wide level, readers can truly assess the degree of contamination and thus the likelihood of the proposed mechanism (i.e., astrocyte-specific TNF production). Importantly, previous studies have suggested that very little neuronal and myeloid contamination is required to dramatically change cellular responses (Foo et al., Neuron, 2011; Liddelow et al., Nature, 2017).

Reviewer #2 (Public review):

Summary:

Abbasi et al. examine how signaling through the major G-protein pathways (Gs, Gq, and Gi) influences tumor necrosis factor expression in astrocytes and microglia. Using a combination of pharmacological receptor activation, chemogenetic manipulation, primary rodent glial cultures, human induced pluripotent stem cell-derived astrocytes, and an in vivo astrocyte-targeted Gi manipulation, the authors report a broadly consistent pattern in which Gs- and Gq-associated signaling reduces tumor necrosis factor expression, whereas Gi signaling increases it. The study's cross-species and cross-preparation design, spanning astrocytes and microglia as well as in vitro and in vivo systems, provides a potentially valuable framework for understanding how neuromodulatory pathways may regulate glial inflammatory signaling.

Strengths:

A major strength of the study is the breadth of experimental systems used, which includes primary rat glia, human induced pluripotent stem cell-derived astrocytes, and an in vivo manipulation, allowing for comparison across species and levels of biological complexity. The use of chemogenetic receptors in astrocytes provides relatively direct control over Gq and Gi signaling, and these experiments yield consistent effects on both tumor necrosis factor messenger RNA and protein, strengthening the internal validity of the astrocyte findings. The observation that similar directional effects are seen in human-derived astrocytes and in microglial cultures further supports the idea that aspects of this regulatory relationship may be conserved across glial cell types. More broadly, the study addresses an important and timely question about how neuromodulatory signaling pathways interface with glial inflammatory outputs, and it generates a coherent set of observations that could serve as a foundation for more mechanistic work.

Weaknesses:

The central claim that Gs, Gq, and Gi signaling broadly and directly constitute a general regulatory code for tumor necrosis factor expression is more expansive than the current evidence fully supports. In particular, the evidence for Gs-dependent effects is indirect, relying on beta-adrenergic receptor activation and forskolin-mediated adenylyl cyclase stimulation rather than direct manipulation of Gs itself, leaving uncertainty about pathway specificity. More generally, the use of different endogenous receptors to represent each G-protein class in microglia complicates interpretation, since individual receptors may engage additional signaling pathways beyond their canonical G-protein coupling, limiting the extent to which the results can be attributed to G-protein class alone.

The in vivo experiment also does not definitively establish the cellular source of the observed increase in tumor necrosis factor, as measurements are taken from bulk cortical tissue following astrocyte-targeted Gi activation. This leaves open the possibility that the observed changes arise indirectly from other cell types, particularly microglia, which are shown elsewhere in the study to be strongly responsive to Gi-related manipulations. In addition, the specificity of chemogenetic expression in vivo is not quantitatively demonstrated, further limiting cell-type attribution.

There are also important issues related to experimental design and statistical interpretation. Across several experiments, it is unclear whether reported sample sizes reflect independent biological replicates, technical replicates, or imaging fields, which is especially consequential for the human induced pluripotent stem cell-derived astrocyte experiments where donor-level independence is not clearly established. The in vivo design also appears to treat hemispheres as independent observations despite their paired nature, which may inflate statistical independence given the small sample size.

Finally, several conclusions would benefit from more cautious framing. The data support differential regulation of tumor necrosis factor relative to interleukin-1 rather than strict cytokine specificity, and measurements based solely on messenger RNA should not be interpreted as direct evidence of cytokine production. The comparison between glial signaling effects and neuronal excitation or inhibition also juxtaposes fundamentally different biological readouts and should not be interpreted as a direct functional opposition. Overall, while the study provides interesting and potentially important observations, the broader pathway-level and cell-type-specific conclusions are not yet fully established by the current experimental evidence.

Reviewer #1 (Public review):

Summary:

This manuscript describes a study examining MEG responses to participants free-viewing natural visual images. The vast majority of our knowledge of visual processing in the brain comes from studies where visual input is presented during fixation and the neural response is measured relative to stimulus onset. Even studies that include eye movements tend to either analyze the data relative to the start of each new fixation, or ignore saccades as noise. The current study simultaneously measures MEG and eye-tracking during active vision, and conducts a variety of analyses testing which of the saccade-related events produce the best alignment to the neural data. Five human participants viewed thousands of complex natural scene images while freely moving their eyes. MEG data were then binned as a function of saccade duration and aligned to different fixation and saccade events. M100 responses were better aligned with the preceding saccade onset than the current fixation onset. An additional analysis showed that when MEG signals were decomposed into independent components, the majority of the components showed more alignment and variance explained from saccade-related events (saccade onset, peak velocity, peak visual motion energy, and peak saccade curvature) compared to fixation-onset-defined events; the strongest performing of these factors was the time of peak saccade curvature. A final analysis compared the similarity of MEG topographies measured from stimulus onset (as would be standard in a static design) to those linked to peak saccade curvature and fixation onset, showing that stimulus onset responses were quite dissimilar to the active vision aligned events.

Strengths:

Overall, I think this is a fundamentally important research question, taking a novel and interesting approach. I very much like the idea behind this study. My enthusiasm is somewhat tempered by the weaknesses described below. However, at the very least I think this study would be valuable as a key launching point for future explorations, and for pushing the field into a much-needed new direction.

Weaknesses:

In its current state, the manuscript seems preliminary/incomplete in terms of both data analysis and engagement with the prior literature.

(1) In terms of the theoretical contribution, there are several potential contributions, some supported more by the data than others, and some more novel than others. In my rough assessment, from most general to most specific:<br /> a. Static vision is not the same as active vision. Supported somewhat by the analyses. Not novel (there are several studies both recent and older making this point, aside from the vaguely referenced sink-source sentence in the discussion), but this is still an understudied/underappreciated area.<br /> b. Neural responses are better aligned to saccade-related events than fixation-related events. Supported pretty compellingly by the analyses, and pretty novel. An important theoretical contribution.<br /> c. Peak saccade curvature is the saccade-related event explaining most variance. An extremely novel finding, but not well supported by the current data. At best, this seems a preliminary, exploratory hint of something to investigate further. It's intriguing but lacking in both empirical support (e.g. is this even consistent across subjects?) and theoretical discussion (what would it mean / what would be the mechanisms of such a link?).

(2) There is a small number of subjects, and for several main analyses, the data are pooled across them. Small N's can be reasonable in cases where there is large data for each subject. But it is standard to show the subjects individually to confirm reliability. Figure 1 does this nicely, but then for the main analyses examining the ICs and variance explained by the different saccade-related events (Figures 2C-F), the data were pooled across subjects. Strong conclusions are being drawn from the pooled data (e.g. highest proportion of explained variance from the peak curvature event), but it's unclear if this is consistent across subjects or potentially dominated by 1 or 2 subjects. Indeed, when the "best" score is presented for each participant (Fig 2E), only 2 of the 5 subjects showed peak saccade curvature as the best. And these results look strikingly different across subjects (P5 doesn't even look anything like an M100 response).

(3) Several parts of the results and methods are hard to follow. I had to read the paper several times to understand it. In many cases, the methods text doesn't even link with the results (e.g. the term "M100" is not anywhere in the methods).

(4) Several parts of the results felt under-explored:<br /> a) The analysis in Figure 1E is very interesting, but it's not reported in enough detail. There are no quantitative results here, just a visual of a distribution and a description of it being broad. I would be particularly interested in seeing the mean alpha reported for the best sensor for each participant (i.e. linking with the rest of that figure).<br /> b) How consistent is the timepoint of peak saccade curvature? It appears to increase with saccade duration, but is it a fixed / consistent percentage of saccade duration? If not, what factors cause it to vary? How similar is this timepoint to the optimal alpha from the analysis in Figure 1E? Would binning the data based on peak saccade curvature instead of saccade duration produce even better alignments for Figure 1D?<br /> c) For the Figure 3 analysis comparing static scene-onset responses to the saccade- and fixation-related responses: I am wondering how much of the difference is actual saccade-related activity vs a true difference in visual processing. It seems the interpretation is that "visual processing", when measured in static contexts, is very different from when measured in active contexts. But what's being compared is not visual processing specifically, but the entire whole-brain MEG response. I think in order to make this conclusion more compelling, there needs to be some way of filtering out these influences. E.g., a study that presents a simulated saccade condition, where a participant keeps their eyes fixated but views snapshots of the visual scene mimicking the exact saccade sequence of another subject.

(5) The discussion felt too thin. See some specific points below. In general, combined with the fact that the results were often hard to follow and sparse, I was left with the impression that this report was being forced into a shorter format than necessary.

(6) How do microsaccades and other types of eye movements fit into this story?

Reviewer #2 (Public review):

Summary:

Although our visual system is continuously analyzing the current visual scene, its processing proceeds in discrete episodes separated by brief eye movements (saccades). It has generally been assumed that the analysis of the next visual snapshot begins in earnest when the eyes land on a new fixated location just after a saccade, but there have been various studies indicating that at least some amount of processing occurs earlier, as the system anticipates the impending eye movement. Here, the authors use magentoencephalography (MEG) measurements to record visually-driven responses and determine at what point exactly the processing of a new visual snapshot begins.

Strengths:

(1) The work is concise and to the point, and the techniques used are a good way to answer the underlying question about visual processing, since they reflect widespread activity in the brain (rather than activity at a particular location or structure).

(2) The use of natural images and extensive data collection from 5 participants is a nice feature of the experimental design which permits characterization of the common effects and of variance across individuals.

(3) The data are analyzed rigorously, but the results are also understood intuitively; for instance, by visual comparison of responses aligned on fixation onset versus saccade onset.

(4) The results provide a clean characterization of when visual analysis begins relative to saccade onset under natural viewing conditions.

Weaknesses:

(1) There were questions about how the scene-onset condition was established, and how data were selected for it.

(2) The significance of the results is slightly overstated; the text would benefit if some of the claims were phrased with a bit more carefully.

(3) In particular, the issue of how motor-related processes (versus stimulus-related content) may determine the processing of the next visual snapshot should be discussed with a bit more nuance.

These are minor weaknesses. Overall, I found the work to be novel and instructive, as it bridges neurophysiological and psychophysical findings in a satisfactory way.

Reviewer #3 (Public review):

Summary:

This manuscript addresses a fundamental question in cognitive neuroscience: which event should serve as the temporal reference for neural processing during natural vision? While fixation onset has traditionally been treated as the analogue of stimulus onset in free-viewing experiments, the authors convincingly demonstrate that this assumption is incomplete.

The study utilizes a remarkable natural-viewing dataset consisting of simultaneous MEG and eye-tracking recordings collected during the exploration of thousands of natural scenes. The authors compare several candidate eye-movement events and evaluate which event best explains the timing of the early M100 response. Across several complementary analyses, saccade-related events consistently outperform fixation onset, with peak saccade curvature emerging as the event that best predicts neural response timing.

Strengths:

A particular strength of the work is that the conclusions do not rely on a single analytical approach. Instead, multiple independent analyses converge on the same interpretation, increasing confidence that the observed timing relationships are robust rather than analysis-specific. The comparison between natural-viewing responses and classical stimulus-onset responses is especially compelling and highlights qualitative differences in their spatiotemporal organization. Of particular conceptual importance, the findings support the broader perspective that perception is intrinsically linked to action and internally generated sensorimotor processes. This aligns well with growing evidence that oculomotor action and active sampling play central roles in perception. The work contributes to an important ongoing shift in how natural vision should be studied experimentally and interpreted theoretically.

Weaknesses:

I identified no major weaknesses in the study. The main limitation is the relatively small number of participants, despite the exceptionally rich dataset. Future work in larger cohorts and across complementary electrophysiological recording modalities will help establish the generalizability of the reported temporal relationships.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors were responsive to the previous comments and, where needed, edited the manuscript to improve clarity around assumptions and to highlight specific sensitivity analyses.]

Summary:

This manuscript seeks to make use of information about Ct values from PCR testing of mosquito pools for West Nile virus infection to make inferences about mosquito prevalence and West Nile risk. It does so through analysis of empirical data and simulated data with a realistic agent-based model.

Strengths:

This work is conceptually innovative for mosquito-borne viruses, building on ideas developed primarily during work on SARS-CoV-2. Exploring this topic is worthwhile regardless of the outcome. The use of data, testing in multiple labs, and complementarity of modeling and empirical data analysis are all strengths of the approach.

Weaknesses:

Some of the primary weaknesses include a dependence of the results on relatively narrow model assumptions, and lack of compelling improvement over existing methods. None of these are fatal flaws but are instead modest weaknesses that limit the potential of or excitement about the method.

Reviewer #2 (Public review):

Summary:

The authors extend their previous population-based Ct-value framework for inferring community epidemic trajectories from human infections to vector infections, using mosquitoes as vectors for West Nile virus. They use agent-based modelling to distinguish virus-positive detections arising from non-active infection states from those reflecting active infections, and then apply this framework to mosquito surveillance data from Colorado and Texas.

Overall, this is a well-designed and carefully evaluated study. The manuscript proposes a feasible and potentially valuable framework for vector infection surveillance. The findings are supported by both mechanistic agent-based simulations and applications to real-world mosquito surveillance data, which strengthens the biological plausibility and practical relevance of the proposed approach.

Strengths:

A major strength of the study is its clear methodological extension from human infection surveillance to vector infection surveillance. The agent-based modelling framework provides a useful basis for distinguishing active infections from virus-positive detections that may reflect non-active infection states. The application to surveillance data from two different geographic settings further supports the feasibility of the framework. Overall, the study is carefully designed, and the model schematic and main analyses are generally clear.

Reviewer #1 (Public review):

This manuscript describes a multi-modal study of associative learning and memory in humans that combines scalp EEG, pupillometry and behavioral analysis to explore the construct of mnemonic prediction errors (MPEs), in terms of their relationship to attention and cognitive control. Across two pooled studies, participants performed associative memory tasks in which they learned the relationship between a cue word (action verb) and subsequent picture (animate or inanimate) with a strong vs. weak (4 or 1 repetitions) encoding manipulation. At test, participants were encouraged to generate a prediction following the cue word to determine whether the subsequently presented picture was a match or mismatch. The timecourse of pupillary responses during match decisions were decomposed using temporal principal components analysis, which identified 6 distinct and overlapping processes. Some of the components (PC3/PC4) exhibited sensitivity to both the strength and mismatch conditions, as well as behavior (both RT and accuracy) and retrieval success on the subsequent trial. Furthermore, relationships were also observed between pupillary responses (specifically for PC4) and both frontal theta and posterior alpha power measures obtained from scalp EEG in Experiment 2, as well as for frontal theta and subsequent learning from mismatch stimuli (assessed using subsequent memory findings from a surprise recognition test). The authors suggest the findings indicate that MPEs elicit changes in attention, arousal and cognitive control which impact subsequent learning.

Strengths:

This manuscript has many strengths, including a clever study design, thoughtful integration of multiple neurocognitive measures, and a set of rigorous and technically sophisticated analyses, which reveal a large set of relationships among the measures and behavior. The findings demonstrating brain/physiology-behavior relationships are particularly important, in that they point to potential functional consequences of MPEs.\

Reviewer #2 (Public review):

Summary:

The authors studied cognitive control and attention in response to mnemonic prediction errors (MPEs): situations in which the external reality violates internal memory-based predictions. The behavioral task first established strong versus weak predictions, and then either confirmed or violated these predictions. The authors examined markers of cognitive control (frontal theta) and attention (posterior alpha suppression, pupil response) while strong and weak predictions were confirmed or violated. They found increased cognitive control (frontal theta) for strong MPEs, which correlated with subsequent memory. Markers of attention (alpha suppression, pupil response) also accompanied strong MPEs but did not correlate with subsequent memory. Pupil response was investigated using an interesting approach that decomposes the response into different components, finding that different components respond earlier or later and show different correlations with MPEs and their strength. The authors also investigated how EEG, reaction time, and pupil responses correlated with one another, providing further insight into the mechanism underlying the response to MPEs. Together, the study points toward multiple control and attention mechanisms involved in MPE response and memory.

Strengths:

The study has a clear behavioral paradigm with multiple measures - behavioral, EEG, and pupillometry that offer an investigation into different aspects of MPE response and memory.

The study is also very comprehensive in looking at multiple phases in processing MPEs: the prediction phase (prior to the violation), the response to MPEs, and subsequent memory of MPEs, all within one study. Specifically, the link between neural mechanisms and subsequent memory is a major advancement, as most prior studies did not include this component. Mechanisms underlying subsequent memory of MPEs are theoretically important, as a primary function of MPEs is to promote learning and memory. As the authors mention, the different neural and pupillary signals are not robustly correlated, suggesting multiple mechanisms underlying MPE detections, which is interesting, offers avenues for future research, and can facilitate a better theory of how MPEs are processed in the brain. Finally, the decomposition of pupil response into different components and their correlation with behavior (RT during match/MPE detection) is interesting.

Reviewer #1 (Public review):

This manuscript is very interesting and timely. By introducing the critical effects of desolvation barriers and solvent (water)-separated minima into the implicit-solvent potentials (of mean force, PMFs) for coarse-grained molecular dynamics simulations of biomolecular liquid-liquid phase separation (LLPS), this work fills a gap that should be apparent to researchers of protein folding in the past couple of decades but has so far escaped deserved attention such that these basic features of aqueous solvation have seldom, though not never, been invoked in recent studies of biomolecular condensates. Although the present paper deals almost exclusively with homopolymers, this work can be a foundation for the future development of a new, more physical coarse-grained interaction schemes for simulating amino acid sequence-dependent effects, which I presume is the authors' ongoing or next endeavor. The results presented in this manuscript are highly valuable.

However, there is room for improvement in the authors' description of (i) the broader impact of effects of desolvation barrier and solvent-separated minimum in the thermodynamics of biomolecular condensates, especially with regard to the ramifications on hydrostatic pressure-dependent effects; (ii) the physical implication of using a 20-parameter hydropathy scale rather than a 210-parameter pairwise amino acid interaction scheme; and (iii) temperature-dependent effects, including the authors' discussion of "enthalpic" and "entropic" contributions. In all these aspects, the authors' discussion should be put in a more comprehensive context of the existing literature. At a few other places, description of the methods and results should be clarified as well.

Comments on revised version

The authors have thoroughly and adequately addressed all my previous concerns and suggestions. The manuscript is now significantly improved in terms of clarity and proper placement in the context of prior works on desolvation effects in protein conformations.

Reviewer #2 (Public review):

Summary:

This manuscript addresses an important and timely question in the molecular simulation of biomolecular condensates. Most residue-level coarse-grained models used for IDP phase separation employ implicit solvent and represent effective interactions through relatively simple pairwise potentials. While these models have been very useful, they usually do not explicitly distinguish direct contacts from solvent-separated interactions, nor do they include an energetic barrier associated with water removal. This manuscript attempts to address that limitation by introducing desolvation-inspired terms into coarse-grained models and examining their consequences for phase behavior, chain conformations, dense-phase packing, and dynamics.

The central idea is physically well motivated. Using a simple homopolymer model, the authors show that increasing the desolvation barrier suppresses phase separation, whereas stabilizing solvent-separated contacts enhances phase separation. They further show that solvent-separated interactions can reduce dense-phase over-compaction, which is a meaningful result given the known challenges in obtaining both accurate single-chain dimensions and realistic dense-phase properties from the same coarse-grained model. The finding that desolvation-like terms can reshape dense-phase packing without simply rescaling the overall interaction strength is interesting and could be useful for future model development. I also found the attempt to connect conformational changes across dilute and dense phases with thermal distance from the critical point to be intriguing. The dynamic analysis, including the FRAP-like simulations and the discussion of kinetic arrest during coarsening, adds another useful dimension to the work.

Overall, I think this is a useful and potentially important contribution.

Comments on revised version.

The authors have addressed my earlier comment regarding conformational changes between the dilute and condensed phases. One small additional suggestion is that they may find two related studies useful in this context: Devarajan et al., Nature Communications (2024), on relationships between dilute-phase conformations and condensate material properties, and Wang et al., Chemical Science (2024), which examines sequence-dependent conformational changes during condensation for both model polyampholyte sequences and naturally occurring IDPs. These studies may provide some complementary context for the discussion. This is simply a literature suggestion and does not affect my overall assessment of the revised manuscript.

Reviewer #1 (Public review):

This paper reports a previously unrecognized mechanism by which platelets compact fibrin fibers during clot retraction. Rather than simply pulling on fibers, the authors propose that platelets generate swirling motions that wind and loop fibrin into dense structures.

While the results are intriguing, the underlying physical mechanism remains unexplained. In particular, it is unclear how platelets generate swirling motion capable of inducing fibrin coiling, especially when suspended in 3d fibrin mesh. This raises concerns about the conclusions. Also, does fibrin have inherent chirality or structural asymmetry that could promote coiling independently of platelet activity? Furthermore, platelet retraction typically involves platelet aggregation rather than isolated cells, and it is unclear how fibrin coiling would proceed in clustered platelets.

Comments on revised version.

The authors have significantly improved the manuscript and enhanced the presentation of the results. In my opinion, the physical mechanism responsible for the compaction of fibers into the coiled structures caging platelets remains somewhat elusive. Nevertheless, I find the results convincing, and I believe the study will make a valuable contribution to the field.

Reviewer #2 (Public review):

Summary:

Grichine et al. investigate platelet-mediated fibrin compaction using human donor platelets and propose a novel mechanistic model in which platelets generate contractile forces and wind fibrin fibres into compact, coiled structures. Using a combination of 2D spreading assays, 3D clot imaging via expansion microscopy, live-cell imaging, and computational modelling, the authors present evidence of cage-like fibrin architectures, coiled fibre morphologies, and platelet-centred "rosette" structures that are present during fibre compaction. They suggest the involvement of actomyosin in fibre compaction and, overall, the study addresses an important and longstanding question in thrombosis and haemostasis while offering a conceptually novel perspective on clot compaction.

Strengths:

The integration of multiple imaging modalities is a notable strength. In particular, the 2D fibre-retraction assay provides a useful model for understanding the spatiotemporal dynamics of platelet-mediated fibrin compaction, which could be applied to other systems and may yield detailed mechanistic insights into biological processes. The live-imaging approaches are particularly well executed and provide valuable dynamic insights into fibre accumulation and compaction.

Weaknesses:

The primary weakness of the paper is the absence of direct evidence demonstrating the mechanism of fibre compaction via cytoskeletal swirling. Consequently, the relationship between platelet dynamics and fibrin organisation, including coordinated measurements of platelet motion and fibre rearrangement, is not directly assessed (perhaps due to technical barriers). However, the paper does provide solid evidence through myosin inhibition and computational modelling, demonstrating how platelets might mediate fibre compaction.

Comments on revised version.

Overall, the study addresses an important question in thrombosis and haemostasis and introduces a potentially impactful conceptual framework for understanding clot compaction. The imaging approaches and datasets presented will be valuable to the community, particularly to researchers interested in platelet mechanics and fibrin organisation. The possibility that fibres can be compacted extracellularly through cytoskeletal swirling represents a compelling and relatively unexplored mechanism. Therefore, this paper does a good job of establishing a thought-provoking mechanism with solid supporting evidence, although a direct demonstration of the underlying molecular mechanism requires further investigation.

Reviewer #3 (Public review):

Summary:

This work aims to understand the mechanisms that platelets use to interact with and compact fibrin fibers during clot formation. This is an important process during wound healing and recent work has demonstrated that platelets play a critical role in generating the force required to drive accumulation of fibrin. The authors argue that current models are insufficient to account for the observed reduction in clot volume and propose that platelets actively 'wind-up' these fibers by undergoing myosin-dependent rotation. While interesting, the experiments performed by the authors do not directly test this mechanism and further evidence is required to support their claims.

Weaknesses:

(1) The motivation to switch from the system used in Figure 1 and 2 to the '2D fiber-retraction assay' is not clear. While the authors state that this system has 'reduced complexity' the differences between these assays appears to disrupt the 'cage-like' organization of fibrin around platelets shown in Figure 1 and 2 (compare images in Figure 2 with those in Figure 4). An in-depth comparison of two methods is needed to support the conclusions from the 2D system. Furthermore, the change in plasma volume (Figure 2 vs Figure 7) should also be tested - the authors state that this increases fibrin fiber formation, but this is not quantified or demonstrated in the figures. Notably, this appears to change the morphology of the fibrin fibers shown (comparing Figure 2 and Figure 7).

(2) It is unclear how the classification of platelets as 'fiber-winding' versus 'fiber compaction' differs in Figure 2. The criteria used for these classifications should be stated. Further, it seems premature to characterize fibers as wound without having established this earlier in the manuscript.

(3) Is the 'gearwheel' different from the 'cage' of fibrin fibers? They appear similar, but it is difficult to distinguish between these with only qualitative descriptions of these phenotypes.

(4) The quantification of platelet extensions in Figure 9 is confusing. While the those in 9A are clear, those in 9B are not. For instance, what is the difference between #7 and #8 in the middle panel of 9B? It does not seem like #8 is labeling an extension.

(5) It is unclear what the modeling accomplishes as there is no comparison between the results of these simulations and their experiments.

(6) The data presented in Figure 12 provides the most direct support for their mechanism, but falls short of directly testing their claims. These experiments should be repeated to include blebbistatin to test the contribution of myosin and include quantitative rather than qualitative comparisons of these experiments.

Comments on revised version:

The manuscript is substantially improved in clarity and organization. The authors have adequately addressed most of my concerns regarding presentation and interpretation through revisions to the text and figures. However, my primary mechanistic concerns remain unresolved. Although the proposed model is now presented more cautiously, the revised manuscript still does not directly test the central mechanism, and the conclusions therefore remain insufficiently supported.

Reviewer #1 (Public review):

Summary:

The authors combine discriminative auditory fear conditioning with longitudinal in vivo calcium imaging to ask how prelimbic (PL) representations of learned and generalized threat evolve across recent and remote memory time points. Using two different CS+ frequencies and a no-shock control group, they report that PL population activity tracks graded behavioral generalization, that population similarity is highest for tones eliciting strong threat responding, and that distinct subnetworks can be identified that appear to encode tone-specific sensory features versus learned threat-related response structure.

To my knowledge, this may be the first study to comprehensively examine neural encoding of fear generalization in prelimbic cortex (PL). The manuscript is ambitious and technically interesting, and several aspects are potentially important. In particular, the suggestion that neurons showing graded, learning-related response patterns become selectively stabilized over time is intriguing. The inclusion of two CS+ training conditions and a no-shock control also strengthens the case that at least some of the reported effects are related to associative learning rather than simple sensory differences. However, in its current form, the manuscript does not yet fully support the strength of the conceptual claims. Several issues limit confidence in the interpretation, including the possibility that repeated testing itself contributes to changes across days, uncertainty about the relationship between neural activity and freezing behavior, limited quantitative documentation of longitudinal cell registration, and a number of problems in figure clarity and statistical framing. Overall, the study contains promising observations, but the claims should be narrowed, and several analyses or controls would be needed to fully support the proposed framework.

Comments on revised version.

The authors have addressed my previous concerns well, and the revised manuscript is substantially improved. In particular, the additional analyses strengthen the conclusion that prelimbic cortical activity reflects learned threat value rather than simply freezing behavior, while the revised framing and additional controls clarify the interpretation of the longitudinal neural dynamics. This paper represents an important contribution to our understanding of the neural mechanisms supporting aversive learning, memory, and generalization.

Reviewer #2 (Public review):

The authors have substantially revised the paper in response to the original review, which is greatly appreciated. It is clear that it will eventually make a nice contribution to the literature. This being said, the following points are somewhere between major and minor in term of their implications for interpretation of the study results. If they were to be addressed, the paper would be again improved.

There are a few remnants of the past language that are not helpful re interpretation of the study results: 1) "Specifically, the observed population gradients could emerge either from the pooled activity of frequency-selective neurons that respond to individual tones or from neuronal subpopulations that integrate information across tones to encode their learned threat-value."; and 2) "Together, these findings suggest that the PL integrates sensory similarity with learned threat value to generate stable representations that support adaptive generalization and discrimination." Neither of these statement follows what has been shown in the study, even with inclusion of the results from the GLM analysis (see point 4 below).

(1) This paragraph in the Discussion is difficult to follow: "Generalization has traditionally been explained by perceptual similarity (Shepard, 1987), whereby stimuli resembling a conditioned cue recruit overlapping sensory representations and evoke similar behavioral responses (Corches et al., 2019; Grosso et al., 2018). Although perceptual similarity clearly influences the extent of generalization, accumulating evidence indicates that it cannot fully account for generalized responding (Verra et al., 2026). More recent frameworks propose that associative learning assigns learned value to novel stimuli by integrating their sensory similarity with previous experience, allowing behavior to scale according to predicted biological significance (Verra et al., 2026; Zaman et al., 2023). Our findings provide a neural framework consistent with these ideas. Sensory similarity promoted consistent neuronal population responses across tones, whereas associative learning organized these responses into graded representations that tracked learned threat value across the stimulus continuum. Thus, sensory similarity appears to define the neuronal substrate upon which associative learning constructs value-based representations that support graded behavioral generalization."

While the revisions have removed the many unnecessary references to inference and integration, this paragraph seems like it is adhering to the original idea of how the authors wished to present their work. If the authors wished to talk about something more than perceptual similarity in the context of generalization, they should have used a task that lends itself to a more-than-perceptual-similarity explanation. Again, the inclusion of the GLM analysis is suggestive for some of what the authors wish to say, but doesn't justify the statements that: "Sensory similarity promoted consistent neuronal population responses across tones, whereas associative learning organized these responses into graded representations that tracked learned threat value across the stimulus continuum." In short, the analysis does not substitute for the design that could have and should have been used to assess learned threat value independently of sensory similarity.

(2) The next paragraph in the Discussion is also confusing. "Such reorganization has been proposed to provide flexibility by allowing new information to be incorporated into existing cortical representations while preserving stable behavioral performance (Mau et al., 2020; Zaki & Cai, 2024). Several mechanisms could contribute to this turnover, including systems consolidation, retrieval-induced reconsolidation or memory updating, and repeated nonreinforced stimulus exposure (Lacagnina et al., 2019; Mau et al., 2020; Sangha, 2015; Zaki & Cai, 2024). Although our experiments cannot distinguish between the first two possibilities, the behavioral data argue against extinction as the primary explanation. Extinction is generally associated with the formation of new CS+-safety associations (Bouton et al., 2021), whereas discrimination ratios increased across retrieval sessions, indicating that animals progressively improved their discrimination between threat-associated and safe stimuli rather than acquiring generalized safety responses. This pattern is consistent with previous work showing that discrimination learning sharpens stimulus representations and narrows behavioral generalization gradients (Dunsmoor & LaBar, 2013; Herzog et al., 2021; Jenkins & Harrison, 1960; Lommen et al., 2017). Importantly, turnover was not uniform across the population. Graded neurons retained remarkably consistent response profiles across retrieval sessions, and their activity remained more strongly associated with learned threat value than with freezing behavior. These observations indicate that stable components of the population code can coexist with extensive reorganization of surrounding neuronal ensembles."

The issue with repeated testing is *not* caused by extinction per se. The issue is that non-reinforcement across the repeated testing should differentially affect the CS+ and CS-. Specifically, it should extinguish responding to the CS- stimulus at a rate that matches its distance from the CS+, thereby sharpening the CS+ versus CS- discrimination in precisely the ways that have been observed. Ergo, the repeated testing *is* a problem for inferences that might be drawn about the way that generalization gradients change with time; and *is* a problem for statements regarding "dynamic reorganization of cortical activity patterns over time." There is nothing in the study that allows one to comment on the reorganization of cortical activity patterns over time. The reorganization can and should be attributed to the repeated testing, which is confounded with time. Nonetheless, the reorganization must be due to the repeated testing and NOT time as the present findings are inconsistent with the well-documented broadening of generalization gradients with time.

(3) In the next paragraph, the authors state: "At the same time, narrower generalization gradients and improved discrimination across retrieval sessions suggests ongoing memory updating. These observations are consistent with contemporary theories proposing that systems consolidation and retrieval-dependent updating are complementary processes through which memories continue to evolve after learning (Mau et al., 2020; Tome et al., 2024; Zaki & Cai, 2024)."

In general, I'm not sure why one would invoke systems consolidation or retrieval-induced reconsolidation as an explanation for any of the present findings: they are not explanations of much at all. In this specific text, the authors seem to be implying an updating process that occurs independently of what is learned across the repeated sessions of testing. Why? The changes that occur in the behaviour and neuronal representations are perfectly explicable in terms of additional learning that occurs - of the sort that I hope to have made clear in my previous comment. Why invoke more than what is needed to explain the observed pattern of results?

(4) Re the GLM analysis - The authors write that: "the fact that the GLM analysis indicates that these neurons reflect learned threat value more than freezing behavior, suggests that they encode an abstract property of the learned stimulus rather than simply mirroring behavioral output."

This is fine if freezing fully indexes the state of conditioned fear and there are no other behaviours in which animals express their fear. If, however, fear is expressed in a range of other behaviours that are likely coordinated by the PL (e.g., startle, vigilance, scanning, orienting to source of danger), this interpretation of the GLM analysis is unwarranted. This is an important point and would be worth noting somewhere in the paragraph where the statement appears.

Reviewer #3 (Public review):

Summary:

Normandin et al. explore the coding of stimuli predicting an aversive event in the prelimbic cortex. Stimuli could either be explicitly paired, explicitly unpaired, or novel but with an inferred association with the aversive event (generalization). Long-term tracking of GCaMP positive neurons allowed them to examine how coding evolves out to a month following training. In general, they found two types of ensemble codes. One was ensembles coding for each stimulus independently, but with enhanced responding to the one eliciting a freezing response. The other was ensembles that responded to all stimuli in proportion to their similarity to the stimulus paired with the aversive event, either increasing or decreasing their activation with the degree of freezing elicited by a stimulus. Importantly, this second set of ensembles was more stable across days, potentially providing a memory trace.

Strengths:

(1) The authors track ensembles in prelimbic cortex over long time scales, providing valuable information on the consolidation of neural codes.

(2) Neural coding of generalization is examined, which is under examined in the field.

Comments on revised version.

The authors have convincingly and thoroughly addressed my concerns. I have no further issues regarding this study.

Reviewer #1 (Public review):

Summary:

This paper characterises the physiological and computational underpinnings of the accumulation of intermittent glimpses of sensory evidence, with a focus on the centroparietal positivity and motor beta lateralization. The main finding is that the centroparietal positivity builds up during evidence accumulation but falls back to baseline during gaps, while motor beta lateralization maintains a continuous a sustained representation throughout the gap and until response.

Strengths:

- Elegant combination of electroencephalography and computational modelling.<br /> - Innovative task design, including parametric manipulation of gap duration.<br /> - The authors describe results of two separate experiments, with very similar results, in effect providing an internal replication.

Weaknesses:

- In their response to the reviewers, the authors now include a figure illustrating the relationship between the centroparietal positivity and motor beta lateralisation. However, in the absence of statistical analyses, it remains difficult to draw firm conclusions about this relationship.

- The paper does not provide an exhaustive characterisation across sensors and frequency bands. However, as the data are publicly available, these questions could be addressed in future work.

Reviewer #2 (Public review):

Summary:

This manuscript examines decision-making in a context where the information for the decision is not continuous, but separated by a short temporal gap. The authors use a standard motion direction discrimination task over two discrete dot motion pulses (but unlike previous experiments, fill the gaps in evidence with 0-coherence random dot motion of differently coloured dots). Previous studies using this task (Kiani et al., 2013; Tohidi-Moghaddam et al., 2019; Azizi et al., 2021; 2023) or other discrete sample stimuli (Cheadle et al., 2014; Wyart et al., 2015; Golmohamadian et al., 2025) have shown decision-makers to integrate evidence from multiple samples (although with some flexible weighting on each sample). In this experiment, decision-makers tended not to use the second motion pulse for their decision. This allows the separation of neural signatures of momentary decision-evidence samples from the accumulated decision-evidence. In this context, classic electroencephalography signatures of accumulated decision-evidence (central-parietal positivity) are shown to reflect the momentary decision-evidence samples.

