Reviewer #1 (Public review):

This work derives a general theory of optimal gain modulation in neural populations. It demonstrates that population homeostasis is a consequence of optimal modulation for information maximization with noisy neurons. The developed theory is then applied to the distributed distributional code (DDC) model of the primary visual cortex to demonstrate that homeostatic DDCs can account for stimulus-specific adaptation.

What I consider to be the most important contribution of this work is the unification of efficient information transmission in neural populations with population homeostasis. The former is an established theoretical framework, and the latter is a well-known empirical phenomenon - the relationship between them has never been fully clarified. I consider this work to be an interesting and relevant step in that direction.

The theory proposed in the paper is rigorous and the analysis is thorough. The manuscript begins with a general mathematical setting to identify normative solutions to the problem of information maximization. It then gradually builds towards questions about approximate solutions, neural implementation and plausibility of these solutions, applications of the theory to specific models of neural computation (DDC), and finally comparisons to experimental data in V1. Such a connection of different levels of abstraction is an obvious strength of this work.

Overall I find this contribution interesting and assess it positively. At the same time, I have three major points of criticism, which I believe the authors should address. I list them below, followed by a number of more specific comments and feedback.

Major comments:

(1) Interpretation of key results and relationship between different parts of the manuscript. The manuscript begins with an information-transmission ansatz which is described as "independent of the computational goal" (e.g. p. 17). While information theory indeed is not concerned with what quantity is being encoded (e.g. whether it is sensory periphery or hippocampus), the goal of the studied system is to *transmit* the largest amount of bits about the input in the presence of noise. In my view, this does not make the proposed framework "independent of the computational goal". Furthermore, the derived theory is then applied to a DDC model which proposes a very specific solution to inference problems. The relationship between information transmission and inference is deep and nuanced. Because the writing is very dense, it is quite hard to understand how the information transmission framework developed in the first part applies to the inference problem. How does the neural coding diagram in Figure 3 map onto the inference diagram in Figure 10? How does the problem of information transmission under constraints from the first part of the manuscript become an inference problem with DDCs? I am certain that authors have good answers to these questions - but they should be explained much better.

(2) Clarity of writing for an interdisciplinary audience. I do not believe that in its current form, the manuscript is accessible to a broader, interdisciplinary audience such as eLife readers. The writing is very dense and technical, which I believe unnecessarily obscures the key results of this study.

(3) Positioning within the context of the field and relationship to prior work. While the proposed theory is interesting and timely, the manuscript omits multiple closely related results which in my view should be discussed in relationship to the current work. In particular:

A number of recent studies propose normative criteria for gain modulation in populations:

- Duong, L., Simoncelli, E., Chklovskii, D. and Lipshutz, D., 2024. Adaptive whitening with fast gain modulation and slow synaptic plasticity. Advances in Neural Information Processing Systems<br /> - Tring, E., Dipoppa, M. and Ringach, D.L., 2023. A power law describes the magnitude of adaptation in neural populations of primary visual cortex. Nature Communications, 14(1), p.8366.<br /> - Młynarski, W. and Tkačik, G., 2022. Efficient coding theory of dynamic attentional modulation. PLoS Biology<br /> - Haimerl, C., Ruff, D.A., Cohen, M.R., Savin, C. and Simoncelli, E.P., 2023. Targeted V1 co-modulation supports task-adaptive sensory decisions. Nature Communications<br /> - The Ganguli and Simoncelli framework has been extended to a multivariate case and analyzed for a generalized class of error measures:<br /> - Yerxa, T.E., Kee, E., DeWeese, M.R. and Cooper, E.A., 2020. Efficient sensory coding of multidimensional stimuli. PLoS Computational Biology<br /> - Wang, Z., Stocker, A.A. and Lee, D.D., 2016. Efficient neural codes that minimize LP reconstruction error. Neural Computation, 28(12),

More detailed comments and feedback:

(1) I believe that this work offers the possibility to address an important question about novelty responses in the cortex (e.g. Homann et al, 2021 PNAS). Are they encoding novelty per-se, or are they inefficient responses of a not-yet-adapted population? Perhaps it's worth speculating about.

(2) Clustering in populations - typically in efficient coding studies, tuning curve distributions are a consequence of input statistics, constraints, and optimality criteria. Here the authors introduce randomly perturbed curves for each cluster - how to interpret that in light of the efficient coding theory? This links to a more general aspect of this work - it does not specify how to find optimal tuning curves, just how to modulate them (already addressed in the discussion).

(3) Figure 8 - where do Hz come from as physical units? As I understand there are no physical units in simulations.

(4) Inference with DDCs in changing environments. To perform efficient inference in a dynamically changing environment (as considered here), an ideal observer needs some form of posterior-prior updating. Where does that enter here?

(5) Page 6 - "We did this in such a way that, for all ν, the correlation matrices, ρ(ν), were derived from covariance matrices with a 1/n power-law eigenspectrum (i.e., the ranked eigenvalues of the covariance matrix fall off inversely with their rank), in line with the findings of Stringer et al. (2019) in the primary visual cortex." This is a very specific assumption, taken from a study of a specific brain region - how does it relate to the generality of the approach?

Reviewer #1 (Public review):

Summary:

In this study, Bu et al examined the dynamics of TRPV4 channel in cell overcrowding in carcinoma conditions. They investigated how cell crowding (or high cell confluence) triggers a mechano-transduction pathway involving TRPV4 channels in high-grade ductal carcinoma in situ (DCIS) cells that leads to large cell volume reduction (or cell volume plasticity) and pro-invasive phenotype.

In vitro, this pathway is highly selective for highly malignant invasive cell lines derived from a normal breast epithelial cell line (MCF10CA) compared to the parent cell line, but not present in another triple-negative invasive breast epithelial cell line (MDA-MB-231). The authors convincingly showed that enhanced TRPV4 plasmamembrane localization correlates with high-grade DCIS cells in patient tissue samples. Specifically in invasive MCF10DCIS.com cells they showed that overcrowding or over-confluence leads to a decrease in cell volume and intracellular calcium levels. This condition also triggers the trafficking of TRPV4 channels from intracellular stores (nucleus and potentially endosomes), to the plasma membrane (PM). When these over-confluent cells are incubated with a TRPV4 activator, there is an acute and substantial influx of calcium, attesting the fact that there are high number of TRPV4 channels present on the PM. Long-term incubation of these over-confluent cells with the TRPV4 activator results in the internalization of the PM-localized TRPV4 channels.

In contrast, cells plated at lower confluence primarily have TRPV4 channels localized in the nucleus and cytosol. Long-term incubation of these cells at lower confluence with a TRPV4 inhibitor leads to the relocation of TRPV4 channels to the plasma membrane from intracellular stores and a subsequent reduction in cell volume. Similarly, incubation of these cells at low confluence with PEG 3000 (a hyperosmotic agent) promotes the trafficking of TRPV4 channels from intracellular stores to the plasma membrane.

Strengths:

The study is elegantly designed and the findings are novel. Their findings on this mechano-transduction pathway involving TRPV4 channels, calcium homeostasis, cell volume plasticity, motility and invasiveness will have a great impact in the cancer field and potentially applicable to other fields as well. Experiments are well-planned and executed, and the data is convincing. Authors investigated TRVP4 dynamics using multiple different strategies- overcrowding, hyperosmotic stress, pharmacological and genetic means, and showed a good correlation between different phenomena.

Reviewer #1 (Public review):

Summary:

The study by Jena et al. addresses important questions on the fundamental mechanisms of genetic adaptation, specifically, does adaptation proceed via changes of copy number (gene duplication and amplification "GDA") or by point mutation. While this question has been worked on (for example by Tomanek and Guet) the authors add several important aspects relating to resistance against antibiotics and they clarify the ability of Lon protease to reduce duplication formation (previous work was more indirect).

A key finding Jena et al. present is that point mutations after significant competition displace GDA. A second one is that alternative GDA constantly arise and displace each other (see work on GDA-2 in Figure 3). Finally, the authors found epistasis between resistance allele that was contingent on lon. Together this shows an intricate interplay of lon proteolysis for the evolution and maintenance of antibiotic resistance by gene duplication.

Strengths:

The study has several important strengths: (i) the work on GDA stability and competition of GDA with point mutations is a very promising area of research and the authors contribute new aspects to it, (ii) rigorous experimentation, (iii) very clearly written introduction and discussion sections. To me, the best part of the data is that deletion of lon stimulates GDA, which has not been shown with such clarity until now.

Weaknesses:

Previously raised minor weaknesses and technical questions have been adequately resolved in the revised manuscript. As the experiments and their results are described in great detail the interested reader needs stamina. The details will, however, be informative to the specialist.

Reviewer #1 (Public review):

Summary:

The authors conducted a human neuroimaging study investigating the role of context in the representation of fear associations when the contingencies between a conditioned stimulus and shock unconditioned stimulus switch between contexts. The novelty of the analysis centered on neural pattern similarity to derive a measure of context and cue stability and generalization across different regions of the brain. Given the complexity and nuance of the results, it is kind of difficult to provide a concise summary. But during fear and reversal, there was cue generalization (between current CS+ cues) in the canonical fear network, and "item stability" for cues that changed their association with the shock in the IFG and precuneus. Reinstatement was quantified as pattern similarity for items or sets of cues from the earlier phases to the test phases, and they found different patterns in the IFG and dmPFC. A similar analytical strategy was applied to contexts.

Strengths:

Overall, I found this to be a novel use of MVPA to study the role of context in the reversal/extinction of human fear conditioning that yielded interesting results. The paper was overall well-written, with a strong introduction and fairly detailed methods and results. The lack of any univariate contrast results from the test phases was used as motivation for the neural pattern similarity approach, which I appreciated as a reader.

Weaknesses:

This is quite a complicated protocol and analysis plan. The authors did a decent job explaining it, given the complexity of the approach and the dense results. But it did take reading it a couple of times to start to understand it. I'm not sure if there is a simpler way to describe the approach though. Just an observation. But perhaps there is a better way to explain the density of the different comparisons between the multiple cues and contexts. It can be difficult to totally avoid jargon in a complex scientific article, but the paper is very jargon-y.

Here are a few more comments and stray observations, in no particular order of importance.

(1) I had a difficult time unpacking lines 419-420: "item stability represents the similarity of the neural representation of an item to other representations of this same item."

(2) The authors use the phrase "representational geometry" several times in the paper without clearly defining what they mean by this.

(3) The abstract is quite dense and will likely be challenging to decipher for those without a specialized knowledge of both the topic (fear conditioning) and the analytical approach. For instance, the goal of the study is clearly articulated in the first few sentences, but then suddenly jumps to a sentence stating "our data show that contingency changes during reversal induce memory traces with distinct representational geometries characterized by stable activity patterns across repetitions..." this would be challenging for a reader to grok without having a clear understanding of the complex analytical approach used in the paper.

(4) Minor: I believe it is STM200 not the STM2000.

(5) Line 146: "...could be particularly fruitful as a means to study the influence of fear reversal or extinction on context representations, which have never been analyzed in previous fear and extinction learning studies." I direct the authors to Hennings et al., 2020, Contextual reinstatement promotes extinction generalization in healthy adults but not PTSD, as an example of using MVPA to decipher reinstatement of the extinction context during test.

(6) This is a methodological/conceptual point, but it appears from Figure 1 that the shock occurs 2.5 seconds after the CS (and context) goes off the screen. This would seem to be more like a trace conditioning procedure than a standard delay fear conditioning procedure. This could be a trivial point, but there have been numerous studies over the last several decades comparing differences between these two forms of fear acquisition, both behaviorally and neurally, including differences in how trace vs delay conditioning is extinguished.

(7) In Figure 4, it would help to see the individual data points derived from the model used to test significance between the different conditions (reinstatement between Acq, reversal, and test-new).

Reviewer #1 (Public review):

Summary:

The authors seek to understand the role of different ratios of excitatory to inhibitory (EI) neurons, which in experimental studies of the cerebral cortex have been shown to range from 4 to 9. They do this through a simulation study of sparsely connected networks of excitatory and inhibitory neurons.

Their main finding is that the participation ratio and decoding accuracy increase as the E/I ratio decreases. This suggests higher computational complexity.

This is the start of an interesting computational study. However, there is no analysis to explain the numerical results, although there is a long literature of reduced models for randomly connected neural networks which could potentially be applied here. (For example, it seems that the authors could derive a mean field expression for the expected firing rate and variance - hence CV - which could be used to target points in parameter space (vs. repeated simulation in Figures 1,2).) The paper would be stronger and more impactful if this was attempted.

Strengths:

Some issues I appreciated are:

(1) The use of a publicly available simulator (Brian), which helps reproducibility. I would also request that the authors supply submission or configuration scripts (if applicable, I don't know Brian).

(2) A thorough exploration of the parameter space of interest (shown in Figure 2).

(3) A good motivation for the underlying question: other things being equal, how does the E/I ratio impact computational capacity?

Weaknesses:

(1) Lack of mathematical analysis of the network model

Major issues I recommend that the authors address (not sure whether these are "weaknesses"):

(1) In "Coding capacity in different layers of visual cortex" the authors measure PR values from layers 2/3 and 4 in VISp and find that layer 2/3 has a higher PR than layer 4.

But in Dahmen et al. 2020 (https://doi.org/10.1101/2020.11.02.365072 ), the opposite was found (see Figure 2d of Dahmen et al.): layer 2 had a lower PR than layer 4. Can the authors explain how that difference might arise? i.e. were they analyzing the same data sets? If so why the different results? Could it have to do with the way the authors subsample for the E/I ratio?

From the Methods of that paper: "Visual stimuli were generated using scripts based on PsychoPy and followed one of two stimulus sequences ("brain observatory 1.1" and<br /> "functional connectivity"). We focused on spontaneous neural activity registered while the animal was not performing any task. In each session, the spontaneous activity condition lasted 30 minutes while the animal was in front of a screen of mean grey luminance. We, therefore, analyzed 26 of the original 58 sessions corresponding to the "functional connectivity" subdataset as they included such a period of spontaneous activity. " This suggests to me they may have analyzed recordings with the other stimulus sequence; however, the hypothesis that E/I ratio should modulate dimensionality would not seem to "care" about which stimulus sequence was used.

(2) In Discussion (pg. 20, line 383): "They showed that brain regions closer to sensory input, like the thalamus, have higher dimensionality than those further away, such as<br /> the visual cortex. " How is this consistent with the hypothesis that "higher dimensionality might be linked to more complex cognitive functions"?

(3) What is the probability of connection between different populations? e.g. the probability of there being a synaptic connection between any two E cells? I could not find a statement about this. It should be included in the Methods.

(4) pg. 27, line 540: "Synchronicity within the network" For each cell pair, the authors use the maximum cross-correlation over time lag. I don't think I have seen this before. Can the authors explain why they use this measurement, vs (a) integrated cross-correlation or (b) cross-correlation at some time scale? Also, it seems like this fails to account for neuron pairs for which there is a strong inhibitory correlation.

(5) "When stimulated, a time-varying input, μext(t), is applied to 2,000 randomly selected excitatory neurons. " I would guess that computing PR would depend on the overlap of the 500 neurons analyzed and this population. Do the authors check or control for that?

5b) Related: to clarify, are the 500 neurons chosen from the analysis equally likely to be E or I neurons?

Reviewer #1 (Public review):

This manuscript presents a pipeline incorporating a deep generative model and peptide property predictors for the de novo design of peptide sequences with dual antimicrobial/antiviral functions. The authors synthesized and experimentally validated three peptides designed by the pipeline, demonstrating antimicrobial and antiviral activities, with one leading peptide exhibiting antimicrobial efficacy in animal models.

Overall, the authors have addressed each major comment through new experiments, particularly by validating 24 peptides, clarifying alignment methods, and demonstrating sequence novelty. These additions have strengthened the manuscript. To further refine the work, it would be helpful to briefly describe any steps taken to mitigate GAN pathologies (such as mode collapse), provide a short rationale for the use of five AVP classifiers and how they complement each other, and clearly present the expanded experimental data (including MIC values and antiviral results) in the main text. Finally, the authors should also compare their approach with recently described deep-learning-enabled antibiotic discovery methods.

Joint Public Review:

This is an interesting, timely, and high-quality study on the potential neuroprotective capabilities of C-C chemokine receptor type 5 (CCR5) antagonists in ischemic stroke. The focus is on preclinical investigations.

An outstanding feature is that stroke patient representatives have directly participated in the work. Although this is often called for, it is hardly realized in research practice, so the work goes beyond established standards.

The included studies were assessed regarding the therapeutic impact and their adherence to current quality assurance guidelines such as STAIR and SRRR, another important feature of this work. While overall results were promising, there were some shortcomings regarding guideline adherence.

The paper is very well written and concise yet provides much highly useful information. It also has very good illustrations, and extremely detailed and transparent supplements.

[Editors' note: The authors have responded appropriately to the comments shared by the reviewers. The authors have provided a good academic justification for not needing to update the literature search, as one of the reviewers had suggested.]

Reviewer #1 (Public review):

Summary:

The manuscript entitled "Phosphodiesterase 1A Physically Interacts with YTHDF2 and Reinforces the Progression of Non-Small Cell Lung Cancer" explores the role of PDE1A in promoting NSCLC progression by binding to the m6A reader YTHDF2 and regulating the mRNA stability of several novel target genes, consequently activating the STAT3 pathway and leading to metastasis and drug resistance.

Strengths:

The study addresses a novel mechanism involving PDE1A and YTHDF2 interaction in NSCLC, contributing to our understanding of cancer progression.

Überblicksartikel von 2019 zu den Angriffen auf die Wissenschaft während der ersten Trump-Regierung und ihre kurz- und langfristigen Folgen. Forschungen zur Klimakrise und öffentlichen Gesundheit wurden behindert, weil sie den Interessen der fossilen Industrien schaden. Der Kampf gegen Foschung, die Interessen bestimmter Unternehmen und Branchen bedroht, ging aber weit über die Klimathematik hinaus und dient u.a. auch der Chemie- und Agroindustrien. Zu den Maßnahmen gehörten: - Beendigung von Forschungsprojekten - Abbau des Einflusses von Wissenschaftler:innen auf regulatorische Entscheidungen - Verhinderung von öffentlichen Stellungnahmen von Wissenschaftler:innen - Behinderung von Forschungen zum menschengemachten Klimawandel - Vorschreiben erwünschter Forschungsergebnisse - Overruling von Experten durch politische Funktionäre bei Begutachtungen und Regulierungen - Einstellungsstopps und Entlassungen - Entfernung bestimmter Wissenschaftler:innen aus Beratungsgremien - Verbot der Berücksichtigung bestimmter Wissenschaftstypen bei Regulierungen - Druck auf Forschende, unwissenschaftliche Aussagen des Präsidenten zu unterstützen - Schließung von Forschungszentren und -büros und Auflösung von Ausschüssen - Umsiedlungen von Behörden und Forschungseinrichtungen in unattraktive Gegenden

https://www.nytimes.com/2019/12/28/climate/trump-administration-war-on-science.html

Reviewer #1 (Public review):

Summary:

This paper presents a compelling and comprehensive study of decision-making under uncertainty. It addresses a fundamental distinction between belief-based (cognitive neuroscience) formulations of choice behavior with reward-based (behavioral psychology) accounts. Specifically, it asks whether active inference provides a better account of planning and decision making, relative to reinforcement learning. To do this, the authors use a simple but elegant paradigm that includes choices about whether to seek both information and rewards. They then assess the evidence for active inference and reinforcement learning models of choice behavior, respectively. After demonstrating that active inference provides a better explanation of behavioral responses, the neuronal correlates of epistemic and instrumental value (under an optimized active inference model) are characterized using EEG. Significant neuronal correlates of both kinds of value were found in sensor and source space. The source space correlates are then discussed sensibly, in relation to the existing literature on the functional anatomy of perceptual and instrumental decision-making under uncertainty.

Comments on revisions:

Many thanks for attending to my previous comments. I think your manuscript is now easier to read - and your new (Bayesian) analyses are described clearly.

Reviewer #2 (Public review):

Summary:

Juvenile hormone (JH) is a pleiotropic terpenoid hormone in insects that mainly regulates their development and reproduction. In particular, its developmental functions are described as the "status quo" action, as its presence in the hemolymph (the insect blood) prevents metamorphosis-initiating effects of ecdysone, another important hormone in insect development, and maintains the juvenile status of insects.

While such canonical functions of JH are known to be mediated by its intracellular receptor complex composed of Met and Tai, there have been multiple reports suggesting the presence of cell membrane receptor(s) for JH, which mediate non-genomic effects of this terpenoid hormone. In particular, the presence of receptor tyrosine kinases (RTKs) that phosphorylate Met/Tai in response to JH and thus indirectly affect the canonical JH signaling pathway has been strongly suggested. Given the importance of JH in insect physiology and the fact that the JH signaling pathway is a major target of insect growth regulators, elucidating the identify and functions of putative JH membrane receptors is of great significance form both basic and applied perspectives.

In the present study, the authors identified candidate receptors for such cell membrane JH receptors, CAD96CA and FGFR1, in the cotton bollworm, Helicoverpa armigera.

Strengths:

Their in vitro analyses are conducted thoroughly using multiple methods, which overall support their claim that these receptors can bind to JH and mediate their non-genomic effects.

Their CRISPR-Cas-mediated mutagenesis in vivo shows that mutation of the two RTKs causes acceleration of pupation, which is consistent with the mutant phenotype of the intracellular JH receptor, Met1. Although this is different from the typical phenotype one would expect from JH signaling deficiency in lepidopteran insects (i.e. precocious metamorphosis), the results overall support their claim that these two RTKs modulate genomic JH effects by phosphorylating the intracellular receptors.

Weaknesses:

Although their loss-of-function analyses suggest that the two RTKs likely have redundant functions in vivo, it is unclear whether they have any different functions in mediating JH functions in different physiological contexts. It also remains unknown whether other endogenous ligands for these RTKs affect canonical, genomic JH signaling in vivo.

Reviewer #1 (Public review):<br /> <br /> Summary:

Juvenile Hormone (JH) plays a key role in insect development and physiology. Although the intracellular receptor for JH was identified long ago, a number of studies have shown that part of JH functions should be fulfilled through binding to an unknown membrane receptor, which was proposed to belong to the RTK family. In this study, the authors screened all RTKs from the H. armigera genome for their ability to mediate responses to JH III treatment both in cultured cells and in developping animals. They also present convincing evidence that CAD96CA and FGFR1 directly bind JH III, and that their role might be conserved in other insect species.

Strengths:

Altogether, the experimental approach is very complete and elegant, providing evidence for the role of CAD96CA and FGFR1 in JH signalling using different techniques and in different contexts. I believe that this work will open new perspectives to study the role of JH and better understand what is the contribution of signalling through membrane receptors for JH-dependent developmental processes.

Weaknesses:

Unfortunately, the revised manuscript does not show significant improvement. While the identification of the receptors is highly convincing, important issues about the biological relevance remain unaddressed.

First, the main point I raised about the first version of this article is that the redundancy and/or specificity of the two receptors should be clarified, even though I understand that it cannot be deeply investigated here. I believe that this point, shared by all reviewers, is highly relevant for the scope of this work. In this revised version, it is still unclear how to reconcile gain and loss-of-function experiments and the different expression profiles of the receptors.

Second, the newly added explanations and pieces of discussion provided about the mild in vivo phenotypes of early pupation upon Cad96ca or Fgfr1 knock-out do not clarify the issue but instead put emphasis on methodological issues. Indeed, it is not clear whether the mild phenotypes reflect the biological role of Cad96ca and Fgfr1, or the redundancy of these two RTKs (and/or others), or some issue with the knock-out strategy (partial efficiency, mosaicism...).

Finally, parts of the updated discussion and the modifications to the figures are confusing.

Reviewer #1 (Public review):

Summary:

This work is meant to help create a foundation for future studies of the Central Complex, which is a critical integrative center in the fly brain. The authors present a systematic description of cellular elements, cell type classifications, behavioral evaluations and genetic resources available to the Drosophila neuroscience community.

Strengths:

The work contributes new, useful and systematic technical information in compelling fashion to support future studies of the fly brain. It also continues to set a high and transparent standard by which large-scale resources can be defined and shared.

Weaknesses:

Manuscript revisions by the authors addressed all proposed weaknesses from the original version.

Reviewer #4 (Public review):

Summary:

This is an important study that underscores that reproduction-survival trade-offs are not manifested (contrary to what generally accepted theory predicts) across a range of studies on birds. This has been studied by a meta-analytical approach, gathering data from a set of 46 papers (30 bird species). The overall conclusion is that there are no trade-offs apparent unless experimental manipulations push the natural variability to extreme values. In the wild, the general pattern for within-species variation is that birds with (naturally) larger clutches survive better.

Likely impact:

I think this is an important contribution to a slow shift in how we perceive the importance of trade-offs in ecology and evolution in general. While the current view still is that one individual excelling in one measure of its life history (i.e. receiving benefits) must struggle (i.e. pay costs) in another part. However, a positive correlation between all aspects of life history traits is possible within an individual (such as due to developmental conditions or fitting to a particular environment). Simply, some individuals can perform generally better (be of good quality than others).

Reviewer #2 (Public review):

Summary:

The authors investigated the expression profile of enterochromaffine (EC) cells after creating a new tryptophan hydroxylase 1 (Tph1) GFP-reporter mouse using scRNAseq and confirmative RNAscope analysis. They distinguish 14 clusters of Tph1+ cells found along the gut axis. The manuscript focuses on two of these, (i) a multihormonal cell type shown to express markers of pathogen/toxin and nutrient detection in the proximal small intestine, and (ii) on a EC-cluster in the distal colon, which expresses Piezo2, rendering these cells mechanosensitive. In- and ex- vivo data explore the role of the mechanosensitive EC population for intestinal/colonic transit, using chemogenetic activation, diptheria-toxin receptor dependent cell ablation and conditional gut epithelial specific Piezo2 knock-out. Whilst some of these data are confirmative of previous reports - Piezo2 has been implicated in mechanosensitive serotonin release previously, as referred to by the authors - the data are solid and emphasize the importance of mechanosensitive serotonin release for colonic propulsion. The transcriptomic data will guide future research.

Strengths:

The transcriptomic data, whilst confirmative, is more granular than previous data sets. Employing new tools to establish a role of mechanosensitive EC cells for colonic and thus total intestinal transit.

Weaknesses:

(1) The proposed villus/crypt distribution of the14 cell types is not verified adequately. The RNAscope and immunohistochemistry samples presented do not allow assessment if this interpretation is correct - spatial transcriptomics, now approaching single cell resolution, likely will help to verify this claim.

(2) The physiological function and/or functionality of most of the transcriptomically enriched gene products has not been assessed. Whilst a role for Piezo2 expressing cells for colonic transit is convincingly demonstrated the nature of the mechanical stimulus or the stimulus-secretion coupling downstream of Piezo2 activation is not clear.

Comments on revisions: I am happy with the manuscript as is.

Reviewer #1 (Public review):

Summary:

The objective of this study was to infer the population dynamics (rates of differentiation, division, and loss) and lineage relationships of clonally expanding NK cell subsets during an acute immune response.

Strengths:

A rich dataset and thorough analysis of a particular class of stochastic models.

