Reviewer #2 (Public Review):

There are data to suggest that intratumour mutational heterogeneity (ITH; the proportion of all mutations that are found only within cancer subclones) is associated with worse therapeutic outcomes. Specifically, patients with more mutations (and thus neoantigens) mostly expressed by subclones (high ITH) have poorer responses to checkpoint immunotherapy. The authors set out to explore the mechanisms underlying this by studying 2 dimensions of neoantigen biology: firstly, distribution (clonal vs subclonal) and secondly, immunogenicity (weak vs strong binding to MHC class I). Using a panel of lung cancer cell lines modified to express individual or dual neoantigens in order to model clonal and subclonal expression, elegant studies show that clonal co-expression with a "strong" neoantigen can boost the immunogenicity of a "weak" neoantigen and result in tumour control. Mechanistically, this is related to engulfment of both neoantigens by cross presenting type 1 conventional dendritic cells and the associated enhanced activation state of this cell type. This is an interesting and potentially important finding that may be related to mechanisms of epitope spreading as immune responses diverge from targeting more to less immunogenic epitopes. Overall, the study is thought-provoking, informative in relation to how neoantigen immunogenicity is shaped and may have practical relevance.

Reviewer #1 (Public Review):

The authors aim to understand the role of clonal heterogeneity of tumors in immunogenicity of clonally expressed antigens. This is a significant problem with many basic as well as translational implications.

The strength of the manuscript lies in the novel demonstration that a poorly immunogenic tumor antigen, when paired with a stronger tumor antigen, begins to elicit significant immune response. The weakness lies in the fact that the actual mechanism of the key demonstration is never shown. There is a lot of speculation and tangential experimentation, but little actual evidence of a mechanism.

By making the key observation (mentioned in the strength section in the previous paragraph), the authors did achieve their objective albeit very partially. Their observation is based on excellent experimental tools and design. This study will stimulate further experiments in this important field.

Their key observation is somewhat reminiscent of the practice of conjugating small "non-immunogenic" antigens (such as some carbohydrates) to large protein carriers (such as serum albumin) in order to elicit strong antibody response to the weaker antigen. It is interesting to contemplate if the underlying mechanisms have any commonality.

Reviewer #1 (Public Review):

Zhou et al. have set up a study to examine how metabolism is regulated across the organism by taking a combined approach looking at gene expression in multiple tissues, as well as analysis of the blood. Specifically, they have created a tool for easily analyzing data from GTEx across 18 tissues in 310 people. In principle, this approach should be expandable to any dataset where multiple tissues of data were collected from the same individuals. While not necessary, it would also raise my interest to see the "Mouse(coming soon)" selection functional, given that the authors have good access to multi-tissue transcriptomics done in similarly large mouse cohorts.

Summary:

The authors have assembled a web tool that helps analyze multiple tissues' datasets together, with the aim of identifying how metabolic pathways and gene regulation are connected across tissues. This makes sense conceptually and the web tool is easy to use and runs reasonably quickly, considering the size of the data. I like the tool and I think the approach is necessary and surprisingly under-served; there is a lot of focus on multi-omics recently, but much less on doing a good job of integrating multi-tissue datasets even within a single omics layer.

What I am less convinced about is the "Research Article" aspect of this paper. Studying circadian rhythm in GTEx data seems risky to me, given the huge range in circadian clock in the sample collection. I also wonder (although this is not even remotely in my expertise) whether the circadian rhythm also gets rather desynchronized in people dying of natural causes - although I suppose this could be said for any gene expression pathway. Similarly for looking at secreted proteins in Figure 4 looking at muscle-hippocampus transcript levels for ADAMTS17 doesn't make sense to me - of all tissue pairs to make a vignette about to demonstrate the method, this is not an intuitive choice to me. The "within muscle" results look fine but panels C-E-G look like noise to me...especially panel C and G are almost certainly noise, since those are pathways with gene counts of 2 and 1 respectively.

I think this is an important effort and a good basis but a significant revision is necessary. This can devote more time and space to explaining the methodology and for ensuring that the results shown are actually significant. This could be done by checking a mix of negative controls (e.g. by shuffling gene labels and data) and a more comprehensive look at "positive" genes, so that it can be clearly shown that the genes shown in Fig 1 and 2 are not cherry-picked. For Figure 3, I suspect you would get almost an identical figure if instead of showing pan-tissue circadian clock correlations, you instead selected the electron transport chain, or the ribosome, or any other pathway that has genes that are expressed across all tissues. You show that colon and heart have relatively high connectivity to other tissues, but this may be common to other pathways as well.

Reviewer #2 (Public Review):

Summary:

Zhou et al. use publicly available GTEx data of 18 metabolic tissues from 310 individuals to explore gene expression correlation patterns within-tissue and across-tissues. They detect signatures of known metabolic signaling biology, such as ADIPOQ's role in fatty acid metabolism in adipose tissue. They also emphasize that their approach can help generate new hypotheses, such as the colon playing an important role in circadian clock maintenance. To aid researchers in querying their own genes of interest in metabolic tissues, they have developed an easy-to-use webtool (GD-CAT).

This study makes reasonable conclusions from its data, and the webtool would be useful to researchers focused on metabolic signaling. However, some misconceptions need to be corrected, as well as greater clarification of the methodology used.

Strengths:

GTEx is a very powerful resource for many areas of biomedicine, and this study represents a valid use of gene co-expression network methodology. The authors do a good job of providing examples confirming known signaling biology as well as the potential to discover promising signatures of novel biology for follow-up and future studies. The webtool, GD-CAT, is easy to use and allows researchers with genes and tissues of interest to perform the same analyses in the same GTEx data.

Weaknesses:

A key weakness of the paper is that this study does not involve genetic correlations, which is used in the title and throughout the manuscript, but rather gene co-expression networks. The authors do mention the classic limitation that correlation does not imply causation, but this caveat is even more important given that these are not genetic correlations. Given that the goal of their study aligns closely with multi-tissue WGCNA, which is not a new idea (e.g., Talukdar et al. 2016; https://doi.org/10.1016/j.cels.2016.02.002), it is surprising that the authors only use WGCNA for its robust correlation estimation (bicor), but not its latent factor/module estimation, which could potentially capture cross-tissue signaling patterns. It is possible that the biological signals of interest would be drowned out by all the other variation in the data but given that this is a conventional step in WGCNA, it is a weakness that the authors do not use it or discuss it.

Reviewer #3 (Public Review):

Summary:

A useful and potentially powerful analysis of gene expression correlations across major organ and tissue systems that exploits a subset of 310 humans from the GTEx collection (subjects for whom there are uniformly processed postmortem RNA-seq data for 18 tissues or organs). The analysis is complemented by a Shiny R application web service.

The need for more multisystems analysis of transcript correlation is very well motivated by the authors. Their work should be contrasted with more simple comparisons of correlation structure within different organs and tissues, rather than actual correlations across organs and tissues.

Strengths and Weaknesses:

The strengths and limitations of this work trace back to the nature of the GTEx data set itself. The authors refer to the correlations of transcripts as "gene" and "genetic" correlations throughout. In fact, they name their web service "Genetically-Derived Correlations Across Tissues". But all GTEx subjects had strong exposure to unique environments and all correlations will be driven by developmental and environmental factors, age, sex differences, and shared and unshared pre- and postmortem technical artifacts. In fact we know that the heritability of transcript levels is generally low, often well under 25%, even studies of animals with tight environmental control.

This criticism does not comment materially detract for the importance and utility of the correlations-whether genetic, GXE, or purely environmental-but it does mean that the authors should ideally restructure and reword text so as to NOT claim so much for "genetics". It may be possible to incorporate estimates of chip heritability of transcripts into this work if the genetic component of correlations is regarded as critical (all GTEx cases have genotypes).

Appraisal of Work on the Field:

There are two parts to this paper: 1. "case studies" of cross-tissue/organ correlations and 2. the creation of an R/Shiny application to make this type of analysis much more practical for any biologist. Both parts of the work are of high potential value, but neither is fully developed. My own opinion is that the R/Shiny component is the more important immediate contribution and that the "case studies" could be placed in the context of a more complete primer. Or Alternatively, the case studies could be their own independent contributions with more validation.

Reviewer #3 (Public Review):

In this paper, the authors analyze a large previously published deep mutational scanning data set using a reference-free regression approach. They extract the contributions of single locus and epistatic effects to the functionality of the sequence (no, weak or strong transcription activation of two response elements). They find that pairwise epistasis plays a crucial and dominant role at creating functional sequences and at connecting the functional sequence space.

I enjoyed reading the paper and the topic (role of epistasis at creating and connecting functional sequences; development of measures of epistasis) is very exciting to me. However, I found it difficult to judge the strength of the paper both because it is written in a rather dense and yet potentially redundant fashion (see comment 1) and because I was left with a number of questions upon reading. I will focus on conceptual questions in the following comments, since I am not able to judge the statistical approach in detail.

1/ Regarding the biological result (importance of pairwise epistasis) I was wondering how potentially redundant the consecutive sections of the paper are. In which situation would the authors expect that pairwise epistasis does *not* play a crucial role for mutational steps, trajectories, or space connectedness, if it is dominant in the genotype-phenotype landscape? I would also appreciate an explanation of how much new biological results this paper delivers as compared with the paper in which the data were published (which I, unfortunately, cannot access at the moment of writing this report).

2a/ Regarding the regression approach: I very much appreciate a reference-free approach to the estimation of epistasis. However, I would enjoy an explanation of how the results would have been (potentially) different if a reference-based approach was used, and how it compares with other reference-free approaches to estimating epistasis (e.g., linear regression or the gamma statistics of Ferretti et al. 2015).

2b/ When comparing the outcomes with and without epistasis, I understood that the authors compare the estimated "full model" with the outcome if epistatic effects were ignored - but without a new estimation of main effects if epistasis is ignored. Wouldn't that be a more fair comparison?

2c/ Where do the authors see the applicability of their approach to data beyond those analyzed in the present study? What are the requirements to use it? Does it only work for combinatorially complete landscapes? I did not have a chance to look at the code - how easily could other researchers apply the approach to their data?

Reviewer #1 (Public Review):

Metzger et al develop a rigorous method filling an important unmet need in protein evolution - analysis of protein genetic architecture and evolution using data from combinatorially complete 20^N variant libraries. Addressing this need has become increasingly valuable, as experimental methods for generating these datasets expand in scope and scale. Their model incorporates several key features - (1) it reports the effects of mutations relative to the average across all variants, rather than a particular genotype, making it useful for examining genetic architectures and evolution in a less biased way, (2) it infers contributions from both "specific" and "non-specific" epistasis, which is essential for some experimental measurements, and perhaps most importantly (3) it does this for all possible 20 states at each site, in contrast to the binary analyses in prior work. These features are not individually novel but integrating them into a single analysis framework is novel and will be incredibly valuable to the protein evolution community. Using a previously published dataset generated by two of the authors, they conclude that (1) changes in function are largely attributable to pairwise but not higher-order interactions, and (2) epistasis potentiates, rather than constrains, evolutionary paths. These findings are well-supported by the data, though the authors' claim that higher-order epistasis cannot account for the variation they see could be better supported by additional analyses or discussion (as noted in recommendations for authors). Overall, this work has important implications for predicting the relationship between genotype and phenotype, which is of considerable interest to protein biochemistry, evolutionary biology, and numerous other fields.

Reviewer #2 (Public Review):

The authors aimed to understand how epistasis influences the genetic architecture of the DNA-binding domain (DBD) of steroid hormone receptor. An ordinal regression model was developed in this study to analyze a published deep mutational scanning dataset that consists of all combinatorial amino acid variants across four positions (i.e. 160,000 variants). This published dataset measured the binding of each variant to the estrogen receptor response element (ERE, sequence: AGGTCA) as well as the steroid receptor response element (SRE, sequence: AGAACA). This model has major strengths of being reference free and able to account for global nonlinearity in the genotype-phenotype relationship. Thorough analyses of the modelling results have performed, which provided convincing results to support the importance of epistasis in promoting evolution of protein functions. This conclusion is impactful because many previous studies have shown that epistasis constrains evolution. However, the model in this study requires transformation of continuous functional data into categorical form, which would reduce precision in estimating the genetic architecture. Besides, generalizability of the findings in this study is unclear. These limitations, which are acknowledged by the authors, are minor and should not affect the conclusion of this study. The novelty of this study will likely stimulate new ideas in the field. The model will also likely be utilized by other groups in the community.

Reviewer #2 (Public Review):

This study aims to describe a physical interaction between the kinase DYRK1A and the Tuberous Sclerosis Complex proteins (TSC1, TSC2, TBC1D7). Furthermore, this study aims to demonstrate that DYRK1A, upon interaction with the TSC proteins regulates mTORC1 activity and cell size. Additionally, this study identifies T1462 on TSC2 as a phosphorylation target of DYRK1A. Finally, the authors demonstrate the role of DYRK1A on cell size using human, mouse, and Drosophila cells.

This study, as it stands, requires further experimentation to support the conclusions on the role of DYRK1A on TSC interaction and subsequently on mTORC1 regulation. Weaknesses include, 1) The lack of an additional assessment of cell growth/size (eg. protein content, proliferation), 2) the limited data on the requirement of DYRK1A for TSC complex stability and function, and 3) the limited perturbations on the mTORC1 pathway upon DYRK1A deletion/overexpression. Finally, this study would benefit from identifying under which nutrient conditions DYRK1A interacts with the TS complex to regulate mTORC1.

The interaction described here is highly impactful to the field of mTORC1-regulated cell growth and uncovers a previously unrecognized TSC-associated interacting protein. Further characterization of the role that DYRK1A plays in regulating mTORC1 activation and the upstream signals that stimulate this interaction will be extremely important for multiple diseases that exhibit mTORC1 hyper-activation.

Reviewer #1 (Public Review):

In this manuscript, Wang et al. demonstrate that knockdown of DYRK1A results in reduced cell size, which is mediated by mTORC1 activity. They found that DYRK1A interacts with TSC1/TSC2 proteins which leads to the phosphorylation of TSC2 at T1462. Phosphorylation of TSC2 at T1462 inhibits TSC2 activity leading to the activation of mTORC1. The authors complement their findings by demonstrating that overexpression of RHEB (positive regulator of mTORC1) rescues the phenotype of DYRK1A (mnb in flies) mutation in the NMJ.

The authors' findings on the regulation of cell size and mTORC1 activity by DYRK1A reflect the previous findings of Levy et al. (PMID: 33840455) that cortical deletion of Dyrk1a in mice causes decreased neuronal size associated with a decreased activity of mTORC1 that can be rescued by the inhibition of Pten or supplementation of IGF1.

The authors demonstrate that T1462 phospho-site at TSC2 is phosphorylated in response to the overexpression of WT but not kinase-dead DYRK1A. However, the authors do not provide any evidence that the regulation of mTORC1 is mediated via phosphorylation of this site. In addition, T1462 site is known to be phosphorylated by Akt. There is a possibility that Akt was co-purified with TSC1/TSC2 complex and DYRK1A promotes phosphorylation of TSC2 indirectly via the activation of AKT that can be tested by using AKT depleted cells.

RHEB is the most proximal regulator of mTORC1 and can activate mTORC1 even under amino acid starvation. The fact that RHEB overexpression rescues the cell size under DYRK1A depletion or mnb (DYRK1A in Drosophila) mutant phenotype does not prove that DYRK1A regulates the cell size via TSC1 as it would rescue any inhibitory effects upstream to mTORC1.

Reviewer #3 (Public Review):

The manuscript describes a combination of in vitro and in vivo results implicating Dyrk1a in the regulation of mTORC. Particular strengths of the data are this combination of cell and whole animal (drosophila) based studies. However, most of the experiments seem to lack a key additional experimental condition that could increase confidence in the authors' conclusions. Overall some tantalizing data is presented. However, there are several issues that should be clarified or otherwise addressed with additional data.

1. In Figure 1G, why not test overexpression levels of Dyrk1a via western rather than only looking at the RNA levels?

2. In Figure 2, while there is clearly TSC1 protein in the Dyrk1a and FLAG-Dyrk1a IPs that supports an interaction between the proteins, it would be good to see the reciprocal IP experiment wherein TSC1 or TSC2 are pulled down and then the blot probed for Dyrk1a.

3. Figures 3 A and D tested the effects of Dyrk1a knockdown using different methods in different cell lines. This is a reasonable approach to ascertain the generalizability of findings. However, each experiment is performed differently. For example, in 3A, the authors found no difference in baseline pS6, so they did a time course of treatment to induce phosphorylation and found differences depending on Dyrk1a expression. In 3D, they only show baseline effects from the CRISPr knockdown. Why not do the time course as well for consistency? Also, why the inconsistency in approaches wherein one shows baseline effects and the other does not? The authors could also consider the pharmacologic inhibition of Dyrk1a activity as well.

4. In Figure 4, RHEB overexpression increases cell size in both Dyrk1a wt and Dyrk1a shRNA treated cells, although the magnitude of the effect appears reduced in Dyrk1a shRNA cells. However, there is the possibility here that RHEB acts independently of Dyrk1a. Why not also do the experiment of Figure 1 wherein Dyrk1a is overexpressed and then knockdown RHEB in that context? If the hypothesis is supported, then RHEB knockdown should eliminate the cell size effect of Dyrk1a overexpression.

5. The discussion should incorporate relevant findings from other models, such as Arabidopsis. Barrada et al., Development (2019), 146 (3).

Reviewer #3 (Public Review):

This work provides a novel design of implantable and high-density EMG electrodes to study muscle physiology and neuromotor control at the level of individual motor units. Current methods of recording EMG using intramuscular fine-wire electrodes do not allow for isolation of motor units and are limited by the muscle size and the type of behavior used in the study. The authors of myomatrix arrays had set out to overcome these challenges in EMG recording and provided compelling evidence to support the usefulness of the new technology.

Strengths:

• They presented convincing examples of EMG recordings with high signal quality using this new technology from a wide array of animal species, muscles, and behavior.<br /> • The design included suture holes and pull-on tabs that facilitate implantation and ensure stable recordings over months.<br /> • Clear presentation of specifics of the fabrication and implantation, recording methods used, and data analysis

Weaknesses:

• The justification for the need to study the activity of isolated motor units is underdeveloped. The study could be strengthened by providing example recordings from studies that try to answer questions where isolation of motor unit activity is most critical. For example, there is immense value for understanding muscles with smaller innervation ratio which tend to have many motor neurons for fine control of eyes and hand muscles.

Reviewer #1 (Public Review):

The main objective of this paper is to report the development of a new intramuscular probe that the authors have named Myomatrix arrays. The goal of the Myomatrix probe is to significantly advance the current technological ability to record the motor output of the nervous system, namely fine-wire electromyography (EMG). Myomatrix arrays aim to provide large-scale recordings of multiple motor units in awake animals under dynamic conditions without undue movement artifacts and maintain long-term stability of chronically implanted probes. Animal motor behavior occurs through muscle contraction, and the ultimate neural output in vertebrates is at the scale of motor units, which are bundles of muscle fibers (muscle cells) that are innervated by a single motor neuron. The authors have combined multiple advanced manufacturing techniques, including lithography, to fabricate large and dense electrode arrays with mechanical features such as barbs and suture methods that would stabilize the probe's location within the muscle without creating undue wiring burden or tissue trauma. Importantly, the fabrication process they have developed allows for rapid iteration from design conception to a physical device, which allows for design optimization of the probes for specific muscle locations and organisms. The electrical output of these arrays are processed through a variety of means to try to identify single motor unit activity. At the simplest, the approach is to use thresholds to identify motor unit activity. Of intermediate data analysis complexity is the use of principal component analysis (PCA, a linear second-order regression technique) to disambiguate individual motor units from the wide field recordings of the arrays, which benefits from the density and numerous recording electrodes. At the highest complexity, they use spike sorting techniques that were developed for Neuropixels, a large-scale electrophysiology probe for cortical neural recordings. Specifically, they use an estimation code called kilosort, which ultimately relies on clustering techniques to separate the multi-electrode recordings into individual spike waveforms.

An account of the major strengths and weaknesses of the methods and results.<br /> The biggest strength of this work is the design and implementation of the hardware technology. It is undoubtedly a major leap forward in our ability to record the electrical activity of motor units. The myomatrix arrays trounce fine-wire EMGs when it comes to the quality of recordings, the number of simultaneous channels that can be recorded, their long-term stability, and resistance to movement artifacts.

The primary weakness of this work is its reliance on kilosort in circumstances where most of the channels end up picking up the signal from multiple motor units. As the authors quite convincingly show, this setting is a major weakness for fine-wire EMG. They argue that the myomatrix array succeeds in isolating individual motor unit waveforms even in that challenging setting through the application of kilosort.

Although the authors call the estimated signals as well-isolated waveforms, there is no independent evidence of the accuracy of the spike sorting algorithm. The additional step (spike sorting algorithms like kilosort) to estimate individual motor unit spikes is the part of the work in question. Although the estimation algorithms may be standard practice, the large number of heuristic parameters associated with the estimation procedure are currently tuned for cortical recordings to estimate neural spikes. Even within the limited context of Neuropixels, for which kilosort has been extensively tested, basic questions like issues of observability, linear or nonlinear, remain open. By observability, I mean in the mathematical sense of well-posedness or conditioning of the inverse problem of estimating single motor unit spikes given multi-channel recordings of the summation of multiple motor units. This disambiguation is not always possible. kilosort's validation relies on a forward simulation of the spike field generation, which is then truth-tested against the sorting algorithm. The empirical evidence is that kilosort does better than other algorithms for the test simulations that were performed in the context of cortical recordings using the Neuropixels probe. But this work has adopted kilosort without comparable truth-tests to build some confidence in the application of kilosort with myomatrix arrays? Furthermore, as the paper on the latest version of kilosort, namely v4, discusses, differences in the clustering algorithm is the likely reason for kilosort4 performing more robustly than kilosort2.5 (used in the myomatrix paper). Given such dependence on details of the implementation and the use of an older kilosort version in this paper, the evidence that the myomatrix arrays truly record individual motor units under all the types of data obtained is under question.

There is an older paper with a similar goal to use multi-channel recording to perform source-localization that the authors have failed to discuss. Given the striking similarity of goals and the divergence of approaches (the older paper uses a surface electrode array), it is important to know the relationship of the myomatrix array to the previous work. Like myomatrix arrays, the previous work also derives inspiration from cortical recordings, in that case it uses the approach of source localization in large-scale EEG recordings using skull caps, but applies it to surface EMG arrays. Ref: van den Doel, K., Ascher, U. M., & Pai, D. K. (2008). Computed myography: three-dimensional reconstruction of motor functions from surface EMG data. Inverse Problems, 24(6), 065010.

The incompleteness of the evidence that the myomatrix array truly measures individual motor units is limited to the setting where multiple motor units have similar magnitude of signal in most of the channels. In the simpler data setting where one motor dominates in some channel (this seems to occur with some regularity), the myomatrix array is a major advance in our ability to understand the motor output of the nervous system. The paper is a trove of innovations in manufacturing technique, array design, suture and other fixation devices for long-term signal stability, and customization for different muscle sizes, locations, and organisms. The technology presented here is likely to achieve rapid adoption in multiple groups that study motor behavior, and would probably lead to new insights into the spatiotemporal distribution of the motor output under more naturally behaving animals than is the current state of the field.

Reviewer #2 (Public Review):

Motoneurons constitute the final common pathway linking central impulse traffic to behavior, and neurophysiology faces an urgent need for methods to record their activity at high resolution and scale in intact animals during natural movement. In this consortium manuscript, Chung et al. introduce high-density electrode arrays on a flexible substrate that can be implanted into muscle, enabling the isolation of multiple motor units during movement. They then demonstrate these arrays can produce high-quality recordings in a wide range of species, muscles, and tasks. The methods are explained clearly, and the claims are justified by the data. While technical details on the arrays have been published previously, the main significance of this manuscript is the application of this new technology to different muscles and animal species during naturalistic behaviors. Overall, we feel the manuscript will be of significant interest to researchers in motor systems and muscle physiology, and we have no major concerns. A few minor suggestions for improving the manuscript follow.

The authors perhaps understate what has been achieved with classical methods. To further clarify the novelty of this study, they should survey previous approaches for recording from motor units during active movement. For example, Pflüger & Burrows (J. Exp. Biol. 1978) recorded from motor units in the tibial muscles of locusts during jumping, kicking, and swimming. In humans, Grimby (J. Physiol. 1984) recorded from motor units in toe extensors during walking, though these experiments were most successful in reinnervated units following a lesion. In addition, the authors might briefly mention previous approaches for recording directly from motoneurons in awake animals (e.g., Robinson, J. Neurophys. 1970; Hoffer et al., Science 1981).

For chronic preparations, additional data and discussion of the signal quality over time would be useful. Can units typically be discriminated for a day or two, a week or two, or longer? A related issue is whether the same units can be tracked over multiple sessions and days; this will be of particular significance for studies of adaptation and learning.

It appears both single-ended and differential amplification were used. The authors should clarify in the Methods which mode was used in each figure panel, and should discuss the advantages and disadvantages of each in terms of SNR, stability, and yield, along with any other practical considerations.

Is there likely to be a motor unit size bias based on muscle depth, pennation angle, etc.?

Can muscle fiber conduction velocity be estimated with the arrays?

The authors suggest their device may have applications in the diagnosis of motor pathologies. Currently, concentric needle EMG to record from multiple motor units is the standard clinical method, and they may wish to elaborate on how surgical implantation of the new array might provide additional information for diagnosis while minimizing risk to patients.

Reviewer #1 (Public Review):

The current manuscript provides a timely contribution to the ongoing discussion about the mechanism of the apical sodium/bile acid transporter (ASBT) transporters. Recent structures of the mammalian ASBT transporters exhibited a substrate binding mode with few interactions with the core domain (classically associated with substrate binding), prompting an unusual proposal for the transport mechanism. Early structures of ASBT homologues from bacteria also exhibit unusual substrate binding in which the core substrate binding domain is less engaged than expected. Due to the ongoing questions of how substrate binding and mechanism are linked in these transporters, the authors set out to deepen our understanding of a model ABST homolog from bacteria N. meningitidis (ABST-NM).

The premise of the current paper is that the bacterial ASBT homologs are probably not physiological bile acid transporters, and that structural elucidation of a natively transported substrate might provide better mechanistic information. In the current manuscript, the authors revisit the first BASS homologue to be structurally characterized, ABST-NM. Based on bacteriological assays in the literature, the authors identify the coenzyme A precursor pantoate as a more likely substrate for ABST-NM than taurocholate, the substrate in the original structure. A structure of ASBT-NM with pantoate exhibits interesting differences in structure. The structures are complemented with MD simulations, and the authors propose that the structures are consistent with a classical elevator transport mechanism.

The structural experiments are generally solid, although showing omit maps would bolster the identification of the substrate binding site. One shortcoming is that, although pantoate binding is observed, the authors do not show transport of this substrate, undercutting the argument that the pantoate structure represents binding of a "better" or more native substrate. Mechanistic proposals, like the proposed role of T112 in unlocking the transporter, would be much better supported by transport data.

Reviewer #2 (Public Review):

The manuscript starts with a demonstration of pantoate binding to ASBTnm using a thermostability assay and ITC, and follows with structure determinations of ASBTnm with or without pantoate. The structure of ASBTnm in the presence of pantoate pinpoints the binding site of pantoate to the "crossover" region formed by partially unwinded helices TMs 4 and 9. Binding of pantoate induces modest movements of side chain and backbone atoms at the crossover region that are consistent with providing coordination of the substrate. The structures also show movement of TM1 that opens the substrate binding site to the cytosol and mobility of loops between the TMs. MD simulations of the ASBT structure embedded in lipid bilayer suggests a stabilizing effect of the two sodium ions that are known to co-transport with the substrate. Binding study on pantoate analogs further demonstrates the specificity of pantoate as a substrate.

The weakness of the manuscript includes a lack of transport assay for pantoate and a lack of demonstration that the observed conformational changes in TM1 and the loops are relevant to the binding or transport of pantoate.

Overall, the structural, functional and computational studies are solid and rigorous, and the conclusions are well justified. In addition, the authors discussed the significance of the current study in a broader perspective relevant to recent structures of mammalian BASS members.

Reviewer #3 (Public Review):

The manuscript describes new ligand-bound structures within the larger bile acid sodium symporter family (BASS). This is the primary advance in the manuscript, together with molecular simulations describing how sodium and the bile acids sit in the structure when thermalized. What I think is fairly clear is that the ligands are more stable when the sodiums are present, with a marked reduction in RMSD over the course of repeated trajectories. This would be consistent with a transport model where sodium ions bind first, and then the bile acid binds, followed by a conformational change to another state where the ligands unbind.

While the authors mention that BASS transporters are thought to undergo an elevator transport mechanisms, this is not tested here. In my reading, all the crystal structures describe the same conformational state, and the simulations do not make an attempt to induce a transition on accessible simulation timescales. Instead, there is a morph between two states where different substrates are bound, which induces a conformational change that looks unrelated to the transport cycle.

Instead, the focus is on what kinds of substrates bind to this transporter, interrogating this with isothermal calorimetry together with mutations. With a Kd in the micromolar range, even the best binder, pantoate, actually isn't a particularly tight binder in the pharmaceutical sense. For a transporter, tight binding is not actually desirable, since the substrate needs to be able to leave after conformational change places it in a position accessible to the other side.

There is one really important point that readers and authors should be aware of. In Figure 2A, the names are not consistent with the chemical structure. "-ate" denotes when a carboxylic acid is in the deprotonated form, creating a charged carboxylate. What is drawn is pantoic acid, ketopantoic acid, and pantoethenic acid. Less importantly, the wedges and hashes for the methyl group are arguably not appropriate, since the carbon they are attached to is not a chiral center. For the crystallization, this makes no difference, since under near-neutral pKas the carboxylic acid will spontaneously deprotonate, and the carboxylate form will be the most common. However, if the structures in Figure 2A were used for classical molecular simulation, that would be a big problem, since now that would be modeling the much rarer neutral form rather than the charged state. I am reasonably sure based on Figure 5 that the MD correctly modeled the deprotonated form with a carboxylate, but that is inconsistent with Figure 2A. Otherwise, the structure and simulation analysis falls into the mainstream of modern structural biology work.

Reviewer #1 (Public Review):

The authors set out to use structural biology (cryo-EM), surface plasmon resonance, and complement convertase assays to understand the mechanism(s) by which ISG65 dampens the cytoxicity/cellular clearance to/of trypanosmes opsonised with C3b by the innate immune system.

The cryo-EM structure adds significantly to the author's previous crystallographic data because the latter was limited to the C3d sub-domain of C3b. Further, the in vitro convertase assay adds an additional functional dimension to this study.

The authors have achieved their aims and the results support their conclusions.

The role of complement in immunity to T. brucei (or lack thereof) has been a significant question in molecular parasitology for over 30 years. The identification of ISG65 as the C3 receptor and now this study providing mechanistic insights represents a major advance in the field.

Reviewer #2 (Public Review):

This is an excellent paper that uses structural work to determine the precise role of one of the few invariant proteins on the surface of the African trypanosome. This protein, ISG65, was recently determined to be a complement receptor and specifically a receptor of C3, whose binding to ISG65 led to resistance to complement-mediated lysis. But the molecular mechanism that underlies resistance was unknown.

Here, through cryoEM studies, the authors reveal the interaction interface (two actually) between ISG65 and C3, and based on this, make inferences regarding downstream events in the complement cascade. Specifically, they suggest that ISG65 preferably binds the converted C3b (rather than the soluble C3). Moreover, while conversion to a C3bB complex is not blocked, the ability to bind complement receptors 1 and 3 is likely blocked.

Of course, all this is work on proteins in isolation and the remaining question is - can this in fact happen on the membrane? The VSG-coated membrane is supposed to be incredibly dense (packed at the limits of physical density) and so it is unclear whether the interactions that are implied by the structural work can actually happen on the membrane of a live trypanosome. This is not necessarily a ding but it should be addressed in the manuscript perhaps as a caveat.

Reviewer #3 (Public Review):

The authors investigate the mechanisms by which ISG65 and C3 recognize and interact with each other. The major strength is the identification of eco-site by determining the cryoEM structure of the complex, which suggests new intervention strategies. This is a solid body of work that has an important impact on parasitology, immunology, and structural biology.