Strengths:

The authors present an excellent analysis of the data in support of their findings. In terms of proportion correct, participants show poorer performance than predicted if assuming both evidence samples were integrated perfectly. A regression analysis suggested a weaker weight on the second pulse, and in line with this, the authors show an effect of the order of pulse strength that is reversed compared to previous studies: A stronger second pulse resulted in worse performance than a stronger first pulse (this is in line with the visual condition reported in Golmohamadian et al., 2025). The authors also show smaller changes in electrophysiological signatures of decision-making (central parietal positivity, and lateralised motor beta power) in response to the second pulse. The authors describe these findings with a computational model which allows for early decision-commitment, meaning the second pulse is ignored on the majority of trials. The model-predicted electrophysiological components describe the data well. Some flexible weighting of the second pulse also described the data well (in line with previous studies), but this explanation suffers from additional model complexity. In particular, this analysis of model-predicted electrophysiology is impressive in providing simple and clear predictions for understanding the data.

Weaknesses:

Behaviour in this experiment is different from previous experiments which use very similar designs (Kiani et al., 2013; Tohidi-Moghaddam et al., 2019; Azizi et al., 2021; 2023). The authors provide some possible explanations for this in the discussion. Overall performance in this experiment was much worse than previous experiments: Participants achieved ~85% correct following 400 ms of 33 - 45% coherent motion. In previous work, performance was ~90% correct following 240ms of 12.8% coherent motion. A second weakness is that, while bounded model can describe the data in this manuscript, it cannot explain the data from previous experiments showing a stronger weight on the second pulse.

Reviewer #1 (Public review):

This work by Antonnen et al. was triggered by claims of auditory-mediated effects on altricial avian embryos which were published without any direct evidence that the relevant parental vocalizations were actually heard. I agree with Anttonen et al. that, based on the available evidence about avian auditory development, those claims are highly speculative and therefore necessitate more direct experimental verification.

Attonen et al. have embarked on a comprehensive series of experiments to

(1) Better characterize acoustically the relevant parental vocalizations (heat whistles; in a separate preprint, not reviewed here)

(2) Characterize the auditory sensitivity of zebra finches at various stages of their posthatching development. Despite the long-standing importance of the zebra finch as a songbird model in neuroethology of learned vocalizations, the auditory development of the species had not been studied so far.

(3) Explore an alternative hypothesis of how the parental vocalizations might be perceived.

The principal method used here is the non-invasive recording of ABR (auditory brainstem response), a standard neurophysiological method in auditory research. The click-evoked ABR provides a quick and objective assessment of basic hearing sensitivity that does not require animal training. Weaknesses of the technique include its limited frequency specificity and low signal-to-noise ratio. The authors are experienced with ABR measurements and well aware of those issues. ABR responses in zebra finches are shown to gradually appear during the first week posthatching and to mature in subsequent weeks, consistent with the auditory development in other altricial bird species studied previously. When matching the acoustic properties of parental heat whistles and auditory sensitivities, hearing of the parental heat whistles by zebra finch hatchlings was convincingly excluded. Although not directly measured, this also convincingly extrapolates to zebra finch embryos. Finally, the authors tested the hypothesis that parental heat whistles could induce perceptible vibrations of the egg and thus stimulate the embryo via a different modality. The method used here was laser doppler vibrometry, an appropriate, state-of-the-art technique that the authors also have proven experience with. The induced vibrations were shown to be several orders of magnitude below known vibrotactile sensitivities in mammals and birds. Thus, although zebra finch vibrotactile thresholds were not obtained directly, the hypothesis of vibrotactile perception of parental heat whistles by zebra finch embryos could also be rejected convincingly.

In summary, even when considering some weaknesses of the techniques (which the authors are aware of), the conclusions of the paper are well supported: Auditory and/or vibration perception of parental heat whistles can be excluded as an explanation for previous reports of developmental programming for high ambient temperatures. As a constructive suggestion towards resolving the apparent paradox, the authors recommend to repeat some of the crucial, previous playback experiments at lower sound levels that better match the natural parental vocalizations.

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 has been a series of studies published in high profile journals that have presumably showed 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 pre-natal 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 improbably 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 you don't discuss potential differences between behavioral audiograms and ABRs. Optimally, one would need to repeat the work of Okanoya and Dooling with your set up 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 that 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 (form pips to bursts) affects the effective bandwidth of the stimulus. I believe that you could give an estimate of this effective bandwidth given what is know from bird auditory filters. I think that this estimate could be useful to compare to the effective bandwidth of the heat-call which you can now also estimate.

(2) Fig 5b. label the green and pink areas as song and heat-call spectrum. Also note that in the legend you 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 you meant. I agree that 1-4 kHz is the best frequency sensitivity of zebra finches but you probably meant green == "song frequency spectrum" and pink == "heat call spectrum". In either case the figure and the legend need clarification.

(3) Fig 5c. Here also, I would change the song and heat-call labels to "song spectrum", "heat call spectrum". You don't want readers to think you 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 your description of the stimulus, you describe "5ms long tone bursts" but these are the tone pips in the main part of the manuscript. Use the same terms.

Comments on revisions:

In the latest version of this manuscript, Anntonen et al have diligently addressed all the issues raised by the reviewers. As I mentioned in our discussions among reviewers, it is impossible to "prove" a null hypothesis and both methods and experimental design could always be improved. At this stage however, they provide convincing evidence that the sound intensity of heat calls are below the hearing thresholds of zebra finch chicks.

Reviewer #3 (Public review):

Summary

This study aims to contest recent findings that prenatal exposure to natural sounds and anthropogenic noise before hatching affects development and fitness in an altricial songbird. To this aim, it attempts to estimate hearing capacities of zebra finch nestlings. It first uses responses to clicks in nestlings and adults to estimate differences in hearing thresholds but uses experimental parameters that systematically lower nestling responses. It then measures responses to tones but restrict nestling data to a protocol (long tones) that failed in adults; response to tones with a correct protocol (short tones) is repeated in adults only. Thirdly, it includes data on loud airborne sound making eggs vibrate, even though this has no relevance to embryonic vibration perception by direct contact with the incubating parent or in incubators. Lastly, it includes a lengthy discussion on how these results, even though inaccurate or incorrect, would show that zebra finch nestlings and embryos are "functionally deaf". It fails to note that even if the experiment had been performed correctly and still failed to detect an auditory response in 2 day hatchlings - which is unlikely given the above and findings in other songbirds - this would not somehow eliminate the developmental effects of prenatal sounds that have been empirically demonstrated.

Strength:

The study is not performed adequately to bring reliable answers, but it addresses the important topic of hearing development in altricial songbirds and the long-held (but untested) assumption that altricial avian embryos cannot hear. More broadly, there is a need to reassess avian auditory perception - and the methodological approaches to measure it - given the accumulating evidence that some bird species respond to high frequency biological sounds beyond their known hearing range.

Weaknesses:

The study presents many experimental flaws that specifically compromise response detection in immature animals in the first experiment, and data from the remaining two experiments are invalid. The revision did not fix any of these issues.

i) Response to clicks, Fig 1: Unlike what the revision claims, the deviations from validated protocols (too rapid stimulation, too few measurements, low temperature, reliance on clicks only) do lead to a potentially large underestimation of nestling hearing sensitivity. Calculation and new data trying to show that these deviations would not matter are wrong or insufficient. Even without strict conventions on ABR methodology, it is striking that every single experimental choice made here i) greatly differs from other avian studies and ii) reduces - rather than maximises - response detection, specifically for low amplitude signals (as in nestlings or near thresholds).

ii) Response to frequency tones, Fig 2: The experiment on frequency sensitivity (long tone burst) failed in adults (positive control) with 0 to only about half of the adults responding (Fig S1), and sensitivity underestimated by 30dB (Fig2). Measures with a failed positive control are invalid, even if the overall pattern of the few data points obtained in nestlings vaguely resemble (but does not match) expectations. That the experiment was repeated in adults with a correct protocol (short tone pips) - but not in nestlings - is highly misleading.

iii) Attempts to validate the protocols above by comparing to published adult values are meaningless (response A.3.1; Fig 5). The one experiment being compared (short tones) was only performed in adults in this study. This cannot validate results obtained by different methodologies in nestlings, for responses to clicks or long tones.

iv) Vibrations: No previous results on the effect of zebra finch heat calls on development rely on the hypothesis or assumption that airborne sound from heat calls makes eggs vibrate. This idea is solely attributable to the authors of the preprint, and is not biologically or experimentally realistic. All speculations from this experiment (Fig3) on vibration perception by embryos or heat call effects are meaningless.

v) Writing and presentation: The text throughout is highly misinformative for non-specialists or any reader not carefully inspecting figures (including in supplementary material) and methods. The confusion is greatly aggravated in the (6-page long) discussion which i) fails to recognise and account for the study shortcomings, and instead ii) greatly overstates the results and what they mean, and iii) misrepresents current knowledge by excluding highly relevant studies showing evidence of early sound perception in embryos and hatchlings, and introducing many errors in the presentation of published papers. This creates an illusion of a strong mismatch between heat-calls and zebra finch sensory capacities, for which the study actually does not provide any evidence for, and which is extremely unlikely to exist.

vi) The revision did not address any of the major flaws of the study outlined above (see detailed assessment below). In particular,<br /> ** For point i):<br /> - estimations for the effect of having done too few (400) measurements are wrong - the effect on hearing thresholds cannot be calculated, but would be much greater than 4dB with the expected 37% noise reduction with the standard 1000 sweeps;

- the new data provided does not measure the impact of high stimulus rate, and measures on adults largely underestimate effects on nestling response;

- body temperature, now provided in the revision, is at the lowest extreme for the species, which may increase hearing thresholds;

- tones do elicit a stronger and earlier response than clicks. Whether this is related to stimulus duration does not change the fact that clicks underestimate hearing thresholds, and delay hearing onset by several days.<br /> ** For points ii) and iv):<br /> No new data or any valid explanation was provided in the revision. It is still the case that nestling frequency responses were obtained with an experiment where the positive control failed; and the vibrating egg experiment is irrelevant to vibration perception in embryos and any observed effects of heat calls on development.<br /> ** The revision greatly lengthens the speculations about heat call perception, based on inaccurate or totally incorrect data.

Conclusion and impact:<br /> i) Overall, the study fails to provide any reliable estimate of zebra finch nestling hearing capacities: it underestimates hearing onsets and thresholds (clicks) and gives no information on nestling frequency sensitivity. It is extremely likely that a better designed ABR experiment, or a more sensitive methodology (e.g. electrophysiology), would have detected a response in 2 day-old nestlings, as in other songbirds. The conclusion of "deafness" in hatchlings (or embryos, which were not tested) is clearly unsupported.<br /> If zebra finch hatchlings were clearly deaf, a well-designed study would have shown this a lot more convincingly.

ii) The data on adults in not new (3 prior studies) - although this study generally underestimates zebra finch high frequency sensitivity. The presentation in relation to heat-calls is flawed: true values of heat-call frequency range and sound levels (>6kHz at 45dB) fall within the adult hearing range.

iii) Without any new evidence, this study does not progress our understanding of heat-call and noise impact on development. Exactly the same issue remains: that heat-call and noise effects on development contradict the general VIEW on hearing ontogeny in altricial birds. But we have learnt nothing from this study on hearing ontogeny or frequency sensitivity. The study provides no reliable neuroscience data to advance the debate.

iv) The largest section of the preprint is a highly speculative discussion, based on erroneous data and wrong interpretations, as well as a misrepresentation of what is known. That these issues would not be recognised is - in my view - of serious concern.

Detailed assessment:

The summary by the authors of my major concerns (R3.A0) is incorrect and misreport many of my statements, without giving any meaningful answers. I will not engage in such discussion.

My actual three major concerns do remain:

(1) Results on Fig 1 overestimate hearing onset and thresholds: All experimental parameters chosen to test responses to clicks are known to lower detection. From their cumulative impact, there is absolutely no doubt that the data in Fig 1 underestimate hearing capacities, and disproportionately so in nestlings compared to adults. Therefore, no quantitative estimate of nestling hearing threshold, absolute or relative (i.e. the estimated "54dB difference"), can be taken from this study. The age of hearing onset based on clicks (4 day old) is also wrong.

(2) All results on Fig 2 are false: 40 to 100% of adults (positive control) failed to respond within their normal hearing range (Fig S1). Data on nestling frequency sensitivity using this methodology (Fig 2) are clearly invalid.

(3) All results on Fig 3 are irrelevant: they assume zebra finch parents are hoovering in front of their nest while heat-calling rather than incubating their eggs, which is nonsense. Any speculation on the role of bone-conduction or vibrotactile stimulation for embryonic heat-call detection is simply unfounded.

The authors' responses to these comments are largely mistaken (see below), and do not change the 3 facts stated above. Overall, the data produced are unreliable, and so are the interpretations and conclusions.<br /> The conclusions that i) heat-calls fall outside of adult hearing range and ii) young nestlings (and embryos) are deaf, are both incorrect. The study provides no actual estimate of nestling hearing and how far off their hearing range heat-calls fall.

(1) Responses to clicks underestimate hearing abilities, specifically in nestlings.

(i) DISPROPORTIONATE EFFECT OF PROTOCOL ON NESTLINGS: As reported in other avian studies (e.g. Brittan Powell et al 2004), because of their immature neural system, nestlings show low amplitude waveforms compared to adults. This occurs even with sound much louder than their hearing threshold. For example here, 8 day old nestlings show waveforms of only low amplitude at 95dB, even though they respond to sound 40dB softer, at 55dB (Fig 1H).

This characteristic of nestling waveforms means that:<br /> - nestling responses are harder to detect,<br /> - nestling responses are more easily attenuated below the detection criteria (>2 S/N),<br /> - a low amplitude response in nestlings at a given sound level does not predict that softer sounds will not be perceived by the animal.

Any deviation in protocol that attenuates waveform amplitude will therefore disproportionately affect nestling thresholds (and artificially lead to the "54dB" estimate).<br /> Even without universal standards (resp R3.A1.1), knowing this, the protocol should be adjusted to maximise response detection. This study does exactly the opposite.

(ii) INSUFFICIENT MEASUREMENTS: using only 400 sweeps, rather than the typical 1000 sweeps, reduces response detection, especially in nestlings.

- The claim that using 1000 sweeps would only decrease the hearing threshold by 4dB (response A3.2; ms L530) is false:<br /> - Based on the square root relationship mentioned by the authors, using 1000 averages instead of 400 would improve the signal-to-noise ratio by 37%, which would allow detecting many small amplitude waves which are currently hidden in the abnormally high noise.<br /> - Lowering the noise floor level by 4dB does not mean that the hearing threshold would only decrease by 4dB. The improvement in hearing threshold would be much greater, especially in nestlings.

(iii) UNSUITABLY HIGH STIMULATION RATE: the new data on pairs of clicks greatly underestimate the attenuation by high stimulation rates, and so do adult measurements compared to nestlings'.<br /> - the click rate used in this study (25 clicks per second) is 5 to 25 times faster than most previous studies in young birds (e.g. Saunders et al 1973, 1974: 1 stim/sec or less; Katayama 1985: 3.3 clicks/sec; Brittan-Powell et al 2004: 4 stim/sec), and 6 times faster than zebra finch heat-calls.<br /> - responses to pairs of clicks (new data in Fig S3; L 543-552, response A3.3) does not measure the response dampening caused by high stimulation rates. Response attenuation (adaptation) after a single click is much weaker than after a train of 400 consecutive clicks (or even just 30). This paired-click measure ignores the cumulative attenuation observed with many consecutive stimuli. Paired-click paradigm is used to measure immediate refractoriness for other purposes (e.g. temporal resolution, diagnosis tool) but does not replicate high stimulation rates.<br /> It is unclear why the authors chose to use this weak approximation rather than simply replicating the measurements at the same slow rate as in other avian studies. This would have given a straightforward answer, comparable to previous studies that have demonstrated the detrimental impact of fast rate on response strength by directly comparing responses to different stimulation rates (e.g. Saunders et al 1973; Brittan-Powell et al 2004).<br /> - Adults are less sensitive to high stimulation rates than immature individuals (e.g. Saunders et al 1973; Khayutin 1985; Brittan-Powell et al 2004 and 6 references cited therein). Effects of fast rate in adults (new data in Fig S3) therefore largely underestimate effects on nestlings (not measured), and the high stimulation rate used in this study increases the relative difference between nestlings and adults.<br /> - Given the 2 points above, it is incorrect to conclude from this new data that the high stimulation rate used had "no effect on ABR amplitude or thresholds" (responses A3.3 L551). Instead, given that 40ms (i.e. interval for 25 clicks/ sec) is at the limit of what adults can handle after a single click, this new data does confirm that the stimulation rate is indeed too high and underestimates hearing in nestlings (and adults to a lesser extent).

(iv) LOW BODY TEMPERATURE can reduce ABR response.<br /> - The average body temperature (39.5C) now provided in the revised manuscript (response A2) is at the lowest extreme of the range for zebra finches. The normal average body temperature for zebra finches is 41C at low ambient temperature, rising to 43-44C at high ambient temperatures (when heat-calls would be produced). This value of 41C is consistent across many studies in wild and domestic zebra finches (e.g. Wojciechowski et al 2020 [avr 41C at 23C]; Udino and Mariette 2022 [avg 41, min=40C at 32C]; Bech and Midtgard 1981 [avr ~41C]; Pessato et al 2022 avg=41C at 27C]). The only study reporting a body temperature average as low as 39C (Cooper et al 2020) was indeed under hypothermic conditions, obtained in adult zebra finches under extreme fasting conditions (17hrs of food deprivation), at ambient temperature below thermoneutrality, during the night (i.e. during "nocturnal hypothermia", when bird body temperature is normally lower).<br /> Therefore 39.5C does corresponds to hypothermic conditions for most individuals. While this body temperature remains considerably higher than that used experimentally to supress hearing response, using a below-normal body temperature, added to other factors, may lower wave amplitude and therefore increase hearing threshold estimates.

(v) CLICKS UNDERESTIMATE HEARING ONSETS<br /> - My statement that, compared to tones, clicks elicit a smaller response, at a later age, is correct (Saunders et al 1973; Brittan-Powell et al 2004).<br /> - It does not matter whether this is due to differences in stimulation duration (response R3.A2.1), since clicks are always much shorter than tones. What matters is that hearing onset based on responses to clicks has been found to underestimate the earliest age at which an auditory response can be obtained by several days (Saunders et al 1973).<br /> - Without any valid nestling data for tones (see below), this study, based on clicks only, does not provide the true age of hearing onset.<br /> - The suggestion of using 170dB clicks (response R3.A2.1) is very odd. The correct approach would have been to use a correct protocol for tones in nestlings, rather than solely correcting it for adults (see below).

(vi) CONFUSING INTERPRETATION OF WAVE AMPLITUDE AND LATENCY<br /> - the text implies throughout that nestlings lacking an adult-like amplitude and latency is a sign of poor hearing (e.g. L122 "ABR wave I gradually reaches maturity 25 days after hatching").<br /> - It should be clarified that this is a characteristic of immature systems but does mean these nestlings do not hear. For example, this characteristic persists even in 10d old nestlings which have similar hearing thresholds to adults.

(2). Results on nestling frequency sensitivity are invalid. Using long (25ms) tones with subdermal electrodes is incorrect, and not used by anyone other than the authors. The failure to repeat the experiment with a correct protocol (5ms tones) in nestlings is misleading:

(i) When 60% of 4-day old chicks respond to clicks (Fig 1), they are described as "functionally deaf" (L78, L261). By contrast, when 0% to 60% of adults respond to tones in the core of their hearing range (Fig S1 for data shown in Fig 2), this is merely presented as a methodological limitation (text added L186-197), and the authors still proceed to presenting results on nestlings with a method that failed in adults (positive control).

(ii) When the positive control fails, the experiment is failed. This principle applies in Neuroscience as in any scientific field.

(iii) That the experiment repeated in adults with the standard and correct short tone protocol (5ms) gave normal results, is not a validation. Instead, it proves the point that 25ms is unsuitable (regardless of whether that is due to rising time, L399). This correction does NOTHING to fix results in nestlings, which were ONLY done with the unsuitable 25ms tones.

(iv) The mixture of adult data with 5 and 25ms tones, instead, creates confusion, because differences in protocols between nestlings and adults are blurred in the text. The abnormally small proportion of adults responding (0 to 60%) with 25ms tones is only shown in supplementary material, and attenuated in the main text (L186: "about half").

(v) The claim (response R3.A1.2) that long 25ms tones is commonly used with the ABR methodology used here is false:<br /> ** ALL (but 1) avian studies using tones of 20ms or longer (cited by myself or by the authors in their reply R3.A1.2) used a different ABR methodology, with electrodes implanted through the skull. The only exception, using 25ms tones with subdermal electrodes (as here), is a study by the authors themselves.<br /> ** All other avian studies with subdermal electrodes used short tones, of 5ms or less (e.g. Brittan-Powell et al 2002, 2004; Henry & Lucas 2008), as in the corrected adult experiment.<br /> ** My initial comment already specified this difference in electrode placement.<br /> ** The results here (failing in adults) unquestionably show that the method of long tones with subdermal electrodes does not work, and the literature shows that no one else uses it.

(vi) When the aim of the study is to contest effects of high frequency sounds (L39-45), it is odd to choose a protocol specifically directed at testing responses to very low frequencies (responses A3.1, R3A.0; L398-403) and that compromises all results.

(vii) That the shape of the few data points obtained in nestlings with long tones would broadly resemble expectations (responses A3.1, R3A.0) is not a validation: See ii.<br /> - The shape is not even correct:<br /> ** Why aren't 4 and 6 day old nestlings responding to any frequency when they were responding to clicks (in spite of poor detection conditions for clicks)?<br /> *** Why are they not responding, when 2 day old flycatchers respond to tones from 1 to 4kHz at 45dB, and 0.5 to 5kHz at 60dB (Aleksandrov and Dmitrieva 1992, Korneeva et al 2006)?

(viii) That only relative measures between nestlings and adults matter (resp R3.A4; L404) is incorrect. Measures that are qualitatively (see vii) and quantitatively (see i) wrong cannot be compared.<br /> If these data with long tones were indeed acceptable, why repeat the experiment in adults with a correct protocol, even before this flaw was pointed to during the review?

(ix) The unusually low number of measurements (400 instead of 1000; L530) will have reduced detectability of low amplitude responses, in nestlings and near thresholds, here as in the click experiment (see above). The claim that this would only increase threshold by 4dB (responses A3.2, L530) is wrong (see above).

(x) There is no explanation as to why only half of the 6-day old nestlings (n=5-6) were tested with tones. Would having 10 in this group shown a response at 6-day old?

(xi) Even the correct 5ms tone protocol in adults overestimated thresholds at higher frequencies (>3kHz) by up to 30dB compared to other published estimates (Fig 5). If inter-population differences among domestic zebra finches (L 393; Fig 5 legend; resp R3.A4) were enough to cause 30dB differences, results on domestic zebra finches here should not be extrapolated to those on wild-derived Australian zebra finches documenting developmental effects of heat calls.

The authors give no other elements than the above in their responses that could demonstrate the validity of their nestling frequency data.

Based on other studies, we can expect zebra finch hearing to develop sensitivity to high frequencies after that to middle frequencies. But pretending that this study provides any evidence towards this is wrong. There is no valid data.

(3) The experiment using loud sounds to make eggs vibrate is biologically and experimentally meaningless. The claim that these measurements would rule out vibration perception in embryos is totally unfounded. The preprint is creating the illusion of having ruled-out a mechanism that they have not tested.

(i) zebra finches are not hovering in front of their nest when heat-calling. They are in physical contact with the eggs while incubating, with vibrations expected to travel directly through solids from adults to eggs, without attenuation.

(ii) the claim that previous studies on heat-call developmental impact rely on the assumption of airborne sound making egg vibrate (response A3.5, R3.A8) is incorrect. This is conceptually wrong and there is no indication of this in any paper.

(iii) vibration perception in embryos in birds and other taxa (e.g. amphibian, reptiles and insects) rely on direct contact with the source, not on loud airborne sounds shaking eggs. Beyond any consideration on heat-calls, claiming that this experiment could give any indication of vibration perception in embryos is nonsense.

The authors give no information in their responses that could demonstrate the validity of this experiment.

(4) Interpretation and discussion

All other songbird studies, individually and collectively, show much greater hearing sensitivity in nestlings that what this study is trying to suggest (e.g Khayutin 1985; Korneeva et al 2006; Aleksandrov and Dmitrieva 1992; Rivera et al 2018; Platzen and Magrath 2004; Haff & Magrath 2012). The only way the authors can reach their conclusion is by:<br /> - presenting data that greatly underestimate hearing sensitivity in zebra finches (see sections 1 and 2) and overstating them, and;<br /> - misrepresenting current knowledge by excluding relevant papers and being unclear about what the literature shows.<br /> This study tries to impose the idea that zebra finch do not detect any sound before day 4-6 post-hatch, and have extremely rudimental hearing until day 8-10 post-hatch. By contrast, other studies show very young hatchlings respond to sound 1 to 3 days after hatching (first age tested) and show quite sophisticated, and totally functional, responses to relevant sounds at 5 days old.

This is not to say that hearing does not continue to improve post-hatch in birds, or that sensitivity to mid frequencies post-hatch would not precede that to high frequencies. But statements throughout this study are so exaggerated and/or wrong that nothing can be learnt. It is undeniable that this study fails to provide the useful and balanced assessment needed to establish were true heat-calls actually sit relative to zebra finch adult, nestling and embryonic hearing range.

It is literally impossible to correct every wrong statement in the discussion and responses to reviewers. I focus here on some examples related the claims of "nestling deafness" or of heat-calls being outside of adult zebra finch hearing range, as well as inaccuracies leading to an apparent match with current literature.

(i) MISALIGNMENT WITH OTHER STUDIES AND MISREPORTING

*** Neurological evidence

- Highly relevant evidence on response to sound in zebra finch embryos (Rivera et al<br /> 2018) is totally excluded.<br /> Excluding this study on the basis that it used a different methodology that does not directly quantifying auditory sensitivity (resp R3.A6a) is a poor justification. Evidence, even indirect or imperfect, should be brought to the attention of the readers.

- This applies to many other studies cited in my first review and arbitrarily excluded here. If one wants to conclude on "deafness", all evidence, even indirect, should be considered. Excluding non-ABR studies means the conclusion cannot be extended beyond flat ABR traces.

- Other studies show much greater sensitivity that what the text describes:

* Flycatcher hatchlings at 2-3d post hatch (first age tested), respond across a wide range of frequencies (0.3 to 5kHz), at low to moderate sound levels (45-65dB)<br /> (Aleksandrov and Dmitrieva 1992, Korneeva et al 2006).

* Stating that these studies in flycatchers "likely yield lower thresholds" (L364) is an astonishing understatement. Thresholds in Aleksandrov and Dmitrieva (1992) at 2-3 day old were 35 dB lower than those here at 4 day old with clicks, and 60 to 80dB lower than those with tones of 1-2kHz at 8 day old.

* Claims that "sensitivity improves rapidly postnatally, with ~40 dB threshold decreases (L365)" is also misreporting these studies' findings. Thresholds decreased by 25dB consistently at 9 out of 11 frequencies tested from 0.3 to 8kHz (Aleksandrov and Dmitrieva, 1992). A difference of 40dB was only found at 5-6kHz (Aleksandrov and Dmitrieva, 1992). Likewise, improvement also varied from 25 to 40dB in Korneeva 2006. These do not average to "~40 dB".

* Even birds developing 4 times slower than songbirds (budgerigars) show a response at 5 day old. My statement that Brittan-Powell 2004 shows an auditory response at 5d old is correct. Re-response R3.A2.2: Fig 1B shows one example for ONE individual. All other figures based on multiple individuals shows at least some individuals responded at 5-6 days old at frequencies less than 4Khz (Fig 1C, 4 and 5).

- Many inaccuracies on avian hearing remain uncorrected in the revision.<br /> * e.g. L 329: extrapolating high frequency hearing (>6khZ) from precocial species is incorrect because even adult chicken and ducks are not sensitive to high frequencies.<br /> The authors imply elsewhere that species of songbirds cannot be compared (resp A4, R3.A6), but make extrapolations from species that are far more remote, phylogenetically, developmentally and ecologically than other songbirds.

*** Behavioural evidence

- contradicts this study findings:

* When correctly cited and described, the literature, does not support the authors' statement that nestling behavioural response "typically emerges between ~5-10 days post-hatch" (L358). It emerges earlier, at an unknown age, including potentially from hatch (present at 1.5day) for innate responses (see below).

* Results in other songbirds are not consistent with this study finding that a "response to loud click stimuli is first detectable at 4-8 days post hatch" (L230). Instead they show nestling hearing capacities described here are abnormally poor.

* Therefore, the conclusion that "The timeline of behavioural studies closely matches the onset and maturation of ABR responses observed here in zebra finches" (L360) is wrong.

- shows a very early response (1-2day post hatch), with no known onset:

* songbird behavioural response to sound, with parental alarm call suppressing begging, has been demonstrated in nestlings as young as 1.5 or 3 days old (Khayutin 1985, Korneeva et al 2006, Aleksandrov and Dmitrieva 1992). None of these results are mentioned in the revision when discussing behavioural evidence (L357-360).

* Instead, they exclusively mention studies that started testing nestlings at 5-6 days old, or much later (e.g. 17 day old: Suzuki 2011; 14 day old: Barati & McDonald 2017).

* ALL of these studies (cited or not) demonstrated a significant response of nestlings to calls on the first age tested. NONE tested the onset of this response.

* the one study looking at progression across 3 ages, at 5, 8 and 11 day old shows parental alarm calls suppress nestling calling at day 5 as much as later on, with no effect of age (Platzen and Magrath 2004). The authors failed to acknowledge this in their response (resp A4) or revision (L359).

* the claim that Haff & Magrath (2012) showed nestlings did not respond at 5-6 day old but did at 10-11 days (resp A4) is wrong. At 5 day old, they responded to their own species alarm calls, as well as to another similar sounding species and to the sound of predators themselves (Table2 in Haff & Magrath 2012; as in Platzen and Magrath 2004).

- learning, not just hearing, improves nestling response with age:

* Haff & Magrath (2012) showed that by 10-11 day old, nestlings had learnt to also respond to heterospecifics, demonstrating that learning improves nestling response with age.

* the intensity of the response to low frequency sound improved more with age than that to high frequency calls. If improvement were related to hearing limitations, the opposite would be expected (Haff & Magrath (2012).

- nestlings discriminate complex calls, including at high frequency

* By 5-6 day old, nestlings can already discriminate several different sounds indicative of danger, among the complex natural acoustic background (Haff & Magrath 2012).

* nestling do not respond indiscriminately to any calls, but only to relevant sounds that specifically present a threat to them (Haff and Magrath 2012; Magrath et al 2006).

* the idea that nestlings only distinguish "low frequency broadband cues" (L362) is inaccurate (resp R3.A6). Nestlings respond to scrubwren chip calls and fairywren alarm calls that are narrowband calls with the fundamental at 8 and 10 kHz respectively (Platzen and Magrath 2004; Haff and Magrath 2012).

* These studies indeed "do not imply mature auditory sensitivity" (L362), they show that auditory maturity is not needed to show a perfectly functional response to biologically meaningful sounds in a natural context.

- Overall, every other songbird species tested shows greater hearing sensitivity than that proclaimed here for zebra finches. It is very unlikely that zebra finches would be such an outlier.

(ii) INCORRECT CONCLUSION ON DEAFNESS

Deafness of young zebra finch nestlings cannot be demonstrated because:

- the study has no valid response to tones in nestlings to establish the age of hearing onset.

- responses to clicks are greatly underestimated (see 1). Had correct, more sensitive, protocol parameters been used, it is very likely that:<br /> * Most 2 day old nestlings would have responded to clicks, instead of 60% of 4 day old nestlings.<br /> * Thresholds would be lower, especially in nestlings.<br /> The >54dB difference between nestlings and adults based on an assumed 95dB threshold in 2d old nestlings is wrong.

- based on data on other songbird nestlings, a difference of 25dB would be more realistic (at frequencies of 1-2 kHz, comparable to clicks, Aleksandrov and Dmitrieva 1992, Korneeva et al 2006). This greatly contrasts with the >54dB estimate here. While the authors qualify their estimate as "conservative" (legend Fig4, L293), it is actually greatly overestimated.

- Even assuming the data in this study were correct, the interpretation is erroneous. Concluding "deafness of young nestlings" is incorrect when 60% of 4 day old nestlings respond to clicks at 80dB. This is especially wrong given that the ABR method systematically overestimates thresholds by 20-40dB.

- That ABR is used in humans to diagnose deafness (L263) does not make ABR the most suitable method for birds, when evidence shows that other methods (e.g. electrophysiology or behaviour) are more accurate. Hearing screening in humans can only use non-invasive methods, and has additional criteria than accuracy (price, ease, etc).

- The discussion fails to acknowledge the implications of the limitations of the study (detailed above). For example, talking in broad terms of differences in protocols (L392-395), does not tell readers that this study, because of the parameters chosen, led to an underestimation of zebra finch hearing capacities.<br /> The discussion instead greatly overstates what the study shows (e.g. L229-232, 261, 277-278, 288, 332, 340, etc).

(iii) INCORRECT CONCLUSION THAT HEAT-CALL FALL OUTSIDE THE ADULT HEARING RANGE.

- heat-calls fall outside the adult hearing range solely because of the authors' decision to:<br /> * restrict heat-call frequency range to the authors' own estimation (7-10kHz) on 4 birds instead of using published values that caused developmental impact (e.g. Katsis et al: 6-10kHz), or were produced in vitro (5.9kHz; Anttonnen et al 2025);

* lowering heat call sound level (34dB at 10 cm) to measurements on 4 isolated birds under unknown temperature conditions for an unknown amount of time, when the same paper gives values of 43.4 dB at 1 m (range: 30.7-53.2) in standard in vitro conditions.

* As soon as EITHER of these two values is corrected, the statement that heat calls are outside zebra finch adult hearing range is false.

* In addition, assuming constant heat-call sound level across contexts is unreasonable. That zebra finch can produce inspiratory syllable very similar to heat calls and during inspiration at 65dB during song (Goller & Dalley 2001) argues against the assumption that heat-calls are always soft.

- Other species also show perception, not just production (resp R3.A10a), of calls above their known hearing range (10-20kHz; e.g. Duque et al 2020). The zebra finch is not the only case in birds of mismatch between signals perceived and known hearing range.

Reviewer #4 (Public review):

Reviewing Editor:

There is a virtuous circle between behavior and neuroscience. Sometimes neuroscience identifies a signal that no behavioral study alone could discern: place cells in rats, replayed song sequences in sleeping birds, compass-like signals in the central complex of the fruit fly. Sometimes behavioral observation is what inspires neuroscience: precise measurements of short and long latency reflexes implicate different neural pathways, and directed escape responses in fish are so fast that they require specialized and lateralized escape circuits. And sometimes a behavioral claim requires an animal's sensory system to possess a capacity nobody had documented. A prime example is bat echolocation: Spallanzani inferred in 1793 that bats navigate by hearing, but the claim was dismissed for over a century because the signal he proposed could not be detected. It was vindicated only when Griffin and Galambos measured the ultrasonic emissions directly in 1940, and the loop closed fully when Suga and colleagues found cortical neurons in the mustached bat tuned to precisely the echo delays and Doppler shifts the behavior required.

In this manuscript we are faced with a fascinating and contemporary instance of this important dialogue between behavior and neurophysiology. Several high profile papers have reported that incubating zebra finch parents produce high frequency "heat calls" when ambient temperatures rise, and that playback of these calls to eggs during late incubation alters offspring growth, begging behavior, thermal preference, and reproductive success in adulthood. That function requires that the embryo be able to sense, presumably to hear, the heat calls. This is textbook ecology and often cited as the prime example of adult behavior affecting the development of their unborn (or unhatched) offspring.

Yet the auditory capacity of very young zebra finches had never been carefully examined. This paper does exactly that, using auditory brainstem responses, a method that detects synchronous volleys of afferent input through low levels of the auditory system. ABRs are not perfect and may miss very subtle or sparsely represented signals, but they are a time-tested way to assess hearing capacity and the development of a system.