Weaknesses:

The stochastic models used are quite simple; each population is considered homogeneous with first-order rates of division, death, and differentiation. In Markov process models such as these, there is no dependence of cellular behavior on its history of divisions. In recent years models of clonal expansion and diversification, in the settings of T and B cells, have progressed beyond this picture. So I was a little surprised that there was no mention of the literature exploring the role of replicative history in differentiation (e.g. Bresser Nat Imm 2022), nor of the notion of family 'division destinies' (either in division number or the time spent proliferating, as described by the Cyton and Cyton2 models developed by Hodgkin and collaborators; e.g. Heinzel Nat Imm 2017). The emerging view is that variability in clone (family) size may arise predominantly from the signals delivered at activation, which dictate each precursor's subsequent degree of expansion, rather than from the fluctuations deriving from division and death modeled as Poisson processes.

As you pointed out, the Gerlach and Buchholz Science papers showed evidence for highly skewed distributions of family sizes and correlations between family size and phenotypic composition. Is it possible that your observed correlations could arise if the propensity for immature CD27+ cells to differentiate into mature CD27- cells increases with division number? The relative frequency of the two populations would then also be impacted by differences in the division rates of each subset - one would need to explore this. But depending on the dependence of the differentiation rate on division number, there may be parameter regimes (and time points) at which the more differentiated cells can predominate within large clones even if they divide more slowly than their immature precursors. One might not then be able to rule out the two-state model. I would like to see a discussion or rebuttal of these issues.

Reviewer #1 (Public review):

Summary:

This study introduces a novel therapeutic strategy for patients with high-risk HER2-positive breast cancer and demonstrates that the incorporation of pyrotinib into adjuvant trastuzumab therapy can improve invasive disease-free survival.

Strengths:

The study features robust logic and high-quality data. Data from 141 patients across 23 centers were analyzed, thereby effectively mitigating regional biases and endowing the research findings with high applicability.

Weaknesses:

(1) Introduction and Discussion: Update the literature regarding the efficacy of pyrotinib combined with trastuzumab in treating HER2-positive advanced breast cancer.<br /> (2) Did all the data have a normal distribution? Expand the description of statistical analysis.<br /> (3) The novelty and innovative potential of your manuscript compared to the published literature should be described in more detail in the abstract and discussion section.<br /> (4) Figure legend should provide a bit more detail about what readers should focus on.<br /> (5) P-values should be clarified for the analysis.<br /> (6) The order (A, B, and C) in Figure 3 should be labeled in the upper left corner of the Figure.

Comments on revisions:

The authors responded well to my questions.

Reviewer #1 (Public review):

The authors aim to assess the effect of salt stress on root:shoot ratio, identify the underlying genetic mechanisms, and evaluate their contribution to salt tolerance. To this end, the authors systematically quantified natural variations in salt-induced changes in root: shoot ratio. This innovative approach considers the coordination of root and shoot growth rather than exploring biomass and development of each organ separately. Using this approach, the authors identified a gene cluster encoding eight paralog genes with a domain-of-unknown-function 247 (DUF247), with the majority of SNPs clustering into SR3G (At3g50160). In the manuscript, the authors utilized an integrative approach that includes genomic, genetic, evolutionary, histological, and physiological assays to functionally assess the contribution of their genes of interest to salt tolerance and root development.

Comments on latest version:

The authors have largely addressed my concerns and comments. I have no additional comments for this round of review.

Reviewer #1 (Public review):

Summary:

In this study by Fang et al., the authors show how STAMBPL1 promotes TNBC angiogenesis via a feed-forward GRHL3/HIF1a/VEGFA axis. They demonstrate that STAMBPL1 interacts with FOXO1, define the required domains in each protein, and illustrate that this interaction facilitates FOXO1 transcriptional factor activity, which then activates GRHL3/HIF1a/VEGFA signaling. Lastly, they show that the combination of VEGFR and FOXO1 inhibitors can synergistically suppress STAMBPL1-overexpressing TNBC.

Strengths:

The manuscript is clearly written, and the results are well explained. The observation that STAMBPL1 mediates GRHL3 transcription through its interaction with FOXO1 is novel. The findings also have important translational potential.

Reviewer #1 (Public review):

Summary:

This paper provide a resource for researchers studying the marine annelid Platynereis dumerilii. It is only the third whole body connectome to be assembled and thus provides a comparison with those less complex animals: the nematode Caenorhabditis elegans and the tunicate Ciona intestinialis. The paper catalogs all cells in the body, not just neurons, and details how sensory neurons, interneurons, motor neurons, and effector organs are connected. From this, the authors are able to extract information about the organization of different aspects of the nervous system. These include the extent of recurrent connectivity, unimodal and multimodal sensory processing, and long-range and short-range connectivity.

Several interesting conclusion are drawn, including the concept that circuit evolution might have proceeded by duplication and diversion of cell types, much as it has been posited that gene evolution has occurred. It also informs the understanding of the evolution of segmental body plans in annelids by mapping and comparing cells in each segment.

Strengths:

This paper contains a wealth of data. The raw dataset is available. The codes and scripts are provided to allow interested readers to utilize this dataset.

The analysis is painstakingly meticulous. The diagrams are organized to orient the reader to the complexities this overwhelming analysis

Weaknesses:

The strength of the paper is also its weakness. It contains so much data and analysis that it is burdensome to read and understand. There are 16 multi-panel data figures in the main text and another 38 supplemental figures and 5 videos.

The impact of the paper is diminished by its size and depth. The paper could be broken up into smaller thematic papers that would be more accessible to researchers interested in particular topics. For example, there could be a single paper on the mushroom body and another paper on the segmental organization.

Comments on revisions:

The authors have addressed all of my concerns.

Reviewer #1 (Public review):

This study presents a refined approach to enhance the sensitivity of PCR for detecting Trypanosoma cruzi in blood by employing DNA fragmentation and deep sampling, involving multiple replicate PCR reactions. Combined with serial blood sampling, these methods enabled consistent detection of the parasite in infected humans, non-human primates, and dogs, including hosts with very low parasitemia levels.

Inspired by earlier methods that cleaved kinetoplast DNA (kDNA) to improve target distribution, this study targets nuclear satellite DNA repeats, which are tandemly arranged in T. cruzi chromosomes. By fragmenting DNA prior to PCR, the authors reduced subsampling errors, breaking large fragments into smaller, evenly distributed units. This improved the frequency of positive reactions and reduced variability among replicate Cq values.

Using contrived blood samples, the study demonstrated that this approach significantly enhances PCR positivity. Moreover, the findings suggest that cell pellets from blood yield higher concentrations of parasite DNA compared to whole blood, prompting a reevaluation of current diagnostic practices, which predominantly use whole blood lysates.

The study also highlights the importance of deep sampling. Serial testing across multiple blood samples mitigated the variability in parasitemia, addressing challenges first noted in early xenodiagnosis studies (Cerisola et al., 1977).

The proposed DNA extraction and amplification procedures effectively captured parasitemia dynamics, achieving detection sensitivities with quantification limits as low as ~0.00025 parasite equivalents/mL, approaching the detection of a single target copy per reaction.

This work underscores the utility of deep-sampling PCR in monitoring parasitemia dynamics and guiding treatment strategies, especially in chronic infections. It also stresses the importance of treating individuals with low parasitic loads, as immune control may change over time.

Strengths:

The strategies used for increasing PCR sensitivity offer the potential for enhancing treatment monitoring and understanding the dynamics of parasite-host interactions in chronic Chagas disease.

Weaknesses:

While the study offers valuable insights for research in T.cruzi infection dynamics and monitoring of trypanocidal drugs efficacy, its broader adoption depends on the development of cost-effective and scalable alternatives to labor-intensive techniques such as sonication, currently required for DNA fragmentation. Additionally, the reliance on blood cell pellets and the DNA fragmentation protocol introduces extra processing steps, which may not be feasible for many clinical laboratories, particularly in resource-limited endemic areas that require simpler and more streamlined procedures.

Reviewer #1 (Public review):

Summary:

Jirouskova and colleagues in their study have carried out an in depth proteomic characterization of the dynamics of the liver fibrotic response and the resulting resolution in two distinct models of liver injury: CCl4-induced model of hepatotoxicity and pericentral/bridging liver fibrosis and the DDC feeding model of obstructive cholestasis and periportal fibrosis. They focussed on both the insoluble extracellular matrix (ECM) components as well as the soluble secreted factors produced by hepatic stellate cells (HSCs) and/or portal fibroblasts (PFs). They identified compartment- and time-resolved proteomic signatures in the two models with disease-specific factors or matrisomes. Their study also identified phenotypic differences between the models such as that while the CCl4-induced model induced profound hepatotoxicity followed by resolution, the DDC model induced more lasting liver damage and proteomic changes that resembled advanced human liver fibrosis favouring hepatocarcinogenesis.

Overall, this comprehensive and very well conducted study is rigorous and well planned. The conclusions are supported by compelling studies and analyses. One caveat is the lack of mechanistic experiments to prove causality, but this can be carried out in follow-up studies.

Strengths:

• A major strength in the study is that the experiments are rigorous and very well conducted. For instance, the authors utilized two models of liver fibrosis to study different aspects of the pathology - hepatotoxicity vs cholestasis. In addition, 4 time points for each model were investigated - 2 for fibrosis development and 2 for fibrosis resolution. They have taken 3 components for proteomic analyses - total lysates, insoluble ECM components as well as the soluble secreted factors. Thus, the authors provide a comprehensive overview of the fibrosis and resolution process in these models.

• Another great strength of the study is that the methodology utilized was able to dissect unique pathways relevant for each model as well as common targets. For example, the authors identified known pathways such as mTOR signalling to be differentially regulated in the CCl4 vs DDC model. mTOR signalling was increased in the DDC model that is associated with hyperproliferation. Thus showing that the approach taken is specific enough to distinguish between the two similar (both induce fibrosis) but distinct mechanisms (hepatotoxicity vs cholestasis) is a strong point of the study.

Weaknesses:

• A caveat of the study is that the authors have not conducted mechanistic (gain of function/loss of function) studies from any of their identified targets to truly prove causality. This remains one of the limitations of this study. Thus, future studies should investigate this point in detail. For instance, it would have been intriguing to dissect if knocking out specific genes involved in one specific model or genes common to both would yield distinct phenotypic outcomes.

Reviewer #1 (Public review):

The paper by Gao et al. describes the effect of capsaicin on the NRF2/KEAP1 pathway. The authors carried out a set of in vitro and in vivo experiments that addressed the mechanisms of the protective effect of capsaicin on ethanol-induced cytotoxicity.

The authors conclude that capsaicin activates NRF2, which leads to the induction of cytoprotective genes, preventing oxidative damage. The paper shows that capsaicin may directly bind to KEAP1 and that it is a noncovalent modification of the Kelch domain.

The authors also designed new albumin-coated capsaicin nanoparticles, which were tested for the therapeutic effect in vivo.

I appreciate the authors' experimental efforts to strengthen the study's conclusions. However, in my opinion, the paper is still not fully technically sound, which weakens the strength of the evidence.

Reviewer #1 (Public review):

Summary:

This study reports the effects of psilocin on iPSC-derived human cortical neurons.

Strengths:

The characterization was comprehensive, involving immunohistochemistry of various markers, 5-HT2A receptors, BDNF, and TrkB, transcriptomics analyses, morphological determination, electrophysiology, and finally synaptic protein measurements. The results are in close agreement with prior work (PMID 29898390) on rat-cultured cortical neurons. Nevertheless, there is value in confirming those earlier findings and furthermore demonstrating the effects in human neurons, which are important for translation. The genetic, proteomics, and cell structure analyses used in this paper are its major strengths. The study supports the value of using iPSC-derived human cortical neurons for drug development involving psychedelics-related compounds.

Weaknesses:

(1) Line 140: 5-HT2A receptor expression was found via immunocytochemistry to reside in the somatodendritic and axonal compartments. However, prior work from ex vivo tissue using electron microscopy has found predominantly 5-HT2A receptor expression in the somatodendritic compartment (PMID: 12535944). Was this antibody validated to be 5-HT2A receptor-specific? Can the authors reason why the discrepancy may arise, and if the axonal expression is specific to the cultured neurons?

(2) Line 143: It would be helpful to specify the dose of psilocin tested, and describe how this dose was chosen.

(3) Figure 1: The interpretation is that the differential internalization in the axonal and somatodendritic compartments is time-dependent. However, given that only one dose is tested, it is also possible that this reflects dose dependence, with the longer time exposure leading to higher dose exposure, so these variables are related. That is, if a higher dose is given, internalization may also be observed after 10 minutes in the dendritic compartment.

(4) Figure 3 & 4: What is the 'control' here? A more appropriate control for the 24 hours after psilocin application would be 24 hours after vehicle application. Here the authors are looking at before and after, but the factor of time elapsed and perturbation via application is not controlled for.

(5) The sample size was not clearly described. In the figure legend, N = the number of neurites is provided, but it is unclear how many cells have been analyzed, and then how many of those cells belong to the same culture. These are important sample size information that should be provided. Relatedly, statistical analyses should consider that the neurites from the same cells are not independent. If the neurites indeed come from the same cells, then the sample size is much smaller and a statistical analysis considering the nested nature of the data should be used.

Reviewer #2 (Public review):

Summary:

The paper attempts to elucidate how feral (wild) pigs cause distortion of the environment in over 54 countries of the world, particularly Australia.

The paper displays proof that over $120 billion worth of facilities were destroyed annually in the United States of America.

The authors have tried to infer that the findings of their work were fundamental and possessing a compelling strength of evidence.

Strengths:

(1) Clearly stating feral (wild) pigs as a problem in the environment.

(2) Stating how 54 countries were affected by the feral pigs.

(3) Mentioning how $120 billion was lost in the US, annually, as a result of the activities of the feral pigs.

(4) Amplifying the fact that 14 species of animals were being driven into extinction by the feral pigs.

(5) Feral pigs possessing zoonotic abilities.

(6) Feral pigs acting as reservoirs for endemic diseases like brucellosis and leptospirosis.

(7) Understanding disease patterns by the social dynamics of feral pig interactions.

(8) The use of 146 GPS-monitored feral pigs to establish their social interaction among themselves.

Weaknesses:

None, as the weaknesses had been already addressed.

Reviewer #1 (Public review):

In Pech et al. the authors take advantage of a genetic model organism to investigate the convergent impact of multiple mutations linked to Parkinson's Disease (PD). To investigate this question they leverage Drosophila genetics to create wild type and mutant alleles for five different mutations linked to PD. An additional novel focus of this work is an examination of the animals in an early phase before apparent dopaminergic degeneration. Having generated this resource, authors discover apply an impressive array of experiments including behavioural assays, calcium imaging and single-cell profiling. They also cross-validate their findings in human PD brains. Strikingly, the authors discover common dysregulated genes between fly and human that converges on synaptic dysregulation. Finally, they demonstrate that even in early timepoints, there is extensive dysfunction of olfactory projection neuron calcium.

This is a fantastic, comprehensive, timely and landmark pan-species work that demonstrates the convergence of multiple familial PD mutations onto a synaptic program. It is extremely well written and the authors have addressed all my comments in this review. I recommend this work be published as soon as possible.

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Reviewer #3 (Public review):

Summary:

This manuscript extends previous research by this group by relating variation in pupil size to the endpoints of saccades produced by human participants under various conditions including trial-based choices between pairs of spots and search for small items in natural scenes. Based on the premise that pupil size is a reliable proxy of "effort", the authors conclude that less costly saccade targets are preferred. Finding that this preference was influenced by the performance of a non-visual, attention-demanding task, the authors conclude that a common source of effort animates gaze behavior and other cognitive tasks.

Strengths:

Strengths of the manuscript include the novelty of the approach, the clarity of the findings, and the community interest in the problem.

Weaknesses:

Enthusiasm for this manuscript is reduced by the following weaknesses:

(1) A relationship between pupil size and saccade production seems clear based on the authors' previous and current work. What is at issue is the interpretation. The authors test one, preferred hypothesis, and the narrative of the manuscript treats the hypothesis that pupil size is a proxy of effort as beyond dispute or question. The stated elements of their argument seem to go like this:<br /> PROPOSITION 1: Pupil size varies systematically across task conditions, being larger when tasks are more demanding.<br /> PROPOSITION 2: Pupil size is related to the locus coeruleus.<br /> PROPOSITION 3: The locus coeruleus NE system modulates neural activity and interactions.<br /> CONCLUSION: Therefore, pupil size indexes the resource demand or "effort" associated with task conditions.<br /> How the conclusion follows from the propositions is not self-evident. Proposition 3, in particular, fails to establish the link that is supposed to lead to the conclusion.

(2) The authors test one, preferred hypothesis and do not consider plausible alternatives. Is "cost" the only conceivable hypothesis? The hypothesis is framed in very narrow terms. For example, the cholinergic and dopamine systems that have been featured in other researchers' consideration of pupil size modulation are missing here. Thus, because the authors do not rule out plausible alternative hypotheses, the logical structure of this manuscript can be criticized as committing the fallacy of affirming the consequent.

(3) The authors cite particular publications in support of the claim that saccade selection is influenced by an assessment of effort. Given the extensive work by others on this general topic, the skeptic could regard the theoretical perspective of this manuscript as too impoverished. Their work may be enhanced by consideration of other work on this general topic, e.g, (i) Shenhav A, Botvinick MM, Cohen JD. (2013) The expected value of control: an integrative theory of anterior cingulate cortex function. Neuron. 2013 Jul 24;79(2):217-40. (ii) Müller T, Husain M, Apps MAJ. (2022) Preferences for seeking effort or reward information bias the willingness to work. Sci Rep. 2022 Nov 14;12(1):19486. (iii) Bustamante LA, Oshinowo T, Lee JR, Tong E, Burton AR, Shenhav A, Cohen JD, Daw ND. (2023) Effort Foraging Task reveals a positive correlation between individual differences in the cost of cognitive and physical effort in humans. Proc Natl Acad Sci U S A. 2023 Dec 12;120(50):e2221510120.

(4) What is the source of cost in saccade production? What is the currency of that cost? The authors state (page 13), "... oblique saccades require more complex oculomotor programs than horizontal eye movements because more neuronal populations in the superior colliculus (SC) and frontal eye fields (FEF) [76-79], and more muscles are necessary to plan and execute the saccade [76, 80, 81]." This statement raises questions and concerns. First, the basis of the claim that more neurons in FEF and SC are needed for oblique versus cardinal saccades is not established in any of the publications cited. Second, the authors may be referring to the fact that oblique saccades require coordination between pontine and midbrain circuits. This must be clarified. Second, the cost is unlikely to originate in extraocular muscle fatigue because the muscle fibers are so different from skeletal muscles, being fundamentally less fatigable. Third, if net muscle contraction is the cost, then why are upward saccades, which require the eyelid, not more expensive than downward? Thus, just how some saccades are more effortful than others is not clear.

(5) The authors do not consider observations about variation in pupil size that seem to be incompatible with the preferred hypothesis. For example, at least two studies have described systematically larger pupil dilation associated with faster relative to accurate performance in manual and saccade tasks (e.g., Naber M, Murphy P. Pupillometric investigation into the speed-accuracy trade-off in a visuo-motor aiming task. Psychophysiology. 2020 Mar;57(3):e13499; Reppert TR, Heitz RP, Schall JD. Neural mechanisms for executive control of speed-accuracy trade-off. Cell Rep. 2023 Nov 28;42(11):113422). Is the fast relative to the accurate option necessarily more costly?

(6) The authors draw conclusions based on trends across participants, but they should be more transparent about variation that contradicts these trends. In Figures 3 and 4 we see many participants producing behavior unlike most others. Who are they? Why do they look so different? Is it just noise, or do different participants adopt different policies?

Comments on revisions:

The authors have addressed the concerns and questions raised in the original review.

Reviewer #1 (Public review):

Summary:

In this valuable study, the authors found that the macrolide drug rapamycin, which is an important pharmacological tool in the clinic and the research lab, is less specific than previously thought. They provide solid functional evidence that rapamycin activates TRPM8 and begin to develop an NMR method to measure the specific binding of a ligand to a membrane protein.

Strengths:

The authors use a variety of complementary experimental techniques in several different systems, and their results support the conclusions drawn.

Weaknesses:

The proposed location of the rapamycin binding pocket within the membrane means that molecular docking approaches designed for soluble proteins alone do not provide solid evidence for a rapamycin binding pocket location in TRPM8, but the authors are appropriately careful in stating that the model is consistent with their functional experiments. The novel STTD method is intriguing and supportive of the functional results and docking predictions, but further validation of this method is needed.

Impact:

This work provides still more evidence for the polymodality of TRP channels, reminding both TRP channel researchers and those who use rapamycin in other contexts that the adjective "specific" is only meaningful in the context of what else has been explicitly tested.

Comments on revisions:

The authors have addressed my major concerns from the previous round of revision, and I agree that those things that remain un-done are outside the scope of this manuscript.

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Joint Public Review:

Summary:

In this manuscript, the authors investigate how different domains of the presynaptic protein UNC-13 regulate synaptic vesicle release in the nematode C. elegans. By generating numerous point mutations and domain deletions, they propose that two membrane-binding domains (C1 and C2B) can exhibit "mutual inhibition," enabling either domain to enhance or restrain transmission depending on its conformation. The authors also explore additional N-terminal regions, suggesting that these domains may modulate both miniature and evoked synaptic responses. From their electrophysiological data, they present a "functional switch" model in which UNC-13 potentially toggles between a basal state and a gain-of-function state, though the physiological basis for this switch remains partly speculative.

Strengths:

(1) The authors conduct a thorough exploration of how mutations in the C1, C2B, and other regulatory domains affect synaptic transmission. This includes single, double, and triple mutations, as well as domain truncations, yielding a large, informative dataset.

(2) The study includes systematically measuring both spontaneous and evoked synaptic currents at neuromuscular junctions, under various experimental conditions (e.g., different Ca²⁺ levels), which strengthens the reliability of their functional conclusions.

(3) Findings that different domain disruptions produce distinct effects on mEPSCs, mIPSCs, and evoked EPSCs suggest UNC-13 may adopt an elevated functional state to regulate synaptic transmission.

Weaknesses:

It remains unclear whether the various domain alterations truly converge on a single "gain-of-function" state or instead represent multiple pathways for enhancing UNC-13 activity. Different mutations selectively affect spontaneous or evoked release, suggesting that each variant may not share the same underlying mechanism. Moreover, many conclusions rely on combining domain deletions or point mutations, yet the electrophysiological data show distinct outcomes across EPSCs, IPSCs, mini, and evoked responses. This raises questions about whether these manipulations all act on the same pathway and whether their observed additivity or suppression genuinely reflects a single mechanistic process. A unifying model-or at least a clearer explanation of why the authors infer one mechanistic state across different domain manipulations would strengthen the paper's conclusions.

The manuscript proposes that UNC-13 toggles from a basal to a "gain-of-function" state under normal synaptic activity. However, it does not address when or how this switch might occur in vivo, since it is demonstrated principally via artificial mutations. Providing direct evidence or additional discussion of such switching under physiological conditions would be particularly informative.

What is the physiological significance of the proposed gain-of-function state? The data suggest that certain mutants (e.g., HK+D1-5N) lacking the gain-of-function state can still support synaptic transmission at wild-type levels. How do the authors reconcile this with the idea that the gain-of-function state plays a critical role at the synapse?

The authors determined the fluorescence intensity of mApple-tagged UNC-13 variants (Figure 1J-K and Figure 7J-K), finding no significant changes compared to the wild-type. However, a more detailed analysis of the density or distribution of fluorescent puncta in axons could clarify whether certain mutations alter the localization of UNC-13 at synapses. Demonstrating colocalization with wild-type UNC-13 (or another presynaptic marker) would help rule out mislocalization effects.

The study mainly relies on extrachromosomal transgenes, which can show variable copy numbers and expression levels among individual worm strains. This variability might complicate interpretation, as differences in expression could mask or exaggerate certain phenotypes.

Finally, the discussion is somewhat diffused. Streamlining the text to focus on the most direct connections would help readers pinpoint the key conclusions and open questions.

Reviewer #1 (Public review):

This is an interesting and timely computational study using molecular dynamics simulation as well as quantum mechanical calculation to address why tyrosine (Y), as part of an intrinsically disordered protein (IDP) sequence, has been observed experimentally to be stronger than phenylalanine (F) as a promoter for biomolecular phase separation. Notably, the authors identified the aqueous nature of the condensate environment and the corresponding dielectric and hydrogen bonding effects as a key to understanding the experimentally observed difference. This principle is illustrated by the difference in computed transfer free energy of Y- and F-containing pentapeptides into a solvent with various degrees of polarity. The elucidation offered by this work is important. The computation appears to be carefully executed, the results are valuable, and the discussion is generally insightful. However, there is room for improvement in some parts of the presentation in terms of accuracy and clarity, including, e.g., the logic of the narrative should be clarified with additional information (and possibly additional computation), and the current effort should be better placed in the context of prior relevant theoretical and experimental works on cation-π interactions in biomolecules and dielectric properties of biomolecular condensates. Accordingly, this manuscript should be revised to address the following, with added discussion as well as inclusion of references mentioned below.

(1) Page 2, line 61: "Coarse-grained simulation models have failed to account for the greater propensity of arginine to promote phase separation in Ddx4 variants with Arg to Lys mutations (Das et al., 2020)". As it stands, this statement is not accurate, because the cited reference to Das et al. showed that although some coarse-grained models, namely the HPS model of Dignon et al., 2018 PLoS Comput did not capture the Arg to Lys trend, the KH model described in the same Dignon et al. paper was demonstrated by Das et al. (2020) to be capable of mimicking the greater propensity of Arg to promote phase separation than Lys. Accordingly, a possible minimal change that would correct the inaccuracy of this statement in the manuscript would be to add the word "Some" in front of "coarse-grained simulation models ...", i.e., it should read "Some coarse-grained simulation models have failed ...". In fact, a subsequent work [Wessén et al., J Phys Chem B 126: 9222-9245 (2022)] that applied the Mpipi interaction parameters (Joseph et al., 2021, already cited in the manuscript) showed that Mpipi is capable of capturing the rank ordering of phase separation propensity of Ddx4 variants, including a charge scrambled variant as well as both the Arg to Lys and the Phe to Ala variants (see Figure 11a of the above-cited Wessén et al. 2022 reference). The authors may wish to qualify their statements in the introduction to take note of these prior results. For example, they may consider adding a note immediately after the next sentence in the manuscript "However, by replacing the hydrophobicity scales ... (Das et al., 2020)" to refer to these subsequent findings in 2021-2022.

(2) Page 8, lines 285-290 (as well as the preceding discussion under the same subheading & Figure 4): "These findings suggest that ... is not primarily driven by differences in protein-protein interaction patterns ..." The authors' logic in terms of physical explanation is somewhat problematic here. In this regard, "Protein-protein interaction patterns" appear to be a straw man, so to speak. Indeed, who (reference?) has argued that the difference in the capability of Y and F in promoting phase separation should be reflected in the pairwise amino acid interaction pattern in a condensate that contains either only Y (and G, S) and only F (and G, S) but not both Y and F? Also, this paragraph in the manuscript seems to suggest that the authors' observation of similar contact patterns in the GSY and GSF condensates is "counterintuitive" given the difference in Y-Y and F-F potentials of mean force (Joseph et al., 2021); but there is nothing particularly counterintuitive about that. The two sets of observations are not mutually exclusive. For instance, consider two different homopolymers, one with a significantly stronger monomer-monomer attraction than the other. The condensates for the two different homopolymers will have essentially the same contact pattern but very different stabilities (different critical temperatures), and there is nothing surprising about it. In other words, phase separation propensity is not "driven" by contact pattern in general, it's driven by interaction (free) energy. The relevant issue here is total interaction energy or the critical point of the phase separation. If it is computationally feasible, the authors should attempt to determine the critical temperatures for the GSY condensate versus the GSF condensate to verify that the GSY condensate has a higher critical temperature than the GSF condensate. That would be the most relevant piece of information for the question at hand.