Reviewer #1 (Public Review):

The apicoplast, a non-photosynthetic vestigial chloroplast, is a key metabolic organelle for the synthesis of certain lipids in apicomplexan parasites. Although it is clear metabolite exchange between the parasite cytosol and the apicoplast must occur, very few transporters associated with the apicoplast have been identified. The current study combines data from previous studies with new data from biotin proximity labeling to identify new apicoplast resident proteins including two putative monocarboxylate transporters termed MCT1 and MCT2. The authors conduct a thorough molecular phylogenetic analysis of the newly identified apicoplast proteins and they provide compelling evidence that MCT1 and MCT2 are necessary for normal growth and plaque formation in vitro along with maintenance of the apicoplast itself. They also provide indirect evidence for a possible need for these transporters in isoprenoid biosynthesis and fatty acid biosynthesis within the apicoplast. Finally, mouse infection experiments suggest that MCT1 and MCT2 are required for normal virulence, with MCT2 completely lacking at the administered dose. Overall, this study is generally of high quality, includes extensive quantitative data, and significantly advances the field by identifying several novel apicoplast proteins together with establishing a critical role for two putative transporters in the parasite. The study, however, could be further strengthened by addressing the following aspects:

Main comments<br /> 1. The conclusion that condition depletion of AMT1 and/or AMT2 affects apicoplast synthesis of IPP is only supported by indirect measurements (effects on host GFP uptake or trafficking, possibly due to effects on IPP dependent proteins such as rabs, and mitochondrial membrane potential, possibly due to effects on IPP dependent ubiquinone). This conclusion would be more strongly supported by directly measuring levels of IPP. If there are technical limitations that prevent direct measurement of IPP then the author should note such limitations and acknowledge in the discussion that the conclusion is based on indirect evidence.

2. The conclusion that condition depletion of AMT1 and/or AMT2 affects apicoplast synthesis of fatty acids is also poorly supported by the data. The authors do not distinguish between the lower fatty acid levels being due to reduced synthesis of fatty acids, reduced salvage of host fatty acids, or both. Indeed, the authors provide evidence that parasite endocytosis of GFP is dependent on AMT1 and AMT2. Host GFP likely enters the parasite within a membrane bound vesicle derived from the PVM. The PVM is known to harbor host-derived lipids. Hence, it is possible that some of the decrease in fatty acid levels could be due to reduced lipid salvage from the host. Experiments should be conducted to measure the synthesis and salvage of fatty acids (e.g., by metabolic flux analysis), or the authors should acknowledge that both could be affected.

Reviewer #2 (Public Review):

In this study Hui Dong et al. identified and characterized two transporters of the monocarboxylate family, which they called Apcimplexan monocarboxylate 1 and 2 (AMC1/2) that the authors suggest are involved in the trafficking of metabolites in the non-photosynthetic plastid (apicoplast) of Toxoplasma gondii (the parasitic agent of human toxoplasmosis) to maintain parasite survival. To do so they first identified novel apicoplast transporters by conducting proximity-dependent protein labeling (TurboID), using the sole known apicoplast transporter (TgAPT) as a bait. They chose two out of the three MFS transporters identified by their screen based and protein sequence similarity and confirmed apicoplast localisation. They generated inducible knock down parasite strains for both AMC1 and AMC2, and confirmed that both transporters are essential for parasite intracellular survival, replication, and for the proper activity of key apicoplast pathways requiring pyruvate as carbon sources (FASII and MEP/DOXP). Then they show that deletion of each protein induces a loss of the apicoplast, more marked for AMC2 and affects its morphology both at its four surrounding membranes level and accumulation of material in the apicoplast stroma. This study is very timely, as the apicoplast holds several important metabolic functions (FASII, IPP, LPA, Heme, Fe-S clusters...), which have been revealed and studied in depth but no further respective transporter have been identified thus far. hence, new studies that could reveal how the apicoplast can acquire and deliver all the key metabolites it deals with, will have strong impact for the parasitology community as well as for the plastid evolution communities. The current study is well initiated with appropriate approaches to identify two new putatively important apicoplast transporters, and showing how essential those are for parasite intracellular development and survival. However, in its current state, this is all the study provides at this point (i.e. essential apicoplast transporters disrupting apicoplast integrity, and indirectly its major functions, FASII and IPP, as any essential apicoplast protein disruption does). The study fails to deliver further message or function regarding AMC1 and 2, and thus validate their study. Currently, the manuscript just describes how AMC1/2 deletion impacts parasite survival without answering the key question about them: what do they transport? The authors yet have to perform key experiments that would reveal their metabolic function. I would thus recommend the authors work further and determine the function of AMC1 and 2.

Reviewer #2 (Public Review):

In this work, the authors investigate the role of CRB3 in the formation of the primary cilium both in a mouse model and in human cells. They confirm in a conditional knock-out (KO) mouse model that Crb3 is necessary for the formation of the primary cilium in mammary and renal epithelial tissues and the new-born mice exhibit classical traits of ciliopathies. In the mouse mammary gland, the absence of Crb3 induces hyperplasia and tumorigenesis and in the human mammary tumor cells MCF10A the knock-down (KD) of CBR3 impairs ciliogenesis and the formation of a lumen in 3D-cultures with less apoptosis and spindle orientation defects during cell division.

To determine the subcellular localization of CRB3 the authors have expressed exogenously a GFP-CRB3 in MCF10A and found that this tagged protein localizes in cell-cell junctions and around pericentrin, a centrosome marker while endogenous CRB3 localizes at the basal body. To dissect the molecular role of CRB3 the authors have performed proteomic analyses after a pull-down assay with the exogenous tagged-CRB3 and found that CRB3 interacts with Rab11 and is present in the endosomal recycling pathway. CRB3 KD also decreases the interactions between components of the gamma-TuRC. In addition, the authors showed that CRB3 interacts with a tagged-Rab11 by its extracellular domain and that CRB3 promotes the interaction between Rab11 and CEP290 while CRB3 KD decreased the co-localization of GCP6 with Rab11 and gamma-Tub.

Finally, the authors showed that CRB3 depletion cannot activate the Hh pathway as opposed to the Wnt pathway.

Reviewer #1 (Public Review):

In this study the authors first perform global knockout of the gene coding for the polarity protein Crumbs 3 (CRB3) in the mouse and show that this leads to perinatal lethality and anopthalmia. Next, they create a conditional knockout mouse specifically lacking CRB3 in mammary gland epithelial cells and show that this leads to ductal epithelial hyperplasia, impaired branching morphogenesis and tumorigenesis. To study the mechanism by which CRB3 affects mammary epithelial development and morphogenesis the authors turn to MCF10A cells and find that CRB3 shRNA-mediated knockdown in these cells impairs their ability to form properly polarized acini in 3D cultures. Furthermore, they find that MCF10A cells lacking CRB3 display reduced primary ciliation frequency compared to control cells, which is in agreement with previous studies implicating CRB3 in primary cilia biogenesis. Using a combination of biochemical, molecular- and imaging approaches the authors then provide some evidence indicating that CRB3 promotes ciliogenesis by mediating Rab11-dependent recruitment of gamma-tubulin ring complex (gamma-TuRC) component GCP6 to the centrosome/ciliary base, and they also show that CRB3 itself is localized to the base of primary cilia. Finally, to assess the functional consequences of CRB3 loss on ciliary signaling function, the authors analyze the effect of CRB3 loss on Hedgehog and Wnt signaling using cell-based assays or a mouse model.

Overall, the described findings are interesting and in agreement with previous studies showing an involvement of CRB3 in epithelial cell biology, tumorigenesis and ciliogenesis. The results showing a role for CRB3 in mammary epithelial development and morphogenesis in vivo seem convincing. Although the authors provide evidence that CRB3 promotes ciliogenesis via (indirect) physical association with Rab11 and gamma-TuRC, the precise mechanism by which CRB3 promotes ciliogenesis remains to be clarified. Specific comments are as follows:

1) For all cell-based assays using shRNA to knock down CRB3, it would be desirable to perform rescue experiments to ensure that the observed phenotype of CRB3 depleted cells is specific and not due to off-target effects of the shRNA.<br /> 2) Figure 3G: it is very difficult to see that the red stained structures are primary cilia.<br /> 3) Figure 5A: it is unfortunate the authors chose not to show the original dataset (Excel file) used for generating this figure; this makes it difficult to interpret the data. It is general policy of the journal to make source data accessible to the scientific community.<br /> 4) The authors have a tendency to overinterpret their data, and not all claims put forth by the authors are fully supported by the data provided.

Reviewer #1 (Public Review):

Here, Ensinck et al. investigated the composition of the yeast mRNA m6A methyltransferase complex required for meiosis. This complex was known to contain three proteins, but is much more complex in mammals, insects and plants. Through IP-MS analysis they identified three more proteins Kar4, Ygl036w and Dyn2. Of these Kar4 and Ygl036w are homologous to Mettl14 and Virma, respectively, and, like the previously described factors are essential for m6A deposition, mating and binding of the reader Pho92 to mRNA during meiosis by evidence acquired with appropriate methodology. Dyn2 is a novel factor not described for any m6A complex and is not essential for m6A deposition, mating and binding of the reader Pho92 to mRNA during meiosis.

In addition, detailed analysis of the Slz1 revealed homology to the mammalian factor m6A complex member ZC3H13 to comprise a conserved complex of five proteins, Mettl3, Mettl14, Mum2/WTAP, Virma and Slz/ZC3H13. When co-expressed in insects cells, they co-purify stoichiometrically and presence of Mum2 as a dimer is also indicated as shown for WTAP.

Complementary to these data they show that stability of the individual complex members is affected in mutants supporting that they are stabilized through complex formation.

Furthermore, the authors then show that kar4 has additional roles in mating that is separable from its role through the m6A complex in meiosis.

The authors employ appropriate methodology throughout to address their aims and present convincing evidence for their claims. The evidence presented here reinforces that the m6A complex is evolutionary highly conserved which has broad scope for its functional analysis in humans and model organisms.

Reviewer #2 (Public Review):

N6-methyladenosine (m6A), the most abundant mRNA modification, is deposited by the m6A methyltransferase complexes (MTC). While MTC in mammals/flies/plants consists of at least six subunits, yeast MTC was known to contain only three proteins. Ensinck, Maman, et al. revisited this question using a proteomic approach and uncovered three new yeast MTC components, Kar4/Ygl036w/Dyn2. By applying sequence and structure comparisons, they identified Kar4, Ygl036w, Slz1 as homologs of the mammalian METTL14, VIRMA. ZC3H13, respectively. While these proteins are essential for m6A deposition, the dynein light chain protein, Dyn2, is not involved in mRNA methylation. Interestingly, while mammalian and fly MTCs are configured as MAC (METTL3 and METTL14) and MACOM (other subunits) complexes, yeast MTC subunits appear to have different configurations. Finally, Kar4 has a different role as transcription regulator in mating, which is not mediated by other MTC members. These data establish fundamental framework for the yeast MTC and also provide novel insights for those studying m6A deposition.

Reviewer #1 (Public Review):

This manuscript compiles the colonization of shrubs during the Late Pleistocene in Northern America and Europe by comparing plant sedimentary ancient DNA (sedaDNA) records from different published lake sediment cores and also adds two new datasets from Island. The major findings of this work aim to illuminate the colonization patterns of woody shrubs (Salicaceae and Betulaceae) in these sediment archives to understand this process in the past and evaluate its importance under future deglaciation and warming of the Arctic.

The strength of evidence is solid as methods (sedimentary DNA) and data analyses broadly support the claims because the authors use an established metabarcoding approach with PCR replicates (supporting the replicability of PCR and thereby proving the occurrence of Salicaeae and Betulaceae in the samples) and quantitative estimation of plant DNA with qPCR (which defines the number of cycles used for each PCR amplification to prevent overamplification). However, the extraction methods need more explanation and the bioinformatic pipeline is not well-known and needs also some further description in the main text (not only referring to other publications).

The authors compare their own data with previously published data to indicate the different timing of shrubification in the selected sites and show that Salicaceae occurs always like a pioneer shrub after deglaciation, followed by Betaluaceae with a various time lag. The successive colonization of Salicaceae followed by Betulaceae is explained by its differences in environmental tolerance, the time lag of colonization in the compared records is e.g. explained by varying distance to source areas.

However, there are some weaknesses in the strength of evidence because full sedaDNA plant DNA assessment, quality of the sedaDNA data (relative abundance and richness of sedaDNA plant composition) and results from Blank controls (for sedaDNA) are not fully provided. I think it is important to show how the plant metabarcoding in general worked out, because it is known that e.g. poor richness can be indicative of less preserved DNA and a full plant assessment (shown in the supplement) would be more comprehensive and would likely attract a larger readership.

Further, it would allow us to see the relative abundance in changes of plants and would make it easier to understand if the families Salicaeae and Betulaceae are a major component of the community signal. Further, the possibility to reach higher taxonomic resolution with sedaDNA compared to pollen or to facilitate a continuous record (which is different from macrofossils) is not discussed in the manuscript but should be added. Also, the taxonomic resolution within these families in the discussed datasets would be of interest, also on the sequence type level if tax. assignments are similar.

Another important aspect is how the abundance/occurrence of Salicaceae is discussed. Many studies on sedaDNA confirm an overrepresentation of this family due to better preservation in the sediment, far-distance transport along rivers, or preferences of primers during amplification etc. As this family is the major objective of this study, such discussion should be added to the manuscript and data should be presented accordingly.

I also miss more clarity about how the authors defined the source areas (refugia) of the shrubs. If these source areas are described in other literature I suggest to show them in a map or so. Further, it should be also discussed and explained more in detail which specific environmental preferences these families have, this is too short in the introduction and too unspecific. Also, it would be beneficial to show relative abundances rather than just highlighted areas in the Figures and it would allow us to see if Salicaeae will be replaced by Betulaceae after colonizing or if both families persist together, which might be important to understand future development of shrubs in these areas.

The author started a discussion about shrubification in the future, but a more defined evaluation and discussion of how to use such paleo datasets to predict future shrubification and its consequences for the Arctic would give more significance to the work.

Reviewer #2 (Public Review):

Harding et al have analysed 75 sedaDNA samples from Store Vidarvatn in Iceland. They have also revised the age-depth model of earlier pollen, macrofossil, and sedaDNA studies from Torfdalsvatn (Iceland), and they review sedaDNA studies for first detection of Betulaceae and Salicaceae in Iceland and surrounding areas. Their Store Vidarvatn data are potentially very interesting, with 53 taxa detected in 73 of the samples, but only results on two taxa are presented. Their revised age-depth model cast new light on earlier studies from Torfdalsvatn, which allows a more precise comparison to the other studies. The main result from both sedaDNA and the review is that Salicaceae arrives before Betulaceae in Iceland and the surrounding area. This is a well-known fact from pollen, macrofossil, and sedaDNA studies (Fredskild 1991 Nordic J Bot, Birks & Birks QSR 2014, Alsos et al. 2009, 2016, 2022) and as expected as the northernmost Salix reach the Polar Desert zone (zone A, 1-3{degree sign}C July temperature) whereas the northernmost Betula rarely goes beyond the Southern Tundra (zone D, 8-9{degree sign}C July temperature, Walker et al. 2005 J. Veg. Sci., Elven et al. 2011 http://panarcticflora.org/ ).

My major concern is their conclusion that lag in shrubification may be expected based on the observations that there is a time gap between deglaciation and the arrival of Salicaceae and between the arrival of Salicaceae and Betulaceae. A "lag" in biological terms is defined as the time from when a site becomes environmentally suitable for a species until the species establish at the site (Alexander et al. 2018 Glob. Change Biol.). The climate requirement for Salicaceae highly depends on species. In the three northernmost zones (A-C), it appears as a dwarf shrub, and it only appears as a shrub in the Southern Tundra (D) and Shrub Tundra (E) zone, and further south it is commonly trees. Thus, Salicaceae cannot be used to distinguish between the shrub tundra and more northern other zones, and therefore cannot be used as an indicator for arctic shrubification. Betulaceae, on the other hand, rarely reach zone C, and are common in zone D and further south. Thus, if we assume that the first Betulaceae to arrive in Iceland is Betula nana, this is a good indicator of the expansion of shrub tundra. Thus, if they could estimate when the climate became suitable for B. nana, they would have a good indicator of colonisation lags, which can provide some valuable information about time lags in shrub expansion (especially to islands). They could use either independent proxy or information from the other species recorded in sedaDNA to reconstruct minimum July temperature (see e.g. Parducci et al. 2012a+b Science, Alsos et al. 2020 QSR).

The study gives a nice summary of current knowledge and the new sedaDNA data generated are valuable for anyone interested in the post-glacial colonisation of Iceland. Unfortunately, neither raw nor final data are given. Providing the raw data would allow re-analysing with a more extensive reference library, and providing final data used in their publication will for sure interest many botanists and palaeoecologist, especially as 73 samples provide high time resolution compared to most other sedaDNA studies.

Reviewer #1 (Public Review):

The current study tests the hypothesis that inhibition of ryanodine receptor 2 (RyR2) in failing arrhythmogenic hearts reduces sarcoplasmic Ca leak, ventricular arrhythmias and improves contractile function. A guinea pig model of nonischemic heart failure (HF) was used and randomized to receive dantrolene (DS) or placebo in early or chronic HF. The authors show that DS treatment prevented ventricular arrhythmias and sudden cardiac death by decreasing dispersion of repolarization. The authors conclude that inhibition of RyR2 hyperactivity with DS mitigates the vicious cycle of sarcoplasmic Ca leak-induced increases in diastolic Ca and reactive oxygen species-mediated RyR2 oxidation. Moreover, the consequent increase in sarcoplasmic Ca2+ load improves contractile function.

In general, the study is well designed and the findings are likely to be of interest to the field. The characterization of the phenotypes is comprehensive, however, the study appears relatively weak in terms of the proposed mechanisms. Only in vivo functional analyses were presented with no in vitro analyses. The rationale for only using the male animals remains unclear. Data presented in Supplemental Figure 1 lacks the HF with DS group. As presented, the manuscript appears relatively descriptive in nature.

Reviewer #2 (Public Review):

Joshi et al. investigated the use of dantrolene, an RyR stabilizing drug, in improving contractile function and slowing pathological progression of pressure-overload heart failure. In a guinea pig model, they found that dantrolene treatment reduced cytosolic Ca2+ levels, improved contractility, reduced the incidence of arrhythmias, reduced fibrosis, and slowed the progression of heart failure. Importantly, delaying treatment until 3 weeks after aortic banding (when heart failure was already established) also resulted in improvements in function and decreased arrhythmogenesis. While some of the mechanistic details remain to be worked out, the data suggest that improving intracellular Ca2+ handling can break the vicious cycle of sympathetic activation, ROS production, and further deterioration of cardiac function.

The functional ECG and echo data are convincing, and very clearly demonstrate the positive effects of dantrolene in heart failure. This is important because dantrolene is already FDA-approved to treat malignant hyperthermia and muscle spasms, so repurposing this drug as a heart failure therapeutic might have a straightforward path to clinical implementation. This also highlights the non-specific nature of dantrolene to interact with RyR1, and therefore, potential side effects. However, this does not detract from the main proof-of-concept demonstrated here.

The guinea pig model employed here is also a strength, as the guinea pig has intracellular Ca2+ handling and ionic currents that are much more similar to human (vs. a murine model, for example).

One weakness is the exclusion of female animals from the study. The authors report more heterogeneity in the progression of HF in the female guinea pig model, however it will be very important to determine effects of dantrolene in the female heart, as there are considerable known sex differences in intracellular Ca2+ handling and contractility. Therefore, it is possible that dantrolene could have sex-dependent effects.

The title and parts of the discussion of the manuscript focus on 'repolarization reserve'. This term is often used in the realm of safety pharmacology, and 'reserve' refers to the fact that blocking a single K+ channel (for example) may not impact action potential duration because there may be enough other K+ currents to ensure proper repolarization. The repolarization reserve refers to this overall balance of depolarizing and repolarizing currents and potential redundancies to ensure proper repolarization. Although the present study clearly demonstrates QT shortening with dantrolene (thus, there must be a change in the balance of depolarizing and repolarizing currents), the study does not definitively demonstrate changes in any membrane currents. While this may seem like a minor point of terminology, it may mislead readers as to the main focus of the study, which is not at all on ionic currents, but on functional outcomes.

Reviewer #1 (Public Review):

This study investigates the structuring of long calls in orangutans. The authors demonstrate long calls are structured around full pulses, repeated following a regular tempo (isochronic rhythm). These full pulses are themselves structured around different sub-pulses, themselves repeated following an isochronic rhythm. The authors argue this patterning is evidence for self-embedded, recursive structuring in orangutang long calls.

The analyses conducted are robust and compelling and they support the rhythmicity the authors argue is present in the long calls. Furthermore, the authors went above and beyond and confirmed acoustically the sub-categories identified were accurate.

However, I believe the manuscript would benefit from a formal analysis of the specific recursive patterning occurring in the long call. Indeed, as of now, it is difficult for the reader to identify what the authors argue to be recursion and distinguish it from simple repetitions of motifs, which is essential. Although the authors already discuss briefly why linear patterning is unlikely, the reader would benefit from expanding on this discussion section and clarifying the argument here (a lay terminology might help). I believe an illustration here might help.<br /> In the same logic, I believe a tree similar to the trees used in linguistics to illustrate hierarchical structuring would help the reader understand the recursive patterning in place here. This would also help get the "big picture", as Fig 1A is depicting a frustratingly small portion of the long call.

Notwithstanding these comments, this paper would provide crucial evidence for recursion in the vocal *production* of a non-human ape species. The implication it would have would represent a key shift in the field of language evolution. The study is very elegant and well-constructed. The paper is extremely well written, and the point of view adopted is original, well-argued and compelling.

Reviewer #2 (Public Review):

I am not qualified to judge the narrow claim that certain units of the long calls are isochronous at various levels of the pulse hierarchy. I will assume that the modelling was done properly. I can however say that the broad claims that (i) this constitutes evidence for recursion in non-human primates, (ii) this sheds light on the evolution of recursion and/or language in humans are, when not made trivially true by a semantic shift, unsupported by the narrow claims. In addition, this paper contains errors in the interpretation of previous literature.

The main difficulty when making claims about recursion is to understand precisely what is meant by "recursion" (arguably a broader problem with the literature that the authors engage with). The authors offer some characterization of the concept which is vague enough that it can include anything from "celestial and planetary movement to the splitting of tree branches and river deltas, and the morphology of bacteria colonies". With this appropriately broad understanding, the authors are able to show "recursion" in orangutans' long calls. But they are, in fact, able to find it everywhere. The sound of a plucked guitar string, which is a sum of self-similar periodic patterns, count as recursive under their definition as well.

One can only pick one's definition of recursion, within the context of the question of interest: evolution of language in humans. One must try to name a property which is somewhat specific to human language, and not a ubiquitous feature of the universe we live in, like self-similarity. Only after having carved out a sufficiently distinctive feature of human language, can we start the work of trying to find it in a related species and tracing its evolutionary history. When linguists speak of recursion, they speak of in principle unbounded nested structure (as in e.g. "the doctor's mother's mother's mother's mother ..."). The author seems to acknowledge this in the first line of the introduction: "the capacity to *iterate* a signal within a self-similar signal" (emphasis added). In formal language theory, which provides a formal and precise definition of one notion of recursivity appropriate for human language, unbounded iteration makes a critical difference: bounded "nested structures" are regular (can be parsed and generated using finite-state machines), unbounded ones are (often) context-free (require more sophisticated automaton). The hierarchy of pulses and sub-pulses only has a fixed amount of layers, moreover the same in all productions; it does not "iterate".

Another point is that the authors don't show that the constraints that govern the shape of orangutans long calls are due to cognitive processes. Any oscillating system will, by definition, exhibit isochrony. For instance, human trills produce isochronouns or near isochronous pulses. No cognitive process is needed to explain this; this is merely the physics of the articulators. Do we know that the rhythm of the pulses and sub-pulses in orangutans is dictated by cognition as opposed to the physics of the articulators?

Even granting the authors' unjustified conclusion that wild orangutans have "recursive" structures and that these are the result of cognition, the conclusions drawn by the authors are too often fantastic leaps of induction. Here is a cherry-picked list of some of the far-fetched conclusions:

- "our findings indicate that ancient vocal patterns organized across nested structural strata were likely present in ancestral hominids". Does finding "vocal patterns organized across nested structural strata" in wild orangutans suggest that the same were present in ancestral hominids?<br /> - "given that isochrony universally governs music and that recursion is a feature of music, findings (sic.) suggest a possible evolutionary link between great ape loud calls and vocal music". Isochrony is also a feature of the noise produced by cicadas. Does this suggest an evolutionary link between vocal music and the noise of cicadas?

Finally, some passages also reveal quite glaring misunderstandings of the cited literature. For instance:

- "Therefore, the search for recursion can be made in the absence of meaning-base operations, such as Merge, and more generally, semantics and syntax". It is precisely Chomsky's (disputable) opinion that the main operation that govern syntax, Merge, has nothing to do with semantics. The latter is dealt within a putative conceptual-intentional performance system (in Chomsky's terminology), which is governed by different operations.<br /> - "Namely, experimental stimuli have consisted of artificial recursive signal sequences organized along a single temporal scale (though not structurally linear), similarly with how Merge and syntax operate". The minimalist view advocated by Chomsky assumes that mapping a hierarchichal structure to a linear order (a process called linearizarion) is part of the articulatory-perceptual system. This system is likewise not governed by Merge and is not part of "syntax" as conceived by the Chomskyan minimalists.

Reviewer #1 (Public Review):

This work introduces a new method of imaging the reaction forces generated by small crawling organisms and applies this method to understanding locomotion of Drosophila larva, an important model organism. The force and displacement data generated by this method are a qualitative improvement on what was previously available for studying the larva, improving simultaneously the spatial, temporal, and force resolution, in many cases by an order of magnitude. The resulting images and movies are quite impressive.

As it shows the novel application of recent technological innovations, the work would benefit from more detail in the explanation of the new technologies, of the rationales underlying the choice of technology and certain idiosyncratic experimental details, and of the limitations of the various techniques. In the methods, the authors need to be sure to provide sufficient detail that the work can be understood and replicated. The description of the results and the theory of motion developed here focus only on forces generated when the larva pushes against the substrate and ignores the equally strong adhesive forces pulling the larva onto the substrate.

The substrate applies upward, downward, and horizontal forces on the larva, but only upward and downward forces are measured, and only upward forces are considered in the discussions of "Ground Reactive Forces." An apparent weakness of the WARP technique for the study of locomotion is that it only measures forces perpendicular to the substrate surface ("vertical forces" in Meek et al.), while locomotion requires the generation of forces parallel to the substrate ("horizontal forces"). It should be clarified that only vertical forces are studied and that no direct information is provided about the forces that actually move the larva forward (or about the forces which impede this motion and are also generated by the substrate). Along with this clarification, it would be helpful to include a discussion of other techniques, especially micropillar arrays and traction force microscopy, that directly measure horizontal forces and of why these techniques are inappropriate for the motions studied here.

The larvae studied are about 1 mm long and 0.1 mm in cross-section. Their volumes are therefore on order 0.01 microliter, their masses about 0.01 mg, and their weights in the range of 0.1 micronewton. This contrasts with the force reported for a single protpodium of 1 - 7 micronewtons. This is not to say that the force measurements are incorrect. Larvae crawl easily on an inverted surface, showing gravitational forces are smaller than other forces binding the larva to the substrate. The forces measured in this work are also of the same magnitude as the horizontal forces reported by Khare et al. (ref 32) using micropillar arrays.

I suspect that the forces adhering the larva to the substrate are due to the surface tension of a water layer. This would be consistent with the ring of upward stress around the perimeter of the larva visible in S4D, E and in video SV3. The authors remark that upward deflection of the substrate may be due to the Poisson's ratio of the elastomer, but the calibration figure S5 shows that these upward deflections and forces are much smaller than the applied downward force. In any case, there must be a downward force on the larva to balance the measured upward forces and this force must be due to interaction with the substrate. It should be verified that the sum of downward minus upward forces on the gel equals the larva's weight (given the weight is neglible compared to the forces involved, this implies that the upward and downward forces should sum to 0)

Much of the discussion and the model imply that the sites where the larva exerts downward force on the gel are the sites where horizontal propulsion is generated. This assumption should be justified. Can the authors rule out that the larva 'pulls' itself forward using surface tension instead of 'pushing' itself forward using protopodia?

More detail should be provided about the methods, their limitations, and the rationale behind certain experimental choices.

Three techniques are introduced here to study how a crawling larva interacts with the substrate: standard brightfield microscopy of a larva crawling in an agarose capillary, ERISM imaging of an immobilized larva, and WARP imaging of a crawling larva. The authors should make clear why each technique was chosen for a particular study - e.g. could the measurements using brightfield microscopy also be accomplished using WARP? They should also clarify how these techniques relate to and possibly improve on existing techniques for measuring forces organisms exert on a substrate, particularly micropillar arrays and Traction Force Microscopy.

As written, "(ERISM) (19) and a variant, Wavelength Alternating Resonance Pressure microscopy (WARP) (20) enable optical mapping of GRFs in the nanonewton range with micrometre and millisecond precision..." (lines 53-55) may generate confusion. ERISM as described in this work has a much lower temporal resolution (requires the animal to be still for 5 seconds - lines 474-5); In this work, WARP does not appear to have nanonewton precision (judging by noise on calibration figures) and it is not clear that it has millisecond precision (the camera used and its frame rate should be specified in the methods).

It would be helpful to have a discussion of the limits of the techniques presented and tradeoffs that might be involved in overcoming them. For instance, what is the field of view of the WARP microscope, and could it be increased by choosing a lower power objective? What would be required to allow WARP microscopy to measure horizontal forces? Can a crawling larva be imaged over many strides by recentering it in the field of view, or are there only particular regions of the elastomer where a measurement may be made?

Reviewer #2 (Public Review):

With a much higher spatiotemporal resolution of ground dynamics than any previous study, the authors uncover new "rules" of locomotory motor sequences during peristalsis and turning behaviors. These new motor sequences will interest the broad neuroscience community that is interested in the mechanisms of locomotion in this highly tractable model. The authors uncover new and intricate patterns of denticle movements and planting that seem to solve the problem of net motion under conditions of force-balance. Simply put, the denticulated "feet" or tail of the Drosophila larva are able to form transient and dynamic anchors that allow other movements to occur.

The biology and dynamics are well-described. The physics is elementary and becomes distracting when occasionally overblown. For example, one doesn't need to invoke Newton's third law, per se, to understand why anchors are needed so that peristalsis can generate forward displacements. This is intuitively obvious. Another distracting allusion to "physics" is correlating deformation areas with displaced volume, finding that "volume is a consequence of mass in a 2nd order polynomial relationship". I have no idea what this "physics" means or what relevance this relationship has to the biology of locomotion.

The ERISM and WARP methods are state-of-the-art, but aside from generally estimating force magnitudes, the detailed force maps are not used. The most important new information is the highly accurate and detailed maps of displacement itself, not their estimates of applied force using finite element calculations. In fact, comparing displacements to stress maps, they are pretty similar (e.g., Fig 4), suggesting that all experiments are performed in a largely linear regime. It should also be noted that the stress maps are assumed to be normal stresses (perpendicular to the plane), not the horizontal stresses that are the ones that actually balance forces in the plane of animal locomotion.

But none of this matters. The real achievements are the new locomotory dynamics uncovered with these amazing displacement measurements. I'm only asking the authors to be precise and down-to-earth about the nature of their measurements.

It would be good to highlight the strength of the paper -- the discovery of new locomotion dynamics with high-resolution microscopy -- by describing it in simple qualitative language. One key discovery is the broad but shallow anchoring of the posterior body when the anterior body undertakes a "head sweep". Another discovery is the tripod indentation at the tail at the beginning of peristalsis cycles.

As far as I know, these anchoring behaviors are new. It is intuitively obvious that anchoring has to occur, but this paper describes the detailed dynamics of anchoring for the first time. Anchoring behavior now has to be included in the motor sequence for Drosophila larva locomotion in any comprehensive biomechanical or neural model.