Here, the authors show, convincingly in my view and in the views of Reviewers 1 and 2, that 2 DPH hatchlings have no detectable ABR to a 95 dB SPL broadband click, and that sensitivity then rises progressively across the first two postnatal weeks. This is the most consequential result, since it bears directly on whether an auditory route to heat call perception is feasible at all. A second finding is that ABR wave I amplitude continues to mature until 20 to 25 days post hatch, coinciding with the onset of sensory song learning, just as young finches need to form a template of an adult male song to copy.

The key question relevant to mediating this review process is: If a two-day-old hatchling shows no detectable auditory brainstem response, over 400 averaged sweeps, to a 95 dB SPL broadband click, in 14/14 animals tested, then how could that same animal, two days earlier and inside an egg, have been sensitive to a far weaker stimulus of roughly 33 dB SPL at 6.8 kHz?

Below I set out the considerations that influenced my judgment as I handled these reviews.

Strengths:

The developmental series is the strength of the design. Seven ages, with multiple early time points, means the negative result at 2 DPH is not a lone flat trace but sits at one end of a graded and internally consistent trajectory. Body temperature was monitored and held within {plus minus}0.5{degree sign}C, and differed by no more than 0.6{degree sign}C across age groups. Every stimulus parameter was applied identically at every age, so the developmental comparison is a within-method one. The vibrometry experiment addresses the most obvious alternative modality with an appropriate and state-of-the-art technique.

The key findings related to the development of the ABR response and, presumably, the hearing capacity. At two days post hatch, the authors presented broadband clicks of 20 µs duration at 95 dB SPL peak equivalent, a stimulus carrying energy across the full spectrum including the 6.8 kHz of the heat whistle. Clicks were delivered at 25 Hz with a 40 ms inter-stimulus interval, 400 presentations per condition with alternating polarity, and responses were scored both by an automated signal-to-noise criterion and by independent visual inspection. No response was observed in any of the 14 animals tested. Two days later, under the same protocol, eight of thirteen animals responded, with a mean threshold of 80.6 {plus minus} 1.6 dB SPL and wave I latencies of roughly 4.0 to 4.7 ms against 1.8 to 2.5 ms in adults. These responses were small, broad, and slow, the signature of an immature auditory system. By 6 DPH nine of ten animals responded, and from 8 DPH onward every animal did at every age tested. Adult thresholds settle at 40.6 {plus minus} 4.0 dB SPL, more than 54 dB below the 2 DPH value. The 4 DPH data show the preparation resolves weak, desynchronized responses under exactly the parameters used at 2 DPH, and that sensitivity emerges on a trajectory consistent with auditory development in other birds and in mammals.

On Reviewer 3's methodological objections:

Reviewer 3 raised a series of objections to the recording parameters: the stimulus rate is faster than in comparable avian developmental studies, 400 sweeps is fewer than the conventional 1000, body temperature sits at the low end of the reported range for the species, and clicks lag tones in developmental onset. Each of these describes a mechanism that would reduce the amplitude of an evoked response relative to some ideal stimulus. But in aggregate my take was that none of these would completely abolish a response that is detectable two days later. That distinction is the crux of my reading and others may disagree. A response reduced by 70 percent is still a response, and the question at 2 DPH is not why the trace was small but why there was no trace at all over 400 averages in all 14 animals tested.

Reviewer 3's concerns are difficult to translate into threshold shifts, and on the narrow point that amplitude reductions do not map cleanly onto decibels, the difficulty that the reviewer faced in converting stimulus concerns to impact on dB threshold is well taken. But the figures supplied are themselves bounded: a 37 percent noise reduction from additional sweeps, a 70 percent amplitude reduction from stimulus rate in the youngest birds, a four day shift in apparent onset from using clicks rather than tones. These are large effects. They are not unbounded ones. And because the decibel is a logarithmic unit, in which every 20 dB corresponds to a tenfold change in sound pressure, the gap they are being asked to explain, exceeding 54 dB, amounts to a difference of more than 500-fold.

The 4 DPH data bear directly on this, because every parameter at issue was applied identically at that age. The same 25 Hz rate, the same 400 sweeps, the same temperature, the same click stimulus resolved small, dispersed, long latency responses in 8 of 13 animals two days later. These are precisely the weak and desynchronized responses an immature auditory system is expected to produce, and precisely what the objections predict should have been lost. Whatever theoretically possible deficits in stimulus design, they did not prevent detection of a marginal response in animals two days older, and no mechanism has been proposed by which their cost would fall from total suppression at 2 DPH to negligible at 4 DPH.

A 95 dB SPL broadband click carries energy at every frequency including 6.8 kHz and exceeds the level at which heat whistles arrive at 10 cm by more than 60 dB, before any attenuation by shell or by an incubating parent. Even a substantial underestimate of hatchling sensitivity leaves that gap open, and at 6.8 kHz it is a broadband stimulus being compared against a narrowband signal in the frequency region that matures last, in this dataset and in every developmental series reported.

Sensory systems as matched filters:

A second consideration: sensory systems as matched filters (survival-critical sensory responses are typically associated with expanded sensory sensitivity for them). Failure to detect an auditory response is not proof of functional deafness. An evoked potential measures synchronized population activity, so sparse discharge below the threshold for ABR sensitivity (a population response) can never be excluded. This is the crux of Reviewer 3's concerns.

But this second consideration makes the difficulty of finding any evidence of hearing or vibrotactile responsiveness in these animals more compelling. Rüdiger Wehner, working on desert ant navigation, noted that sensory systems are matched filters. They are tuned to the narrow slice of the world that matters for survival and reproduction and discard the rest. From the tuning of an ant's polarization channel you can infer what it navigates by, and from the work of Capranica we know that the tuning of a frog's inner ear relates to the sound of conspecific frogs. If acoustic or vibrotactile processing of heat calls were genuinely critical to the embryo, natural selection would have built the outsized sensitivity to receive it. Instead there is a greater than 54 dB deficit and a frequency range where nothing is detectable at all. I interpret this as evidence that evolution did not build auditory sensitivity into two-day-old hatchlings, which suggests functional deafness in the embryo.

One might invert this argument and object that the filter in the embryo is precisely for the heat whistle itself, so that neither a broadband click nor a 25 ms tone burst, the only two stimuli presented to 2 DPH animals, is the right probe. Feature detectors that respond to a specific signal while ignoring stimuli of far greater energy are common: cricket AN2 neurons fire to bat-like pulse intervals and stay quiet to loud broadband noise, and anuran midbrain neurons are interval-tuned and silent to spectrally matched noise exceeding the call in level. Embryonic sensory systems also carry transient specializations that later disappear, and the heat whistle is unusually specifiable, narrowband near 6.8 kHz and delivered in rhythmic trains. A detector tuned to that rhythm would not have been engaged by any stimulus used here, since the actual call was never played to any animal at any age.

But feature selectivity is typically computed centrally, downstream of peripheral transduction, and ABR wave I reflects auditory nerve output, below any circuit that could implement pattern selectivity. A central detector still requires afferent input to operate on, and it is that input which seems to be absent here. It's conceivable that the cochlea itself exhibits some very special tuning to the heat whistle and implements some kind of yet-to-be discovered surround suppression at the periphery, such that a click would not be able to activate the hair cells in the heat whistle's frequency range. But 2 DPH animals were also tested directly with narrowband 6 and 8 kHz stimuli at 95 dB SPL, bracketing the heat whistle frequency, also without response. The surviving version of the objection therefore requires a pathway with too few fibers to generate a far-field response, tuned to a temporal structure nobody tested, in an animal whose auditory nerve shows no signal at some 60 dB above the natural signal level.

Caveats:

The paper comes with some caveats, which the authors note in their discussion. First, no embryo was tested. The embryonic claim is an extrapolation from hatchlings. I regard it as a reasonable one, since sound must additionally traverse the shell and since auditory systems gain rather than lose function as development proceeds, but it is an extrapolation nonetheless. Second, frequency-specific thresholds in nestlings were not obtained with a full stimulus set. The low to high developmental sequence therefore rests on a conservative stimulus. Pip data in nestlings would be a valuable addition to the record. Finally, the study offers no pre-neural measure, such as cochlear microphonics or otoacoustic emissions. Such a measure would distinguish a cochlea that is not transducing from one that transduces without synchronized output, and would address the strongest form of the objection raised in review.

Summary:

Absence of evidence is not evidence of absence, and some future study could in principle identify single neuron responses to heat calls in an embryo. The evidence in this paper makes that outcome unlikely in my assessment. It is worth noting what the precedent actually supports. Prenatal hearing is real and well documented in precocial birds: mallard embryos deprived of exposure to their own calls fail to recognize the maternal assembly call after hatching, and chickens show evoked responses well before hatching. But those animals hatch at a developmental stage altricial songbirds do not reach until days later, and the calls involved carry their energy below 3 kHz, the frequency region that comes online first. The claim at issue here requires sensitivity at 6.8 kHz, the region that matures last, in an animal at a far earlier stage. Something may still be happening to the embryo during heat calls, but whatever the mechanism, it is probably not the embryo listening. Behavioral claims that lack strong precedent, such as hearing through an eggshell, need to sit in a virtuous circle with neurophysiological investigation, and this study is what that looks like from the physiological side.

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors investigate the mechanisms underlying macrostructure formation in a freshwater filamentous cyanobacterium strain, F. draycotensis, focusing on how its ability to aggregate and form these structures depends on the physical properties of the filaments. Using experimental observations, they demonstrate that the cyanobacterium actively captures and surrounds particles, a process driven primarily by gliding motility.

To explain these physical dynamics, the authors present a 3D model indicating that particle collection relies on filament length, as well as a specific mechanical response, namely, filament buckling and the subsequent formation of loops of bundles of filaments. While the authors have previously documented the buckling and looping characteristics of this strain, this study provides new insight by demonstrating that these physical phenomena are essential for particle capture and collection.

Strengths:

This manuscript benefits from a rigorous and detailed quantitative analysis of video recordings, which clearly documents the motility, buckling behaviour, and particle collection dynamics of the filaments.

The authors effectively validate their hypothesis by using a naturally shorter filamentous strain, which fails to collect particles, suggesting that filament length is indeed a critical parameter.

To further confirm the length dependency within the same species, the authors experimentally generated shorter filaments of F. draycotensis. The fact that these shortened filaments also lose the capacity to collect particles provides strong evidence supporting their proposed mechanism.

Weaknesses:

There is a conceptual concern. The authors linked the specific physical properties of this strain to evolutionary data, highlighting that the studied lineages diverged approximately two billion years ago. This creates a misleading impression that particle collection via flexible looping filaments is a recent evolutionary adaptation. However, particle collection has been observed in other cyanobacteria, such as Trichodesmium, which features short, rigid filaments. Therefore, the term "emerging" does not seem appropriate for the title and text. The capacity to collect particles in the studied strain F. draycotensis appears to be primarily a function of physical characteristics (filament length and flexibility) rather than evolutionary age. Any cyanobacterial strain possessing similar physical properties is likely to exhibit comparable behaviour, rendering the evolutionary timeframe largely irrelevant to the core mechanism. In addition, the phylogenetic tree presented in Figure S5 does not reflect the current consensus on cyanobacterial evolution and systematics and does not align with modern phylogenomic frameworks (see, for example, Strunecky et al., 2023 https://doi.org/10.1111/jpy.13304). There is also no such order Cyanobacteriales, which has been mentioned in a few older publications but is clearly outdated.

Another concern is that the authors nearly completely ignore the role of type IV pili in the gliding motility of cyanobacteria, including filamentous strains. For a long time, there was a misconception that the gliding motility of cyanobacteria was due to slime protrusion. Slime plays a role in this process. However, several studies have shown that filamentous strains also use type IV pili to glide on surfaces. The authors should discuss this and include it in their model. In addition, the authors concluded that gliding motility is responsible for particle collection by Fluctiforma draycotensis. Although I believe that their conclusion is correct, there might be several limitations to the experiments which allow for other reasons to be considered. Their conclusions were based on the use of a non-motile strain and an unspecified community without the motile Fluctiforma draycotensis strain. The problem I see here is that it is not clear why this strain is not motile; it could be because of the lack of type IV pili, mutations which alter their functionality, defects in slime secretion, any other mutation (e.g. in chemoreceptors), cellular structure, metabolism, or combinations of these. Furthermore, it is possible that the community changes its composition and behaviour when it lives without the cyanobacterium with a rich carbon source (glucose) or with a non-motile cyanobacterium which may not secrete slime or, for example, a signalling component which controls behaviour of the bacteria in the community. For that reason, the authors should be more cautious with their conclusion that solely motility behaviour of Fluctiforma draycotensis is responsible for particle collection. Additional factors might be responsible for these effects.

Reviewer #2 (Public review):

Summary:

The authors studied aggregation, buckling, and particle collection by the filamentous cyanobacterium Fluctiforma draycotensis, as well as by the filamentous Pseudanabaena sp. (order Pseudoanabenales). They performed a range of experiments, from imaging individual gliding filaments to multiple-day experiments showing the formation of large aggregates around a particle formed from a precipitate. They also developed a model of buckling filaments to argue that the ability of elastic filaments to collect particles and form macrostructures is confined to a part of the filament phase space in terms of length and flexibility, meaning that gliding combined with certain filament length and flexibility naturally reproduces the observations.

Strengths:

This is an impressive study that uses multiple tools to connect macrostructure formation with filaments' gliding motility and buckling. It adds an important perspective on the biological and physical factors at play in the emergence of aggregates.

Weaknesses:

The authors ignore the possibility that filament behavior plays an important role in the emergence of the observed patterns. Cyanobacteria have been shown to control their gliding motility (Pfreundt et al Science 2023; Kurjahn et al Nature Comm 2024), and their molecular motors are known to be regulated by chemotaxis-like signaling pathways (Risser ARM 2025). As far as I know, how the coordination between the pulling agents along an individual filament works is actively debated, but there seems to be little doubt that it exists. 

To illustrate this point better, note that the aggregation observed by the authors is consistent with the length-dependent ability of filaments to coordinate gliding (I'm not saying this is how it works in Fluctiforma draycotensis; I'm saying it's consistent). Suppose the coordination requires sufficiently long filaments, which could be the case when signaling molecules travel along the filament, propagating information about when individual pulling agents should reverse. In such a model, short filaments act randomly because they fail to coordinate gliding by the time they glide off nascent aggregates, whereas longer filaments can perform informed reversals because they have more time for coordination. Such behavior then explains the lack of aggregation in Pseudanabaena sp. (via behavior, not lack of stiffness). Note that Trichodesmium is stiff; its filaments do not buckle, yet Trichodesmium forms organized aggregates via tightly controlled motility. Note also that, as the authors report, since Pseudanabaena sp. is both shorter and faster, its filaments have relatively (to the time needed to glide the filaments' length) little time to coordinate reversals. In my opinion, whether the observed patterns passively emerge from gliding and buckling or result from active behavior remains an open question.

I also have a small suggestion regarding this statement on model novelty:

The essential novelty of this model is that the filament itself is active and out of equilibrium, and additionally, the forces and torques are applied locally along its centreline, and not at its extremities as in previous steady-state mechanical studies of elastic, twistable filaments such as DNA [31-33] (see Methods and SI).

This statement needs to be revised as it ignores a substantial body of work on self-organization of active filaments: (R. E. Isele-Holder, J. Elgeti, G. Gompper, Soft Matter 2015; Pfreudnt et al, Science 2023; Faluweki et al PRL 2023; Kurjahn et al Nature Comm 2024).

Last point: the authors often say that their observations are reproducible ('...reproducibly forms macroscopic granules...'). What is meant? Different experiments on different days, different aliquots?

Reviewer #3 (Public review):

Summary:

The authors report and characterize the formation of aggregate microstructures by the motile filamentous cyanobacterium Fluctiforma draycotensis, which exhibits gliding motility accompanied by rotation along the long axis while excreting EPS. In experiments with motile F. draycotensis cultures, they observed the formation of granular structures composed of cyanobacteria and other material (iron, polystyrene beads, etc.), with macrostructures on the scale of 1mm within 24 hours. The structures were motile at speeds comparable to that of the cyanobacteria filaments, resulting in their growth through coalescence over time. Notably, such macrostructures were absent in nonmotile F. draycotensis, pointing to the role of filament motility in their formation. Through experiments examining the micro-scale dynamics, inert material such as small polystyrene beads was found to be transported by the gliding, buckling, and plectoneme dynamics of the filaments, pointing to the underlying mechanism by which particles are collected into larger-scale microgranule structures.

To interrogate the properties that drive the cyanobacteria filament buckling, plectoneme formation, and entanglement, the authors develop a mechanical model for filaments as nearly inextensible, slender bodies with resistance to twisting and bending under active gliding forces and torques and responding to fluid flows and surface adhesion. They derive expressions for the thresholds for buckling and twisting instabilities, which are additionally demonstrated and interrogated through simulation via the Immersed Boundary Method. Most importantly, bending and plectoneme formation only occur with sufficiently long filaments, and the threshold is shorter for bending than for plectoneme formation. Experimental observations with wild-type filaments agree with the model-predicted thresholds. The authors perform additional experiments with shorter filaments below both thresholds, including the filamentous bacterium Pseudanabaena, which fail to collect particles (though can in principle form macrostructures).

Strengths:

This work appears to be novel (notably, the discovery and characterization of the particle collection behavior of a filamentous cyanobacterium) and has interesting implications for both naturally observed cyanobacterial macrostructures as well as the controllable parameters in engineering them. The experimental and modeling work is well motivated, contributing to the broader understanding of macrostructure formation and material aggregation through active filament dynamics (not exclusive to cyanobacteria), as well as the underlying physical properties governing important filamentous cyanobacterium dynamics. As such, I would expect the results of this paper to be of broad interest to both biophysicists and microbiologists. Generally, the manuscript is well written with clear, compelling figures that illustrate the important conclusions of this study.

Weaknesses:

In the section on "Shorter gliding filaments cannot collect particles nor form granule macrostructures", the filamentous cyanobacteria considered *all* fall below the predicted thresholds for bending and twisting. The "long" F. draycotensis are 60 microns in length, notably less than the 120 and 320 micron thresholds derived in the previous section as well as the lengths of filaments considered in Figure 3D, yet these "long" 60 micron filaments form macrostructures. How can this be understood in the context of the model predictions? Is the nature of the macrostructures in Figure 4B, the microscale parameters, or the collection of particles somehow different than those with filaments an order of magnitude longer in earlier parts of the paper? The paper would be stronger if these sorts of questions were addressed in the text and/or with supplementary figures.

Reviewer #1 (Public review):

In this study, Telias et al. identify the P2X7 receptor as a key component of retinoic acid signaling-mediated remodeling in the degenerating rd1 retina. The authors report increased P2X7R expression in the inner retina following photoreceptor loss and link P2X7R signaling to retinal ganglion cell hyperactivity, membrane hyperpermeability, and altered calcium homeostasis. Genetic deletion of p2rx7 abolishes ganglion cell hyperpermeability and reduces several features of pathological remodeling in the rd1 retina. The study provides valuable mechanistic insight into retinal remodeling following photoreceptor degeneration. However, several issues currently limit the strength of the conclusions. In particular, key comparisons are confounded by differences in genetic background, the cellular source of P2X7R expression is not sufficiently resolved, and several experiments require additional controls and more cautious interpretation.

Major comments:

(1) The Methods state that C57BL/6J mice were used as wild-type controls, whereas rd1 mice were maintained on a C3H/HeJ background, and the rd1-p2rx7 knockout line is on a mixed background. Direct comparisons among these groups are therefore potentially confounded by strain-specific differences. Authors should use littermate rd1 het mice as healthy controls in all their experiments.

(2) The authors do not demonstrate P2X7R expression in RGCs. The P2X7R signal in the rd1 retina shown in Figure 1B appears saturated and is therefore difficult to compare directly with the WT image in Figure 1A. Furthermore, Figure 1E indicates that overall P2X7R fluorescence in the GCL is not significantly different between WT and rd1 retinas, whereas the representative images appear to suggest a marked increase. The authors should provide images acquired and displayed under identical settings and consider including retinal whole-mount staining with an RGC-specific marker. P2X7R abundance should then be quantified specifically within identified RGCs in both healthy and rd1 retinas. As mentioned above, het rd1 mice should be included. As an additional control, the authors also should include the staining of rd1 p2x7r KO retinas.

(3) Does the increase in P2X7R abundance correlate with photoreceptor loss? Please include staining of younger rd1 mice along with het rd1 littermates.

(4) In Figure 1G-H, the description of the reporter is internally inconsistent: the Results refer to an artificial mini-Pax6 promoter, whereas the Figure 1 legend describes the Ple344 neuronal mini-promoter derived from Tubb3. Please clarify which promoter is used and what cell population the ECFP signal labels. Figure 1G should explain the function of each reporter element and how RAR activity is inferred. Figure 1H should include an RGC marker such as RBPMS and provide quantitative analysis of RBPMS-positive, reporter-positive, and Yo-Pro-positive cells. Additional controls are needed to exclude effects of viral transduction or retinal inflammation on Yo-Pro uptake. They should include rd1 retinas without AAV, rd1 het retinas with and without the reporter AAV.

(5) In addition, lines 143-144 state that two experiments were performed, but only one is described in that paragraph; the text should be reorganized or clarified.

(6) Yo-Pro-1-positive cell density in rd1 mice between Figure 1H and Figure 2D is different. Why?

(7) Constitutive deletion of p2rx7 may cause developmental or compensatory changes that could contribute to the observed phenotype in Figures 2 and 3. Additional controls are therefore needed to distinguish acute effects of p2rx7 loss from developmental consequences. The authors should assess whether p2rx7 deletion alters retinal cell-type composition, including RGC density, or affects the timing or extent of photoreceptor degeneration. Perform a rescue experiment to determine whether overexpression of p2rx7 in the knockout background restores the phenotype. For all experiments, het rd1 control mice should be included.

(8) Figure 3D and E experiments should include control AAV expression such as GFP.

(9) Figure 5 experiments should include control rd1 het mice.

Reviewer #2 (Public review):

Summary:

In this study, the authors used genetic, transcriptomic, imaging, and electrophysiological approaches to investigate the role of P2X7R in retinal remodeling in rd1 mice. The authors propose that RA signaling upregulates P2X7R, leading to altered Ca²⁺ signaling, HCN1 expression, and spontaneous RGC hyperactivity.

Strengths:

Multiple lines of experiments were conducted, focusing on an important question in the field.

Weaknesses:

However, some aspects of the experimental design, statistical analysis, and interpretation require clarification. In particular, the genetic controls and causal evidence should be strengthened before the proposed RA-P2X7R-Ca²⁺-HCN1 pathway can be fully supported.

Some major issues:

(1) The Abstract states that P2X7R deletion prevents the upregulation of RA-responsive genes, whereas the Results state that RAR-dependent genes were not consistently changed by P2rx7 deletion. This central statement should be corrected and clarified.

(2) The P2rx7 knockout model requires further discussion. JAX strain 005576 targets exon 13 and has previously been reported to retain truncated P2X7 transcripts with residual activity (Masin et al., 2012). The authors should avoid describing this allele as complete loss of the entire P2rx7 gene unless additional isoform-specific validation is provided.

(3) The evidence that RAR directly regulates P2rx7 transcription remains incomplete. Predicted promoter motifs and reduced P2X7R protein after BMS-493 treatment are supportive, but they do not establish direct transcriptional regulation. Measurement of P2rx7 mRNA, RAR promoter occupancy, or promoter mutagenesis would strengthen this conclusion.

(4) Several statistical results require verification. In Figure 2H, four paired eyes are analyzed using an unpaired Mann-Whitney test, and the reported p<0.001 is difficult to reconcile with n=4. Similarly, the significance levels in Figure 5A-D are not compatible with a two-sided Wilcoxon rank-sum test using n=3 mice per group. The statistical unit, exact P values, and number of biological replicates should be rechecked.

(5) The overall causal pathway remains partially inferential. The study does not directly show that increased Ca²⁺ causes HCN1 upregulation or that HCN1 is required for RGC hyperactivity. These steps should either be experimentally tested or presented as a proposed model rather than an established mechanism.

Reviewer #1 (Public review):

Summary:

This paper suggests an alternative model for the function of the multiple demand network. Specifically, its role is not necessarily to sustain cognitive control and maintain task sets, but rather to "stabilize task-appropriate modes of thought". Evidence for this would be that the MD network is responsible for maintaining a particular thought state during a task. To investigate this, they use a combination of fMRI brain data during a set of 14 tasks and experience sampling in a different set of participants performing the same tasks. Using dimensionality reduction, they reduced the space of task features (and brain systems) to a smaller, more tractable set of dimensions and examined whether stability in specific thought components was related to recruitment of specific brain systems during the task.

Strengths:

Overall, this is an interesting and creative study with strong analytic methods that do a good job accounting for confounds or alternative explanations (save one I mention below).

Weaknesses:

I have mostly minor comments and one major one.

Major:

The principal finding is that tasks that evoke brain activity patterns that resemble the MDN also had more stable "deliberate task focus" features. While all the analysis and controls are impressive, I'm still left with the sense that this is reifying something we already know or that alternative explanations are more parsimonious than the MDN induces stability in "thought".

I thought an example might be easiest to understand my point: If I gave participants a series of working-memory-related tasks. Some of these are the crème de la crème, and others are sloppy and poorly designed. Then suppose I assess them on measures related to deliberate thought; I'd likely find the "good" tasks elicit more consistent/reliable deliberate task focus. I also would bet money that these same tasks would evoke canonical WM and MDN activity patterns more than the sloppy tasks. This isn't evidence of MDN stabilizing patterns, but rather that both stable thought patterns and activity in the MDN share a common cause. Thus, I would predict that with my thought experiment, your analysis would find the same result. So it strikes me as a strong alternative possibility for these results is that tasks that reliably evoke deliberate task focus are also those that more strongly and consistently evoke working-memory demand (i.e., Figure 2 shows that they are primarily driven by the executive/WM tasks).

Minor:

(1) The PCA was reviewed previously, and I don't want to relitigate a prior method, but I had one minor concern. It would be useful to know how the principal results are based merely on the "deliberate" or "focus" items specifically. Is the thought space necessary, or do the individual items that likely drive the "deliberate task focus" PC essentially replicate the main result?

(2) I struggled with the motivation for projecting the task data onto a resting state FC analysis that focuses on "gradients". I understand that with 14 tasks activation maps, data reduction is a good thing. But as someone who isn't as enmeshed in this work, I didn't follow why this specific "atlas" was chosen over any other (parcellations, meta-analytic maps of canonical networks, etc.). Maybe a brief sentence saying why this and not that would help readers who find themselves in my shoes.

Reviewer #2 (Public review):

Summary:

The study's aim was to establish whether stability in thought patterns relates to the particular thought pattern, the task context, or their interaction. And further, whether stable thought patterns could be linked with distinct brain patterns.

Strengths:

The core reliability framing is novel, and the trait/state/interaction decomposition is a fruitful way to pose the question, leading to the finding that stability is neither a pure trait nor a pure task property, but emerges from their interaction, which is a solid contribution.

The aim to characterise aspects of stability across individuals and across tasks was achieved and is well supported.

Weaknesses:

While the paper makes excellent use of existing data sets, the independent samples, i.e., one study sample for the cognitive/thought-sampling data, and several different study samples to generate the brain maps, do limit the brain-behaviour conclusions that can be drawn.

Reviewer #1 (Public review):

Summary:

This manuscript reports on simultaneous neural recordings in the olfactory tubercle (OTu) and ventral tegmental area in head-fixed mice performing a simple go-nogo odor-guided reversal task. In the task, there were 3 odors that predicted lick-spout water at 0%, 50%, and 100% probability, with 0% and 100% odors reversing at some point each session. The authors fitted this neural data to a value function approximator in which reward prediction errors fed back onto state representations, allowing the optimal set of representations to be learned. They found that model predictions of adjustments to state representations were correlated with trial-by-trial changes in OTu neural activity, from which the authors conclude that such a system, with dopaminergic errors feeding back onto OTu representations of states, which then generate reward predictions, is biologically plausible.

Strengths:

This is a novel and creative modeling approach that has important implications. It seems to be showing the biological plausibility of a model that can learn state representations rather than relying on a fixed set of states that are programmed into the model. This makes tremendous sense, because the real world is much less well-defined than the kinds of tasks conventionally used by neuroscientists to probe reinforcement learning. As such, it is an important demonstration.

Weaknesses:

The task used in this study is quite simple in its state space, and in particular in how it maps sensory stimuli (odors) onto states, such that the task would seem not to require a system that can learn state representations, or at least that it would not be ideal for testing such a model. This mismatch raises some questions about why this model would perform as well as it appears to be doing here.

The model has two updating functions, both using dopaminergic RPE's. One of these maps raw stimuli to state representations using a parameter termed theta; the second maps state representations to a value prediction, using a parameter termed w. The interaction of these two updating functions seems to be giving the model its interesting characteristics. But it is critical to test what the first of these updates is doing in this model, given that odor stimuli appear to map straightforwardly onto states. For example, one might test the effect of ablating this part of the model, leaving only updates of what the authors term w. Relatedly, one might test the extent to which OTu neurons show simple odor selectivity before and after reversals, asking whether these neurons reflect state representations in this model merely by being selective for a particular odor, or if they develop a more complex kind of responsiveness.<br /> The authors compare the full model, which uses a gradient descent update, to a series of alternatives. The fact that the full model performs significantly better than any of the alternatives leads to the conclusion that the brain is using something like this model in this task. But these alternative models are all reduced or simplified versions of the primary model. This suggests that the full model is the best version within the basic framework posed by the authors. But to draw the conclusion that this model is capturing what is occurring in the brain, one would want to test how this model would perform compared to a different class of model, in particular one that assumes a fixed set of states.<br /> A second weakness of the paper is that the authors do not show the behavioral or raw neural data, which would be important to summarize for the sake of transparency and to help readers get an intuitive sense of what is going on in the task and why the model performs as well as it does. One essential issue is: how much training do mice receive before neural data used in the analysis are collected? Do mice get pre-exposure to contingency reversals before analyzed neural data is collected? Relatedly, how quickly (i.e., in how many trials) do mice show behavioral evidence of having learned initial contingencies and then reversed contingencies? What is the behavioral criterion? With regard to the number of trials mice take to learn the reversals, this can change enormously over training, and such changes could have a big effect on how the model performs. Regarding the neural data, one would want to show some measure of odor selectivity of SPN's and DAN's and how each population responds to delivery and omission of reward in different conditions.

Reviewer #2 (Public review):

Summary:

In this paper, the authors use electrophysiological recordings from the olfactory tubercle (OTu) and ventral tegmental area (VTA) of mice learning an olfactory Pavlovian conditioning task to demonstrate the consistency of changes in OTu odour responses with gradient descent updates minimising reward prediction error (RPE). The paper is clearly written and the work well motivated. The authors address a gap in the literature on animal reinforcement learning by providing neural evidence for gradient-based representation learning, something that had been proposed but not yet tested. The results are convincing and the limitations comprehensively addressed. Of particular interest is the proposal that OTu SPNs could solve the weight transport problem through knowledge of the sign of their downstream connections from their expression of either D1/D2 receptors. This makes a concrete experimental prediction that future research could test.

Strengths:

The paper provides one of the first demonstrations backed by neural recordings that representation learning in the brain is consistent with gradient descent. It shows how, although weight transport may be biologically implausible, the brain appears to find other ways to compute a gradient in multilayered networks for efficient learning. The study builds nicely on recent work in systems neuroscience and provides evidence for a concrete implementation in the OTu-VTA circuitry of mice.

The paper demonstrates that changes in OTu striatal projection neuron (SPN) activity over trials are proportional not only to the RPE relayed by VTA dopamine neurons, but also account for the influence of each particular SPN on the RPE. If an SPN decreases the RPE when active, its activity will increase on the next trial after a positive RPE. The activity will instead decrease for an SPN that increases the RPE. This relation is encapsulated in the update rule of Equation 5.

Weaknesses:

The main weakness of the paper is that it provides only indirect evidence for the update mechanism by inferring synaptic weights based on the (justified) assumption of VTA dopamine neurons encoding RPE. This is still a substantial contribution to understanding representation learning in the brain, though I do think that the authors could provide some additional evidence to further convince readers. One idea could be to analyse the distribution of inferred weights and validate whether it agrees with known statistics of connectivity between OTu SPNs and their downstream projections (e.g. fraction of D1/D2 SPNs).

Further, as dopamine neurons are known to have asymmetrical responses for positive and negative RPEs (with the dips in activity related to negative RPEs being generally smaller) I'd expect an improvement in the correlation of the learning updates particularly after the reversal if the authors account for this in the model.

Reviewer #3 (Public review):

Most models of reinforcement learning in the brain treat the question of how the external world is represented as an afterthought. In "Error driven representation learning in the mesolimbic system", the authors begin by calling attention to this limitation of previous work, then proceed to show that neural activity in part of the ventral striatum evolves in a manner consistent with dopaminergic RPE-driven representation learning. Overall, the question is interesting, the modeling is well done, and the claims are bold. While I am not convinced that olfactory tubercle outputs _mainly_ reflect state features acquired through error-driven learning (see main points below), I am now more willing to believe that they might. I am confident that this work will spark discussion.

Strengths:

The latent weight trajectory inference approach is a nice application of Kalman filtering, the model validation and comparison steps are well executed and thorough, the discussion is nicely written and includes an appropriate caveat about the weight transport problem, and the general idea of striatal output being value-like but also having state-like aspects that evolve over time is thought-provoking.

Weaknesses:

In my view, the main limitation of this work is that the authors do not clearly rule out (1) non-representation learning and (2) non-error-driven learning. This fits with the narrow research question stated at the end of the introduction (L71-72), which is confirmatory in nature and does not claim to exclude alternatives, but other aspects of the framing are less consistent.

Main points of criticism

(1) Representation vs. value learning

The first two pages of the manuscript gave me the impression that the authors wish to draw a clear distinction between representation and value learning, and that they would squarely position this paper as a study of representation learning. The substance of the work does not seem consistent with this positioning, a mismatch that could be addressed either by incorporating new analysis and discussion or by changing the framing.

Examples of emphasis on representation:

- Abstract L14-17 defines value and representation learning and states why they are different.

- First three paragraphs of introduction explain the power of learned representations.

- Results L103-108 attribute state representations to OTu and value to downstream regions.

For this level of emphasis, it would be good to see a convincing argument that OTu MSN activity is better understood as a state representation than as the output of a value function.

Options for establishing OTu as state and not value:

- Explicitly claim in the introduction that previous work has established this, and explain why evidence of stimulus valence being encoded in this area (citations on L68-70) does not favour the value interpretation. Discussing how OTu differs from other parts of ventral striatum that are canonically seen as value coding would also help.

- Directly compare the extent of state vs. value encoding in the present data. The $w=1$ control is a good step in this direction, but its connection to value coding is mentioned only in passing.

(2) Error driven learning vs. other types of learning

Similar to my previous point, the authors seem to claim that the representational changes they study are specifically error driven. While the authors include a good number of controls and ablations, it was not obvious to me that any of them correspond to a form of non-error driven learning that could plausibly generate useful representations. Adding Hebbian learning or a sparsifying learning rule would strengthen this aspect of the work.

Reviewer #2 (Public review):

[Editors' note: The Reviewing Editor has assessed the revised article without further input from the original reviewers. The Reviewing Editor noted the authors further addressed a methodological concern, and eLife's Assessment remains unchanged from the previous review.]

Summary:

The study aimed to assess the associations between meteorological drivers and influenza is important although not new. The authors used 6 years of surveillance data and deep learning models, combining distributed lag non-linear models (DLNM) with Bayesian-optimized LSTM neural networks for predictive modeling. The key interest in this area is to explore the subtropical locations, where influenza is less common and circulates year-round. The authors further claimed that such an association could be able to provide an early warning in the community.

Strengths:

Study design based on a prospective cohort to analyse the data for retrospective outcomes.

Reviewer #2 (Public review):

Summary:

This manuscript presents a sophisticated investigation into the mechanisms by which different inhibitor classes affect the SARS-CoV-2 main protease (Mpro), a pivotal antiviral drug target. This study reveals that effective inhibition can be achieved by modulating the stabilization of the essential dimeric state. It also indicates the dimer interface could be a druggable allosteric site, which may offer a strategy for developing broad-spectrum anticoronaviral agents.

Strengths:

The identification of dimer interface stabilization/destabilization as distinct inhibitory mechanisms and the discovery of C300 as a potential allosteric site for ebselen are important contributions to the field. The experimental approach is modern, multi-faceted, and generally well-executed.