(3) Page 9, lines 315-316: "...Our ε [relative permittivity] values ... are surprisingly close to that derived from experiment on Ddx4 condensates (45{plus minus}13) (Nott et al., 2015)". For accuracy, it should be noted here that the relative permittivity provided in the supplementary information of Nott et al. was not a direct experimental measurement but based on a fit using Flory-Huggins (FH), but FH is not the most appropriate theory for a polymer with long-spatial-range Coulomb interactions. To this reviewer's knowledge, no direct measurement of relative permittivity in biomolecular condensates has been made to date. Explicit-water simulation suggests that the relative permittivity of Ddx4 condensate with protein volume fraction ≈ 0.4 can have a relative permittivity ≈ 35-50 (Das et al., PNAS 2020, Fig.7A), which happens to agree with the ε = 45{plus minus}13 estimate. This information should be useful to include in the authors' manuscript.

(4) As for the dielectric environment within biomolecular condensates, coarse-grained simulation has suggested that whereas condensates formed by essentially electric neutral polymers (as in the authors' model systems) have relative permittivities intermediate between that of bulk water and that of pure protein (ε = 2-4, or at most 15), condensates formed by highly charged polymers can have relative permittivity higher than that of bulk water [Wessén et al., J Phys Chem B 125:4337-4358 (2021), Fig.14 of this reference]. In view of the role of aromatic residues (mainly Y and F) in the phase separation of IDPs such as A1-LCD and LAF-1 that contain positively and negatively charged residues (Martin et al., 2020; Schuster et al., 2020, already cited in the manuscript), it should be useful to address briefly how the relationship between the relative phase-separation promotion strength of Y vs F and dielectric environment of the condensate may or may not be change with higher relative permittivities.

(5) The authors applied the dipole moment fluctuation formula (Eq.2 in the manuscript) to calculate relative permittivity in their model condensates. Does this formula apply only to an isotropic environment? The authors' model condensates were obtained from a "slab" approach (page 4 and thus the simulation box has a rectangular geometry. Did the authors apply Equation 2 to the entire simulation box or only to the central part of the box with the condensate (see, e.g., Figure 3C in the manuscript). If the latter is the case, is it necessary to use a different dipole moment formula that distinguishes between the "parallel" and "perpendicular" components of the dipole moment (see, e.g., Equation 16 in the above-cited Wessén et al. 2021 paper). A brief added comment will be useful.

(6) With regard to the general role of Y and F in the phase separation of biomolecules containing positively charged Arg and Lys residues, the relative strength of cation-π interactions (cation-Y vs cation-F) should be addressed (in view of the generality implied by the title of the manuscript), or at least discussed briefly in the authors' manuscript if a detailed study is beyond the scope of their current effort. It has long been known that in the biomolecular context, cation-Y is slightly stronger than cation-F, whereas cation-tryptophan (W) is significantly stronger than either cation-Y and cation-F [Wu & McMahon, JACS 130:12554-12555 (2008)]. Experimental data from a study of EWS (Ewing sarcoma) transactivation domains indicated that Y is a slightly stronger promoter than F for transcription, whereas W is significantly stronger than either Y or F [Song et al., PLoS Comput Biol 9:e1003239 (2013)]. In view of the subsequent general recognition that "transcription factors activate genes through the phase-separation capacity of their activation domain" [Boija et al., Cell 175:1842-1855.e16 (2018)] which is applicable to EWS in particular [Johnson et al., JACS 146:8071-8085 (2024)], the experimental data in Song et al. 2013 (see Figure 3A of this reference) suggests that cation-Y interactions are stronger than cation-F interactions in promoting phase separation, thus generalizing the authors' observations (which focus primarily on Y-Y, Y-F and F-F interactions) to most situations in which cation-Y and cation-F interactions are relevant to biomolecular condensation.

(7) Page 9: The observation of weaker effective F-F (and a few other nonpolar-nonpolar) interactions in a largely aqueous environment (as in an IDP condensate) than in a nonpolar environment (as in the core of a folded protein) is intimately related to (and expected from) the long-recognized distinction between "bulk" and "pair" as well as size dependence of hydrophobic effects that have been addressed in the context of protein folding [Wood & Thompson, PNAS 87:8921-8927 (1990); Shimizu & Chan, JACS 123:2083-2084 (2001); Proteins 49:560-566 (2002)]. It will be useful to add a brief pointer in the current manuscript to this body of relevant resources in protein science.

Reviewer #1 (Public review):

Summary:

Wang and Colleagues present a study aimed at demonstrating the feasibility of repeated ultrasound localization microscopy (ULM) recording sessions on mice chronically implanted with a cranial window transparent to US. They provided quantitative information on their protocol, such as the required number of Contrast enhancing microbubbles (MBs) to get a clear image of the vasculature of a brain coronal section. Also, they quantified the co-registration quality over time-distant sessions and the vasodilator effect of isoflurane.

Strengths:

Strengths: the study showed a remarkable performance in recording precisely the same brain coronal section over repeated imaging sessions. In addition, it sheds light on the vasodilator effect of isoflurane (an anesthetic whose effects are not fully understood) on the different brain vasculature compartments, although, as the Authors stated, some insights in this aspect have already been published with other imaging techniques. The experimental setting and protocol are very well described.

Wang and co-authors submitted a revised version of their study, which shows improvements in the clarity of the data description.<br /> However, the flaws and limitations of this study are substantially unchanged.

The main issues are:<br /> - Statistics are still inadequate. The TOST test proposed in this revised version is not equivalent to an ANOVA. Indeed, multivariate analyses should be the most appropriate, given that some quantifications were probably made on multiple vessels from different mice. The 3 reviewers mentioned the flaws in statistics as the primary concern.<br /> - No new data has been added, such as testing other anesthetics.<br /> - The Authors still insist on using the term Vascularity which they define as: 'proportion of the pixel count occupied by blood vessels within each ROI, obtained by binarizing the ULM vessel density maps and calculating the percentage of the pixels with MB signal.'. Why not use apparent cerebral blood volume or just CBV? Introducing an unnecessary and redundant term is not scientifically acceptable. In this revised version, vascularity is also used to indicate a higher vascular density (Line 275), which does not make sense: blood vessels do not generate from the isoflurane to the awake condition in a few minutes. Rev2 also raised this point.<br /> - The long-term recordings mentioned by the Authors refer to the 3-week time frame analyzed in this study. However, within each acquisition, the time available from imaging is only a few minutes (< 10', referring to most of the plots showing time courses) after the animals' arousal from isoflurane and before bubbles disappear. This limitation should be acknowledged.<br /> - The more precise description of the number of mice and blood vessels analyzed in Figure 6 makes it apparent the limited number of independent samples used to support the findings of this work. A limitation that should be acknowledged. The newly provided information added as Supplementary Figure 1 should be moved to the main text, eventually in the figure legends. The limited data in support of the findings was also highlighted by Rev2 and, indirectly, by Rev3.

Reviewer #1 (Public review):

Summary:

This paper proposes a neural mechanism underlying the perception of ambiguous images: neuromodulation changes the gain of neural circuits promoting a switch between two possible percepts. Converging evidence for this is provided by indirect measurements of neuromodulatory activity and large-scale brain dynamics which are linked by a neural network model. However, both the data analysis as well as the computational modeling are incomplete and would benefit from a more rigorous approach.

This is a revised version of the manuscript which, in my view, is a considerable step forward compared to the original submission.

In particular, the authors now model phasic gain changes in the RNN, based on the network's uncertainty. This is original and much closer to what is suggested by the phasic pupil responses. They also show that switching is actually a network effect because switching times depend on network configuration (Fig 2). This resolves my main comments 1 and 2 about the model.

The mechanism, as I understand it, is different from what the authors described before in the RNN with tonic gain changes. As uncertainty increases, the network enters a regime in which the two excitatory populations start to oscillate. My intuition is that this oscillation arises from the feedback loop created by the new gain control mechanism. If my intuition is correct, I think it would be worth to explain this mechanism in the paper more explicitly.

Overall, the modeling part of the paper has changed quite a lot and I think it is now more solid which is why I have updated my "strength of evidence" rating.

Reviewer #1 (Public Review):

This study reports that spatial frequency representation can predict category coding in the inferior temporal cortex. The original conclusion was based on likely problematic stimulus timing (33 ms which was too brief). Now the authors claim that they also have a different set of data on the basis of longer stimulus duration (200 ms).

One big issue in the original report was that the experiments used a stimulus duration that was too brief and could have weakened the effects of high spatial frequencies and confounded the conclusions. Now the authors provided a new set of data on the basis of a longer stimulus duration and made the claim that the conclusions are unchanged. These new data and the data in the original report were collected at the same time as the authors report.

The authors may provide an explanation why they performed the same experiments using two stimulus durations and only reported one data set with the brief duration. They may also explain why they opted not to mention in the original report the existence of another data set with a different stimulus duration, which would otherwise have certainly strengthened their main conclusions.

Reviewer #1 (Public review):

(1) Summary of the Paper:

This paper by Chen et al. examines the cellular composition and gene expression of the hypothalamic medial preoptic area (MPOA) in two closely related deer mouse species (P. maniculatus and P. polionotus) that exhibit distinct social behaviors. Through single-nucleus RNA sequencing (snRNA-seq), Chen et al., identify sex- and species-specific neuronal cell types that likely contribute to differences in mating and parental care. By comparing monogamous and promiscuous species, the study provides insights into how neuronal diversity and gene expression changes in the MPOA might underlie the evolution of social behaviors.

(2) Strengths of the Paper:

The paper excels in several areas. First, the data presentation is clear and well-organized, making the complex findings easy to follow. The writing is straightforward and highly accessible, which enhances the overall readability. The experimental design is innovative, particularly in how they combined samples from different species into the same dataset and then used post-hoc identification to distinguish cell types by species. This dramatically controls for potential batch effects in my opinion. Additionally, the authors contextualize their findings within the framework of previously published studies on Mus musculus, providing a strong comparative analysis that enhances the significance of their work.

(3) Weaknesses of the Paper:

The major limitation of the study is the absence of causal experiments linking the observed changes in MPOA cell types to species-specific social behaviors. While the study provides valuable correlational data, it lacks functional experiments that would demonstrate a direct relationship between the neuronal differences and behavior. For instance, manipulating these cell types or gene expressions in vivo and observing their effects on behavior would have strengthened the conclusions, although I certainly appreciate the difficulty in this, especially in non-musculus mice. Without such experiments, the study remains speculative about how these neuronal differences contribute to the evolution of social behaviors.

Reviewer #1 (Public review):

Summary:

This manuscript by Guo and Uusisaari describes a series of experiments that employ a novel approach to address long-standing questions on the inferior olive in general and the role of the nucleo-olivary projection specifically. For the first time, they optimized the ventral approach to the inferior olive to facilitate imaging in this area that is notoriously difficult to reach. Using this approach, they are able to compare activity in two olivary regions, the PO and DAO, during different types of stimulation. They demonstrate the difference between the two regions, linked to Aldoc-identities of downstream Purkinje cells, and that there is co-activation resulting in larger events when they are clustered. Periocular stimulation also drives larger events, related to co-activation. Using optogenetic stimulation they activate the nucleo-olivary (N-O) tract and observe a wide range of responses, from excitation to inhibition. Zooming in on inhibition they test the assumption that N-O activation can be responsible for suppression of sensory-evoked events. Instead, they suggest that the N-O input can function to suppress background activity while preserving the sensory-driven responses.

Strengths:

This is an important study, tackling the long-standing issue of the impossibility to do imaging in the inferior olive and using that novel method to address the most relevant questions. The experiments are technically very challenging, the results are presented clearly and the analysis is quite rigorous. There is quite a lot of room for interpretation, see weaknesses, but the authors make an effort to cover many options.

Weaknesses:

The heavy anesthesia that is required during the experiment could severely impact the findings. Because of the anesthesia, the firing rate of IO neurons is found to be ~0.1 Hz, significantly lower than the 1 Hz found in non-anesthetized mice. This is mentioned and discussed, but what the consequences could be cannot be understated and should be addressed more. Although the methods and results are described in sufficient detail, there are a few points that, when addressed, would improve the manuscript.

Reviewer #1 (Public review):

This study provides a thorough analysis of Nup107's role in Drosophila metamorphosis, demonstrating that its depletion leads to developmental arrest at the third larval instar stage due to disruptions in ecdysone biosynthesis and EcR signaling. Importantly, the authors establish a novel connection between Nup107 and Torso receptor expression, linking it to the hormonal cascade regulating pupariation.

However, some contradictory results weaken the conclusions of the study. The authors claim that Nup107 is involved in the translocation of EcR from the cytoplasm to the nucleus. However, the evidence provided in the paper suggests it more likely regulates EcR expression positively, as EcR is undetectable in Nup107-depleted animals, even below background levels. Additionally, the link between Nup107 and Torso is not fully substantiated. While overexpression of Torso appears to rescue the lack of 20E production in the prothoracic gland, the distinct phenotypes of Torso and Nup107 depletion-developmental delay in the former versus complete larval arrest in the latter complicate understanding of Nup107's precise role.

To clarify these discrepancies, further investigation into whether Nup107 interacts with other critical signaling pathways related to the regulation of ecdysone biosynthesis, such as EGFR or TGF-β, would be beneficial and could strengthen the findings.

In summary, although the study presents some intriguing observations, several conclusions are not well-supported by the experimental data.

Reviewer #1 (Public review):

Summary:

In this study, the authors propose a "unifying method to evaluate inter-areal interactions in different types of neuronal recordings, timescales, and species". The method consists of computing the variance explained by a linear decoder that attempts to predict individual neural responses (firing rates) in one area based on neural responses in another area.

The authors apply the method to previously published calcium imaging data from layer 4 and layers 2/3 of 4 mice over 7 days, and simultaneously recorded Utah array spiking data from areas V1 and V4 of 1 monkey over 5 days of recording. They report distributions over "variance explained" numbers for several combinations: from mouse V1 L4 to mouse V1 L2/3, from L2/3 to L4, from monkey V1 to monkey V4, and from V4 to V1. For their monkey data, they also report the corresponding results for different temporal shifts. Overall, they find the expected results: responses in each of the two neural populations are predictive of responses in the other, more so when the stimulus is not controlled than when it is, and with sometimes different results for different stimulus classes (e.g., gratings vs. natural images).

Strengths:

(1) Use of existing data.

(2) Addresses an interesting question.

Weaknesses:

Unfortunately, the method falls short of the state of the art: both generalized linear models (GLMs), which have been used in similar contexts for at least 20 years (see the many papers, both theoretical and applied to neural population data, by e.g. Simoncelli, Paninsky, Pillow, Schwartz, and many colleagues dating back to 2004), and the extension of Granger causality to point processes (e.g. Kim et al. PLoS CB 2011). Both approaches are substantially superior to what is proposed in the manuscript, since they enforce non-negativity for spike rates (the importance of which can be seen in Figure 2AB), and do not require unnecessary coarse-graining of the data by binning spikes (the 200 ms time bins are very long compared to the time scale on which communication between closely connected neuronal populations within an area, or between related areas, takes place).

In terms of analysis results, the work in the manuscript presents some expected and some less expected results. However, because the monkey data are based on only one monkey (misleadingly, the manuscript consistently uses the plural "monkeys"), none of the results specific to that monkey, nor the comparison of that one monkey to mice, are supported by robust data. One of the main results for mice (bimodality of explained variance values, mentioned in the abstract) does not appear to be quantified or supported by a statistical test and is only present in two out of three mice. Moreover, the two data sets differ in too many aspects to allow for any conclusions about whether the comparisons reflect differences in species (mouse vs. monkey), anatomy (L2/3-L4 vs. V1-V4), or recording technique (calcium imaging vs. extracellular spiking).

Reviewer #1 (Public review):

Summary:

Epiney et al. use single-nuclei RNA sequencing (snRNA-seq) to characterize the lineage of Type-2 (T2) neuroblasts (NBs) in the adult Drosophila brain. To isolate cells born from T2 NBs, the authors used a genetic tool that specifically allows the permanent labeling of T2-derived cell types, which are then FAC-sorted for snRNA-seq. This effective labeling approach also allows them to compare the isolated T2 lineage cells with T1-derived cell types by a simple exclusion method. The authors begin by describing a transcriptomic atlas for all T1 and T2-derived neuronal and glia clusters, reporting that the T2-derived lineage comprises 161 neuronal clusters, in contrast to the T1 lineage which comprises 114 of them. The authors then use the expression of VAChT, VGlut, Gad1, Tbh, Ple, SerT, and Tdc2 to show that T2 neuroblasts generate all major neuron classes of fast-acting neurotransmitters. Strikingly, they show that a subset of glia and neuronal clusters have disproportionate enrichment in males or females, suggesting that T2 neuroblasts generate sex-biased cell types. The authors then proceed to characterize neuropeptide expression across T2-derived neuronal clusters and argue that the same neuropeptide can be expressed across different cell types, while similar cell types can express distinct neuropeptides. The functional implication of both observations, however, remains to be tested. Furthermore, the authors describe combinatorial transcription factor (TF) codes that are correlated with neuropeptide expression for T2-derived neurons along with an overall TF code for all T2-derived cell types, both of which will serve as an important starting point for future investigations. Finally, the authors map well-studied neuronal types of the central complex to the clusters of their T2-derived snRNA-seq dataset. They use known marker combinations, bulk RNA-seq data and highly specific split-GAL4 driver lines to annotate their T2-derived atlas, establishing a comprehensive transcriptomic atlas that would guide future studies in this field.

Strengths:

This study provides an in-depth transcriptomic characterization of neurons and glia derived from Type-2 neuroblast lineages. The results of this manuscript offer several future directions to investigate the mechanisms of diversifying neuronal identity. The datasets of T1-derived and T2-derived cells will pave the way for studies focused on the functional analysis of combinatorial TF codes specifying cell identity, sex-based differences in neurogenesis and gliogenesis, the relationship between neuropeptide (co)expression and cell identity, and the differential contributions of distinct progenitor populations to the same cell type.

Weaknesses:

The study presents several important observations based on the characterization of Type II neuroblast-derived lineages. However, a mechanistic insight is missing for most observations. The idea that there is a sex-specific bias to certain T2-derived neurons and glial clusters is quite interesting, however, the functional significance of this observation is not tested or discussed extensively. Finally, the authors do not show whether the combinatorial TF code is indeed necessary for neuropeptide expression or if this is just a correlation due to cell identity being defined by TFs. Functional knockdown of some candidate TFs for a subset of neuropeptide-expressing cells would have been helpful in this case.

Reviewer #1 (Public review):

Summary:

Detecting unexpected epistatic interactions among multiple mutations requires a robust null expectation - or neutral function - that predicts the combined effects of multiple mutations on phenotype, based on the effects of individual mutations. This study assessed the validity of the product neutrality function, where the fitness of double mutants is represented as the multiplicative combination of the fitness of single mutants, in the absence of epistatic interactions. The authors utilized a comprehensive dataset on fitness, specifically measuring yeast colony size, to analyze epistatic interactions.

The study confirmed that the product function outperformed other neutral functions in predicting the fitness of double mutants, showing no bias between negative and positive epistatic interactions. Additionally, in the theoretical portion of the study, the authors applied a well-established theoretical model of bacterial cell growth to simulate the growth rates of both single and double mutants under various parameters. The simulations further demonstrated that the product function was superior to other functions in predicting the fitness of hypothetical double mutants. Based on these findings, the authors concluded that the product function is a robust tool for analyzing epistatic interactions in growth fitness and effectively reflects how growth rates depend on the combination of multiple biochemical pathways.

Strengths:

By leveraging a previously published extensive dataset of yeast colony sizes for single- and double-knockout mutants, this study validated the relevance of the product function, commonly used in genetics to analyze epistatic interactions. The finding that the product function provides a more reliable prediction of double-mutant fitness compared to other neutral functions offers significant value for researchers studying epistatic interactions, particularly those using the same dataset.

Notably, this dataset has previously been employed in studies investigating epistatic interactions using the product neutrality function. The current study's findings affirm the validity of the product function, potentially enhancing confidence in the conclusions drawn from those earlier studies. Consequently, both researchers utilizing this dataset and readers of previous research will benefit from the confirmation provided by this study's results.

Weaknesses:

This study exhibits several significant logical flaws, primarily arising from the following issues: a failure to differentiate between distinct phenotypes, instead treating them as identical; an oversight of the substantial differences in the mechanisms regulating cell growth between prokaryotes and eukaryotes; and the adoption of an overly specific and unrealistic set of assumptions in the mutation model. Additionally, the study fails to clearly address its stated objective-investigating the mechanistic origin of the multiplicative model. Although it discusses conditions under which deviations occur, it falls short of achieving its primary goal. Moreover, the paper includes misleading descriptions and unsubstantiated reasoning, presented without proper citations, as if they were widely accepted facts. Readers should consider these issues when evaluating this paper. Further details are discussed below.

(1) Misrepresentation of the dataset and phenotypes

The authors analyze a dataset on the fitness of yeast mutants, describing it as representative of the Malthusian parameter of an exponential growth model. However, they provide no evidence to support this claim. They assert that the growth of colony size in the dataset adheres to exponential growth kinetics; in contrast, it is known to exhibit linear growth over time, as indicated in [Supplementary Note 1 of https://doi.org/10.1038/nmeth.1534]. Consequently, fitness derived from colony size should be recognized as a different metric and phenotype from the Malthusian parameter. Equating these distinct phenotypes and fitness measures constitutes a fundamental error, which significantly compromises the theoretical discussions based on the Malthusian parameter in the study.

(2) Misapplication of prokaryotic growth models

The study attempts to explain the mechanistic origin of the multiplicative model observed in yeast colony fitness using a bacterial cell growth model, particularly the Scott-Hwa model. However, the application of this bacterial model to yeast systems lacks valid justification. The Scott-Hwa model is heavily dependent on specific molecular mechanisms such as ppGpp-mediated regulation, which plays a crucial role in adjusting ribosome expression and activity during translation. This mechanism is pivotal for ensuring the growth-dependency of the ribosome fraction in the proteome, as described in [https://doi.org/10.1073/pnas.2201585119]. Unlike bacteria, yeast cells do not possess this regulatory mechanism, rendering the direct application of bacterial growth models to yeast inappropriate and potentially misleading. This fundamental difference in regulatory mechanisms undermines the relevance and accuracy of using bacterial models to infer yeast colony growth dynamics.

If the authors intend to apply a growth model with macroscopic variables to yeast double-mutant experimental data, they should avoid simply repurposing a bacterial growth model. Instead, they should develop and rigorously validate a yeast-specific growth model before incorporating it into their study.

(3) Overly specific assumptions in the theoretical model

The theoretical model in question assumes that two mutations affect only independent parameters of specific biochemical processes, an overly restrictive premise that undermines its ability to broadly explain the occurrence of the multiplicative model in mutations. Additionally, experimental evidence highlights significant limitations to this approach. For example, in most viable yeast deletion mutants with reduced growth rates, the expression of ribosomal proteins remains largely unchanged, in direct contradiction to the predictions of the Scott-Hwa model, as indicated in [https://doi.org/10.7554/eLife.28034]. This discrepancy emphasizes that the Scott-Hwa model and its derivatives do not reliably explain the growth rates of mutants based on current experimental data, suggesting that these models may need to be reevaluated or alternative theories developed to more accurately reflect the complex dynamics of mutant growth.

(4) Lack of clarity on the mechanistic origin of the multiplicative model

The study falls short of providing a definitive explanation for its primary objective: elucidating the "mechanistic origin" of the multiplicative model. Notably, even in the simplest case involving the Scott-Hwa model, the underlying mechanistic basis remains unexplained, leaving the central research question unresolved. Furthermore, the study does not clearly specify what types of data or models would be required to advance the understanding of the mechanistic origin of the multiplicative model. This omission limits the study's contribution to uncovering the biological principles underlying the observed fitness patterns.

Reviewer #1 (Public review):

This study is focused on identifying unique, innovative surface markers for mature Achilles tendons by combining the latest multi-omics approaches and in vitro evaluation, which would address the knowledge gap of the controversial identity of TPSCs with unspecific surface markers. The use of multi-omics technologies, in vivo characterization, in vitro standard assays of stem cells, and in vitro tissue formation is a strength of this work and could be applied for other stem cell quantification in musculoskeletal research. The evaluation and identification of Cd55 and Cd248 in TPSCs have not been conducted in tendons, which is considered innovative. Additionally, the study provided solid sequencing data to confirm co-expressions of Cd55 and Cd248 with other well-described surface markers such as Ly6a, Tpp3, Pdgfra, and Cd34. Generally, the data shown in the manuscript support the claims that the identified surface antigens mark TPSCs in juvenile tendons.

However, there are missing links between scientific questions aimed to be addressed in Introduction and Methodology/Results. If the study focuses on unsatisfactory healing responses of mature tendons and understanding of mature TPSCs, at least mature Achilles tendons from more than 12-week-old mice and their comparison with tendons from juvenile/neonatal mice should be conducted. However, either 2-week or 6-week-old mice, used for characterization here, are not skeletally mature, Additionally, there is a lack of complete comparison of TPSCs between 2-week and 6-week-old mice in the transcriptional and epigenetic levels.

In order to distinguish TPSCs and characterize their epigenetic activities, the authors used scRNA-seq, snRNA-seq, and snATAC-seq approaches. The integration, analysis, and comparison of sequencing data across assays and/or time points is confusing and incomplete. For example, it should be more comprehensive to integrate both scRNA-seq and snRNA-seq data (if not, why both assays were used for Achilles tendons of both 2-week and 6-week timepoints). snRNA-seq and snATAC-seq data of 6-week-old mice were separately analyzed. No comparison of difference and similarity of TPSCs of 2-week and 6-week-old mice was conducted.

Given the goal of this work to identify specific TPSC markers, the specificity of Cd55 and Cd248 for TPSCs is not clear. First, based on the data shown here, Cd55 and Cd248 mark the same cell population which is identified by Ly6a, TPPP3, and Pdgfra. Although, for instance, Cd34 is expressed by other tissues as discussed here, no data/evidence is provided by this work showing that Cd55 and Cd248 are not expressed by other musculoskeletal tissues/cells. Second, the immunostaining of Cd55 and Cd248 doesn't support their specificity. What is the advantage of using Cd55 and Cd248 for TPSCs compared to using other markers?

Reviewer #1 (Public review):

This manuscript presents an interesting new framework (VARX) for simultaneously quantifying effective connectivity in brain activity during sensory stimulation and how that brain activity is being driven by that sensory stimulation. The core idea is to combine the Vector Autoregressive model that is often used to infer Granger-causal connectivity in brain data with an encoding model that maps the features of a sensory stimulus to that brain data. The authors do a nice job of explaining the framework. And then they demonstrate its utility through some simulations and some analysis of real intracranial EEG data recorded from subjects as they watched movies. They infer from their analyses that the functional connectivity in these brain recordings is essentially unaltered during movie watching, that accounting for the driving movie stimulus can protect one against misidentifying brain responses to the stimulus as functional connectivity, and that recurrent brain activity enhances and prolongs the putative neural responses to a stimulus.