Reviewer #1 (Public Review):

This study reports a long-term, multisite study of tropical herbivory on Piper plants. The results are clear that lack of water leads to lower plant survival and altered herbivory. The results varied substantially among sites. The caveats are that ecosystem processes beyond water availability are not investigated although they are brought into play in the title and in the paper, that herbivory beyond leaf damage was not reported (there might be none, the reader needs to be shown the evidence for this), that herbivore diversity is defined by leaf damage (authors need to give evidence that this is a valid inference), that the plots were isolated from herbivores beyond their borders, that the effects of extreme climate events were isolated to Peru, that intraspecific variation in the host plants needs to be explained and interpreted in more detail, the results as reported are extremely complicated, the discussion is overly long and diffuse.

Reviewer #2 (Public Review):

This is an important and large experimental study examining the effects of plant species richness, plant genotypic richness, and soil water availability on herbivory patterns on Piper species in tropical forests.

A major strength is the size of the study and the fact that it tackled so many potentially important factors simultaneously. The authors examined both interspecific plant diversity and intraspecific plant diversity. They crossed that with a water availability treatment. And they repeated the experiment across five geographically separated sites.

The authors find that both water availability and plant diversity, intraspecific and interspecific, influence herbivore diversity and herbivory, but that the effects differ in important ways across sites. I found the study to be solid and the results to be very convincing. The results will help the field grapple with the importance of environmental change and biodiversity loss and how they structure communities and alter species interactions.

Reviewer #1 (Public Review):

In principle a very interesting story, in which the authors attempt to shed light on an intriguing and poorly understood phenomenon; the link between damage repair and cell cycle re-entry once a cell has suffered from DNA damage. The issue is highly relevant to our understanding of how genome stability is maintained or compromised when our genome is damaged. The authors present the intriguing conclusion that this is based on a timer, implying that the outcome of a damaging insult is somewhat of a lottery; if a cell can fix the damage within the allocated time provided by the "timer" it will maintain stability, if not then stability is compromised. If this conclusion can be supported by solid data, the paper would make a very important contribution to the field.

However, the story in its present form suffers from a number of major gaps that will need to be addressed before we can conclude that MASTL is the "timer" that is proposed here. The primary concern being that altered MASTL regulation seems to be doing much more than simply acting as a timer in control of recovery after DNA damage. There is data presented to suggest that MASTL directly controls checkpoint activation, which is very different from acting as a timer. The authors conclude on page 8 "E6AP promoted DNA damage checkpoint signaling by counteracting MASTL", but in the abstract the conclusion is "E6AP depletion promoted cell cycle recovery from the DNA damage checkpoint, in a MASTL-dependent manner". These 2 conclusions are definitely not in alignment. Do E6AP/MASTL control checkpoint signaling or do they control recovery, which is it?

Also, there is data presented that suggest that MASTL does more than just controlling mitotic entry after DNA damage, while the conclusions of the paper are entirely based on the assumption that MASTL merely acts as a driver of mitotic entry, with E6AP in control of its levels. This issue will need to be resolved.

and finally, the authors have shown some very compelling data on the phosphorylation of E6AP by ATM/ATR, and its role in the DNA damage response. But the time resolution of these effects in relation to arrest and recovery have not been addressed.

Revised manuscript:<br /> I think the authors did a good job in revising the paper, and provide compelling support for a timer function in the checkpoint. I do think they still have missed one important point how MASTL could act as a timer to control recovery. The data clearly show that MASTL somehow controls ATM/ATR activity, whilst their final model (fig.9) places MASTL upstream of CDK activity, without mentioning its feedback on ATM/ATR. I think there are 2 possible explanations for the timer function of MASTL they have discovered here, both may be relevant. The first is enhanced CDK activation by direct control of CDK phosphorylation through MASTL/B55/PP2A. The second is through MASTL-mediated shut-down of ATM/ATR activation (mechanism to be determined) which is also reported here. Their final model and discussion do not display sufficient appreciation for this latter option, and I would argue that the HU-recovery experiment shown in Fig.5B is actually in strong support of the second explanation, rather than the first.

Reviewer #2 (Public Review):

This manuscript describes a role for the ATM-E6AP-MASTL pathway in DNA damage checkpoint recovery. However, the data in the first version of the manuscript strongly suggest that E6AP is involved in checkpoint activation, which raises doubts about the exact function of this pathway. Additional minor issues were raised regarding the quality of some of the data. Although some minor points were addressed in the revised manuscript, the major issue whether the E6AP-MASTL pathway mediates checkpoint activation or checkpoint recovery was not experimentally addressed. Instead, the authors state that "the expression level of MASTL is not upregulated during the activation stages of the DNA damage checkpoint". However, their data show otherwise: MASTL upregulation coinciding with RPA phosphorylation and p-ATM/ATR signal.

I am therefore not convinced the revised manuscript sufficiently addressed the comments to fully support the conclusions.

Reviewer #1 (Public Review):

Membrane receptor guanylyl cyclases are important for many physiological processes but their structures in full-length and their mechanism are poorly understood. Caveney et al. determined the cryo-EM structure of a highly engineered GC-C in a complex with endogenous HSP90 and CDC37. The structural work is solid and the structural information will be useful for the membrane receptor guanylyl cyclases field and the HSP90 field.

Reviewer #2 (Public Review):

Caveney et al have overexpressed an engineered construct of the human membrane receptor guanyl cyclase GC-C in hamster cells and co-purified it with the endogenous HSP90 and CDC37. They have then determined the structure of the resultant complex by single particle cryoEM reconstruction at sufficient resolution to dock existing structures of HSP90 and CDC37, plus an AlphaFold model of the pseudo-kinase domain of the guanylyl cyclase. The novelty of the work stems from the observation that the pseudo-kinase domain of GC-C associates with CDC37 and HSP90 similarly to how the bona fide protein kinases CDK4, CRAF and BRAF have been previously shown to interact.

Reviewer #3 (Public Review):

A detailed understanding of how membrane receptor guanylyl cyclases (mGC) are regulated has been hampered by the absence of structural information on the cytoplasmic regions of these signaling proteins. The study by Caveney et al. reports the 3.9Å cryo-EM structure of the human mGC cyclase, GC-C, bound to the Hsp90-Cdc37 chaperone complex. This structure represents a first view of the intracellular functional domains of any mGC and answers without doubt that Hsp90-Cdc37 recognizes mGCs via their pseudokinase (PK) domain. This is the primary breakthrough of this study. Additionally, the new structural data reveals that the manner in which Hsp90-Cdc37 recognizes the GC-C PK domain C-lobe is akin to how kinase domains of soluble kinases docks to the chaperone complex. This is the second major finding of this study, which provides a concrete framework to understand, more broadly, how Hsp90-Cdc37 recruits a large number of other diverse client proteins containing kinase or pseudokinase domains. Finally, the Hsp90-Cdc37-GC-C structure offer clues as to how GC-C may be regulated by phosphorylation and/or ubiquitinylation by serving as a platform for recruitment of PP5 and/or E3 ligases.

Reviewer #1 (Public Review):

The authors apply a new approach to monitor brain-wide changes in sensory-evoked hemodynamic activity after focal stroke in fully conscious rats. Using functional ultrasound (fUS), they report immediate and lasting (up to 5 days) depression of sensory-evoked responses in somatosensory thalamic and cortical regions.

Strengths: This a technically challenging and proof-of-concept study that employs new methods to study brain-wide changes in sensory-evoked neural activity, inferred from changes in cerebral blood flow. Despite the minor typos/grammatical errors and small sample size, the authors provide compelling images and rigorous analysis to support their conclusions. Overall, this was a very technically difficult study that was well executed. I believe that it will pave the way for more extensive studies using this methodological approach. Therefore I support this study and my recommendations to improve it are relatively minor in nature and should be simple for the authors to address.

Weaknesses: The primary weakness of this paper is the small sample sizes. Drawing conclusions based on the small sham control group (n=2) or 5-day stroke recovery group (n=2), is rather tenuous. One way to alleviate some uncertainty with regard to the conclusions would be to state in the discussion that the findings (ie. loss of thalamocortical function after stroke) are perfectly consistent with previous studies that examined thalamocortical function after stroke. The authors missed some of these supporting studies in their reference list (see PMID: 28643802, 1400649). A second issue that can easily be resolved is their analysis of the 69 brain regions. This seems like a very important part of the study and one of the primary advantages of employing efUS. As presented, I had difficulty seeing the data. I think it would be worthwhile to expand Fig 3 (especially 3C) into a full-page figure with an accompanying table in the Supplementary info section describing the % change in CBF for each brain region.

Other Recommendations for the authors:.<br /> - Since there is variability in spreading depolarizations, was there any trend in the relationship between # SD's and ischemic volume? I know there are few data points but a scatterplot might be of interest.<br /> - For statistical comparisons of 'response curves' in Fig 3 and 4, what exactly was the primary dependent measure: changes in peak amplitude (%) or area under the curve?<br /> - There are several typos and minor grammatical errors in the manuscript. Some editing is recommended.

Reviewer #2 (Public Review):

Brunner et al. present a new and promising application of functional ultrasound (fUS) imaging to follow the evolution of perfusion and haemodynamics upon thrombotic stroke in awake rats. The authors leveraged a chemically induced occlusion of the rat Medial Cerebral Artery (MCA) with ferric chloride in awake rats, while imaging with fUS cerebral perfusion with high spatio and temporal resolution (100µm x 110µm x 300µm x 0.8s). The authors also measured evoked haemodynamic response at different timepoints following whisker stimulation.

As the fUS setup of the authors is limited to 2D imaging, Brunner and colleagues focused on a single coronal slice where they identified the primary Somatosensory Barrel Field of the Cortex (S1BF), directly perfused by the MCA and relay nuclei of the Thalamus: the Posterior (Po) and the Ventroposterior Medial (VPM) nuclei of the Thalamus. All these regions are involved in the sensory processing of whisker stimulation. By investigating these regions the authors present the hyper-acute effect of the stroke with these main results:

- MCA occlusion results in a fast and important loss of perfusion in the ipsilesional cortex.<br /> - Thrombolysis is followed by Spreading Depolarisation measured in the Retrosplenial cortex.<br /> - Stroke-induced hypo-perfusion is associated with a significant drop in ipsilesional cortical response to whisker stimulation, and a milder one in ipsilesional subcortical relays.<br /> - Contralesional hemisphere is almost not affected by stroke with the exception of the cortex which presents a mildly reduced response to the stimulation.

In addition, the authors demonstrate that their protocol allows to follow up stroke evolution up to five days post-induction. They further show that fUS can estimate the size of the infarcted volume with brilliance mode (B-mode), confirming the presence of the identified lesional tissue with post-mortem cresyl violet staining.

Upon measuring functional response to whisker stimulation 5 days after stroke induction, the authors report that:<br /> - The ipsilesional cortex presents no response to the stimulation<br /> - The ipsilesional thalamic relays are less activated than hyper acutely<br /> - The contralesional cortex and subcortical regions are also less activated 5d after the stroke.

These observations mainly validate the new method as a way to chronically image the longitudinal sequelae of stroke in awake animals. However, the potentially more intriguing results the authors describe in terms of functional reorganization of functional activity following stroke appear to be preliminary, and underpowered ( N = 5 animals were imaged to describe hyper-acute session, and N = 2 in a five day follow-up). While highly preliminary, the research model proposed by the author (where the loss of the infarcted cortex induces reduces activity in connected regions, whether by cortico-thalamic or cortico-cortical loss of excitatory drive), is interesting. This hypothesis would require a greatly expanded, sufficiently powered study to be validated (or disproven).

Reviewer #3 (Public Review):

The authors set out to demonstrate the utility of functional ultrasound for evaluating changes in brain hemodynamics elicited acutely and subacutely by the middle cerebral artery occlusion model of ischemic stroke in awake rats.

Functional ultrasound affords a distinct set of tradeoffs relative to competing imaging modalities. Acclimatization of rats for awake imaging has proven difficult with most, and the high quality of presented data in awake rats is a major achievement. The major weakness of the approach is in its being restricted to single-slice acquisitions, which also complicates the registration of acquisition across multiple imaging sessions within the same animal. Establishing that awake imaging represents an advancement in relation to studies under anesthesia hinges upon the establishment of the level of stress experienced by the animals in the course of imaging, i.e., requires providing data on the assessment of stress over the course of these long imaging sessions. This is particularly significant given how significant a stressor physical restraint has been established to be in rodent models of stress. Furthermore, assessment of the robustness of these measurements is of particular significance for supporting the wide applicability of this approach to preclinical studies of brain injury: the individual animal data (effect sizes, activation areas, kinetics) should thus be displayed and the statistical analysis expanded. Both within-subject, within/across sessions, and across-subjects variability should be evaluated. Thoughtful comments on the relationship between power doppler signal and cerebral blood volume are important to include and facilitate comparisons to studies recording other blood volume-weighted signals. Finally, the contextualization of the observations with respect to other studies examining acute and subacute changes in brain hemodynamics post focal ischemic stroke in rats is needed. It is also quite helpful, for establishing the robustness of the approach, when the statistical parametric maps are shown in full (i.e. unmasked).

Reviewer #1 (Public Review):

Many labs worldwide now use the blind source deconvolution technique to identify the firing patterns of multiple motor units simultaneously in human subjects. This technique has had a truly transformative effect on our understanding of the structure of motor output in both normal subjects and, increasingly, in persons with neurological disorders. The key advance presented here is that the software provides real-time identification of these firing patterns.

The main strengths are the clarity of the presentation and the great potential that real-time decoding will provide. Figures are especially effective and statistical analyses are excellent.

The main limitation of the work is that only male subjects were included in the validation of the software. The reason given - that yield of number of motor units identified is generally larger in males than females - is reasonable in the sense that this is the first systematic test of this real-time approach. At a minimum, however, the authors should clearly commit to future work with female subjects and emphasize the importance of considering sex differences.

A second weakness is that the Introduction does a poor job of establishing the potential importance of the real-time approach.

Reviewer #2 (Public Review):

Rossato et al present I-spin live, a software package to perform real-time blind-source separation-based sorting of motor unit activity. The core contribution of this manuscript is the development and validation of a software package to perform motor unit sorting, apply the resulting motor unit filters in real-time during muscle contractions, and provide real-time visual feedback of the motor unit activity.

I have a few concerns with the work as presented:

- I found it challenging to specifically understand the technical contributions of this manuscript. The authors do not appear to be claiming anything novel algorithmically (with respect to spike sorting) or methodologically (with respect to manual editing of spikes before the use of the algorithms in real-time). My takeaway is that the key contributions are C1) development of an open-source implementation of the Negro algorithm, C2) validating it for real-time application (evaluating its sorting efficacy, and closed-loop performance, etc), and developing a software package to run in closed-loop with visual feedback. I will comment on each of these items separately below. It would be great if the authors could more explicitly lay out the key contributions of this manuscript in the text.

- Related to the above, much of the validation of the algorithms in this manuscript has a "trust me" feel - the authors note that the Negro et al. algorithm has already been validated, so very few details or presentations of primary data showing the algorithm's performance are shown. Similarly, the efficacy of the decomposition approach is evaluated using manual editing of the sorting output as a reference, which is a subjective process, and users would greatly benefit from explicit guidance. There are very few details of manual editing shown in this manuscript (I believe the authors reference the Hug et al. 2021 paper for these details), and little discussion of the core challenges and variability of that process, even though it seems to be a critical step in the proposed workflow. So this is very hard to evaluate and would be challenging for readers to replicate.

- I found the User Guide in the Github package to be easy to follow. Importantly, it seems heavily tied to the specific hardware (Quattrocento). I understand it may be difficult to make the full software package work with different hardware, but it seems important to at least make an offline analysis of recorded data possible for this package to be useful more broadly.

- While this may be a powerful platform, it is also very possible that without more details and careful guidance for users on potential pitfalls, many non-experts in sorting could use this as a platform for somewhat sloppy science.

- The authors mention that data is included with the Github software package. I could not find any included data, or instructions on how to run the software offline on example data.

- Given the centrality of the real-time visual feedback to their system, the authors should show some examples of the actual display etc. so readers can understand what the system in action actually looks like (I believe there is no presentation of the actual system in the manuscript, just in the User Guide). Similarly, it would be helpful to have a schematic figure outlining the full workflow that a user goes through when using this system.

- The authors note all data was collected with male subjects because more motor units can be decomposed from male subjects relative to females. But what is the long-term outlook for the field if studies avoid female subjects because their motor units may be harder to decompose? This should at least be discussed - it is an important challenge for the field to solve, and it is unacceptable if new methods just avoid this problem and are only tested on male subjects.

Specific comments on the core contributions of this paper:

C1. Development of an open-source implementation of the Negro algorithm<br /> This seems an important contribution and useful for the community. There are very few figures showing any primary data, the efficacy of sorting, raw traces showing the waveforms that are identified, cluster shapes, etc. I realize the high-level algorithm has been outlined elsewhere, but the implementation in this package, and its efficacy, is a core component of the system and the claims being made in this paper. Much more presentation of data is needed to evaluate this.

Similarly, more information on the offline manual editing process (e.g. showing before/after examples with primary data) would be important to gain confidence in the method. The current paper shows application to both surface EMG and intramuscular EMG, but I could not find IM EMG examples in the Hug paper (apologies if I missed them). Surface and IM data are very, very different, so one would imagine the considerations when working with them should also be different.

All descriptions of math/algorithms are presented in text, without any actual math, variable definitions, etc. This presentation makes it difficult to understand what is done. I would strongly recommend writing out equations and defining variables where possible.

More details on how the level of sparseness is controlled during optimization would be helpful. And how this sparseness penalty is weighed against other optimization costs.

Overall the paper is not very rigorous about the accuracy of motor unit identification. For example, the authors note that SIL of 0.9 is generally used for offline evaluation (why is this acceptable?), but it was lowered to 0.8 for particular muscles in this study. But overall, it is unclear how sorting accuracy/inaccuracy affects performance in the target applications of this work.

C2. For real-time experiments, variability/jitter is important to characterize. Fig. 4 seems to be presenting mean computational times, etc, but no presentation of variability is shown. It would be helpful to depict data distributions somehow, rather than just mean values.

There is some description about the difference between units identified during baseline contractions, and how they might be misidentified during online contractions ("Accuracy of the real-time identification..."). This should be described in more detail.

Fig. 6: Given that a key challenge in sorting should be that collisions occur during large contractions, much more primary data should be presented/visualized to show how the accuracy of sorting changes during larger contractions in online experiments.

Fig.7: In presenting the accuracy of biofeedback, it is very hard to gain any intuition for performance by just looking at RMSE values. Showing the online decoded and edited trajectories would help readers understand the magnitude of errors.

Reviewer #3 (Public Review):

In this manuscript, Rossato and colleagues present a method for real-time decoding of EMG into putative single motor units. Their manuscript details a variety of decision points in their code and data collection pipeline that lead to a final result of recording on the order of ~10 putative motor units per muscle in human males. Overall the manuscript is highly restricted in its potential utility but may be of interest to aficionados. For those outside the field of human or nonhuman primate EMG, these methods will be of limited interest.

Notes<br /> 1. Artificial data should be used with this method to provide ground truth performance evaluations. Without it, the study assumptions are unchallenged and could be seriously flawed.

2. From the point of view of a motor control neuroscientist studying movement in animals other than humans or non-human primates, the title was misleadingly hopeful. The use case presented in this study requires human participants to perform isometric contractions, facilitating spatially redundant recordings across the muscle for the algorithm to work. It is unclear whether these methods will be of utility to use cases under more physiological conditions (ie. dynamic movement).

3. The text states that "EMG signals recorded with an array of electrodes can be considered and instantaneous mixture of the original motor unit spike trains and their delayed versions." While this may be a true statement, it is not a complete statement, since motor units at distal sites may be shared, not shared, or novel. It was not clear to me whether the diversity of these scenarios would affect the performance of the software or introduce artifacts. In other words, if at site 1 you can pick up the bulk signal of units 1,2,3,4; at site two you pick up the signals of units 2,3,4,5 and site three you pick up the signal of units 3,4,5,6, what does the algorithm assume is happening and what does it report and why?

4. I could not fully appreciate the performance gap solved by the current methods. What was not achievable before that is now achievable? The 125 ms speed of deconvolution? What was achievable before? Intro text around ln 85 states that 'most of the current implementations of this approach rely on offline processing, which restricts its ability to be used..." but no reference is provided here about what the non 'most' of can achieve.

5. Relatedly, it would have been nice to see a proof of concept using real-time feedback for some kind of biofeedback signal. If that is the objective here, why not show us this? I found the actual readout metrics of performance rather esoteric. They may be of interest to very close experts so I will defer to them for input.

6. I was disappointed to see that only male participants are used because of some vague statement that 'it is widely known in the field' that more motor units can be resolved in males, without thorough referencing. It seems that the objective of the algorithm is the speed of analysis, not the number of units, which makes the elimination of female participants not justified.

7. Human curation is often used in spike sorting, but the description of criteria used in this step or how the human curation choices are documented is missing.

8. The authors might try to add text to be more circumspect about the contributions of this method. I would recommend emphasizing the conceptual advances over the specifics of the performance of the algorithm since processor speed and implementation of the ideas in a faster environment (Matlab can be slow) will change those outcomes in a trivial way. Yet, much of the results section is very focused on these metrics.<br /> Minor<br /> Ln 115, "inversing" is not a word. "inverse" is not a verb<br /> Ln 186, typo, bioadhesive<br /> MVC should be defined on first use. It is currently defined on 3rd use or so.<br /> The term rate is used in a variety of places without units. Eg line 465 but not limited to that

Reviewer #1 (Public Review):

The manuscript by Kadkova et al. describes an electrophysiological analysis of 3 neurodevelopmental disease-causing SNAP-25 mutations in hippocampal neuron autaptic cultures. The work expands on a prior study of these 3 mutations, along with several others in SNAP-25, that was performed in acutely dissociated hippocampal cultures by another group (Alten et al, 2021). Most of the physiology defects found are pretty similar for the 3 mutations the two research groups characterized, with differences largely found in the effects on the size of the readily releasable pool (RRP) of SVs. These differences could be due to technical differences in the approach but are also likely to reflect in part differences in autapses as a model that has been previously described. In addition to the physiological analysis in cultured neurons, the current work extends the analysis beyond the prior study by analyzing the effects of these SNAP-25 mutations in vitro liposome fusion assays with purified proteins, and some modeling of the effects on energy landscapes during priming and fusion.

The authors use lentiviral expression of wildtype or one of the 3 mutants in SNAP-25 autaptic neurons and assay neuronal survival and synaptic output. The authors also combine wildtype with each of the 3 mutants as well, given these diseases manifest as spontaneous mutations in only 1 of the SNAP-25 alleles, suggesting a dominant effect. The authors observe that the V48F and D166Y alleles (that are suggested to disrupt the Syt1-SNAP-25/SNARE interface) result in a very large increase in a spontaneous release that exceeds the Syt1 null mutant alone, suggesting an effect on spontaneous SV release beyond a lack of Syt1 regulation of SNARE-mediated fusion. In contrast, Syt1 nulls have a much more severe loss of evoked release, though both V48F and D166Y also have modest decreases in release. They find both mutants also cause a decrease in the RRP. Applying some modeling for these results, the authors suggest V48F and D166Y lower the energy barrier for fusion, creating enhanced spontaneous release rates and causing a decrease of the RRP. They also find evidence for reduced SV priming. In contrast, a SNAP-25 I167N disease mutation in the SNARE assembly interaction layer causes dramatic decreases in both evoked and spontaneous release, consistent with a disruption to SNARE assembly/stability. In vitro fusion assays with these mutant SNAP-25 alleles were also done and provided supportive evidence for these interpretations for all 3 alleles. The ability to control calcium, Syt1, PIP2, and Complexin levels in the in vitro assays provided additional information on defining the precise steps of the fusion process these mutations disrupt. Together, the study indicates the I167N mutation acts as a dominant-negative allele to block fusion, while the other two alleles have both loss- and gain-of function properties that cause more complex disruptions that decrease evoked release while dramatically enhancing spontaneous fusion.

Overall, these results build on prior work and shed light on how disruptions to the SNAP-25 t-SNARE alter the process of SV priming and fusion.

Reviewer #2 (Public Review):

Kádková, Murach, Pedersen, and colleagues studied how three disease-causing missense mutations in SNAP25 affect synaptic vesicle exocytosis. These mutations have previously been studied by Alten et al., 2021. The authors observed similar impairments in spontaneous and evoked release as Alten et al., 2021, but the measurement of readily releasable pool (RRP) size differed between the two studies. The authors found that the V48F and D166Y mutations affect the interaction with the Ca2+ sensor synaptotagmin-1 (Syt1), but do not entirely phenocopy Syt1 loss-of-function because they also exhibit a gain-of-function. Thus, these mutations affect multiple aspects of the energy landscape for vesicle priming and fusion. The I67N mutation specifically increases the fusion energy barrier without affecting upstream vesicle priming.

The strength of the study includes careful and technically excellent dissection of the synaptic release process and a combination of electrophysiology, biophysics, and modeling approaches. This study gained a deeper mechanistic understanding of these mutations in vesicle exocytosis than the previous study but did not result in a paradigm shift in our understanding of SNAP25-associated encephalopathy because the same spontaneous and evoked release phenotypes were previously identified.

1) The authors discussed possible reasons for the different results of the RRP sizes between this study and Alten et al., 2021. One of them is how the hypertonic solution is applied. The authors thought that the long application of hypertonic solution in Alten et al., 2021 caused an overlapping release of RRP and upstream vesicle pools because Alten et al., 2021 measured 10-fold larger RRP size than what was measured in this study. However, Alten et al., 2021 measured RRP from IPSCs and a single inhibitory vesicle fusion causes larger charge transfer than an excitatory vesicle. The authors need to take this into consideration and 10-fold is likely an overestimate.

2) Statistical tests should be performed for protein expression levels (Fig 2A and Fig 10A) and in vitro fusion assays (Fig 8D,E and Fig 9 B,C).

Reviewer #1 (Public Review):

Valk and Engert et al. examined the potential relations between three different mental training modules, hippocampal structure and functional connectivity, and cortisol levels over a 9-month period. They found that among the three types of mental training: Presence (attention and introspective awareness), Affect (socio-emotional - compassion and prosocial motivation), and Perspective (socio-cognitive - metacognition and perspective taking) modules; Affect training most consistently related to changes in hippocampal structure and function - specifically, CA1-3 subfields of the hippocampus. Moreover, decreases in diurnal cortisol correlated to bilateral increases in volume, and decreases in diurnal and chronic cortisol left CA1-3 functional connectivity. Chronic cortisol levels also related to right CA4/DG volume and left subiculum function. The authors demonstrate that mindfulness training programs impact hippocampus and are a potential avenue for stress interventions, a potential avenue to improve health. The data contribute to the literature on plasticity of hippocampal subfields during adulthood, the impact of mental training interventions on the brain, and the link between CA1-3 and both short- and long-term stress changes. Additional clarification and extension of the methods is needed to strengthen the authors' conclusions.

The authors thoughtfully approached the study of hippocampal subfields, utilizing a method designed for T1w images that outperformed Freesurfer 5.3 and that produced comparable results to an earlier version of ASHS. However, given the use of normalized T1-weighted images to delineate hippocampal subfield volume, some caution may be warranted (Wisse et al. 2020). While the authors note the assessment of quality control processes, the difficulty in ensuring valid measurement is an ongoing conversation in the literature. This also extends to the impact of functional co-registration using segmentations. I appreciate the inclusion of Table 5 in documenting reasons for missing data across subjects. Providing additional details on the distribution of quality ratings across subfields would help contextualize the results and ensure there is equal quality of segmentations across subfields.

Given the consistent pattern of finding results with CA1-3, in contrast to other subfields, it would help to know if the effects of the different training modules on subfields differed from each other statistically (i.e., not just that one is significant, and one is not) to provide an additional context of the strength of results focused on Affect training and CA1-3 (for example, those shown in Figure 3).

Reviewer #2 (Public Review):

In this study, Valk, Engert et al. investigated effects of stress-reducing behavioral intervention on hippocampal structure and function across different conditions of mental training and in relation to diurnal and chronic cortisol levels. The authors provide convincing multimodal evidence of a link between hippocampal integrity and stress regulation, showing changes in both volume and intrinsic functional connectivity, as measured by resting-state fMRI, in hippocampal subfield CA1-3 after socio-affective training as compared to training in a socio-cognitive module. In particular, increased CA1-3 volume following socio-affective training overlapped with increased functional connectivity to medial prefrontal cortex, and reductions in cortisol. The conclusions of this paper are well supported by the data, although some aspects of the data analysis would benefit from being clarified and extended.

A main strength of the study is the rigorous design of the behavioral intervention, including test-retest cohorts, an active control group, and a previously established training paradigm, contributing to an overall high quality of included data. Similarly, systematic quality checking of hippocampal subfield segmentations contributes to a reliable foundation for structural and functional investigations.

Another strength of the study is the multimodal data, including both structural and functional markers of hippocampal integrity as well as both diurnal and chronic estimates of cortisol levels. However, the included analyses are not optimally suited for elucidating multivariate interrelationships between these measures. Instead, effects of training on structure and function, and their links to cortisol, are largely characterized separately from each other. This results in the overall interpretation of results, and conclusions, being dependent on a large number of separate associations. Adopting multivariate approaches would better target the question of whether there is cortisol-related structural and functional plasticity in the hippocampus after mental training aimed at reducing stress.

The authors emphasize a link between hippocampal subfield CA1-3 and stress regulation, and indeed, multiple lines of evidence converge to highlight a most consistent role of CA1-3. There are, however, some aspects of the results that limit the robustness of this conclusion. First, formal comparisons between subfields are incomplete, making it difficult to judge whether the CA1-3, to a greater degree than other subfields, display effects of training. Relatedly, it would be of interest to assess whether changes in CA1-3 make a significant contribution to explaining the link between hippocampal integrity and cortisol, as compared to structure and functional connectivity of the whole hippocampus. Second, both structural and functional effects (although functional to a greater degree), were most pronounced in the specific comparison of "Affect" and "Perspective" training conditions, possibly limiting the study's ability to inform general principles of hippocampal stress-regulation.

Reviewer #1 (Public Review):

In this manuscript, the authors use a large dataset of neuroscience publications to elucidate the nature of self-citation within the neuroscience literature. The authors initially present descriptive measures of self-citation across time and author characteristics; they then produce an inclusive model to tease apart the potential role of various article and author features in shaping self-citation behavior. This is a valuable area of study, and the authors approach it with an appropriate and well-structured dataset.

The study's descriptive analyses and figures are useful and will be of interest to the neuroscience community. However, with regard to the statistical comparisons and regression models, I believe that there are methodological flaws that may limit the validity of the presented results. These issues primarily affect the uncertainty of estimates and the statistical inference made on comparisons and model estimates - the fundamental direction and magnitude of the results are unlikely to change in most cases. I have included detailed statistical comments below for reference.

Conceptually, I think this study will be very effective at providing context and empirical evidence for a broader conversation around self-citation. And while I believe that there is room for a deeper quantitative dive into some finer-grained questions, this paper will be a valuable catalyst for new areas of inquiry around citation behavior - e.g., do authors change self-citation behavior when they move to more or less prestigious institutions? do self-citations in neuroscience benefit downstream citation accumulation? do journals' reference list policies increase or decrease self-citation? - that I hope that the authors (or others) consider exploring in future work.

Statistical comments:

(1) Throughout the paper, the nested nature of the data does not seem to be appropriately handled in the bootstrapping, permutation inference, and regression models. This is likely to lead to inappropriately narrow confidence bands and overly generous statistical inference.

(2) The discussion of the data structure used in the regression models is somewhat opaque, both in the main text and the supplement. From what I gather, these models likely have each citation included in the model at least once (perhaps twice, once for first-author status and one for last-author status), with citations nested within citing papers, cited papers, and authors. Without inclusion of random effects, the interpretation and inference of the estimates may be misleading.

(3) I am concerned that the use of the inverse hyperbolic sine transform is a bit too prescriptive, and may be producing poor fits to the true predictor-outcome relationships. For example, in a figure like Fig S8, it is hard to know to what extent the sharp drop and sign reversal are true reflections of the data, and to what extent they are artifacts of the transformed fit.

(4) It seems there are several points in the analysis where papers may have been dropped for missing data (e.g., missing author IDs and/or initials, missing affiliations, low-confidence gender assessment). It would be beneficial for the reader to know what % of the data was dropped for each analysis, and for comparisons across countries it would be important for the authors to make sure that there is not differential missing data that could affect the interpretation of the results (e.g., differences in self-citation being due to differences in Scopus ID coverage).