Comments on latest version:

All of my concerns have been adequately addressed.

Reviewer #1 (Public review):

Summary:

In this report, the authors investigate the mechanisms underlying large-scale genomic amplification (DIGA) induced by genome-wide DNA double-strand breaks (DSBs), such as those generated by ionizing radiation (IR).

Strengths:

The authors demonstrate that DSB-induced DIGA does not require origin re-licensing but is dependent on proteins involved in break-induced replication (BIR). This finding represents a major strength of the study, as it reveals a previously unrecognized mechanism of DSB-induced genomic amplification. Additional strengths include the demonstration that DIGA is promoted by DNA end resection and suppressed by the 53BP1-RIF1-shieldin pathway. The authors also show that SET8 and SUV4-20H1 have opposing effects on CDT1 overexpression-induced and IR-induced re-replication. Furthermore, the finding that the extent of DIGA in cancer cells correlates with sensitivity to IR has potential implications for cancer treatment.

Weaknesses:

However, more comprehensive studies are needed to strengthen the conclusions. Although IR- or DSB-induced DIGA was observed in multiple cancer cell lines, the overall mechanisms underlying why DIGA is more pronounced in certain cell lines but not others remain unclear. Beyond p53 status, additional factors that determine DIGA susceptibility should be investigated. In addition, the evidence that DIGA-associated DNA synthesis occurs within the same cell cycle is not yet sufficient. For instance, a time-course experiment (EdU versus DAPI) should be performed after IR to determine when DIGA initiates relative to normal S-phase DNA replication. A parallel analysis of re-replication at different time points following MLN4924 treatment would provide a useful comparison. Cyclin B and phospho-histone H3 (Ser10) levels should be monitored to define cell cycle stage. Additional evidence supporting a BIR-dependent mechanism, such as demonstrating conservative DNA synthesis and mapping DIGA sites following AsiSI-induced DSBs, would be needed.

Overall, this study provides new insights into the mechanisms driving genome-wide amplification following DSB formation. Additional mechanistic studies will further strengthen the conclusions and broaden the impact of this work.

Reviewer #2 (Public review):

Summary:

In this study, Benamar et al. investigate whether DNA double-strand breaks induce extensive abnormal DNA synthesis in cancer cells and whether this response contributes to the cytotoxic effects of ionizing radiation and other DNA-damaging treatments. The authors refer to this process as double-strand-break-induced genomic amplification (DIGA). Mechanistically, they propose that insufficient protection of broken DNA ends permits excessive resection, followed by RAD51-dependent strand invasion and RAD52-POLD3-POLD4-dependent DNA synthesis resembling break-induced replication.

Overall, the study addresses an interesting and potentially important question. Break-induced replication was originally defined as a pathway that repairs one-ended DNA breaks through extended synthesis from an invaded homologous template. Studies in yeast established that this process involves a migrating DNA-synthesis bubble, conservative inheritance of newly synthesized DNA, frequent template switching, and high mutagenicity. Related forms of DNA synthesis have subsequently been described in mammalian cells at collapsed replication forks, telomeres, under-replicated mitotic regions, and some transcription-associated DNA breaks.

The important advance of this study is the proposal that double-strand-break-associated DNA synthesis, with several features of break-induced replication, can become sufficiently extensive to cause a measurable increase in total cellular DNA content and that this synthesis correlates with radiation-induced cell death. However, the physical structure, genomic distribution, and extent of the additional DNA have not yet been directly established.

Strengths:

Radiation-induced breaks are generally considered in relation to DNA repair, chromosome rearrangements, checkpoint activation, mitotic failure, senescence, and cell death. The possibility that broken DNA ends can also initiate extensive DNA synthesis provides a potentially important additional link between defective break repair, genome amplification, and treatment-induced cytotoxicity.

The authors examine this phenomenon using several complementary approaches and comparisons across multiple cancer cell lines. The finding that several double-strand-break-inducing treatments produce a similar response suggests that the phenotype is not restricted to ionizing radiation or to a single cellular background.

The authors also make efforts to distinguish DIGA from canonical origin-dependent re-replication, such as that caused by CDT1 stabilization and inappropriate origin relicensing. They find that, following irradiation, CDT1 is degraded rather than stabilized and that CDT1 depletion does not suppress DIGA. Perturbation of ORC1 or ORC2 also has little effect on the phenotype. In addition, depletion of SET8 or loss of SUV4-20H1 increases, rather than decreases, DIGA.

The authors carry out a systematic analysis of DNA-end protection and processing. Loss of ATM, RNF8, RNF168, 53BP1, RIF1, or Shieldin components enhances DIGA, whereas depletion or inhibition of CtIP, MRE11, EXO1, RAD51, RAD52, POLD3, or POLD4 suppresses it. These experiments support a model in which insufficient end protection permits excessive DNA-end resection, followed by strand invasion and recombination-associated DNA synthesis involving factors linked to break-induced replication.

Overall, the findings place DIGA within a growing body of evidence that recombination-associated DNA synthesis can extend well beyond short repair patches. The study attempts to connect the processing of double-strand breaks with abnormal DNA synthesis, increased cellular DNA content, and the cytotoxic response to radiation.

Major weaknesses and suggested experiments:

(1) The main evidence for DIGA is the appearance of cells with greater-than-G2/M DNA content by flow cytometry. BrdU incorporation shows that active DNA synthesis occurs within this population, and the density-gradient experiments provide further evidence for newly synthesized DNA. However, these methods do not reveal the physical nature of the proposed genomic amplification-for example, which genomic regions are copied or how long the synthesis tracts are.

This is important for the central conclusion of the study because mammalian break-induced replication can produce genomic duplications, but the extent of synthesis depends strongly on the type of DNA lesion. Previous work has shown that repair of damaged replication forks can produce segmental genomic duplications (Costantino et al., 2014; PMID: 24310611). By contrast, recent measurements at defined two-ended double-strand breaks suggest that mammalian break-induced-replication tracts can be relatively restricted (Li et al., 2021; PMID: 33470420; Shah et al., 2024; PMID: 39368985).

Thus, the large increase in total DNA content detected by flow cytometry in this study would require many simultaneous synthesis events, very long synthesis tracts, or an alternative process such as whole-genome duplication. The authors should therefore characterize the additional DNA directly. Whole-genome sequencing of sorted cells with greater-than-G2/M DNA content could be particularly informative.

(2) The genetic dependencies are consistent with synthesis initiated from resected DNA ends, but they do not directly demonstrate that the new DNA synthesis begins at double-strand breaks. DNA damage could indirectly alter replication-origin activity, cell-cycle progression, or DNA synthesis at genomic regions distant from the original lesions. Increased DNA content alone therefore does not establish amplification initiated directly at DNA breaks.

(3) MLN4924-induced re-replication is used throughout the study, but it is unclear whether the authors have combined MLN4924 with ionizing radiation and measured the resulting DNA synthesis. This experiment could clarify whether conventional re-replication and DIGA are independent, overlapping, or mechanistically connected.

(4) The results involving canonical non-homologous end joining are complex. Loss or inhibition of DNA-PKcs increases DIGA, whereas loss of XRCC4 or XLF strongly suppresses it, and loss or inhibition of LIG4 has a weaker suppressive effect. The authors suggest that XRCC4 and XLF stabilize broken DNA ends and thereby permit the synthesis reaction independently of final ligation. This is an interesting model, but the current evidence does not yet establish it. XRCC4 and XLF can affect end synapsis, break persistence, chromosome fusion, resection, and cell-cycle progression. Their loss could therefore reduce DIGA through several indirect mechanisms. The authors should measure DNA-end resection, RAD51 loading, persistence of double-strand breaks, and recruitment of RAD52 or POLD3 in XRCC4-, XLF-, and LIG4-deficient cells. Complementation with separation-of-function mutants that differentially affect XRCC4-XLF end bridging and LIG4 recruitment could test whether end stabilization, rather than ligation, is important. Without this, the opposing effects of upstream and downstream non-homologous end-joining components remain difficult to understand.

(5) The correlation between the amount of DIGA and radiation sensitivity across cancer cell lines is interesting. However, cell lines differ in many factors that influence radiation responses, including p53 status, apoptosis, checkpoint activity, ploidy, homologous recombination capacity, and proliferation rate. Matched models would provide stronger evidence. Conversely, restoring DNA-end protection in a DIGA-prone cancer cell line could test whether this reduces susceptibility. These experiments would help determine whether DIGA is a general property of cancer cells or a feature of particular repair-defective genetic backgrounds.

Reviewer #3 (Public review):

Summary:

In this study, the authors show that exposure of cancer cells to DSBs induced enzymatically or by ionizing radiation (IR) results in large-scale genomic amplifications (DIGA: DSB-induced genomic amplifications) that are detectable by FACS. This phenomenon was observed in diverse cancer cell lines and was shown to be limited by p53 in paired cell lines. In principle, DIGA could result from re-initiation of DNA synthesis within the same cell cycle, mitotic segregation errors, or repair-associated DNA synthesis. The authors conduct experiments to distinguish between these possibilities and conclude that DIGA is the result of extensive RAD51-dependent DNA synthesis.

Strengths:

The observation of genome amplification in response to DSBs specifically in cancer cells is striking, particularly at high IR doses or by AsiSI endonuclease induction. At 9 Gy, almost 50% of cells have a >4N DNA content. The correlation between high levels of DIGA and reduced clonogenic survival of melanoma cells suggests that DIGA contributes to IR-induced cytotoxicity. The authors convincingly show that DIGA occurs in a single cell cycle and is not due to chromosome mis-segregation at mitosis. Because DIGA is partially dependent on resection nucleases, POLD3, POLD4, RAD52 and RAD51, the authors conclude that DIGA results from repair synthesis by a BIR-like process.

There are significant weaknesses in the study:

(1) It is unclear to this reviewer how BIR-like synthesis could increase genomic DNA copy number by 50% or more, as indicated by the FACS plots. In the case of AsiSI, there are ~150 sites that are efficiently cleaved in U2OS cells. Each of these sites would need to prime extensive synthesis by an inefficient migrating D-loop mechanism. Studies of BIR-like synthesis at DSBs in U2OS cells have shown that repair tracts are fairly short, around 3-10 kb in length. Thus, it is hard to rationalize how BIR at a few hundred DSBs could initiate such large changes in genome size.

(2) The BrdU-FACS plot shown in Figure S4 shows that most of the cells have an 8N content 48 and 72 h after AsiSI induction and do not have much BrdU incorporated. This finding would suggest that genomic DNA doubling is mostly independent of de novo synthesis. Also, there does not seem to be a continuum from 4N up to 8N in these plots as one might expect from variable length DNA synthesis tracts.

(3) The requirement for XRCC4, XLF and LIG4 to promote DIGA is puzzling if synthesis occurs by a BIR-like mechanism. Although there is evidence that DNA synthesis at DSBs can be initiated by homology-directed strand invasion and terminated by NHEJ, this mechanism would limit the extent of synthesis to a few kb at each site. One might have expected an increase in DIGA in the absence of core NHEJ factors because of the increased number of DSBs available for BIR.

(4) Although the authors rule out re-replication as a contributor to IR-induced DIGA, the FACS profiles of MLN4924 and 9 Gy treatment look remarkably similar, and both would be inhibited by aphidicolin treatment. A previous study showed that DSBs induce endoreduplication in Arabidopsis (Adachi et al. PNAS 2011).

【方法】文章建议需要立即审查安全模型，但没有提供具体的实施步骤或时间表。需要了解这些审查的具体内容、涉及的部门、预期的完成时间，以及如何衡量这些审查的有效性。缺乏这些细节使得这些建议难以转化为实际行动。

Reviewer #1 (Public review):

Summary:

Dong et al. present an in-depth analysis of mutant phenotypes of the Rab GTPases Rab5, Rab7, and Rab11 in Drosophila second-order olfactory neuron development. These three Rab GTPases are amongst the best-characterized Rab GTPases in eukaryotes and have been associated with major roles in early endosomes, late endosomes, and recycling endosomes, respectively. All three have been investigated in Drosophila neurons before; however, this study provides the most detailed characterization and comparison of mutant phenotypes for axonal and dendritic development of fly projection neurons to date. In addition, the authors provide excellent high-resolution data on the distribution of each of the three Rabs in developmental analyses.

Strengths:

The strength of the work lies in the detailed characterization and comparison of the different Rab mutants on projection neuron development, with clear differences for the three Rabs and by inference for the early, late, and recycling endosomal functions executed by each.

Comments on revised version.

The authors conducted extensive revision experiments, especially to characterize developmental defects. Efforts to identify cargoes were not successful. The evidence is now convincing.

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 of 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 manuscript is well-written and explanatory, very accessible to a wide audience without sacrificing technical accuracy.

Comments on revised version.

The paper is greatly improved with new data and better-nuanced interpretation. The clarity of explanations for a non-Drosophila reader have been redone particularly well.

Reviewer #3 (Public review):

Summary:

The authors aimed at a comprehensive phenotypic characterization of the roles of all Rab proteins expressed in PN neurons in developing Drosophila olfactory system. Important data are shown for a number of these Rabs with small/no phenotypes (in the Supplements) as well as the main endosomal Rabs, Rab5, 7, and 11 in the main figures.

Strengths:

The mosaic analysis is a great strength allowing visualization of small clones or single neuron morphologies. This also allows some assessment of cell autonomy of the observed phenotypes. The impact of the work lies in the comprehensiveness of the experiments. The rescue experiments are a strength. The added developmental data strengthen the impact of the paper.

Weaknesses:

The main weakness is that the experiments do not address the mechanisms that are affected by the loss of these Rab proteins, especially in terms of the most significant cargos. The insights thus do not extend far beyond what is already known from other work in many systems.

Reviewer #1 (Public review):

Summary:

The authors sequenced 888 individuals from the 1000 Genomes Project using the Oxford Nanopore long-read sequencing method to achieve highly sensitive, genome-wide detection of structural variants (SVs) at the population level. They conducted solid benchmarking of SV calling and systematically characterized the identified SVs. While short-read sequencing methods, including those used in the 1000 Genomes Project, have been widely applied, they exhibit high accuracy in detecting single nucleotide variants (SNVs) and small insertions and deletions but have limited sensitivity for SV detection. This study significantly enhances SV detection capabilities, establishing it as a valuable resource for human genetic research. Furthermore, the authors constructed an SV imputation panel using the generated data and imputed SVs in 488,130 individuals from the UK Biobank. They then conducted a proof-of-principle genome-wide association study (GWAS) analysis based on the imputed SVs and selected traits within the UK Biobank. Their findings demonstrate that incorporating SV-GWAS analysis provides additional insights beyond conventional GWAS frameworks focusing on SNVs, particularly in improving fine-mapping.

Strengths:

The authors constructed a high-sensitivity reference panel of genome-wide SVs at the population level, addressing a critical gap in the field of human genetics. This resource is expected to significantly advance research in human genetics. They demonstrated the imputation of SVs in individuals from the UK Biobank using this panel and conducted a proof-of-concept SV-based GWAS. Their findings highlight a novel and effective strategy for integrating SVs into GWAS, which will facilitate the analysis of human genetic data from the UK Biobank and other datasets. Their conclusions are supported by comprehensive analyses.

Weaknesses:

The authors have addressed many of my previous comments, and I appreciate their efforts. However, I still have two related concerns.

(1) Shortly after reviewing this manuscript last year, my laboratory obtained access to the UK Biobank (UKB) Tier 3 dataset for an unrelated project. In August 2025, I searched the UKB Research Analysis Platform (UKB-RAP) for the imputed structural variant (SV) dataset described in this manuscript but was unable to locate it. After contacting UKB, I was informed that they were developing the system for releasing the data. To the best of my knowledge, the dataset remains unavailable. A major contribution of this work is the generation of an imputed SV resource for approximately 500,000 UKB participants with extensive phenotypic information. If this resource is not accessible to the research community, even to authorized UKB users, the practical impact and utility of the study are substantially diminished.

(2) Given that the imputed SV dataset is currently unavailable, it becomes even more important for the authors to provide a detailed, ready-to-run SV imputation pipeline for UKB-RAP, even if the "data processing simply consisted of running standard bioinformatics tools with the parameters exactly as described in the manuscript". In particular, the pipeline should include practical information such as computational requirements (e.g., memory and storage), expected running time, and estimated cost. Anyone with experience using UKB-RAP will agree that reproducing large-scale analyses on the platform can be both technically complex and financially expensive. Such pipeline would greatly improve the reproducibility and accessibility of this work.

Because my initial assessment of the manuscript was generally positive, I do not wish to change my overall evaluation, summary, or assessment of its strengths. However, I would view the work even more favorably if either (i) the imputed SV dataset became publicly available to authorized UKB users, or (ii) the authors extended their SV-GWAS analyses to the full range of UKB phenotypes and released the resulting summary statistics, analogous to the Pan UKBB ("https://pan.ukbb.broadinstitute.org/") resource. Although this would require considerable additional effort and computational resources, it would substantially enhance the long-term value and impact of the study.

Finally, I would like to emphasize that these comments are not intended to create unnecessary difficulties for the authors or the editors. Rather, I believe this highlights a broader issue in the use of this kind of large public datasets: reviewers cannot independently verify key results, and readers cannot readily build upon the work if the underlying resources are inaccessible, even after obtaining authorized access to the original dataset. I hope the authors, together with the eLife editors and UK Biobank where appropriate, can help facilitate the timely release of this valuable resource.

Reviewer #1 (Public review):

Summary:

In this MS, Muenker and colleagues, explore the intracellular mechanics of a range of animal adherent cells. The study is based on the use of an optical tweezer set up, which allows to apply oscillatory forces on endocytosed/phagocytosed glass beads with a large frequency range (from ~1 to 1000 Hz) , allowing to probe cytoplasm material properties at multiple time scales. By switching off the laser trap, the authors also record the positional fluctuations of beads, to extract passive rheological signatures. The combination of both methods allow to fit 6 parameters (from power law fits) that allow to characterize the viscous and elastic nature of the cytoplasm material as well as an effective active energy driven by cellular metabolism. Using these methodologies, the authors first establish/confirm, using HeLa cells, that the cytoplasm is more solid like at short frequencies, and more fluid like at higher frequencies, and that these material states depend on both microtubules and actin cytoskeleton. The manuscript then goes on to explore how these parameters evolve in other 6 cell types including muscles, highly migratory and epithelial cells. These results show for instance that muscle cells are much stiffer, while migratory cells are more fluid like with an increased active energy. Finally using statistical methods and principal component analysis , the authors establish some mechanical fingerprints (activity, fluidity and resistance) that allow to distinguish cell's mechanical state and relate it to their particular functions.

Strengths:

Overall, this is a very well executed work, which provides a large body of rigorous numbers and data to understand the regulation of cytoplasm mechanics and its relation to cell state/function. This work opens up on the possibility to systematically link cellular phenotype and cytoskeleton organization to intracellular mechanical signatures among many cell types and contexts.

Reviewer #2 (Public review):

Summary:

By analyzing cells' frequency-dependent viscoelastic properties and intracellular activity through microrheology, Münker et al simplify the complex active mechanical state into six key parameters that constitute the mechanical fingerprint. They apply this concept to cells treated with cytoskeleton-inhibiting drugs. Additionally, a comprehensive statistical analysis across various cell types shows how cells coordinate their mechanical properties within a defined phase-space marked by activity, mechanical resistance, and fluidity.

Strengths:

(1) The distribution of the six parameters: they have been well characterized based on established theories, and they can be used to understand cell-type-specific biomechanical differences. The examples of muscle cells and immune cells were profound and informative.<br /> (2) Efforts to perform dimension reduction of parameter space into activity (E), fluidity (C1) and resistance (A) are insightful and will be helpful for future characterization of cell mechanics.

Comments on revised version.

In the original submission, cytochalasin B alone showed little effect on viscoelastic and active energy parameters, and it was unclear whether this reflected a true absence of actin's role or an artifact of the perturbation method used. In the revised manuscript, the authors addressed this by repeating the cytochalasin B measurements with larger sample sizes and adding latrunculin A, a mechanistically distinct and more potent actin-depolymerizing drug, together with immunostaining to confirm cytoskeletal disruption. This convincingly shows that actin depolymerization does affect the solid-like prefactor and fluidity, resolving the original concern.

Nocodazole-induced microtubule depolymerization previously did not appear to reduce the solid-like property A, which was unexplained. The revised manuscript removes the speculative compensation-mechanism explanation, adds a discussion comparing the results to prior AFM literature (explaining the discrepancy as reflecting different mechanical compartments probed - cortex vs. intracellular), and the new data now show a significant reduction of A with nocodazole treatment as well. This weakness is resolved.

Reviewer #3 (Public review):

Summary:

Cells and tissues are viscoelastic materials. However, metabolic processes that underly survival, growth and migration render the cell as an active matter at non-equilibrium. These two facts contribute to the difficulty of probing mechanical properties especially with sub-cellular resolution. However, the concept that the mechanical phenotype can be indicative of normal physiology necessitates approaches of defining the cellular phenotype. Here, Muenker et al evokes a powerful argument for mapping intracellular mechanics using optical tweezer- active microrheology. They present a suite of parameters towards a definition of a mechanical fingerprint. This is a compelling idea. There are some concerns as detailed below

Strengths:

These are technically challenging experiments and the authors provide systematic approaches to probe a system at non-equilibrium.

Weaknesses:

The importance of the mechanical fingerprint is diluted due to some missing controls needed for biological relevance. As it reads, sinusoidal waves are applied sequentially from 1- 1024Hz.<br /> Please clarify if amplitude is the same for each frequency, also how many frequencies are used?

On this point, due to perturbations due to alterations in pre-stress, are the orders of frequencies randomized?

How many beads are probed in a given cell.

Is the graph in 1 c G', G" per cell or average of many cells?

Figure 1e is quite nice, however is there an equivalent performed in a non-linear ECM such as collagen for comparison, in a similar vein can the equivalent be calculated for cells with/without treatment with low doses of cycloheximide to reduce protein synthesis? Yes, cytoskeletal elements are important for cell mechanics, but cytoplasm crowding is often an overlooked factor.

The biggest issue is the interpretation of the different factors as each of these cells have different energetic needs.<br /> The comparison between cancer cells with different aggressiveness, immune and epithelial cells.<br /> For example, some types of cancer cells will be dominated by glycolysis vs oxphos, which will influence both the cytoplasmic and nuclear mechanics?

It would be useful to carefully assess factors not restricted to<br /> a) Cytoskeleton<br /> b) Protein synthesis<br /> c) Metabolic state

For similar lines and/ or cells where there are lineages that are either more metastatic in cancer, normal counterpart or drug resistant in an effort to link the fingerprint to a biological output. Specifically, is migration, proliferation, survival correlated with the measurements.

The reviewer is sensitive to the technical difficulties of the experiments. However, the interpretation and importance of the mechanical fingerprinting requires additional work as mentioned above.

Reviewer #1 (Public Review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers.]

Summary:

The study claims to explore plant microbiome engineering using host-mediated selection as a strategy to enhance rice growth and drought tolerance.

Strengths:

The authors have derived and identified simplified microbiomes from wild microbial communities of rice fields, deserts, and serpentine seep soils by selecting microbiomes from plants with desired phenotypes across generations. Metagenome-assembled genomes revealed enriched functions, such as glycerol-3-phosphate and iron transport, known to mediate plant-microbe interactions during drought.

Reviewer #2 (Public Review):

Summary:

In this study, Styer et al. impose artificial selection on root-associated microbiomes to increase drought tolerance in rice plants using different soils as starting microbiomes. Using NDVI and biomass as a proxy for plant health, they find that iterative passaging of the microbiomes of the best-performing plants increased plant resilience to drought stress in a soil-dependent manner. The study makes use of numerous controls. The authors survey the microbiota of the plants across generations, using an array of interesting analyses to characterize their observations. Firstly, the authors find that the acquired microbiomes are divergent towards the beginning of the selection experiment, but nearly converge later suggesting that the selected communities become more similar over time. One reason is that the diversity of the microbiomes severely decreases after only one or two generations of selection AND that microbes from each inoculation source appear to easily disperse across the experiment, leading to microbiome homogeneity. The authors then present an analysis to correlate ASVs with the NDVI and Biomass over the course of the experiment (using the rice soil selection lines) to develop hypotheses about which ASVs may impact plant traits.

Strengths:

The authors set out to refine the understanding of microbiome artificial selection, a topic of recent interest to the plant microbiome field. The authors use an established approach (Mueller et al), expanding upon it by including multiple starting soil inocula to ask whether the strength of selection varies by input microbiome. This is an important and novel question. Using drought resilience as measured by NDVI and plant biomass to select upon was a wise choice for this type of study, given their relative ease and quickness to assess. The inclusion of several types of controls, multiple selection lines, and several starting soil inocula showed a thoughtful experimental design. The analyses were diverse, non-standard, and attempted to address microbiome dynamics on multiple fronts. I am not necessarily convinced by some of the conclusions (see below), however, I think this study examines an important and exciting topic in the area of plant microbiomes. I predict the findings of the experiments will inform a wide audience of researchers attempting similar studies and be helpful in their designs.

Reviewer #3 (Public Review):

Summary:

In this work, Styer et al. explore host selection as a means for recruiting microbes that may aid their host under stressful conditions, in this case under drought stress, as an alternative to target-SynCom design. They do so by subjecting rice plants to several generations of soil transplantation, and by using the most successful rice plants as donors for the next generation. By using several NGS approaches and very thorough bioinformatics analysis, the authors identify potential microbial taxa and the associated functions enriched in the conditions of interest.

Strengths:

In general, I think this approach was very much needed in the field as an alternative to SynComs, which are still not readily usable in croplands. This work sets the grounds for future similar approaches, using different stresses and different host plants.

In this work, the experimental setup is well thought-through and well-replicated. In addition, an exhaustive set of preliminary experiments was performed before deciding on the final panel of soils to use and scoring methodology. The figures are clear and well-explained.

Reviewer #1 (Public review):

Dwulet et al. combined experimental and modeling approaches to investigate how correlated spontaneous activity in the mouse's primary visual (V1) and primary somatosensory (S1) areas drives the development of multisensory integration in area RL. Notably, they focused on early developmental stages, before sensory experience occurs. Consistent with previous experimental findings, the authors first demonstrated that spontaneous activity becomes more sparse across development in all three areas, as measured by event amplitude, event duration, and participation ratio. Using a linear mixed model analysis to compare the maturation of this spontaneous activity, they found evidence that S1 matured the fastest. The authors then presented experimental evidence suggesting that these spontaneous events were moderately correlated both spatially and temporally.

They hypothesized that activity-dependent mechanisms use these correlations to establish connectivity across these regions. To test this hypothesis, the authors modeled a feedforward network with connections from S1 to RL and from V1 to RL, where the strength of connections depended on a Hebbian term for potentiation and a heterosynaptic term for depression. By investigating different levels of V1-S1 correlations, they found that moderate levels of correlation led to the significant development of topographically organized connectivity while maintaining a mix of bimodal and unimodal cells in RL. Additionally, when simulating a network with a more mature S1, they observed that topographical maps improved not only between S1 and RL but also between V1 and RL. Finally, the authors use linear regression to suggest that the mixture of bimodal and unimodal cells in RL is optimal for encoding the maximum amount of information from both V1 and S1.

Comments on revised version:

The revision closes most of the data-model gaps raised in my original review. The authors have clarified the experimental measures and statistical comparisons, improved the spatial correlation-map analysis, added a temporal-lag analysis that argues against stereotyped traveling waves, expanded the model description, and performed additional simulations examining the effects of differences in spontaneous activity. Taken together, these changes provide solid support for the paper's principal conclusion: structured and moderately correlated activity can, within the proposed model, guide the refinement of an initially coarse connectivity scaffold into aligned multisensory representations.

The remaining limitations primarily concern the more specific claim that the somatosensory pathway matures first and guides refinement of the visual pathway. The experiments support the conclusion that spontaneous activity in the somatosensory cortex matures earlier. However, the proposed consequence of this difference is carried in the model by an assumed stronger initial somatosensory-to-higher-order connectivity bias, motivated by pilot anatomical observations that are not included quantitatively in the manuscript. The new supplementary simulations suggest that differences in activity amplitude and frequency alone are insufficient, but the parameters are varied over ranges considerably smaller than the differences measured experimentally, and event duration is not varied. These simulations therefore do not strongly establish that the measured activity differences are insufficient to produce the effect. In addition, the Figure 4 caption and portions of the Discussion continue to imply that more mature somatosensory activity itself instructs map alignment, whereas the revised Results present the more qualified conclusion that an additional connectivity difference is required.

A few internal inconsistencies also remain. The abstract still describes activity in the three areas as being recorded simultaneously, although the cellular-resolution recordings were acquired sequentially; only the wide-field data were collected simultaneously across areas. The revised model also assigns spontaneous events durations and intervals in milliseconds, while the measured calcium events last several seconds and occur only a few times per minute.

Reviewer #2 (Public Review):

The revised manuscript has substantially improved, and the authors have satisfactorily addressed most of the concerns raised in my original review. Overall, the experimental evidence and its relationship to the computational model are now presented more clearly and rigorously, substantially strengthening the manuscript.

My main reservation in the original review concerned the role of the initial topographic connectivity bias in the computational model. The revised manuscript provides a clearer interpretation of this aspect. The initial bias represents a coarse activity-independent scaffold, while the final organization of the maps depends on its interaction with the structure and degree of correlated spontaneous activity. Importantly, the simulations show that the presence of the initial bias alone does not determine the final connectivity pattern. I therefore consider the computational results substantially better supported and interpreted in the revised manuscript. Nevertheless, as the model starts from a predefined coarse topographic organization of the projections from the primary sensory cortices to RL, in my opinion, the results demonstrate how structured spontaneous activity can refine and align an initially organized connectivity scaffold, rather than showing that spontaneous activity itself establishes this topographic organization.

This distinction is relevant when interpreting the central mechanistic conclusion of the study. The work provides convincing support for the idea that correlated spontaneous activity can contribute to the refinement and alignment of multisensory cortical maps, conditional on the existence of an initial coarse topographic organization. Establishing experimentally how this initial connectivity is organized during the relevant developmental period, and how spontaneous activity modifies it, remains an important question for future work.

Overall, I consider the revised manuscript considerably stronger than the original submission. Most of my previous concerns have been adequately resolved, and the study provides valuable experimental and computational insight into how spontaneous activity may contribute to the development of aligned multisensory representations.

Reviewer #3 (Public review):

Summary:

The study by Dwulet et al. explores how the development of spontaneous neural activity in primary sensory cortices influences the co-alignment of multiple sensory modalities in higher-order brain areas (HOAs). To address this question, they focus on connectivity between the primary visual (V1) and somatosensory (S1) cortices and an associative cortical area (RL) in mice. The authors combine experimental (wide-field and two-photon calcium imaging) and computational approaches to show that spontaneous activity matures at a different pace across these brain regions. Their data indicate that S1 develops more rapidly than V1, which is possibly beneficial for RL's integration of visual and somatosensory inputs through correlated spontaneous activity. Using a computational model, they demonstrate that a moderate correlation between V1 and S1 activity can optimally guide the formation of bimodal neurons in RL, which are crucial for maximizing the decodability of multisensory stimuli. This finding highlights the role of correlated spontaneous activity in primary sensory cortices in establishing co-aligned topographic multimodal sensory representations in downstream circuits.

Strengths:

The manuscript is well written and it provides strong enough evidence to support the main claim of the authors. The insights on the role of correlated activity on instructing co-aligned multisensory maps in HOAs are not trivial and are an important advancement for the field.

Weaknesses:

In the opinion of this reviewer, the study has no major weaknesses. A drawback of the work is that none of the predictions of the computational modeling have been corroborated through mechanistic experimental manipulations of early brain activity.

Comments on revised version:

The authors have addressed all my previous concerns. I have no further comments.

Reviewer #1 (Public review):

Summary:

This study builds on earlier work showing that early-life odor exposure can trigger glial-mediated pruning of specific olfactory neuron terminals in Drosophila. Moving from indirect to direct functional imaging, the authors show that pruning during a narrow developmental window leads to long-lasting suppression of odor responses in one neuron type (Or42a) but not another (Or43b). The combination of calcium and voltage imaging with connectomic analysis is a strength, though the voltage imaging results are less straightforward to interpret and may not reflect synaptic output changes alone.

Strengths:

Biologically, one of the main strengths of this work is the direct comparison between two odor-responsive OSN types that differ in their long-term adaptation to early-life odor exposure. While Or42a OSNs undergo pruning and remain persistently suppressed into late adulthood, Or43b OSNs, which also respond to the same odor, show little lasting change. This contrast not only underscores the cell-type specificity of critical-period plasticity but also points to a potential role of inhibitory network architecture in determining susceptibility. The persistence of the Or42a suppression well beyond the developmental window provides compelling evidence that early glia-mediated pruning can imprint a stable, life-long functional state on selected sensory channels. By situating these functional outcomes within the context of detailed connectomic data, the study offers a framework for linking structural connectivity to long-term sensory coding stability or vulnerability.

Comments on revised version:

I thank the authors for their careful revision and thoughtful responses to the reviewers' comments. The revised manuscript addresses my previous concerns in a satisfactory manner, and the interpretation of the findings has been appropriately clarified and balanced. I have no further major comments.

Reviewer #2 (Public review):

Recent work from the authors identified the synaptic changes and glial reaction that occurs during exposure of a Drosophila odorant receptor neuron population to continued exposure of a stimulating odorant. This work markedly advanced our understanding of cellular response to critical periods. This current Advance manuscript carries that work forward and examines the non-autonomous responses to constant odorant exposure. The authors discover that the changes to ORN populations are not accompanied by changes to either PN dendrite or PN axon volume, nor are they concurrent with changes in postsynaptic PN structures. These changes are, however, notable accompanied by changes in Ca2+ and voltage responses in ORNs. Importantly, this set of responses is specific for the Or42a ORNs (that are highly sensitive to the odorant in question, ethyl butyrate) and not the Or43b ORNs (which respond to ethyl butyrate, but not as drastically). Finally, the authors include connectomics analyses showing that Or43b and Or42a ORNs differ in their synaptic input/output relationships.

This is an excellent use of the Advance mechanism for the journal as these are important follow-up findings for the parent story. The non-autonomous effects (or lack thereof) on PNs is an important part of the story as is the functional response of Or42a ORNs and the differing response of similarly (but not identically) sensitive Or43b ORNs. The experiments are well conceived, controlled, and conducted. Where the story falters a bit, though, is with the connectomics analysis. The authors show distinct differences between Or43b and Or42b ORN input output relationships and suggest that those differences may underlie the differences observed in their response to ethyl butyrate exposure during the critical period. This is certainly a possibility, but as it stands now, it is too disconnected to offer significant proof. There would have to be additional experiments to address this. Right now, the inclusion of the connectomics work feels like a distraction at best, and a complete non sequitur at worst. To be clear, the connectomics work is well done and I have no issues with its validity, but is not helpful to the central thesis of the work. I would suggest the authors either remove it entirely or strongly rethink how it fits into the paper.

Comments on revised version:

I appreciate the consideration of my comments and the authors' responses. The additional data on PN synapse number is intriguing (and welcome) as is the text discussing potential postsynaptic compensatory mechanisms. I respect the authors' decision in retaining the connectivity analysis, but despite the textual changes, I still feel that it is peripherally related to the main thesis of the work and would best be omitted from the paper and included in a separate, more relevant study. Ultimately, though, that is their choice.

Reviewer #1 (Public review):

Summary:

Recent findings have established that macrophage function is tailored to individual tissues through upregulation of tissue-specific transcription factors in response to local microenvironmental signals. However, how these transcriptional pathways affect macrophage lipid metabolism and the importance of this for homeostasis of neighbouring immune cells remains relatively uncharted. One exemplary pathway is the specific expression of GATA-6 by macrophages within the serous cavities that is triggered by local retinoic acid production. Here, Czubala et al have used mice with macrophage-specific deletion of GATA6 (GATA-6KO-mye) to study the importance of tissue-specific macrophage programming in regulating the macrophage and tissue lipidome and the functional importance of this for the regulation of eosinophil numbers in the tissue.