This manuscript presents an interesting new framework (VARX) for simultaneously quantifying effective connectivity in brain activity during sensory stimulation and how that brain activity is being driven by that sensory stimulation. Overall, I thought this was an interesting manuscript with some rich and intriguing ideas. That said, I had some concerns also - one potentially major - with the inferences drawn by the authors on the analyses that they carried out.

Main comments:

(1) My primary concern with the way the manuscript is written right now relates to the inferences that can be drawn from the framework. In particular, the authors want to assert that, by incorporating an encoding model into their framework, they can do a better job of accounting for correlated stimulus-driven activity in different brain regions, allowing them to get a clearer view of the underlying innate functional connectivity of the brain. Indeed, the authors say that they want to ask "whether, after removing stimulus-induced correlations, the intrinsic dynamic itself is preserved". This seems a very attractive idea indeed. However, it seems to hinge critically on the idea of fitting an encoding model that fully explains all of the stimulus-driven activity. In other words, if one fits an encoding model that only explains some of the stimulus-driven response, then the rest of the stimulus-driven response still remains in the data and will be correlated across brain regions and will appear as functional connectivity in the ongoing brain dynamics - according to this framework. This residual activity would thus be misinterpreted. In the present work, the authors parameterize their stimulus using fixation onsets, film cuts, and the audio envelope. All of these features seem reasonable and valid. However, they surely do not come close to capturing the full richness of the stimuli, and, as such, there is surely a substantial amount of stimulus-driven brain activity that is not being accounted for by their "B" model and that is being absorbed into their "A" model and misinterpreted as intrinsic connectivity. This seems to me to be a major limitation of the framework. Indeed, the authors flag this concern themselves by (briefly) raising the issue in the first paragraph of their caveats section. But I think it warrants much more attention and discussion.

(2) Related to the previous comment, the authors make what seems to me to be a complex and important point on page 6 (of the pdf). Specifically, they say "Note that the extrinsic effects captured with filters B are specific (every stimulus dimension has a specific effect on each brain area), whereas the endogenous dynamic propagates this initial effect to all connected brain areas via matrix A, effectively mixing and adding the responses of all stimulus dimensions. Therefore, this factorization separates stimulus-specific effects from the shared endogenous dynamic." It seems to me that the interpretation of the filter B (which is analogous to the "TRF") for the envelope, say, will be affected by the fact that the matrix A is likely going to be influenced by all sorts of other stimulus features that are not included in the model. In other words, residual stimulus-driven correlations that are captured in A might also distort what is going on in B, perhaps. So, again, I worry about interpreting the framework unless one can guarantee a near-perfect encoding model that can fully account for the stimulus-driven activity. I'd love to hear the authors' thoughts on this. (On this issue - the word "dominates" on page 12 seems very strong.)

(3) Regarding the interpretation of the analysis of connectivity between movies and rest... that concludes that the intrinsic connectivity pattern doesn't really differ. This is interesting. But it seems worth flagging that this analysis doesn't really account for the specific dynamics in the network that could differ quite substantially between movie watching and rest, right? At the moment, it is all correlational. But the dynamics within the network could be very different between stimulation and rest I would have thought.

(4) I didn't really understand the point of comparing the VARX connectivity estimate with the spare-inverse covariance method (Figure 2D). What was the point of this? What is a reader supposed to appreciate from it about the validity or otherwise of the VARX approach?

(5) I think the VARX model section could have benefitted a bit from putting some dimensions on some of the variables. In particular, I struggled a little to appreciate the dimensionality of A. I am assuming it has to involve both time lags AND electrode channels so that you can infer Granger causality (by including time) between channels. Including a bit more detail on the dimensionality and shape of A might be helpful for others who want to implement the VARX model.

(6) A second issue I had with the inferences drawn by the authors was a difficulty in reconciling certain statements in the manuscript. For example, in the abstract, the authors write "We find that the recurrent connectivity during rest is largely unaltered during movie watching." And they also write that "Failing to account for ... exogenous inputs, leads to spurious connections in the intrinsic "connectivity".

Reviewer #1 (Public review):

Summary:

This work seeks to predict differences in neural function and behavior between male and hermaphrodite C. elegans by comparing their nervous system maps of synaptic wiring. The authors then seek to validate some of their predictions by measuring differences in neural activity or behavior, including in response to neuron-specific genetic manipulations. In particular, the authors focus on the role of neuron AVA which has notable differences in its connectivity between the male and hermaphrodite, and they use this and behavior measurements to argue for a role of AVA in mate-searching behavior in males.

Strengths:

A major strength of this work is its approach to investigating differences in wiring between males and hermaphrodites in a systematic and quantitative way. The work laudably takes advantage of recently available comprehensive connectomes, including across sexes of the same species, and applies concepts from network science to mining their differences. Another strength of the work is that it supplements network analysis with measurements of behavior, including with cell-specific genetic manipulations. The measurements and analysis will be of value to the scientific community.

Weaknesses:

The evidence to support conclusions about the special relationship between differences in AVA's wiring and male mate-finding appears incomplete. The authors selected AVA based on changes in wiring and then observed a decrease in male chemotaxis towards hermaphrodites for animals in which neuron AVA is inhibited. This is presented as evidence that specifically AVA is important for mate-finding, and therefore that changes in wiring inform changes in function. But given AVA's known role in all reversal-related locomotion, it is important to more forcefully rule out an alternative hypothesis that the observed deficits in mate-finding could be explained by any reversal circuitry motor defect (including those without wiring differences), rather than specifically attributed to AVA and its wiring. Similarly, more evidence is needed to show that deficits in reversal circuitry preferentially affect mate-seeking compared to other goal-directed navigation behaviors.

There are some areas where methods would benefit from further justification or clarification. For example, the work would benefit from better justification for selecting sub-networks to study, or for combining bilaterally symmetric neurons. More details are also needed to better interpret calcium imaging studies, such as details about the indicator and illumination wavelength and intensity.

Finally, there are some weaknesses inherent to the entire field of connectomic analysis that are necessarily also present here. For example, it is unclear how to weight the relative contributions of chemical versus electrical gap junctions when performing analyses of the wiring diagram, and the choice could potentially influence results. The wiring diagram also lacks information about timescales of neural dynamics or the role of neuromodulators or other molecular details that may influence the strength or function of various connections, and this poses a major challenge for predicting neural dynamics from neural wiring. For example, in their neural dynamics simulation, the authors assume that all neurons have the same conductance and reversal potentials - a standard practice - despite known diversity among neurons that limits the usefulness of this approach. It will be helpful to further acknowledge these limitations of the broader field.

Reviewer #2 (Public review):

Summary:

This study presents an important finding that the activation of TFEB by sulforaphane (SFN) could promote lysosomal exocytosis and biogenesis in NPC, suggesting a potential mechanism by SFN for the removal of cholesterol accumulation, which may contribute to the development of new therapeutic approaches for NPC treatment.

Strengths:

The cell-based assays are convincing, utilizing appropriate and validated methodologies to support the conclusion that SFN facilitates the removal of lysosomal cholesterol via TFEB activation.

Comments on revisions:

The authors have addressed most of my questions. I have only one minor technical point to emphasize, which does not affect the overall strength of the evidence for this project.

The pKa values of pHrodo Green (P35368, pKa=6.757) and pHrodo Red-Dex (P10361, pKa=6.816) are very similar. Prof. Xu's article, cited in the response letter (Hu, Li et al. 2022), is an excellent example of lysosomal pH measurement. He used LysoTracker Red DND-99 for a rough estimation of lysosomal acidity, and for accurate monitoring of lysosomal pH, he employed the ratiometric OG488-dex (pKa 4.6).

Reviewer #1 (Public review):

Fuchs describes a novel method of enzymatic protein-protein conjugation using the enzyme Connectase. The author is able to make this process irreversible by screening different Connectase recognition sites to find an alternative sequence that is also accepted by the enzyme. They are then able to selectively render the byproduct of the reaction inactive, preventing the reverse reaction, and add the desired conjugate with the alternative recognition sequence to achieve near-complete conversion. I agree with the authors that this novel enzymatic protein fusion method has several applications in the field of bioconjugation, ranging from biophysical assay conduction to therapeutic development. Previously the author has published on the discovery of the Connectase enzymes and has shown its utility in tagging proteins and detecting them by in-gel fluorescence. They now extend their work to include the application of Connectase in creating protein-protein fusions, antibody-protein conjugates, and cyclic/polymerized proteins. As mentioned by the author, enzymatic protein conjugation methods can provide several benefits over other non-specific and click chemistry labeling methods. Connectase specifically can provide some benefits over the more widely used Sortase, depending on the nature of the species that is desired to be conjugated. Overall, this method provides a novel, reproducible way to enzymatically create protein-protein conjugates.

The manuscript is well-written and will be of interest to those who are specifically working on chemical protein modifications and bioconjugation.

Comments on revisions:

The authors have improved the manuscript significantly by clarifying the questions raised adding new text, providing additional references and/or adding additional data. The thorough study and efficiency of the method for enzymatic protein-protein conjugation using the enzyme Connectase warrants publication of this manuscript in its current form.

Reviewer #1 (Public review):

Summary:

In this manuscript, Fuchsberger et al. demonstrate a set of experiments which ultimately identifies the de novo synthesis of GluA1-, but not GluA2-containing Ca2+ permeable AMPA receptors as a key driver of dopamine-dependent LTP (DA-LTP) during conventional post-before-pre spike-timing dependent (t-LTD) induction. The authors further identify adenylate cyclase 1/8, cAMP, and PKA as the crucial mitigators of these actions. While some comments have been identified below, the experiments presented are thorough and address the aims of the manuscript, figures are presented clearly (with minor comments), and experimental samples sizes and statistical analyses are suitable. Suitable controls have been utilized to confirm the role of Ca2+ permeable AMPAR. This work provides a valuable step forward built on convincing data towards understanding the underlying mechanisms of spike-timing dependent plasticity and dopamine.

Strengths:

Appropriate controls were used.

The flow of data presented is logical and easy to follow.

The quality of the data is solid.

Weaknesses:

Our concerns raised within the first round of review have been appropriately addressed by the authors.

Reviewer #1 (Public review):

Summary:

The paper presents a model for sequence generation in the zebra finch HVC, which adheres to cellular properties measured experimentally. However, the model is fine-tuned and exhibits limited robustness to noise inherent in the inhibitory interneurons within the HVC, as well as to fluctuations in connectivity between neurons. Although the proposed microcircuits are introduced as units for sub-syllabic segments (SSS), the backbone of the network remains a feedforward chain of HVC_RA neurons, similar to previous models.

Strengths:

The model incorporates all three of the major types of HVC neurons. The ion channels used and their kinetics are based on experimental measurements. The connection patterns of the neurons are also constrained by the experiments.

Weaknesses:

The model is described as consisting of micro-circuits corresponding to SSS. This presentation gives the impression that the model's structure is distinct from previous models, which connected HVC_RA neurons in feedforward chain networks (Jin et al 2007, Li & Greenside, 2006; Long et al 2010; Egger et al 2020). However, the authors implement single HVC_RA neurons into chain networks within each micro-circuit and then connect the end of the chain to the start of the chain in the subsequent micro-circuit. Thus, the HVC_RA neuron in their model forms a single-neuron chain. This structure is essentially a simplified version of earlier models.

In the model of the paper, the chain network drives the HVC_I and HVC_X neurons. The role of the micro-circuits is more significant in organizing the connections: specifically, from HVC_RA neurons to HVC_I neurons, and from HVC_I neurons to both HVC_X and HVC_RA neurons.

How useful is this concept of micro-circuits? HVC neurons fire continuously even during the silent gaps. There are no SSS during these silent gaps.

A significant issue of the current model is that the HVC_RA to HVC_RA connections require fine-tuning, with the network functioning only within a narrow range of g_AMPA (Figure 2B). Similarly, the connections from HVC_I neurons to HVC_RA neurons also require fine-tuning. This sensitivity arises because the somatic properties of HVC_RA neurons are insufficient to produce the stereotypical bursts of spikes observed in recordings from singing birds, as demonstrated in previous studies (Jin et al 2007; Long et al 2010). In these previous works, to address this limitation, a dendritic spike mechanism was introduced to generate an intrinsic bursting capability, which is absent in the somatic compartment of HVC_RA neurons. This dendritic mechanism significantly enhances the robustness of the chain network, eliminating the need to fine-tune any synaptic conductances, including those from HVC_I neurons (Long et al 2010).

Why is it important that the model should NOT be sensitive to the connection strengths?

First, the firing of HVC_I neurons is highly noisy and unreliable. HVC_I neurons fire spontaneous, random spikes under baseline conditions. During singing, their spike timing is imprecise and can vary significantly from trial to trial, with spikes appearing or disappearing across different trials. As a result, their inputs to HVC_RA neurons are inherently noisy. If the model relies on precisely tuned inputs from HVC_I neurons, the natural fluctuations in HVC_I firing would render the model non-functional. The authors should incorporate noisy HVC_I neurons into their model to evaluate whether this noise would render the model non-functional.

Second, Kosche et al. (2015) demonstrated that reducing inhibition by suppressing HVC_I neuron activity makes HVC_RA firing less sparse but does not compromise the temporal precision of the bursts. In this experiment, the local application of gabazine should have severely disrupted HVC_I activity. However, it did not affect the timing precision of HVC_RA neuron firing, emphasizing the robustness of the HVC timing circuit. This robustness is inconsistent with the predictions of the current model, which depends on finely tuned inputs and should, therefore, be vulnerable to such disruptions.

Third, the reliance on fine-tuning of HVC_RA connections becomes problematic if the model is scaled up to include groups of HVC_RA neurons forming a chain network, rather than the single HVC_RA neurons used in the current work. With groups of HVC_RA neurons, the summation of presynaptic inputs to each HVC_RA neuron would need to be precisely maintained for the model to function. However, experimental evidence shows that the HVC circuit remains functional despite perturbations, such as a few degrees of cooling, micro-lesions, or turnover of HVC_RA neurons. Such robustness cannot be accounted for by a model that depends on finely tuned connections, as seen in the current implementation.

The authors examined how altering the channel properties of neurons affects the activity in their model. While this approach is valid, many of the observed effects may stem from the delicate balancing required in their model for proper function.

In the current model, HVC_X neurons burst as a result of rebound activity driven by the I_H current. Rebound bursts mediated by the I_H current typically require a highly hyperpolarized membrane potential. However, this mechanism would fail if the reversal potential of inhibition is higher than the required level of hyperpolarization. Furthermore, Mooney (2000) demonstrated that depolarizing the membrane potential of HVC_X neurons did not prevent bursts of these neurons during forward playback of the bird's own song, suggesting that these bursts (at least under anesthesia, which may be a different state altogether) are not necessarily caused by rebound activity. This discrepancy should be addressed or considered in the model.

Some figures contain direct copies of figures from published papers. It is perhaps a better practice to replace them with schematics if possible.

Reviewer #1 (Public review):

Summary:

Structural colors (SC) are based on nanostructures reflecting and scattering light and producing optical wave interference. All kinds of living organisms exhibit SC. However, understanding the molecular mechanisms and genes involved may be complicated due to the complexity of these organisms. Hence, bacteria that exhibit SC in colonies, such as Flavobacterium IR1, can be good models.

Based on previous genomic mining and co-occurrence with SC in flavobacterial strains, this article focuses on the role of a specific gene, moeA, in SC of Flavobacterium IR1 strain colonies on an agar plate. moeA is involved in the synthesis of the molybdenum cofactor, which is necessary for the activity of key metabolic enzymes in diverse pathways.

The authors clearly showed that the absence of moeA shifts SC properties in a way that depends on the nutritional conditions. They further bring evidence that this effect was related to several properties of the colony, all impacted by the moeA mutant: cell-cell organization, cell motility and colony spreading, and metabolism of complex carbohydrates. Hence, by linking SC to a single gene in appearance, this work points to cellular organization (as a result of cell-cell arrangement and motility) and metabolism of polysaccharides as key factors for SC in a gliding bacterium. This may prove useful for designing molecular strategies to control SC in bacterial-based biomaterials.

Strengths:

The topic is very interesting from a fundamental viewpoint and has great potential in the field of biomaterials.

The article is easy to read. It builds on previous studies with already established tools to characterize SC at the level of the flavobacterial colony. Experiments are well described and well executed. In addition, the SIBR-Cas method for chromosome engineering in Flavobacteria is the most recent and is a leap forward for future studies in this model, even beyond SC.

Weaknesses:

The paper appears a bit too descriptive and could be better organized. Some of the results, in particular the proteomic comparison, are not well exploited (not explored experimentally). In my opinion, the problem originates from the difficulty in explaining the link between the absence of moeA and the alterations observed at the level of colony spreading and polysaccharide utilization, and the variation in proteomic content.

First, the effect of moeA deletion on molybdenum cofactor synthesis should be addressed.

Second, as I was reading the entire manuscript, I kept asking myself if moeA (and by extension molybdenum cofactor) was really involved in SC or it was an indirect effect. For example, what if the absence of moeA alters the cell envelope because the synthesis of its building blocks is perturbed, then subsequently perturbates all related processes, including gliding motility and protein secretion? It would help to know if the effects on colony spreading and polysaccharide metabolism can be uncoupled. I don't think the authors discussed that clearly.

Reviewer #1 (Public review):

Summary:

The authors isolated and cultured pulmonary artery smooth muscle cells (PASMC) and pulmonary artery adventitial fibroblasts (PAAF) of the lung samples derived from the patients with idiopathic pulmonary arterial hypertension (PAH) and the healthy volunteers. They performed RNA-seq and proteomics analyses to detail the cellular communication between PASMC and PAAF, which are the main target cells of pulmonary vascular remodeling during the pathogenesis of PAH. The authors revealed that PASMC and PAAF retained their original cellular identity and acquired different states associated with the pathogenesis of PAH, respectively.

Strengths:

Although previous studies have shown that PASMC and PAAF cells each have an important role in the pathogenesis of PAH, there have been scarce reports focusing on the interactions between PASMC and PAAF. These findings may provide valuable information for elucidating the pathogenesis of pulmonary arterial hypertension.

Comments on revisions:

The authors adequately responded to my concerns and revised their manuscript to elaborate on the new data from new experiments and address my queries. Although some of the issues I initially raised could not be fully resolved, the revised manuscript has been significantly improved. This manuscript provides essential insights into the communications across the PASMCs and PAAFs in PAH. This would greatly interest various researchers in both basic and clinical fields.

Reviewer #2 (Public review):

Summary:

This paper from Sutlief et al. focuses on an apparent contradiction observed in experimental data from two related types of pursuit-based decision tasks. In "forgo" decisions, where the subject is asked to choose whether or not to accept a presented pursuit, after which they are placed into a common inter-trial interval, subjects have been shown to be nearly optimal in maximizing their overall rate of reward. However, in "choice" decisions, where the subject is asked which of two mutually-exclusive pursuits they will take, before again entering a common inter-trial interval, subjects exhibit behavior that is believed to be sub-optimal. To investigate this contradiction, the authors derive a consistent reward-maximizing strategy for both tasks using a novel and intuitive geometric approach that treats every phase of a decision (pursuit choice and inter-trial interval) as vectors. From this approach, the authors are able to show that previously-reported examples of sub-optimal behavior in choice decisions are in fact consistent with a reward-maximizing strategy. Additionally, the authors are able to use their framework to deconstruct the different ways the passage of time impacts decisions, demonstrating the time cost contains both an opportunity cost and an apportionment cost, as well as examine how a subject's misestimation of task parameters impacts behavior.

Strengths:

The main strength of the paper lies in the authors' geometric approach to studying the problem. The authors chose to simplify the decision process by removing the highly technical and often cumbersome details of evidence accumulation that is common in most of the decision-making literature. In doing so, the authors were able to utilize a highly accessible approach that is still able to provide interesting insights into decision behavior and the different components of optimal decision strategies.

Weaknesses:

The authors have made great improvements to the strength of their evidence through revision, especially concerning their treatment of apportionment cost. However, I am concerned that the story this paper tells is far from concise, and that this weakness may limit the paper's audience and overall impact. I would strongly suggest making an effort to tighten up the language and structure of the paper to improve its readability and accessibility.

Reviewer #1 (Public review):

Summary:

The authors investigate the role of HSPA2 during mouse preimplantation development. Knocking down HSPA2 in zygotes, the authors describe lower chances of developing into blastocysts, which show a reduced number of inner cell mass cells. They find that HSPA2 mRNA and protein levels show some heterogeneity among blastomeres at the 4-cell stage and propose that HSPA2 could contribute to skewing their relative contribution to embryonic lineages. To test this, the authors try to reduce HSPA2 expression in one of the 2-cell stage blastomere and propose that it biases their contribution to towards extra-embryonic lineages. To explain this, the authors propose that HSPA2 would interact with CARM1, which controls chromatin accessibility around genes regulating differentiation into embryonic lineage.

Strengths:

(1) The study offers simple and straightforward experiments with large sample sizes.

(2) Unlike most studies in the field, this research often relies on both mRNA and protein levels to analyse gene expression and differentiation.

Weaknesses:

(1) Image and statistical analyses are not well described.

(2) The functionality of the overexpression construct is not fully validated.

(3) Tracking of KD cells in embryos injected at the 2-cell stage with GFP is unclear.

(4) A key rationale of the study relies on measuring small differences in the levels of mRNA and proteins using semi-quantitative methods to compare blastomeres. As such, it is not possible to know whether those subtle differences are biologically meaningful. For example, the lowest HSPA2 level of the embryo with the highest level is much higher than the top cell from the embryo with the lowest level. What does this level mean then? Does this mean that some blastomeres grafted from strong embryos would systematically outcompete all other blastomeres from weaker embryos? That would be very surprising. I think the authors should be more careful and consider the lack of quantitative power of their approach before reaching firm conclusions. Although to be fair, the authors only follow a long trend of studies with the same intrinsic flaw of this approach.

(5) Some of the analyses on immunostaining do not take into account that this technique only allows for semi-quantitative measurements and comparisons.<br /> a) Some of the microscopy images are shown with an incorrect look-up table.<br /> b) Some of the schematics are incorrect and misleading.

Reviewer #1 (Public review):

Summary:

Boldt et al test several possible relationships between trandiagnostically-defined compulsivity and cognitive offloading in a large online sample. To do so, they develop a new and useful cognitive task to jointly estimate biases in confidence and reminder-setting. In doing so, they find that over-confidence is related to less utilization of reminder-setting, which partially mediates the negative relationship between compulsivity and lower reminder-setting. The paper thus establishes that, contrary to the over-use of checking behaviors in patients with OCD, greater levels of transdiagnostically-defined compulsivity predicts less deployment of cognitive offloading. The authors offer speculative reasons as to why (perhaps it's perfectionism in less clinically-severe presentations that lowers the cost of expending memory resources), and sets an agenda to understand the divergence in cognitive between clinical and nonclinical samples. Because only a partial mediation had robust evidence, multiple effects may be at play, whereby compulsivity impacts cognitive offloading via overconfidence and also by other causal pathways.

Strengths:

The study develops an easy-to-implement task to jointly measure confidence and replicates several major findings on confidence and cognitive offloading. The study uses a useful measure of cognitive offloading - the tendency to set reminders to augment accuracy in the presence of experimentally manipulated costs. Moreover, the utilizes multiple measures of presumed biases -- overall tendency to set reminders, the empirically estimated indifference point at which people engage reminders, and a bias measure that compares optimal indifference points to engage reminders relative to the empirically observed indifference points. That the study observes convergenence along all these measures strengthens the inferences made relating compulsivity to the under-use of reminder-setting. Lastly, the study does find evidence for one of several a priori hypotheses and sets a compelling agenda to try to explain why such a finding diverges from an ostensible opposing finding in clinical OCD samples and the over-use of cognitive offloading.

Weaknesses:

Although I think this design and study are very helpful for the field, I felt that a feature of the design might reduce the tasks's sensitivity to measuring dispositional tendencies to engage cognitive offloading. In particular, the design introduces prediction errors, that could induce learning and interfere with natural tendencies to deploy reminder-setting behavior. These PEs comprise whether a given selected strategy will be or not be allowed to be engaged. We know individuals with compulsivity can learn even when instructed not to learn (e.g., Sharp, Dolan and Eldar, 2021, Psychological Medicine), and that more generally, they have trouble with structure knowledge (eg Seow et al; Fradkin et al), and thus might be sensitive to these PEs. Thus, a dispositional tendency to set reminders might be differentially impacted for those with compulsivity after an NPE, where they want to set a reminder, but aren't allowed to. After such an NPE, they may avoid moreso the tendency to set reminders. Those with compulsivity likely have superstitious beliefs about how checking behaviors lead to a resolution of catastrophes, that might in part originate from inferring structure in the presence of noise or from purely irrelevant sources of information for a given decision problem.<br /> It would be good to know if such learning effects exist, if they're modulated by PE (you can imagine PEs are higher if you are more incentivized - e.g., 9 points as opposed to only 3 points - to use reminders, and you are told you cannot use them), and if this learning effect confounds the relationship between compulsivity and reminder-setting.

A more subtle point, I think this study can be more said to be an exploration than a deductive of test of a particular model -> hypothesis -> experiment. Typically, when we test a hypothesis, we contrast it with competing models. Here, the tests were two-sided because multiple models, with mutually exclusive predictions (over-use or under-use of reminders) were tested. Moreover, it's unclear exactly how to make sense of what is called the direct mechanism, which is supported by the partial (as opposed to complete) mediation.

Comments on revisions:

I have the following final comments for your manuscript revisions:

To improve the clarity of the work, I suggest a final note to the authors to say more explicitly that objective accuracy has a finer resolution *due to the number of "special circles" per trial* in their task. This task detail got lost in my read of the manuscript, and confused me with respect to the resolution of each accuracy measure. Similarly for clarification, they could point out that their exclusion criteria removes subjects that have lower OIP than their AIP analysis allows (which is good for comparison between OIP and AIP). Thus, it removes the possibility that very poor performing subjects (OIP) are forced to have a higher than actual AIP due to the range).

Reviewer #1 (Public review):

Summary:

You, Zhang et al. comprehensively characterize the long-term fates of mouse HSCs in the unperturbed setting using transposon-based lineage tracing for up to 2 years post-labeling. Their analyses reveal a complex heterogeneity of long-term fates, dominated by two behaviors: i) long-lived differentiation-biased clones, and ii) self-renewal & platelet-biased clones. They further identify two categories of multipotent progenitor clones, with one group showing a markedly reduced differentiation activity.

Strengths:

You et al. present a very comprehensive and high-resolution characterization of mouse hematopoietic clonal dynamics, with robust replicates, and technical prowess. The manuscript is beautifully written, with in-depth and clear explanations of the logic behind experimental design choices, and very well-thought-out interpretations of results.

Some of the results integrate well with past observations in the field, whereas many of them are quite unique and novel.

This will surely be a highly impactful study in the field of hematopoiesis and stem cell biology.

Weaknesses:

The authors trace hematopoiesis in situ, in a fully unbiased way for almost 2-years. They compare this time course with the last few years of Cre-LoxP-based tracing studies and they make an assumption that most hematopoiesis will be derived from some type of HSC at that point in time. They then use this assumption to support that what is being measured in their model are the long-term fates of HSCs (or at least cells that were HSC at the point of labeling). While this is a generally valid assumption, the short-lived nature of certain populations (myeloid cells, megakaryocytes) means that these cells are being produced in the context of a relatively aged environment by the time of sampling, which might change the properties of the system. In other words, the "steady-state" is always changing. It is important to read and interpret this manuscript with this in consideration.