Reviewer #2 (Public Review):

The authors provide a comprehensive investigation of self-citation rates in the field of Neuroscience, filling a significant gap in existing research. They analyze a large dataset of over 150,000 articles and eight million citations from 63 journals published between 2000 and 2020. The study reveals several findings. First, they state that there is an increasing trend of self-citation rates among first authors compared to last authors, indicating potential strategic manipulation of citation metrics. Second, they find that the Americas show higher odds of self-citation rates compared to other continents, suggesting regional variations in citation practices. Third, they show that there are gender differences in early-career self-citation rates, with men exhibiting higher rates than women. Lastly, they find that self-citation rates vary across different subfields of Neuroscience, highlighting the influence of research specialization. They believe that these findings have implications for the perception of author influence, research focus, and career trajectories in Neuroscience.

Overall, this paper is well written, and the breadth of analysis conducted by authors, with various interactions between variables (eg. gender vs. seniority), shows that the authors have spent a lot of time thinking about different angles. The discussion section is also quite thorough. The authors should also be commended for their efforts in the provision of code for the public to evaluate their own self-citations. That said, here are some concerns and comments that, if addressed, could potentially enhance the paper:

1. There are concerns regarding the data used in this study, specifically its bias towards top journals in Neuroscience, which limits the generalizability of the findings to the broader field. More specifically, the top 63 journals in neuroscience are based on impact factor (IF), which raises a potential issue of selection bias. While the paper acknowledges this as a limitation, it lacks a clear justification for why authors made this choice. It is also unclear how the "top" journals were identified as whether it was based on the top 5% in terms of impact factor? Or 10%? Or some other metric? The authors also do not provide the (computed) impact factors of the journals in the supplementary.

By exclusively focusing on high impact journals, your analysis may not be representative of the broader landscape of self-citation patterns across the neuroscience literature, which is what the title of the article claims to do.

2. One other concern pertains to the possibility that a significant number of authors involved in the paper may not be neuroscientists. It is plausible that the paper is a product of interdisciplinary collaboration involving scientists from diverse disciplines. Neuroscientists amongst the authors should be identified.

3. When calculating self-citation rate, it is important to consider the number of papers the authors have published to date. One plausible explanation for the lower self-citation rates among first authors could be attributed to their relatively junior status and short publication record. As such, it would also be beneficial to assess self-citation rate as a percentage relative to the author's publication history. This number would be more accurate if we look at it as a percentage of their publication history. My suspicion is that first authors (who are more junior) might be more likely to self-cite than their senior counterparts. My suspicion was further raised by looking at Figures 2a and 3. Considering the nature of the self-citation metric employed in the study, it is expected that authors with a higher level of seniority would have a greater number of publications. Consequently, these senior authors' papers are more likely to be included in the pool of references cited within the paper, hence the higher rate.

While the authors acknowledge the importance of the number of past publications in their gender analysis, it is just as important to include the interplay of seniority in (1) their first and last author self-citation rates and (2) their geographic analysis.

4. Because your analysis is limited to high impact journals, it would be beneficial to see the distribution of the impact factors across the different countries. Otherwise, your analysis on geographic differences in self-citation rates is hard to interpret. Are these differences really differences in self-citation rates, or differences in journal impact factor? It would be useful to look at the representation of authors from different countries for different impact factors.

5. The presence of self-citations is not inherently problematic, and I appreciate the fact that authors omit any explicit judgment on this matter. That said, without appropriate context, self-citations are also not the best scholarly practice. In the analysis on gender differences in self-citations, it appears that authors imply an expectation of women's self-citation rates to align with those of men. While this is not explicitly stated, use of the word "disparity", and also presentation of self-citation as an example of self-promotion in discussion suggest such a perspective. Without knowing the context in which the self-citation was made, it is hard to ascertain whether women are less inclined to self-promote or that men are more inclined to engage in strategic self-citation practices.

Reviewer #3 (Public Review):

This paper analyses self-citation rates in the field of Neuroscience, comprising in this case, Neurology, Neuroscience and Psychiatry. Based on data from Scopus, the authors identify self-citations, that is, whether references from a paper by some authors cite work that is written by one of the same authors. They separately analyse this in terms of first-author self-citations and last-author self-citations. The analysis is well-executed and the analysis and results are written down clearly. There are some minor methodological clarifications needed, but more importantly, the interpretation of some of the results might prove more challenging. That is, it is not always clear what is being estimated, and more importantly, the extent to which self-citations are "problematic" remains unclear.

When are self-citations problematic? As the authors themselves also clarify, "self-citations may often be appropriate". Researchers cite their own previous work for perfectly good reasons, similar to reasons of why they would cite work by others. The "problem", in a sense, is that researchers cite their own work, just to increase the citation count, or to promote their own work and make it more visible. This self-promotional behaviour might be incentivised by certain research evaluation procedures (e.g. hiring, promoting) that overly emphasise citation performance. However, the true problem then might not be (self-)citation practices, but instead, the flawed research evaluation procedures that emphasis citation performance too much. So instead of problematising self-citation behaviour, and trying to address it, we might do better to address flawed research evaluation procedures. Of course, we should expect references to be relevant, and we should avoid self-promotional references, but addressing self-citations may just have minimal effects, and would not solve the more fundamental issue.

Some other challenges arise when taking a statistical perspective. For any given paper, we could browse through the references, and determine whether a particular reference would be warranted or not. For instance, we could note that there might be a reference included that is not at all relevant to the paper. Taking a broader perspective, the irrelevant reference might point to work by others, included just for reasons of prestige, so-called perfunctory citations. But it could of course also include self-citations. When we simply start counting all self-citations, we do not see what fraction of those self-citations would be warranted as references. The question then emerges, what level of self-citations should be counted as "high"? How should we determine that? If we observe differences in self-citation rates, what does it tell us?

For example, the authors find that the (any author) self-citation rate in Neuroscience is 10.7% versus 15.9% in Psychiatry. What does this difference mean? Are psychiatrists citing themselves more often than neuroscientists? First author men showed a self-citation rate of 5.12% versus a self-citation rate of 3.34% of women first authors. Do men engage in more problematic citation behaviour? Junior researchers (10-year career) show a self-citation rate of about 5% compared to a self-citation rate of about 10% for senior researchers (30-year career). Are senior researchers therefore engaging in more problematic citation behaviour? The answer is (most likely) "no", because senior authors have simply published more, and will therefore have more opportunities to refer to their own work. To be clear: the authors are aware of this, and also take this into account. In fact, these "raw" various self-citation rates may, as the authors themselves say, "give the illusion" of self-citation rates, but these are somehow "hidden" by, for instance, career seniority.

Again, the authors do consider this, and "control" for career length and number of publications, et cetera, in their regression model. Some of the previous observations then change in the regression model. Neuroscience doesn't seem to be self-citing more, there just seem to be junior researchers in that field compared to Psychiatry. Similarly, men and women don't seem to show an overall different self-citation behaviour (although the authors find an early-career difference), the men included in the study simply have longer careers and more publications.

But here's the key issue: what does it then mean to "control" for some variables? This doesn't make any sense, except in the light of causality. That is, we should control for some variable, such as seniority, because we are interested in some causal effect. The field may not "cause" the observed differences in self-citation behaviour, this is mediated by seniority. Or is it confounded by seniority? Are the overall gender differences also mediated by seniority? How would the selection of high-impact journals "bias" estimates of causal effects on self-citation? Can we interpret the coefficients as causal effects of that variable on self-citations? If so, would we try to interpret this as total causal effects, or direct causal effects? If they do not represent causal effects, how should they be interpreted then? In particular, how should it "inform author, editors, funding agencies and institutions", as the authors say? What should they be informed about?

The authors also "encourage authors to explore their trends in self-citation rates". It is laudable to be self-critical and review ones own practices. But how should authors interpret their self-citation rate? How useful is it to know whether it is 5%, 10% or 15%? What would be the "reasonable" self-citation rate? How should we go about constructing such a benchmark rate? Again, this would necessitate some causal answer. Instead of looking at the self-citation rate, it would presumably be much more informative to simply ask authors to check whether references are appropriate and relevant to the topic at hand.

In conclusion, the study shows some interesting and relevant differences in self-citation rates. As such, it is a welcome contribution to ongoing discussions of (self) citations. However, without a clear causal framework, it is challenging to interpret the observed differences.

Reviewer #1 (Public Review):

This study demonstrates that vitamin D-bound VDR increased the expression of SIRT1 and that vitamin D-bound VDR interacts with SIRT1 to cause auto-deacetylation on Lys610 and activation of SIRT1 catalytic activity. This is an important finding that is relevant to the actions of VDR on colorectal cancer. The data presented to support the presented conclusion is convincing.

A strength of the study is that it is focused on a narrow group of conclusions.

The major weakness of the study is that the site of SIRT1 regulatory lysine acetylation is defined by mutational analysis rather than by direct biochemical analysis. This issue is partially mitigated by previous reports of K610 acetylation using mass spec (https://www.phosphosite.org/proteinAction.action?id=5946&showAllSites=true). However, Fig. 4E is reassuring because it shows that the apparent acetylation of the K610 mutant SIRT1 appears to be lower than WT SIRT1

A second weakness of the study relates to the use of shRNA-mediated knockdown of VDR for some studies in which a previously reported cell line was employed. The analysis presented would be more compelling if similar data was obtained using more than one shRNA. Similarly, only a single siRNA for SIRT1 is presented in Table 1.

A third weakness of the study is that the conclusion that the VDR interaction with SIRT1 is the cause of auto-deacetylation rather than an associated event mediated by another mechanism would be more strongly supported by mutational analysis of SIRT1 and VDR residues required for the binding interaction. Will VDR increase SIRT1 activity when mutations are introduced to block the interaction? While the finding that catalytically inactive SIRT1 does not interact with VDR is helpful, this does not address the role of the binding surface.

A fourth weakness of the study is that it would be improved by testing the proposed hypothesis through in vitro reconstitution with purified proteins. Does VDR cause auto-deacetylation and activation of Sirt1 in vitro?

Reviewer #2 (Public Review):

The authors provide a comprehensive analysis of vitamin D-mediated signaling through VDR, SIRT1, and Ace H3K9. They specifically emphasize the significance of K610 in SIRT1 within this signaling pathway. The article effectively presents a convincing and straightforward argument. The experiments conducted are meticulously executed, and the statistical analysis is sound. The inclusion of complex biochemistry details adequately covers the topic at hand. These findings hold great relevance to both normal and pathological physiology across different cell lineages, making them of considerable interest.

Reviewer #1 (Public Review):

The objective of this investigation was to determine whether experimental pain could induce alterations in cortical inhibitory/facilitatory activity observed in TMS-evoked potentials (TEPs). Previous TMS investigations of pain perception had focused on motor evoked potentials (MEPs), which reflect a combination of cortical, spinal, and peripheral activity, as well as restricting the focus to M1. The main strength of this investigation is the combined use of TMS and EEG in the context of experimental pain. More specifically, Experiment 1 investigated whether acute pain altered cortical excitability, reflected in the modulation of TEPs. The main outcome of this study is that relative to non-painful warm stimuli, painful thermal stimuli led to an increase on the amplitude of the TEP N45, with a larger increase associated with higher pain ratings. Because it has been argued that a significant portion of TEPs could reflect auditory potentials elicited by the sound (click) of the TMS, Experiment 2 constituted a control study that aimed to disentangle the cortical response related to TMS and auditory activity. Finally, Experiment 3 aimed to disentangle the cortical response to TMS and reafferent feedback from muscular activity elicited by suprathreshold TMS applied over M1. The fact that the authors accompanied their main experiment with two control experiments strengthens the conclusion that the N45 TEP peak could be implicated in the perception of painful stimuli. Perhaps, the addition of a highly salient but non-painful stimulus (i.e. from another modality) would have further ruled out that the effects on the N45 are not predominantly related to intensity/saliency of the stimulus rather than to pain per se.

Reviewer #2 (Public Review):

The authors have used transcranial magnetic stimulation (TMS) and motor evoked potentials (MEPs) and TMS-electroencephalography (EEG) evoked potentials (TEPs) to determine how experimental heat pain could induce alterations in these metrics.
In Experiment 1 (n = 29), multiple sustained thermal stimuli were administered over the forearm, with the first, second, and third block of stimuli consisting of warm but non-painful (pre-pain block), painful heat (pain block) and warm but non-painful (post-pain block) temperatures respectively. Painful stimuli led to an increase in the amplitude of the fronto-central N45, with a larger increase associated with higher pain ratings. Experiments 2 and 3 studied the correlation between the increase in the N45 in pain and the effects of a sham stimulation protocol/higher stimulation intensity. They found that the centro-frontal N45 TEP was decreased in acute pain.

The study comes from a very strong group in the pain fields with long experience in psychophysics, experimental pain, neuromodulation, and EEG in pain. They are among the first to report on changes in cortical excitability as measured by TMS-EEG over M1.

While their results are in line with reductions seen in motor-evoked responses during pain and effort was made to address possible confounding factors (study 2 and 3), there are some points that need attention. In my view the most important are:<br /> 1. The method used to calculate the rest motor threshold, which is likely to have overestimated its true value : calculating highly abnormal RMT may lead to suprathreshold stimulations in all instances (Experiment 3) and may lead to somatosensory "contamination" due to re-afferent loops in both "supra" and "infra" (aka. less supra) conditions.<br /> 2. The low number of pulses used for TEPs (close to ⅓ of the usual and recommended), lack of measures to mask auditory noise.<br /> 3. A supra-stimulus heat stimulus not based on individual HPT, that oscillates during the experiment and that lead to large variations in pain intensity across participants is unfortunate. So is the lack of report on measures taken to correct for a fortuitous significance (multiple comparison correction) in such a huge number of serial paired tests.

Reviewer #3 (Public Review):

The present study aims to investigate whether pain influences cortical excitability. To this end, heat pain stimuli are applied to healthy human participants. Simultaneously, TMS pulses are applied to M1 and TMS-evoked potentials (TEPs) and pain ratings are assessed after each TMS pulse. TEPs are used as measures of cortical excitability. The results show that TEP amplitudes at 45 msec (N45) after TMS pulses are higher during painful stimulation than during non-painful warm stimulation. Control experiments indicate that auditory, somatosensory, or proprioceptive effects cannot explain this effect. Considering that the N45 might reflect GABAergic activity, the results suggest that pain changes GABAergic activity. The authors conclude that TEP indices of GABAergic transmission might be useful as biomarkers of pain sensitivity.

Pain-induced cortical excitability changes is an interesting, timely, and potentially clinically relevant topic. The paradigm and the analysis are sound, the results are mostly convincing, and the interpretation is adequate. The following clarifications and revisions might help to improve the manuscript further.

1. Non-painful control condition. In this condition, stimuli are applied at warmth detection threshold. At this intensity, by definition, some stimuli are not perceived as different from the baseline. Thus, this condition might not be perfectly suited to control for the effects of painful vs. non-painful stimulation. This potential confound should be critically discussed.<br /> 2. MEP differences between conditions. The results do not show differences in MEP amplitudes between conditions (BF 1.015). The analysis nevertheless relates MEP differences between conditions to pain ratings. It would be more appropriate to state that in this study, pain did not affect MEP and to remove the correlation analysis and its interpretation from the manuscript.<br /> 3. Confounds by pain ratings. The ISI between TMS pulses is 4 sec and includes verbal pain ratings. Considering this relatively short ISI, would it be possible that verbal pain ratings confound the TEP? Moreover, could the pain ratings confound TEP differences between conditions, e.g., by providing earlier ratings when the stimulus is painful? This should be carefully considered, and the authors might perform control analyses.<br /> 4. Confounds by time effects. Non-painful and painful conditions were performed in a fixed order. Potential confounds by time effects should be carefully considered.<br /> 5. Data availability. The authors should state how they make the data openly available.

Public Review:

In countries endemic for P vivax the need to administer a primaquine (PQ) course adequate to prevent relapse in G6PD deficient persons poses a real dilemma. On one hand PQ will cause haemolysis; on the other hand, without PQ the chance of relapse is very high. As a result, out of fear of severe haemolysis, PQ has been under-used.

In view of the above, the Authors have investigated in well-informed volunteers, who were kept under close medical supervision in hospital throughout the study, two different schedules of PQ administration: (1) escalating doses (to a total of 5-7 mg/kg); (2) single 45 mg dose (0.75 mg/kg).

It is shown convincingly that regimen (1) can be used successfully to deliver within 3 weeks, under hospital conditions, the dose of PQ required to prevent P vivax relapse.

As expected, with both regimens acute haemolytic anaemia (AHA) developed in all cases. With regimen (2), not surprisingly, the fall in Hb was less, although it was abrupt. With regimen (1) the average fall in Hb was about 4 G. Only in one subject the fall in Hb mandated termination of the study.

Since the data from the Chicago group some sixty years ago, there has been no paper reporting a systematic daily analysis of AHA in so many closely monitored subjects with G6PD deficiency. The individual patient data in the Supplementary material are most informative and more than precious.

Having said this, I do have some general comments.<br /> 1. Through their remarkable Part 1 study, the Authors clearly wish to set the stage for a revision of the currently recommended PQ regimen for G6PD deficient patients. They have shown that 5-7 mg/kg can be administered within 3 weeks, whereas the currently recommended regimen provides 6 mg/kg over no less than 8 weeks.<br /> 2. Part 2 aims to show that, as was known already, even a single PQ dose of 0.75 mg/kg causes a significant degree of haemolysis: G6PD deficiency-related haemolysis is characteristically markedly dose-dependent. Although they do not state it explicitly in these words (I think they should), the Authors want to make it clear that the currently recommended regimen does cause AHA.<br /> 3. Regulatory agencies like to classify a drug regimen as either SAFE or NOT-SAFE; they also like to decide who is 'at risk' and who is 'not at risk'. A wealth of data, including those in this manuscript, show that it is not correct to say that a G6PD deficient person when taking PQ is at risk of haemolysis: he or she will definitely have haemolysis. As for SAFETY, it will depend on the clinical situation when PQ is started and on the severity of the AHA that will develop.

The above three issues are all present in the discussion, but I think they ought to be stated more clearly.

Finally, by the Authors' own statement on page 15, the main limitation is the complexity of this approach. The authors suggest that blister packed PQ may help; but to me the real complexity is managing patients in the field versus the painstaking hospital care in the hands of experts, of which volunteers in this study have had the benefit. It is not surprising that a fall in Hb of 4 g/dl is well tolerated by most non-anaemic men; but patients with P vivax in the field may often have mild to moderate to severe anaemia; and certainly they will not have their Hb, retics and bilirubin checked every day. In crude approximation, we are talking of a fall in Hb of 4 G with regimen (1), as against a fall in Hb of 2 G with regimen (2), that is part of the currently recommended regimen: it stands to reason that, in terms of safety, the latter is generally preferable (even though some degree of fall in Hb will recur with each weekly dose). In my view, these difficult points should be discussed deliberately.

Reviewer #1 (Public Review):

Sun and colleagues investigated the cross-reactive antibodies between E.Coli and the host in severe alcoholic hepatitis (SAH). The study found that IgA and IgG were deposited in the liver of SAH patients. Complements C3d and C4d were also deposited in the SAH patient's liver. Moreover, they found that the Ig accumulated in the SAH liver, but not in the SAH serum, induced hepatocyte killing, suggesting that liver Ig is important. Then, they found that these Ig can recognize both human and E. Coli antigens. Very interestingly, SAH-derived Ig shows cross-reactivity to both human and E. Coli antigens, suggesting E, Coli-primed Ig in SAH may damage hepatocytes through host antigen recognition. These Ig are not observed in alcoholic cirrhosis patients. The liver RNA-seq data suggested that Ig was also produced in the liver, not only gut-derived Ig. This is a very interesting study showing the novel mechanism of SAH mediated by the Ig with the cross-reactivity with bacteria and host antigens, which is not observed in AC patients. Overall, the study design is reasonable and the data are consistent to support their central hypothesis. There are a few comments.

Specific comments:<br /> 1. Figures 1 and 2 show Ig deposition in the liver (it seems on hepatocytes). Not only Ig reaction to the specific antigen but also non-specific Fc receptor-mediated binding to hepatocytes could be contributed.<br /> 2. Similarly, in Figure 2G Ig-mediated hepatocyte killing, Fc receptor-mediated hepatocyte killing may be involved.<br /> 3. The study examined the possibility of liver resident B cell and plasma cell-mediated Ig. As the authors mentioned in the discussion, B cells may be translocated from the intestine to the liver. Or the resident B cells (not from the gut) are also involved.

Reviewer #2 (Public Review):

In this paper, Ahmadi et al demonstrated that antibodies produced locally in the liver by infiltrating B cells can enhance liver damage caused by fat accumulation. The main finding is that human samples extracted from severe alcoholic hepatitis showed antibody accumulation that may be related to an enhanced immune response to self-antigens, which could ultimately fuel liver damage - which was already present due to alcohol consumption. Their data are corroborated by arrays and gene ontology assays, and I strongly believe that these data could add to the future options we have to treat patients.

Reviewer #1 (Public Review):

The work by Debashish U. Menon, Noel Murcia, and Terry Magnuson brings important knowledge about histone H3.3 dynamics involved in meiotic sex chromosome inactivation (MSCI). MSCI is unique to gametes and failure during this process can lead to infertility. Classically, MSCI has been studied in the context of DNA Damage repair pathways and little is known about the epigenetic mechanisms behind maintenance of the sex body as a silencing platform during meiosis. One of the major strengths of this work is the evidence provided on the role of ARID1A, a BAF subunit, in MSCI through the regulation of H3.3 occupancy in specific genic regions. This is well supported by a combination of immunofluorescence, RNA seq, CUT&RUN and ATAC-seq.<br /> The mouse model in this study is a conditional Stra8 Cre mouse. Loss of ARID1A in this mouse, caused up regulation of XY linked genes in prophase I spermatocytes and ingression of RNA pol II to the sex body, indicating a role for this chromatin remodeller in MSCI. Using RNA seq and CUT&RUN and ATAC-seq, the authors show that ARID1A regulates chromatin accessibility of the sex chromosomes. ARID1A interacts with gene transcription start sites of sex-linked genes, and loss of ARID1A increased promoter accessibility of XY linked genes with concomitant gene up regulation.

This work suggests that ARID1A regulates chromatin composition of the sex body relative to the autosomes. In the absence of ARID1A, spermatocytes show less enrichment of H3.3 in the sex chromosomes and stable levels of the canonical histones H3.1/3.2. By overlapping CUT&RUN and ATAC-seq data, authors show that changes in chromatin accessibility in the absence of ARID1A are given by redistribution of occupancy of H3.3. Gained open chromatin in mutants corresponds to up regulation of H3.3 occupancy at transcription start sites of genes regulated by ARID1A.

Interestingly, ARID1A loss caused increased promoter occupancy by H3.3 in regions usually occupied by PRDM9. PRDM9 is a protein with histone methyltransferase activity that catalyzes histone H3 lysine 4 trimethylation during meiotic prophase I, and positions double strand break (DSB) hotspots. Lack of ARID1A causes reduction in occupancy of DMC1, a recombinase involved in DSB repair, in non-homologous sex regions. These data suggest that ARID1A might indirectly influence DNA DSB repair on the sex chromosomes by regulating the localization of H3.3. This is very interesting given the suggested role for ARID1A in genome instability in cancer cells (Nacarelli et al 2020: 10.1080/23723556.2019.1690923, Zhang et al. 2023: 10.1093/carcin/bgad011 and others). It raises the question of whether this role is also involved in meiotic DSB repair in autosomes and/or how this mechanism differs in sex chromosomes compared to autosomes.

It is worth mentioning that authors show that there are Arid1a transcripts that escape the Cre system. This might mask the phenotype of the Arid1a knockout, given that many of the sequencing techniques used here are done on a heterogeneous population of knockout and wild type spermatocytes. In relation to this, I think that the use of the term "pachytene arrest" might be overstated, since this is not the phenotype truly observed (these mice produce sperm). ARID1A is present throughout prophase I and it might have pre-MSCI roles that impact earlier stages of Meiosis I and cell death might be happening in these earlier stages too.

Overall the research presented here is solid, adds new knowledge on how the sex chromatin is silenced during meiosis and has generated relevant databases for the field.

Reviewer #2 (Public Review):

The authors tried to characterize the function of the SWI/SNF remodeler family, BAF, in spermatogenesis. The authors focused on ARID1A, a BAF-specific putative DNA binding subunit, based on gene expression profiles. The study has several serious issues with the data and interpretation. The conditional deletion mouse model of ARIDA using Stra8-cre showed inefficient deletion; spermatogenesis did not appear to be severely compromised in the mutants. Using this data, the authors claimed that meiotic arrest occurs in the mutants. This is obviously a misinterpretation. In the later parts, the authors performed next-gen analyses, including ATAC-seq and H3.3 CUT&RUN, using the isolated cells from the mutant mice. However, with this inefficient deletion, most cells isolated from the mutant mice appeared not to undergo Cre-mediated recombination. Therefore, these experiments do not tell any conclusion pertinent to the Arid1a mutation. Furthermore, many of the later parts of this study focus on the analysis of H3.3 CUT&RUN. However, Fig. S7 clearly suggests that the H3.3 CUT&RUN experiment in the wild-type simply failed. Thus, none of the analyses using the H3.3 CUT&RUN data can be interpreted. Overall, I found that the study does not have rigorous data, and the study is not interpretable. If the author wishes to study the function of ARID2 in spermatogenesis, they may need to try other cre-lines to have more robust phenotypes, and all analyses must be redone using a mouse model with efficient deletion of ARID2.

Reviewer #3 (Public Review):

In this manuscript, Magnuson and colleagues investigate the meiotic functions of ARID1A, a putative DNA binding subunit of the SWI/SNF chromatin remodeler BAF. The authors develop a germ cell specific knockout mouse model using Stra8-cre and observe that ARID1A-deficient cells undergo pachytene arrest, although due to inefficiency of the Stra8-cre system the mice retain ARID1A-expressing cells that yield sperm and allow fertility. Because ARID1A was found to accumulate at the XY body late in Prophase I, the authors suspected a potential role in meiotic silencing and by RNAseq observe significant misexpression of sex-linked genes that typically are silenced at pachytene. They go on to show that ARID1A is required for exclusion of RNA PolII from the sex body, consistent with a meiotic sex chromosome inactivation (MSCI) defect. The authors proceed to investigate the impacts of ARID1A on chromatin accessibility and H3.3 deposition genome-wide. H3.3 is known be regulated by ARID1A and is linked to silencing, and here the authors find that upon loss of ARID1A, overall H3.3 enrichment at the sex body as measured by IF failed to occur, but H3.3 was enriched specifically at transcriptional start sites of sex-linked genes that are normally regulated by ARID1A. The results suggest that ARID1A normally prevents H3.3 accumulation at target promoters on sex chromosomes and based on additional data, restricts H3.3 to intergenic sites. Finally, the authors present data implicating ARID1A and H3.3 occupancy in DSB repair, finding that ARID1A KO leads to a reduction in focus formation by DMC1, a key repair protein. Overall the paper covers a lot of ground, provides important new insights into the process of MSCI from the perspective of chromatin composition and structure, and raises many interesting questions. In general the paper is well written and the data are clear. Specific points to address are as follows:

1. A challenge with the author's CKO model is the incomplete efficiency of ARID1A loss, due to incomplete CRE-mediated deletion. The authors effectively work around this issue, but they don't state specifically what percentage of CKO cells lack ARID1A staining. This information should be added. They refer to cells that retain ARID1A staining in CKO testes as 'internal controls' but this reviewer finds that label inappropriate. Although some cells that retain ARID1A won't have undergone CRE-mediated excision, others may have excised but possibly have delayed kinetics of deletion or ARID1A RNA/protein turnover and loss. Such cells likely have partial ARID1A depletion to different extents and therefore in some cases are no longer wild-type. In subsequent figures in which co-staining for ARID1A is done, it would be appropriate for the authors to specify if they are quantifying all cells from CKO testes, or only those that lack ARID1A staining.

2. The authors don't see defects in a few DDR markers in ARID1A CKO cells and conclude that the role of ARID1A in silencing is 'mutually exclusive to DDR pathways' (p 12) and 'occurs independently of DDR signaling' (p30). The data suggest that ARID1A may not be required for DDR signaling, but do not rule out the possibility that ARID1A is downstream of DDR signaling (and the authors even hypothesize this on p30). The data provided do not justify the conclusion that ARID1A acts independently of DDR signaling.

3. After observing no changes in levels or localization of H3.3 chaperones, the authors conclude that 'ARID1A impacts H3.3 accumulation on the sex chromosomes without affecting its expression or incorporation during pachynema.' It's not clear to this reviewer what the authors mean by this. Aside from the issue of not having tested DAXX or HIRA activity, are they suggesting that some other process besides altered incorporation leads to H3.3 accumulation and if so what process would that be?

4. The authors find an interesting connection between certain regions that gained chromatin accessibility after ARID1A loss (clusters G1 and G3) and presence of the PRDM9 sequence motif. The G1 and G3 clusters also show DMC1 occupancy and H3K4me3 enrichment. However, an additional cluster with gained accessibility (G4) also shows DMC1 occupancy and H3K4me3 enrichment but unlike clusters G1 and G3 has modest H3.3 accumulation. The paper would benefit for additional discussion about the G4 cluster (which encompasses 960 peak calls). Is there any enrichment of PRDM9 sites in G4? If H3.3 exclusion governs meiotic DSBs, how does cluster G4 fit into the model?

5. The impacts of ARID1A loss on DMC1 focus formation (reduced sex chromosome association) are very interesting and also raise additional questions. Are DMC1 foci on autosomes also affected during pachynema? The corresponding lack of apparent effect on RAD51 implies that breaks are still made and resected, enabling RAD51 filament formation. A more thorough quantitative assessment of RAD51 focus formation will be interesting in the long run, enabling determination of the number of break sites and the kinetics of repair, which the authors suggest is perturbed by ARID1A loss but don't directly test. It isn't clear how a nucleosomal factor (H3.3) would influence loading of recombinases onto ssDNA, especially if the alteration is not at the level of resection and ssDNA formation. Additional discussion of this point is warranted. Lastly, there currently are various notions for the interplay between RAD51 and DMC1 in filament formation and break repair, and brief discussion of this area and the implications of the new findings from the ARID1A CKO would strengthen the paper further.

Reviewer #3 (Public Review):

Neuronal migration is one of the key processes for appropriate neuronal development. Defects in neuronal migration are associated with different brain disorders often accompanied by intellectual disabilities. Therefore, the study of the mechanisms involved in neuronal migration helps to understand the pathogenesis of some brain malformations and psychiatric disorders.

FMRP is an RNA-binding protein implicated in RNA metabolism regulation and mRNA local translation. FMRP loss of function causes fragile X syndrome (FXS), the most common form of inherited intellectual disability. Previous studies have shown the role of FMRP in the multipolar to bipolar transition during the radial migration in the cortex and its possible relation with periventricular heterotopia and altered synaptic communication in humans with FXS. However, the role of FMRP in neuronal tangential migration is largely unknown. In this manuscript, the authors aim to decipher the role of FMRP in the tangential migration of neuroblasts along the rostral migratory stream (RMS) in the postnatal brain. By extensive live-imaging analysis of migrating neuroblasts along the RMS, they demonstrate the requirement of FMRP for neuroblast migration and centrosomal movement. These migratory defects are cell-autonomous and mediated by the microtubule-associated protein Map1b.

Overall, the manuscript highlights the importance of FMRP in neuronal tangential migration. They performed an analysis of different aspects of migration such as nucleokinesis and cytokinesis in migrating neuroblasts from live-imaging videos.<br /> However, the work is quite incomplete. The role of FMRP and Map1b in neuronal migration is not well introduced and discussed. In the cortex, FMRP is mainly implicated in the multipolar to bipolar transition of immature neurons, but not in the migration itself (la Fata et al., 2014). In fact, Fmr1 KO mice do not show impairment in cortical lamination. On the other hand, very less is mentioned about the role of Map1b in neuronal migration. It is not shown whether overexpression of Map1b alters neuroblast migration and recapitulates the Fmr1 KO phenotype.