Strengths and Weaknesses:

The authors show accumulation of lipid-rich vesicles in the absence of GATA6, which lipidomic analysis suggests are largely comprised of sphingolipids and glycophospholipids. Using published transcriptional data identifies candidate genes in GATA6-deficient cells that may underlie these changes. Manipulating two of these candidate genes, Gba2 and Smpd1, in a macrophage cell line leads to similar changes in sphingolipid composition to those in GATA6-deficient macrophages in vivo, supporting the hypothesis that tissue specialisation of peritoneal macrophages induces transcriptional changes via GATA6 that directly control sphingolipid metabolism. GATA6 deficiency is then shown to affect the oxylipin content of peritoneal macrophages and peritoneal fluid, including higher levels of LTE4 in fluid. Elevated expression of the Ltc4s in GATA6-deficient cells is predicted as the likely mechanism leading to elevated LTE4.

To determine the functional effects of altered lipid metabolism, and specifically LTE4, the authors focus on the elevated accumulation of peritoneal eosinophils previously reported to occur in GATA-6KO-mye mice. They show that eosinophils undergo less apoptosis in these mice and the absence of a measurable increase in known eosinophil chemokines leads them to conclude that eosinophil numbers arise through increased longevity. However, this point remains to be formally demonstrated, and directly measuring the longevity of eosinophils in the cavity would greatly strengthen their conclusions. The authors then examine known regulators of eosinophil survival, IL-5 and GM-CSF. They convincingly demonstrate a role for IL-5 in the regulation of peritoneal eosinophil numbers but conclude that survival factors other than IL-5 and GM-CSF likely control the differential numbers in control and GATA-6KO-mye mice, given IL-5 was observed to be a general survival signal in both genotypes and that no difference in the levels of these growth factors was observed in lavage fluid between genotypes. The authors then blocked production of prostaglandins using the inhibitor indomethacin. This treatment also led to a general reduction in survival and number of eosinophils in both control and GATA-6KO-mye mice, leading to the conclusion that altered prostaglandin production is not the underlying mechanism regulating elevated eosinophil numbers in the absence of GATA6.

One weakness in these conclusions is that if the GATA-6-KO-mye phenotype does lead to increased production of a homeostatic growth factor for eosinophils, then inhibition/blockade of such a factor would be expected to lead to loss of eosinophils in both WT and GATA-6KO-mye mice. Furthermore, cytokines, chemokines, and lipid mediators can be rapidly bound and removed or metabolised in vivo by their receptors, meaning detecting an increase in production in body fluids can be difficult.

Finally, they block production of LTE4 using an inhibitor of the upstream enzyme 5-LO. This treatment reduces eosinophil survival and number in GATA-6KO-mye mice, from which the key conclusion is drawn that elevated LT4E is responsible for the increased survival and accumulation of eosinophils in GATA-6KO-mye mice. The major weakness here is that the equivalent experiment in control mice to determine if inhibition of 5-LO leads to a general reduction in survival/number of eosinophils or if this effect is restricted to the GATA-6KO-mye appears not to have been performed.

Impact and context:

Overall, this study demonstrates key alterations in lipid metabolism and lipid mediator release resulting from loss of GATA6 expression in peritoneal macrophages, and links this to the elevated survival/accumulation of eosinophils that occurs concurrently in GATA6-KO-mye mice. The role of endogenous LTE4 in regulation of eosinophil survival and/or migration into tissues is exciting and opens up a new avenue of research for understanding the importance of this pathway in regulation of eosinophils across tissues and during disease. Furthermore, unlike in the mouse, GATA6-expressing macrophages represent only a minor proportion of macrophages in the human peritoneal cavity, while the dominant GATA6-negative population is more equivalent to the GATA6-KO-mye cells studied here (PMID: 38102487). Hence, the data presented in the current manuscript could have important implications for how eosinophil numbers and lipid metabolism may be regulated by these cells in people.

Reviewer #2 (Public review):

Summary:

This manuscript examines how GATA6-dependent programming of resident peritoneal macrophages regulates their lipidome and, in turn, eosinophil homeostasis, combining lipid imaging, mass spectrometry, transcriptional analysis and in vivo pharmacology. BODIPY/CARS microscopy with targeted lipidomics convincingly shows substantial lipid changes following myeloid GATA6 deficiency, particularly in sphingolipids, with Smpd1 and Gba2 manipulations providing mechanistic support.

Strengths:

The authors also connect these changes to eosinophil biology, confirming increased peritoneal eosinophils in Gata6-deficient mice with reduced apoptosis (via two methods) rather than increased production. Testing of alternative explanations (chemokines, IL-5, prostaglandins, 12/15-LOX products) strengthens the argument by narrowing candidate mechanisms. The identification of increased LTE4 is notable as it correlates with eosinophil abundance, and zileuton reduces LTE4, eosinophil numbers, and increases apoptosis. This supports a role for 5-LOX/cysteinyl-leukotriene signalling.

Weaknesses:

The principal weakness is specificity: zileuton affects the broader leukotriene pathway, not LTE4 alone, so correlation with LTE4 doesn't establish causality. This matters more given the LTE4 receptor remains unidentified (to the best of my knowledge). Similarly, the proposed transcellular biosynthesis mechanism (ImmGen data suggesting complementary enzyme expression across cell types converting LTC4 to LTE4) is inferential; direct evidence of cellular source and transfer is lacking.

Design limitations include reliance on pooled animals in some lipidomic measurements, small replicate numbers, and a stronger eosinophil phenotype in females that shifts subsequent analysis toward females. Indeed, this sex dependence deserves more discussion given it limits generalisability.

Overall, this is a technically strong, conceptually interesting study. The core conclusions, that GATA6-dependent regulation of the macrophage lipidome and a role for cystl Lts in eosinophil survival, are well supported. The more specific claim that LTE4 is the causal factor via a defined transcellular pathway is plausible but not yet firmly established. Experimental strengthening or moderated claims would improve the study.

Reviewer #3 (Public review):

Summary:

The authors sought to define how GATA6-dependent programming of resident peritoneal macrophages regulates lipid metabolism and, in turn, eosinophil survival. By integrating a myeloid-restricted GATA6-deficiency model with cellular phenotyping, lipidomic analyses, and measurements of lipid mediators, the study attempts to connect macrophage transcriptional identity to sphingolipid and cysteinyl leukotriene pathways that may shape eosinophil persistence. The work also appears intended to provide a mechanistic bridge between prior observations from this group and others regarding GATA6-positive macrophages, lipid metabolism, and eosinophil homeostasis.

Strengths:

(1) The study addresses an important and understudied question: how tissue-resident macrophage identity controls the local lipid environment and thereby influences eosinophil survival.

(2) The use of a genetically defined GATA6-deficiency model provides a biologically relevant framework for testing the contribution of macrophage programming.

(3) The lipidomic data broaden the analysis beyond a single mediator and identify coordinated changes in sphingolipids and glycerophospholipids that may generate useful hypotheses for the field.

(4) The finding that GATA6 deficiency promotes eosinophil survival is clear, potentially important, and consistent with prior work cited by the authors.

(5) The study is performed by a knowledgeable team and brings together macrophage biology, eosinophil biology, and lipid metabolism in a way that is likely to interest several research communities.

Weaknesses:

(1) The central mechanistic chain-GATA6 deficiency leading to altered sphingolipid abundance, altered LTE4 production, and consequently increased eosinophil survival-is not fully demonstrated. The data support associations among these features, but the causal order remains uncertain.

(2) The cited literature linking sphingolipid and cysteinyl leukotriene biosynthesis does not substitute for direct testing in this model. Perturbation or rescue experiments targeting sphingolipid synthesis and cysteinyl leukotriene production would be needed to establish necessity and directionality.

(3) The broader lipidomic changes complicate the emphasis on sphingolipids. Because glycerophospholipids are also increased, the phenotype may reflect more extensive membrane-lipid remodeling, altered phospholipase activity, changes in the Lands cycle, or shifts in free fatty-acid availability.

(4) The manuscript would benefit from a clearer distinction between observations made directly in GATA6-deficient peritoneal macrophages and mechanistic inferences extrapolated from prior studies.

(5) The physiological and pathological relevance is not yet sufficiently established. It remains unclear whether enhanced eosinophil survival translates into altered eosinophil accumulation, activation, or tissue injury during inflammatory disease in the peritoneal cavity or lung.

Reviewer #1 (Public review):

Summary:

This paper describes an interesting phenotype of C. elegans lite-1 mutants. Previous work showed that lite-1 mutants lose a violet / blue light avoidance response. The authors show here that lite-1 mutants also show a defect in negative diacetyl chemotaxis. While wild-type worms avoid diacetyl at high concentrations, lite-1 mutants are instead *attracted* to it. The authors go on to perform Ca2+ imaging in sensory neurons and find that ADL and ASK neurons show altered Ca2+ responses to diacetyl in lite-1 mutants, suggesting LITE-1 is required for these responses. As unc-13 mutants with defective synaptic transmission show similar diacetyl Ca2+ responses as wild-type, this suggests these neurons respond cell autonomously to diacetyl. Indeed, expression of LITE-1 in ADL from a specific promoter shows phenotypic rescue. The authors then use a strain that expresses LITE-1 in the body wall muscles and show this expression is sufficient to engender them with sensitivity to diacetyl, as measured through altered swimming, hypercontractility, and egg laying. The authors interpret this result as LITE-1 may act as a diacetyl receptor. The authors test whether a structurally similar molecule, 2,3 pentanedione shows similar effects, and they find it does. Alpha-fold modeling and molecular docking analysis show where diacetyl might bind to the LITE-1 protein. They then test whether lite-1 mutants show chemotaxis defects to other molecules as seen with diacetyl.

Strengths:

Overall, the study follows up on an interesting and useful result. The experiments as presented are generally well-conceived and performed. The authors use a variety of behavior and imaging approaches to test how LITE-1 mediates diacetyl avoidance. The author revisions addressed the concerns I raised previously.

Weaknesses:

In response to the first submission, Reviewer 3 raised the possibility that light facilitates the production of diacetyl which then activates LITE-1. The authors helpfully revised the manuscript to incorporate this mechanisms. However, is it possible that diacetyl and 2,3-pentanedione are instead (or also) acting as photosensitizers, generating an(other) activator of LITE-1? Diacetyl has been previously shown to have chemical reactivity which is enhanced by light (citations below). I realize that the experiments have ruled out a role for acute light exposure in causing phenotypes in some of the experiments, but it is formally possible that prior light exposure may have caused diacetyl to generate peroxides or other photo-products that have the observed biological effect which is then lost in the lite-1 mutant. That is, what if the relevant molecule is already present in the diacetyl bottle / stock solution? At that point, further light exposure may not matter. This possibility was not really addressed in the manuscript.

-Huang CY, Li J, Liu W, Li CJ. Diacetyl as a "traceless" visible light photosensitizer in metal-free cross-dehydrogenative coupling reactions. Chem Sci. 2019 Apr 8;10(19):5018-5024. doi: 10.1039/c8sc05631e. PMID: 31183051; PMCID: PMC6530541.<br /> -Pengcheng Lian, Ruyi Li, Xiao Wan, Zixin Xiang, Hang Liu, Zhiyu Cao, Xiaobing Wan Acetylation of alcohols and amines under visible light irradiation: diacetyl as an acylation reagent and photosensitizer. Organic Chemistry Frontiers 2022, 9 (2), 311-319.<br /> -Rowell, Keiran N & Kable, Scott & Jordan, Meredith J. T. (2022). An assessment of the tropospherically accessible photo-initiated ground state chemistry of organic carbonyls. Atmospheric Chemistry and Physics. 22. 929-949. 10.5194/acp-22-929-2022.

Reviewer #2 (Public review):

Summary:

Koh and colleagues investigate the broader sensory role of LITE-1, a gustatory receptor previously linked to UV light detection in C. elegans. Their study explores whether LITE-1 also mediates avoidance of specific chemical stimuli-namely, high concentrations of diacetyl and 2,3-pentanedione. They show that LITE-1 is required in the ADL and ASK neurons for calcium responses to diacetyl, and that its expression in body-wall muscles is sufficient to trigger hypercontraction upon odorant exposure. Molecular docking suggests both odorants may directly bind to LITE-1 with micromolar affinity. These findings suggest LITE-1 may act as a multimodal receptor for both light and chemical stimuli.

Strengths:<br /> • Methodological Precision: The study is technically strong, with well-executed calcium imaging and quantitative behavioral assays that clearly show neural and muscular responses to chemical stimuli.<br /> • Novelty and Scope: The work presents a compelling case for LITE-1 functioning as a multimodal sensor, which is an intriguing expansion of its known role.<br /> • Potential Impact: If validated, the findings could significantly advance the understanding of sensory integration in C. elegans, and the tools developed may be broadly useful to the research community.<br /> • Relevance to the Field: The study adds to evidence that C. elegans uses non-canonical sensory pathways and may inspire further exploration of multimodal receptor functions in other systems.

Weaknesses:<br /> • Lack of Rescue Experiments: The absence of rescue experiments makes it difficult to definitively link the observed phenotypes to loss of lite-1.<br /> • Single Loss-of-Function Approach: The reliance on a single genetic mutant limits interpretability. Additional strategies such as RNAi (e.g., neuron-specific knockdown) would provide stronger evidence.<br /> • Unclear Neuronal Contribution: While calcium responses in ADL and ASK are reduced, it's unclear which neuron(s) are necessary for behavioral avoidance. Cell-specific rescue or knockdown experiments are needed.<br /> • Unvalidated Docking Data: The molecular docking predictions lack experimental validation. Site-directed mutagenesis would be needed to support claims of direct interaction.<br /> • Limited Odorant Specificity Testing: Docking analysis does not include non-binding odorants, making it difficult to assess binding specificity.<br /> • Incomplete Quantification: Some calcium imaging results (e.g., in AWA neurons of unc-13 mutants) lack statistical comparisons, which limits their interpretive value.

Comments on revisions:

I thank the authors for their thorough revision. The manuscript is substantially improved, and most of the concerns raised in my original review have been addressed.

The strongest improvement is the addition of new genetic evidence supporting a role for LITE-1 in high-concentration diacetyl avoidance. The use of multiple independent lite-1 alleles strengthens the conclusion that the phenotype is specifically due to loss of lite-1 function, and the ADL-specific rescue experiment is an important addition. While the rescue is not complete, it is convincing and supports the idea that LITE-1 activity in ADL contributes to the avoidance response.

The neuronal analysis is also stronger. The new statistical analysis across the sensory neurons addresses my previous concerns regarding quantification, and the revised interpretation of the calcium imaging data is more balanced. The revised title of this section is also more consistent with the data and appropriately focuses on ADL and ASK rather than ASH.

I also appreciate the additional controls addressing possible effects of ambient light. The light versus dark experiments make it unlikely that the observed behavioral phenotypes are secondary to unintended activation of LITE-1 by environmental illumination.

The expanded odorant analysis and inclusion of docking predictions for additional compounds are useful additions. Together with the ectopic expression experiments in body-wall muscles, these data strengthen the argument that LITE-1 can respond to diacetyl and related compounds.

My main remaining concern is the same one raised in the initial review: the docking results remain largely computational predictions and have not been tested experimentally through binding-site mutagenesis or other functional validation. As a result, the manuscript still does not demonstrate direct ligand binding to LITE-1. However, I think the authors have strengthened the indirect evidence considerably, and the conclusions are now generally written in an appropriately cautious manner. I would encourage the authors to continue framing the docking results as supportive of a direct interaction rather than definitive proof of one.

Overall, I believe the manuscript has been significantly strengthened by the revision. The remaining limitation is largely mechanistic and does not, in my opinion, undermine the central conclusions of the study.

Reviewer #3 (Public review):

In this work, Brown and colleagues report that the photosensor protein LITE-1 of the nematode C. elegans may also a chemosensor that can be activated by high concentrations of the compound diacetly. LITE-1 was described as a putative ion channel of the gustatory receptor family, which is mainly constituted by insect odorant receptors. These form tetrameric ion channels that can be activated by odorant. Specificity is achieved by forming heteromeric channels from three copies of the odorant receptor co-receptor (ORCO) and another subunit that resembles ORCO in the pore-forming C-terminus, but brings in a binding site for the respective odorant. LITE-1 has a very similar structure, according to Alphafold3 predictions, and also carries a binding pocket. In LITE-1, this was proposed to be occupied by a light-absorbing molecule that activates the channel when a photon is absorbed. Alternatively, compounds generated by absorption of high-energy photons may be formed in vivo and bound by the LITE-1 binding pocket. Koh et al. now demonstrate that another, non-light activated compound, diacetyl, at high concentrations, can activate cells expressing LITE-1. Such (chemosensory) cells are also responsible for the avoidance of high concentrations of diacetyl. For this aspect, the protein seems to act in neurons, which are not necessarily the same cells in which LITE-1 is evoking the photophobic response. LITE-1 activation in excitable cells, i.e muscles, causes strong body contraction and paralysis, and the authors show that this is also the case when diacetyl is present. This action is surprisingly rapid, i.e. within 10 seconds after adding diacetyl, raising the question of how the compound can enter the body so quickly. The authors further present molecular docking studies showing that diacetyl could occupy the binding pocket of LITE-1. Last, they show that another compound chemically resembling diacetyl, i.e. 2,3-pentanedione, can also induce avoidance in a LITE-1 dependent manner, though not as potently.

The data are intriguing and the demonstration of LITE-1 being a diacetyl chemosensor is interesting. Following the first submission and review, the authors addressed most of the questions that this reviewer had and improved the paper significantly. It will add to the further understanding of the still-mysterious multimodal sensory ion channel LITE-1.

The authors identified mutants lacking diacetyl responses. In their chemotaxis assay (Fig. 1A, B), they show that lite-1 mutants do not avoid high concentrations of diacetyl. However, the animals actually show attraction, as the chemotaxis index was positive. If the lite-1 animals were insensitive, they should be indifferent and the chemotaxis index should be close to zero. The authors now showed that other neurons contribute to the avoidance response that are not themselves bona fide chemosensory neurons, as the avoidance behavior remained in a tax-4 mutant, that is lacking most sensory neuron responses. The authors further showed that diacetyl responses of ADL can be rescued by expressing LITE-1 specifically in this neuron in a lite-1 mutant background, thus demonstrating that LITE-1 acts cell-autonomously in ADL to affect avoidance behavior.

The effect of diacetyl on muscle cells (Fig. 3C) is pretty rapid. As shown in the initial submission, already during 1 minute after application the animals are almost maximally contracted. The authors now provide a time course with data points every 10 seconds. This shows that contraction is maximal already after 10 seconds of exposure (provided the zero time point is the one where diacetyl is added). This is remarkable, as the compound would have to either pass the worm cuticle, or enter through the gut and diffuse through the body to reach the muscle cells. It would be of interest to compare this to time courses of other pharmacological agents that need to enter the worm's body for their action. As a comparison, often sodium azide is used to paralyze worms for imaging purposes. This molecule is even smaller than diacetyl, but azide action typically requires more time for maximal effects. Could there be active transport mechanisms involved? Maybe diacetyl can pass through some transporters for related molecules into / through intestinal cells quickly, to then reach the body fluid and muscle cells.

One alternative explanation could be that other mechanisms may be at play. E.g. diacetyl may be immediately sensed by ciliated chemosensory neurons that might release a signaling molecule that leads to activation of LITE-1 in muscles, or that sensitizes it somehow, responding to light used for filming animals. The authors addressed these concerns by repeating their assay in a lite-1 mutant background. The authors had tested unc-13 mutants to rule out indirect effects on the neurons recorded. Likewise, eliminating neuropeptide signaling via unc-31 mutants would have been informative, as neuropeptide signaling plays a role in LITE-1-mediated light avoidance behavior (PMID 40238937, 39489735).

Molecular docking studies are now described in more detail. The authors also provide a structural model of the diacetyl-docked LITE-1. In this model, only one of the four putative binding sites carries diacetyl. Maybe the authors could test how structure is affected if all four sites contain diacetyl? Mutations of LITE-1 that lack aminoacids shown to be contacted by diacetyl have been described (C300, R222). It would have been insightful to test if such mutants are still activated by diacetyl. This would also verify that there is not an unknown breakdown product of diacetyl that could affect LITE-1 function through oxidative pathways, as diacetyl has been implicated as a photosensitizer in the past.

Reviewer #1 (Public review):

Summary:

This paper examines whether humans use protracted temporal integration in a noise-free, deferred-response contrast discrimination task, using a covert evidence-duration manipulation combined with EEG (SSVEP, CPP, Mu/Beta). The key finding is that evidence for protracted sampling is behaviorally and neurally supported, but even joint CPP + behaviour fitting cannot fully discriminate a standard integration (DDM) model from a novel "extremum-flagging" non-integration model. The paper is transparent about this outcome.

Strengths:

This is a well-conducted and well-written study that makes a genuine contribution to the perceptual decision-making literature by introducing a clean experimental design for probing temporal integration without participants adapting their strategy and demonstrating for the first time that a non-integration model (extremum-flagging) can replicate CPP waveform dynamics that have long been considered hallmarks of evidence accumulation. The transparent treatment of equivocal modelling outcomes is commendable.

Weaknesses:

My main concerns relate to statistical power, the under-specification of the and the extremum-flagging mechanism. Addressing these would greatly strengthen the paper.

(1) The sample of 16 participants (15, after the exclusion of one participant) is described as "close to similar EEG studies" with no formal power analysis. Given that the paper's core claim rests on subtle quantitative differences between two model classes - differences that are, by the authors' own admission, not sufficient to declare a winner - even a modest increase in sample size might yield a more decisive outcome. At minimum, the authors should report a sensitivity analysis or post-hoc power calculation to indicate what effect sizes the current N could reliably detect, particularly for the rmANOVA comparisons and the neural constraint fitting.

(2) The Extremum-flagging model is the paper's most novel contribution, yet its physiological basis is underspecified. The model posits that each decision-terminating bound-crossing triggers a stereotyped, half-sine-shaped centroparietal signal, but no neural circuit or computational mechanism is proposed for how the brain could detect the first bound-crossing event in a non-accumulating evidence stream or generate a temporally precise, fixed-amplitude signal in response. Possible connections to P3b theories of context updating and response facilitation are acknowledged, but these are vague functional descriptions rather than mechanistic accounts. I think the discussion should engage more directly with potential neural substrates that could generate this flagging signal, and whether these are consistent with the known generators of the CPP/P3b. Without this, the extremum-flagging model risks being viewed as a mathematical convenience rather than a biologically plausible alternative.

(3) The Integration model at the preferred neural weighting estimates a high-to-low contrast drift rate ratio of 8.7, whereas the empirical Mu/Beta lateralization slopes suggest a ratio of approximately 3.5. The authors attribute this discrepancy to the nonlinear contrast response function of early visual cortex and the salience of the high-contrast evidence onset, but these explanations are speculative. These outcomes are arguably the most quantitatively damaging result for the integration model, so they deserves more than a brief discussion. I would recommend that the authors (a) estimate what range of contrast response nonlinearities would be required to close this gap, (b) test whether an alternative drift rate parameterization (e.g., scaling drift rates directly by SSVEP amplitude rather than contrast) reduces the discrepancy, or (c) be more explicit about treating this as a point against the Integration account.

(4) The sensitivity analysis over neural constraint weightings (w = 0.1 to 1000) is thoughtful, but the paper ultimately acknowledges that the preferred weighting is w=10, chosen because it achieves "a good fit to CPP dynamics without substantively sacrificing behavioral fit" - a qualitative criterion. No principled statistical framework is used to select the optimal weighting or to compare models at a given weighting. A Bayesian model comparison could provide a more formal framework for combining behavioral and neural fit components, and would allow a clearer statement about the relative posterior probability of each model.

Comments on revisions:

In reply to my comments, the authors have added a post-hoc power analysis that provides adequate justification for the sample size, a more nuanced discussion of neural mechanisms that could support an extremum flagging model, and several supplementary analyses that show the generality of findings across parameter levels. These are welcome additions that strengthen confidence in key findings while acknowledging nuances involved in quantitative analyses and model fitting.

Reviewer #2 (Public review):

The manuscript by Hajimohammadi, Mohr, O'Connell and Kelly is intended to demonstrate that participants integrate evidence over time to make a decision, even in a noise-free, static decision context. This is validated by the observation that 1) participant accuracy improves with increased exposure to the stimulus; and 2) there is a correlation between participant accuracy and a neural index of evidence accumulation, as measured by centro-parietal positivity (CPP).

Strengths:

(1) Joint modelling of accuracy and CPP dynamics is a significant achievement, as behaviour alone often cannot distinguish between competing theories of decision-making. In the case of protracted sampling in particular, the absence of reaction times (RT) due to the delayed nature of the response makes this method highly appealing.

(2) The experimental manipulations and the method used to extract the different neural indices are well chosen, enabling the mapping of putative cognitive processes such as evidence accumulation and motor preparation onto the recorded EEG with clarity.

(3) The in-depth discussion of the results clearly articulates those reported by the authors and in previous works.

Weaknesses:

(1) Regarding the first point I raised in the first version of the manuscript, I'm satisfied with the author's response.

(2) For the second point, however, I'm still unconvinced, noting that my understanding of the fitting routine is relatively limited. To me, the comparison of the behavioral and the joint-modelling is relatively weak in terms of evidence. Despite the revision, it is still unclear whether the behavioral models are well conditioned given the very weak constraint exerted by (aggregated, see below) binary decision data only. To my previous comment, the authors reply, "We can instead address identifiability somewhat indirectly through parameter estimate consistency across the 10 fits we conducted with different instantiations of noise". I'm worried that the different instantiations of noise (limited to 10), generated for the parameter search, have any impact at all. A better quantification of the uncertainty in parameter estimates, as well as the AIC, is needed, for example through a cross-validation scheme, or bootstrapping/jack-knifing at the level of the participants. Without this, I remain unconvinced that the behavioral models are suited for the comparison with the joint-neural models:

(3) Relatedly, regarding the response of the authors to my minor comment 4, after the revision of the manuscript, it is clearer that the behavioral models were fitted only on 6 data points (accuracies averaged over participants for each condition) for models with up to 3 parameters. I understand that the authors average behavior to make a comparison with the joint neural model, whose neural signals are noisy at the participant level. However, if the neural model, or the chosen linking function, needs this aggregation to outperform the behavioral model, that questions a bit whether the joint model is really useful in practice.

While I see these two last points as serious for the comparison between behavioural and joint-neural models, this does not change the main addition of the paper: that is, the joint model and the evidence for protracted sampling.

Reviewer #3 (Public review):

Summary:

The authors aim to compare proposal models of perceptual decision making using a joint modeling approach, where they fit models to both behavioral outcomes as well as CPP. Most notably, they compare a standard evidence accumulation model with models that track the evidence without integrating it over time (extrema detection). The authors report that the joint CPP-behavioral data do not discriminate between two of their proposals.

Strengths:

This is an interesting finding that reinforces the idea that what we believe to see based on aggregation over trials may not be what happens on every single trial. The models are creative and the simulations are convincing, relating the models to multiple neural markers of decision formation. These include the CPP but also mu/beta power spectra.

Initial weaknesses:

Contrary to the original draft, the current version now clarifies the goals of the study as well as the role of internal vs external noise.

The authors clarify their stance on the optimality of extrema detection in the Public Review, where they make some good points. Specifically, they argue that models that have studied optimal decision making in the past have considered a quite narrow definition of optimality, for example, ignoring energetic costs.

The authors clarified the fixed value of the scaling parameter (which apparently was already mentioned in the initial draft, which I had missed). My comment about the discrepancy between the bounded integration model and the EZ diffusion model can thus be ignored. However, I do think that the similarity of the bounded integration model and the EZ diffusion model could be acknowledged in the manuscript somewhere.

I still think the choice of modeling the grand average accuracy and EEG signal may distort the results. As Figure 1 reveals, there is in fact substantial variation in the change in accuracy across conditions. I can imagine that one model may be preferred over another based on the aggregate data, while the other model is preferred for some participants. On the group level, this may lead to different conclusions, at least quantitatively (e.g., in terms of G2), but potentially even qualitatively. This is especially true for the neurally-informed models because of the covariation between behavioral and neural data.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

In this study by Kitto et al., the authors set out to identify specific signaling components regulating the hypoxic response from the neurons to the periphery and which components are required for lifespan extension. Their previous work had shown that expression of a stabilized HIF-1 mutant in the nervous system extends lifespan through the serotonin receptor SER-7 and leads to the induction of fmo-2 in the intestine. In the current study, they mapped the precise neural circuits required for this response, as well as the signaling mediators. Their work reveals that neurotransmitters GABA and tyramine, and the neuropeptide NLP-17, act downstream of neuronal HIF-1 to convey a "hypoxic signal" to peripheral tissues. Through cell-type-specific expression studies, targeted knockouts, and comprehensive lifespan analysis, the authors provide robust evidence to support their conclusions. The insights gained from the study are both moving the field forward as they advance our understanding of neuro-peripheral hypoxic signaling, but they also lay the groundwork for potential therapeutic strategies aimed at the modulation of such signaling pathways.

Strengths:

(1) This study provides new evidence further delineating signaling components required for hypoxic signaling-mediated longevity, from the nervous system to the periphery. Using a rigorous approach where they express stabilized HIF-1 mutant selectively in ADF, NSM, and HSN serotonergic neurons, followed by cell-type-specific tph-1 knockouts to pinpoint ADF-dependent serotonin signaling as essential for both lifespan extension and intestinal fmo-2 induction.

This was followed by generating 11 transgenic lines that drive SER-7 expression under distinct neuron-specific promoters, to systematically tease out in which of 27 candidate neurons SER-7 functions to mediate hypoxia-induced longevity. This ultimately highlighted the RIS interneuron as the required signaling hub.

(2) As the intestine lacks direct neuronal innervation, the authors employ neuron-specific RNAi (TU3311 strain) and dense core vesicle analyses to identify that the neuropeptide NLP-17 is required to transmit the hypoxic signal from RIS to induce fmo-2 in the intestine.

(3) Overall, the paper is very well written. The experiments were carried out carefully and thoroughly, and the conclusions drawn are also well supported by the results they are showing.

Reviewer #2 (Public review):

Summary:

The authors aimed to identify the specific neurons, neurotransmitters, and neuropeptides that mediate the longevity effects of the hypoxic response in C. elegans. By genetically dissecting the pathway downstream of HIF-1, they define a neural circuit involving ADF serotonergic neurons, the SER-7 receptor in the RIS interneuron, tyraminergic signaling from RIM, and neuropeptide NLP-17, ultimately linking neuronal hypoxic sensing to pro-longevity signaling in the intestine.

Strengths:

The study employs a diverse genetic toolkit, including neuron-specific transgenes, tissue-specific knockouts and rescues, RNAi knockdowns, allowing the authors to pinpoint causality, sufficiency, and necessity with high resolution. The comprehensive mapping of cell-nonautonomous signaling adds depth to our understanding of how HIF and serotonin signaling interface with aging pathways. The conclusions are supported by consistent survival assays and fmo-2 gene expression analyses.

Reviewer #3 (Public review):

Summary:

This study found that ADF serotonergic neurons have a significant role in extending lifespan mediated by HIF-1, as well as serotonin receptor SER-7 in the GABAergic RIS interneurons. The author focuses on the sufficiency and necessity of components from the central nervous system and how they contribute to aging upon hypoxia.

Previous work from the lab has identified that the stabilization of HIF-1 in neurons is sufficient to extend lifespan through the serotonin receptor, SER-7, which subsequently activates fmo-2 in the intestine and leads to lifespan extension. Building on this, the author sought to determine which serotonergic neurons are involved and found that serotonin signaling in ADF neurons is required for lifespan extension mediated by HIF-1.

The author next tested which subset of neurons requires Ser-7 expression to rescue hypoxic response. They found that ser-7 expression in multiple neurons is sufficient to induce fmo-2, with the top candidate being the RIS neuron. Ablation of the RIS neuron did not extend lifespan, suggesting that ser-7 expression in the RIS neuron is required for lifespan extension, positioning it as a key component in the longevity signaling pathway.

The author also investigated neurotransmitters and found that GABA and tyramine are important components in this circuit. They showed that the tyramine receptor called tyra-3 is required for vhl-1-mediated longevity. Given that tyra-3 is expressed in oxygen- and carbon dioxide-sensing neurons, the author demonstrated that these sensing neurons work downstream of serotonin signaling. Lastly, the author screened neuropeptide/receptor binding pairs and identified NLP-17 as playing a role in hypoxia-mediated longevity.

Originality and Significance:

This research is significant in that it uncovers components that are sufficient and necessary for lifespan extension via the hypoxic response. It provides comprehensive data supporting longevity induced by HIF-1-mediated hypoxic response, in conjunction with fmo-2, a longevity gene, as demonstrated in previous work from the lab. Moreover, it provides a number of new transgenic worm tools for C. elegans and aging communities.

Conclusions:

This study provides insights into how hypoxic response regulates aging in a cell non-autonomous manner, outlining a potential circuit involving neurons, neurotransmitters, and neuropeptides.

Reviewer #2 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. The authors have addressed the comments raised in the previous round of review.]

Summary:

The manuscript by Wang and colleagues aims to determine whether hepatic glucose metabolism is differentially regulated by the left and right sides of the LPGi and to reveal decussation of hepatic sympathetic nerves.

The authors used tissue clearing to identify sympathetic fibers in the liver lobes, then injected PRV into the hepatic lobes. Five days post-injection, PRV-labeled neurons in the LPGi were identified. The results indicated contralateral dominance of premotor neurons and partial innervation of more than one lobe. The authors then activated each side of the LPGi, resulting in a greater increase in blood glucose levels after right-sided activation than after left-sided activation, and in changes in protein expression in the liver lobes. These data suggested lobe-specific modulation of HGP. Chemical denervation of a particular lobe did not affect glucose levels due to compensation by the other lobes. In addition, nerve bundles decussate in the hepatic portal region.

Strengths:

The manuscript is timely and relevant. It is important to understand the sympathetic regulation of the liver and the contribution of each lobe to hepatic glucose production. The authors use state-of-the-art methodology.

Weaknesses:

(1) Image clarity was improved in some cases, but not in others. For example, Figure 3I, showing c-Fos expression, is not convincing due to the image quality and lack of orientation.

(2) The methods section states that 8-week-old male mice were used in the experiments without specifying the experiments (e.g., brain injection with AAVs or PRV organ inoculation). The authors should include these details.

(3) The authors should use the exact location of pre- and postganglionic neurons, as they often refer to neurons in the sympathetic chain. Their findings should be compared with the existing literature on the location of preganglionic cells.

(4) Figure legends should be revised and matched with the text.

Reviewer #4 (Public review):

Summary of General Strengths & Weaknesses:

The studies here are highly informative for anatomical tracing and sympathetic nerve function in the liver in relation to glucose levels, but because they are conducted in a single species, it is challenging to translate them to humans or determine whether these neural circuits are evolutionarily conserved. Dual-labeling anatomical studies are elegant, and the addition of chemogenetic and optogenetic studies provides mechanistically informative. Denervation studies lack proper controls, and sensory innervation in the liver is overlooked.

Specific Weaknesses - Major:

(1) The species name should be included in the title.

(2) Tyrosine hydroxylase was used to mark sympathetic fibers in the liver, but this marker also labels a portion of sensory fibers that need to be ruled out in whole-mount imaging data.

(3) Chemogenetic and optogenetic data demonstrating hyperglycemia should be described in the context of prior work demonstrating liver nerve involvement in these processes. The Discussion currently mentions this only briefly, but comparing methods and observations would be helpful.

(4) Sympathetic denervation with 6-OHDA can drive compensatory increases in tissue sensory innervation, and this should be measured in the liver denervation studies to implicate potential crosstalk, especially given the increase in LPGi cFOS that may be due to afferent nerve activity. Compensatory sympathetic drive may not be the only culprit, though that is clearly assumed. The sensory or parasympathetic/vagal innervation of the liver is altogether ignored in this paper and could be better described in general.

Comments on the revised version.

Across all reviewer comments, the revised resubmission has adequately addressed all concerns.

Reviewer #1 (Public review):

Summary:

The presented investigation aims to expand the sleep definition and its relationship with blood meal and/or circadian clock in the mosquito, Aedes aegypti. The authors exhausted the established sleep analytical paradigm and three behaviour toolkits: LAM10, EthoVision, and DART. They also investigated the potential underlying molecular mechanism by using dsRNA injection (LkR) and KO mosquito (Cyc-/-).