Reviewer #1 (Public review):

Summary

Pyrazinamide (PZA) is a key drug in the anti-TB arsenal, yet despite over 50 years of clinical use, its precise mechanism of action remains unclear. This study offers valuable insights into the in vitro potentiating effect of PZA when used with exogenous oxidative agents. The authors suggest that oxidative stress, specifically thiol oxidation, may be a primary driver of PZA/POA's bactericidal activity. Although the work is substantial, conceptually innovative, and timely, the evidence supporting the authors' conclusions requires further investigation with additional controls and experiments to fully validate the proposed mechanism of action. Once revised, this work will undoubtedly be of significant interest to the TB drug discovery community and researchers focusing on mycobacterial diseases.

Strengths

The authors have long-standing experience in the field of PZA mode of action, with several publications that have been highly relevant to the field. They are particularly well aware of the literature, and this is clearly visible in the introduction of the manuscript which is beautifully articulated. The biological question(s) and their hypotheses are also well-formulated in the introduction section.

The understanding of PZA mode of action is a long-lasting question in the TB community, therefore studies reporting well-conducted research that aims at deciphering the underlying mechanism responsible for PZA peculiar activity is always appreciated. Since PZA/POA are poorly active in conventional 7H9 media, but very potent in cellulo or in vivo; looking at host-mediated stress that can eventually lead to an increased vulnerability is extremely relevant. In that context, most of the work has been focused on host-cell endolysosomal pH but very little information is available on other stress. Thus, investigating the contribution of oxidative stress and ROS as specific host environments that might contribute to PZA/POA activity is overall novel and conceptually very interesting.

To address this question, the authors combine multiple approaches including conventional antimicrobial susceptibility profiling, CFU-based counting, and checkerboard assays to report the potentiating effect of PZA pre-treatment on hydrogen peroxide- and diamide-mediated antibacterial action. The use of multiple reference strains including Mtb H37Ra, Mtb H37Rv, M.bovis BCG, and M.bovis BCG::pncA is a great asset of the manuscript, even though they might have been more appropriately used to get further mechanistical insights on the proposed model of action. The findings are reported in 4 major figures that are clear and in an order that appears logical for the understanding of the story.

Weaknesses

Although the manuscript is conceptually very interesting and contains intriguing results, it sometimes fails to fully convince and some additional controls/experiments might help to better back up the authors' claims and really strengthen the study. Indeed, some conclusions seem premature therefore leading to some molecular assumptions regarding a potential mode of action that is not fully supported by the presented data.<br /> The rationale behind some of the experiments is not always clearly explained which makes difficult to follow the authors ideas, the biological hypothesis/model that they test, and therefore the overall scientific story.

The authors conclude their study by proposing a mechanism by which the active form of the drug POA acts in concert with exogenous ROS to promote cellular oxidative damage. This is tested within two models of macrophage infection where they propose that IFN-γ mediated ROS production is essential for PZA activity. Unfortunately, the in cellulo part presents some weaknesses and inconsistencies that the authors need to carefully address.

Finally, the in vitro experiments performed in this manuscript mainly report that PZA pre-treatment increases H2O2-mediated killing or inhibition. There is no direct evidence that clearly shows that oxidative stress drives the potent bactericidal activity of PZA. In these settings, the oxidative stress is always applied after PZA pre-treatment and is therefore likely displaying the major lethal effect.

Reviewer #1 (Public review):

Summary:

The question of how central nervous system (CNS) lamination defects affect functional integrity is an interesting topic, though it remains a subject of debate. The authors focused on the retina, which is a relatively simple yet well-laminated tissue, to investigate the impact of afadin - a key component of adherens junctions on retinal structure and function. Their findings show that the loss of afadin leads to significant disruptions in outer retinal lamination, affecting the morphology and localization of photoreceptors and their synapses, as illustrated by high-quality images. Despite these severe changes, the study found that some functions of the retinal circuits, such as the ability to process light stimuli, could still be partially preserved. This research offers new insights into the relationship between retinal lamination and neural circuit function, suggesting that altered retinal morphology does not completely eliminate the capacity for visual information processing.

Strengths:

The retina serves as an excellent model for investigating lamination defects and functional integrity due to its relatively simple yet well-organized structure, along with the ease of analyzing visual function. The images depicting outer retinal lamination, as well as the morphology and localization of photoreceptors and their synapses, are clear and well-described. The paper is logically organized, progressing from structural defects to functional analysis. Additionally, the manuscript includes a comprehensive discussion of the findings and their implications.

Weaknesses:

While this work presents a wealth of descriptive data, it lacks quantification, which would help readers fully understand the findings and compare results with those from other studies. Furthermore, the molecular mechanisms underlying the defects caused by afadin deletion were not explored, leaving the role of afadin and its intracellular signaling pathways in retinal cells unclear. Finally, the study relied solely on electrophysiological recordings to demonstrate RGC function, which may not be robust enough to support the conclusions. Incorporating additional experiments, such as visual behavior tests, would strengthen the overall conclusions.

Reviewer #1 (Public review):

Summary:

In this paper, Derkaloustian et. al look at the important topic of what affects fine touch perception. The observations that there may be some level of correlation with instabilities are intriguing. They attempted to characterize different materials by counting the frequency (occurrence #, not of vibration) of instabilities at various speeds and forces of a PDMS slab pulled lengthwise over the material. They then had humans make the same vertical motion to discriminate between these samples. They correlated the % correct in discrimination with differences in frequency of steady sliding over the design space as well as other traditional parameters such as friction coefficient and roughness. The authors pose an interesting hypothesis and make an interesting observation about the occurrences of instability regimes in different materials while in contact with PDMS, which is interesting for the community to see in the publication. It should be noted that the finger is complex, however, and there are many factors that may be quite oversimplified with the use of the PDMS finger, and the consideration and discounting of other parameters are not fully discussed in the main text or SI. Most importantly, however, the conclusions as stated do not align with the primary summary of the data in Figure 2.

Strengths:

The strength of this paper is in its intriguing hypothesis and important observation that instabilities may contribute to what humans are detecting as differences in these apparently similar samples.

Weaknesses:

The most important weakness is that the findings do not support the statements of findings made in the abstract. Of specific note in this regard is the primary correlation in Figure 2B between SS (steady sliding) and percent correct discrimination. While the statistical test shows significance (and is interesting!), the R-squared value is 0.38, while the R-squared value for the "Friction Coefficient vs. Percent Correct" plot has an R-squared of 0.6 and a p-value of < 0.01 (including Figure 2B). This suggests that the results do not support the claim in the abstract: "We found that participant accuracy in tactile discrimination was most strongly correlated with formations of steady sliding, and response times were negatively correlated with stiction spikes. Conversely, traditional metrics like surface roughness or average friction coefficient did not predict tactile discriminability." This is the most fundamental weakness of this paper.

Along the same lines, other parameters that were considered such as the "Percent Correct vs. Difference in Sp" and "Percent Correct vs. Difference in SFW" were not plotted for consideration in the SI. It would be helpful to compare these results with the other three metrics in order to fully understand the relationships. Other parameters such as stiction magnitude and differences in friction coefficient over the test space could also be important and interesting.

Beyond this fundamental concern, there is a weakness in the representativeness of the PDMS finger, the vertical motion, and the speed of sliding to real human exploration. The real finger has multiple layers with different moduli. In fact, the stratum corneum cells, which are the outer layer at the interface and determine the friction, have a much higher modulus than PDMS. In addition, the slanted position of the finger can cause non-uniform pressures across the finger. Both can contribute to making the PDMS finger have much more stick-slip than a real finger. In fact, if you look at the regime maps, there is very little space that has steady sliding. This does not represent well human exploration of surfaces. We do not tend to use a force and velocity that will cause extensive stick-slip (frequent regions of 100% stick-slip) and, in fact, the speeds used in the study are on the slow side, which also contributes to more stick-slip. At higher speeds and lower forces, all of the materials had steady sliding regions. Further, on these very smooth surfaces, the friction and stiction are more complex and cannot dismiss considerations such as finger material property change with sweat pore occlusion and sweat capillary forces. Also, the vertical motion of both the PDMS finger and the instructed human subjects is not the motion that humans typically use to discriminate between surfaces. Finally, fingerprints may not affect the shape and size of the contact area, but they certainly do affect the dynamic response and detection of vibrations.

This all leads to the critical question, why are friction, normal force, and velocity not measured during the measured human exploration and in a systematic study using the real human finger? The authors posed an extremely interesting hypothesis that humans may alter their speed to feel the instability transition regions. This is something that could be measured with a real finger but is not likely to be correlated accurately enough to match regime boundaries with such a simplified artificial finger.

Reviewer #1 (Public review):

This manuscript by Ori and colleagues investigates the role of Lmod1 in muscle stem cell activation and differentiation. The study begins with a time-course mass spectrometry analysis of primary muscle stem cells, identifying Lmod1 as a pro-myogenic candidate (Figure 1). While the initial approach is robust, the subsequent characterization lacks depth and clarity. Although the data suggest that Lmod1 promotes myogenesis, the underlying mechanisms remain vague, and key experiments are missing. Please find my comments below.

(1) The authors mainly rely on coarse and less-established readouts such as myotube length and spherical Myh-positive cells. More comprehensive and standard analyses, such as co-staining for Pax7, MyoD, and Myogenin, would allow quantification of quiescent, activated, and differentiating stem cells in knockdown and overexpression experiments. The exact stage at which Lmod1 functions (stem cell, progenitor, or post-fusion) is unclear due to the limited depth of the analysis. Performing similar experiments on cultured single EDL fibers would add valuable insights.

(2) In supplementary Figure 2E, the distinction between Hoechst-positive cells and total cell counts is unclear. The authors should clarify why Hoechst-positive cells increase and relabel "reserve cells," as the term is confusing without reading the legend.

(3) The specificity of Lmod1 and Sirt1 immunostaining needs validation using siRNA-treated samples, especially as these data form the basis of the mechanistic conclusions.

(4) The authors must test the effect of Lmod1 siRNA on Sirt1 localization, as only overexpression experiments are shown.

(5) In Figure S3, the biotin signal in LMOD2 samples appears weak. The authors need to address whether comparing LMOD1 and LMOD2 is valid given the apparent difference in reaction efficiency. It would also help to highlight where Sirt1 falls on the volcano plot in S3B.

(6) The immunostaining data suggest that Lmod1 remains cytoplasmic throughout differentiation, whereas Sirt1 shows transient cytoplasmic localization at day 1 of differentiation. The authors should explain why Sirt1 is not constantly sequestered if Lmod1's cytoplasmic localization is consistent. It is also unclear whether day 1 is the key time point for Lmod1 function, as its precise role during myogenesis remains ambiguous.

(7) The introduction does not sufficiently establish the motivation or knowledge gap this work aims to address. Instead, it reads like a narration of disparate topics in a single paragraph. The authors should clarify the statement in line 150, "since this protein has been...,".

Overall, while the identification of Lmod1 as a pro-myogenic factor is convincing, the mechanistic insights are insufficient, and the manuscript would benefit from addressing these concerns.

Reviewer #1 (Public review):

Summary:

The authors introduce a denoising-style model that incorporates both structure and primary-sequence embeddings to generate richer embeddings of peptides. My understanding is that the authors use ESM for the primary sequence embeddings, take resolved structures (or use structural predictions from AlphaFold when they're not available), then develop an architecture to combine these two with a loss that seems reminiscent of diffusion models or masked language model approaches. The embeddings can be viewed as ensemble-style embedding of the two levels of sequence information, or with AlphaFold, an ensemble of two methods (ESM+AlphaFold). The authors also gather external datasets to evaluate their approach and compare it to previous approaches. The approach seems promising and appears to out-compete previous methods at several tasks. Nonetheless, I have strong concerns about a lack of verbosity as well as exclusion of relevant methods and references.

Advances:

I appreciate the breadth of the analysis and comparisons to other methods. The authors separate tasks, models, and sizes of models in an intuitive, easy-to-read fashion that I find valuable for selecting a method for embedding peptides. Moreover, the authors gather two datasets for evaluating embeddings' utility for predicting thermostability. Overall, the work should be helpful for the field as more groups choose methods/pretraining strategies amenable to their goals, and can do so in an evidence-guided manner.

Considerations:

Primarily, a majority of the results and conclusions (e.g., Table 3) are reached using data and methods from ProteinGym, yet the best-performing methods on ProteinGym are excluded from the paper (e.g., EVE-based models and GEMME). In the ProteinGym database, these methods outperform ProtSSN models. Moreover, these models were published over a year---or even 4 years in the case of GEMME---before ProtSSN, and I do not see justification for their exclusion in the text.

Secondly, related to comparison of other models, there is no section in the methods about how other models were used, or how their scores were computed. When comparing these models, I think it's crucial that there are explicit derivations or explanations for the exact task used for scoring each method. In other words, if the pre-training is indeed the important advance of the paper, the paper needs to show this more explicitly by explaining exactly which components of the model (and previous models) are used for evaluation. Are the authors extracting the final hidden layer representations of the model, treating these as features, then using these features in a regression task to predict fitness/thermostability/DDG etc.? How are the model embeddings of other methods being used, since, for example, many of these methods output a k-dimensional embedding of a given sequence, rather than one single score that can be correlated with some fitness/functional metric. Summarily, I think the text is lacking an explicit mention of how these embeddings are being summarized or used, as well as how this compares to the model presented.

I think the above issues can mainly be addressed by considering and incorporating points from Li et al. 2024[1] and potentially Tang & Koo 2024[2]. Li et al.[1] make extremely explicit the use of pretraining for downstream prediction tasks. Moreover, they benchmark pretraining strategies explicitly on thermostability (one of the main considerations in the submitted manuscript), yet there is no mention of this work nor the dataset used (FLIP (Dallago et al., 2021)) in this current work. I think a reference and discussion of [1] is critical, and I would also like to see comparisons in line with [1], as [1] is very clear about what features from pretraining are used, and how. If the comparisons with previous methods were done in this fashion, this level of detail needs to be included in the text.

To conclude, I think the manuscript would benefit substantially from a more thorough comparison of previous methods. Maybe one way of doing this is following [1] or [2], and using the final embeddings of each method for a variety of regression tasks---to really make clear where these methods are performing relative to one another. I think a more thorough methods section detailing how previous methods did their scoring is also important. Lastly, TranceptEVE (or a model comparable to it) and GEMME should also be mentioned in these results, or at the bare minimum, be given justification for their absence.

[1] Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models, Francesca-Zhoufan Li, Ava P. Amini, Yisong Yue, Kevin K. Yang, Alex X. Lu bioRxiv 2024.02.05.578959; doi: https://doi.org/10.1101/2024.02.05.578959<br /> [2] Evaluating the representational power of pre-trained DNA language models for regulatory genomics, Ziqi Tang, Peter K Koo bioRxiv 2024.02.29.582810; doi: https://doi.org/10.1101/2024.02.29.582810

Comments on revisions:

My concerns have been addressed. What seems to remain are some semantical disagreements and I'm not sure that these will be answered here. Do MSAs and other embedding methods lead to some notable type of data leakage? Does this leakage qualify as "x-shot" learning under current definitions?

Reviewer #1 (Public review):

This manuscript makes a significant contribution to the field by exploring the dichotomy between chemical synaptic and gap junctional contributions to extracellular potentials. While the study is comprehensive in its computational approach, adding experimental validation, network-level simulations, and expanded discussion on implications would elevate its impact further.

Strengths:

Novelty and Scope:<br /> The manuscript provides a detailed investigation into the contrasting extracellular field potential (EFP) signatures arising from chemical synapses and gap junctions, an underexplored area in neuroscience.<br /> It highlights the critical role of active dendritic processes in shaping EFPs, pushing forward our understanding of how electrical and chemical synapses contribute differently to extracellular signals.

Methodological Rigor:<br /> The use of morphologically and biophysically realistic computational models for CA1 pyramidal neurons ensures that the findings are grounded in physiological relevance.<br /> Systematic analysis of various factors, including the presence of sodium, leak, and HCN channels, offers a clear dissection of how transmembrane currents shape EFPs.

Biological Relevance:<br /> The findings emphasize the importance of incorporating gap junctional inputs in analyses of extracellular signals, which have traditionally focused on chemical synapses.<br /> The observed polarity differences and spectral characteristics provide novel insights into how neural computations may differ based on the mode of synaptic input.

Clarity and Depth:<br /> The manuscript is well-structured, with a logical progression from synchronous input analyses to asynchronous and rhythmic inputs, ensuring comprehensive coverage of the topic.

Weaknesses and Areas for Improvement:

Generality and Validation:<br /> The study focuses exclusively on CA1 pyramidal neurons. Expanding the analysis to other cell types, such as interneurons or glial cells, would enhance the generalizability of the findings.<br /> Experimental validation of the computational predictions is entirely absent. Empirical data correlating the modeled EFPs with actual recordings would strengthen the claims.

Role of Active Dendritic Currents:<br /> The paper emphasizes active dendritic currents, particularly the role of HCN channels in generating outward currents under certain conditions. However, further discussion of how this mechanism integrates into broader network dynamics is warranted.

Analysis of Plasticity:<br /> While the manuscript mentions plasticity in the discussion, there are no simulations that account for activity-dependent changes in synaptic or gap junctional properties. Including such analyses could significantly enhance the relevance of the findings.

Frequency-Dependent Effects:<br /> The study demonstrates that gap junctional inputs suppress high-frequency EFP power due to membrane filtering. However, it could delve deeper into the implications of this for different brain rhythms, such as gamma or ripple oscillations.

Visualization:<br /> Figures are dense and could benefit from more intuitive labeling and focused presentations. For example, isolating key differences between chemical and gap junctional inputs in distinct panels would improve clarity.

Contextual Relevance:<br /> The manuscript touches on how these findings relate to known physiological roles of gap junctions (e.g., in gamma rhythms) but does not explore this in depth. Stronger integration of the results into known neural network dynamics would enhance its impact.

Suggestions for Improvement:

Broader Application:<br /> Simulate EFPs in multi-neuron networks to assess how the findings extend to network-level interactions, particularly in regions with mixed synaptic connectivity.

Experimental Correlation:<br /> Collaborate with experimental groups to validate the computational predictions using in vivo or in vitro recordings.

Mechanistic Insights:<br /> Provide a more detailed mechanistic explanation of how specific ionic currents (e.g., HCN, sodium, leak) interact during gap junctional vs. chemical synaptic inputs.

Implications for Neural Coding:<br /> Discuss how the observed differences in EFP signatures might influence neural coding, especially in circuits with heavy gap junctional connectivity.

Reviewer #2 (Public review):

Summary:

This manuscript reports a comparison of microbial traits and host response traits in a laboratory model of infected granuloma using Mtb strains from different lineages. The authors report increased bacillary growth and granuloma formation, inversely associated with T cell activation that is characterized by CXCL9, granzyme B and TNF expression. They therefore infer that these T cell responses are likely to be host-protective and that the greater virulence of modern Mtb lineages may be driven by their ability to avoid triggering these responses.

Strengths:

The comparison of multiple Mtb lineages in a granuloma model that enables evaluation of the potential role of multiple host cells in Mtb control, offers a valuable experimental approach to study the biological mechanisms that underpin differential virulence of Mtb lineages that has been previously reported in clinical and epidemiological studies.

Weaknesses:

The study is rather limited to descriptive observations, and lacks experiments to test causal relationships between host and pathogen traits. Some of the presentation of the data are difficult to interpret, and some conclusions are not adequately supported by the data.

Comments on revisions:

The authors have addressed my previous comments with appropriate revisions and explanations.

Reviewer #1 (Public review):

Summary:

Chen and Phillips describe the dynamic appearance of cytoplasmic granules during embryogenesis analogous to SIMR germ granules, and distinct from CSR-1-containing granules, in the C. elegans germline. They show that the nuclear Argonaute NRDE-3, when mutated to abrogate small RNA binding, or in specific genetic mutants, partially colocalizes to these granules along with other RNAi factors, such as SIMR-1, ENRI-2, RDE-3, and RRF-1. Furthermore, NRDE-3 RIP-seq analysis in early vs. late embryos is used to conclude that NRDE-3 binds CSR-1-dependent 22G RNAs in early embryos and ERGO-1-dependent 22G RNAs in late embryos. These data lead to their model that NRDE-3 undergoes small RNA substrate "switching" that occurs in these embryonic SIMR granules and functions to silence two distinct sets of target transcripts - maternal, CSR-1 targeted mRNAs in early embryos and duplicated genes and repeat elements in late embryos.

Strengths:

The identification and function of small RNA-related granules during embryogenesis is a poorly understood area and this study will provide the impetus for future studies on the identification and potential functional compartmentalization of small RNA pathways and machinery during embryogenesis.

Weaknesses:

(1) The authors acknowledge the following issue that loss of SIMR granules have no significant impact on NRDE-3 small RNA loading weakens the functional relevance of these structures. However, this point is clearly discussed and, as they note in their Discussion, it is entirely possible that these embryonic granules may be "incidental condensates."

Reviewer #1 (Public review):

Summary:

The works seeks to investigate the efficacy of linalool as a natural alternative for combating Saprolegnia parasitica infections, which would provide great benefit to aquaculture. This paper shows the effect of linalool in vitro using a variety of techniques including changes in S. parasitica membrane integrity following linalool exposure and alterations in cell metabolism and ribosome function. Additionally, this work goes on to show that prophylactic and concurrent treatment of linalool at the time of S. parasitica infection can improve survival and tissue damage in vivo in their grass carp infection model. The conclusions of the paper are partially supported by the data with the corrections done by the authors improving clarity such that I believe there is merit in the work.

Reviewer #1 (Public review):

Summary:

The manuscript by Wang et al. investigates the relationship between Streptococcus Suis (S. Suis) growth phases and levels of virulence factor, capsular polysaccharide (CPS), in the bacterial cell wall. They use an understudied mouse intranasal infection model to connect growth phase related CPS abundance to the pathogenicity of the bacteria in the nose, blood, and other organs. Adoptive transfer of serum against either CPS or V5 (five other virulence factors) reinforces their discovery of CPS levels on S. Suis in different organs and stages of infection. Vaccination against bacterial infections can be difficult, and understanding how the serotype of a bacterial pathogen changes between infection sights and systemic disease is critical. Further, understanding host-pathogen interactions at early time points in the upper respiratory tract may have broad implications for vaccine development. While some of the results are interesting and compelling, others are not supported by the data and require further experimental work.

Strengths:

The model of intranasal infection is compelling to expand upon work previously done in vitro and with systemic routes of infection. The histology and fluorescent imaging of the olfactory epithelium and olfactory bulb complement work in Figure 2 about the attachment of S. suis to epithelial cells and the bacterial burden over time in different organs of Figure 3. Histology was performed at 1 hour and 9 days after intranasal infection with stationary phase S. suis and drives home that this pathogen can invade the olfactory nerve and may potentially cause bacterial meningitis seen in some infected swine.

The adoptive transfer of either anti-CPS or anti-V5 to mice before infection at both longer (12 hr), and shorter (0.5 hr) time points is useful to demonstrate that the changes in cell wall composition between the NALT/CSF and blood compartments result in different efficacy in clearing bacteria from those locations. This is fundamental for the development of vaccines for the swine industry and begs those developing other bacterial vaccines to consider what virulence factors are the most useful as neutralizing antibody targets at the sight of bacterial invasion.

Demonstrating that the amount of CPS within the cell wall of S. Suis is related to the growth phase of the bacteria is an important consideration for vaccine development. While others had previously shown that CPS levels were higher in the blood than in the CNS, and that CPS decreases the invasion of epithelial cells, the close look at the olfactory epithelium at an early time point ties together in vitro findings. The control of a CPS-negative strain was critical to understanding their findings. The location and the microbial community that bacterial pathogens live within may change the growth phase and therefore also the cell wall components.

Weaknesses:

The authors present compelling data that is relevant to the development of anti-bacterial vaccinations and show a relationship between CPS levels and pathogenicity. However, the use of a laboratory murine model requiring acetic acid pre-treatment and a high i.n. dose. Therefore, the findings presented may not represent what occurs in swine. Furthermore, several conclusions are not supported by the data and require substantial new experimental support. Thus, major concerns remain that impact the validity of the findings.

Major concerns for the manuscript:

The intranasal infections were done with S. Suis in the stationary phase which has been shown to have less CPS on the cell wall. While this mimics the literature that shows S. Suis to have less CPS in the CNS, the difference in the pathogenesis of a log phase vs. stationary phage intranasal infection would be interesting. Especially because the bacteria is a part of the natural microbial community of swine tonsils, it is curious if the change in growth phase and therefore CPS levels may be a causative reason for pathogenic invasion in some pigs. To take this line of thought a step further, the authors should consider taking the bacteria from NALT/CSF and blood and compare the lag times bacteria from different organs take to enter a log growth phase to show whether the difference in CPS is because S. Suis in each location is in a different growth phase. If log phase bacteria were intranasally delivered, would it adapt a stationary phase life strategy? How long would that take? Lastly, the authors should be cautious about claims about S. suis downregulating CPS in the NALT for increased invasion and upregulating CPS to survive phagocytosis in blood. While it is true that the data shows that there are different levels of CPS in these locations, the regulation and mechanism of the recorded and observed cell wall difference is not investigated past the correlation to the growth phase. While mechanistic work is outside the scope of the current work, readers should keep in mind that these results may be explained multiple ways. In addition, the mouse model is used rather than the usual host of a pig. The NALTs of conventional pigs and SPF mice certainly have unique microbial communities and this may affect the pathogenesis of S. suis in the mouse, therefore influencing the results. Because the authors show a higher infection rate in the mouse with acetic acid, they may want to consider investigating what the mouse NALT microenvironment is naturally doing to exclude more bacterial invasion in future studies. Is it simply a host mismatch or is there something about the microbiome or steady-state immune system in the nose of mice that is different from pigs?

Reviewer #1 (Public review):

The authors have strengthened their conclusions by providing additional information about the specificity of their antibodies, but at the same time the authors have revealed concerning information about the source of their antibodies.

It appears that many of the antibodies used in this study have been discontinued because the supplier company was involved in a scandal of animal cruelty and all their goats and rabbits Ab products were sacrificed. The authors acknowledge that this is unfortunate but they also claim that the issue is out of their hands.

The authors' statement is false; the authors ought to not use these antibodies, just as the providing company chose to discontinue them, as<br /> those antibodies are tied to animal cruelty. The issue that the authors feel OK with using them is of concern. In short, please remove any results from unethical antibodies.

Removal of such results also best serves science. That is, any of their results using the discontinued antibodies means that the authors' results are non-reproducible and we should be striving to publish good, reproducible science.

For the antibodies that do not have unethical origins the authors claim that their antibodies have been appropriately validated, by "testing in positive control tissue and/or Western blot or in situ hybridization". This is good but needs to be expanded upon. It is a strong selling point that the Abs are validated and I want to see additional information in their Supplementary Table 2 stating for each Ab specifically:

(1) What +ve control tissue was used in the validation of each Ab and which species that +ve control came from. Likewise, if competition assays to confirm validity was used, please also specify.

(2) Which assay was the Ab validated for (WB, IHC, ELISA, all etc)

(3) For Antibodies that were validated for, or using WBs please let the reader know if there were additional bands showing.