Moreover, it is unclear to me which are the anatomical consequences of aberrant migration of neuroblasts in the Fmr1 KO mice. Authors mention that neuroblasts properly arrive at the OB and they refer to a previous publication (Scotto-Lomassese et al., 2011). However, this study does not show the distribution of neuroblasts in the SVZ, along the RMS or in the olfactory bulb (OB) in mutant mice. On the contrary, they said that there is no delay in the migration or maturation of granular cells arriving at the OB (Scotto-Lomassese et al., 2011). In summary, the authors do not show the functional consequences of aberrant neuroblast migration in the Fmr1 KO mice, making weaker the assumption that the study is important for the understanding of FXS pathophysiology.

Reviewer #1 (Public Review):

This work investigated Fragile X Messenger Ribonucleoprotein (FMRP) protein impact on neuroblast tangential migration in the postnatal rostral migratory stream (RMS). Authors conducted series of live-imaging on organotypic brain slices from Fmr1-null mice. They continued their analysis silencing Fmr1 exclusively from migrating neuroblasts using electroporation-mediated RNA interference method (MiRFmr1 KD). These impressive approaches show that neuroblasts tangential migration is impaired in Fmr1-null mice RMS and these defects are mostly recapitulated in the MiRFmr1neuroblasts.This nicely supports the idea that FMRP have a cell autonomous function in tangentially migrating neuroblasts. It is an important part of this work as migrating neuroblasts are in contact with each other and surrounding glial cells while migrating towards the olfactory bulb. The authors also confirm that FMRP mRNA target Microtubule Associated Protein 1B (MAP1B) is overexpressed in the Fmr1-null mice RMS. They successfully use electroporation-mediated RNA interference method to silence Map1b in the Fmr1-null mice neuroblasts. This discreet and elaborate experiment rescues most of the migratory defects observed both in Fmr1-null and MiRFmr1neuroblasts. Altogether, these results strongly suggest that FMRP-MAP1B axis has an important role in regulation of the neuroblasts tangential migration in RMS. Neurons move forward in cyclic saltatory manner which includes repeated steps of leading process extension, migration of the cell organelles and nuclear translocation. Authors reveal by analyzing the live-imaging data that FMRP-MAP1B axis is affecting movement of centrosome and nucleus during saltatory migration. An important part of the centrosome and nucleus movement is forces mediated by microtubule dynamics. Authors propose that FMRP regulate tangential migration via microtubule dynamics regulator MAP1B. This work provides valuable new information on regulation of the neuroblasts tangential saltatory migration. These findings also increase and improve our understanding of the issues involved in Fragile X Syndrome (FXS) disorders. The conclusions of this work are mostly supported by the data. However, methods and data analysis would benefit from more careful and comprehensive scrutiny.

1.) It would be beneficial for the detail-oriented readers to have a more comprehensive section of neuronal migration analysis. It would help to understand better the details of the results and analysis. For example, percentage of pausing time. Is neuroblast migration speed and pausing time (%) separated from each other? Does this mean that migration speed is measured from time of the nucleus movement, and it excludes pausing time? Sometimes migration speed refers to the total distance that cells have moved divided by the time between images (e.g., Nam et al. 2007, J Comp Neurol 505: 190-208). This is also important as neuroblasts migration speed fluctuate during their migration in RMS (e.g., Belvindrah et al. 2017, J Cell Biol 216: 2443-2461). It could be useful, for example, to show a plot of total migration distance distribution between controls, Fmr1-null, MiRFmr1 KD and MiRMap1b KD neuroblasts.

2.) The author's claim that Fmr1 interfering RNA (MiFmr1 KD) model "recapitulates the entire migratory phenotype described in Fmr1-null mutants". This is evident from the data analysis for the migration speed, pausing time percentage and NK distance. Parallel, but slightly weaker effect is seen in, NK frequency, CK frequency and CK efficiency. However, interpretation of the directionality analysis causes some concerns.<br /> a) Sinuosity index<br /> Fmr1-null mice (ctr: 1.32{plus minus}0.04; Fmr1-null: 1.93{plus minus}0.16; Figure 2C) and MiFmr1 KD neurons (MiRNEG: 1.5{plus minus}0.12; MiRFmr1 KD 1.62 {plus minus}0.08; Figure S1C). The latter results are significant, but standard error of means (SEM) seems to overlap. In addition, there is only a minor difference between control and MiRFmr1 KD cells sinuosity index.<br /> b) Directionality radar<br /> Migration directionality radar seems to be considerably different between Fmr1-null (Figure 2D) and MiFmr1 KD results (Figure S1D).<br /> It would be beneficial for this article to fully disclose, how these analyses were performed. For example, how sinuosity index was calculated and what does it precisely measure. It would greatly help to understand better the directionality analysis. To make these results more solid authors could have used original migration trajectories in the rose and/or trajectory plots. These plots visualize better the migration directionality results and clarify the changes in the directionality during migration.

3.) Authors claim that "Overall, our results demonstrate that MAP1B is the main FMRP mRNA target involved in the regulation of neuronal migration". Results and analysis show that migration speed, pausing time percentage, NK distance and NK frequency migratory defects are all rescued in Fmr1-null mice when MiRMap1b KD was introduced to the neuroblasts (Figure 4). These results are very interesting, linking FMRP-MAP1B axis to the microtubule dynamics.

4.) Authors could refine in discussion what is known about FRMP in neuronal migration. For example, La Fata et al. 2014 found that N-cadherin protein levels were lower in Fmr1-null mice and reintroducing N-cadherin rescued embryonic radial migration defects. N-cadherin is also expressed in the RMS and its deficiency affects negatively to the neuroblast migration (e.g., Porlan et al. 2014, Nat Cell Biol (7):629-38). This relationship of FMRP and N-cadherin could be discussed and considered in the article more closely. Overall, the article will benefit from clearer writing and more comprehensive discussion.

Reviewer #2 (Public Review):

In this manuscript, the authors conducted a straightforward molecular approach to link FMRP and MAP1B proteins functionally. Both proteins are connected since FMRP is a translational regulator of the MAP1B protein, a microtubule-stabilizing factor.

The results combined molecular genetics (FMRP knock-out mice) with acute inactivation of FRMP and MAP1B to conclusively support the notion that FMRP-dependent regulation of MAP1B is necessary for proper neuronal migration toward the olfactory bulb using the rostral migratory stream.

Overall, these results increase our knowledge of the molecular mechanism that controls how neurons migrate in the brain to reach their final destinations and confirms that cytoskeleton regulators are key players in this process.

Reviewer #1 (Public Review):

This work provides a new dataset of 71,688 images of different ape species across a variety of environmental and behavioral conditions, along with pose annotations per image. The authors demonstrate the value of their dataset by training pose estimation networks (HRNet-W48) on both their own dataset and other primate datasets (OpenMonkeyPose for monkeys, COCO for humans), ultimately showing that the model trained on their dataset had the best performance (performance measured by PCK and AUC). In addition to their ablation studies where they train pose estimation models with either specific species removed or a certain percentage of the images removed, they provide solid evidence that their large, specialized dataset is uniquely positioned to aid in the task of pose estimation for ape species.

The diversity and size of the dataset make it particularly useful, as it covers a wide range of ape species and poses, making it particularly suitable for training off-the-shelf pose estimation networks or for contributing to the training of a large foundational pose estimation model. In conjunction with new tools focused on extracting behavioral dynamics from pose, this dataset can be especially useful in understanding the basis of ape behaviors using pose.

Since the dataset provided is the first large, public dataset of its kind exclusively for ape species, more details should be provided on how the data were annotated, as well as summaries of the dataset statistics. In addition, the authors should provide the full list of hyperparameters for each model that was used for evaluation (e.g., mmpose config files, textual descriptions of augmentation/optimization parameters).

Overall this work is a terrific contribution to the field and is likely to have a significant impact on both computer vision and animal behavior.

Strengths:<br /> - Open source dataset with excellent annotations on the format, as well as example code provided for working with it.<br /> - Properties of the dataset are mostly well described.<br /> - Comparison to pose estimation models trained on humans vs monkeys, finding that models trained on human data generalized better to apes than the ones trained on monkeys, in accordance with phylogenetic similarity. This provides evidence for an important consideration in the field: how well can we expect pose estimation models to generalize to new species when using data from closely or distantly related ones?<br /> - Sample efficiency experiments reflect an important property of pose estimation systems, which indicates how much data would be necessary to generate similar datasets in other species, as well as how much data may be required for fine-tuning these types of models (also characterized via ablation experiments where some species are left out).<br /> - The sample efficiency experiments also reveal important insights about scaling properties of different model architectures, finding that HRNet saturates in performance improvements as a function of dataset size sooner than other architectures like CPMs (even though HRNets still perform better overall).

Weaknesses:<br /> - More details on training hyperparameters used (preferably full config if trained via mmpose).<br /> - Should include dataset datasheet, as described in Gebru et al 2021 (arXiv:1803.09010).<br /> - Should include crowdsourced annotation datasheet, as described in Diaz et al 2022 (arXiv:2206.08931). Alternatively, the specific instructions that were provided to Hive/annotators would be highly relevant to convey what annotation protocols were employed here.<br /> - Should include model cards, as described in Mitchell et al (arXiv:1810.03993).<br /> - It would be useful to include more information on the source of the data as they are collected from many different sites and from many different individuals, some of which may introduce structural biases such as lighting conditions due to geography and time of year.<br /> - Is there a reason not to use OKS? This incorporates several factors such as landmark visibility, scale, and landmark type-specific annotation variability as in Ronchi & Perona 2017 (arXiv:1707.05388). The latter (variability) could use the human pose values (for landmarks types that are shared), the least variable keypoint class in humans (eyes) as a conservative estimate of accuracy, or leverage a unique aspect of this work (crowdsourced annotations) which affords the ability to estimate these values empirically.<br /> - A reporting of the scales present in the dataset would be useful (e.g., histogram of unnormalized bounding boxes) and would align well with existing pose dataset papers such as MS-COCO (arXiv:1405.0312) which reports the distribution of instance sizes and instance density per image.

Reviewer #2 (Public Review):

The authors present the OpenApePose database constituting a collection of over 70000 ape images which will be important for many applications within primatology and the behavioural sciences. The authors have also rigorously tested the utility of this database in comparison to available Pose image databases for monkeys and humans to clearly demonstrate its solid potential. However, the variation in the database with regards to individuals, background, source/setting is not clearly articulated and would be beneficial information for those wishing to make use of this resource in the future. At present, there is also a lack of clarity as to how this image database can be extrapolated to aid video data analyses which would be highly beneficial as well.

I have two major concerns with regard to the manuscript as it currently stands which I think if addressed would aid the clarity and utility of this database for readers.

1. Human annotators are mentioned as doing the 16 landmarks manually for all images but there is no assessment of inter-observer reliability or the such. I think something to this end is currently missing, along with how many annotators there were. This will be essential for others to know who may want to use this database in the future.

Relevant to this comment, in your description of the database, a table or such could be included, providing the number of images from each source/setting per species and/or number of individuals. Something to give a brief overview of the variation beyond species. (subspecies would also be of benefit for example).

2. You mention around line 195 that you used a specific function for splitting up the dataset into training, validation, and test but there is no information given as to whether this was simply random or if an attempt to balance across species, individuals, background/source was made. I would actually think that a balanced approach would be more appropriate/useful here so whether or not this was done, and the reasoning behind that must be justified.

This is especially relevant given that in one test you report balancing across species (for the sample size subsampling procedure).

And another perhaps major concern that I think should also be addressed somewhere is the fact that this is an image database tested on images while the abstract and manuscript mention the importance of pose estimation for video datasets, yet the current manuscript does not provide any clear test of video datasets nor engage with the practicalities associated with using this image-based database for applications to video datasets. Somewhere this needs to be added to clarify its practical utility.

Reviewer #1 (Public Review):

In their manuscript entitled, "Reward contingency gates selective cholinergic suppression of amygdala neurons," Kimchi and colleagues explore the engagement and consequences of acetylcholine (ACh) signaling in the basolateral amygdala (BLA) using a number of sophisticated methodological approaches.

Perhaps the most compelling new idea in this manuscript is that ACh may have different effects on network activity in the BLA, a conclusion based on the measurement of equivalent photo-stimulated ACh levels in BLA during rewarded vs. unrewarded lick bouts despite increased licking/consumption in the rewarded bouts. The authors hypothesize that, "this could suggest that reward associations may gate post-synaptic responses to photostimulation." The electrophysiological data showing that overall firing of BLA neurons during licking was higher as a result of photostimulation during unreinforced, and lower as a result of photostimulation during reinforced, sessions is intriguing in this context, as is the contrast with the overall ACh-mediated stimulation of firing in dorsomedial prefrontal cortex. The ex-vivo data presented showing that ACh depresses BLA neuron activity via muscarinic ACh receptors on glutamate neurons and nicotinic ACh receptors on GABA neurons, along with previous data in the field suggesting that ACh has divergent effects on neuronal firing rate depending on whether baseline firing is low (tonic) or high (phasic), provides intriguing hints as to the role of ACh in state-dependent modulation of BLA activity.

One of the primary questions that came up while reading this manuscript was what behavioral domains were being measured with the "windows of opportunity" task. As noted by the authors, the cholinergic system has been implicated in arousal, reward thresholds, motivation and many other behaviors that might alter performance in this task, complicating interpretation of the data presented. In addition, some additional details of the task are needed for the field to be able to replicate these experiments.

Reviewer #2 (Public Review):

Kimchi et al. examined the role of cholinergic inputs to the amygdala in regulating reward-seeking behavior. To investigate this, the authors developed a head-fixed behavioral task where animals were trained to lick at random intervals, with some of these responses being reinforced ("windows of opportunity") as opposed to control epochs when no reward was delivered.

The authors conducted in vivo optogenetic stimulation of basal forebrain cholinergic neurons and discovered that a 2-second optical stimulation of these neurons encouraged licking behavior when followed by reward delivery. This was in comparison to time epochs where no reward was delivered or compared to control mice only expressing EYFP. However, it remained unclear how many trials were required for this effect to manifest.

Furthermore, they demonstrated that the stimulation of basal forebrain cholinergic neurons did not induce real-time place preference or affect locomotion. The reward-driven licking behavior was also mitigated by systemic cholinergic receptor antagonists.<br /> Next, the authors observed the bulk calcium dynamics from these neurons in a version of the task where an auditory cue predicted reward availability. They found strong calcium signals when mice were licking and when the tone was present, but also reported signals when mice were spontaneously licking.

By injecting a genetically encoded Acetylcholine (Ach) sensor directly into the Basolateral Amygdala (BLA), they showed that Ach signals were present when mice were engaged in licking, both during reward availability and for non-rewarded licks. Photostimulation of Ach terminals directly in the BLA increased licking behavior when a reward was available.

Finally, using in vivo and ex vivo physiology, they demonstrated that Ach signaling influences the electrophysiological dynamics in the BLA. This may help clarify some of the postsynaptic responses triggered by this neuromodulator.

Strengths of the paper:

1. The experiments were well-executed and sufficiently powered, with most statistics being correctly reported.<br /> 2. The paper is a technical tour de force, employing fiber photometry, in vivo and ex vivo electrophysiology, optogenetics, and behavioral approaches.<br /> 3. Robust effects were observed in most of the experiments.<br /> Weaknesses:<br /> 1. The experimental design varies slightly across each behavioral experiment, making it difficult to directly compare one effect to another.<br /> 2. The paper doesn't include data showing the precise location for the Ach recordings. As a result, it is unclear whether these signals are specific to the BLA, or whether they might also be coming from neighboring regions.

Reviewer #3 (Public Review):

This important manuscript investigates the role of basal forebrain cholinergic interneurons in conditioned responding by measuring the licking behaviour of head-fixed mice during photostimulation of the aforementioned neurons. Licking is found to increase only during windows when licking is rewarded, and similar behaviour is observed when terminals are stimulated in basolateral amygdala, then several more experiments are conducted to determine the behavioural and anatomical specificity of the effect. The findings are solid, particularly those relating to the recordings, although the interpretation of the behavioural findings is still somewhat unclear.

Strengths<br /> • The manuscript is beautifully written and structured. I found it really easy to follow and felt that the authors did an exceptional job of walking me through each experiment that they completed, the rationale for it, and what they found.<br /> • The question of the function of basal forebrain cholinergics is an interesting one and a somewhat understudied question, so the study is timely and on an interesting topic.<br /> • The experiments are well-designed and the findings are novel. There are a number of important control experiments performed to determine that the observed effects were not due to locomotor activity and that stimulating basal forebrain ACh neurons is not inherently reinforcing.<br /> • The discussion is really nice - covering important topics such as potential interactions with dopamine, the potential anatomical specificity of the effects observed, and the possibility that projections other than those studied here might mediate effects, among other things.

Weaknesses<br /> • Although very clearly written and set out, I found myself confused by the behavioural findings and their interpretation. Mainly this was because photostimulation only increased licking during the window of opportunity, which is not signalled by any discrete stimulus, which means that the only signal that the animal receives to determine that they are within the reward window is them receiving the reward. Therefore, the only time within this window that licking could be increased is post-reward (otherwise the reward window is identical to a non-rewarded window) and it is not clear to me what this increase in post-award licking might mean? In fact, this time post-award is actually the time the animal is most certain to not receive another reward for a few seconds, meaning that licking at this time is not a useful behaviour and therefore it is difficult to interpret what it means to artificially increase licking at this time. I think it would probably have been less confusing for the authors to study a paradigm in which animals develop a conditioned response that is unsignaled by discrete stimuli and then to inhibit basal forebrain ACh prior to that response.<br /> • I should also note that the authors state (Lines 249-251) that stimulation increases responding prior to reinforcer delivery, but I couldn't find evidence for this, and it seems counterintuitive to me that it would do so because then how would the animals discriminate the window of opportunity from a non-rewarded window? Perhaps I misunderstood something, but I found this confusing.<br /> • I do not think the behaviour in this task can be classed as operant - it is still a good task and still fine for detecting conditioned responding, but it cannot determine whether the responding is governed by a response-outcome association in the absence of a stimulus-outcome association (with stimuli being the licking spout, other facets of the behavioural context etc) through bidirectionality or omission, as would be required to demonstrate its operant nature.<br /> • I was confused by the pupil dilation data in Figure S4 as the authors seem to want to argue that this effect, although specific to the rewarded window as licking is, is independent of the licking behaviour as it develops more slowly than the behaviour (Lines 201-202). I was curious as to how the authors interpret these data then? Does it indicate that stimulating basal forebrain ACh interneurons does both things (i.e. increases arousal AND conditioned responding in the absence of discrete stimuli) but that the two things are independent of each other?<br /> • The authors refer to the dorsal medial prefrontal cortex in mice, which from the methods appears to be the prelimbic region. My understanding is that dmPFC has fallen out of favour for use in mice as it is not homologous to the same region in primates and can be confusing for this reason.

Reviewer #1 (Public Review):

The manuscript by Hage et al. presents interesting results from a foraging behavior in Marmosets that explores the interactions of saccade and lick vigor with pupil dilation and performance as well as a marginal value theory and foraging theory-inspired value-based decision-making model thereof. The results are generally robust and carefully presented and analyses, particularly of vigor, are carefully executed.

The authors constructed a model that makes two predictions: "In summary, this simple theory made two sets of predictions: in response to an increased cost of harvest, one should work longer, but move with reduced vigor. In response to an increased reward value, as in hunger, one should also work longer, but now move with increased vigor." Their behavioral data meets these predictions. It is not clear if the model was designed and tweaked in order to make those predictions and match the data, or derived from principles. Furthermore, it is not clear what other models would make similar predictions. It would help to assess what is predicted by other simple models, as well as different functional forms for the effort costs in their model.

Line 37 page 6; the link of pupil to NE/LC is tenuous. Other modulators systems and circuits may be equally important and should be mentioned (e.g. Reimer, Jacob, Matthew J. McGinley, Yang Liu, Charles Rodenkirch, Qi Wang, David A. McCormick, and Andreas S. Tolias. "Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex." Nature communications 7, no. 1 (2016): 13289.)<br /> Line 35 page 6-page 7 line 10 emphasizes a cognitive interpretation of the pupil dilations they is emphasized, in relation to effort costs. But there are also concomitant more vigorous movements. Could all of their pupil results be explained by motor correlates? This should be tested and ruled out before making cognitive interpretations.<br /> Page 7, line 37-42: How would the model need to be modified in order to account for this discrepancy with the data? Ideally, this would be tested.<br /> Page 9, line 2-11: In this section, it would help to also consider 'baseline' pupil size (in between trials). This would give a signal that is not 'contaminated' by movements, and may reflect control state. Relatedly, changes in control state may impact and confound the movement-related dilation magnitudes due to e.g. floor and ceiling effects on pupil size, which has a strong tendency for reversion to the mean.<br /> Page 10 line 21-32 presents a dated view of pupil that has/had little data supporting it. They should mention other neuromodulators (Reimer et al., 2016) and related interpretations.<br /> The hunger-related and reward-size related analyses are both heavily confounded since they were not manipulated directly and could co-vary with many latent factors. For example, why might a given Marmoset be lower weight on a given day? Could it affect sleep, stress, activity, or other factors during the preceding 24 hours? If so, could these other variables be driving the results that are interpreted as 'hunger?' Relatedly, since the reward size is determined by the animals behavior on each trial (how much they worked), factors (internal brain state, external noises, etc.) that alter how much they worked will influence the subsequent reward size. Therefore interpretations about reward expectancy are confounded. Both of these issues should be discussed and manipulations of them (different feeding schedules and reward size-work functions proposed, respectively.<br /> A major issue is a lack of alternative models. The authors seem to have constructed a particular model designed to capture the behavioral patterns they observed in the data. The model fails in some instances, as they point out. Even more importantly, there are no results or discussion about how other plausible models could or couldn't fit the data. The lack of model comparisons makes it difficult to interpret the conclusions or put the results in a broader context.

Reviewer #2 (Public Review):

Hage et al examine how the foraging behavior of marmoset monkeys in a laboratory setting systematically takes into account the reward value and anticipated effort cost associated with the acquisition and consumption of food. In an interesting comprehensive framework, the authors study how experimental and natural variation of these factors affect both the decisions and actions necessary to gather and accumulate food, as well as the actions necessary to consume the food.

The manuscript proposes a computational model of how the monkeys may guide all these aspects of behavior, by maximizing a food capture rate that trades off the food that can be gathered with the effort and duration of the underlying actions. They use this model to derive qualitative predictions for how monkeys should react to an increase in the effort associated with food consumption: Monkeys should work longer before deciding to consume the accumulated food, but should move more slowly. The model also predicts that monkeys should show a different reaction to an increase in reward value of the food, also working longer but moving faster. The authors test these predictions in an interesting experimental setup that requires monkeys to collect small increments of food rewards for successful eye movements to targets. The monkeys can decide freely when to interrupt work and consume the accumulated food, and the authors measure the speed of the eye movements involved in the food acquisition as well as the tongue movements involved in the food consumption.

By and large, the behavioral findings fall in line with the qualitative model predictions: When the effort involved in food consumption increases, monkeys collect more food before deciding to consume it, and they move slower both during food acquisition and food consumption. In a second test, the authors approximate the effects of reward value of the food at stake, by comparing monkey behavior during different days with natural variations in body weight. These quasi-experimental increases in the reward value of food also lead to longer work times before consumption, but to faster movements during food consumption. Finally, the authors show that these effects correlate with pupil size, with pupils dilating more for low-effort foraging actions with increased saccade speed and decreased work duration. The authors conclude that the effort associated with anticipated actions can lead to changes in global brain state that simultaneously affect decisions and action vigor.

The paper proposes an interesting model for how one unified action policy may simultaneously affect multiple types of decisions and movements involved in foraging. The methods employed to measure behavior and test these predictions are generally sound, and the paper is well written. While the model and paper in their present form can clearly inspire researchers to consider this integrated perspective, and trigger further research employing such a framework, there are some conceptual and methodical shortcomings that reduce the conclusiveness of the results and the usefulness of the proposed model.

(1) The model proposed in the paper takes a very specific functional form that is neither motivated by the previous literature nor particularly useful for indexing the behavioral tendencies of individual monkeys (or of the same monkey in different contexts). For example, while it is clear that the saccade effort cost will need to outgrow the increase in the utility of the accumulated food for the monkey to start feeding, it is unclear why this needs to be modeled with a fixed quadratic exponent on the number of saccades? Similarly, why do licks deplete the food stash with the specific rate hard-coded in the model? Finally, the proportion of successful saccades and lick events is assumed to be fixed, even though it very likely to be directly influenced by movement speed (speed-accuracy trade-off), which is also contained in the model. It would strongly increase the plausibility and potential impact of the model if the authors could clearly state where these hard-coded model terms come from. Ideally, they would formulate the model in more general terms and also consider other functional forms, as briefly suggested in the discussion. This latter point would be particularly important since not all model predictions were actually borne out in the data.

(2) The authors derive qualitative predictions, by simulating their model with apparently arbitrary parameters. They then test these qualitative predictions with conventional statistics (e.g., t-tests of whether monkeys lick more for high vs low effort trials). The reader wonders why the authors chose this route, instead of formulating their model with flexible parameters and then fitting these to data. This would allow them (and future researchers) to test their model not just qualitatively but also quantitatively, and to compare the plausibility of different functional forms. The authors certainly have enough data and power to do this, given the vast number of sessions the monkey completed.

(3) The effort manipulation chosen by the authors (distance of food tube) goes hand in hand with a greater need for precision since the monkey's tongue needs to hit an opening of similar size, but now located at a greater distance. This raises the question of whether the monkeys moved slower to enhance its chance of collecting the food (in line with a speed-accuracy trade off). The manuscript would benefit from an explicit test of this possibility, for example by reporting whether for each of the two conditions, the speed of tongue movements on a trial-by-trial basis predicts the probability of food collection? At the very least, the manuscript should explicitly discuss this issue and how it affects the certainty with which effects of tube distance can be linked to anticipated effort cost alone.

(4) The authors report most of the effects on the different measures (work duration, movement vigor, lick vigor, etc) in separate analyses. However, their model predicts that all of these measures result from the same action policy (maximization of the capture rate) and should therefore be related on a trial-by-trial basis. This is so far hardly tested in the presented analyses (with the exception of the pupil correlations in Figure 5). The model's assumed action policy would appear more plausible if the authors could demonstrate these trial-by-trial interrelations with some tests of association (e.g., correlations/regressions as already done for pupil measures in Figure 5) or possibly with dimensionality reduction of the multivariate data.

(5) The manuscript measures pupil dilation in a time period ranging from -250ms before to 250 ms after saccade onset. However, the pupil changes strongly during saccade execution relative to the preceding baseline, leaving doubts as to whether the aggregated measure blurs several interesting and potentially different effects. It would be more conclusive if the manuscript could report the analyses of pupil size separately for a period prior to saccade onset and during/after the saccade.

Reviewer #1 (Public Review):

This manuscript by He et al. explores the molecular basis of the different stinging behaviors of two related anemones. The freshwater Nematostella which only stings when a food stimulus is presented with mechanical stimulation and the saltwater Exaiptasia which stings in response to mechanical stimuli. The authors had previously shown that Nematostella stinging is calcium-dependent and mediated by a voltage-gated calcium channel (VGCC) with very pronounced voltage-dependent inactivation, which gets removed upon hyperpolarization produced by taste receptors.

In this manuscript, they show that Exaiptacia and Nematostella differing stinging behavior is near optimal, according to their ecological niche, and conforms to predictions from a Markov decision model.

It is also shown that Exaiptacia stinging is also calcium-dependent, but the calcium channel responsible is much less inactivated at resting potential and can readily induce nematocyte discharge only in the presence of mechanical stimulation. To this end, the authors record calcium currents from Exaipacia nematocysts and discover that the VGCCs in this anemone are not strongly inactivated and thus are easily activated by mechanical stimuli-induced depolarization accounting for the different stinging behavior between species. The authors further explore the role of the auxiliary beta subunit in the modulation of VGCC inactivation and show that different n-terminal splice variants in Exaiptacia produce strong and weak voltage-dependent inactivation.

The manuscript is clear and well-written and the conclusions are in general supported by the experiments and analysis. The findings are very relevant to increase our understanding of the molecular basis of non-neural behavior and its evolutionary basis. This manuscript should be of general interest to biologists as well as to more specialized fields such as ion channel biophysics and physiology.

Some findings need to be clarified and perhaps additional experiments performed.

1) The authors identify by sequencing that the Exaiptacia Cav is a P-type channel (cacna1a). However, the biophysical properties of the nematocyte channel are different from mammalian P-type channels. The cnidarian channel inactivation is exceedingly rapid and activation happens at relatively low voltages. These substantial differences should be mentioned and commented on.

2) The currents from Nematostella in Figure 3d seem to be poorly voltage-clamped. Poor voltage-clamp is also evident in the sudden increase of conductance in Figure 3C and might contribute to incorrect estimation of voltage dependence of activation and if present in inactivation experiments, also to incorrect estimation of the inactivation voltage range. This problem should be reassessed with new data.

3) While co-expression of the mouse Cav channel with the beta1 isoform from Exaiptacia indeed shifts inactivation to more negative voltages, it does not recapitulate the phenotype of the more inactivated Ca-currents in nematocytes (compare Figures 4d and 5d). It should be explained if this might be due to the use of a mammalian alpha subunit. Related to this, did the authors clone the alpha subunit from Exaiptacia? Using this to characterize the effect of beta subunits on inactivation might be more accurate.

4) The in situ shown in Figure 4b are difficult to follow for a non-expert in cnidarian anatomy. Some guidance should be provided to understand the structures. Also, for the left panels, is the larger panel the two-channel image? If so, blue would indicate co-localization of the two isoforms and there seems to be a red mark in the same nematocyte.

Reviewer #2 (Public Review):

This manuscript links the distinctive stinging behavior of sea anemones in different ecological niches to varying inactivation properties of voltage-gated calcium channels that are conferred by the identity of auxiliary Cavbeta subunits. Previous work from the Bellono lab established that the burrowing anemone, Nematostella vectensis, expresses a CaV channel that is strongly inactivated at rest which requires a simultaneous delivery of prey extract and touch to elicit a stinging response, reflecting a precise stinging control adapted for predation. They show here that by contrast, the anemone Exaiptasia diaphana which inhabits exposed environments, indiscriminately stings for defense even in the absence of prey chemicals, and that this is enabled by the expression of a CaVbeta splice variant that confers weak inactivation. They further use the heterologous expression of CaV channels with wild type and chimeric anemone Cavbeta subunits to infer that the variable N-termini are important determinants of Cav channel inactivation properties.

1. The authors found that Exaiptasia nematocytes could be characterized by two distinct inactivation phenotypes: (1) nematocytes with low-voltage threshold inactivation similar to that of Nematostella (Vi1/2 = ~ -85mV); and (2) a distinct population with weak, high-voltage threshold inactivation (Vi1/2 = ~ -48mV). What were the relative fractions of low-voltage and high-voltage nematocytes? Do the low-voltage Exaiptasia nematocytes behave similarly to Nematostella nematocytes with respect to requiring both prey extract and touch to discharge?

2. The authors state in Fig 3 legend and in the results that Exaiptasia nematocyte voltage-gated Ca2+ currents have weak inactivation compared with Nematostella. This description is imprecise and inaccurate. Figure 3 in fact shows that Exaiptasia nematocyte voltage-gated Ca2+ currents display a faster rate of inactivation compared to Nematostella Ca2+ currents. A sub-population of Exaiptasia nematocytes does display less resting state (or steady-state) inactivation compared to Nematostella Ca2+ currents. The authors need to be more accurate and qualify what type of inactivation property they are talking about.

3. In a similar vein, the authors need to be more accurate when referring to 'rat beta' used in heterologous expression experiments. It should be made explicit throughout the manuscript that the rat beta isoform used is rat beta2a. Among the distinct beta isoforms, beta2a is unique in being palmitoylated at the N-terminus which confers a characteristic slow rate of inactivation and a right-shifted voltage-dependence of steady-state inactivation consistent with the data shown in Fig. 4D. Almost all other rat beta isoforms do not have these properties.