Strengths:

The authors presented a very solid dataset showing posture changes and increase in the arousal threshold of mosquito after 10 minutes of immobility. This is major clarification and extension to our understanding in insect sleep beyond Drosophila. Inclusion of analytical parameters such as bout length, waking activity and pDoze/Wake provide critical reminder for other investigators of the steps needed for defining sleep in a new species. The investigation, with its technical span in behaviour assays, therefore, establish a good standard for mosquito sleep analysis to the same quality seen in the landmark studies (Shaw et al 2000 and Hendricks et al 2000) for Drosophila sleep. The pioneering data showing clear effect of blood meal and LkR reduction on locomotion and sleep provides an entry point for further investigations. The author has addressed previous concern on coincidence of sleep increase and locomotion reduction by using their two high-res. video tracking velocity or pDoze/Wake, showing that the "sleepy" mosquitos remain capable to reach high speed locomotion albeit less frequently. The authors also discuss the possibility of ATP and alternative explanation regarding sugar content in diet.

Reviewer #2 (Public review):

Summary:

Zhang et al. investigate how blood feeding and dietary protein influence sleep in the mosquito Aedes aegypti. The authors first establish a behavioural definition of sleep using postural analysis and arousal threshold measurements, then demonstrate that both blood meals and a bovine serum albumin (BSA)-based protein diet increase sleep for several days. They further show that RNAi-mediated knockdown of the leucokinin receptor (Lkr) enhances sleep, implicating neuropeptide signalling in the regulation of postprandial sleep.

Strengths:

The central question is well-motivated, and the experimental approach is systematic. The use of multiple independent methods to characterise sleep - postural analysis, infrared activity monitoring, videography, and arousal threshold - provides converging evidence. The 10-minute immobility criterion is grounded in the arousal threshold data, bouts exceeding 10 minutes corresponding to the first bin at which a significant effect emerges. The demonstration that the sleep increase is already detectable before oviposition establishes that the phenotype begins with feeding rather than with the completion of the reproductive cycle. The BSA feeding experiment is a particularly effective demonstration that dietary protein, rather than other blood components, is a key regulator of the sleep increase. The conservation of leucokinin signalling in sleep regulation between Drosophila and Ae. aegypti is a noteworthy finding that adds comparative depth. The "opportunistic versus determined" host-seeking distinction is appropriately framed as a hypothesis for future testing rather than as a conclusion drawn from the present data, and the limits of the design with respect to reproductive physiology are stated explicitly.

Weaknesses:

(1) Confound of reproduction and sleep. Blood and BSA both support egg development, so neither condition isolates nutrient sensing from reproductive physiology. The relative contributions of diet, egg development and post-reproductive recovery remain undetermined.

(2) Sleep versus reduced locomotion. The pDoze and pWake measures are defined here as proportions of time above or below a velocity threshold, rather than as the per-minute transition probabilities of the established definition (Wiggin et al. 2020, PNAS). So defined, they are equivalent to percent sleep and percent wake and cannot distinguish a sleep-like state from the mechanical consequences of engorgement.

(3) Data availability. Raw data are stated to be available on request rather than deposited in a public repository, which makes independent reanalysis less straightforward than it need be.

Reviewer #1 (Public review):

Summary:

Maigler et al. set out to test the hypothesis that individual differences in taste preferences are (in part) due to individual differences in central taste processing. They first tested rats' preferences for a variety of taste stimuli on multiple days. They then recorded responses of neurons in taste cortex to the same tastes on two consecutive days.

Strengths:

The authors collected high-resolution behavioral data from the same animals across multiple days, allowing for a detailed characterization of individual variation in taste preferences. They then performed recordings from the same set of animals in response to the same stimuli, allowing them to draw parallels between behavioral and neural responses.

Weaknesses:

(1) The authors collect extensive behavioral data and show that preference vary between animals and days, but little insight is provided into what underlies these changes and to what extent they reflect "preference". Two animals drank equal amounts of sucrose and quinine on day one of preference testing, suggesting that behavior does not reflect preference but (lack of) habituation to/proficiency with the testing environment.

(2) Recordings were performed only after multiple days of preference testing, and preferences were not tested in between/following recording sessions. This design precludes a direct comparison between neural and behavioral responses.

(3) Similarly, correlations between neural responses and behavioral measures are not analyzed/reported on an animal-by-animal basis.

Reviewer #2 (Public review):

Summary:

The study from Maigler et al investigates how between- and within-animal differences in taste preference relate to differences in neural responsiveness. The experiments rely on an elegant combination of behavioral assays to measure preference (e.g., repeated brief access testing, BAT) and electrophysiological recordings to monitor the activity of ensembles of neurons in the gustatory cortex (GC) of rats.

BAT with distinct batteries of tastants revealed pronounced variability in preference (measured as licking bout size) across individuals. This variability across individuals persisted after repeated testing. Repeated BAT also revealed that each individual rat's preference for different tastants changed across time.

Electrophysiological responses of GC neurons to batteries of tastants showed that firing in the "late epoch" of taste processing (i.e., 500ms post taste delivery) correlated more strongly with the individualized rat's BAT preference rather than with a canonical preference ranking. Importantly, this correlation was stronger for the last BAT session compared to the first. Finally, the authors show that the correlation disappeared in a second, consecutive recording session, indicating that exposure to tastants reconfigure preferences.

Strengths:

(1) The experimental design allows for an unprecedented look at the relationship between individual variability in taste preferences and neural processing.

(2) The study demonstrates that taste preference variability is not mere experimental noise but reflects the dynamic nature of taste. A key strength is the clear evidence that behavioral variability is reflected in neural activity patterns, establishing a strong correlation between brain and behavior.

(3) The evidence that simple exposure to familiar tastes can reconfigure preferences and taste representations is interesting.

Weaknesses:

The authors appropriately addressed the weaknesses in the revision process.

Reviewer #3 (Public review):

Summary:

Maigler & Lin et al present a convincing set of behavioral and electrophysiological experiments and analyses exploring how individual differences in taste preference map onto neural responses in the gustatory cortex (GC). They go on to examine how both preferences and neural responses shift following intervening taste experience. Their experiments are strengthened by examining tastes of distinct identities and palatability (sweet, sour, salty, bitter) and correspond each animal's individual preference to the palatability-related late phase of the neural response.

Strengths:

(1) They demonstrate a relationship between the behavioral expression of taste preference and palatability-related GC neural responses. The direct correlation of expression of taste preference with GC neural responses indicates that taste preference behavior may be less noisy than previously thought, reflecting actual neural activity.

(2) They address the stability of individual taste preference by comparing within and between session expression. This finding indicates that individual preference on any given trial or test session can differ from canonical palatability.

(3) The animal's preferences for various tastes are reflected in the neurophysiological recordings, despite that behavior and physiology sessions are separated by several weeks, with an intervening surgery, across multiple delivery methods (active licking vs passive delivery), and across homeostatic states (thirsty vs sated).

(4) They provide evidence that representational drift in palatability coding may arise from sensory experience rather than from the passive passage of time.<br /> The findings are novel and impactful, and the results are relatively complete.

Weaknesses:

(1) The authors state that "no differences in effects were observed between taste batteries" (Methods), but it is not clear which analyses were performed to determine this, especially considering that many of the analyses are within-animal. Without more clarity, it is difficult to evaluate whether the interaction of different tastes within the sets of stimuli bias the main conclusions.

(2) It is not clear how the analyses in Figure 3 emerge from the behavioral patterns across Figures 2A2 and 2B2. Along these lines, citric acid responses for R1 and R2 and saccharine responses for R7 and R8 are not shown in Figures 2A2 and 2B2, thus, we cannot determine if they change from the first to final BAT sessions. Salt, even at low concentrations, may not be palatable when rats are in a water-restricted state. It would be interesting to see Figure 3's analysis exclusively for sweet or for bitter tastes.

(3) A potential reason why a single taste experience session causes taste palatability responses in GC neurons to revert to a reflection of canonical palatability ranks, as is seemingly shown in Figure 6, is not discussed.

Reviewer #1 (Public review):

Summary:

The authors describe a clever genetic system based on rapamycin-inducible expression of a beta-galactose reporter. The authors compare this spectrophotometer-based readout to the parasite reduction rate version 2 (PRRv2) recently described by some of the same authors and based on incorporation of [3H]-hypoxanthine. The results are generally comparable, with some differences for slower-acting compounds. The authors report that this format is better suited for higher-throughput studies and requires less time to quantify time-dependent onset of parasiticidal action compared with the PRRv2.

This is a very well-executed and well-described body of work with a comprehensive set of analyses. The revised manuscript provided more context in comparing this method to other methods in the field, with a clearer explanation that the current MULT-i2 assay focuses on assessing viability, whereas other methods are more focused on assessing growth inhibition. The new assay is also faster than the prior PRR methodology. The current design will be useful to stay multi-drug combinations. The authors state that this parasite line will be available from BEI with an accompanying MTA. Other earlier comments and concerns were very well addressed by the authors.

Reviewer #2 (Public review):

Summary

Antimalarial combination therapy is the standard of care for malaria, a disease that impacts hundreds of millions of people annually. Combination therapy is crucial for effectively treating the disease and delaying the emergence of drug resistance. Despite the importance of choosing appropriate partner antimalarials for combination therapy, drug interactions are typically evaluated late in the course of drug development. Standard in vitro assays that determine synergistic, antagonistic or additive interactions between drug combinations rely on measuring inhibition of parasite proliferation, which is inadequate for translation to pharmacodynamic models for parasite clearance in the patient. Direct measurement of parasite viability under drug treatment has previously relied on methods that are labor and resource intensive, limiting applications to single compounds and single concentrations. Here, Hellingman et al make use of an inducible chemiluminescence reporter to measure cell viability and apply this novel approach to quantify drug interactions. The methodology is a significant improvement upon prior methods, requiring significantly fewer resources, half the time, and substantially less handling than the standard PRRv2 assay, whilst maintaining high resolution and sensitivity.

They assess the limit of detection for the improved method and cross-reference their results for single drugs at a single concentration with the currently standard PRRv2 assay. The authors next established analytical methods to characterize the impact of drug combinations on parasite viability using the GDPI pharmacodynamic model and compare their MULT-i2 assay to the prior cPRR approach. Their refined workflow allowed them to comprehensively evaluate the known synergistic combination between atovaquone and proguanil with greater resolution than the comparable cPRR assay and identified additional interaction parameters between the fast-acting antimalarials piperaquine and pyrimethamine. Overall, the authors demonstrate that their inducible lacZ system provides significant advantages compared with prior approaches to determine parasite viability. They convincingly demonstrate the strengths of their approach by characterizing two antimalarial combinations at much greater resolution than previously possible with prior methods. The system and methods established here will be particularly useful for evaluating novel antimalarial combinations with chemical series in preclinical evaluation and to optimize future antimalarial therapies.

Strengths:

The streamlined approach relies on induction of the lacZ enzyme only after drug washout. As opposed to when stably expressed, this allows the authors to estimate parasite viability without undergoing serial dilutions to estimate viable parasite titers. This innovation vastly reduced resource and time intensity, enabling greater throughput for parasite viability estimation. The established methodology and analysis pipeline enabled the testing of 49 drug combinations for parasite viability in the MULT-i2 assay compared to only 9 in the conventional cPRR assay. This provided improved resolution in the ability to estimate drug combination parameters in a pharmacodynamic model. The ability to comprehensively characterize combination pharmacodynamic properties in vitro will have important implications for downstream modelling of in vivo combinations, and for optimizing future antimalarial combination therapies.

The authors made good use of modelling and AICc for parametric estimation and model evaluation to demonstrate the advantages of the richer dataset afforded by the MULT-i2 assay.

Weaknesses:

The authors correctly identified a range of confounding effects that lead to artefacts in their assay results when compared to the cPRR assay. For instance, the authors observed reduced signal at high parasite density during recovery due to overgrowth and likely enzyme degradation, and suggested residual signal may remain from non-proliferating sexual stage parasites surviving drug treatment that would not be detected in the cPRR assay.<br /> Measurement of parasite viability in the MULT-i2 assay was achieved by extrapolating chemoluminescence signal to that of a serial dilution of parasites made at the initiation of drug treatment. How did the authors account for differing levels of enzyme expression at early (eg ring) vs late stage parasites (trophozoite or schizonts)? Were cultures synchronized prior to initiation of assays? Could differences in life-cycle progression following drug treatment be an additional confounding factor that may account for differences with the PRRv2 assay?

The addition of an inducible element is an improvement of their earlier lacZ/β-galSENSOR (PMID: 41575867), however, the authors fail to explain why this is an improvement and how this adds additional merit over the initial system. While the authors compare their new assay to the PRRv2, they fail to compare it to their own non-inducible lacZ/β-galSENSOR system. Their non-inducible system already showed superiority to the cPRR assays and it would be good to show how they compare and what the advantages of the new system are over the old. Eg how is the signal to noise improved? How does the sensitivity compare? How quickly does the can the signal be detected after induction? They show signal after 48h but it would be very useful to the community to look at earlier timepoints as well and compare it to the uninduced line and a line that has been induced 48h earlier to match the expression patterns throughout the lifecycle (something like 2h,4h,6h, 12h and 24h).

Is the chemiluminescence signal for the i-lacZ induced parasites comparable to the stably expressed lacZ parasites previously characterized by the group? If so, do the authors consider this inducible iteration a complete replacement for PRR assays?

Comments on revised version:

The authors adequately addressed our comments and the resulting manuscript describes a specialized resource for antimalarial drug development.

Reviewer #3 (Public review):

In this manuscript, the authors strived to develop a highly efficient drug survival assay for in vitro cultured human malaria parasites P. falciparum. This was done by generating a transgenic P. falciparum line using a creLox strategy that allows detection of (presumably) viable parasites by a β-lactamase assay. To estimate the Limit of quantification of the recombined P. falciparum NF54i-lacZ, the authors ultimately designed a protocol in which viable parasites are detected by the luminescence of β-D-galactoside generated by β-lactamase within the transgenic parasites. For this, the parasite must be incubated with rapamycin for 120 hours to induce CreLox recombinase, which places β-lactamase under an active promoter. Using this assay, termed MULTI-i2, the author shows interactions between two antimalarial drug pairs that were previously demonstrated by another assay. In the case of pyronaridine and piperaquine pair, the NULT-i2 assay generated some additional insights compared to the previous assay, presumably by virtue of including more concentration datapoints. In conclusion, the authors argue that the MULTI-i2 assay is much less resource-intensive and time-consuming and can be applied on a large scale at a much lower cost and with the highest efficiency.

Overall, the data generated in this manuscript are clear and well represented, and I am convinced that MULTI-i2 provides yet another of many drug assays for malaria parasites and could be put to good use. However, I struggle to fully appreciate the merit of his study, as the manuscript reads more like a technical document than a scientific study.

I particularly lack an understanding of the strengths and weaknesses/limitations of the MULTI-i2 methodology and, thus, its applicability. I also do not fully appreciate the need for such an elaborate luminescence-based experimental setup. It would be good if some of these issues were addressed.

Specifically:

(1) The whole assay is based on detecting parasites by luminescence after 120 hr (5 days) after drug exposure. During that time, presumably the parasites that survived the drug pressure regrow to a detectable level and, at the same time, perform efficacious CreLox-based recombination to produce β-D-galactoside for detection. Is this necessary? How superior is this detection method to other methods, such as Fluorescence-assisted Cell Sorting (FACS) e.t.c.? Moreover, the 5-day growth-CreLox-β-D-galactoside production could introduce a series of confounding effects. In my view, more studies (beyond comparisons with a single existing method) would be useful for understanding this entire process.

(2) Related to that above, how would MULTI-i2 perform in case of drugs that do not necessarily kill all parasites, such as artemisinin? In the case of artemisinin, it is becoming evident that at least a small fraction of the parasite revives after treatment via a temporary dormancy state. This has, in fact, also been shown for other drugs such as mefloquine, pyrimethamine, etc. Would such a situation produce a range of false readings? In general, in its current state, it is hard to see what the limitations of this method are, which makes it hard to decide whether to use it for a particular application.

(3) Given the stated cost and labor efficiency of MULTI-i2, it is disappointing to see only two applications for two drug pairs: atovaquone/proguanil and piperquine/pyronaridine, for both of which their interactions were already known. The manuscript would benefit greatly if the authors demonstrated more drug interactions and identified (and ultimately validated) new ones. This would certainly make MULT-i2 method more attractive. In particular, it would be nice to see if one could use MULTI-i2 for studies of triple combinations as enthusiastically suggested.

(4) Throughout the manuscript, the authors claim that MULTI-i2 is considerably less expensive and can be done much faster than previous methods. In my view, this is not exactly a scientific argument. The cost of an assay depends heavily on the cost of reagents and labor, which are subject to market price fluctuations. The efficiency and time consumption can very much depend on laboratory organization etc. Unless the author could specifically demonstrate where and how these assays are cheaper and faster, I suggest not discussing this.

Comments on revisions:

I have no more comments.

Reviewer #1 (Public review):

Summary:

Patients with STX11 mutations develop familial hemophagocytic lymphohistiocytosis Type 4, a fatal immune disorder marked by defective T and NK cell cytotoxicity and cytokine storm. The conventional explanation attributes this to impaired cytotoxic granule release, but this has never fully accounted for the broader disease picture. This study proposes an alternative mechanism. The authors show that STX11 is required for store-operated calcium entry through ORAI1 channels, which are essential for both cytotoxic killing and NFAT-driven gene expression in T cells. In STX11-deficient cells, ORAI1 currents drop, NFAT nuclear translocation fails, IL-2 expression is suppressed, and degranulation is impaired. These defects are largely rescued by ionomycin or a constitutively active ORAI1 mutant, placing the primary lesion at calcium signaling rather than the fusion machinery. Mechanistically, STX11 binds the C-terminal tail of ORAI1 via its Habc domain and maintains ORAI1 in a state competent for productive assembly prior to STIM1-dependent gating, a step the authors call "priming."

Strengths:

The paper identifies a novel and disease-relevant role for STX11 in calcium channel regulation and raises the possibility of using channel agonists as a therapeutic strategy in the disease. The biochemical and functional data are of high quality and generally consistent with the interpretation. The proposal that a non-conventional syntaxin directly interacts with ion channels to prime its activation is novel and interesting. Additional experiments now exclude the possibility that STX11 acts as a SNARE to sustain calcium fluxes by promoting the delivery of additional functional channels.

Weaknesses:

Previous studies reporting regulation of ORAI1 by vesicular trafficking are ignored and alternative mechanisms are not considered.

Reviewer #2 (Public review):

Summary:

Vig's lab delineates a critical role for STX11 in CRAC channel function, particularly in the context of the fatal immune disorder familial hemophagocytic lymphohistiocytosis type 4 (FHL4). They demonstrate that Syntaxin 11 directly binds and regulates Orai1, and that STX11 depletion abolishes CRAC currents and downstream signaling. Loss of STX11 reduces IL2 gene expression and impairs degranulation, both of which are rescued by the constitutively active Orai1 mutant H134S, whereas a gain‑of‑function mutant targeting the C‑terminus fails to restore these defects. The authors conclude that STX11 primes Orai1 for optimal local assembly that is independent of STIM1 yet required for CRAC channel gating.

Strengths:

This study is firmly grounded in disease biology and demonstrates that STX11 downregulation leads to profound functional defects. Using a comprehensive suite of methods and analyses, the authors interrogate the co-regulation of STX11 and Orai1 and present a near-complete view of STX11's modulatory role in CRAC channel function and downstream signaling pathways. The figures are clear, and the statistical analyses are rigorous and convincing.

Weaknesses:

The authors conclude that Syntaxin 11 directly binds Orai1. This conclusion is well supported by a multifaceted approach-including co-immunoprecipitation (co-IP), molecular dynamics simulations, co-localization/FRET assays, and targeted mutational analysis-all of which are thoroughly executed. While the interaction appears reasonably strong in co-IP experiments, the STX11-Orai1 interaction is comparatively weaker in pull-down assays, which the authors attribute to instability of the purified His-STX11 protein. A remaining gap is direct evidence of interaction in live cells; this is understandably challenging given that fluorescent tagging of STX11 is not feasible. Fully resolving this question lies beyond the scope of the present study and will require more advanced approaches to capture STX11 binding dynamics.

Comments on revised version.

The authors have addressed all my comments highly satisfactorily!

Reviewer #1 (Public review):

Summary:

In this article, Vialat and his colleagues examine the early stages - which remain largely unknown - of the tumor escape process, particularly the basal extrusion of tumor cells following endocrine therapy for prostate cancer.

They first used the "Prostate Cancer Atlas" database, which provides access to a vast amount of transcriptomic data, to perform high-throughput analyses. Interestingly, analyzing a series of Androgen Receptor (AR) target genes in castration-resistant prostate cancers, they concluded that the loss of the canonical AR signaling pathway may contribute to tumor resistance.

Using a well-established model in Drosophila, they then replicated in vivo an endocrine therapy targeting the accessory gland by genetically inhibiting the expression of ecdysone, the only sex steroid present in Drosophila. These experiments induced basal extrusion similar to the mechanism observed in tumor escape in humans.<br /> These results suggest that the deprivation of sex steroids may play an important role in tumor progression.

However, although the data from the "Prostate Cancer Atlas" constitutes a powerful tool that serves as the basis for this new concept, clinical validation using carefully selected human tumor samples would help strengthen the authors' conclusions.

Strengths:

(1) The Prostate Cancer Atlas is a comprehensive collection of clinical data derived from RNA sequencing and serves as a powerful tool for conducting high-throughput analyses in this paper.

(2) The Drosophila model used in this article is well established and has already been the subject of publications by the team. In addition to being an in vivo model, Drosophila offers a threefold advantage for this study: i) the presence of an accessory gland, similar to the prostate, which allows for the simulation of tumor formation and, in particular, extrusion mechanisms; ii) its regulation by a single sex steroid, ecdysone; iii) the genetic ability to modulate or inactivate ecdysone expression, which allows for a parallel to be drawn with hormonal deprivation in humans.

(3) This study presents interesting and original findings. The data are, for the most part, of high quality.

Weaknesses:

(1) The Prostate Cancer Atlas, which is an essential tool in this study, was described only briefly - if at all - in both the introduction and the "Materials and Methods" section. The selection criteria used to distinguish CRPC or NEPC from adenocarcinoma in the Atlas or as determined by the authors, as well as the analytical methods, were not specified. It is therefore difficult to be convinced by the results, particularly those presented in Figures 1 and 2.

(2) Although the hypothesis put forward by the authors - that the deprivation of sex hormones contributes to tumor progression - is strongly supported by the Drosophila model and by the in silico analysis of transcriptomic data from the Atlas, this concept still needs to be clinically validated by analyzing a series of prostate cancer samples, either through transcriptomic analysis or by tracking gene expression in histological sections.

(3) With regard to the cells responsible for tumor escape, stem cells have been described as "candidates for the initiating resistant tumor growth" (lanes 50-55), but it is also essential to address the recent concept of "persistent cells". Indeed, these cells have been primarily associated with their tolerance to treatment (chemotherapy) and are referred to as "drug-tolerant cells". However, persistent cells could also correspond to cells that evade hormone therapy in the case of prostate cancer. This possibility should be discussed in the article.

Reviewer #2 (Public review):

Summary:

In this study, Vialat and collaborators study the role of steroid hormone signalling on the development of prostate cancer (patients) and of accessory gland tumours in Drosophila, a tissue functionally equivalent to the prostate. Mining publicly available prostate cancer expression data and using gene expression signatures, they uncover that androgen signalling is actually down-regulated in castration resistant prostate cancers (CRPC) compared to "primary" cancers, leading the authors to wonder whether down-regulation of canonical androgen signalling could represent an important event increasing tumour aggressiveness. They then take advantage of their recently published tumour model in the accessory gland of Drosophila adult males, in which cells are primed for tumorigenesis by the constitutive activation of the EGFR receptor, to test directly this hypothesis. They show that the genetic invalidation of ecdysone reception and signalling increases the aggressiveness of the "pre-cancerous" lesions, and that ecdysone-insensitive tumours present higher proliferation and initiate basal extrusion.

Strengths:

The authors bring original observations on the role of ecdysone signalling to prevent male accessory gland tumour development in Drosophila

Weaknesses:

(1) The link between the human data mining and Drosophila model is not straightforward.<br /> (2) Important information, in particular clinical information, is missing in the presentation of the cancer patients' data, making it complicated to grasp the solidity of the claims.<br /> (3) Data-mining insights should be validated by orthogonal approaches.<br /> (4) Ecdysone signalling activity should be monitored.

While the two parts of the study both investigate the role of steroid signalling on tumour growth, the link remains slightly artificial. I think starting with Drosophila and then opening with some patient data would be better suited to the level of proof reached here, implying that the anti-tumoral role of steroids observed experimentally in the fly might be conserved based on data mining in patients, rather than trying to prove in the fly the hints gained from public data mining. Indeed, there are many important differences between the mammalian prostate and the fly accessory gland, as well as between sex hormone androgen signalling and developmental timing ecdysone signalling.

The prostate cancer data mining and re-evaluation brings some interesting observations that appear to challenge the androgen driver, contrary to the vast amount of literature. Indeed, the authors observe an apparent decrease in androgen signalling in the more advanced states of the disease, in particular CRPC. In order to better evaluate its clinical relevance, more background on the tumours analysed should be provided.

What treatments were received by the patients? Hormonotherapy? LH/RH analogues? +/- anti-androgens? Are these treatments still given when CRPC emerge and tissues were banked? Metastatic disease? Are these only primary tumours in situ? Are there metastases included in the analyses?

Frequently, castration resistance is associated with alternatively spliced variants of the AR (AR-V7) that become constitutive and could bind to new AR-sensitive enhancers, even in the absence of androgen. Is the splice variant status of patients known, or could it be inferred from the expression data? Would there be different responses according to AR-V7 status?

Regarding the signature used. Why not monitor PSMA, one of the major prostate cancer markers, which is regulated by AR?

Finally, to consolidate the surprising observation that AR signalling is repressed in CRPCs, the authors should back these in silico predictions with orthogonal approaches such as histochemistry on patients' TMA or tissues from mouse models, monitoring AR activity.

Regarding the fly experiments, the observation that ecdysone signalling depletion cooperates with EGFR-lambda activation to generate big overgrowths that delaminate basally without passing through the muscular sheet is interesting. However, several important controls need to be provided in order to support the claims:<br /> a) The authors should use an ecdysone reporter (ERE-LacZ, ERE-GFP...) to monitor and show that Ecdysone signalling is indeed lower in the tumours after genetic manipulations, or that it is higher in EGFR-lambda small clones.<br /> b) EcR is normally a repressor, which is turned into an activator in the presence of 20-hydroxyecdysone. The removal of EcR could lead to de-repression of genes and thus slightly activate the pathway. Monitoring ecdysone signalling activity is thus critical.<br /> c) The authors should also monitor the expression of Phantom, Shadow, Shade, and EcR in the different accessory glands (wild-type, EGFR-lambda, EGFR-lambda & EcR-RNAi). It is extremely surprising that systemic ecdysone has so little role since Phantom, Shadow, or Shade RNAi appear as potent as EcR-RNAi. This quantification has actually been performed for Sad in Figure S5, which is not even mentioned in the text. It should be done for Phtm.

A UAS-yellow-RNAi (or similarly irrelevant RNAi) rather than UAS-GFP should be used as a control for the EcR, Phtm, Sad, Shd, and Tub RNAi. Indeed, loading the RNAi machinery could have some unexpected effects not controlled by the UAS-GFP.

The authors should not use the term "sex steroid" when referring to ecdysone. It is a steroid hormone important for developmental timing and rate of growth, but is not a sex hormone, as sex is cell autonomously genetically determined in the fly.

Reviewer #1 (Public review):

[Editors' note: this version has been assessed by the Reviewing Editor without further input from the original reviewers. We thank the authors for revising the manuscript according to the reviewers' comments. We have no further comments.]

In this manuscript the applicants study two residues in the GHKL ATPase active site of Aq MutL and GyrB, and argue that the catalytic base function is shared between two conserved acidic residues that are 3 residues apart.

In the manuscript, the authors generated mutant versions in MutL and GyrB (both ala and the appropriate Asn/Gln version) and performed ATPase analysis. They also generated high resolution crystal structures of the GyrB NTD with AMPPnP for WT and mutants of the two acidic residues. The data show that mutation in either of these residues does not fully kill activity (with the exception of the Alanine mutation of the first of the two, that interferes with ATP (or AMPPnP) binding). When the acidic residues are mutated to Asn/Gln, the catalytic water can still be positioned, and hence these mutants are more active than the Ala mutants. In both cases the double mutation is catalytic dead.

The authors then perform phylogenetic analysis and ancestral gene reconstruction and based on this they argue that HSP90 forms a different class of GHKL ATPases, and lost rather than gained this separate status.

Reviewer #2 (Public review):

Summary:

In this manuscript, Fukui et al. re-examined the ATP hydrolysis mechanism in GHKL ATPases, revealing a cooperative role of two conserved acidic residues rather than one. The authors have used a range of biochemical and structural techniques on various mutants from different members of the GHKL ATPase family to test and validate their proposed mechanism.

Through a detailed re-analysis of their previously published structure of the aqMutL NTD (ATPase domain) in complex with AMPPCP, they identified Glu29 and Glu32 as interacting with nucleophilic water for the catalysis. The authors carefully dissected the respective roles of these two acidic residues with a series of site-directed mutations. Mutations at Glu29 impaired ATPase activity without affecting protein secondary structure or ATP binding in the case of the E29Q mutant. Moreover, mutations at Glu32 did not affect secondary structure (except for E32G) but reduce ATPase activity. Activity was abolished when both residues (E29Q/E32Q) are mutated.

The authors extended their study to another GHKL ATPase, aqGyrB. Their findings further supported the cooperative function of the corresponding acidic residues in aqGyrB (Glu48 and Asp51) during ATP hydrolysis. Mutation of these residues partially impaired ATP hydrolysis without affecting protein secondary structure. ATPase activity was completely lost in the double mutant E48Q/D51M. While the E48Q mutant retained the ability to bind ATP, the E48A mutant did not. High-resolution structures of the WT and E48A, E48Q, D51A and D51N mutants of the aqGyrB NTD demonstrated that nucleophilic water positioning depended on these residues. E48 played a dominant role in water positioning and is critical for stabilising ATP lid formation and associated conformational changes, whereas D51 contributed cooperatively to catalysis.

The authors investigated the functional impact of mutating the corresponding residues in the human MutL homologs PMS2 and MLH1. Clinical variants consistently exhibited reduced or abolished ATPase activity, providing a potential molecular basis for Lynch syndrome, through impaired DNA mismatch repair.

Lastly, through evolutionary analysis, the authors inferred that the second acidic residue was likely present in the common ancestor of MutL, GyrB, and MORC proteins, but was lost in the case of Hsp90.

Strengths:

(1) This study contains a detailed structural and biochemical analysis of a biologically important set of GHKL ATPases. The authors identify a second acidic residue that is conserved and contributes to catalysis in a large subset of GHKL ATPases. An updated and extended mechanistic model of ATP hydrolysis by this class of enzymes is proposed, which involves cooperative and partially overlapping roles for the catalytic residue pair. This revised mechanistic model is invaluable for the interpretation of clinical variants of GHKL ATPases such as PMS2 and MLH1.

(2) The work described was performed to an excellent and rigorous technical standard. The structural and biochemical data are sound. The evidence supporting the claims is compelling.

Weaknesses:

(1) The identification in this study of a second acidic residue contributing to catalysis but not absolutely essential for catalysis is a useful finding. However, given that many structures of GHLK ATPases have been determined with different nucleotide analogs bound and that the essential role of the first acidic residue is well established, the importance and scope of the advances described here remain focused within the field of study of GHKL ATPases.

(2) The authors assessed the consequences of variants in the human MutL homologs PMS2 and MLH1, but various other human GHKL ATPases contain clinically relevant variants, some of which have stronger disease associations than the mutations examined in this study. A broader analysis of any effect of disease-linked mutations in GHKL ATPases would have strengthened this study.

(3) The effect of other aqMutL NTD E32 mutants, particularly, the E32K mutant on ATP binding remains unclear, although experimental assessment of nucleotide binding would be challenging due to the high protein concentrations required for the equilibrium dialysis assay.

Reviewer #1 (Public review):

Summary:

The authors elegantly demonstrate a biochemically reconstituted approach to showcase the VDAC2-BAX interaction using lipid nanodiscs. The reconstitution method is specific to VDAC2 (and not VDAC1) and can capture several structural conformations. The authors show that the VDAC2-BAX heterodimer is sufficient for the direct capture and stabilization of BAX on the outer mitochondrial membrane by VDAC2. Their structural model demonstrates that a GXXXA motif within α-helix 9 of BAX drives its interaction with the β-barrel interface of VDAC2 in the membrane. AlphaFold 3 models suggest BAX adopts several distinct conformations, notably including both a strongly pore-occluding state and a loosely pore-occluding state. Functionally, electrophysiology experiments suggest that the addition of BAX modulates the voltage-gating function of VDAC2 by reducing conductance. Finally, conformation-specific antibodies and cross-linking mass spectrometry capture these structural rearrangements of BAX, reinforcing the proposed structural model.

Strengths:

Overall, the manuscript provides a solid structural and molecular rationale for BAX recruitment to VDAC2 and its subsequent oligomerization.

Weaknesses:

The authors have not sufficiently discussed key protein modifications during apoptosis in detail, especially regarding residues implicated in phosphorylation and their impact on VDAC2 association.

Overall, the manuscript is well written and presents an elegant biochemical and biophysical approach to identifying key functional states of the VDAC2-BAX complex. However, certain key functions of the complex are not extensively discussed or accounted for in the final model. For instance, components of this complex are phosphorylated in response to apoptotic or anti-apoptotic cues. Specifically, phosphorylation of S184 (located within the critical α-helix 9), T167, and S163 has key functions in promoting or preventing outer mitochondrial membrane translocation. How do the authors reconcile their structural models with the functional states of the complex generated in response to these signaling cues? This is particularly relevant given that the expression systems used here presumably yield proteins lacking these post-translational modifications (PTMs). The authors should consider running AlphaFold 3 predictions that incorporate key PTMs and discuss their potential functional impact. In its current state, the manuscript implies that unmodified BAX is sufficient for membrane translocation. Clarifying how PTMs influence pore occlusion and 6A7 epitope accessibility would significantly enrich this body of work.

Reviewer #2 (Public review):

In this study, the authors aimed to elucidate the precise molecular details underlying the BAX-VDAC2 interaction and subsequent BAX activation. To achieve this, they successfully combined AlphaFold3 structural modeling, cross-linking mass spectrometry, site-directed mutational screening, biochemical assays, and functional electrophysiology experiments.

The authors demonstrate that the direct interaction between BAX and VDAC2 is fully autonomous, occurring independently of any additional mitochondrial or cellular proteins. Their findings suggest that BAX exists on the outer mitochondrial membrane in two distinct populations: loosely membrane-associated, and tightly stabilized via its specific interaction with VDAC2. Crucially, the data overturn historical assumptions by demonstrating that BAX does not insert into the internal VDAC2 channel pore. Instead, the BAX α9 helix docks onto the lipid-facing outer surface of the VDAC2 β-barrel.

Interestingly, while the anchor is external, the soluble domain of BAX physically blocks the pore opening, leading to the observed occlusions of the VDAC channel. Following this docking event, the N-terminal 6A7 epitope of BAX becomes exposed, signaling a conformationally active state. However, the authors show that this structural activation does not trigger an immediate release from VDAC2 or prompt immediate oligomerization. Rather, BAX is maintained in a pre-oligomeric, primed intermediate state while bound to VDAC2. What ultimately regulates the release of this primed intermediate from VDAC2 to allow full oligomerization and pore formation remains an open question.

Altogether, this study provides pivotal mechanistic insights, clearly defining VDAC2 as a key checkpoint regulator of mitochondrial apoptosis.

Reviewer #3 (Public review):

Summary:

The authors are trying to provide the molecular basis for the emerging role of VDAC2 in mitochondrial apoptosis. They use multiple approaches from biochemistry, cell biology, and structural biology.

Strengths:

Isolating the VDAC2-BAX complex and providing the molecular basis of this interaction in mitochondrial apoptosis is pretty innovative and significant.

The authors have tried to validate their results using multiple approaches, which corroborates the quality of the study.