(4) Include references to the literature that supports these validations. That is, please make it easy for the reader to appreciate the hard work that went into the validation of the Antibodies.

Finally, for the Abs, when the authors write that "All antibodies used have been validated by testing in positive control tissue and/or Western blot or in situ hybridization" I fail to understand what in situ hybridisation means in this context. I am under the impression that in situ hybridisation is some nucleic acid -hybridising-to-organ or tissue slice. Not polypeptide binding.

Reviewer #3 (Public review):

In this study, the authors tested a dietary intervention focused on improving meal regularity. Participants first utilized a smartphone application to track their meal frequencies, and then they were asked to restrict their meal intake to times when they most often eat to enhance meal regularity for six weeks. This, supposedly, resulted in some weight loss, supposedly independent of changes in caloric intake.

The concept is appealing, and it is interesting to use a smartphone app in participants' typical everyday environment to regularize food intake. It asks from participants to stick to meal intake times that are supported in many cultures, and it asks them not to eat outside of what are likely unhealthy habits such as grazing a refrigerator late at night. In essence, this is a restrictive diet, not restricting caloric intake but the timing of food intake, and it has many parallel to time restricted feeding. It is important to note that there are many restrictive diets, and a common problem with restrictive diets is that while they allow one to lose a couple of pounds for a couple of months just as with this diet, the long-term success is very poor because they depend on restriction. This issue is still not discussed.

Further, why the participants lose weight, whether this is indeed due to a reduction in food intake as implied, or if the weight loss occurred without a reduction in caloric intake as first stated by the authors and now suggested remains to be determined as the method of food diary as a method to assess caloric intake lacks rigor as has been well established and has been shown again and again to be misleading even though many readers without that knowledge draw conclusions from such studies and they should best have been omitted.

The authors hypothesize that the intervention improves metabolism by improving circadian rhythmicity. That's plausible, but the study provides only a subjective questionnaire and lacks more objective measures such as actigraphy.

While the authors now state now that this as a pilot study, the study falls short of providing mechanistic insights into what underlies the weight loss and the many correlations provided do not make up for this weakness.

Overall, while this pilot study introduces an interesting approach to meal regularity, its limitations highlight the need for more rigorous studies to validate these findings.

(1) Unreliable method of caloric intake

The trial's reliance on self-reported caloric intake is problematic, as participants tend to underreport intake. As pointed out earlier by me and now cited in the revised manuscript, the NEJM paper (DOI: 10.1056/NEJM199212313272701) reported that some participants underreported caloric intake by approximately 50%, rendering such data unreliable and hence misleading. The question is, why include such unreliable data that is more misleading than informative at all? These data should have been omitted. More rigorous methods for assessing food intake should have been utilized. I understand this requires more effort, such as providing participants with meals, or using better methods that photograph and weigh the meals, etc., but it is certainly feasible. It has been done many times in other studies. Further, the control group was not asked to restrict their diet in any way, and hence, asking for a restriction in timing in the treatment group may be sufficient to reduce caloric intake and induce weight loss.<br /> Merely acknowledging the unreliability of self-reported caloric intake is insufficient, as it still leaves the reader with the impression that this weight loss is independent of caloric intake when, in reality, we actually have no idea if food intake contributes to it. A more robust approach to assessing food intake is imperative. Even if a decrease in caloric intake is observed through rigorous measurement, as I am convinced a more rigorous study would unveil testing this paradigm, this intervention may merely represent another restrictive diet among countless others that show that one may lose weight by going on a diet. Seemingly, any restrictive diet works for a few months. The trouble is they do not work long-term because they depend on restriction. I agree with the authors that their intervention seems common sense and has little downside, but one also needs to be realistic about the prospects of this intervention.

(2) Lack of objective data regarding circadian rhythm

The assessment of circadian rhythm using the MCTQ, a self-reported measure of chronotype, is subjective. More objective methods like actigraphy would have strengthened the study.

Actigraphy is considered better than a sleep questionnaire for assessing circadian rhythms because it provides objective data on activity patterns over time, offering a more accurate picture of sleep-wake cycles compared to subjective self-reported information from a questionnaire.

The authors' responses to my prior review are misleading.

I understand that this is a pilot study. Is it appropriate to point out weaknesses and flaws in the conclusion drawn from a pilot study? Absolutely, that is the reviewer's job.

I also understand that food intake can affect circadian rhythm, which was part of the rationale behind the study. Is it appropriate to criticize the study for not examining the effect of the intervention on circadian rhythm using objective measures provided by actigraphy? Yes, it is, as this would have provided mechanistic insights that are more rigorous. I understand that this was not the declared goal, but it should have been examined in a pilot study. To jump to the conclusion that based on prior studies, the intervention will improve circadian rhythms as the authors do is not rigorous and hence a weakness.

A less rigorous method, such as a food questionnaire, to assess caloric intake can result in inadequately supported and potentially misleading conclusions. By including it, the reader may conclude that there was no change in caloric intake when indeed we do not know. I disagree with the authors that this is a minor issue. The associations and correlations the authors provide do not solve the issue. Hence, to make it very clear, it remains to be studied if this intervention reduces weight by reducing caloric intake or other mechanisms. Including this data reduces the study's rigor as it suggests that there is no difference in food intake.

I did not suggest to only use an actimeter (which is a device); I suggested actigraphy. Actigraphy is widely recognized in the field for its utility in circadian rhythm research and provides objective data, while the questionnaire used is subjective. The authors do quote papers comparing their survey to actigraphy by correlation analysis, but the fundamental difference of the two approaches remains. Does an objective measure increase rigor compared to a subjective assessment? Yes, it does.

Similarly, I did not state "that any form of imposed diet appears to lead to weight loss over several months." I said that many forms of restrictive diets do induce weight loss of a similar magnitude to this diet.

The authors should have discussed the fundamental confounder of the study in that the treatment group is asked to restrict food intake to specific times while the control group is not asked to restrict in any way and the potential contribution of this to the weight loss observed.

Reviewer #1 (Public review):

Summary:

The authors found that IL-1b signaling is pivotal for hypoxemia development and can modulate NETs formation in LPS+HVV ALI model.

Strengths:

They used IL1R1 ko mice and proved that IL1R1 is involved in ALI model proving that IL1b signalling leads towards ARDS. In addition, hypothermia reduces this effect, suggesting a therapeutic option.

Weaknesses:

(1) IL1R1 binds IL1a and IL1b. What would be the role of IL1a in this scenario?

(2) The authors depleted neutrophils using anti-Ly6G. What about MDSCs? Do these latter cells be involved in ARDS and VILI?

(3) The authors found that TH inhibited IL-1β release from macrophages led to less NETs formation and albumin leakage in the alveolar space in their lung injury model. A graphical abstract could be included suggesting a cellular mechanism.

(4) If Macrophages are responsible for IL1b release that via IL1R1 induces NETosis, what happens if you deplete macrophages? what is the role of epithelial cells?

DOI: 10.1016/j.isci.2025.112074

Resource: (ZFIN Cat# ZDB-GENO-060207-1,RRID:ZFIN_ZDB-GENO-060207-1)

Curator: @areedewitt04

SciCrunch record: RRID:ZFIN_ZDB-GENO-060207-1

What is this?

Reviewer #1 (Public review):

Summary:

The authors investigated the role of an E3 ubiquitin ligase ITCH in regulating the viral life cycle of SARS-CoV-2. The authors showed that ITCH mediates ubiquitination of the membrane (M) and envelope (E) proteins of SARS-CoV-2. Ubiquitination of E and M results in enhanced interactions between the structural proteins and redistribution of the structural proteins into autophagosomes. The authors claim that the enhanced interactions between structural proteins and trafficking of the structural proteins into autophagosomes contribute to SARS-CoV-2 replication and egress, prompting ITCH as a potential antiviral target. ITCH also alters the cellular distribution of host proteases important for spike cleavage which protect and stabilize spike with cleavage. The authors also demonstrated that SARS-CoV-2 replication is augmented by ITCH in which virus replication is significantly impaired in cells lacking ITCH expression.

Strengths:

The authors provided high-quality data with appropriate experimental controls to justify their claims and conclusions. The mechanistic analyses are excellent and presented in a logical manner. The investigation of the role of ubiquitination in coronavirus assembly and egress is novel as most previous studies focused on its role in mediating innate immune responses.

Weaknesses:

Although the authors showed that ITCH ubiquitinates E and M proteins, the claim that such ubiquitination promotes virion assembly and egress is circumstantial. The enhanced interaction between the structural proteins and targeting of ubiquitinated structural proteins into autophagosomes does not necessarily result in increased virion production and release as suggested by the authors. There is a disconnect between the ubiquitination of structural proteins and the role of ITCH in augmenting virus replication as shown in Fig. 6A and B. In addition, the authors showed that the catalytic activity of ITCH is important for the localization and maturation of host proteases. However, the mechanism behind is unknown. Also, it is unclear how protection of spike from cleavage conferred by ITCH explains its role in promoting replication as a lack of spike cleavage would inevitably compromise entry. The major weakness of the manuscript is the lack of experimental data that explains the molecular role of ITCH in relation to its phenotype observed during SARS-CoV-2 infection.

Reviewer #1 (Public review):

This study uses structural and functional approaches to investigate the regulation of the Na/Ca exchanger NCX1 by an activator, PIP2, and an inhibitor, SEA0400.

State-of-the-art methods are employed, and the data are of high quality and presented very clearly. The manuscript combines two rather different studies (one on PIP2; and one on SEA0400) neither of which is explored in the depth one might have hoped to form robust conclusions and significantly extend knowledge in the field.

The novel aspect of this work is the study of PIP2. Unfortunately, technical limitations precluded structural data on binding of the native PIP2, so an unnatural short-chained analog, di-C8 PIP2, was used instead. This raises the question of whether these two molecules, which have similar but very distinctly different profiles of activation, actually share the same binding pocket and mode of action. In an effort to address this, the authors mutate key residues predicted to be important in forming the binding site for the phosphorylated head group of PIP2. However, none of these mutations prevent PIP2 activation. The only ones that have a significant effect also influence the Na-dependent inactivation process independently of PIP2, thus casting doubt on their role in PIP2 binding, and thus identification of the PIP2 binding site. A more extensive mutagenic study, based on the di-C8 PIP2 binding site, would have given more depth to this work and might have been more revealing mechanistically.

The SEA0400 aspect of the work does not integrate particularly well with the rest of the manuscript. This study confirms the previously reported structure and binding site for SEA0400 but provides no further information. While interesting speculation is presented regarding the connection between SEA0400 inhibition and Na-dependent inactivation, further experiments to test this idea are not included here.

Reviewer #1 (Public review):

DiPeso et al. develop two tools to i) classify micronucleated (MN) cells, which they call VCS MN, and ii) segment micronuclei and nuclei with MNFinder. They then use these tools to identify transcriptional changes in MN cells.

The strengths of this study are:

- Developing highly specialized tools to speed up the analysis of specific cellular phenomena such as MN formation and rupture is likely valuable to the community and neglected by developers of more generalist methods.

- A lot of work and ideas have gone into this manuscript. It is clearly a valuable contribution.

- Combining automated analysis, single-cell labeling, and cell sorting is an exciting approach to enrich for phenotypes of interest, which the authors demonstrate here.

The authors addressed my original concerns related to the first version of this manuscript.

Reviewer #2 (Public review):

The fledgling field of epitranscriptomics has encountered various technical roadblocks with implications as to the validity of early epitranscriptomics mapping data. As a prime example, the low specificity of (supposedly) modification-specific antibodies for the enrichment of modified RNAs, has been ignored for quite some time and is only now recognized for its dismal reproducibility (between different labs), which necessitates the development of alternative methods for modification detection. Furthermore, early attempts to map individual epitranscriptomes using sequencing-based techniques are largely characterized by the deliberate avoidance of orthogonal approaches aimed at confirming the existence of RNA modifications that have been originally identified.

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

As for m5C, the subject of the manuscript submitted by Zhou et al., its identification in mRNA goes back to Squires et al., 2012 reporting on >10.000 sites in mRNA of a human cancer cell line, followed by intermittent findings reporting on pretty much every number between 0 to > 100.000 m5C sites in different human cell-derived mRNA transcriptomes. The reason for such discrepancy is most likely of a technical nature. Importantly, all studies reporting on actual transcript numbers that were m5C-modified relied on RNA bisulfite sequencing, an NGS-based method, that can discriminate between methylated and non-methylated Cs after chemical deamination of C but not m5C. RNA bisulfite sequencing has a notoriously high background due to deamination artifacts, which occur largely due to incomplete denaturation of double-stranded regions (denaturing-resistant) of RNA molecules. Furthermore, m5C sites in mRNAs have now been mapped to regions that have not only sequence identity but also structural features of tRNAs. Various studies revealed that the highly conserved m5C RNA methyltransferases NSUN2 and NSUN6 do not only accept tRNAs but also other RNAs (including mRNAs) as methylation substrates, which in combination account for most of the RNA bisulfite-mapped m5C sites in human mRNA transcriptomes. Is m5C in mRNA only a result of the Star activity of tRNA or rRNA modification enzymes, or is their low stoichiometry biologically relevant?

In light of the short-comings of existing tools to robustly determine m5C in transcriptomes, other methods, like DRAM-seq, aiming to map m5C independently of ex situ RNA treatment with chemicals, are needed to arrive at a more solid "ground state", from which it will be possible to state and test various hypotheses as to the biological function of m5C, especially in lowly abundant RNAs such as mRNA.

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

Reviewer #1 (Public review):

Summary:

The paper begins with phenotyping the DGRP for post-diapause fecundity, which is used to map genes and variants associated with fecundity. There are overlaps with genes mapped in other studies and also functional enrichment of pathways including most surprisingly neuronal pathways. This somewhat explains the strong overlap with traits such as olfactory behaviors and circadian rhythm. The authors then go on to test genes by knocking them down effectively at 10 degrees. Two genes, Dip-gamma and sbb are identified as significantly associated with post-diapause fecundity, which they also find the effects to be specific to neurons. They further show that the neurons in the antenna but not arista are required for the effects of Dip-gamma and sbb. They show that removing antenna has a diapause specific lifespan extending effect, which is quite interesting. Finally, ionotropic receptor neurons are shown to be required for the diapause associated effects.

Strengths:

Overall I find the experiments rigorously done and interpretations sound. I have no further suggestions except an ANOVA to estimate heritability of the post-diapause fecundity trait, which is routinely done in the DGRP and offers a global parameter regarding how reliable phenotyping is.

Weaknesses:

A minor point is I cannot find how many DGRP lines are used.

Reviewer #1 (Public review):

Summary:

Gao et al. has demonstrated that the the pesticide emamectin benzoate (EB) treatment of brown plathopper (BPH) leads to increased egg laying in the insect, which is a common agricultural pest. The authors hypothesize that EB upregulates JH titer resulting in increased fecundity.

Strengths:

The finding that a class of pesticide increases fecundity of brown planthopper is interesting.

Weaknesses:

(1) EB is an allosteric modulator of GluCl. That means it EB physically interacts with GluCl initiating a structural change in the cannel protein. Yet the authors here central hypothesis is about how EB can upregulate the mRNA of GluCl. I do not know whether there is any evidence that an allosteric modulator can function as a transcriptional activator for the same receptor protein. The basic premise of the paper sounds counterintuitive. This is a structural problem and should be addressed by the authors by giving sufficient evidence about such demonstrated mechanisms before.<br /> (2) I am surprised to see a 4th instar larval application or treatment with EB results in upregulation of JH in the adult stages. Complicating the results further is the observation that a 4th instar EB application results in an immediate decrease in JH titer. There is a high possibility that this late JH titer increase is an indirect effect.<br /> (3) The writing quality of the paper needs improvement. Particularly with respect to describing processes, and abbreviations. In several instances authors have not adequately described the processes they have introduced, thus confusing the readers.<br /> (4) In the section 'EB promotes ovarian development' the authors have shown that EB treatment results in increased detention of eggs which contradicts their own results which show that EB promotes egg laying. Again, this is a serious contradiction that nullifies their hypothesis.<br /> (5) Furthermore, the results suggest that oogenesis is not affected by EB application. The authors should devote a section to discussing how they are observing increased egg numbers in EB-treated insects while not impacting Oogenesis.<br /> (6) Met is the receptor of JH and to my understanding, remains mostly constant in terms of its mRNA or protein levels throughout various developmental periods in many different insects. Therefore, the presence of JH becomes the major driving factor for physiological events and not the presence of the receptor Met. Here the authors have demonstrated an increase in Met mRNA as a result of EB treatment. Their central hypothesis is that EB increases JH titer to result in enhanced fecundity. JH action will not result in the activation of Met. Although not contradictory to the hypothesis, the increase in mRNA content of Met is contrary to the findings of the JH field thus far.<br /> (7) As pointed out before, it is hard to rationalize how a 4th instar exposure to EB can result in upregulation of key genes involved in JH synthesis at the adult stage. The authors must consider providing a plausible explanation and discussion in this regard.<br /> (8) I have strong reservations against such an irrational hypothesis that Met (the receptor for JH) and JH-Met target gene Kr-h1 regulates JH titer (Line 311, Fig 3 supplemental 2D). This would be the first report of such an event on the JH field and therefore must be analysed to depth before it may go to publication. I strongly suggest the authors remove such claims from the manuscript without substantiating it.<br /> (9) Kr-h1 is JH/Met target gene. The authors demonstrate that silencing of Kr-h1 results in inhibition of FAMeT, which is a gene involved in JH synthesis. The feedback loop in JH synthesis is unreported. Authors must go ahead with a mechanistic detail of Kr-h1 mediated JH upregulation before this can be concluded. Mere qPCR experiments are not sufficient to substantiate a claim that is completely contrary to the current understanding of JH signalling pathway.<br /> (10) Authors have performed knockdowns of JHAMT, Met and Kr-h1 to demonstrate the effect of these factors on fecundity n BPH. Additionally, they have performed rescue experiments with EB application on these knockdown insects (Figure 3K-M). This I believe is a very flawed experiment. The authors demonstrate EB works through JHAMT in upregulating JH titer. In the absence of JHAMT, EB application is not expected to rescue the phenotype. But authors have reported a complete rescue here. In the absence of Met, the receptor of JH, either EB or JH is not expected to rescue the phenotype. But a complete rescue has been reported. These two experimental results contradict their own hypothesis.<br /> (11) A significant section of the paper deals with how EB upregulates JH titer. JH is a hormone synthesized in the Corpora Allata. Yet the authors have chosen to use the whole body for all of their experiments. Changes in the whole body for mRNA of those enzymes involved in JH synthesis does may not reflect on the situation in Corpora Allata. Although working with corpora Allata is challenging, discarding the abdomen and thorax region and working with the head and neck region of the insect is easily doable. Results from such sampling is always more convincing when it comes to JH synthesis studies.<br /> (12) The phenomenon reported was specific for BPH and not found in other insects. This limits the implications of the study.<br /> (13) Overall, the molecular experiments are very poorly designed and can at best be termed superficial. There are several contradictions within the paper and no discussion or explanation has been provided for that.

Comments on revisions:

(1) The onus of making the revisions understandable to the reviewers lies with the authors. In its current form, how the authors have approached the review is hard to follow, in my opinion. Although the authors have taken a lot of effort in answering the questions posed by reviewers, parallel changes in the manuscript are not clearly mentioned. In many cases, the authors have acknowledged the criticism in response to the reviewer, but have not changed their narrative, particularly in the results section.<br /> (2) In the response to reviewers, the authors have mentioned line numbers in the main text where changes were made. But very frequently, those lines do not refer to the changes or mention just a subsection of changes done. The problem is throughout the document making it very difficult to follow the revision and contributing to the point mentioned above.<br /> (3) The authors need to infer the performed experiments rationally without over interpretation. Currently, many of the claims that the authors are making are unsubstantiated. As a result of the first review process, the authors have acknowledged the discrepancies, but they have failed to alter their interpretations accordingly.<br /> (4) I would like to point to the fact that there are significant experimental modifications added to the manuscript. The decision from the first cycle of review was given on 8th Nov 2024. The authors re-submitted the manuscript on 20th Nov 2024. It just beats my understanding, how so many experiments can be done in such a short time. The rush in resubmission is evident in the writing quality as well. Which I think is now poorer than the original version.<br /> (5) The writing quality is still extremely poor.

Reviewer #1 (Public review):

Summary:

The authors aimed to confirm the association between the human leukocyte antigen (HLA)-II region and tuberculosis (TB) susceptibility within admixed African populations. Building upon previous findings from the International Tuberculosis Host Genetics Consortium (ITHGC), this study sought to address the limitations of small sample size and the inclusion of admixed samples by employing the Local Ancestry Allelic Adjusted (LAAA) model, as well as identify TB susceptibility loci in an admixed South African cohort.

Strengths:

The major strengths of this study include the use of multiple TB case-control datasets from diverse South African populations and ADMIXTURE for global ancestry inference.

Weaknesses:

The major weakness of this study include insufficient significant novel discoveries and reliance on cross-validation. The use of existing models did not add value to this study.

Appraisal:<br /> The authors achieved their aims. However, the results still needed to be further validated in the future.

Impact:<br /> The innovative use of the LAAA model and the comprehensive dataset in this study may make contributions to the field of genetic epidemiology.

Reviewer #1 (Public review):

Summary:

The authors of this study sought to define a role for IgM in responses to house dust mites in the lung.

Strengths:

Unexpected observation about IgM biology.<br /> Combination of experiments to elucidate function.

Weaknesses:

Would love more connection to human disease

Reviewer #1 (Public review):

Summary:

The manuscript performs a comprehensive biochemical, structural, and bioinformatic analysis of TseP, a type 6 secretion system effector from Aeromonas dhakensis that includes identification of a domain required for secretion and residues conferring target organism specificity. Through targeted mutations, they have expanded the target range of a T6SS effector to include a gram-positive species, which are not typically susceptible to T6SS attack. Although this is not the first dual domain effector to be described, this is the first time anyone has been able to modify a T6SS effector to have an expanded target species range.

Strengths:

The thorough dissection of TseP activity and modulation of target specificity represent a novel contribution to the field of antibacterial research.

Weaknesses:

Although the mechanistic activity of TseP is fully dissected here, there are some unaddressed questions regarding the importance/evolution of the dual activity domain organization. For example, does the modified Gram-positive targeting TseP effector still kill Gram-negative bacteria in bacterial mixtures? And if so, what is the evolutionary benefit of having a TseP that cannot target Gram-positives? And can something be inferred about the biology of Aeromonas from this?

Comments on revisions:

The comments and critiques from the initial submission have been addressed. However, some of them have only been addressed in the author's rebuttal. Some of the discussion particularly regarding the validity of using E. coli PG, the ability for TseP_C4+ to still kill E. coli, and the advantages of having dual domain function effectors probably should be present in the actual manuscript.

Reviewer #2 (Public review):

Summary

In this extensive comparative study, Moreno-Borrallo and colleagues examine the relationships between plasma glucose levels, albumin glycation levels, diet and life-history traits across birds. Their results confirmed the expected positive relationship between plasma blood glucose level and albumin glycation rate but also provided findings that are somewhat surprising or contrast with findings of some previous studies (positive relationships between blood glucose and lifespan, or absent relationships between blood glucose and clutch mass or diet). This is the first extensive comparative analysis of glycation rates and their relationships to plasma glucose levels and life history traits in birds that is based on data collected in a single study, with blood glucose and glycation measured using unified analytical methods (except for blood glucose data for 13 species collected from a database).

Strengths

This is an emerging topic gaining momentum in evolutionary physiology, which makes this study a timely, novel and important contribution. The study is based on a novel data set collected by the authors from 88 bird species (67 in captivity, 21 in the wild) of 22 orders, except for 13 species, for which data were collected from a database of veterinary and animal care records of zoo animals (ZIMS). This novel data set itself greatly contributes to the pool of available data on avian glycemia, as previous comparative studies either extracted data from various studies or a ZIMS database (therefore potentially containing much more noise due to different methodologies or other unstandardised factors), or only collected data from a single order, namely Passeriformes. The data further represents the first comparative avian data set on albumin glycation obtained using a unified methodology. The authors used LC-MS to determine glycation levels, which does not have problems with specificity and sensitivity that may occur with assays used in previous studies. The data analysis is thorough, and the conclusions are substantiated. Overall, this is an important study representing a substantial contribution to the emerging field evolutionary physiology focused on ecology and evolution of blood/plasma glucose levels and resistance to glycation.

Weaknesses

Unfortunately, the authors did not record handling time (i.e., time elapsed between capture and blood sampling), which may be an important source of noise because handling-stress-induced increase in blood glucose has previously been reported. Moreover, the authors themselves demonstrate that handling stress increases variance in blood glucose levels. Both effects (elevated mean and variance) are evident in Figure ESM1.2. However, this likely makes their significant findings regarding glucose levels and their associations with lifespan or glycation rate more conservative, as highlighted by the authors.

Reviewer #1 (Public review):

Summary:

This work introduces the differentiable Gillespie algorithm, DGA, which is a differentiable variant of the celebrated (and exact) Gillespie algorithm commonly used to perform stochastic simulations across numerous fields, notably in the life sciences. The proposed DGA approximates the exact Gillespie algorithm using smooth functions yielding a suitable approximate differentiable stochastic system as a proxy for the underlying discrete stochastic system, where DGA stochastic reactions have continuous reaction index and the species abundances. To illustrate their methodology, the authors specifically consider in detail the case of a well-studied two-state promoter gene regulation system that they analyze using a machine learning approach, and by combining simulation data with analytical results. For the two-state promoter gene system, the DGA is benchmarked by accurately reproducing the results of the exact Gillespie algorithm. For this same simple system, the authors also show how the DGA can be used for estimating kinetic parameters of both simulated and real noisy experimental data. This lets them argue convincingly that the DGA can become a powerful computation tool for applications in quantitative and synthetic biology. In order to argue that the DGA can be employed to design circuits with ad-hoc input-output relations, these considerations are then extended to a more complex four-state promoter model of gene regulation. The main strength of the paper is its clarity and its pedagogical presentation of the simulation methods.

Strengths:

The main strength of the paper is its clarity and its pedagogical presentation of the simulation methods.

Weaknesses:

It would have been useful to have a brief discussion, based on a concrete example, of what can be achieved with the DGA and is totally beyond the reach of the Gillespie algorithm and the numerous existing stochastic simulation methods. A more comprehensive and quantitative analysis of the limitations of the DGA, e.g. for rare events, and how it might be used for stochastic spatial systems would have also been helpful. However, this is arguably beyond the scope of this study whose primary goal is to introduce the DGA and demonstrate that it can achieve tasks like parameter estimation and network design.

Comments on revisions:

The authors have made a sound effort to address many of the comments raised in the previous reports. This has helped improve the clarity of the discussion.