4. The profiling of the impact of different Cnidarian Cavbeta subunits on reconstituted Ca2+ channel current waveforms is nice (Fig 5 and Fig 5S1). The N-terminus sequence of EdCaVβ2 is different from palmitoylated rat beta2a, though both have similar properties in showing slow inactivation and a right-shifted voltage-dependence of steady-state inactivation. Does EdCaVβ2 target autonomously the plasma membrane when expressed in cells? If so, this would reconcile with what was previously known and provide a rational explanation for the observed functional impact of the distinct Cavbetas.

Reviewer #3 (Public Review):

Summary:<br /> The present article attempts to answer both the ultimate question of why different stinging behaviours have evolved in Cnidiarians with different ecological niches and shed light on the proximate question of which electro-physiological mechanisms underlie these distinct behaviours.

Account of major methods and results:<br /> In the first part of the paper, the authors try to answer the ultimate question of why distinct dependencies of the sting response on internal starvation levels have evolved. The premise of the article that Exaiptasia's nematocyte discharge is independent of the presence of prey (Artemia nauplii) as compared to Nematostella's significant dependence of the discharge on the presence of actual prey, is shown be a robust phenomenon justified by the data in Figure 1.

The hypothesis that defensive vs. predatory stinging leads to different nematocyte discharge behaviours is analysed in mathematical models based on the suitable framework of optimal control/decision theory. By assuming functional relations between the:<br /> 1) cost of a full nematocyte discharge and the starvation level.<br /> 2) probability of successful predation/avoidance on the discharge level.<br /> 3) desirability/reward of the reached nutritional state.

Based on these assumptions of environmental and internal influences, the optimal choice of attack intensity is calculated using Bellman's equation for this problem. The model predictions are validated using counted nematocytes on a coverslip. The scaling of normalised nematocyte discharge numbers with scaled starvation time is qualitatively comparable to what is predicted from the models. The abundance of nematocytes in the tentacles was, on the other hand, independent of the starvation state of the animals.

Next, the authors turn to investigate the proximate cause of the differential stinging behaviour. The authors have previously reported convincing evidence that a strongly inactivating Cav2.1 channel ortholog (nCav) is used by Nematostella to prevent stinging in the absence of prey (Weir et al. 2020). This inactivation is released by hyperpolarising sensory inputs signalling the presence of prey. In this article, it is clearly shown by blocking respective currents that Exaiptasia, too, relies on extracellular Ca2+ influx to initiate stinging. Patch clamp data of the involved currents is provided in support. However, the authors find that in addition to the nCav with a low-inactivation threshold, Exaiptasia has a splice variant with a higher inactivation threshold expressed (Figure 3D).

The authors hypothesise that it is this high-threshold nCav channel population that amplifies any voltage depolarisation to release a sting irrespective of the presence of prey signals. They found that the β subunit that is responsible for Nematostella's unusually low inactivation threshold exists in Exaiptasia as two alternative splice isoforms. These N-terminus variants also showed the greatest variation in a phylogenetic comparison (Figure 5), rendering it a candidate target for mutations causing variation in stinging responses.

Appraisal of methodology in support of the conclusions:<br /> The authors base their inference on a normative model that yields quantitative predictions which is an exciting and challenging approach. The authors take care in stating the model assumptions as well as showing that the data indeed does not contradict their model predictions. The interesting comparative nature of the modelling part of the study is complicated by slightly different cost assumptions for the two scenarios. Hence, Figure 2 needs to be carefully digested by readers.

It would be even more prudent to analyse the same set of cost-of-discharge vs. starvation scenarios for both species. Specifically, for Nematostella the complete cost-of-discharge vs starvation-state curves as for Exaiptasia (Figure 2E, example 2-4) could be used. It is likely that the differential effect size of Nematostella and Exaiptasia behaviour is the strongest if only the flat cost-of-discharge vs starvation is used (Figure 2A) for Nematostella. But as a worst-case comparison the other curves, where the cost to the animal scales with starvation would be a good comparison. This could help the reader to understand when the different prediction of Nematostella's behaviour breaks down. In addition, this minor change could shed light on broader topics like common trade-offs in pursuit predation.

The qualitatively similar scaling of the model-derived relation between starvation and sting intensity with the counted nematocytes for different feeding pauses is evidence that feeding has indeed been optimised for the two distinct ecological niches.<br /> To prove that Exaiptasia uses a similar Ca2+ channel ortholog as well as a different splice variant, the authors employed both clean electrophysiological characterisaiton (Figure 3) as well as transcriptomics data (Figure 4S1).

To strengthen the authors' hypothesis that variation in the N-termini leads to changes in Ca2+ channel inactivation and hence altered stinging, the response sequence variability of 6 Cnidaria was analysed.

Additional context:<br /> Although, the present article focuses on nematocytes alone, currently, there has been a refocus in neurobiology on the nervous systems of more basal metazoans, which received much attention already in the works of Romanes (1885). In part, this is driven by the goal to understand the early evolution of nervous systems. Cnidarians and Ctenophors are exciting model organisms in this venture. This will hopefully be accompanied by more comparative studies like the present one. Some of the recent literature also uses computational models to understand mechanisms of motor behaviour using full-body simulations (Pallasdies et al. 2019; Wang et al. 2023), which can be thought of as complementary to the normative modelling provided by the authors.

Comparative studies of recent Cnidarians, such as the present article, can shed light on speculative ideas on the origin of nervous systems (Jékely, Keijzer, and Godfrey-Smith 2015). During a time (the Ediacarium/Cambrium transition) that has seen the genesis of complex trophic foodwebs with preditor-prey interaction, symbioses, but also an increase of body sizes and shapes, multiple ultimate causes can be envisioned that drove the increase in behavioural complexity. The authors show that not all of it needs to be implemented in dedicated nerve cells.

References:

Jékely, Gáspár, Fred Keijzer, and Peter Godfrey-Smith. 2015. "An Option Space for Early Neural Evolution." Philosophical Transactions of the Royal Society B: Biological Sciences 370 (December): 20150181. https://doi.org/10.1098/rstb.2015.0181.

Pallasdies, Fabian, Sven Goedeke, Wilhelm Braun, and Raoul-Martin Memmesheimer. 2019. "From Single Neurons to Behavior in the Jellyfish Aurelia Aurita." eLife 8 (December). https://doi.org/10.7554/elife.50084.

Romanes, G. J. 1885. Jelly-Fish, Star-Fish and Sea-Urchins: Being a Research on Primitive Nervous Systems. Appleton.

Wang, Hengji, Joshua Swore, Shashank Sharma, John R. Szymanski, Rafael Yuste, Thomas L. Daniel, Michael Regnier, Martha M. Bosma, and Adrienne L. Fairhall. 2023. "A Complete Biomechanical Model of hydra Contractile Behaviors, from Neural Drive to Muscle to Movement." Proceedings of the National Academy of Sciences 120 (March). https://doi.org/10.1073/pnas.2210439120.

Weir, Keiko, Christophe Dupre, Lena van Giesen, Amy S-Y Lee, and Nicholas W Bellono. 2020. "A Molecular Filter for the Cnidarian Stinging Response." eLife 9 (May). https://doi.org/10.7554/elife.57578.

Reviewer #1 (Public Review):

In this manuscript, the authors explore the effects of DNA methylation on the strength of regulatory activity using massively parallel reporter assays in cell lines on a genome-wide level. This is a follow-up of their first paper from 2018 that describes this method for the first time. In addition to adding more in-depth information on sequences that are explored by many researchers using two main methods, reduced bisulfite sequencing and sites represented on the Illumina EPIC array, they now show also that DNA methylation can influence changes in regulatory activity following a specific stimulation, even in absence of baseline effects of DNA methylation on activity. In this manuscript, the authors explore the effects of DNA methylation on the response to Interferon alpha (INFA) and a glucocorticoid receptor agonist (dexamethasone). The authors validate their baseline findings using additional datasets, including RNAseq data, and show convergences across two cell lines. The authors then map the methylation x environmental challenge (IFNA and dex) sequences identified in vitro to explore whether their methylation status is also predictive of regulatory activity in vivo. This is very convincingly shown for INFA response sequences, where baseline methylation is predictive of the transcriptional response to flu infection in human macrophages, an infection that triggers the INF pathways. The extension of the functional validity of the dex-response altering sequences is less convincing. Sequences altering the response to glucocorticoids, however, were not enriched in DNA methylation sites associated with exposure to early adversity. The authors interpret that "they are not links on the causal pathway between early life disadvantage and later life health outcomes, but rather passive biomarkers". However, this approach does not seem an optimal model to explore this relationship in vivo. This is because exposure to early adversity and its consequences is not directly correlated with glucocorticoid release and changes in DNA methylation levels following early adversity could be related to many physiological mechanisms, and overall, large datasets and meta-analyses do not show robust associations of exposure to early adversity and DNA methylation changes. Here, other datasets, such as from Cushing patients may be of more interest.

Overall, the authors provide a great resource of DNA methylation-sensitive enhancers that can now be used for functional interpretation of large-scale datasets (that are widely generated in the research community), given the focus on sites included in RBSS and the Illumina EPIC array. In addition, their data lends support that differences in DNA methylation can alter responses to environmental stimuli and thus of the possibility that environmental exposures that alter DNS methylation can also alter the subsequent response to this exposure, in line with the theory of epigenetic embedding of prior stimuli/experiences. The conclusions related to the early adversity data should be reconsidered in light of the comments above.

Reviewer #2 (Public Review):

This work presents a remarkably extensive set of experiments, assaying the interaction between methylation and expression across most CpG positions in the genome in two cell types. To this end, the authors use mSTARR-seq, a high-throughput method, which they have previously developed, where sequences are tested for their regulatory activity in two conditions (methylated and unmethylated) using a reporter gene. The authors use these data to study two aspects of DNA methylation: 1. Its effect on expression, and 2. Its interaction with the environment. Overall, they identify a small number of 600 bp windows that show regulatory potential, and a relatively large fraction of these show an effect of methylation on expression. In addition, the authors find regions exhibiting methylation-dependent responses to two environmental stimuli (interferon alpha and glucocorticoid dexamethasone).

The questions the authors address represent some of the most central in functional genomics, and the method utilized is currently the best method to do so. The scope of this study is very impressive and I am certain that these data will become an important resource for the community. The authors are also able to report several important findings, including that pre-existing DNA methylation patterns can influence the response to subsequent environmental exposures.

The main weaknesses of the study are: 1. The large number of regions tested seems to have come at the expense of the depth of coverage per region (1 DNA read per region per replicate). I have not been convinced that the study has sufficient statistical power to detect regulatory activity, and differential regulatory activity to the extent needed. This is likely reflected in the extremely low number of regions showing significant activity. 2. Due to the position of the tested sequence at the 3' end of the construct, the mSTARR-seq approach cannot detect the effect of methylation on promoter activity, which is perhaps the most central role of methylation in gene regulation, and where the link between methylation and expression is the strongest. This limitation is evident in Fig. 1C and Figure 1-figure supplement 5C, where even active promoters have activity lower than 1. Considering these two points, I suspect that most effects of methylation on expression have been missed.

Overall, the combination of an extensive resource addressing key questions in functional genomics, together with the findings regarding the relationship between methylation and environmental stimuli makes this a key study in the field of DNA methylation.

Reviewer #1 (Public Review):

The studies by Hwangbo et al. diligently attempt to account for many of the typically neglected dietary and non-dietary factors.

Strengths:

• Work addresses many potential artifacts of dietary (e.g., dehydration stress, macronutrient ratios, and protein source) and non-dietary (e.g., leaky expression of S106-GAL4) manipulations-important factors that are too often overlooked.<br /> • Balanced and complementary behavioral, molecular, and bioinformatic experiments<br /> • Show necessity of proteostatic subunits in the fat body for DR-mediated longevity. The findings in the current manuscript lay the ground for future studies that test sufficiency of fat body prosβ3 and rpn7, or necessity of other proteostatic genes in other tissues.

Weaknesses:

• Could the lack of DR response in clock mutants across dietary concentrations be simply because the clock mutants are better at compensatory feeding adjustments to dietary dilutions? If this were the case, there are two major implications to the authors' conclusions:<br /> a) The Clk mutants are differently responding to dietary dilutions, not to dietary restriction, per se.<br /> b) Nutritional intake was unaffected by the dietary manipulations. If the changes in fat body proteostasis and lifespan were due to nourishment, it would be expected that the physiology and lifespan do not change.<br /> Accurate measurements of food consumption and the resulting protein intake could potentially clarify this critical question.

Reviewer #2 (Public Review):

Dietary restriction (DR) increases lifespan, an effect that has been consistently observed in several organisms, but we still lack a clear mechanism to explain this phenomenon. In this work, Hwangbo et al. revisited the role of the circadian clock in DR-mediated lifespan effects. They found that the increase in lifespan produced by DR is missing on a clock mutant, a clock dependency that is also observed at the level of nutrient-dependent egg laying. By conducting RNA-seq with an impressive temporal resolution, they showed that DR triggers an increment in the number of cycling genes expressed in the fat body, the fly functional analog of the mammalian liver. Interestingly, from these genes, a group of them are de novo daily expressed genes, meaning that their expression was not rhythmic under the control diet but appear rhythmically expressed under DR. Among those, genes encoding proteasome subunits are enriched. The authors finally showed that adult-specific knockdown of these genes in the fat body prevents the increase in lifespan under DR, further supporting a role of the proteasome in this process. Overall, the conclusions are mostly supported by the evidence presented, and the authors' discussion nicely frame their results with other research in the field.

Strengths:

- Many studies have limited their observations of DR on lifespan to a few dietary conditions which makes the reach of some previous conclusions somewhat limited. The dilution strategy that the authors used in this work provides a strong indication that the effect of DR on lifespan relies on clock expression regardless of the conditions used. Furthermore, the inclusion of the egg-laying assay is a good addition to support this hypothesis.<br /> - Because the strength of the rhythmicity statistics relies heavily on the number of data points collected, the temporal resolution used for the RNA-seq experiments (every 2 hrs per 48hrs) is remarkable. This allows exquisite dissection of the phase of rhythmic genes in different conditions. The dataset produced in this work might be of use to other groups interested in weighting the role of other represented gene clusters in DR.

Weaknesses:

I see only minor flaws in this work, that if addressed, might strengthen the authors' conclusions, particularly:

- The results of the lifespan assays are quite variable and in some instances contradictory (Fig. S8) across trials, possibly because there are other unaccounted variables we still do not understand. The fecundity assay, in contrast, seems to be a better readout (Fig. 2). Confirming at least the two genes picked for the study (Fig. 5) would be good support for the claim that the proteasome mediates the effects of DR.<br /> - According to the model, the acute effect of DR on gene expression is related to CLOCK protein function. However, I am not sure how this link was established. It is tempting to assume that CLOCK upstream is the reason for having an increase in rhythmic genes under DR, but the experiments did not test this. The tests conducted either assessed the role of clk or the effect of an impaired proteasome on DR-dependent extension of lifespan. Thus, it is difficult to assert the authors' claims on the link between CLK and the changes in cycling genes and to the proteasome upon DR.

Reviewer #3 (Public Review):

In this study, Hwangbo and co-workers investigate the extent to which the well-established life extending effects of DR rely on the molecular circadian clock and how the landscape of clock-controlled gene expression changes in the face of DR within the fat body of the fly, a tissue that performs the functions associate with both the liver and adipose tissue of mammals. The authors evidence that DR extends lifespan in a manner that depends on only one of the two major limbs of the fly's molecular circadian clock, namely the positive limb, that DR produces major changes in the identities of cycling clock output genes, and that genes related to the proteosome represent a major component of DR-induced transcript cycling. Though interesting, these conclusions are not strongly supported by the data and there are two major reasons for this. First, the authors rely on only one loss of function genotype each for the loss of positive and negative limb clock gene function. Second, though they wish to address the "circadian transcriptome" under normal and DR conditions, the authors conduct all their work under strong Light/Dark cycles, making it impossible to address circadian phenomena. These shortcomings are problematic in the extreme, as they leave open obvious alternative explanations for the results and fail to directly determine if the rhythmic expression, they observe are clock controlled or merely driven by the light/dark cycles, which themselves produce major effects on activity, feeding, etc., that may be responsible for differentially driving rhythmic transcripts under normal and DR conditions in the fat bodies.

Major Weakness One: The use of only genotype each for the loss of positive (Clk^JRK) and negative (Per^01) limb of the circadian represents a major challenge for a central conclusion of the study. Phenotypes caused by the loss of a single clock gene may be due to the loss of circadian timekeeping, or they may represent a pleiotropic effect of the loss of function mutant being used. There are multiple precedents for pleiotropic (non-circadian) effects of clock gene mutants. It is, therefore, possible that the differences in the extent of DR mediated life extension between Clk^JRK and Per^01 may not represent a difference between breaking the positive and negative limbs of the clock but may simply reflect a pleiotropic effect of the dominant negative Clk^JRK. This possibility is acknowledged by the authors (lines 343-344). This could be addressed quite easily by extending the analysis to other loss of function mutants, for example, tim01 for the negative limb and cyc01 for the positive. Given the central focus here on the "circadian transcriptome," leaving open this alternative explanation for Clk's role in DR induced life extension represents a major weakness of the study. Furthermore, given the fact that Clk^JRK appears to be short lived on most of the media tested in the study, is it really surprising or informative that they would display lower life extension under DR?

Major Weakness Two: The authors have not established that any of cycling transcripts they have detected in the fat body under normal and DR conditions are driven by the circadian clock. This is because: 1.) they have conducted their transcriptomic analysis on cells taken from flies entrained to light dark cycles, which can themselves drive daily changes in expression levels and 2.) they have not shown that the cycling measured on normal diet or DR conditions depends on a functional circadian clock. The "significant reorganization of the circadian transcriptome" is presented as a major conclusion of this study, but the authors have not addressed circadian control of transcription at all here, either by an examination of transcription under free-running conditions and/or in loss of function clock mutants.

In addition, there is a logical gap in this study. The authors have shown that DR produces less life extension in Clk^JRK mutants than Per^01 or wild-type controls. They then show that DR produces changes in the rhythmic transcriptome when flies are place on DR. The central model presented in Fig. 6 shows/concludes that CLK drives increases in proteome-related transcript rhythms under DR. This conclusion could have been directly tested by asking if the changes in rhythmic gene expression induced by DR are gone the loss of function Clk mutants, or if the transcriptomic landscapes fail to differ between feeding conditions in these mutants.

In conclusion, the study falls far short of directly testing the ideas it puts forth, greatly limiting its impact and interest.

Reviewer #1 (Public Review):

Ciampa et al. investigated the role of the hypoxia-inducible factor 1 (HIF-1) pathway in placental aging. They performed transcriptomic analysis of prior data of placental gene expression over serial timepoints throughout gestation in a mouse model and identified increased expression of senescence and HIF-1 pathways and decreased expression of cell cycle and mitochondrial transcripts with advancing gestational age. These findings were confirmed by RT-PCR, Western blot, and mitochondrial assessment from mouse placental tissues from late gestation time points. Studies of human placental samples at similar late gestational ages showed similar trends in increased HIF-1 targets and decreased mitochondrial abundance with increasing gestation, but were not significantly significant due to the limited availability of uncomplicated preterm placenta samples. The authors demonstrated that stabilization of HIF-1 in vitro using primary trophoblasts and choriocarcinoma cell lines recapitulated the gene and mitochondrial dysfunction seen in the placental tissues and were consistent with senescence. Interestingly, cell-conditioned media from HIF-1 stabilized placenta cell lines induced myometrial cell contractions in vitro and correspondingly, induction of HIF-1 in pregnant mice was associated with preterm labor in vivo. These data support the role of the HIF-1 pathway in the process of placental senescence with increasing gestational age and highlight this pathway as a potentially important contributor to gestational length and a potential target for therapeutics to reduce preterm birth.

Overall, the conclusions of this study are mostly well supported by the data. The concept of placental aging has been controversial, with several prior studies with conflicting viewpoints on whether placental aging occurs at all, is a normal process during gestation, or rather only a pathologic phenomenon in abnormal pregnancies. This has been rather difficult to study given the difficulty of obtaining serial placental samples in late gestation. The authors used both a mouse model of serial placental sampling and human placental samples obtained at preterm, but non-pathologic deliveries, which is an impressive accomplishment as it provides insight into a previously poorly understood timepoint of pregnancy. The data clearly demonstrate changes in the HIF-1 pathway and cellular senescence at increasing gestational ages in the third trimester, which is consistent with the process of aging in other tissues.

Weaknesses of this study are that although the authors attribute alterations in HIF-1 pathways in advanced gestation to hypoxia, there are no experiments directly assessing whether the changes in HIF-1 pathways are due to hypoxia in either in vitro or in vivo experiments. HIF-1 has both oxygen-dependent and oxygen-independent regulation, so it is unclear which pathways contribute to placental HIF-1 activity during late gestation, especially since the third-trimester placenta is exposed to significantly higher oxygen levels compared to the early pregnancy environment. Additionally, the placenta is in close proximity to the maternal decidua, which consists of immune and stromal cells, which are also significantly affected by HIF-1. Although the in vitro experimental data in this study demonstrate that HIF-1 induction leads to a placenta senescence phenotype, it is unclear whether the in vivo treatment with HIF-1 induction acts directly on the placenta or rather on uterine myometrium or decidua, which could also contribute to the initiation of preterm labor.

Reviewer #2 (Public Review):

The authors sought to characterize normal placental aging to better understand how the molecular and cellular events that trigger the labor process. An understanding of these mechanisms would not only provide insight into term labor, but also potential triggers of preterm labor, a common pregnancy complication with no effective intervention. Using bulk transcriptomic analysis of mouse and human placenta at different gestational timepoints, the authors determined that stabilization of HIF-1 signaling accompanied by mitochondrial dysfunction and cellular senescence are molecular signatures of term placenta. They also used in vitro trophoblast (choriocarcinoma) and a uterine myocyte culture system to further validate their findings. Lastly, using chemically induced HIF-1 induction in vivo in mice, the authors showed that stabilization of HIF-1 protein in the placenta reduced the gestational length significantly.

The major strength of this study is the use of multiple model systems to address the question at hand. The consistency of findings between mouse and human placenta, and the validation of mechanisms in vitro and in vivo modeling are strong support for their conclusions. The rationale for studying the term placentas to understand the abnormal process of preterm birth is clearly explained. Although the idea that hypoxic stress and placental senescence are triggers for labor is not novel, the comprehensiveness of the approach and idea to study the normal aging process are appreciated.

There are some areas of the manuscript that lack clarity and weaknesses in the methodology worth noting. The rationale for focusing on senescence and HIF-1 is not clearly given that other pathways were more significantly altered in the WGCNA analysis. The placental gene expression data were from bulk transcriptomic analyses, yet the authors do not explicitly discuss the limitations of this approach. Although the reader can assume that the authors attribute the mRNA signature of aging to trophoblasts - of which, there are different types - clarification regarding their interpretation of the data and the relevant cell types would strengthen the paper. Additionally, while the inclusion of human placenta data is a major strength, the differences between mouse and human placental structure and cell types make highlighting the specific cells of interest even more important; although there are correlations between mouse and human placenta, there are also many differences, and the comparison is further limited when considering the whole placenta rather than specific cell populations.

Additional details regarding methods and the reasons for choosing certain readouts are needed. Trophoblasts are sensitive to oxygen tension which varies according to gestational age, and it is unclear if this variable was taken into consideration in this study. Many of the cellular processes examined are well characterized in the literature yet the rationale for choosing certain markers is unclear (e.g., Glb1 for senescence; the transcripts selected as representative of the senescence-associated secretory phenotype; mtDNA lesion rate).

Overall, the findings presented are a valuable contribution to the field. The authors provide a thoughtful discussion that places their findings in the context of current literature and poses interesting questions for future pursuit. Their efforts to be comprehensive in the characterization of placental aging is a major strength; few placental studies attempt to integrate mouse and human data to this extent, and the validation and presentation of a potential mechanism by which fetal trophoblasts signal to maternal uterine myocytes are exciting. Nevertheless, a clear discussion of the methodologic limitations of the study would strengthen the manuscript.

Reviewer #3 (Public Review):

In this study, Ciampa and colleagues demonstrate that HIF-1α activity is increased with gestation in humans and mice placentas and use several in vitro models to indicate that HIF activation in trophoblasts may release factors (yet to be identified) which promote myometrial contraction. Previous studies have linked placental factors to the preparation of the myometrium for labour (e.g. prostaglandins), but HIF-1α has not been implicated.

Weaknesses and concerns:

1) The author's rebuttal state that placentas undergo subclinical cellular aging as they reach term. Although several future studies are described to test functional deficits at the cellular level, the current manuscript does not provide convincing evidence of cellular aging. The only evidence of cellular senescence provided in both human and mouse data is the mRNA expression of a single gene associated with senescence.

2) The authors have not responded to the concern regarding CoCl2 mediating differentiation. The paragraph from a ref states that JAR cells do not respond as well as BeWOs to forskolin. However, this does not mean that JAR cells do not differentiate. This point is particularly pertinent as a quick search of their RNA-seq data shows upregulation of STB genes following CoCl2 treatment including ERVs (ERVFRD1, ERVV-1, ERVV-2, ERV3-1), CYP19A1 and OVOL1 just to name a few. If the authors' conclusion is that CoCl2 treatment did not alter trophoblast differentiation, the authors should provide additional data showing this. For example, cell fusion assays showing E-cadherin/desmoplakin staining and nuclear localization within stained boundaries.

3) The authors acknowledge the possibility of extraplacental effects of DMOG in the initiation of labour in their model, no additional evidence has been provided to support placental effects of their model. The authors also argue that although PMID 30808919 (which specifically overexpressed HIF-1a in the placenta) did not show changes in birth length, they propose that this may be due to constitutive HIF1a expression at the beginning of pregnancy. This argument is invalid since placental maldevelopment is consistently linked with several pregnancy complications including spontaneous preterm birth. If anything, perturbations in the beginning of pregnancy are more likely to lead to worse outcomes than those at the end of pregnancy.

4) Regarding induction of syncytialisation, please provide additional evidence that the cells have/have not syncytialised.

5) Lack of cohesion between experimental models. Please provide evidence that DMOG mediates similar effects on SA-β gal activity as CoCl2 in JARs.

6) Evidence of senescence and mitochondrial abundance could be strengthened by providing additional markers. E.g. only GLB1 mRNA expression is provided as evidence of senescence, and COX IV protein for mitochondrial abundance in mouse and human placentas. This point has not been addressed. Please provide at least one additional marker of senescence and mitochondrial abundance.

Reviewer #1 (Public Review):

This manuscript employs a string method with swarms of trajectories to extract a free energy map of KcsA channel inactivation and its model dependence. The approach connects X-ray structures for closed, partially and fully open, and inactivated KcsA through optimisation of a string defined in a collective variable space consisting of distances involving gate size, cavity-filter and filter pinching (as defined in the proposed X-ray structure for an inactivated state). The final trajectory includes pore opening and filter collapse with water penetration behind the filter, via different intermediates depending on the force field. The authors propose a role for residue L81 in controlling water entry in the final stage of this process. The results suggest that KcsA more easily inactivates with the Charmm force field, with lower barrier and direct passage from a partially open state, whereas the pathway for Amber involves transition first to a fully open state with higher barrier, despite not being the dominant open state seen experimentally under activating conditions. The results also suggest that PG lipids help activate the channel within the Amber force field, consistent with experimental evidence. The work represents large-scale advanced MD simulation. Some questions remain, however, such as if the CV space chosen is sufficient to capture all possible slow coordinates in the inactivation process, and how the resultant free energy surfaces may potentially depend on the end structures and initial pulling procedure.

Collective variable choice:

The explanation for the choice of CVs on page 5 is not sufficient to understand the process and its likely success. How were the most important and unimportant CVs identified exactly? Table 2 on page 19 shows only gate distances, cavity-filter distances and a single variable related to filter structure itself (77 CA - 77 CA) representing a pinch. Is that pinching really the only slow variable associated with inactivation changes in the filter? Why are there no variables, say for carbonyl flipping, E71 or D80 movements or even for ion and water occupancy (although water may be sampled with control of other interactions, such as involving L81)? I understand that the X-ray structure is the one source of information used to define an inactivated structure and is one with just a pinch and no complete carbonyl flipping away from the pore, as has been identified in past studies and discussed as being involved by the authors on page 14. Key changes like carbonyl flipping surely are part of the story and may be slow variables. At the very least, if not part of the CV space, could be analysed.

On page 10 the authors discuss possible differences in Amber and Charmm involving the extent to which the 4 subunits change in respect to the L81-W67 water pathway and W67-D80 hydrogen bond, arguing the different results for force field could be to do with different numbers of subunits doing different things. If I understand, the chosen CVs are all tetramer-based distances (including across subunits) and not subunit-based CVs, so that random and incomplete changes may occur to subunits for a given point in CV space. There is thus potential for the string to converge on a local minimum pathway with partial changes to its interactions within and between subunits, and may not be a unique global solution. Can the authors please explain whether or not this is possible and what analysis has been done to check it?

X-ray endpoints and initial pathway:

The string was created from a pulling/steered MD between existing X-ray structures for the closed (5VKH), partially open (3FB5), fully open (5VK6) and finally inactivated (5VKE) states. The authors write on page 12 that "The block of conduction during inactivation appears to result from pinching at the selectivity filter...", but given the end point was forced to be the X-ray structure with pinching, wasn't this outcome predetermined? This raises a significant point of how much has choice of endpoints predetermined the final states of the string? i.e. How much is an end state actually allowed to draft away from the initial Xray structure. Was a bead placed at the very endpoint and allowed to update via swarms, or was it fixed and all beads just interpolate between those fixed end states? The reason this is important is that it is plausible the inactivated crystal structure with pinching but not other changes (such as complete V76 carbonyl flipping or outer filter splaying), may not be the actual free energy minimum structure for that state and that force field.

Another obvious concern is the possible reliance on the initial pulling procedure used before string optimisation began. Fig.2 Supp 1 shows generally that the Amber path stayed pretty close to the initial steered MD path, whereas Charmm drifted downward away from that path. One could justifiably ask, if a very different initial path was chosen, might different local minimum pathways result, including Amber sampling a path like Charmm? How does one test whether or not the final path has not been trapped in some local trough of free energy? e.g. Imagine starting the Amber string using an initial path like the more diagonal Charmm-like path, or even a more extreme unphysiological one, such as a steered trajectory that initially inactivates before opening the gate. Would the final results be the same? I appreciate the simulations are very expensive and such trials may not be possible, but what evidence is there that the final path has not been trapped away from the global minimum?

One test offered by the authors is a set of unbiased MD simulations launched from points on the string. The authors ran 200ns simulations and write on page 5 that "These simulations have the expected stability based on their starting values. This is a good quality test to check the correct estimation of the general features of the free energy surface". While this sounds reasonable, 200ns MD may only be sufficient to begin to explore locally within the solved free energy trough, much like the swarms in the iterations were able to do. My own examination of Fig2 Supp 5 is that some of these simulations linger around the expected states and some drift away within the general trough of sampling, which is a good sign. What those 200ns simulations may not be able to do is escape that trough and see evidence of other possible solutions, beyond what was sampled with the string that was tied to Xray endpoints and trapped in the solution pathway that was already formed after 100-300 iterations. Overall, the string involved 800 iterations of 10ps swarms (80ns around each bead; albeit 32 trajectories in parallel), allowing good local sampling around the beads in the free energy trough, but in terms of ability to diffuse away from that point, only being comparable in contiguous trajectory time to the unbiased MD tests. It therefore would have been interesting to see if longer simulations remain in this trough; though I understand the challenges in running so much MD. Such simulations may, however, lead to exploration beyond what was seen in the string solutions.

Force field effects and origin:

Regarding the effect of the chosen force field, the authors state that "Given that our simulations were conducted under activating conditions, we had expected the open states to be more populated than the closed ones. Simulations carried out at higher pH may be able to resolve this inconsistency". Also running at high pH would be a nice thing to do to prove the method is in fact sensitive to conditions to see a shift in the distribution of states. But the question is why were open states not more occupied under low pH and 50mM K+? From my analysis of the figures, the results show that the Charmm force field tends to allow for opening of the channel somewhat (at least with similar free energy for partially and fully open to closed) whereas Amber tends to close the channel more (with more uphill energy as the channel opens than Charmm; Fig 2). i.e. at low pH and 50 K+, isn't the Amber model incorrectly reporting fairly strong bias against opening? Moreover, regarding the free energy of the inactivated state itself, why should we not expect equilibrated channels under activating conditions to eventually fall into an inactivated state, in which case we should expect low free energy of that state (as found with Charmm and not Amber in Fig2), but with a slow rate. While much discussion in the manuscript appears to discuss limitations in Charmm (although on page 12 discussion leans either way), these factors may seem to favour Charmm over Amber.