Weaknesses:

The scientific data and its presentation could be improved.

Reviewer #1 (Public review):

This paper looks at the effect of vincristine-induced peripheral neuropathy (VIND), a common effect of cancer therapy. The authors performed in vivo experiments in mice by injecting them with vincristine sulphate i.p. (+/- various inhibitors or antibodies) or E-selectin intraplantar (i.pl.), and in vitro experiments using dorsal root ganglia (DRG) neurons and bone marrow derived macrophages (BMDMs).

Inhibition of E-selectin with antibodies or genetic depletion reduced the accumulation of F4/80+ macrophages in the DRG and sciatic nerves (located beside the spine) after vincristine administration, and attenuated the mechanical hypersensitivity (paw withdrawal).

The authors went on to perform spatial transcriptomics on isolated DRG neurons and found some pathways changed. E-selectin injected directly intraplantar (i.pl.) mimicked the effect of vincristine administration on the mechanical hypersensitivity. Whereas chlodronate depletion of myeloid cells reduced these changes in the E-selectin model. Using LPS priming before vincristine in BMDMs in vitro, the authors demonstrate an increase in many cytokines, including IL-1beta (typically associated with the formation of an inflammasome) and elevated p-NFkB. Finally, treatment of mice with anakinra (which neutralizes IL-1beta) also attenuated the E-selection-induced reduction in mechanical hypersensitivity when injected i.pl.

The authors address an important aspect that after cancer therapy, there can be peripheral nerve damage that has lasting consequences for patients, although the precise mechanism is unknown. The authors delineate that E-selectin has an important role in the mouse model, where depletion or inhibition attenuated the negative effect of vincristine (i.p.) on mechanical hypersensitivity (paw withdrawal). Administration of E-selectin into the foot (i.pl.) also mimicked the changes observed in the vincristine-treated mice. There seems to be a role for macrophages, as they were associated with DRGs in vivo, and depletion attenuated motor deficits in the E-selectin injection model.

However, I am not convinced by the data supporting some of the conclusions drawn by the authors, particularly on the role of the NLRP3 inflammasome in their in vivo model.

Main points:

(1) The initial experimental paradigm looks at the DRG neurons, which are located by the spine, and from there the foot pad is examined in subsequent experiments. It would be relevant to show whether the foot pad is altered in the vincristine-treated mice and whether the infiltration of myeloid cells that was demonstrated at DRGs is also observed in the foot in the vincristine model. Otherwise, the mechanism being investigated in the vincristine model, which might have similar functional results (paw withdrawal), but the mechanism behind both could be completely different.

(2) The rationale of performing spatial sequencing on DRG neurons isolated from vincristine mice is unclear. It is likely that more information could have been obtained from looking at sections from these animals, and there would be a better link to the experiments on BMDMs which follow afterwards. Indeed, the spatial data does not seem to play a key role in the study. There is not a clear link between it (which was carried out on DRGs) and the later focus on macrophages and indeed the NLRP3 inflammasome.

(3) The authors suggest that the E-selectin is enhancing NFkB-induced priming of the NLRP3 inflammasome. LPS+vincristine increased IL-1b release from BMDMs in vitro, which was elevated in the presence of E-selectin. E-selectin also increased ASC speck formation by approx. 20% in vitro. The ASC speck formation in vitro was blocked by MCC950, a specific NLRP3 inhibitor, but the authors went on to use anakinra in vivo using the E-selectin i.pl. model. It is really unclear why the switch to anakinra occurred for the in vivo work, as blocking IL-1b is central to many inflammatory pathways, not just NLRP3. Use of MCC950 would have been more appropriate to demonstrate that negative effects on mechanical function are mediated by the NLRP3 inflammasome. As there were no readouts of NLRP3 inflammasome activity measured in any of the mice in vivo (e.g. local ASC specks, IL-1b release, western blot of typical inflammasome components such as IL-1b, caspase-1, ASC or gasdermin D) either at the DRG site or the foot, we cannot say that the cell culture data mimics or models the in vivo conditions at this time.

(4) Additionally, the reliance on the E-selectin administration models for the second half of the paper is curious. It would have been relevant to test whether the immune-modulating inhibitors could also attenuate the vincristine-induced effects on mechanism hypersensitivity, to better link the E-selectin model with the vincristine one.

(5) Details are missing from the figure legends and the methods. The concentrations of compounds used in cell culture and exposure times are not clear.

Reviewer #2 (Public review):

Summary:

Using antibody treatments, genetic models and in vitro studies, the authors convincingly show that E-Selectin is a driver of VIPN.

Strengths:

In vivo studies are robust. Antibody studies as well as the inflammasome-related work are very well done.

Weaknesses:

(1) The spatial transcriptomics data need to be improved in terms of visualization.

The authors should plot genes that define the cell types in the sequencing dataset, and also show the cellular map on the cut, not only UMAPs. Can the authors not use the n=3 samples per condition to perform some statistical analyses? While the CellChat analyses are informative, they are difficult to read. Fold change over control when comparing conditions and pathways may be a better way of visualization.

(2) In Figure 1B, the % DAB is not easy to understand. It would be better to do the staining also via IF, and then maybe to count nuclei. The corresponding figures shown in the supplemental figure are not convincing. If F4/80 is not working well, Iba1 could be an alternative.

(3) The authors should define the background of all the mice used. Have they been back-crossed to B6j mice? One cannot compare C57BL6J mice with full knockouts if they are not littermate controls. Especially immunological responses are completely dependent on the background of mice. See e.g. PMID: 40568896.

(4) Could the authors comment on the role of ICAM2? Why was this not tested as well?

Reviewer #1 (Public review):

Summary:

Late endosomes and lysosomes (LEL) are dynamic organelles with critical roles in cell physiology via transport of cargos to various destinations, degrading cargos, and as calcium stores. The latter is a less studied function of LELs, and virtually nothing is known about LEL function and transport in astrocytic processes. This manuscript investigates the dynamics of LELs in astrocyte processes co-cultured with neurons and finds that the lysosomal calcium channel Trpml1 regulates their positioning near astrocytic specializations (PAPs) downstream of synaptic activity.

Strengths:

Rigorous and well-controlled study of an understudied area of cellular neuroscience, namely regulation of organelle transport in astrocytes to shape synaptic environment and functionality.

Weaknesses:

Some of the same mechanistic links have been probed in neurons and other cell types, but astrocyte cell biology is still less extensively studied, making this an important contribution. Currently, only cultured astrocytes are being investigated.

Reviewer #2 (Public review):

Summary:

Many ion channels/transporters in endosomes and lysosomes remain poorly understood. Even though the functional importance of endo-lysosomes in astrocytes has been recently recognized in many neurological diseases including lysosomal storage disorders and neurodegenerative diseases, the basic biology has not been much studied. In this manuscript, Spivey et al. showed how one of the key ion channels i.e., TRPML1, regulates endosomes and lysosomes (LELs) in astrocytes -which are also not much investigated in the field, compared to neurons- and its activity may further affect the structure of astrocytes and synaptic activity of neighboring neurons. The authors elegantly use multiple controls from agonists, antagonists, and TRPML1 knockdown to corroborate the results. The data are very strong and well supported. I believe that revising a few parts of the manuscript will greatly augment the significance of this work.

Strength:

The rigor of the study and data using various controls. The quality of the data is also very impressive.

Weakness:

A limitation of the study is that the mechanistic experiments rely primarily on overexpression or genetic knockdown of TRPML1 approaches, both of which alter TRPML1 abundance on endolysosomal membranes and potentially introduce artifacts related to protein level, affecting luminal ion homeostasis. While the overall conclusions are convincing, validation in a genetic MCOLN1 knockout mouse model would provide more definite evidence for the proposed mechanism.

Reviewer #3 (Public review):

Summary:

In their manuscript, the authors assess how TRPML1 influences lysosome trafficking and function in astrocytes using a neuron-astrocyte coculture system. Specifically, it was found that activation of TRPML1 reduces LEL motility in astrocyte branches while TRPML1 increases it, and a model was proposed in which TRPML1 coordinates lysosomal positioning along astrocyte branches, enabling LELs to locally regulate actin-membrane linkers that influence PAP (peripheral astrocyte processes) structure and plasticity. The authors primarily use pharmacology to buttress their findings.

Strengths:

TRPML1 is currently under investigation as a potential therapeutic target for lysosomal storage disorders and neurodegenerative diseases such as AD and PD. The manuscript is hence timely and important as the crosstalk between glia cells and neurons is likewise increasingly recognized as disease-relevant.

Weaknesses:

Unfortunately, experiments performed to investigate the role of TRPML1 are based purely on pharmacological tools. No bona fide KO data are available. At least for some experiments, this should be done. MLIV iPSC lines are available.

If no KO controls are being provided, at least the authors shall use ML1-SA1 (EVP-169) as an agonist instead of ML-SA1, because ML-SA1 activates all three TRPML channels, which would be a major problem for this study. Likewise, the ML-SI3 antagonist also has effects on other TRPMLs. EDME is a blocker with higher specificity for TRPML1.

When using pharmacological tools, the original papers relating to these tools may be cited. For example:

- For ML-SA1 https://www.nature.com/articles/ncomms1735 and for MK6-83 https://www.nature.com/articles/ncomms5681

- ML-SI3 as a blocker for TRPML1 seems problematic: https://pubmed.ncbi.nlm.nih.gov/33187805/ ; an alternative may be: https://www.nature.com/articles/s41598-021-87817-4

No reference is made to other important regulators of lysosomal cation homeostasis such as TPC1 or TPC2, two other Ca2+/Na+ permeable cation channels, or other TRPML channels. The authors should provide some data supporting or excluding a role of these channels.

Reviewer #1 (Public review):

Bajohr and colleagues propose a transcription factor-driven approach to generating bonafide oligodendrocyte lineage cells (OLCs) from primary mouse astrocytes. Ectopic expression of Olig2, Sox10, or Nkx6.2 in isolated astrocytes produced a range of OLC-like cell states, with Sox10 emerging from lineage tracing and single cell RNA sequencing experiments as the most successful transcription factor in driving direct lineage reprogramming. The authors strengthened their claims with an unbiased, deep learning perturbation model to predict genetic drivers of the astrocyte cluster to OLC cluster transition observed in their scRNA seq dataset. Here, Sox10 surfaced in the top ten correlated genes, and the top transcription factor, mediating this fate shift. Altogether, this paper presents an interesting approach to generate OLCs, a cell type historically difficult to procure, from primary mouse astrocytes to study this lineage in development and disease and perhaps repopulate it in dysmyelinating conditions. While this certainly addresses a technical gap in the field, authors defined iOLCs as ones with lineage-specific gene expression and morphological characteristics, lacking any functional analysis to assess the reprogrammed cells' capacity to myelinate. This comment and other critiques are discussed below.

While Sox10 and Mbp expression in iOLCs, as confirmed by IHC, is a promising result suggesting that ectopic Sox10 instructs transduced cells to develop into cells of myelinating potential, functional confirmation is essential. As mentioned in the discussion, the absence of a substrate for myelination may have also contributed to the low DLR efficiency. Co-culturing Sox10 iOLCs with primary neurons and examining the cells' potential to engage and enwrap axons would greatly strengthen the authors' claim that this could be an effective therapeutic approach to myelin regeneration in vivo, or even a technical approach to studying myelin dynamics in vitro.

In Figure 1B, it appears that Mbp expression in tdTomato+ cells decreases in Sox10 transduced iOLs during the observed time period. Can the authors elaborate on this result, given that MBP expression is crucial for myelination and should, if anything, increase with time?

The authors acknowledge that there is a conversion of tdTomato- zsGreen+ cells with an astrocyte-like morphology to OLC cells expressing Mbp following Sox10 induction (Supplementary figure 5C,D). While they note the diversity of the astrocyte lineage in the discussion, further analysis should be applied to this subset of cells to confirm the subset of astrocyte or progenitor-like cell type that gives rise to their cell endpoint of interest (Sox10-driven Mbp+ iOLs).

Finally, ectopic expression of Olig2 and Sox10 in primary astrocytes resulted in very different OLC subtypes, as evidenced by OLC marker expression seen in IHC and the subclustering of these cell types in scRNA seq. Although this diversity in OLC type and generation efficiency follows with previous reports showing that these two transcription factors vary in effect, might the authors further discuss this discrepancy given that the two transcription factors regulate one another (as mentioned in the introduction) and should theoretically give rise to more similar cells? Perhaps due to the lower specificity of Olig2 in marking a pure OLC population relative to Sox10?

Reviewer #1 (Public review):

Summary:

The authors describe a new database that rigorously explores protein conformations.

Strengths:

It is extremely well done, using state-of-the-art tools by a group at the top of the field of structural modeling. The evaluation of qualities and the benchmarking of the structures are outstanding, and it is expected that the new database will have a significant impact on the field.

Weaknesses:

The authors are using MD simulation to generate some of the structure, and therefore should have access to standard MD energies. I am surprised that no evaluation is provided based on these energies that can be extended to free energies.

Reviewer #2 (Public review):

Summary:

The authors developed a dataset of protein conformations by running molecular dynamics simulations starting from both native and decoy conformations for a large number of proteins. These conformations were put together as a dataset for querying and downloading, along with their energies under different force fields. The authors suggest that such conformations represent the proteins' conformational landscape, so that they will be useful for evaluating methods generating multiple conformations of proteins.

Strengths:

The dataset is online and working. It has good documentation for others to use.

Weaknesses:

The biggest weakness is that the collected conformations very likely do not represent the true conformational landscape. To represent the conformational landscape, the structures need to be sampled based on the Boltzmann distribution. However, in this study, conformations are generated by running very short (125ps to 375ps) MD simulations starting from near-native conformations and decoys. Such short simulations will produce small fluctuations around the starting conformations, so the distribution of conformations is largely dominated by the distribution of the initial conformations, which by one means are Boltzmann distributed. A conformation might be physically plausible, but it might have very small weight in the Boltzmann distribution. On the other hand, conformations with large weights might not be in the dataset.

Reviewer #3 (Public review):

Summary:

This manuscript describes a web-based tool that allows researchers to compare large numbers of representative ("plausible") conformations of proteins. It also includes energetic analysis from multiple widely used structure-prediction methods.

Strengths:

This tool will likely be useful for students who want to learn more about the ensemble properties of proteins. The resource is well organized and it represents a large amount of computing resources.

Weaknesses:

It is not entirely clear how the database may be utilized by other groups to advance research. It could be helpful if the authors add a short section that provides example use cases that illustrate how this database can support new strategies for studying protein dynamics.

Reviewer #2 (Public review):

This work is composed of two largely independent parts. The first part (Figures 1-4) attempts to study correlations between the anterior cingulate cortex (ACC) and hippocampal area CA1 in the context of learning and memory; a number of issues including missing controls make this part inconclusive and hard to interpret. The second part (Figures 5 and 6) presents evidence for a pathway in which inputs from the ACC indirectly inhibit pyramidal cells in the superficial sublayer of CA1. The optogenetic evidence demonstrating the functional connection, including the interneurons likely to be involved, is convincing, making the second part of the manuscript a valuable contribution to neuroscience. However, I do not see evidence for this connection in the correlational analyses in the first part of the study, making the involvement of this pathway in learning and memory uncertain.

Strengths:

The biggest strength of the work is the optogenetic manipulation experiments in the second part of the study (Figures 5 and 6), which convincingly demonstrate that stimulation of ACC pyramidal neurons activates an interneuron population with symmetric spike waveforms, and inhibits parvalbumin interneurons and pyramidal cells in CA1sup, while CA1deep cells remained largely unaffected by the stimulation.

Weaknesses:

The main weakness is the disconnected nature of the two parts of the study. The second part convincingly shows that ACC provides a net inhibitory drive to the hippocampus (at least to CA1sup pyramidal and PV cells, while CA1deep cells were mostly unaffected). However, the first part investigates positive cross-correlations between pre-ripple ACC activity and subsequent CA1 ripple activity. This can be observed in Figure 1-supplement 1, where CA1 cells' activity peaks around 70ms after ACC spikes. Moreover, the GLM analyses were also based on positive ACC cell-CA1 cell pair correlations as the authors reported no bias towards negative weights for the GLM analyses (see the rebuttal letter). Thus, the correlational and GLM analyses in the first part primarily characterize a positive ACC-CA1 relationship, rather than the inhibitory influence demonstrated in the second part; the two parts of the manuscript therefore investigate different phenomena (possibly confounding inputs and network effects in part 1 versus the direct ACC-CA1 connection in part 2).

The key problem is that the main results of the two parts - namely, a dampening of the positive cross-correlations following learning in part 1 and the inhibitory ACC-CA1 connection revealed in part 2 - would be contradictory if they were interpreted as describing the same phenomenon. If the inhibitory ACC-CA1 connection was key to the downregulation of CA1 activity after learning as the authors suggest in the discussion, then we would expect ACC activity driving this change to be particularly predictive of CA1 activity in this post-learning period. Indeed, because prediction gain measures how well ACC spiking can predict subsequent CA1 spiking, any additional predictive information from the direct ACC->CA1 pathway should increase prediction gain. Instead, prediction gain decreased following learning. Thus, the positive (dampened after learning) ACC-CA1 correlations observed in the first part cannot be explained by the inhibitory ACC-CA1 pathway demonstrated in the second part. The most likely explanation is therefore that the cross-correlations studied in part 1 are dominated by other factors (such as shared inputs from other areas or coordination of cortical rhythms) and reported changes in prediction gain therefore primarily reflect changes in these factors, while the contribution of the direct ACC-CA1 pathway is drowned out and undetectable using this approach. As they stand, the two halves of the paper cannot be reconciled into the same framework.

The second weakness is the lack of control for learning. The main result of part 1 of the study is that there is dampening of the (positive) CA1 response to ACC pre-ripple activity after learning. However, nothing indicates this is due to learning as there is no control data with no learning. Moreover, the pre- and post- task periods were not matched for duration and sleep depth, so it is entirely possible that the observed dampening could be due to reduced recruitment of some cells in ripples. An appropriate control would therefore be important for attributing this to learning

The final weakness is statistical and goes beyond the lack of hierarchical statistics (which is also an issue with this work). The failure of a test to reach significance cannot be interpreted as evidence for the opposite. Yet the authors interpret it as such: for example, the lack of significant correlation between prediction gain values in pre- and post-task sleep in Figure 3C (p=0.14) is incorrectly interpreted as proof that ACC-CA1sup communication has reorganized as a result of learning. The claims of reorganization (mentioned multiple times in the abstract) hinge solely on this failed statistical test. Yet a failure to reach significance does not successfully demonstrate reorganization as it could result from a number of other reasons, including lack of statistical power or noisy estimates. To demonstrate reorganization, one would need to show that the observed change is greater than expected under an appropriate control (e.g. control task with no learning; or sleep data split in two halves), but this is missing from this manuscript.

Note that in the entire manuscript, the only differences between CA1sup and CA1deep are reported as two independent tests, one of which is significant and the other does not reach statistical significance. However, this is not evidence for different effects in CA1sup and CA1deep and statements like "we uncovered a pathway-specific difference" to describe these findings are unwarranted and not supported by the data; only direct statistical comparison between the two effects could support such claims. The exception to this weakness is the optogenetic experiments in Figure 5 where CA1sup and CA1deep responses to optogenetic ACC stimulation were directly compared and found to be different.

Reviewer #2 (Public review):

This study investigates how altered neural oscillations may contribute to unilateral spatial neglect (USN) following right-hemisphere stroke. By combining steady-state visual evoked potentials (SSVEPs), phase-amplitude coupling (PAC), transfer entropy (TE), and computational modeling, the authors aim to show that USN arises from disrupted hemispheric synchronization dynamics rather than simply from lesion extent. The integration of empirical EEG data with a mechanistic model is a major strength and offers a valuable new perspective on how frequency-specific neural dynamics relate to clinical symptoms.

The work has several notable strengths. The combination of experimental and modeling approaches is innovative and powerful, and the findings provide a coherent mechanistic framework linking abnormal neural entrainment to attentional deficits. The study also provides concrete compelling evidence supporting the potential for frequency-specific neuromodulatory interventions, which could have translational relevance.

In the revised manuscript, the authors have carefully and comprehensively addressed the concerns raised during the first round of review. In particular, the additional characterization of lesion distribution and volume provides important anatomical context for the electrophysiological findings, while the rationale for the choice of electrodes and clinical correlation analyses is now much clearer. The methodological description has also been improved substantially, including clarification of the SSVEP measure, analysis procedures, and potential confounds related to transfer entropy and volume conduction. In addition, the discussion now provides a more nuanced account of the relationship between stimulus-locked responses and intrinsic oscillatory activity, as well as the potential contribution of alpha lateralization to attentional dysfunction.

Overall, I consider the revised manuscript to provide compelling evidence for an important contribution to our understanding of the neural dynamics underlying spatial neglect. The authors have addressed my previous concerns satisfactorily, and the manuscript now provides a clearer and more balanced account of both the strengths and limitations of the findings. It should serve as a valuable reference for future work on oscillatory mechanisms in stroke and attention.

Reviewer #1 (Public review):

Summary:

The authors tackle a long-standing question in developmental theory: given a gene-regulatory network that includes extracellular signaling, which topologies are even capable of transforming an initial spatial profile into a genuinely new pattern? Building on the classical reaction-diffusion framework in one dimension, but imposing biologically motivated constraints, they prove that every one-signal sub-network must be either Hierarchical (H), self-activating (L+), or self-inhibiting (L-). They further demonstrate that only three composite classes of full networks - pure H, a coupled L+ L- "Turing" pair, and an L- module fed by an intracellular positive loop ("noise-amplifying")-can create non-trivial spatial transformations. Analytical criteria and illustrative simulations are provided, together providing a closed taxonomy, which is supposed to be relevant for real systems.

Strengths:

- Useful classification framework. Reducing a vast number of possible gene circuits to three canonical pattern-forming motifs is a valuable organizing insight for both theorists and experimentalists.

- Practical interpretability. Given a reaction network diagram, one can now decide (assuming the model applies to real systems) whether spatial patterning is even possible, saving experimental effort on in silico screens that could never succeed.

Weaknesses:

- Theoretical limitations in the application of Linear Stability Analysis (LSA): I remain uncertain about the framework's reliance on LSA as a necessary condition for non-trivial pattern transformation, especially for large initial perturbations ("spikes"). The revised manuscript itself states that spike amplitudes must be sufficiently small for the linearization to hold. In the rebuttal, the authors argue that large spikes can nevertheless be treated because their influence is initially small outside the spike. However, linear stability of a homogeneous steady state only describes the response to infinitesimal perturbations around that state; it does not generally exclude finite-amplitude perturbations from entering a different nonlinear basin of attraction and producing a heterogeneous stationary state, e.g., as in subcritical Turing patterns. Thus, I do not think the rebuttal establishes the stronger claim that a linearly stable network cannot produce a non-trivial pattern regardless of nonlinear terms.

- Presentation: The manuscript remains difficult to follow. The argument is distributed across many named requirements and topology classes, long prose descriptions of network structures, and repeated cross-references to the Supplementary Information. Given that the main contribution is a conceptual classification, I think the logical hierarchy should be considerably easier to reconstruct.

Discussion:

The study offers a solid conceptual organization of pattern-forming networks. However, the theoretical bridge between infinitesimal linear stability and macroscopic, non-linear pattern emergence still presents some uncertainties. The way the current framework formally treats large initial perturbations leaves some questions open regarding its broad analytical applicability to real biological tissues.

Reviewer #2 (Public review):

Summary:

The authors propose that bidirectional redistribution 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 redistribution 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, 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.

Comments on revised version.

The authors have adequately addressed my previous concerns regarding the optogenetic experiments, and the addition of the new modeling analysis further strengthens the study.

Reviewer #1 (Public review):

Summary:

The study presents a novel analysis of MRI resources for 16 avian species, spanning major (though not all) clades and ecological niches. This is a significant step towards large-scale datasets on internal parcellation and long-range connectivity, central to evolutionary studies for understanding the evolution of the bird brain.

Strengths:

The integration of high-resolution T2-weighted and diffusion-weighted MRI with histological validation (Nissl and Luxol Fast Blue staining) provides a strong, cross-validated framework for studying avian brain anatomy. Data on long-range connectivity are particularly useful for understanding how relationships between brain components evolved. The approach is also scalable, allowing for more detailed evolutionary analyses compared to what is currently possible.

Weaknesses:

The sampling supports evidence of modular evolution in the bird brain, but it is limited for broad evolutionary claims, as the effects of sizes and phylogenies can be hard to disentangle without enough species per clade.

Tractography-based claims should be treated cautiously without sensitivity analyses. This is particularly important when comparing brains with different sizes and tissue properties.

Existing literature is not acknowledged sufficiently. This makes some claims of novelty misleading, and prevents readers from understanding the current state of knowledge in this research area.

Reviewer #2 (Public review):

This manuscript presents a comparative MRI dataset from 16 avian species and uses MRI and tractography to examine variation in brain organization across birds. The authors argue that their analyses support mosaic brain evolution and provide a framework for comparative neuroanatomy. Although the dataset represents a useful resource, particularly given the inclusion of understudied species like penguins, toucans, and hornbills, I have substantial concerns regarding the novelty of the study, the anatomical interpretation of the results, and the validity of the tractography analyses. In its current form, I do not believe the manuscript provides sufficient new biological insight to support many of its conclusions.

Major Concerns

(1) The authors repeatedly state that comparative neuroanatomical studies in birds have largely been unable to examine internal brain organization or "internal parcellation". This claim is inaccurate and reflects limited engagement with a substantial body of literature. For decades, comparative studies have examined variation in the size of major avian brain subdivisions as well as specific sensory, motor, and associative nuclei. For example, the extensive work of Andrew Iwaniuk and colleagues has documented variation in numerous brain regions across birds and related these differences to ecology, behavior, and sensory specialization (e.g., Gutierrez-Ibanez et al., 2009; Iwaniuk et al., 2006, 2008, 2010; Corfield et al., 2015). Other authors have also made important contributions in this area (e.g., Boire and Baron, 1994; Burish et al., 2004; Moore and DeVoogd, 2011, 2017). Importantly, previous work has already examined variation in major subdivisions of the avian brain using relatively standardized datasets (e.g., Iwaniuk et al., 2004; Iwaniuk and Hurd, 2005), including datasets that contain more species and greater taxonomic diversity than the current study. In other words, these studies have already provided detailed analyses of internal brain organization across broad taxonomic samples.

The manuscript should therefore be reframed as providing a new MRI-based resource rather than introducing the first comparative framework for studying internal avian brain organization. The current framing significantly overstates the novelty of the work.

(2) A second significant concern is the lack of anatomical specificity in the tractography analyses. The authors repeatedly refer to regions such as "anterior cortex," "dorsal cortex," and "temporal cortex." These terms are not standard anatomical designations in avian neuroanatomy and provide little information about the actual structures being analyzed.

For example, the "temporal cortex" could potentially include portions of the nidopallium (including the caudolateral nidopallium, NCL), mesopallium, and arcopallium. Similarly, the "anterior cortex" could correspond to the somatosensory or visual Wulst, the anterior nidopallium, or several other structures. The designation "dorsal cortex" is similarly difficult to interpret. Because these seed regions may encompass multiple functionally distinct systems, it is impossible to evaluate the biological significance of the reported connectivity patterns.

I strongly encourage the authors to define their seed regions using accepted avian neuroanatomical terminology and to provide detailed anatomical maps. More informative analyses would focus on well-defined structures with known connectivity, such as the Wulst, arcopallium, entopallium, or NCL. As currently presented, the tractography results are too coarse to support meaningful biological conclusions.

(3) I am not an MRI specialist, but I have concerns regarding the interpretation of the tractography results. Bird brains are small, and diffusion MRI tractography is already known to be challenging even in substantially larger brains. The manuscript provides limited information regarding image resolution, diffusion sampling, and the expected accuracy of tract reconstruction in these specimens. More importantly, there is little validation of the tractography results. Diffusion tractography is prone to both false positives and false negatives, and reconstructed pathways cannot be assumed to represent true anatomical connections.

The authors should provide evidence that their tractography pipeline can accurately recover known pathways. For example, they could compare reconstructed tracts with well-established anatomical pathways such as the anterior commissure or major visual pathways, which would substantially strengthen confidence in the results. Without such validation, it is difficult to determine whether the observed species differences reflect biological variation or methodological artifacts.

(4) I also have some methodological concerns regarding the comparisons of anterior commissure (AC) size and cerebellar foliation. First, the authors measure the AC in a coronal section. I would recommend measuring the AC area in a midsagittal section instead. Furthermore, the authors use the cross-sectional area of the same coronal section as the scaling variable. This seems problematic because the area of any given section will depend on the angle of sectioning and other technical factors. If the objective is to compare the relative size of the AC, then total brain volume or telencephalon volume would be more appropriate scaling variables.

With respect to cerebellar foliation, the authors developed their own metric. I would encourage them to use methods already established in the literature, such as the foliation index described by Iwaniuk et al. (2006). Their approach may yield similar results, but using the foliation index would facilitate direct comparisons with existing datasets and would allow incorporation of additional published data (e.g., Cunha et al., 2021, which includes foliation index measurements for 54 bird species). The authors should also be aware that the foliation index scales with body size. Consequently, the high degree of foliation observed in penguins may not necessarily indicate cerebellar expansion or increased demands for sensorimotor integration associated with their specialized locomotion. I therefore believe that the conclusions regarding variation in AC size and cerebellar foliation should be re-evaluated after more appropriate analyses are performed.

Reviewer #1 (Public review):

Summary:

Naina Gour and colleagues provide a detailed observational study in which they demonstrate that MRGPRX4, a human G-protein coupled receptor (GPCR), is expressed exclusively in human melanomas and, when expressed in mouse melanocytes, drives the development of melanomas in mice. These findings provide evidence that MRGPRX4 has the properties of an oncogene, at least in certain cellular environments.

Strengths:

A strength of this work is the nice historical note in which overexpression of MAS1, a GPCR, led to classic studies of transformed fibroblasts in culture and tumors in nude mice. Cloning of MAS1 led to the identification of the MRGPR family of receptors, now known to be key players in neuroimmune and neurosensory phenomena. Here, the story comes full circle with a member of the MRGPR family being linked to a tumor, specifically melanoma. Perhaps the story is not entirely surprising given that the neural crest serves as a precursor for both nerves and melanocytes. But it is nice to see.

Additional strengths include the vast array of tools and techniques employed, from public databases to engineered mice, to establish firmly that MRGPRX4 is expressed in melanomas, although not in every malignant cell.

Weaknesses:

Given the power of the strengths of the data and story, the following comment is only sort of a weakness, as the topic is addressed while being saved for future studies. Specifically, what leads to the expression of MRGPRX4? The authors posit that it is an epigenetic phenomenon, look briefly at methylation, and rather than going down the proverbial rabbit hole of what comes first, have reasonably decided to punt.

Another concern is that given what comes across as the initial observation of MRGPRX4 being expressed in melanoma, what do all of the additional studies add?

For the non-cognoscenti, and to make the manuscript more accessible, the abbreviation NC/EMT, which is also inverted to EMT/NC, should be spelled out periodically as neural crest/epithelial-mesenchymal transition.

Please explain how this study came about. Was it a result of someone deciding to look at expression in the GTEx project and compare it to a tumor database?

A comment could be made to explain that while NSG and normal mice were used, the former are immunocompromised, and drawing conclusions without specifying these differences is a weakness.

In Figure 1A, the p-value of -145 begs for a little explanation. I don't recall seeing such a p-value.

Have you considered treating the murine melanomas with murine via PD-L1? I appreciate that this comment is somewhat superfluous given the inhibition of MRGPRX4 with compound 31-2, but given the human therapeutics combined with the fact that you have done 'everything else', I wonder what might happen.

Given the basal ligand-independent signaling, might engineering variants of MRGPRX4 that do not signal be of value?

Reviewer #2 (Public review):

Summary:

This study presents a fundamental new finding - the identification of a sensory-neuron itch receptor, MRGPRX4, as an unexpected melanoma oncogene through a mechanism of lineage-inappropriate expression rather than mutation. The evidence supporting the core observation (tumor-specific upregulation, restriction to invasive transcriptional states, and sufficiency to drive fully penetrant metastatic melanoma in vivo) is compelling, drawing on convergent human genomic datasets and a well-controlled genetic mouse model. However, several of the mechanistic and translational claims - particularly regarding causal drivers of invasion, the immunosuppressive tumor microenvironment, and in vivo pharmacological efficacy - remain incomplete, relying on correlative evidence.

Strengths

The authors propose that MRGPRX4, normally restricted to a subset of peripheral sensory neurons, is aberrantly re-expressed in melanoma rather than through mutational mechanisms, and that this re-expression is sufficient to drive tumorigenesis through basal, ligand-independent GPCR signaling. This is a genuinely novel model for oncogenesis, and the manuscript deploys an impressive range of approaches - bulk and single-cell transcriptomics, spatial transcriptomics, proteomics, phosphoproteomics, and pharmacology - to support it.

Strengths:

The claim that MRGPRX4 is selectively upregulated in melanoma and confined to neural-crest-like/invasive transcriptional states is well supported, with consistent results across multiple independent human scRNA-seq datasets. The claim that ectopic MRGPRX4 is sufficient to drive melanoma is convincingly demonstrated by the fully penetrant, metastatic phenotype in the Tyr-CreER;MRGPRX4-LSL model, with appropriate specificity controls showing that MRGPRX1, MRGPRX2, and MRGPRX3 do not phenocopy this effect.

The claim that MRGPRX4 signals through basal, ligand-independent activity is reasonably well supported by bile-acid quantification showing endogenous ligand concentrations well below the EC50 required for activation.

Weaknesses:

The claim that MRGPRX4 remodels the tumor microenvironment toward an immunosuppressive state rests on flow cytometric frequency data (altered neutrophil/eosinophil ratios, increased PD-L1+ myeloid populations) but lacks any functional immune assay to demonstrate that this remodeling actually impairs anti-tumor immune responses.

The claim that the two MRGPRX4-enriched tumor subpopulations (ECM-rich and NC-like/invasive) underlie the observed invasive and metastatic phenotype is not directly tested; the authors appropriately acknowledge this as an open question, but it is worth noting explicitly that this leaves the mechanistic link between the identified cell states and the functional phenotype (proliferation, invasion, metastasis shown in Figure 4) unresolved.

Finally, the comparison with BRAF- and NRAS-driven GEMMs (Figure 3K-L) establishes overlap in transcriptional cell states but does not report whether these canonical models themselves upregulate endogenous Mrgprx4. This omission leaves unclear whether MRGPRX4 acts as a convergent node downstream of canonical oncogenic signaling, or represents an independent, parallel route to a similar phenotypic endpoint - a distinction that matters considerably for how broadly the finding should be interpreted.

Overall assessment:

The manuscript's central, most novel claim - that lineage-inappropriate expression of a sensory GPCR is sufficient to drive melanoma - is compellingly supported. The secondary mechanistic and translational claims built around this finding are convincing and consistent with the broader literature but are currently supported by correlative rather than causal or functional evidence.

Reviewer #1 (Public review):

Summary:

This work characterizes the regulation of lysine lactylation on influenza A virus PA protein, and describes how this post-translational modification at residues K605/K609 facilitates asymmetric polymerase dimerization at the ANP32 interface. The authors identify ATAT1 as the host enzyme mediating PA lactylation and SIRT1 as the enzyme responsible for removing this modification. They present evidence that PA lactylation enhances viral polymerase activity and viral replication, while suppression of lactylation impairs viral growth, polymerase function, and viral pathogenicity in vivo.

Strengths:

Overall, this manuscript explores a virus-host interaction axis illustrating how host metabolic signaling modulates influenza polymerase function. These findings are likely to attract broad interest, including influenza virologists studying polymerase regulation, as well as researchers investigating the functional roles of lactylation. This mechanistic insight may also offer clues for developing host-targeted antiviral strategies.

Weaknesses:

The manuscript lacks direct experimental evidence connecting lactylation to the proposed functional mechanism. While lactylation is detected in virions and overexpression systems, it remains unclear whether lactylation dynamically modulates polymerase function during infection. It is also unknown what proportion of PA undergoes lactylation at distinct infection stages, and whether lactylation specifically takes place within replication-competent asymmetric polymerase dimers. Importantly, the authors have not shown that mutation of K605/K609 abrogates the functional effects induced by lactate supplementation or ATAT1/SIRT1 overexpression in viral replication assays, which would help establish a direct connection between lactylation and viral replication. Therefore, although a correlation exists between these residues and viral replication, a direct mechanistic link between lactylation and the proposed replication model has not been firmly established. At minimum, the authors are encouraged to acknowledge these key limitations and moderate (tone down) their conclusions. For example, the observations are consistent with, but do not definitively prove, a functional role for PA lactylation in viral genome replication.