Reviewer #1 (Public review):

Summary:

The manuscript puts forward a statistical method to more accurately report the significance of correlations within data. The motivation for this study is two-fold. First, the publication of biological studies demands the report of p-values, and it is widely accepted that p-values below the arbitrary threshold of 0.05 give the authors of such studies justification to draw conclusions about their data. Second, many biological studies are limited by the number of replicate samples that are feasible, with replicates of less than 5 typical. The authors report a statistical tool that uses a permute-match approach to calculate p-values. Notably, the proposed method reduces p-values from around 0.2 to 0.04 as compared to a standard permutation test with a small sample size. The approach is clearly explained, including detailed mathematical explanations and derivations. The advantage of the approach is also demonstrated through analysis of computer-generated synthetic data with specified correlation and analysis of previously published data related to fish schooling. The authors make a clear case that this method is an improvement over the more standard approach currently used, and also demonstrate the impact of this methodology on the ability to obtain p-values that are the standard for biological research. Overall, this paper is very strong. While the subject matter seems somewhat specialized, I would make the case that this will be an important study that has broad general interest to readers. The findings are very general and applicable to many research contexts. Experimentalists also want to report accurate p-values in their work and better understand how these values are calculated. Although I believe the previous statement is true, I am not sure that many research groups doing biological work are reading specialized statistics journals regularly. Therefore a useful and broadly applicable statistical tool is well placed in this journal.<br /> Strengths:

The proposed method is broadly applicable to many realistic datasets in many experimental contexts.

The power of this method was demonstrated with both real experimental data and "synthetic" data. The advantages of the tool are clearly reported. The zebrafish data is a great example dataset.

The method solves a real-life problem that is frequently encountered by many experimental groups in the biological sciences.

The writing of the paper is surprisingly clear, given the technical nature of the subject matter. I would not at all consider myself a statistician or mathematician, but I found the text easy to follow. The authors did an impressive job guiding the reader through material that would often be difficult to grasp. The introduction was also well-written and clearly motivated the goals of the study.

Weaknesses:

A few changes could be made if the manuscript is revised. I would consider all of these points minor, but the paper could be improved if these points were addressed.

(1) The caption of Figure 2 doesn't seem to mention panel D. Figure A-2 also does not mention C in the caption.

(2) Figure 2D is a little hard to follow. First, the definition of "Power" is not clear, and I couldn't find the precise definition in the text. Second, the legend for the different lines in 2D is only given in Figure A-2. Perhaps a portion of the caption for Figure 2 is missing?

(3) The concept of circular variance for the fish data was heard to understand/visualize. The equation on line 326 did not help much. If there is a very simple picture that could be added near line 326 that helps to explain Ct and theta, that could be a big help for some readers who do not work on related systems. The analysis performed is understandable, the reader just has to accept that circular variance captions the degree of alignment of the fish.

(4) For the data discussed in Figure 3, I wasn't 100% sure how the time windows were selected. In the caption, it says "time series to different lengths starting from the first frame". So the 20 s time window was from t=0 to t= 20 s. Would a different result be obtained if a different 20 s window was chosen (from t = 4 min to t = 4 min 20 s just to give a specific example). I suppose by chance one of the time windows would give a p-value less than the target 0.05, that wouldn't be surprising. Maybe a random time window should be selected (although I am not indicating what was reported was incorrect)? A little more discussion on this aspect of the study may be helpful.

Reviewer #1 (Public review):

Summary:

Meteorin proteins were initially described as secreted neurotrophic factors. In this manuscript, Eggeler et al. demonstrate a novel role for Meteorins in establish left-right axis formation in the zebrafish embryo. The authors generated null mutations in each of the three zebrafish meteorin genes - metrn, metrnla, and metrnlab. Triple mutant embryos displayed phenotypes strongly associated with left-right defects such as heart looping and visceral organ placement, and disrupted expression of Nodal-responsive genes, as did single mutants for metrn and metrnla. The authors then go on to demonstrate that these defects in left-right asymmetry are likely to due to defects in Kupffer's Vesicle and the progenitor dorseal forerunner cells including impaired lumen formation and reduced fluid flow, reduced clustering among DFCs, impaired DFC migration, mislocalization of apical proteins ZO-1 and aPKC, and detachment of DFCs from the EVL. Notably, the authors found that expression of marker genes sox32 and sox17 were not affected, suggesting Meteorins are required for DFC/KV morphogenesis but not necessarily fate specification. Finally, the authors show genetic interaction between Meteorins and integrin receptors, which were previously implicated in left-right patterning. In a supplemental figure, the manuscript also presents data showing expression of meteorin genes around the chick Hensen's node, suggesting that the left-right patterning functions may be conserved among vertebrates.

Strengths:

Strengths of this study include the generation of a triple mutant line that targets all known zebrafish meteorin family members. The experiments presented in this study were rigorous, especially with respect to quantification and statistical analysis.

Weaknesses:

Although the authors convincingly demonstrate a role for Meteorins in zebrafish left-right patterning, data supporting a conserved role in other vertebrates is compelling but limited to one supplemental figure.

Reviewer #1 (Public review):

Summary:

For each of the three key transcription factor (TF) proteins in E. coli, the authors generate a large library of TF binding site (TFBS) sequences on plasmids, such that each TFBS is coupled to the expression of a fluorescence reporter. By sorting the fluorescence of individual cells and sequencing their plasmids to identify each cell's TFBS sequence (sort-seq), they are able to map the landscape of these TFBSs to the gene expression level they regulate. The authors then study the topographical features of these landscapes, especially the number and distribution of local maxima, as well as the statistical properties of evolutionary paths on these landscapes. They find the landscapes to be highly rugged, with about as many local peaks as a random landscape would have, and with those peaks distributed approximately randomly in sequence space. The authors find that there are a number of peaks that produce regulation stronger than that of the wild-type sequence for each TF and that it is not too unlikely to reach one of those "high peaks" from a random starting sequence. Nevertheless, the basins of attractions for different peaks have significant overlap, which means that chance plays a major role in determining which peak a population will evolve to.

Strengths:

(1) The experiments and analysis of this paper are very well-executed and, by and large, very thorough (with an important exception identified below). I appreciated the systematic nature of the project, both the large-scale experiments done on three TFs with replicates and the systematic analysis of the resulting landscapes. This not only makes the paper easy to follow but also inspires confidence in their results since there is so much data and so many different ways of analyzing it. It's a great recipe for other studies of genotype-phenotype landscapes to follow.

(2) Considering how technical the project was, I am really impressed at how easy to read I found the paper, and the authors deserve a lot of credit for making it so. They do a great job of building up the experiments and analyses step-by-step and explaining enough of the basics of the experimental design and the essence of each analysis in the main text without getting too complicated with details that can be left to the Methods or SI. Compared to other big data papers, this one was refreshingly not overwhelming.

Weaknesses:

(1) The main weakness of this paper, in my view, is that it felt disconnected from the larger body of work on fitness and genotype-phenotype landscapes, including previous data on TFBSs in E. coli, genotype-phenotype maps of TFBSs in other systems, protein sequence landscapes (e.g., from mutational scans or combinatorially-complete libraries), and fitness landscapes of genomic mutations (e.g., combinatorially-complete landscapes of antibiotic resistance alleles). I have no doubt the authors are experts in this literature, and they probably cite most of it already given the enormous number of references. But they don't systematically introduce and summarize what was already known from all that work, and how their present study builds on it, in the Abstract and Introduction, which left me wondering for most of the paper why this project was necessary. Eventually, the authors do address most of these points, but not until the end, in the Discussion. Readers who have no familiarity with this literature might read this paper thinking that it's the first paper ever to study topography and evolutionary paths on genotype-phenotype landscapes, which is not true.

There were two points that made this especially confusing for me. First, in order to choose which nucleotides in the binding sites to vary, the authors invoke existing data on the diversity of these sequences (position-weight matrices from RegulonDB). But since those PWMs can imply a genotype-phenotype map themselves, an obvious question I think the authors needed to have answered right away in the Introduction is why it is insufficient for their question. They only make a brief remark much later in the Results that the PWM data is just observed sequence diversity and doesn't directly reflect the regulation strength of every possible TFBS sequence. But that is too subtle in my opinion, and such a critical motivation for their study that it should be a major point in the Introduction.

The second point where the lack of motivation in the Introduction created confusion for me was that they report enormous levels of sign epistasis in their data, to the point where these landscapes look like random uncorrelated landscapes. That was really surprising to me since it contrasts with other empirical landscape data I'm familiar with. It was only in the Discussion that I found some significant explanation of this - namely that this could be a difference between prokaryotic TFBSs, as this paper studies, and the eukaryotic TFBSs that have been the focus of many (almost all?) previous work. If that is in fact the case - that almost all previous studies have focused on eukaryotic TFBSs or other kinds of landscapes, and this is the first to do a systematic test of prokaryotic TFBS, then that should be a clear point made in the Abstract and Introduction. (I find a comparable statement only in the very last paragraph of the Discussion.) If that's the case, then I would also find that point to be a much stronger, more specific conclusion of this paper to emphasize than the more general result of observing epistasis and contingency (as is currently emphasized in the Abstract), which has been discussed in tons of other papers. This raises all sorts of exciting questions for future studies - why do the landscapes of prokaryotic TFBSs differ so dramatically from almost all the other landscapes we've observed in biology? What does that mean for the evolutionary dynamics of these different systems?

(2) I am a bit concerned about the lack of uncertainties incorporated into the results. The authors acknowledge several key limitations of their approach, including the discreteness of the sort-seq bins in determining possible values of regulation strength, the existence of a large number of unsampled sequences in their genotype space, as well as measurement noise in the fluorescence readouts and sequencing. While the authors acknowledge the existence of these factors, I do not see much attempt to actually incorporate the effect of these uncertainties into their conclusions, which I suspect may be important. For example, given the bin size for the fluorescence in sort-seq, how confident are they that every sequence that appears to be a peak is actually a peak? Is it possible that many of the peak sequences have regulation strengths above all their neighbors but within the uncertainty of the fluorescence, making it possible that it's not really a peak? Perhaps such issues would average out and not change the statistical nature of their results, which are not about claiming that specific sequences are peaks, just how many peaks there are. Nevertheless, I think the lack of this robustness analysis makes the results less convincing than they otherwise would be.

Reviewer #1 (Public review):

Summary:

The manuscript by Cupollilo et al describes the development, characterization, and application of a novel activity labeling system; fast labelling of engram neurons (FLEN). Several such systems already exist but this study adds additional capability by leveraging an activity marker that is destabilized (and thus temporally active) as well as being driven by the full-length promoter of cFos. The authors demonstrate the activity-dependent induction and time course of expression, first in cultured neurons and then in vivo in hippocampal CA3 neurons after one trial of contextual fear conditioning. In a series of ex vivo experiments, the authors perform patch clamp analysis of labeled neurons to determine if these putative engram neurons differ from non-labelled neurons using both the FLEN system as well as the previously characterized RAM system. Interestingly the early labelled neurons at 3 h post CFC (FLEN+) demonstrated no differences in excitability whereas the RAM-labelled neurons at 24h after CFC had increased excitability. Examination of synaptic properties demonstrated an increase in sEPCS and mEPSC frequencies as well as those for sIPSCs and mIPSCs which was not due to a change in the mossy fiber input to these neurons.

Strengths:

Overall the data is of high quality and the study introduces a new tool while also reassessing some principles of circuit plasticity in the CA3 that have been the focus of prior studies.

Weaknesses:

No major weaknesses were noted.

Reviewer #1 (Public review):

Summary:

After mating, male mice undergo a behavioral switch from infanticide to parental behavior (postmating switch). The neural mechanisms underlying this switch are still largely unknown. Studies performed in different mouse strains have also resulted in mixed evidence for whether mating (specifically: ejaculation) itself is sufficient for this switch, or whether subsequent cohabitation with the pregnant female, and parental experience with pups is required. Recent work found that while lesions to the central part of the medial preoptic area (cMPOA) promote infanticidal behavior, lesions to the rhomboid nucleus of the bed nucleus of the stria terminalis (BSTrh) inhibit infanticide. The current work convincingly adds to this evidence by showing that mating and cohabitation lead to reduced inhibition from Cart-positive medial amygdala neurons onto cMPOA neurons, and that this synaptic change is in fact critical for the postmating switch. Further, the authors demonstrate that parental experience increases inhibitory synaptic transmission onto BSTrh neurons. The male postmating switch thus appears to rely on two sequential stages of synaptic plasticity.

Strengths:

(1) The behavioral characterization is thorough and the authors nicely manage to disentangle the relative contributions of mating, cohabitation, and parental experience to the postmating switch. Their finding of dissociable plasticity mechanisms underlying mating/cohabitation vs pup experience is intriguing.

(2) Most conclusions are based on complementary evidence from different experimental approaches and are compelling.

Weaknesses:

(1) The authors do not provide an explicit synthesis/model of the circuit-level changes underlying this switch. For instance, how does cMPOA-to-BSTrh connectivity change in fathers, and how does the necessity of the cMPOA for the exposure/sensitisation effect square with the effect being postsynaptic in the BSTrh?

(2) The presentation of the manuscript (clarity of language, grammar, reporting of stats in figures etc.) needs to be improved.

Reviewer #1 (Public review):

The propagation of electrical signals within neuronal circuits is tightly regulated by the physical and molecular properties of neurons. Since neurons vary in size across species, the question arises whether propagation speed also varies to compensate for it. The present article compares numerous speed-related properties in human and rat neurons. They found that the larger size of human neurons seems to be compensated by a faster propagation within dendrites but not axons of these neurons. The faster dendritic signal propagation was found to arise from wider dendritic diameters and greater conductance load in human neurons. In addition, the article provides a careful characterization of human dendrites and axons, as the field has only recently begun to characterize post-operative human cells. There are only a few studies reporting dendritic properties and these are not all consistent, hence there is added value of reporting these findings, particularly given that the characterization is condensed in a compartmental model.

Strengths

The study was performed with great care using standard techniques in slice electrophysiology (pharmacological manipulation with somatic patch-clamp) as well as some challenging ones (axonal and dendritic patch-clamp). Modeling was used to parse out the role of different features in regulating dendritic propagation speed. The finding that propagation speed varies across species is novel as previous studies did not find a large change in membrane time constant nor axonal diameters (a significant parameter affecting speed). A number of possible, yet less likely factors were carefully tested (Ih, membrane capacitance). The main features outlined here are well known to regulate speed in neuronal processes. The modeling was also carefully done to verify that the magnitude of the effects is consistent with the difference in biophysical properties. Hence, the findings appear very solid to me.

Weaknesses

The role of diameter in regulating propagation speed is well known in the axon literature.

Comment on the revised version: the authors have now made clearer that the role of diameter was well known in the manuscript.

Reviewer #3 (Public review):

Summary:

Davenport et al have investigated how a masculinizing dose of estrogen changes the transcriptomes of several key song nuclei song and adjacent brain areas in juvenile zebra finches of both sexes. Only male zebra finches sing, learn song, and normally have a fully developed song control circuitry, so the study was aimed at further understanding how genetic and hormonal factors contribute to the dimorphism in song behavior and related brain circuitry in this species. Using WGCNA and follow-up correlations to re-analyze published transcriptome datasets, the authors provide evidence that the main variance of several identified gene co-expression modules significantly correlates with one or some of the factors examined, including sex, estrogen treatment, regional neuroanatomy, chromosomal placement, or vocal learning, noting that the latter is largely based on inference due to expression in song control nuclei.

Strengths:

Among the main strengths are the thorough gene co-expression module and correlation analyses, and the inclusion of both song nuclei and adjacent areas, the latter serving as sort of controls for areas that are not dimorphic and likely broadly present in birds in general. In situ hybridization data discussed in a previous publication (Choe et al., Hormones and Behavior, 2021) provides some support for the neuroanatomical specializations of gene expression. It is also significant that the transcriptome re-analysis was performed with an improved genome assembly that also includes the sex chromosomes, thus expanding the Z/W chromosome gene analyses in Friedrich et al, Cell Reports, 2022. The most relevant finding is arguably the identification of some modules where gene expression variation within song nuclei correlates with hormonal effects and/or gene location on sex chromosomes, which are present at different dosages between sexes. Sex differences in gene expression in areas that are not song nuclei may also bring insights into functions other than song behavior or vocal learning. The study also shows how a published RNA-seq dataset can be reanalyzed in novel and informative ways.

Weaknesses:

The validation of the inferred direction of regulation in the identified co-expression modules is limited to the in situ data mentioned above. Further evidence that representative genes in the main modules differ in expression when comparing sexes or E2- vs VEH-treated tissues using independent samples and/or methods would provide further validation and enhance rigor. Most importantly, E2 is known to exert various actions on brain physiology and neuronal function. Because there was no manipulation of candidate genes, nor assessment/manipulation of vocal behavior or vocal learning, an involvement of the identified candidate genes in setting up the sexual dimorphism of the song system or song behavior was not directly tested in this study. For the latter reason, the implication of the Title (..."gene expression associated with vocal learning...") is not well supported. While novel insights were gained into brain expression of Z chromosome genes, it cannot be excluded that the higher male expression of some Z genes may not affect brain cell function and thus may not require active compensation (as discussed for nucleus RA in Friedrich et al, Cell Reports, 2022).

Reviewer #2 (Public review):

Summary:

The authors provide an open-source graphic user interface (GUI) called Heron, implemented in Python, that is designed to help experimentalists to:

(1) Design experimental pipelines and implement them in a way that is closely aligned with their mental schemata of the experiments<br /> (2) Execute and control the experimental pipelines with numerous interconnected hardware and software on a network.

The former is achieved by representing an experimental pipeline using a Knowledge Graph and visually representing this graph in the GUI. The latter is accomplished by using an actor model to govern the interaction among interconnected nodes through messaging, implemented using ZeroMQ. The nodes themselves execute user-supplied code in, but not limited to, Python.

Using three showcases of behavioral experiments on rats, the authors highlighted four benefits of their software design:

(1) The knowledge graph serves as a self-documentation of the logic of the experiment, enhancing the readability and reproducibility of the experiment,<br /> (2) The experiment can be executed in a distributed fashion across multiple machines that each has different operating system or computing environment, such that the experiment can take advantage of hardware that sometimes can only work on a specific computer/OS, a commonly seen issue nowadays,<br /> (3) The users supply their own Python code for node execution that is supposed to be more friendly to those who do not have a strong programming background,<br /> (4) The GUI can also be used as an experiment control panel for users to control/update parameters on the fly.

Strengths:

(1) The software is light-weight and open-source, provides a clean and easy-to-use GUI,<br /> (2) The software answers the need of experimentalists, particularly in the field of behavioral science, to deal with the diversity of hardware that becomes restricted to run on dedicated systems. It can also be widely adopted in many other experimental settings.<br /> (3) The software has a solid design that seems to be functionally reliable and useful under many conditions, demonstrated by a number of sophisticated experimental setups.<br /> (4) The software is well documented. The authors pay special attention to documenting the usage of the software and setting up experiments using this software.

Comments on revisions: The authors have addressed my concerns from the initial review.

Reviewer #2 (Public review):

Summary:

Using in vivo fiber-photometry the authors first establish that DA release when contacting their partner mouse increases with days of cohabitation while this increase is not observed when contacting a stranger mouse. Similar effects are found in D1-MSNs and D2-MSNs with the D1-MSN responses increasing and D2-MSN responses decreasing with days of cohabitation. They then use slice physiology to identify underlying plasticity/adaptation mechanisms that could contribute to the changes in D1/D2-MSN responses. Last, to address causality the authors use chemogenetic tools to selectively inhibit or activate NAc shell D1 or D2 neurons that project to the ventral pallidum. They found that D2 inhibition facilitates bond formation while D2 excitation inhibits bond formation. In contrast, both D1-MSN activation and inhibition inhibits bond formation.

Strengths:

The strength of the manuscript lies in combining in vivo physiology to demonstrate circuit engagement and chemogenetic manipulation studies to address circuit involvement in pair bond formation in a monogamous vole.

Weaknesses:

Weaknesses include that a large set of experiments within the manuscript are dependent on using short promoters for D1 and D2 receptors in viral vectors. As the authors acknowledge this approach can lead to ectopic expression and the presented immunohistochemistry supports this notion. It seems to me that the presented quantification underestimates the degree of ectopic expression that is observed by eye when looking at the presented immunohistochemistry. However, given that Cre transgenic animals are not available for Microtus mandarinus and given the distinct physiological and behavioral outcomes when imaging and manipulating both viral-targeted populations this concern is minor.

The slice physiology experiments provide some interesting outcomes but it is unclear how they can be linked to the in vivo physiological outcomes and some of the outcomes don't match intuitively (e.g. cohabitation enhances excitatory/inhibitory balance in D2-MSNs but the degree of contact-induced inhibition is enhanced in D2-MSN).

One interesting finding is that the relationship between D2-MSN and pair bond formation is quite clear (inhibition facilitates while excitation inhibits pair bond formation). In contrast, the role of D1-MSNs is more complicated since both excitation and inhibition disrupts pair bond formation. This is not convincingly discussed.

It seemed a missed opportunity that physiological read out is limited to males. I understand though that adding females may be beyond the scope of this manuscript.

Comments on revised version:

The authors addressed most of my comments, some would still need to be addressed.

(1) Previous comment: "The authors do not use an isosbestic control wavelength in photometry experiments, although they do use EGFP control mice which show no effects of these interventions, a within-subject control such as an isosbestic excitation wavelength could give more confidence in these data and rule out motion artefacts within subjects."

The authors should include a paragraph in the discussion addressing the limitations of not using an internal control for the fiberphotometric measurements.

(2) Previous Comment: The slice physiology experiments provide some interesting outcomes but it is unclear how they can be linked to the in vivo physiological outcomes and some of the outcomes don't match intuitively (e.g. cohabitation enhances excitatory/inhibitory balance in D2-MSNs but the degree of contact-induced inhibition is enhanced in D2-MSN).

My comment may not have been clear and the response didn't address my comment. What is missing in the discussion is an explanation of why a relative increase in excitation of D2-MSNs in the slice (Fig. 4J) is associated with an increased inhibition in vivo (Fig. 2H)?

(3) Previous Comment: One interesting finding is that the relationship between D2-MSN and pair bond formation is quite clear (inhibition facilitates while excitation inhibits pair bond formation). In contrast, the role of D1-MSNs is more complicated since both excitation and inhibition disrupt pair bond formation. This is not convincingly discussed.

Similarly, here the response provided does not address my question. Please focus on discussing why both excitation and inhibition of D1-MSNs can disrupt pair bond formation (Figure 7).

Reviewer #1 (Public review):

The authors demonstrated that NINJ1 promotes TF-positive MV release during pyroptosis and thereby triggers coagulation. Coagulation is one of the risk factors that can cause secondary complications in various inflammatory diseases, making it a highly important therapeutic target in clinical treatment. This paper effectively explains the connection between pyroptosis and MV release with Ninj1, which is a significant strength. It provides valuable insight into the potential of targeting Ninj1 as a therapeutic strategy.

Although the advances in this paper are valuable, several aspects need to be clarified. Some comments are discussed below.

(1) Since it is not Ninj1 directly regulating coagulation but rather the MV released by Ninj1 playing a role, the title should include that. The current title makes it seem like Ninj1 directly regulates inflammation and coagulation. It would be better to revise the title.

(2) Ninj1 is known to be an induced protein that is barely expressed in normal conditions. As you showed in "Fig1G" data, control samples showed no detection of Ninj1. However, in "Figure S1", all tissues (liver, lung, kidney and spleen) expressed Ninj1 protein. If the authors stimulated the mice with fla injection, it should be mentioned in the figure legend.

(3) In "Fig3A", the Ninj1 protein expression was increased in the control of BMDM +/- cell lysate rather than fla stimulation. However, in MV, Ninj1 was not detected at all in +/- control but was only observed with Fla injection. The authors need to provide an explanation for this observation. Additionally, looking at the MV β-actin lane, the band thicknesses appear to be very different between groups. It seems necessary to equalize the protein amounts. If that is difficult, at least between the +/+ and +/- controls.

(4) Since the authors focused Ninj1-dependent microvesicle (MV) release, they need to show MV characterizations (EM, NTA, Western for MV markers, etc...).

(5) To clarify whether Ninj1-dependent MV induces coagulation, the authors need to determine whether platelet aggregation is reduced with isolated +/- MVs compared to +/+ MVs.

(6) Even with the authors well established experiments with haploid mice, it is a critical limitation of this paper. To improve the quality of this paper, the authors should consider confirming the findings using mouse macrophage cell lines, such as generating Ninj1-/- Raw264.7 cell lines, to examine the homozygous effect.

(7) There was a paper reported in 2023 (Zhou, X. et al., NINJ1 Regulates Platelet Activation and PANoptosis in Septic Disseminated Intravascular Coagulation. Int. J. Mol. Sci. 2023) that revealed the relationship between Ninj1 and coagulation. According to this paper, inhibition of Ninj1 in platelets prevents pyroptosis, leading to reduced platelet activation and, consequently, the suppression of thrombosis. How about the activation of platelets in Ninj1 +/- mice? The author should add this paper in the reference section and discuss the platelet functions in their mice.

Reviewer #2 (Public review):

Summary:

Golamalamdari, van Schaik, Wang, Kumar Zhang, Zhang and colleagues study interactions between the speckle, nucleolus and lamina in multiple cell types (K562, H1, HCT116 and HFF). Their datasets define how interactions between the genome and the different nuclear landmarks relate to each other and change across cell types. They also identify how these relationships change in K562 cells in which LBR and LMNA are knocked out.

Strengths:

Overall, there are a number of datasets that are provided, and several "integrative" analyses performed. This is a major strength of the paper, and I imagine the datasets will be of use to the community to further probed and the relationships elucidated here further studied. An especially interesting result was that specific genomic regions (relative to their association with the speckle, lamina, and other molecular characteristics) segregate relative to the equatorial plane of the cell.

Weaknesses:

The experiments are primarily descriptive, and the cause-and-effect relationships are limited (though the authors do study the role of LMNA/LBR knockdown with their technologies).

Reviewer #1 (Public review):

Summary:

The drug Ivermectin is used to effectively treat a variety of worm parasites in the world, however resistance to Ivermectin poses a rising challenge for this treatment strategy. In this study, the authors found that loss of the E3 ubiquitin ligase UBR-1 in the worm C. elegans results in resistance to Ivermectin. In particular, the authors found that ubr-1 mutants are resistant to the effects of Ivermectin on worm viability, body size, pharyngeal pumping and locomotion. The authors previously showed that loss of UBR-1 disrupts homeostasis of the amino acid and neurotransmitter glutamate resulting in increased levels of glutamate in C. elegans. Here, the authors found that the sensitivity of ubr-1 mutants to Ivermectin can be restored if glutamate levels are reduced using a variety of different methods. Conversely, treating worms with exogenous glutamate to increase glutamate levels also results in resistance to Ivermectin supporting the idea that increased glutamate promotes resistance to Ivermectin. The authors found that the primary known targets of Ivermectin, glutamate-gated chloride channels (GluCls), are downregulated in ubr-1 mutants providing a plausible mechanism for why ubr-1 mutants are resistant to Ivermectin. Although it is clear that loss of GluCls can lead to resistance to Ivermectin, this study suggests that one potential mechanism to decrease GluCl expression is via disruption of glutamate homeostasis that leads to increased glutamate. This study suggests that if parasitic worms become resistant to Ivermectin due to increased glutamate, their sensitivity to Ivermectin could be restored by reducing glutamate levels using drugs such as Ceftriaxone in a combination drug treatment strategy.

Strengths:

- The use of multiple independent assays (i.e., viability, body size, pharyngeal pumping, locomotion and serotonin-stimulated pharyngeal muscle activity) to monitor the effects of Ivermectin<br /> - The use of multiple independent approaches (got-1, eat-4, ceftriaxone drug, exogenous glutamate treatment) to alter glutamate levels to support the conclusion that increased glutamate in ubr-1 mutants contributes to Ivermectin resistance

Weaknesses:

- The primary target of Ivermectin is GluCls so it is not surprising that alteration of GluCl expression or function would lead to Ivermectin resistance<br /> - It remains to be seen what percent of Ivermectin resistant parasites in the wild have disrupted glutamate homeostasis as opposed to mutations that more directly decrease GluCl expression or function.