On page 12 the authors explain the possible causes for force field dependence, although this seems limited to ion interactions, glutamate charges and dihedrals. But it would be nice to get a bit more insight into what terms may have influenced the pathway, in particular involving interactions between TM2 and the base of the selectivity filter and hydration behind the filter. Regarding ion interactions, is there a good reason to believe ions are key to the difference seen? i.e. How were ions involved differently in the state transitions involving Amber and Charmm? The authors have noted a role for ion-carbonyl interactions. It is important that the authors explain which is the two competing models has been used and why. i.e. Off-the-shelf Charmm36 force field includes strong K+-backbone carbonyl interaction, previously seen to promote high ion occupancy, similar to Amber, whereas Lennard-Jones parameters modified to match N-methyl-acetamide and water partitioning (such as early Berneche, Noskov and Roux work) reduce ion occupancy and increase water content inside the filter.

Reviewer #2 (Public Review):

The authors describe a computational study into the energetics of KcsA inactivation. Using enhanced sampling, a converged free energy landscape of the inactivation process is achieved in two modern molecular mechanics force fields. The obtained profiles confirm the literature finding of too rapid inactivation, in particular in simulations using the CHARMM force field. Interestingly, it is found that selectivity filter collapse does not gradually follow opening of the inner gate, but proceeds rather switch-like. A key role for residue L81 is proposed as opening gateway in this process.

The study is impressive and interesting. However, I have a number of concerns that the authors may wish to address in a revised version of the manuscript.

First, concerning a set of unbiased simulations spawned at different regions of the investigated free energy landscapes, the authors write: "These simulations have the expected stability based on their starting values".<br /> Fig 2.c shows a rather smooth downhill slope in the free energy curve towards the closed state for AMBER , so wouldn't the expected behavior in that case be that all unbiased trajectories end up in the closed state, or at least travel a substantial amount in that direction? However, that is not observed. This should be further investigated.

Second, "This suggests that stabilization of the partially open state by the removal of bound lipids can explain the increase in open probability" is an odd statement, as "stabilization of the partially open state" means almost the same as "increase in open probability".

The statement "both force fields yield inactivation barriers that are orders of magnitude lower than what is expected from electrophysiology experiments" seems inaccurate. Perhaps the authors mean "inactivation rates that are orders of magnitude lower" rather than barriers?

In addition, the assertion "The CHARMM force field, on the other hand, results in landscapes in agreement with the fact that one of the dominant states in activating conditions is the partially open state, as revealed by a combination of ssNMR+MD." seems to hold for the AMBER force field without PG lipids rather than for CHARMM?

Together with the higher barrier towards the inactivated state as well as covering most known x-ray structures along the inactivation pathway, this would seem to point all in the direction that the studied AMBER force field provides a more faithful picture of the inactivation pathway than CHARMM. I, therefore, find the somewhat inconclusive summary as presented in Fig. 5 a bit uninformative, as it suggests that both mechanisms might be equally likely.

Overall, the study would benefit from a follow-up step to become more conclusive. This could be either in the form of the suggested L81 mutation or changing the simulation conditions to inactivating conditions such as low salt, in which case the inactivated state would be expected to become a minimum, which would provide an additional reference point for validation. Either of these would narrow down the spectrum of possible mechanisms.

Reviewer #3 (Public Review):

The computational study reported in the manuscript "Free energy landscapes of KcsA inactivation" by Pérez-Conesa and Delemotte is quite interesting and insightful.

The computations provide the first complete analysis of how the opening of the activation gate and the constriction of the selectivity filter are coupled in the KcsA channel.

The analysis is careful and is state-of-the-art. The results reveal remarkable differences between the CHARMM and AMBER force fields.

Unfortunately, the "elephant in the room" with regards to K+ channel inactivation is the significance of the dilated structures more recently obtained by Xray and EM. While it is worthwhile doing our best to really understand the constriction mechanism of KcsA, and the present manuscript does an excellent job at that, the ground has shifted and understanding finer points about KcsA constriction has become, unfortunately, not the most prominent issue in the field at the present time.

Let's discuss the current situation about the inactivation of K+ channels. The situation is fairly unsettled. The KcsA channel was the first for which some atomic structure and mechanism, centered on a constriction of the selectivity filter, were proposed. The constricted conformation really does not conduct because the filter is too narrow. More recently a few structures (Xray and EM) for channel mutants known to have more propensity to inactivate have revealed a different conformation of the filter which appears to be dilated toward the extracellular side. This is a conformation that had never been seen previously. Different "camps" co-exist in the K+ channel community about inactivation. Those who were very skeptical about the constricted conformation claim that the new dilated structures is the final truth. While the dilated structures are certainly part of the body of information that we have now, but their significance remains somewhat unclear if anything because of the fact that they are not perfectly occluded and they allow ion conduction! While it is worthwhile doing our best to really understand the constriction mechanism of KcsA, and the present manuscript does an excellent job at that, the ground has shifted and understanding finer points about KcsA constriction has become, unfortunately, not the most prominent issue in the field at the present time.

Public Review:

The primary goal of this paper is to examine microtubule detyrosination as a potential therapeutic target for axon regeneration. Using dimethylamino-parthenolide (DMAPT), this study extensively examines mechanistic links between microtubule detyrosination, hyper-interleukin-6 (hIL-6), and PTEN in neurite outgrowth in retinal ganglion cells in vitro. These findings provide convincing evidence that parthenolide has a synergistic effect on hIL-6- and PTEN-related mechanisms of neurite outgrowth in vitro. The potential efficacy of systemic DMAPT treatment to promote axon<br /> regeneration in mouse models of optic nerve crush and spinal cord injury was also examined.

Strengths:

1) The examination of synergistic activities between parthenolide, hyperIL-6, and PTEN knockout is leveraged not only for potential therapeutic value, but also to validate and delineate mechanism of action.

2) The in vitro studies utilize a multi-level approach that combines cell biology and biochemistry approaches to dissect the mechanistic link from parthenolide to microtubule dynamics.

3) The studies provide a basis for others to test the role of DMAPT in other settings, particularly in the context of other effective pro-regenerative approaches.

Weaknesses:

1) In vivo studies are limited to select outcomes of recovery and do not validate or address mechanism of action in vivo.

2) Known activities of DMAPT beyond microtubule detyrosination, such as oxidative stress, mitochondrial function and NFkB inhibition, are not considered in experimental examinations or in the interpretation of findings.

Reviewer #1 (Public Review):

Using the colon transcriptomes of 52 BXD mouse strains fed either chow or a high-fat diet (HFD), Li et al. present their findings on gene-by-environment interactions underpinning inflammation and inflammatory bowel disease (IBD). They discovered modules that are enriched for IBD-dysregulated genes using co-expression gene networks. They determined Muc4 and Epha6 to be the leading candidates causing variations in HFD-driven intestinal inflammation by using systems genetics in the mouse and integration with external human datasets. In their analysis, they concluded that their strategy "enabled the prioritization of modulators of IBD susceptibility that were generalizable to the human situation and may have clinical value." This dataset is intriguing and generates hypotheses that will be investigated in the future. However, there were no mechanistic or causation-focused investigations; the results were primarily observational and correlative.

Reviewer #2 (Public Review):

In this paper, the authors seek to identify genes that contribute to gut inflammation by capitalizing on deep phenotyping data in a mouse genetic reference population fed a high-fat or chow diet and then integrating it with human genetic data on gut inflammatory diseases, such as inflammatory bowel disease (IBD) and Ulcerative Colitis (UC). To achieve this the authors performed genome-wide gene expression in the colon of 52 BXD strains of mice fed either a high-fat or chow diet. From this analysis, they observed significant variation in gene expression related to inflammation among the 52 BXD strains and differential gene expression of inflammatory genes fed a high-fat diet. Overlaying this data with existing mouse and human data of inflammatory gut disease identified a significant enrichment. Using the 52 BXD strains the authors were able to identify specific subsets of strains that were susceptible and resistant to gut inflammation and analysis of gene expression within the colon of these strains was enriched with mouse and human IBD. Furthermore, analysis of cytokine levels of IL-10 and IL-15 were analyzed and found to be increased in resistant BXD strains and increased in susceptible BXD strains.

Using the colon genome-wide gene expression data from the 52 BXD strains, the authors performed gene co-expression analysis and were able to find distinct modules (clusters) of genes that correlated with mouse UC and human IBD datasets. Using the two modules, termed HFD_M28 and HFD_M9 that correlated with mouse UC and human IBD, the authors performed biological interrogation along with transcription factor binding motif analysis to identify possible transcriptional regulators of the module. Next, they performed module QTL analysis to identify potential genetic regulators of the two modules and identified a genome-wide significant QTL for the HFD_M28 on mouse chromosome 16. This QTL contained 552 protein-coding genes and through a deduction method, 27 genes were prioritized. These 27 genes were then integrated with human genetic data on IBD and two candidate genes, EPHA6 and MUC4 were prioritized.

Overall, this paper provides a framework and elegant use of data from a mouse genetic reference population coupled with human data to identify two strong candidate genes that contribute to human IBD and UC diseases. In the future, it will be interesting to perform targeted studies with EPHA6 and MUC4 and understand their role in gut inflammatory diseases.

Reviewer #1 (Public Review):

Jamge et al. sought to identify the relationships between histone variants and histone modifications in Arabidopsis by systematic genomic profiling of 13 histone variants and 12 histone modifications to define a set of "chromatin states". They find that H2A variants are key factors defining the major chromatin types (euchromatin, facultative heterochromatin, and constitutive heterochromatin) and that loss of the DDM1 chromatin remodeler leads to loss of typical constitutive heterochromatin and replacement of this state with features common to genes in euchromatin and facultative heterochromatin. This study deepens our understanding of how histone variants shape the Arabidopsis epigenome and provides a wealth of data for other researchers to explore.

Strengths:

1. The manuscript provides convincing evidence supporting the claims that: A) Arabidopsis nucleosomes are homotypic for H2A variants and heterotypic for H3 variants, B) that H3 variants are not associated with specific H2A variants, and C) H2A variants are strongly associated with specific histone post-translational modifications (PTMs) while H3 variants show no such strong associations with specific PTMs. These are important findings that contrast with previous observations in animal systems and suggest differences in plant and animal chromatin dynamics.

2. The authors also performed comprehensive epigenomic profiling of all H2A, H2B, and H3 variants and 12 histone PTMs to produce a Hidden Markov Model-based chromatin state map. These studies revealed that histone H2A variants are as important as histone PTMs in defining the various chromatin states, which is unexpected and of high significance.

3. The authors show that in ddm1 mutants, normally heterochromatic transposable element (TE) genes lose H2A.W and gain H2A.Z, along with the facultative heterochromatin and euchromatin signatures associated with H2A.Z at silent and expressed genes, respectively.

Reviewer #2 (Public Review):

Jamge et al. set out to delineate the relationship between histone variants, histone modifications and chromatin states in Arabidopsis seedlings and leaves. A strength of the study is its use of multiple types of data: the authors present mass-spec, immunoblotting and ChIP-seq from histone variants and histone modifications. They confirm the association between certain marks and variants, in particular for H2A, and nicely describe the loss of constitutive heterochromatin in the ddm1 mutant.

Overall, this study nicely illustrates that, in Arabidopsis, histone variants (and H2A variants in particular) display specificity in modifications and genomic locations, and correlate with some chromatin sub-states. This encourages future work in epigenomics to consider histone variants with as much attention as histone modifications.

Reviewer #3 (Public Review):

How chromatin state is defined is an important question in the epigenetics field. Here, Jamge et al. proposed that the dynamics of histone variant exchange control the organization of histone modifications into chromatin states. They found 1) there is a tight association between H2A variants and histone modifications; 2) H2A variants are major factors that differentiate euchromatin, facultative heterochromatin, and constitutive heterochromatin; 3) the mutation in DDM1, a remodeler of H2A variants, causes the mis-assembly of chromatin states in TE region. The topic of this paper is of general interest and the results are novel.

Overall, the paper is well-written and the results are clearly presented. The biochemical analysis part is solid.

Reviewer #4 (Public Review):

This work aims at analyzing the impact of histone variants and histone modifications on chromatin states of the Arabidopsis genome. Authors claim that histone variants are as significant as histone modifications in determining chromatin states. They also study the effect of mutations in the DDM1 gene on the exchange of H2A.Z to H2A.W, which convert the silent state of transposons into a chromatin state normally found on protein coding genes.

This is an interesting and well done study on the organization of the Arabidopsis genome in different chromatin states, adding to the previous reports on this issue.

Reviewer #1 (Public Review):

In this work, Urbanska and colleagues use a machine-learning based crossing of mechanical characterisations of various cells in different states and their transcriptional profiles. Using this approach, they identify a core set of five genes that systematically vary together with the mechanical state of the cells, although not always in the same direction depending on the conditions. They show that the combined transcriptional changes in this gene set is strongly predictive of a change in the cell mechanical properties, in systems that were not used to identify the genes (a validation set). Finally, they experimentally after the expression level of one of these genes, CAV1, that codes for the caveolin 1 protein, and show that, in a variety of cellular systems and contexts, perturbations in the expression level of CAV1 also induce changes in cell mechanics, cells with lower CAV1 expression being generally softer.

Overall the approach seems accessible, sound and is well described. My personal expertise is not suited to judge its validity, novelty or relevance, so I do not make comments on that. The results it provides seem to have been thoroughly tested by the authors (using different types of mechanical characterisations of the cells) and to be robust in their predictive value. The authors also show convincingly that one of the genes they identified, CAV1, is not only correlated with the mechanical properties of cells, but also that changing its expression level affects cell mechanics. At this stage, the study appears mostly focused on the description and validation of the methodological approach, and it is hard to really understand what the results obtain really mean, the importance of the biological finding - what is this set of 5 genes doing in the context of cell mechanics? Is it really central, or is it just one of the set of knobs on which the cell plays - and it is identified by this method because it is systematically modulated but maybe, for any given context, it is not the dominant player - all these fundamental questions remain unanswered at this stage. On one hand, it means that the study might have identified an important novel module of genes in cell mechanics, but on the other hand, it also reveals that it is not yet easy to interpret the results provided by this type of novel approach.

Reviewer #2 (Public Review):

A key strength is the quantitative approaches all add rigor to what is being attempted. The approach with very different cell culture lines will in principle help identify constitutive genes that vary in a particular and predictable way. To my knowledge, one other study that should be cited posed a similar pan-tissue question using mass spectrometry proteomics instead of gene expression, and also identified a caveolae component (cavin-1, PTRF) that exhibited a trend with stiffness across all sampled tissues. The study focused instead on a nuclear lamina protein that was also perturbed in vitro and shown to follow the expected mechanical trend (Swift et al 2013).

Reviewer #3 (Public Review):

In this work, Urbanska et al. link the mechanical phenotypes of human glioblastoma cell lines and murine iPSCs to their transcriptome, and using machine learning-based network analysis identify genes with putative roles in cell mechanics regulation. The authors identify 5 target genes whose transcription creates a combinatorial marker which can predict cell stiffness in human carcinoma and breast epithelium cell lines as well as in developing mouse neurons. For one of the target genes, caveolin1 (CAV1), the authors perform knockout, knockdown, overexpression and rescue experiments in human carcinoma and breast epithelium cell lines. They determine the cell stiffness via RT-DC, AFM indentation and AFM rheology and confirm that high CAV1 expression levels correlate with increased stiffness in those model systems. This work brings forward an interesting approach to identify novel genes in an unbiased manner, but surprisingly the authors validate caveolin 1, a target gene with known roles in cell mechanics regulation.

I have two main concerns with the current version of this work:<br /> 1) The authors identify a network of 5 genes that can predict mechanics. What is the relationship between the 5 genes? If the authors aim to highlight the power of their approach by knockdown, knockout or over-expression of a single gene why choose CAV1 (which has an individual p-value of 0.16 in Fig S4)? To justify their choice, the authors claim that there is limited data supporting the direct impact of CAV1 on mechanical properties of cells but several studies have previously shown its role in for example zebrafish heart stiffness, where a knockout leads to higher stiffness (Grivas et al., Scientific Reports 2020), in cancer cells, where a knockdown leads to cell softening (Lin et al., Oncotarget 2015), or in endothelial cell, where a knockout leads to cell softening (Le Master et al., Scientific Reports 2022).<br /> 2) The authors do not show how much does PC-Corr outperforms classical co-expression network analysis or an alternative gold standard. It is worth noting that PC-Corr was previously published by the same authors to infer phenotype-associated functional network modules from omics datasets (Ciucci et al., Scientific Reports 2017).

Altogether, the authors provide an interesting approach to identify novel genes associated with cell mechanics changes, but the current version does not fulfill such potential by focusing on a single gene with known roles in cell mechanics.

Reviewer #1 (Public Review):

The authors have approached the study of the mechanism by which the two more antigenic proteins of the influenza A virus, hemagglutinin (HA) and neuraminidase (NA), are expressed later during the infection. For this aim, they set an experimental approach consisting of a 2-hour-long infection at a multiplicity of infection of 2 with the viral strain WSN. They used cells from the lung carcinoma cell line A549. They used the FISH technique to detect the mRNAs in situ and developed an imaging-based assay for mathematically modeling and estimating the nuclear export rate of each of the eight viral segments. They propose that the delay in the expression of HA and NA is based on the retention of their mRNA within the nucleus.

The main strength of this work is the fact that the authors have studied a long-unaddressed mechanism in influenza A virus infectious cycle, as is the late expression of HA and NA, by creating a work flow including mRNA detection (FISH) plus mathematical calculations to arrive at a model, which additionally could be useful for general biological processes where transcription occurs in a burst-like manner. The weakness of this work in its present state is that in order to "quantify" the export rate of the transcripts, several assumptions regarding the viral infection are made without empirical data. It would greatly improve if more precise experiments could be performed and/or include demonstration of the assumptions made (i.e., synchronized infections, empirically demonstrating that cRNA production does not occur within the first 2 hours of infection, and/or separate transcription and replication, inhibiting RNA degradation during viral infection).

Reviewer #2 (Public Review):

In this study the authors developed a framework to investigate the export rates of Influenza viral RNAs translocating from the nucleus to the cytoplasm. This model suggests that the influenza virus may control gene expression at the RNA export level, namely, the retention of certain transcripts in the nucleus for longer times, allows the generation of other viral encoded proteins that are exported regularly, and only later on do certain mRNAs get exported. These encode proteins that alert the cell to the presence of viral molecules, hence keeping their emergence to very end, might help the virus to avoid detection as late as possible in the infection cycle.

The study is of limited scope. The notion that some mRNAs are retained in the nucleus after transcription is concluded early on from the FISH data. The model does not contribute much to the understanding and is mostly confirming the FISH data. The export rate is an ambiguous number and this part is not elaborated upon. One is left with more questions since no mechanistic knowledge emerges, and no additional experimentation is attempted to try drive to a deeper understanding.

Reviewer #1 (Public Review):

This study revealed that one of the mechanisms for iTreg (induced-Treg) lineage instability upon restimulation is through sustained store-operated calcium entry (SOCE), which activates transcription factor NFAT and promotes changes in chromatin accessibility to activated T cell-related genes. The authors revealed that, unlike thymus-derived Tregs (tTreg) with blunted calcium signaling and NFAT activation, iTregs respond to TCR restimulation with fully activated SOCE and NFAT similar to activated conventional T cells. Activated NFAT binds to open chromatin regions in genes related to T helper cells, increases their expression, and leads to the instability of iTreg cells. On the other hand, inhibition of the SOCE/NFAT pathway by chemical inhibitors could partially rescue the loss of Foxp3 expression in iTreg upon restimulation. The conclusion of the study is unexpected since previous studies showed that NFAT is required for Foxp3 induction and iTreg differentiation (Tone Y et al, Nat Immunol. 2008, PMID: 18157133; Vaeth M et al, PNAS, 2012, PMID: 22991461). Additionally, Foxp3 interacts with NFAT to control Treg function (Wu Y et al, Cell, 2006, PMID: 16873067). The data presented in this study demonstrated the complex role NFAT plays in the generation and stability of iTreg cells.

Several concerns are raised from the current study.<br /> 1. Previous studies showed that iTregs generated in vitro from culturing naïve T cells with TGF-b are intrinsically unstable and prone to losing Foxp3 expression due to lack of DNA demethylation in the enhancer region of the Foxp3 locus (Polansky JK et al, Eur J Immunol., 2008, PMID: 18493985). It is known that removing TGF-b from the culture media leads to rapid loss of Foxp3 expression. In the current study, TGF-b was not added to the media during iTreg restimulation, therefore, the primary cause for iTreg instability should be the lack of the positive signal provided by TGF-b. NFAT signal is secondary at best in this culturing condition.

2. It is not clear whether the NFAT pathway is unique in accelerating the loss of Foxp3 expression upon iTreg restimulation. It is also possible that enhancing T cell activation in general could promote iTreg instability. The authors could explore blocking T cell activation by inhibiting other critical pathways, such as NF-kb and c-Jun/c-Fos, to see if a similar effect could be achieved compared to CsA treatment.

3. The authors linked chromatin accessibility and increased expression of T helper cell genes to the loss of Foxp3 expression and iTreg instability. However, it is not clear how the former can lead to the latter. It is also not clear whether NFAT binds directly to the Foxp3 locus in the restimulated iTregs and inhibits Foxp3 expression.

Reviewer #2 (Public Review):

The phenotypic instability of in vitro-induced Treg cells (iTregs) has been discussed for a long time, mainly in the context of the epigenetic landscape of Treg-signature genes; e.g. Treg-specifically CpG-hypomethylated Foxp3 CNS2 enhancer region. However, it has been insufficiently understood the upstream molecular mechanisms, the particularity of intracellular signaling of natural Treg cells, and how they connect to stable/unstable suppressive function.

Huiyun Lv et al. addressed the issue of phenotypic instability of in vitro-induced regulatory T cells (iTregs), which is a different point from the physiological natural Treg cells and an obstacle to the therapeutic use of iTreg cells. The authors focused on the difference between iTreg and nTreg cells from the perspective of their control of store-operated calcium entry (SOCE)-mediated cellular signaling, and they clearly showed that the sustained SOCE signaling in iTreg and nTreg cells led to phenotypic instability. Moreover, the authors pointed the correlation between the incomplete conversion of chromatin configuration and the NFAT-mediated control of effector-type gene expression profile in iTreg cells. These findings potentially cultivate our understanding of the cellular identity of regulatory T cells and may shed light on the therapeutic use of Treg cells in many clinical contexts.

The authors demonstrated the biological contribution of Ca2+ signaling with the variable methods, which ensure the reliability of the results and the claims of the authors. iTreg cells sustained SOCE-signaling upon stimulation while natural Treg cells had lower strength and shorter duration of SOCE-signaling. The result was consistent with the previously-proposed concept; a certain range of optimal strength and duration of TCR-signaling shape the Treg generation and maintenance, and it provides us with further in-depth mechanistic understanding.

In the later section, authors found the incomplete installment of Treg-type open chromatin landscape in some effector/helper function-related gene loci in iTreg cells. These findings propose the significance to focus on not only the "Treg"-associated gene loci but also "Teffector-ness"-associated regions to determine the Treg conversion at epigenetic level.

Limitations and weaknesses;<br /> (1) Some concerns about data processing and statistic analysis.<br /> The authors did not provide sufficient information on statistical data analysis; e.g. lack of detailed descriptions about<br /> -the precise numbers of technical/biological replicates of each experiment<br /> -the method of how the authors analyze data of multiple comparisons... Student t-test alone is generally insufficient to compare multiple groups; e.g. figure 1.<br /> These inappropriate data handlings are ruining the evidence level of the precious findings.

(2) Untransparent data production; e.g. the method of Motif enrichment analysis was not provided.<br /> Thus, we should wait for the author's correction to fully evaluate the significance and reliability of the present study.

(3) Lack of evidence in human cells.<br /> I wonder whether human PBMC-derived iTreg cells are similarly regulated.

(4) NFAT regulation did not explain all of the differences between iTregs and nTregs, as the authors mentioned as a limitation.<br /> Also, it is still an open question whether NFAT can directly modulate the chromatin configuration on the effector-type gene loci, or whether NFAT exploits pre-existing open chromatin due to the incomplete conversion of Treg-type chromatin landscape in iTreg cells. The authors did not fully demonstrate that the distinct pattern of chromatin regional accessibility found in iTreg cells is the direct cause of an effector-type gene expression.

Reviewer #1 (Public Review):

Terzioglu and co-workers tested the provocative hypothesis that mitochondria maintain an internal temperature considerably higher than cytosolic/external environmental temperature due to the inherent thermodynamic inefficiency of mitochondrial oxidative phosphorylation. As a follow-up to a prior paper from some of the same authors, the goal of this study was to conduct additional experiments to assess mitochondrial temperature in cultured cells. Consistent with the prior work, the authors provide consistent evidence that the temperature of mitochondria in four different types of cultured mammalian cells, as well as cells from Drosophila (poikilotherms), is 15oC or more above the external temperature at which cells are maintained (e.g., 37oC). Additional evidence shows that mitochondria maintain higher temperatures under several different types of cellular metabolic stresses predicted to decrease the dependence on OxPhos, adding to the notion that natural thermodynamic inefficiency and heat generation may be an important, and potentially regulated, characteristic of mitochondrial metabolism.

Strengths<br /> Demonstration that both a fluorescent (Mito Thermo Yellow) and a genetic-based (mito-gTEMP) mitochondrial targeted temperature probe elicit similar quantitative changes in mitochondrial temperature under different experimental conditions is a strength. The addition of the genetic probe to the current study supports prior findings using the fluorescent probe and thus achieves a primary objective of the study.

The experiments are well-designed and executed. Specific attention given to potential artifacts affecting probe signal and/or non-specific effects from the different experimental interventions is a strength.

The use of different cultured cell lines from different organisms provides additional evidence of elevated temperature as a general property of functioning mitochondria, representing additional validation.

Weakness:<br /> While the findings and potential interpretations put forward by the authors are intriguing, the severity of the interventions (e.g., mitochondrial complex-specific inhibitors, inhibition of protein synthesis) and the absence of simultaneous or parallel measurements of other key bioenergetic parameters (i.e., membrane potential, oxygen consumption rate, etc.) limits the ability to interpret potential cause and effect - whether the thermogenesis aspect of OxPhos is being sensed and regulated, or whether temperature changes are more of a biproduct of adjustments in OxPhos flux under the experimental circumstances. In other words, the physiological relevance of the findings remains unclear.

Related, several of the interventions are employed to either increase or decrease dependence on OxPhos flux, but no outcome measures are reported to document whether the intended objective was achieved (e.g., increased OxPhos flux in low glucose plus galactose, decreased ATP demand-OxPhos flux with anisomycin, etc.).

Reviewer #2 (Public Review):

An important paper that confirms the validity of the initial findings of Chretien et al regarding the hot temperatures at which the mitochondrion is operating. There are certain gaps in the literature covered in its list of cited references and, as a consequence, in the argumentation of the paper - but these can be easily fixed.

Reviewer #3 (Public Review):

The goal of this study was to use a combination of fluorescent dyes and genetically encoded reporters to estimate the temperature of mitochondria. The authors provide additional evidence that they claim to support "hot" mitochondria.

Strengths:<br /> 1. The authors use several methods, including a mitochondrial fluorescent reporter dye, as well as a genetically encoded gTEMP temperature probe, to estimate mitochondrial temperature.<br /> 2. The authors couple these measurements with other perturbation of mitochondria, such as OXPHOS inhibitors, to show consistency

Weaknesses:<br /> 1. The methodology for inferring mitochondrial temperature is not well-established to begin with and requires additional controls for interpretation.<br /> a. Very little benchmarking is done of the "basal" fluorescence ratio, and whether that fluorescence ratio actually reflects true organelle temperature. For instance, the authors should in parallel compare between different organelles to see if only mitochondria appear "hot" or whether this is some calibration error. Another control is to use different incubator temperatures and see how mitochondrial (vs other organelle) temperature varies as a function of external temperature.<br /> b. The authors do not rigorously control for other factors that may also be changing fluorescence and may be confounders to the delta fluorescence (eg, delta calcium in response to mito inhibitors, membrane potential, redox status, ROS, etc.). There should be additional calibration for all potential confounders.<br /> c. It was unclear where the mito-targeted dyes/probes localized in terms of mitochondrial compartment. Regardless, one important control would be to target these dyes to each of the different compartments eg. Matrix vs IMS vs outer membrane to determine if a gradient of temperatures can be observed.<br /> d. Can these probes be used in isolated mitochondria and other isolated organelles. Such data would also help to clarify whether the high temperature is a specific to mitochondria.<br /> 2. The authors should try to calibrate their fluorescence inference of temperature with an alternative method and benchmark to others in the field. For instance, Okabe et al Nat Comm 2012 used a polymeric thermometer to measure temperature and reported 33degC cytoplasm and 35degC nucleus. Can the authors also show a ~2degC difference in their hands between those two compartments, and under those conditions are mitochondria still 10degC hotter?<br /> 3. There are some theoretical considerations and critiques about temperature imaging in cells (eg Baffou et al Nat Methods 2014; Lane et al Plos Biology 2018), and the possible magnitude of theoretical variation between compartments. The authors should address some of those theoretical concerns, either experimentally or in the discussion.

Based on the aforementioned weaknesses, in my opinion, the authors did not achieve their Aims to accurately determine the temperature of mitochondria. The results, while interesting, are preliminary and require additional controls before conclusions can be drawn. Previous studies have indicated intra-organelle temperature variations within cells; typically, previous reports have estimated that the variation is within a few degrees (Okabe et al Nat Comm 2012). Only one report has previously suggested that mitochondria are at 50degC (Cretien, Plos biology 2018). The study does not substantially clarify the true temperature of mitochondria or resolve potential discrepancies in previous estimates of mitochondrial temperature.

Reviewer #1 (Public Review):

This is an interesting study deploying convergent methodologies to address a timely question: can non-human primates distinguish theory of mind from random behaviours during passive viewing of animated shapes, and what brain regions are implicated? As the authors note, fMRI studies of brain activation in response to the theory of mind stimuli in non-human primates are scarce, and none have explored the processing of abstract stimuli in this context.

The major strengths of the study are the application of the Frith-Happé shapes task in a group of marmosets during fMRI in conjunction with concurrent eye tracking recording. Eye tracking is a very nice addition as it enables the authors to determine the gaze patterns and fixation duration on distinct aspects of the task stimuli (e.g., large triangle versus small triangle) as well as group differences. Overall, the study seems well-designed and technically rigorous, and the major conclusions appear to be supported by the data.

However, there is one aspect I would appreciate some clarity on, namely the failure to include the original "Goal directed condition" from the Frith-Happé task. The authors contrast visuo-oculomotor and fMRI activation between the Random (no discernible interaction or purposeful behaviour) and the ToM (goal-directed behaviours with mental interaction) but neglect the intermediate step of physical interaction between the shapes that the Goal-directed behaviour condition portrays. As such, it is difficult to make clear statements as to what the activation patterns in the ToM condition represent - perhaps this merely reflects the processing of an unfolding narrative rather than random movements.

Reviewer #2 (Public Review):

In this study, Dureux and colleagues show that marmosets are sensitive to the Frith and Happe social illusion. This result is particularly interesting from an evolutionary perspective as rhesus macaques are insensitive to this social illusion.

Although marmosets show sensitivity to the illusion of social interaction between two geometric shapes, behavioural and neuronal evidence also show differences between humans and marmosets.

Reviewer #3 (Public Review):

To assess the degree to which highly social primates like marmosets share a human-like Theory of Mind (ToM), the authors used eye tracking and functional magnetic resonance brain imaging on marmosets and humans who were viewing two of the three categories from classic Frith-Happé animations. Humans viewing the ToM animations showed, relative to the random movement animations, longer fixation times, more viewing of the large shape, and more viewing of the small shape. In contrast, the marmosets did not differ in their viewing of the ToM videos as a category and did not show differential viewing of the small shape. The marmosets did show differential viewing of the large shape, but this difference was blunted relative to that seen in humans. Neurally, both species showed widespread brain activation in many areas that discriminated between ToM videos and random movement videos. This pattern of activation partially overlapped and partially was different in humans and marmosets. It was also partially overlapping and partially different when comparing humans in this study to humans in another study. Overall, the authors conclude that their evidence cannot address whether marmosets have a Theory of Mind, but that marmosets show a "clear preference for interacting shapes" that may be an ancestral form of human Theory of Mind.