Major points:

(1) All experiments were performed using PR8, a laboratory-adapted H1N1 strain. Although this strain is commonly used for mechanistic investigations, evidence demonstrating conservation of this mechanism in currently circulating viral strains or other subtypes of influenza viruses would substantially support the conclusion that lactylation promotes viral pathogenicity. In the absence of such data, it remains unclear whether the observed findings apply broadly or are limited to the PR8 strain. In addition, the authors are encouraged to verify these phenotypes in additional cell lines.

(2) While the authors cite published work indicating that ATAT1 possesses lactyltransferase activity, it would be valuable to clarify whether ATAT1 directly catalyzes PA lactylation or functions indirectly as an intermediate. Similar considerations apply to SIRT1 regarding its potential role in removing lactylation from PA. Direct biochemical evidence, such as in vitro modification assays, would help strengthen the proposed mechanism.

(3) The available data cannot rule out the possibility that phenotypic changes induced by K605/K609 mutations stem from structural or charge alterations independent of lactylation. In fact, the results in Figure 4A and 4B support this alternative explanation: the K609R mutant shows reduced lactylation without obvious alterations in polymerase activity. This observation raises the question of whether the functional effects of these residues are driven by modified lactylation status or merely charge alterations.

(4) The proviral effect of ATAT1 appears largely independent of its enzymatic activity (Figure 2H), making it challenging to clarify whether ATAT1 functions by modifying PA to regulate polymerase activity and viral replication. Experiments examining SIRT1 on viral replication encounter similar interpretative limitations.

(5) Several siRNA knockdown results warrant careful interpretation. In Figure 3F and Figure 2E, the knockdown efficiency of SIRT1 and ATAT1 appears limited, especially at 12 and 24 h.p.i. Additional independent experiments with improved silencing efficiency or complementary approaches (such as CRISPR knockout) would help strengthen these observations.

Reviewer #2 (Public review):

This work reveals a role for PA lactylation in influenza virus replication, and the proposed involvement of ATAT1 and SIRT1 is certainly intriguing. These observations open up new avenues for understanding how host metabolism may influence viral infection. Nevertheless, a few mechanistic issues remain to be clarified. Notably, the direct evidence for ATAT1 and SIRT1 acting as the writer and eraser of this modification is still incomplete, and the functional relevance of the identified sites could be further substantiated.

Major Comments:

(1) The direct evidence supporting ATAT1 as a PA lactyltransferase and SIRT1 as a PA delactylase is still lacking. It remains possible that these two molecules affect PA lactylation indirectly. Therefore, in vitro lactylation/delactylation assays to clarify whether ATAT1 and SIRT1 act directly on PA should be performed.

(2) Although Figure 4A shows that K605A/K609A mutations reduce PA lactylation, the use of lactylation-mimetic mutants in functional complementation assays could further strengthen the conclusion.

(3) ATAT1 and SIRT1 are known to regulate multiple substrates. Therefore, whether the viral phenotypes resulting from ATAT1/SIRT1 manipulation truly operate via PA K605/K609 remains to be demonstrated. Complementation experiments would help address this issue.

(4) The mechanistic analysis currently focuses on polymerase dimerization. IP-MS assays comparing the host protein interaction profiles of PA WT versus K605/K609 mutants could reveal whether additional host factors are involved.

(5) The downstream consequences of PA lactylation have not been explored in the context of host antiviral immunity, particularly type I interferon (IFN-I) signaling. We would suggest examining the expression of IFN-β, ISG56, and other ISGs upon infection with WT versus PA K605/K609 mutant viruses.

Reviewer #1 (Public review):

Summary:

The authors ask whether self-supervised pretraining on related fungal genomes gives a useful prior for predicting gene expression in S. cerevisiae, where the compact ~12 Mb genome supplies too few independent windows to train a large supervised model from scratch. They pretrain a BERT-style masked DNA language model on a corpus of fungal genomes and fine-tune it to predict RNA-seq gene expression. They found a surprisingly (to me) large improvement in performance: 0.78 prediction Pearson R versus 0.67 for a randomly initialized model.

The manuscript also presents a new experimental resource: 3,053 RNA-seq data sets with perturbations using the YETI experimental platform to upregulate specific genes.

Strengths:

(1) Overall, the manuscript is well-written and is likely to be impactful.

(2) The protocol handles the train/test split of orthologous sequences well, which is nontrivial.

(3) The authors did a good job "steelman-ing" Shorkie_Random_Init: it received its own learning-rate sweep, and the authors tested two reduced-capacity from-scratch architectures to rule out some overparameterization issues.

(4) The public codebase is unusually well-organized.

Weaknesses:

I have a number of comments, none of which significantly impact the main findings.

Two analyses appear missing from the MPRA section: (1) Does self-supervised pre-training improve MPRA models such as DREAM-RNN? and (2) Is Shorkie better than Shorkie_Random_Init at the MPRA task? The language about "correlative, non-causal" associations makes me think the authors tried this and got poor results; it would be informative to include these as a supplementary negative result. (There is also (3): Does MPRA pre-training improve genomic models? But this is clearly out of scope for this paper.)

Reviewer #2 (Public review):

Summary:

Chao et al. study whether multi-species self-supervised pretraining learns sequence representations that can be transferred to improve downstream expression prediction in budding yeast. The rationale is that the budding yeast genome is relatively small and compact, which may not provide enough sequence variation for standard reference-genome-based supervised learning.

This paper has two stages. They first train U-Net-style DNA language models on collections of fungal genomes with increasing phylogenetic breadth using a BERT-style masked language modeling (MLM) objective. The model with the best sequence reconstruction (i.e., lowest perplexity) on held-out budding yeast sequences is called Shorkie LM. They then use Shorkie LM's weights to initialize Shorkie, a supervised model for predicting functional genomic tracks (RNA-seq, ChIP-exo, ChIP-MNase) in budding yeast. Compared with a randomly initialized model with the same architecture, Shorkie clearly performs better on held-out expression prediction and outperforms the randomly initialized model on all three variant effect benchmarks. This is good evidence that the pretraining is beneficial. For Shorkie LM and Shorkie, the authors also use interpretation methods to analyze motifs captured across a range of loci, and the results seem to be consistent with known yeast biology.

Overall, the experiments are well thought out and controlled, and most claims are supported with sufficient evidence. While the idea that pretraining can be beneficial for budding yeast has been reported previously (for scalar expression prediction) [1], this paper's exploration of optimal evolutionary scope and genomic language model pretraining in general still holds practical value for the field. The Shorkie model itself is also a useful resource and ranks first on many tasks in a recent public benchmark for fungal sequence-to-expression models [2]. I only have some minor concerns/suggestions.

Strengths:

(1) The authors put considerable effort into evaluating their modeling choices. For the pretraining corpora, they compare four phylogenetic scopes (a species, strain, order, kingdom). Each corpus is evaluated across multiple model architectures/capacities. Extra care is taken with homology filtering between training and held-out data. For supervised transfer, several candidate language models are carried forward to test whether their ranking by language model selection criterion (perplexity) predicts their ranking on the downstream task. In addition, the same-architecture randomly initialized baseline for Shorkie is itself optimized for learning rate, with additional randomly initialized CNN and U-Net models included as additional controls, giving some strong nulls to compare against.

(2) The experimental dataset generated in this study is also a valuable resource. Using the ministat array, the authors generated ~3,000 time-resolved RNA-seq profiles following transcriptional regulator inductions. Such data are important for understanding transient regulatory events and how they shape the transcriptome over time.

(3) Several figures include schematic panels that make the whole workflow easy to understand.

Weaknesses:

(1) As acknowledged by the authors, the current evolutionary "sweet spot" at 165 Saccharomycetales genomes is potentially confounded by factors like corpus size, annotation quality, and optimization difficulties. I agree that it would be hard to disentangle these factors, but a relatively simple control appears to be missing. Although unlikely, it is still possible that the "sweet spot" is driven partly by the amount of data rather than the phylogenetic scope. One simple control would be to sample 165 genomes from the broader fungal corpus and match the total number of training windows to the Saccharomycetales dataset.

(2) L148, "These results demonstrate that Shorkie LM captures conserved regulatory grammar." The evidence presented in this section is mainly about recovery of known fungal/yeast sequence motifs, which are more like words than grammar. The latter is usually understood as relationships between motifs such as their spacing, multiplicity, and arrangement. So I suggest the authors either tone down the claim or provide additional analyses that directly test this. One possibility would be to generate nucleotide dependency maps [3] for a handful of loci with well-characterized regulatory syntax.

(3) Figure 2E. The interpretation of t-SNE clusters might be confounded by the length of genomic elements. The five classes of elements shown in the plot have very different length distributions, but they are extracted and zero-padded to the same input length, and their embeddings are mean-pooled across the full padded sequence. As a result, the fraction of real sequence entering the mean embedding differs substantially across genomic element classes, which could contribute to observed separation independently of learned regulatory features.

(4) Lines 216-218, "transfer learning from pan-fungal self-supervised pretraining yields generalizable representations of exon-intron structure and regulatory grammar, substantially improving in expression prediction." Similar to point 2, I think this statement is somewhat stronger than what the current evidence supports. The results clearly show that pretraining improves downstream expression prediction, but it is less clear that this improvement can be specifically attributed to the transfer of regulatory grammar and gene structure, rather than motif representations or more general learned inductive biases acquired during pretraining. This is itself an interesting question. It might be possible to get at it by selectively reinitializing the convolution layers vs the transformer blocks while keeping the rest of the Shorkie LM weights, although this could still be hard to interpret if the relevant information is distributed across the model.

(5) The ISM for Figures 4 and 5 seems to correspond to the summed predicted coverage across all output bins (Methods, Equation 17). I was unclear about the intended goal here. For example, when mutating the ATG42 promoter in Figure 5, is the goal to quantify the predicted effect on ATG42 expression specifically? If so, should the ISM instead be computed by summing only the bins covering the target gene? Otherwise, predicted coverage from neighboring genes could also contribute to the ISM score and affect the comparison across induction time points.

References:

[1] Wang Y, Cai Z, Zeng Q, Gao Y, Ouyang J, Xu Y, et al. Genomic Touchstone: benchmarking genomic language models in the context of the central dogma. bioRxiv. Preprint posted online June 30, 2025. doi:10.1101/2025.06.25.661622

[2] Schneider T. ybench: a benchmark for fungal sequence-to-expression models. GitHub. Accessed August 18, 2026. https://github.com/Tom-Ellis-Lab/yeast-seq2expression-benchmark

[3] Tomaz da Silva P, Karollus A, Hingerl J, et al. Nucleotide dependency analysis of genomic language models detects functional elements. Nat Genet. 2025;57(10):2589-2602. doi:10.1038/s41588-025-02347-3

Reviewer #1 (Public review):

Summary:

In this study, the authors examine what happens when two facultative endosymbionts, Rickettsiella viridis and Regiella insecticola, are introduced into a novel aphid host, the Russian wheat aphid (Diuraphis noxia). They ask whether these introduced symbionts affect aphid performance, plant damage, alate production, dispersal, plant defense responses, and symbiont dynamics. The main result is that the two symbionts have contrasting effects: Rickettsiella tends to increase plant damage and reduce dispersal-related traits, whereas Regiella tends to reduce plant damage and aphid population growth, with less evidence for an effect on dispersal.

Strengths:

The manuscript presents successful establishment of stable transinfected populations of an agriculturally important aphid species, which is a substantial technical achievement in itself. I also appreciated that the authors examined the system across several experimental contexts, including different host plants, mixed cages at two temperatures, whole-plant assays, and a mesocosm dispersal experiment, rather than relying on a single laboratory setup. Taken together, these experiments provide a useful and reasonably convincing demonstration that novel symbiont associations can generate contrasting phenotypes in this system.

Weaknesses:

There are some major aspects of this paper that I thought could be strengthened. My main concern is that the manuscript feels broader than it is conceptually focused. A wide range of outcomes is measured, which gives the study breadth, but it also makes the central question harder to identify. As written, the paper reads more strongly as a proof-of-principle demonstration of ecologically relevant phenotypes than as a tightly framed test of a specific biological idea.

A second issue is that the biological basis of the reported phenotypes remains less developed than the phenotypic description itself. The authors make a genuine effort to address mechanism through JA, JA-Ile, SA, and metabolomic profiling, but these analyses only partially explain the main results. The negative result for the canonical defense markers is informative, yet it still leaves a substantial gap between the observed variation in plant damage and the processes responsible for it.

I also think some caution is needed in how the two symbionts are compared. The authors explain why some follow-up experiments were designed differently for Rickettsiella and Regiella, and that rationale is understandable. Still, because the downstream assays were not fully matched, the paper is strongest when each symbiont is interpreted on its own terms rather than as a strict comparison.

Overall, I would suggest softening the Significance Statement so that it more clearly reflects what is directly shown here, namely that introduced symbionts can alter plant damage and dispersal-related phenotypes under controlled conditions, rather than implying that the study directly tests management utility in agricultural settings.

Reviewer #2 (Public review):

Summary:

The authors generated two novel aphid-symbiont associations and examined the impact of these new symbiotic associations on plant-insect-symbiont interactions. The authors notably provide detailed phenotypic assessments of the insect hosts and host plants. They show that one introduced symbiont, Rickettsiella, increases aphid-induced damage to host plants, while the other, Regiella, ameliorates aphid damage. The authors suggest that such novel insect-symbiont pairings may be used as tools to mitigate crop damage in the future.

Strengths:

Although a few experiments seem to have limited sample sizes and limited statistical power, these are often complemented with highly replicated smaller-scale experiments. The combination of larger mesocosm and population-level experiments along with assessments of individual insects generally provides a comprehensive depiction of the effects of these symbionts on their hosts. The opposing impacts of Regiella and Rickettsiella infection on the aphid host plant are of broad interest. It is also surprising that the host plants did not exhibit strong differences in canonical defensive signalling, despite these differences.

Weaknesses:

One thing that I struggled a little with was the rapid spread of Regiella in the shared plant experiments. Possibly this could be attributed to an increased reproductive output (due to faster developmental time, and/or an increase in fecundity) or efficient horizontal transmission. However, the other experiments performed indicate a slight negative impact (Figure 4a) or no influence (Figure 4C, 4D, Figure S6) of Regiella infection on host fitness. Given these other results, it seems that Regiella must spread fairly efficiently between hosts, which comes as a surprise, and there are very few examples of horizontal transmission of Regiella like this in the literature. The manuscript would benefit from a clear and direct demonstration of horizontal transmission, rather than it being inferred indirectly. The similar spread observed in the Rickettsiella mixed cages is less surprising, because there are several examples where this has been demonstrated.

It is also a little surprising that mesocosm-dispersal experiments were not also conducted using Regiella-infected lines. At several points throughout the manuscript, the idea of using symbiont transfections to reduce plant harm is raised. I can understand that these experiments are likely time-, space-, and resource-intensive, but that seems like these would have been relevant experiments, especially in the context of controlling damage to plants.

Reviewer #3 (Public review):

Summary:

The authors were investigating the impact of introducing novel facultative bacterial endosymbionts into the pest aphid, Diuraphis noxia, to explore the possibility of using facultative symbionts as a crop protection tool. They successfully established the vertical transmission of both endosymbionts and performed a series of aphid performance and dispersal experiments together with measurement of aphid feeding on host plant health, growth, and metabolism. While most of the experiments revealed no effect of the endosymbionts, some significant treatment effects were found, showing that Rickettsiella reduced aphid dispersal, and Regiella reduced aphid population growth and feeding damage.

Strengths:

The team worked with two novel facultative symbionts (Rickettsiella viridis and Regiella insecticola) that they were able to successfully establish in D. noxia. The data were collected and analyzed using solid, well-described methodology.

Weaknesses:

While interpretation of the data is reasonable, the few experiments which revealed significant treatment effects rest on relatively small sample sizes.

Measuring symbiont density is difficult. The authors use quantitative PCR to measure the "density" of endosymbionts relative to a host gene. This is a standard approach in the field; however, recent work has shown that endosymbionts like the aphid primary endosymbiont, Buchnera, are variably polyploid [1]; further the aphid cells that house the symbionts are also highly polyploid and variable in their ploidy [2]. It is important to understand that what is being measured when using qPCR is DNA copy number and not quantification of the number of symbiont cells. Alternative approaches to measuring symbiont density include flow cytometry [3], and SymbiQuant [4], a machine vision tool that can quantitatively characterize symbiont populations from DAPI-stained confocal images. These alternate approaches also have their limitations. Currently, there is no perfect approach to measuring symbiont density, which remains an important measure in experiments such as these. Put simply, it is important for a reader to be aware of the limitations of each approach and interpret data accordingly.

[1] Komaki, K., and H. Ishikawa. 2000. Genomic copy number of intracellular bacterial symbionts of aphids varies in response to developmental stage and morph of their host. Insect Biochemistry and Molecular Biology 30:253-258.<br /> [2] Nozaki, T., and S. Shigenobu. 2022. Ploidy dynamics in aphid host cells harboring bacterial symbionts. Scientific Reports 12:9111.<br /> [3] Simonet, P., G. Duport, K. Gaget, M. Weiss-Gayet, S. Colella, G. Febvay, H. Charles, J. Viñuelas, A. Heddi, and F. Calevro. 2016. Direct flow cytometry measurements reveal a fine-tuning of symbiotic cell dynamics according to the host developmental needs in aphid symbiosis. Scientific Reports 6:19967.<br /> [4] James, E. B., X. Pan, O. Schwartz, and A. C. C. Wilson. 2022. SymbiQuant: A machine learning object detection tool for polyploid independent estimates of endosymbiont population size. Frontiers in Microbiology 13:816608.

Impact and Significance:

Food security and production, and pest control are major challenges facing the human population. This work contributes knowledge that will benefit the development of alternate pest control strategies in agriculture.

The original DNA sequence in the image has a C that should be a G on the right strand, and the sequence given in the image description has a different pattern, is 2 letters longer, and doesn't line up with the mRNA sequence given in the image description. Also the tRNA in the image has both Ts and Us??

Reviewer #1 (Public review):

Summary:

This study examines how type I IFN and IFN-γ exert opposing effects on macrophage responses relevant to TB. Using bone marrow-derived macrophages from genetically susceptible B6.Sst1S mice, the authors describe a persistent pathological activation state induced by TNF and characterized by sustained type I IFN signalling, oxidative stress and lipid peroxidation. They show that IFN-γ priming limits several features of this state and propose altered iron metabolism as one mechanism underlying this protective effect. They then use a computational cell-state approach to identify pharmacological interventions that may mimic aspects of IFN-γ activity. In particular, CDK4/6 inhibition with trilaciclib and activation of retinoic acid signalling with ATRA appear to act through complementary mechanisms and, when combined at low concentrations, improve control of intracellular M. tuberculosis.

Strengths:

A major strength of the study is the combination of several complementary approaches, including genetic susceptibility, cytokine signalling, oxidative stress, iron and lipid metabolism, transcriptomics, computational modelling and pharmacological perturbation. Together, these experiments build a coherent model of macrophage dysfunction.

The evidence that type I IFN signalling contributes to maintenance of the pathological state is particularly convincing within the TNF stimulation model. Blocking the type I IFN receptor after the phenotype has developed restores responsiveness to IFN-γ and prevents further accumulation of lipid-peroxidation products. The authors also provide evidence that persistence does not simply reflect continued TNF signalling, since blockade of the TNF receptor after 24 h does not abolish the elevated lipid-peroxidation phenotype. Another strength is that the computational analysis generates experimentally testable predictions, and two mechanistically distinct interventions identified by this approach are subsequently validated in macrophages.

Weaknesses:

There are, however, several limitations that affect the strength and scope of the conclusions.

(1) First, the use of the terms "persistent" and especially "self-sustaining" would be better supported by a more complete time-course analysis.

(2) Second, the proposed central role of ferritin-mediated iron sequestration in the protective effect of IFN-γ is not yet demonstrated directly. The data clearly link IFN-γ treatment to ferritin induction and reduced labile iron, but the causal contribution of ferritin itself remains to be established.

(3) Third, an important limitation is the connection between the mechanistic model developed with TNF stimulation and actual M. tuberculosis infection. Most of the mechanistic analysis, including type I IFN super-induction, lipid peroxidation, ferritin induction, labile iron and HIF1α regulation, is performed in TNF-stimulated macrophages. The infection experiments show that IFN-γ improves bacterial control and that low-dose trilaciclib plus ATRA reduces intracellular bacterial burden, but they do not establish that M. tuberculosis infection induces the same pathological circuit, or that these interventions improve bacterial control by acting through that circuit. The study therefore defines a convincing TNF-driven macrophage phenotype with relevance to bacterial control, but the broader conclusion that this mechanism underlies IFN-dependent susceptibility to TB remains only partially supported.

(4) Finally, the therapeutic implications go beyond the experimental evidence currently presented, since all of the pharmacological experiments are performed in cultured macrophages and there is no in vivo validation.

Conclusion:

Overall, this study proposes an interesting framework for understanding how inflammatory activation may become maladaptive in susceptible macrophages and how IFN-γ may combine antimicrobial activation with protection from oxidative damage. The convergence between IFN-γ, iron metabolism, lipid peroxidation and the pharmacological perturbations identified computationally is a clear strength. However, the causal role of ferritin, the operation of the proposed circuit during M. tuberculosis infection, and the in vivo relevance of the pharmacological strategy remain to be established. These limitations leave the mechanistic and translational evidence incomplete, while the study itself remains potentially important.

Reviewer #2 (Public review):

Summary:

The authors have carried out extensive transcriptomic, phenotypic and modelling-based analyses to provide novel insights into the interaction of the type I and II interferon programs in the determination of macrophage activation status and resistance to Mtb infection and infection-mediated damage. They demonstrate how an antagonistic effect between the two programs goes beyond classical downstream immune signalling pathways to lipid peroxidation maintained in a sustained autocrine manner and generation of a persistent pathological activation state (pPAS). Based on these analyses, the authors propose a therapeutic strategy of boosting specific pathways that increase oxidative stress resilience to reduce inflammatory pathology without suppressing host defenses for bacterial control and resisting pPAS. The conceptual framework may prove applicable to interferonopathies and to other bacterial and viral infections, though this remains to be tested.

Strengths:

(1) The study uses macrophages from a disease-relevant genetic murine model in which the sst1 locus drives the formation of necrotic pulmonary granulomas resembling human TB lesions- pathology not seen in standard C57BL/6 mice. This provides a genetically defined comparison between susceptible and resistant macrophages on an otherwise identical background, allowing the authors to attribute differences in activation state to a single locus rather than to strain-level variation.

(2) The experimental design isolates the phenomenon of interest: the TNF withdrawal and restimulation scheme allows the authors to establish that the aberrant activation state persists after removal of the initiating stimulus, rather than simply reflecting ongoing stimulation. The timed IFNAR blockade at 2, 12 and 24 h similarly separates initiation of the state from its maintenance.

(3) Lipid peroxidation is assessed through two orthogonal readouts: 4-HNE immunostaining for accumulated adducts and linoleamide alkyne click chemistry for ongoing synthesis. These, coupled with ROS and labile iron pool measurements, isotype antibody controls, parallel B6 and B6.Sst1S comparisons, and an anti-TNFR control, help in establishing that the phenotype is independent of continued TNF signalling. The convergence of these independent measures gives confidence in the peroxidation phenotype itself.

(4) The cSTAR analysis is applied here using regression rather than classification, generating a continuous DPD_TB score that correlates with measured Mtb fold change and thus provides a quantitative transcriptomic metric of macrophage priming state. Critically, the pathway predictions arising from this analysis (CDK4/6 inhibition and RAR activation) were tested and confirmed experimentally. The inferred network topology further predicted synergy between these two interventions, which bore out experimentally as an approximately ten-fold reduction in the effective dose of each agent in controlling Mtb during infection.

Weaknesses:

(1) Figure 2C is difficult to interpret as presented. The row labels ("No TNF"/"TNF") use different terminology from the corresponding conditions in panel A ("TNF withdrawal"/"TNF restimulated"), and "TNF" appears on both axes referring to different phases of the experiment; no timepoint is given on the panel itself, unlike neighbouring panels. Harmonising the labels with panel A and stating the harvest timepoint would help the reader. More substantively, the remaining lipid peroxidation readouts in this figure (panels D-G) are all at early timepoints of TNF stimulation (2-24 h) rather than during withdrawal, which limits what they can say about sustained autocrine signalling. Extending these assays to the later timepoints used in Figure 1 would considerably strengthen the claim that IFN-I maintains, rather than only initiates, the pathological state. The same applies to Figure 2G, where the contribution of itaconate to 4-HNE accumulation over time is not yet resolved.

(2) Several of the pathways implicated here are reported to behave differently between murine and human macrophages, and between macrophage subsets (alveolar versus monocyte-derived macrophages), during Mtb infection. This does not diminish the findings in this model, but it does bear on how broadly they can be generalised.

a) Type I interferon responses differ by species and by macrophage subset across multiple reports. Since the proposed model depends on autocrine IFN-I signalling reaching a threshold sufficient to sustain the pathological state, these differences in IFN-I output are worth keeping in mind when interpreting the wider significance of the findings.

b) Similarly, itaconate production in murine BMDMs is 20-fold higher than in LPS-activated human monocyte-derived macrophages and 50-fold higher than in LPS-activated alveolar macrophage-like cells, and Mtb infection of these human macrophages very weakly induces ACOD1 with almost no detectable itaconate (PMID 41797714). This is relevant to the Acod1/4-OI arm of the mechanism.

c) In a cross-species comparison of Mtb-infected macrophages, cholesterol homeostasis genes (including HMGCS1, IDI1, LSS) were significantly upregulated in human alveolar macrophages but downregulated in subcutaneous BCG-exposed murine alveolar macrophages (PMID 41208107)- the opposite direction to the lipid biosynthesis suppression treated here as a defining pPAS feature. The same group reports that murine AMs lack c-Maf and IL-10 whereas murine BMDMs express both (PMID 40073087), indicating that the autocrine anti-inflammatory brake on IFN-I responses is itself subset-dependent.

d) Finally, the cSTAR network predictions were inferred from human THP-1 perturbation data, but tested only in murine BMDMs. Establishing how this circuit operates in human macrophages, and during Mtb infection rather than TNF stimulation alone, would be a valuable extension of the work.

(3) The causal relationships linking IFN-I, lipid peroxidation, ROS and loss of IFNγ responsiveness could be drawn together more clearly. These elements are each established, but the connections between them are not always demonstrated directly. IFN-I appears to promote peroxidation through Acod1/itaconate and suppression of lipid biosynthesis rather than through iron, since neither IFNβ nor IFNAR blockade alters the labile iron pool. This would suggest two separable inputs to 4-HNE rather than a single pathway. This raises a further question about the persistent state itself: the labile iron pool rise appears to be TNF-driven, yet all labile iron measurements are made at 24 h in the continued presence of TNF and none under the withdrawal condition, so it is unclear whether elevated catalytic iron is sustained once the initiating stimulus is removed. Similarly, while IFNAR blockade reduces peroxidation, the reciprocal arm is not tested. An antioxidant or iron chelator could be used to ask whether peroxidation in turn drives Ifnb1 super-induction. In the absence of this information, the proposed feedback loop remains partly inferred. It would considerably strengthen the manuscript if the authors could clarify, through additional experiments or in the text, how the labile iron pool and lipid peroxidation relate to one another and what sustains each of them after TNF withdrawal.

(4) Reading across the manuscript, the labile iron pool emerges as the variable most consistently associated with the phenotype. Every protective intervention tested converges on it. By contrast, the alternative candidate mechanisms do not track with outcome. Lipid biosynthesis genes are suppressed by IFNγ yet induced by both trilaciclib and ATRA, all three of which are protective. GPX4 is unchanged under IFNγ and trilaciclib. The Acod1/itaconate axis cannot account for it since IFNγ priming blocks 4-HNE accumulation induced by exogenous itaconate. Yet, a direct causal role for iron is never tested. Additionally, IFNβ induces 4-HNE with the labile iron pool entirely unchanged, indicating at least one route to lipid peroxidation that bypasses catalytic iron. Focusing on iron handling would make the manuscript's message more coherent and its therapeutic argument more compelling.

Reviewer #3 (Public review):

Summary:

Araveti et al. demonstrate that Type I Interferon (IFN-I) and Interferon-gamma (IFN-γ) play opposing roles in regulating lipid peroxidation and host resistance during Mycobacterium tuberculosis (Mtb) infection. While both the two pathways drive inflammation, they differ fundamentally in cell protection. IFN-I signaling triggers a destructive, self-amplifying cycle catalysing the generation of reactive oxygen species (ROS) and lipid peroxidation, which ultimately impairs the host's ability to clear Mtb. Conversely, the authors demonstrate that IFN-γ couples antimicrobial activation with cytoprotection. It primes macrophages to fight the mycobacteria while simultaneously shielding them from oxidative stress. It achieves this by sequestering iron, which successfully prevents ROS from converting into damaging lipid peroxidation products.

Strengths:

Ultimately, this study highlights a critical biological distinction: IFN-γ safely balances inflammatory activation with cellular defense, whereas IFN-I promotes uncontrolled pathological damage. This divergent coupling of inflammation and cytoprotection carries major consequences for disease progression and host survival.

Weaknesses:

This study demonstrates all the findings in specific mouse strains. How these translate in human macrophages is not well characterised, thus raising the issue of its overall impact in tuberculosis disease.

Reviewer #1 (Public review):

Summary:

The control of bovine tuberculosis in managed populations such as Ireland and Great Britain is unusual in that demonstrably sick animals are rarely, if ever, seen in herds. Control is therefore focused on the identification and removal of animals that test positive to the tuberculin skin test (the legal definition of infection). Despite over a century of study, the relationship between tuberculin test status, infection and most importantly infectiousness is still poorly quantified. Different formats of the tuberculin skin test are acknowledged to have both poor sensitivity and compromised specificity, although the characteristics of these tests are likely to vary considerably between contexts due to both biological variation and discretion in measurements by testers. There is an urgent need for new, more reliable and cheaper diagnostics to address the failures of existing control programs and to enable control in emerging markets that do not currently control the disease.

Strengths:

A key strength of this study is the use of samples from both naturally infected and experimentally infected animals. This data set is used to perform a careful and exhaustive evaluation of the extent to which patterns of transcriptomic expression can be used to classify between disease free animals and those infected with bovine tuberculosis.

The experimentally infected animal samples provide evidence that expression patterns of infected animals vary with respect to the time from infection. The authors highlight that this suggests transcriptomic markers may be able to detect infection earlier than tuberculin and IGRA tests that target cell-mediated immune responses. However, these methods could potentially provide a valuable new tool for quantifying the role of individual variation and progression for a disease where the individual life-history is still frustratingly mysterious.

Weaknesses:

However, the high levels of individual variation - and in particular differences in patterns of expression between naturally and experimentally infected animals do raise questions about how diagnostic tests developed from these tools would be used in practice. In particular, while many of the models considered achieved high sensitivity - estimated specificity is consistently lower than current diagnostic tests and considerably lower than that necessary for screening tests given the frequency of testing carried out as part of statutory control programs.

Expanding the number of samples may help to address these issues, but I would have liked to see some discussion of the extent to which the level of biological variation observed in this study may limit the precision of diagnostic tests developed using these tools. Given the likely characteristics of tests based on these methods, I would be interested to hear how the authors think they could fit within current statutory programs, either as supplementary or replacement tests?

Reviewer #2 (Public review):

Summary:

This study evaluates whether peripheral blood transcriptomic profiles can be used to classify cattle infected with Mycobacterium bovis using a range of machine-learning approaches. By integrating RNA-seq datasets from naturally and experimentally infected animals, the authors develop and test predictive models capable of distinguishing infected from uninfected cattle and assess their ability to differentiate bovine tuberculosis from other infectious diseases. The study addresses an important challenge in bovine tuberculosis control and presents evidence that host transcriptional signatures may have utility as an adjunct diagnostic approach.

Strengths:

- The study combines data from multiple independent cohorts, including both naturally and experimentally infected cattle, which increases the biological relevance of the findings.

- The analytical workflow is comprehensive, scientifically sound and clearly described. Multiple machine-learning approaches are evaluated and compared rather than relying on a single modelling strategy.

- The inclusion of a held-out test set, especially because such data is limited, provides a useful assessment of model performance beyond cross-validation alone.<br /> - Thorough evaluation against datasets from cattle infected with MAP, BoHV-1 and BRSV is a valuable addition and provides useful information regarding the specificity of the identified transcriptional signatures.

- The authors acknowledge important limitations, including batch effects and the need for additional validation.

- All underlying data and code are made publicly available

Weaknesses:

- My main concern relates to generalisability. Although a separate testing dataset was used, the training and testing datasets were generated through random partitioning of samples from the same underlying studies. As a result, classifier performance in a completely independent external cohort remains unclear. Discussion of this limitation, and whether alternative validation strategies such as leave-one-study-out analyses were considered, would strengthen the manuscript.

- The authors identify substantial study-specific batch effects following dataset integration and appropriately account for these in the modelling framework. However, given the magnitude of the reported batch structure, additional discussion regarding the potential influence of residual between-study variation on classifier performance would be helpful.

- The manuscript is framed in the context of global bovine tuberculosis control, yet the practical implementation of a transcriptomic diagnostic approach is not discussed in great detail. Since bovine tuberculosis remains a significant challenge in many low- and middle-income settings, further consideration of the feasibility, cost, infrastructure requirements, and potential translation of these signatures into more deployable diagnostic platforms would improve the broader relevance of the study.

- The datasets used for classifier development are derived primarily from Ireland, the UK and the United States. It would be useful to discuss whether differences in circulating M. bovis lineages, cattle populations, management systems, or co-infection pressures could influence host transcriptional responses and therefore the performance of the proposed classifiers in other epidemiological settings. This ties to the previous comment, since epidemiological settings in LMIC countries with a high burden of M.bovis disease would be vastly different from where the data was sourced.

Reviewer #3 (Public review):

Summary:

This is an excellent piece of work which sheds greater light on the responses of cattle to both experimental and natural infection in cattle with Mycobacterium bovis infection, using data from different experimental and field groups.

Strengths:

The work is based on robust analysis of a range of highly relevant experimental and field sample sets, using transcriptomic approaches. It provides insight into pathogenesis and disease responses, as well as some evidence regarding potential future diagnostic advances.

Weaknesses:

I have some simple, but important comments on how the work is discussed. (Consequently, most comments focus on the discussion section). In particular, I suggest that the authors have confused or conflated the great progress that they have made in improving the understanding of the responses to M. bovis infection with an improved ability to practically improve the diagnosis of the infection in the field. Minor differences in specificity and sensitivity - and predictive values - of tests or assays being used can have profound effects in different prevalence settings on the farm, and I don't feel that this understanding is adequately reflected in the discussion in particular. In this respect, the authors really should, in my view, focus not on the outstanding results that come in or from their model fitting approaches, to focus on their model testing results in relation to extrapolated meaning / external validity. The text uses words like 'robust' and 'highly accurate' which are meaningless in the context of test interpretation in the field.

I get their enthusiasm, based on really interesting findings in relation to disease progression and immune and inflammatory responses, but these indistinct claims rather devalue the quality of the rest of their work in my view.

One great challenge in work of this nature, using natural cases from farms, is that there is no gold standard for identifying the cases that current diagnostic approaches miss and which they hope their new approaches can help with. This is not discussed or mentioned in their enthusiasm for what they have achieved. Their field datasets are based on the current, insensitively detected cases. It misses the 'occult' cases that are present but undiagnosed.

Reviewer #2 (Public review):

Summary:

The authors wanted to achieve a detailed ultrastructural reconstruction of the gustatory sensory organs in the Drosophila pharynx. Using serial EM and the associated bioinformatics tools they have achieved their goal.

Strengths:

Given the dataset, finding presented are solid and will be an important work of reference for the future.

Comments on revised version.

The authors have well responded to my previous comments and added text and figure material.