Comments on revisions: All my concerns have been addressed by the authors.

Reviewer #1 (Public review):

Summary:

Joshua G. Medina-Feliciano et al. investigated the single-cell transcriptomic profile of holoturian regenerating intestine following evisceration, a process used to expel their viscera in response to predation. Using single-cell RNA-Sequencing and standard analysis such as "Find cluster markers", "Enrichment analysis of Gene Ontology" and "RNA velocity", they identify 13 cell clusters and their potential cell identity. Based on bioinformatic analysis they identified potentially proliferating clusters and potential trajectories of cell differentiation. This manuscript represents a useful dataset that can provide candidate cell types and cell markers for more in-depth functional analysis of the holoturian intestine regeneration.

The conclusions of this paper are supported only by bioinformatic analyses since the in vivo validation through HCR is not sufficient to support them.

Strengths:

- The Authors are providing a single-cell dataset obtained from sea cucumbers regenerating their intestines. This represents the first fundamental step to an unbiased approach to better understand this regeneration process and the cellular dynamics taking part in it.

- The Authors run all the standard analyses providing the reader with a well digested set of information about cell clusters, potential cell types, potential functions and potential cell differentiation trajectories.

Weaknesses:

- The Authors frequently report the percentage of cells with a specific feature (either labelled or expressing a certain gene or belonging to a certain cluster). This number can be misleading since that is calculated after cell dissociation and additional procedures (such as staining or sequencing and dataset cleanup) that can heavily bias the ratio between cell types. Similarly, the Authors cannot compare cell percentage between anlage and mesentery samples since that can be affected by technical aspects related to cell dissociation, tissue composition and sequencing depth.

- The Authors did not validate all the clusters.

- There is no validation of the trajectory analysis and there is no validation of the proliferating cluster with H3P or EdU co-labeling.

Joint Public Review:

Páramo et al. used 3D geometric morphometric analyses of the articulated femur, tibia, and fibula of 17 macronarian taxa (known to preserve these three skeletal elements) to investigate morphological changes that occurred in the hind limb through the evolutionary history of this sauropod clade. A principal components analysis was completed to understand the distribution of the morphological variation. A supertree was constructed to place evolutionary trends in morphological variation into phylogenetic context, and hind limb centroid size was used to investigate potential relationships between skeletal anatomy and gigantism. The majority of the results did not yield statistically significant differences, but they did identify interesting shape-change trends, especially within subclades of Titanosauria. Many previous studies have attempted to elucidate a link between wide-gauge posture and gigantism, which in this study Páramo et al. investigate among several titanosaurian subclades. They propose that morphologies associated with wide-gauge posture arose in parallel with increasing body size among basal members of Macronaria and that this connection became less significant once wide-gauge posture was acquired within Titanosauria. The authors also suggest that other biomechanical factors influenced the independent evolution of subclades within Titanosauria and that these influences resulted in instances of convergent evolution. Therefore, they infer that, overall, wide-gauge posture was not significantly correlated with gigantism, though some morphological aspects of hind limb skeletal anatomy appear to have been associated with gigantism. Their work also supports previous findings of a decrease in body size within Titanosauriformes (which they found to be not significant with shape variables but significant with Pagel's lambda). Collectively, their results support and build on previous work to elucidate more specifics on the evolution of this enigmatic clade. Further study will show if their hypotheses stand or if the inclusion of additional specimens and taxa yields alternative results.

[Editors' note: One of the original reviewers, Reviewer 2, reviewed this revised version of the manuscript; they reported satisfaction with the changes made by the authors in response to the original reviewer comments.]

Reviewer #1 (Public review):

In this paper, the authors had 2 aims:

(1) Measure macaques' aversion to sand and see if its' removal is intentional, as it likely in an unpleasurable sensation that causes tooth damage.

(2) Show that or see if monkeys engage in suboptimal behavior by cleaning foods beyond the point of diminishing returns, and see if this was related to individual traits such as sex and rank, and behavioral technique.

They attempted to achieve these aims through a combination of geochemical analysis of sand, field experiments, and comparing predictions to an analytical model.

The authors' conclusions were that they verified a long-standing assumption that monkeys have an aversion to sand as it contains many potentially damaging fine grained silicates, and that removing it via brushing or washing is intentional.

They also concluded that monkeys will clean food for longer than is necessary, i.e. beyond the point of diminishing returns, and that this is rank-dependent.

High and low-ranking monkeys tended not to wash their food, but instead over-brushed it, potentially to minimize handling time and maximize caloric intake, despite the long-term cumulative costs of sand.

This was interpreted through the *disposable soma hypothesis*, where dominants maximize immediate needs to maintain rank and increase reproductive success at the potential expense of long-term health and survival.

# Strengths

The field experiment seemed well designed, and their quantification of the physical and mineral properties of quartz particles (relative to human detection thresholds) seemed good relative to their feret diameter and particle circularity (to a reviewer that is not an expert in sand). The *Rank Determination* and *Measuring Sand* sections were clear.

In achieving Aim 1, the authors validated a commonly interpreted, but unmeasured function, of macaque and primate behavior-- a key study/finding in primate food processing and cultural transmission research.

I commend their approach in trying to develop a quantitative model to generate predictions to compare to empirical data for their second aim.<br /> This is something others should strive for.

I really appreciated the historical context of this paper in the introduction and found it very enjoyable and easy to read.

I do think that interpreting these results in the context of the *disposable soma hypothesis* and the potential implications in the *paleolithic matters* section about interpreting dental wear in the fossil record are worthwhile.

# Weaknesses

Several of my concerns in an earlier review were addressed in revision, which I appreciate. One thing I think could strengthen this paper is a clearer link to social foraging theory to explore heterogeneity in handling times (as the currency they are trying to maximize).

I am satisfied with the improvements in statistics and that I can access the code and data.

I am still struck that there was an analysis of only trials where <3 individuals are present. If rank was important, I would imagine that behavior might be different in social contexts when theft, scrounging, policing, aggression, or other distractions might occur-- where rank would have effects on foraging behavior. Maybe lower rankers prioritize rapid food intake then. If rank should be related to investment in this behavior, we might expect this to be magnified (or different) in social contexts where it would affect foraging. It might just be that the data was too hard to score or process in those settings, or the analysis was limited. Additionally, I think that more robust metrics of rank from more densely sampled focal follow data would be a better measure, but I acknowledge the limitations in getting the ideal . Since rank is central to the interpretation of these results, I think that reduced social contexts in which rank was analyzed and the robustness of the data from which rank was calculated and analyzed are the main weaknesses of the evidence presented in this paper.

While some of the boxes about raccoons and Concorde Fallacy were interesting, they did feel like a bit of a distraction from the main message in the paper.

Reviewer #1 (Public review):

Summary:

In their manuscript, Gomez-Frittelli and colleagues characterize the expression of cadherin6 (and -8) in colonic IPANs of mice. Moreover, they found that these cdh6-expressing IPANs are capable of initiating colonic motor complexes in the distal colon, but not proximal and midcolon. They support their claim by morphological, electrophysiological and optogenetic, and pharmacological experiments.

Strengths:

The work is very impressive and involves several genetic models and state-of-the-art physiological setups including respective controls. It is a very well-written manuscript that truly contributes to our understanding of GI-motility and its anatomical and physiological basis. The authors were able to convincingly answer their research questions with a wide range of methods without overselling their results.

Weaknesses:

The authors put quite some emphasis on stating that cdh6 is a synaptic protein (in the title and throughout the text), which interacts in a homophilic fashion. They deduct that cdh6 might be involved in IPAN-IPAN synapses (line 247ff.). However, Cdh6 does not only interact in synapses and is expressed by non-neuronal cells as well (see e.g., expression in the proximal tubuli of the kidney). Moreover, cdh6 does not only build homodimers, but also heterodimers with Chd9 as well as Cdh7, -10, and -14 (see e.g., Shimoyama et al. 2000, DOI: 10.1042/0264-6021:3490159). It would therefore be interesting to assess the expression pattern of cdh6-proteins using immunostainings in combination with synaptic markers to substantiate the authors' claim or at least add the possibility of cell-cell-interactions other than synapses to the discussion. Additionally, an immunostaining of cdh6 would confirm if the expression of tdTomato in smooth muscle cells of the cdh6-creERT model is valid or a leaky expression (false positive).

Comments on revisions:

The authors have updated their manuscript and have provided insights and discussions to my remarks.

Reviewer #1 (Public review):

Summary:

Asthenospermia, characterized by reduced sperm motility, is one of the major causes of male infertility. The "9 + 2" arranged MTs and over 200 associated proteins constitute the axoneme, the molecular machine for flagellar and ciliary motility. Understanding the physiological functions of axonemal proteins, particularly their links to male infertility, could help uncover the genetic causes of asthenospermia and improve its clinical diagnosis and management. In this study, the authors generated Ankrd5 null mice and found that ANKRD5-/- males exhibited reduced sperm motility and infertility. Using FLAG-tagged ANKRD5 mice, mass spectrometry, and immunoprecipitation (IP) analyses, they confirmed that ANKRD5 is localized within the N-DRC, a critical protein complex for normal flagellar motility. However, transmission electron microscopy (TEM) and cryo-electron tomography (cryo-ET) of sperm from Ankrd5 null mice did not reveal any structural abnormalities.

Strengths:

The phenotypes observed in ANKRD5-/- mice, including reduced sperm motility and male infertility, are conversing. The authors demonstrated that ANKRD5 is an N-DRC protein that interacts with TCTE1 and DRC4. Most of the experiments are thoughtfully designed and well executed.

Weaknesses:

The cryo-FIB and cryo-ET analyses require further investigation, as detailed below. The molecular mechanism by which the loss of ANKRD5 affects sperm flagellar motility remains unclear. The current conclusion that Ankrd5 knockout reduces axoneme stability is not well-supported. Specifically, are other axonemal proteins diminished in Ankrd5 knockout sperm? Conducting immunofluorescence analyses and revisiting the quantitative proteomics data may help address these questions.

Reviewer #1 (Public review):

Summary:

In this study, the authors examined the role of Afadin, a key adaptor protein associated with cell-adhesion molecules, in retinal development. Using a conditional knockout mouse line (Six3-Cre; AfadinF/F), the authors successfully characterized a disorganized pattern of various neuron types in the mutant retinae. Despite these altered distributions, the retinal neurons maintained normal cell numbers and seemingly preserved some synaptic connections. Notably, tracing results indicated mistargeting of retinal ganglion cell (RGC) axon projections to the superior colliculus, and electroretinography (ERG) analyses suggested deficits in visual functions.

Strengths:

This compelling study provides solid evidence addressing the important question of how cell-adhesion molecules influence neuronal development. Compared to previous research conducted in other parts of the central nervous system (CNS), the clearly defined lamination of cell types in the retina serves as a unique model for studying the aberrant neuronal localizations caused by Afadin knockout. The data suggest that cell-cell interactions are critical for retinal cellular organization and proper axon pathfinding, while aspects of cell fate determination and synaptogenesis remain less understood. This work has broad implications not only for retinal studies but also for developmental biology and regenerative medicine.

Weaknesses:

While the phenotypes observed in the Afadin knockout (cKO) mice are intriguing, I would expect to see evidence confirming that Afadin is indeed knocked out in the retina through immunostaining. Specifically, is Afadin knocked out only in certain retinal regions and not others, as suggested by Figures 4A-B? Are Afadin levels different among distinct neuron types, which could mean that its knockout may have a more pronounced impact on certain cell types, such as rods compared to others?

The authors suggest that synapses may form between canonical synaptic partners, based on the proximity of their processes (Figure 2). However, more solid evidence is needed to verify these synapses through the use of synaptic marker staining or transsynaptic labeling before drawing further conclusions.

Although the Afadin cKO mice displayed dramatic phenotypes, additional experiments are necessary to clarify the details of this process. By manipulating Afadin levels in specific cell types or at different developmental time points, we could gain a better understanding of how Afadin regulates accurate retinal lamination and axonal projection.

Reviewer #1 (Public review):

Summary:

The authors address the role of the centromere histone core in force transduction by the kinetochore.

Strengths:

They use a hybrid DNA sequence that combines CDEII and CDEIII as well as Widom 601 so they can make stable histones for biophysical studies (provided by the Widom sequence) and maintain features of the centromere (CDE II and III).

Weaknesses:

The main results are shown in one figure (Figure 2). Indeed the Centromere core of Widom and CDE II and III contribute to strengthening the binding force for the OA-beads. The data are very nicely done and convincingly demonstrate the point. The weakness is that this is the entire paper. It is certainly of interest to investigators in kinetochore biology, but beyond that, the impact is fairly limited in scope.

Reviewer #2 (Public review):

Summary:

Casas-Tinto et al., provide new insight into glial plasticity using a crush injury paradigm in the ventral nerve cord (VNC) of adult Drosophila. The authors find that both astrocyte-like glia (ALG) and ensheating glia (EG) divide under homeostatic conditions in the adult VNC and identify ALG as the glial population that specifically ramps up proliferation in response to injury, whereas the number of EGs decreases following the insult. Using lineage-tracing tools, the authors interestingly observe interconversion of glial subtypes, especially of EGs into ALGs, which occurs independent of injury and is dependent on the availability of the transcription factor Prospero in EGs, adding to the plasticity observed in the system. Finally, when tracing the progeny of glia, Casas-Tinto and colleagues detect cells of neuronal identity and provide evidence that such glia-derived neurogenesis is favored following ventral nerve cord injury, which puts forward a remarkable way in which glia can respond to neuronal damage.

Strengths:

This study highlights a new facet of adult nervous system plasticity at the level of the ventral nerve cord, supporting the view that proliferative capacity is maintained in the mature CNS and stimulated upon injury.

The injury paradigm is well chosen, as the organization of the neuromeres allows specific targeting of one segment, compared to the remaining intact and with the potential to later link observed plasticity to behavior such as locomotion.

Numerous experiments have been carried out in 7-day old flies, showing that the observed plasticity is not due to residual developmental remodeling or a still immature VNC.

Different techniques are used to observe proliferation in the VNC.

By elegantly combining different methods, the authors show glial divisions including with mitotic-dependent tracing and find that the number of generated glia is refined by apoptosis later on.

The work identifies prospero in glia as important coordinator of glial cell fate, from development to the adult context, which draws further attention to the upstream regulatory mechanisms.

Weaknesses:

The authors do not discuss their results on gliogenesis or neurogenesis in the adult VNC to previous findings made in the context of the injured adult brain.

The authors speculate about the role of glial inter-conversion for tissue homeostasis or regeneration, but no supportive evidence is cited or provided. Further experiments will be required to test the function of the described glial plasticity.

Elav+ cells originating from glia do not express markers for mature neurons at the analysed time-point. If they will eventually differentiate<br /> or what type of structure is formed by them will have to be followed up in future studies.

Context/Discussion

Highlighting some differences in the reactiveness of glia in the VNC compared to the brain could reveal important differences in repair strategies in different areas of the CNS.

Reviewer #1 (Public review):

Summary:

The authors investigated sleep and circadian rhythm disturbances in Fmr1 KO mice. Initially, they monitored daily home cage behaviors to assess sleep and circadian disruptions. Next, they examined the adaptability of circadian rhythms in response to photic suppression and skeleton photic periods. To explore the underlying mechanisms, they traced retino-suprachiasmatic connectivity. The authors further analyzed the social behaviors of Fmr1 KO mice and tested whether a scheduled feeding strategy could mitigate sleep, circadian, and social behavior deficits. Finally, they demonstrated that scheduled feeding corrected cytokine levels in the plasma of mutant mice.

Strengths:

(1) The manuscript addresses an important topic-investigating sleep deficits in an FXS mouse model and proposing a potential therapeutic strategy.

(2) The study includes a comprehensive experimental design with multiple methodologies, which adds depth to the investigation.

Weaknesses:

(1) The first serious issue in the manuscript is the lack of a clear description of how they performed the experiments and the missing definitions of various parameters in the results. Given that monitoring and analyzing sleep behaviors are the key experiments of this manuscript, I use the "Immobility-Based Sleep Behavior" section of Methods as an example to elaborate:

Incomplete or Incorrect Description of Tracking Threshold:<br /> o The phrase "tracked the (40 sec or greater as previously described" is incomplete and does not clarify what is being tracked. This appears to be an error in writing or editing.<br /> Unclear Relationship Between Threshold and EEG Validation:<br /> o The threshold "40 sec or greater" is mentioned without context or explanation of what it represents (e.g., sleep bout duration, inactivity, or another parameter). The reference to Fisher et al. (2016) and "99% correlation with EEG-defined sleep" seems misaligned with the paragraph's content.

Confusing Definition of Sleep Bout:<br /> o The definition of a sleep bout is unclear. Sleep bouts should logically be based on periods of inactivity, not activity. The sentence suggesting sleep is measured by "activity staying above the threshold" is confusing. The phrase "3 counts of sleep per minute for longer than one minute" requires clarification.

Unclear Data Selection for Analysis:<br /> o The phrase "2 days with the best recording quality" is vague and does not specify how "best" was determined or why only two days out of five were analyzed.

Awkward Grammar and Structure:<br /> o Phrases like "Acquiring data were exported in 1-min bins" are grammatically awkward. "Acquiring" should be "Acquired." Some sentences are overly long and lack clarity, making the text harder to follow.<br /> In addition to this section, the authors should review all paragraphs in the Methods section to improve readability.

(2) Although the manuscript has a relatively long Methods section, some essential information is missing. For instance, the definition of sleep bout, as described above, is unclear. Additional missing information includes:

Figure 2: "Rhythmic strength (%)" and "Cycle-to-cycle variability (min)."<br /> Figure 3: "Activity suppression."<br /> Figure 4: "Rhythmic power (V%)" (is this different from rhythmic strength (%)?) and "Subjective day activity (%)."<br /> Figure 5: Clear labeling of the SCN's anatomical features and an explanation for quantifying only the ventral part instead of the entire SCN. Alternatively, the authors should consider quantifying the whole SCN.<br /> Figure 6: Inconsistencies in terms like "Sleep frag. (bout #)" and "Sleep bouts (#)." Consistent terminology throughout the manuscript is essential.

(3) Figure 1A shows higher mouse activity during ZT13-16. It is unclear why the authors scheduled feeding during ZT15-21, as this seems to disturb the rhythm. Consistent with this, the body weights of WT and Fmr1 KO mice decreased after scheduled feeding. The authors should explain the rationale for this design clearly.

(4) The interpretation of social behavior results in Figure 6 is questionable. The authors claim that Fmr1 KO mice cannot remember the first stranger in a three-chamber test, writing, "The reduced time in exploring and staying in the novel-mouse chamber suggested that the Fmr1 KO mutants were not able to distinguish the second novel mouse from the first now-familiar mouse." However, an alternative explanation is that Fmr1 KO mice do remember the first stranger but prefer to interact with it due to autistic-like tendencies. Data in Table 5 show that Fmr1 KO mice spent more time interacting with the first stranger in the 3-chamber social recognition test, which support this possibility. Similarly, in the five-trial social test, Fmr1 KO mice's preference for familiar mice might explain the reduced interaction with the second stranger.

In Figure 6C (five-trial social test results), only the fifth trial results are shown. Data for trials 1-4 should be provided and compared with the fifth trial. The behavioral features of mice in the 5-trial test can then be shown completely. In addition, the total interaction times for trials 1-4 (154 {plus minus} 15.3 for WT and 150 {plus minus} 20.9 for Fmr1 KO) suggest normal sociability in Fmr1 KO mice (it is different from the results of 3-chamber). Thus, individual data for trials 1-4 are required to draw reliable conclusions.

In Table 6 and Figure 6G-6J, the authors claim that "Sleep duration (Figures 6G, H) and fragmentation (Figures 6I, J) exhibited a moderate-strong correlation with both social recognition and grooming." However, Figure 6I shows a p-value of 0.077, which is not significant. Moreover, Table 6 shows no significant correlation between SNPI of the three-chamber social test and any sleep parameters. These data do not support the authors' conclusions.

(5) Figure 7 demonstrates the effect of scheduled feeding on circadian activity and sleep behaviors, representing another critical set of results in the manuscript. Notably, the WT+ALF and Fmr1 KO+ALF groups in Figure 7 underwent the same handling as the WT and Fmr1 KO groups in Figures 1 and 2, as no special treatments were applied to these mice. However, the daily patterns observed in Figures 7A, 7B, 7F, and 7G differ substantially from those shown in Figures 2B and 1A, respectively. Additionally, it is unclear why the WT+ALF and Fmr1 KO+ALF groups did not exhibit differences in Figures 7I and 7J, especially considering that Fmr1 KO mice displayed more sleep bouts but shorter bout lengths in Figures 1C and 1D.

Furthermore, it is not specified whether the results in Figure 7 were collected after two weeks of scheduled feeding (for how many days?) or if they represent the average data from the two-week treatment period.

The rationale behind analyzing "ZT 0-3 activity" in Figure 7D instead of the parameters shown in Figures 2C and 2D is also unclear.

In Figure 7F, some data points appear to be incorrectly plotted. For instance, the dark blue circle at ZT13 connects to the light blue circle at ZT14 and the dark blue circle at ZT17. This is inconsistent, as the dark blue circle at ZT13 should link to the dark blue circle at ZT14. Similarly, it is perplexing that the dark blue circle at ZT16 connects to both the light blue and dark blue circles at ZT17. Such errors undermine confidence in the data. The authors need to provide a clear explanation of how these data were processed.

Lastly, in the Figure 7 legend, Table 6 is cited; however, this appears to be incorrect. It seems the authors intended to refer to Table 7.

(6) Similar to the issue in Figure 7F, the data for day 12 in Supplemental Figure 2 includes two yellow triangles but lacks a green triangle. It is unclear how the authors constructed this chart, and clarification is needed.

(7) In Figure 8, a 5-trial test was used to assess the effect of scheduled feeding on social behaviors. It is essential to present the results for all trials (1 to 4). Additionally, it is unclear whether the results for familial mice in Figure 8A correspond to trials 1, 2, 3, or 4.<br /> The legend for Figure 8 also appears to be incorrect: "The left panels show the time spent in social interactions when the second novel stranger mouse was introduced to the testing mouse in the 5-trial social interaction test. The significant differences were analyzed by two-way ANOVA followed by Holm-Sidak's multiple comparisons test with feeding treatment and genotype as factors." This description does not align with the content of the left panels. Moreover, two-way ANOVA is not the appropriate statistical analysis for Figure 8A. The authors need to provide accurate details about the analysis and revise the figure legend accordingly.

(8) The circadian activity and sleep behaviors of Fmr1 KO mice have been reported previously, with some findings consistent with the current manuscript, while others contradict it. Although the authors acknowledge this discrepancy, it seems insufficiently thorough to simply state that the reasons for the conflicts are unknown. Did the studies use the same equipment for behavior recording? Were the same parameters used to define locomotor activity and sleep behaviors? The authors are encouraged to investigate these details further, as doing so may uncover something interesting or significant.

(9) Some subtitles in the Results section and the figure legends do not align well with the presented data. For example, in the section titled "Reduced rhythmic strength and nocturnality in the Fmr1 KOs," it is unclear how the authors justify the claim of altered nocturnality in Fmr1 KO mice. How do the authors define changes in nocturnality? Additionally, the tense used in the subtitles and figure legends is incorrect. The authors are encouraged to carefully review all subtitles and figure legends to correct these errors and enhance readability.

Reviewer #1 (Public review):

Summary:

This manuscript presents a comprehensive structure-guided secretome analysis of gall-forming microbes, providing valuable insights into effector diversity and evolution. The authors have employed AlphaFold2 to predict the 3D structures of the secretome from selected pathogens and conducted a thorough comparative analysis to elucidate commonalities and unique features of effectors among these phytopathogens.

Strengths:

The discovery of conserved motifs such as 'CCG' and 'RAYH' and their central role in maintaining the overall fold is an insightful finding. Additionally, the discovery of a nucleoside hydrolase-like fold conserved among various gall-forming microbes is interesting.

Weaknesses:

Important conclusions are not verified by experiments.

Reviewer #1 (Public review):

Summary:

The goal of this study was to overcome the apparent difficulty in constructing structural models of the open state of the CFTR chloride channel. While several CFTR structural models at near-atomic resolution have been published under a variety of conditions, none of them have demonstrated a pore open across the full dimension of the plasma membrane. Instead, these have routinely been referred to as "near-open" models. In the present study, the authors extended their findings from a prior paper from their group that investigated a series of brief MD simulations, a small number of which exhibited permeation events where chloride ions permeated the pore. This study included massively repeated simulations initiated from these aforementioned Cl permeable conformations. Extensive analysis of the data identified a novel penta-helical structure that comprises the channel pore. This comprehensive study attempted to explain several features of conducting CFTR channels, including single-channel conductance, selectivity, and the mechanisms linking the ATP-induced dimerization of the cytosolic nucleotide-binding domains (NBDs) to the opening of the channel pore (a.k.a., "pore-gating".

Strengths:

The major strength of this study is its comprehensive nature. The approaches applied are cutting-edge and beyond, and are used to explain many different aspects of channel function in CFTR. The strength of evidence is very strong. The paper is extremely well-written, and the arguments are well-supported.

Weaknesses:

The major weakness is that none of the novel conclusions (i.e., those arising solely from this study and not previously published (have been supported by experimental confirmation. That is typical of computational studies such as this.

Reviewer #1 (Public review):

Summary:

This paper investigated the dynamic self-assembly of branched actin networks and the relation between the nonequilibrium features of the dynamics with the thermodynamic cost. The authors constructed a chain model to describe the self-assembly process of a branched actin network, including events like nucleation, polymerization, and capping. The forward and backward transition rates associated with the events allowed them to investigate the entropy production rate of the dynamics. They then used the fact that the entropy production rate has to be greater than zero to derive inequalities that set bounds for the maximum force produced by the branched actin network. The idea is similar to estimating the polymerization force of actin filament via the equation F_{max} = dG/delta, which sets a bound on the maximum force by the thermodynamic potential dG which is the chemical energy associated with ATP hydrolysis and delta is the length increment upon monomer insertion. Furthermore, they speculated the dissipative cost beyond what is necessary to move the load may be necessary to maintain an adaptive steady state.

Strengths:

The authors developed a simple model that is capable of qualitatively reproducing some mechanical phenomena for a branched actin network. The model has captured the essential dynamic elements in the branched actin network and built connections between the maximum load and the adaptation behavior with the energetic cost. It is an interesting study that provides a new perspective to look at the mechanical response of the branched actin network.

Weaknesses:

The text needs to be improved, particularly in the model introduction part. It is unclear to me what happens to the state when the reverse reaction in Figure 2 occurs.

Furthermore, what the authors have done is similar to estimate the polymerization force of actin filaments but in a more complicated scenario. Their conclusion that "dissipative cost in the system beyond what is necessary to move the load may be necessary to maintain an adaptive steady state" is skeptical. The branched actin network is a nonequilibrium system driven by active processes like ATP hydrolysis that converts chemical energy into mechanical work. There has to be a gap between the actual E-C_f curve and that when dissipation rate dot{S} = 0. If the authors want to make the claim, they have to decompose the dissipation into different parts and show that a particular part is associated with adaption. Otherwise, the conclusion about the gap is baseless.