There are several laudable strengths to this report. It reports a direct human/monkey comparison. It uses a robust population of subjects, especially for the monkey experiment. It uses strong imaging methods that use modern parcellation maps, compares human data from this study to comparable data from another study, and accounts for lateralization differences convincingly using maps of signal-to-noise ratio. It uses eye-tracking methods and stimuli that are solidly grounded in the human literature and that has recently been used in a different monkey species.

Unfortunately, the weaknesses of this report limit its interpretability. First, it omits one of the three major categories of the Frith-Happé animations: Goal-Directed actions. Data from this category are critical because they provide a case where the shapes are engaging in biological motion but are not behaving as if they attribute minds to each other. Without including it, readers cannot interpret whether any given finding is due to biological motion or mentalizing. Second, the study did not gather explicit reports of mental state attribution from humans. This does not allow for a manipulation check about whether humans were even engaging in mentalizing and does not allow the researchers to separate out what brain activation patterns are due to mentalizing and which are due to eye movements or stimulus movement. Third, in interpreting the data, the researchers gloss over the major species differences and primarily focus on one small species similarity. Both this study and a previous human study (Klein et al., 2009, Quart. J. Exp. Psychol.) have shown longer fixations for the ToM videos relative to the random motion videos and that these fixations correlate with explicit ratings of the intentionality of the shapes (Klein et al., 2009). That the marmosets don't show this difference should be a major piece of evidence against the hypothesis that they are engaging in anything like mentalizing. The marmosets also failed to show a viewing difference for the small shape. In short, the small viewing difference in the large shape, itself blunted relative to that seen in humans, is not sufficient evidence to justify the conclusion that marmosets engage in anything like ToM or even that they show a "clear preference for interacting shapes". Fourth, alternative explanations for the small differences that do exist were not sufficiently explored. The videos that make up the categories in the Frith-Happé animations differ in many ways, such as in the amount of visual motion, smoothness/jerkiness of motion, amount of the screen taken up by shapes vs white space, etc. Indeed, in the prior study to use these stimuli with monkeys, the authors also found that the categories differed in viewing parameters but that this difference disappeared once low-level visual motion was accounted for (Schafroth et al., 2021, Sci. Rep.). Without a similar analysis here or a second experiment that assesses generalization to stimuli that don't differ on low-level perceptual features, readers cannot know whether the small viewing difference that exists is due to something like mentalizing or something about low-level visual motion. Indeed, other studies have found overlapping brain activity patterns in monkeys that are driven primarily by low-level visual motion (e.g., Russ et al., 2015, Neuroimage). Fifth, the prior monkey study to use these stimuli raised the point that these stimuli may not even be appropriate to test ToM in nonhumans. Human-like displays of "mocking", "coaxing", or "seducing" are likely meaningless to monkeys. This weakness has not been addressed in the current study.

Considering the weaknesses in the behavioral methods, the well-collected neural activity patterns cannot be interpreted in a meaningful way. As such, the authors' conclusions are not justified at the current time. Nevertheless, this report may be useful to others who attempt similar experiments of their own.

Reviewer #1 (Public Review):

The study of Aso and colleagues seeks to understand how learned information is steering motor output. Using an artificial training paradigm consisting of odor presentation combined with dopamine neuron activation, they identify upwind orientation as an important parameter of appetitive memory recall (as has been shown before - e.g. Handler 2019). Using the Drosophila genetic targeting library and optogenetic activation, they identify several populations of neurons responsible for upwind orientation by analyzing freely moving animals in an airflow chamber. They concentrate on a specific subset, which they call upwind neurons (UPWINs), and which they can anatomically link downstream to the flies' memory center, the mushroom body (MB), building on the ultrastructural connectome brain atlas. In combination with electrophysiology, in-vivo calcium imaging, and memory assays, they successfully show that (1) UPWINs promote upwind orientation including acceleration of angular speed and bias turning towards the upwind direction, (2) UPWINs receive excitatory and inhibitory input from specific parts of the MB, (3) UPWINs increase odor-evoked activity upon (artificial) appetitive training and (4) appetitive memory recall is impaired when blocking UPWIN neurons only during the memory test.

The authors use state-of-the-art techniques combining tools like optogenetics, connectome analysis as well as electrophysiology, in-vivo calcium imaging, and memory/behavioral assays tracking individual flies. It provides new insights into mushroom body memory retrieval circuits and how they integrate with information from other brain areas. However, some concerns remain regarding some claims of the paper. The timeline of the behavioral and the physiological experiments differ. It is therefore difficult to define the memory phases when upwind orientation is important for recall. Moreover, one main conclusion the authors draw from their data is that upwind orientation is promoted by disinhibition from a specific MB output connection, however, physiological evidence of this effect is missing. The UPWINs seem to have a more complex function in behavioral control beyond memory recall. The fact that optogenetic UPWIN activation is leading to upwind orientation only in starved flies together with the fact that flies show a high returning probability even without any odor present suggests a functional role in state-dependent exploration behavior.

Reviewer #2 (Public Review):

Associative learning assigns valence to sensory cues paired with reward or punishment. Brain regions such as the amygdala in mammals and the mushroom body in insects have been identified as primary sites where valence assignment takes place. However, little is known about the neural mechanisms that translate valence-specific activity in these brain regions into appropriate behavioral actions. This study identifies a small set of upwind neurons (UpWiNs) in the Drosophila brain that receive direct inputs from two mushroom body output neurons (MBONs) representing opposite valences. Through a series of behavioral, imaging, and electrophysiological experiments, the authors show that UpWiNs are differentially regulated by the two MBONs, i.e., inhibited by the glutamatergic MBON-α1(encoding negative valence) while activated by the cholinergic MBON-α3 (encoding positive valence). They also show that UpWiNs control the wind-directed behavior of flies. Activation of UpWiNs is sufficient to drive flies to orient and move upwind, and inhibition of UpWiNs reduces flies' upwind movement toward the source of reward-predicting odors (CS+). These results, together with existing knowledge about the function of the mushroom body in memory processing, suggest an appealing model in which reward learning decreases and increases the responses of MBON-α1 and MBON-α3 to the CS+ odor, respectively, and these changes cause UpWiNs to respond more strongly to the CS+ odor and drive upwind locomotion. Interestingly, in the final part of the results, the authors reveal a wind-independent function of UpWiNs: increasing the probability that flies will revisit the site where UpWiNs were activated. Thus, UpWiNs guide learned reward-seeking behavior with and without airflow. Although the mushroom body has been extensively studied for its role in learning and memory, the downstream neural circuits that read the information from the mushroom body to guide memory-driven behaviors remain poorly characterized. This study provides an important piece of the puzzle for this knowledge gap.

Strength

1. Memory studies have predominantly relied on binary choice (go or no-go) assays as measures of memory performance. While these assays are convenient and efficient, they fall short of providing a comprehensive understanding of underlying behavioral structures. In an effort to overcome this limitation, the current study used video recording and tracking software to delve deeper into memory-guided behavior. This innovative approach allowed the authors to uncover novel neurons and examine their contribution to behavior with a level of detail not possible with binary choice assays.

2. This study used electron microscopy-based Drosophila hemibrain connectome data to reveal the synaptic connection between UpWiNs and MBON-α1 and MBON-α3. Using this method, the study shows that a single UpWiN receives direct input from both MBON-α1 and MBON- α3, which is confirmed by a functional imaging experiment. The connectome dataset also reveals several neurons downstream of UpWiNs, opening avenues for further research into the neural mechanisms linking memory and behavior.

Weakness

1. The authors repeatedly state in the manuscript that MBON-α1 and MBON-α3 convey appetitive or aversive memories, respectively. This assertion may not be entirely accurate. Evidence from sugar reward conditioning experiments suggests that MBON-α3 is potentiated and required for sugar reward memory retrieval. Therefore, the compartmentalization for appetitive and aversive memories appears not as obvious at the level of MBONs.

2. This study did not conclusively establish the importance of the MBON-α1/α3 to UpWiN pathways in memory-driven behavior. In the experiments shown in Figure 5, flies were trained to associate the activation of reward-related DANs with a specific odor (CS+). After conditioning, UpWiNs were observed to show enhanced responses to the CS+ odor. However, the results should be interpreted with caution because the driver line used to activate DANs (R58E02-LexAp65) labels not only DANs projecting to the MBON-α1 compartment, but all DANs in the protocerebral anterior medial (PAM) cluster. Thus, it remains unclear to what extent the observed enhanced responses are influenced by changes in inhibitory inputs from MBON-α1. While UpWiNs have been shown to play a critical role in the expression of sugar reward memory (Figure 7), it should be noted that UpWiNs receive inputs from multiple upstream neurons, making it difficult to accurately assess the contribution of MBON-α1/α3 to UpWiN pathways in UpWiN recruitment. Further research is needed to fully address this issue.

3. UpWind neurons (UpWiNs) were so named because their activation promotes upwind locomotion. However, when activated in the absence of airflow, flies show increased locomotor speed and an increased probability of revisiting the same location (Figure 7 and Figure 7-figure supplement 1). The revisiting behavior can be observed during the activation of UpWiNs, which is distinct from the local search behavior that typically begins after a reward stimulus is turned off (e.g., Gr64f-GAL4 results in Figure 7-figure supplement 1). Because revisiting a location can also be a consequence of repeated turns, it seems more accurate to describe UpWiNs as controlling the speed and likelihood of turns and promoting upwind movement by integrating with neurons that sense the direction of airflow.

Reviewer #3 (Public Review):

Aso et al. provide insight into how learned valences are transformed into concrete memory-driven actions, using a diverse set of proven techniques.

Here the authors use a four-armed arena to evaluate flies' preference for a reward-predicting odor and measure upwind locomotion. This behavioral paradigm was combined with the photoactivation of different memory-eliciting neurons, revealing that appetitive memories stored in different compartments of the mushroom bodies (center of olfactory memory) induce different levels of upwind locomotion. The authors then proceed to a non-exhaustive optogenetic screen of the neurons located downstream of the output neurons of the mushroom bodies (MBONs) and identify a group of 8-11 Cholinergic neurons promoting significant changes in upwind locomotion, the UpWins. By combining confocal immunolabelling of these neurons with electron microscope images, they manage to establish the UpWins' connectome within themselves and with the MBONs. Then, using two in vivo cell recording techniques, electrophysiology, and calcium imaging, they define that UpWins integrate both inhibitory and excitatory synaptic inputs from the MBONs encoding appetitive and aversive memory, respectively. In addition, they show that the UpWins' response to a reward-predicting odor is increased after appetitive training. On a behavioral level, the authors establish that the UpWins respond to wind direction only and are not involved in lower-level motor parameters, such as turning direction and acceleration. Finally, they demonstrate that the UpWins' activity is necessary for long-term appetitive memory retrieval, and even suggest a broader role for the UpWins in olfactory navigation, as their photoactivation increases the probability of revisiting behavior. In the end, the authors state that they provide new insights into how memory is translated into concrete behavior, which is fully supported by their data. Altogether, the authors present a pretty complete study that provides very interesting and reliable data, and that opens a new field of investigation into memory-driven behaviors.

Strengths of the study:

- To support their conclusions, the authors provide detailed data from different levels of analysis (behavioral, cellular, and molecular), using multiple sophisticated techniques.

- The measurement of multiple parameters in the behavioral analysis supports the strong changes in upwind locomotion. In addition, taken individually these parameters provide precise insights into how upwind locomotion changes, and allow the authors to more precisely define the role of the UpWins.

- The authors use split-Gal4 drivers instead of Gal4, allowing them to better refine neuron labelling.

The authors discussed and investigated all possible biases, making their data very reliable. For example, they demonstrated that the phenotypes observed in the behavioral assay were wind-directed behaviors and could not be explained by bias avoidance of the arena's center area.

Limitations of the study:

- In the absence of more precise drivers, the UpWins' labelling lacks precision. For example, there is no way to know exactly which UpWin is responding in the electrophysiological experiment presented in Figure 4.

- The screening of neurons located downstream of the MBONs is not exhaustive, meaning that other groups of neurons might be involved in memory-driven upwind locomotion. Although, it does not diminish the authors' conclusions.

- All data were obtained with walking flies. So far, there have been no experiments on flying flies.

Reviewer #1 (Public Review):

The authors present a PyTorch-based simulator for prosthetic vision. The model takes in the anatomical location of a visual cortical prostheses as well as a series of electrical stimuli to be applied to each electrode, and outputs the resulting phosphenes. To demonstrate the usefulness of the simulator, the paper reproduces psychometric curves from the literature and uses the simulator in the loop to learn optimized stimuli.

One of the major strengths of the paper is its modeling work - the authors make good use of existing knowledge about retinotopic maps and psychometric curves that describe phosphene appearance in response to single-electrode stimulation. Using PyTorch as a backbone is another strength, as it allows for GPU integration and seamless integration with common deep learning models. This work is likely to be impactful for the field of sight restoration.

However, one of the major weaknesses of the paper is its model validation - while some results seem to be presented for data the model was fit on (as opposed to held-out test data), other results lack quantitative metrics and a comparison to a baseline ("null hypothesis") model.<br /> - On the one hand, it appears that the data presented in Figs. 3-5 was used to fit some of the open parameters of the model, as mentioned in Subsection G of the Methods. Hence it is misleading to present these as model "predictions", which are typically presented for held-out test data to demonstrate a model's ability to generalize. Instead, this is more of a descriptive model than a predictive one, and its ability to generalize to new patients remains yet to be demonstrated.<br /> - On the other hand, the results presented in Fig. 8 as part of the end-to-end learning process are not accompanied by any sorts of quantitative metrics or comparison to a baseline model. The results seem to assume that all phosphenes are small Gaussian blobs, and that these phosphenes combine linearly when multiple electrodes are stimulated. Both assumptions are frequently challenged by the field. For all these reasons, it is challenging to assess the potential and practical utility of this approach as well as get a sense of its limitations.

Another weakness of the paper is the term "biologically plausible", which appears throughout the manuscript but is not clearly defined. In its current form, it is not clear what makes this simulator "biologically plausible" - it certainly contains a retinotopic map and is fit on psychophysical data, but it does not seem to contain any other "biological" detail. In fact, for the most part the paper seems to ignore the fact that implanting a prosthesis in one cerebral hemisphere will produce phosphenes that are restricted to one half of the visual field. Yet Figures 6 and 8 present phosphenes that seemingly appear in both hemifields. I do not find this very "biologically plausible".

Reviewer #2 (Public Review):

Van der Grinten and De Ruyter van Steveninck et al. present a design for simulating cortical-visual-prosthesis phosphenes that emphasizes features important for optimizing the use of such prostheses. The characteristics of simulated individual phosphenes were shown to agree well with data published from the use of cortical visual prostheses in humans. By ensuring that functions used to generate the simulations were differentiable, the authors permitted and demonstrated integration of the simulations into deep-learning algorithms. In concept, such algorithms could thereby identify parameters for translating images or videos into stimulation sequences that would be most effective for artificial vision. There are, however, limitations to the simulation that will limit its applicability to current prostheses.

The verification of how phosphenes are simulated for individual electrodes is very compelling. Visual-prosthesis simulations often do ignore the physiologic foundation underlying the generation of phosphenes. The authors' simulation takes into account how stimulation parameters contribute to phosphene appearance and show how that relationship can fit data from actual implanted volunteers. This provides an excellent foundation for determining optimal stimulation parameters with reasonable confidence in how parameter selections will affect individual-electrode phosphenes.

Issues with the applicability and reliability of the simulation are detailed below:

1) The utility of this simulation design, as described, unfortunately breaks down beyond the scope of individual electrodes. To model the simultaneous activation of multiple electrodes, the authors' design linearly adds individual-electrode phosphenes together. This produces relatively clean collections of dots that one could think of as pixels in a crude digital display. Modeling phosphenes in such a way assumes that each electrode and the network it activates operate independently of other electrodes and their neuronal targets. Unfortunately, as the authors acknowledge and as noted in the studies they used to fit and verify individual-electrode phosphene characteristics, simultaneous stimulation of multiple electrodes often obscures features of individual-electrode phosphenes and can produce unexpected phosphene patterns. This simulation does not reflect these nonlinearities in how electrode activations combine. Nonlinearities in electrode combinations can be as subtle the phosphenes becoming brighter while still remaining distinct, or as problematic as generating only a single small phosphene that is indistinguishable from the activation of a subset of the electrodes activated, or that of a single electrode.

If a visual prosthesis happens to generate some phosphenes that can be elicited independently, a simulator of this type could perhaps be used by processing stimulation from independent groups of electrodes and adding their phosphenes together in the visual field.

2) Verification of how the simulation renders individual phosphenes based on stimulation parameters is an important step in confirming agreement between the simulation and the function of implanted devices. That verification was well demonstrated. The end use a visual-prosthesis simulation, however, would likely not be optimizing just the appearance of phosphenes, but predicting and optimizing functional performance in visual tasks. Investigating whether this simulator can suggest visual-task performance, either with sighted volunteers or a decoder model, that is similar to published task performance from visual-prosthesis implantees would be a necessary step for true validation.

3) A feature of this simulation is being able to convert stimulation of V1 to phosphenes in the visual field. If used, this feature would likely only be able to simulate a subset of phosphenes generated by a prosthesis. Much of V1 is buried within the calcarine sulcus, and electrode placement within the calcarine sulcus is not currently feasible. As a result, stimulation of visual cortex typically involves combinations of the limited portions of V1 that lie outside the sulcus and higher visual areas, such as V2.

Reviewer #3 (Public Review):

The authors are presenting a new simulation for artificial vision that incorporates many recent advances in our understanding of the neural response to electrical stimulation, specifically within the field of visual prosthetics. The authors succeed in integrating multiple results from other researchers on aspects of V1 response to electrical stimulation to create a system that more accurately models V1 activation in a visual prosthesis than other simulators. The authors then attempt to demonstrate the value of such a system by adding a decoding stage and using machine-learning techniques to optimize the system to various configurations. While there is merit to being able to apply various constraints (such as maximum current levels) and have the system attempt to find a solution that maximizes recoverable information, the interpretability of such encodings to a hypothetical recipient of such a system is not addressed. The authors demonstrate that they are able to recapitulate various standard encodings through this automated mechanism, but the advantages to using it as opposed to mechanisms that directly detect and encode, e.g., edges, are insufficiently justified. The authors make a few mistakes in their interpretation of biological mechanisms, and the introduction lacks appropriate depth of review of existing literature, giving the reader the mistaken impression that this is simulator is the only attempt ever made at biologically plausible simulation, rather than merely the most recent refinement that builds on decades of work across the field. The authors have importantly not included gaze position compensation which adds more complexity than the authors suggest it would, and also means the simulator lacks a basic, fundamental feature that strongly limits it utility. Finally, the computational capacity required to run the described system is substantial and is not one that would plausibly be used as part of an actual device, suggesting that there may be difficulties with converting results from this simulator to an implantable system. With all of that said, the results do represent an advance, and one that could have wider impact if the authors were to reduce the computational requirements, and add gaze correction.

Review #1 Public Review:

This is an interesting study which attempts to assess the effect of the pandemic on diagnoses of pancreatic cancer. The authors have used a large national database to evaluate this, however, it should be noted that this database only captures 40% of the population in England. The authors have looked at specific parameters including Body Mass Index (BMI) as well as markers of diabetes and liver function. Only BMI had a difference in the frequency of measurements during the pandemic, presumably due to reduced face-to-face visits to allow weight and height to be captured.

Interestingly the authors noticed a reduction in surgery for pancreatic cancer by 25%, yet reported that there were no differences in the frequency of death within 6 months following the diagnosis of pancreatic cancer. The reduction in surgery is likely related at least in part to the loss of operating lists due to pandemic restrictions, however, this paper is not equipped to address another important possibility behind this, which is that pancreatic cancers were presenting too late for surgical intervention. It is not sufficient to comment that pancreatic cancer treatment was not affected by the pandemic based on the data presented on deaths within 6 months of the diagnosis of pancreatic cancer alone, as the median survival of patients diagnosed with pancreatic cancer within the pandemic has not been captured and compared to that of patients diagnosed in the preceding 5 years.

Therefore while the study can conclude no difference in pancreatic cancer diagnoses before and during the pandemic, more work needs to be done to truly assess if the pandemic had any effect on the outcomes from pancreatic cancer for patients diagnosed within this timeframe.

Reviewer #1 (Public Review):

This research aimed to discern the pattern of methylation changes that occur during aging, distinguishing between a unified specific mechanism and stochastic changes. To date, no unified hypothesis exists to guide our understanding of the changes in chromatin geography observed during the aging of cells. This work analysed six different types of purified blood-borne white blood cells allowing comparison across different immune cell subsets to determine if similar patterns occurred in all cell populations. Intriguingly, each subset exhibited its own distinct differential methylation rather than a single program. However, a core set of gene changes close to age-associated CpGs was identified suggesting that a central program existed, but that individual cell type function and metabolism shaped the overall chromatin landscape for the population. These findings establish a new framework for considering the aging process and open new questions about how the individual clocks of different populations might be regulated. While circulating cells are readily accessible for evaluation in humans, the majority of immune cells that regulate immune homeostasis are found within the tissues of the body. Whether these cells exhibit a similar profile to circulating cells or are rather shaped by their tissue or organ-specific ecosystem remains to be determined. In this setting, these tissue-resident cells are exposed to very different oxygen tensions and metabolic substrates. Furthermore, genes identified have been associated with aging, they concurrently appear to be associated with inflammation, thus it is not clear whether aging and low-grade inflammation are inherently linked, or whether these two pathways can be segregated. Thus a number of questions remain warranting further investigation.

Reviewer #2 (Public Review):

The authors utilized publicly available datasets to investigate age-related DNA methylation changes in six immune cell types. They identified 350 differentially methylated sites that were changing in the same directions among all cell types, while most of the differentially methylated sites were cell type-specific during aging. Further analyses of enriched pathways and motifs indicate that these DNA methylation changes may be induced by the fluctuations in oxygen availability.

Analyzing cell type-specific DNA methylation data and comparing cross-sectional and longitudinal datasets, the authors are able to identify age-associated DNA methylation sites that may be regulated by a common mechanism in aging. However, sex differences should be considered, and the proposed mechanism could spur future studies to test it.

Reviewer #3 (Public Review):

In this study, titled "Epigenetic signature of human immune aging: the GESTALT study," the authors reanalysed data from five highly purified human immune cell types from 55 healthy volunteers across a wide age range to characterize age-related changes in DNA methylation status. Additionally, they performed some integrative analyses with chromatin state and transcriptional data. Findings support that age-related DNA methylation changes are predominantly cell type-specific. Out of thousands of age-associated sites, only 350 sites were differentially methylated in the same direction in all cell types and validated in an independent longitudinal cohort. Some conserved changes exist, which appear to be underpinned by alterations in the hypoxia response, with linked enrichment of transcription factor binding motifs related to ARNT and REST. The authors conclude that DNA methylation changes in healthy aging may represent adaptive responses to fluctuations in oxygen availability.

Strengths:

- The study utilised data from a large cohort of individuals (n=55), with participants ranging in age from their 20s to 80s, providing a comprehensive age-related analysis.

- The data set reanalysed was based on highly purified cells rather than unfractionated PBMCs. This revealed the largely cell-type-specific nature of these changes and demonstrated that conflicting directional changes can cancel each other out, going undetected at the PBMC level.

- The authors were able to verify the DNA methylation changes that were conserved across cell types longitudinally in PBMCs by reanalyzing published datasets from the InCHIANTI study, adding robustness to their findings.

Weaknesses:

- The authors make statements in the abstract and manuscript that overreach the study's findings. Specifically, they claim that "DNA methylation changes in healthy aging may represent adaptive responses to fluctuations in oxygen availability." In reality, the study shows that a small minority of conserved DNA methylation changes across hematopoietic cell types appear to be driven by hypoxia response processes. The study does not demonstrate that hypoxia response processes account for a large proportion of DNA methylation changes or that these processes apply to non-hematopoietic cell types. These statements should be put into context relative to the study findings.

- The authors should make it clear in the introduction and methods section that this current study is merely reanalysing a data set they published before. Also, the authors should describe in the introduction the key findings of the initial analysis as presented in their 2021 Immunity publication.

- In some instances, the manuscript lacks citations to support claims.

Reviewer #1 (Public Review):

The authors convincingly show in this study the effects of the fas5 gene on changes in the CHC profile and the importance of these changes toward sexual attractiveness.

The main strength of this study lies in its holistic approach (from genes to behaviour) showing a full and convincing picture of the stated conclusions. The authors succeeded in putting a very interdisciplinary set of experiments together to support the main claims of this manuscript.

The main weakness stems from the lack of transparency behind the statistical analyses conducted in the study. Detailed statistical results are never mentioned in the text, nor is it always clear what was compared to what. I also believe that some tests that were conducted are not adequate for the given data. I am therefore unable to properly assess the significance of the results from the presented information. Nevertheless, the graphical representations are convincing enough for me to believe that a revision of the statistics would not significantly affect the main conclusions of this manuscript.

The second major problem I had with the study was how it brushes over the somewhat contradicting results they found in males (Fig S2). These are only mentioned twice in the main text and in both cases as being "similarly affected", even though their own stats seem to indicate otherwise for many of the analysed compound groups. This also should affect the main conclusion concerning the effects of fas5 genes in the discussion, a more careful wording when interpreting the results is therefore necessary.

Reviewer #2 (Public Review):

Insects have long been known to use cuticular hydrocarbons for communication. While the general pathways for hydrocarbon synthesis have been worked out, their specificity and in particular the specificity of the different enzymes involved is surprisingly little understood. Here, the authors convincingly demonstrate that a single fatty acid synthase gene is responsible for a shift in the positions of methyl groups across the entire alkane spectrum of a wasp, and that the wasps males recognize females specifically based on these methyl group positions. The strength of the study is the combination of gene expression manipulations with behavioural observations evaluating the effect of the associated changes in the cuticular hydrocarbon profiles. The authors make sure that the behavioural effect is indeed due to the chemical changes by not only testing life animals, but also dead animals and corpses with manipulated cuticular hydrocarbons.

I find the evidence that the hydrocarbon changes do not affect survival and desiccation resistance less convincing (due to the limited set of conditions and relatively small sample size), but the data presented are certainly congruent with the idea that the methyl alkane changes do not have large effects on desiccation.

Reviewer #3 (Public Review):

In this manuscript, the authors are aiming to demonstrate that a fatty-acyl synthase gene (fas5) is involved in the composition of the blend of surface hydrocarbons of a parasitoid wasp and that it affects the sexual attractiveness of females for males. Overall, the manuscript reads very well, it is very streamlined, and the authors' claims are mostly supported by their experiments and observations. However, I find that some experiments, information and/or discussion are absent to assess how the effects they observe are, at least in part, not due to other factors than fas5 and the methyl-branched (MB) alkanes. I'm also wondering if what the authors observe is only a change in the sexual attractiveness of females and not related to species recognition as well.

The authors explore the function of cuticular hydrocarbons (CHCs) and a fatty-acyl synthase in Nasonia vitripennis, a parasitic wasp. Using RNAi, they successfully knockdown the expression of the fas5 gene in wasps. The authors do not justify their choice of fatty-acyl synthase candidate gene. It would have been interesting to know if that is one of many genes they studied or if there was some evidence that drove them to focus their interest in fas5. The authors observe large changes in the cuticular hydrocarbons (CHC) profile of male and females. These changes are mostly a reduction of some MB alkanes and an increase in others as well as an increase of n-alkene in fas5 knockdown females. For males fas5 knockdowns, the overall quantity of CHC is increased and consequently, multiple types of compounds are increased compared to wild-type, with only one compound appearing to decrease compared to wild-type. Insects are known to rely on ratios of compounds in blends to recognize odors. Authors address this by showing a plot of the relative ratios, but it seems to me that they do show statistical tests of those changes in the proportions of the different types of compounds. In the results section, the authors give percentages while referring to figures showing the absolute amount of CHCs. They should also test if the ratios are significantly different or not between experimental conditions. Similar data should be displayed for the males as well. Furthermore, the authors didn't use an internal standard to measure the quantity of CHCs in the extracts, which, to me, is the gold standard in the field. If I understood correctly, the authors check the abundance measured for known quantities of n-alkanes. I'm sure this method is fine, but I would have liked to be reassured that the quantities measured through this method are good by either testing some samples with an internal standard, or referring to work that demonstrates that this method is always accurate to assess the quantities of CHC in extracts of known volumes.

The authors provide a sensible control for their RNAi experiments: targeting an unrelated gene, absent in N. vitripennis (the GFP). This allows us to see if the injection of RNAi might affect CHC profiles, which it appears to do in some cases in males, but not in females. The authors also show to the reader that their RNAi experiments do reduce the expression of the target gene. However, one of the caveats of their experiments, is that the authors don't provide evidence or information to allow the (non-expert) reader to assess whether the fas5 RNAi experiments did affect the expression of other fatty-acyl synthase genes. I'm not an expert in RNAi, so maybe this suggestion is not relevant, but it should, at least, be addressed somewhere in the manuscript that such off-target effects are very unlikely or impossible, in that case, or more generally.

The authors observe that the modified CHCs profiles of RNAi females reduce courtship and copulation attempts, but not antennation, by males toward live and (dead) dummy females. They show that the MB alkanes of the CHC profile are sufficient to elicit sexual behaviors from males towards dummy females and that the same fraction from extracts of fas5 knockdown females does so significantly less. From the previous data, it seems that dummy females with fas5 female's MB alkanes profile elicit more antennation than CHC-cleared dummy females, but the authors do not display data for this type of target on the figure for MB alkane behavioral experiments. Unfortunately, the authors don't present experiments testing the effect of the non-MB alkanes fractions of the CHC extracts on male behavior toward females. As such, they are not able to (and didn't) conclude that the MB-alkane is necessary to trigger the sexual behaviors of males. I believe testing this would have significantly enhanced the significance of this work. I would also have found it interesting for the authors to comment on whether they observe aggressive behavior of males towards females (live or dead) and/or whether such behavior is expected or not in inter-individual interactions in parasitoids wasps.

CHCs are used by insects to signal and/or recognize various traits of targets of interest, including species or groups of origin, fertility, etc. The authors claim that their experiments show the sexual attractiveness of females can be encoded in the specific ratio of MB alkanes. While I understand how they come to this conclusion, I am somewhat concerned. The authors very quickly discuss their results in light of the literature about the role of CHCs (and notably MB alkanes) in various recognition behaviors in Hymenoptera, including conspecific recognition. Previous work (cited by the authors) has shown that males recognize males from females using an alkene (Z9C31). As such, it remains possible that the "sexual attractiveness" of N. vitripennis females for males relies on them not being males and being from the right species as well. The authors do not address the question of whether the CHCs (and the MB alkanes in particular) of females signal their sex or their species. While I acknowledge that responding to this question is beyond the scope of this work, I also strongly believe that it should be discussed in the manuscript. Otherwise, non-specialist readers would not be able to understand what I believe is one of the points that could temper the conclusions from this work.

Reviewer #1 (Public Review):

"Melanocortin 1 receptor regulates cholesterol and bile acid metabolism in the liver" by Thapa et al. extends previous findings that MC1R global knockout mice have dysregulated lipid metabolism in APOE KO mice. The authors generated a hepatocyte-specific MC1R KO mouse to assess the hepatic effects of MC1R on the regulation of lipid metabolism. Thapa et al. go on to show that hepatic MC1R deletion leads to dyslipidemia and hepatic steatosis. The authors subsequently show that altered cholesterol homeostasis disrupts bile acid metabolism in hepatic MC1R KO mice. Finally, the authors provide data to suggest a role for AMPK in mediating the effects of MSH on hepatic cholesterol metabolism. The authors designed rigorous experiments using multiple different models (in vivo and in vitro) as well as different approaches (genetic and pharmacological).

The work described herein would have an impact on the field in multiple ways. Firstly, it demonstrates a novel metabolic role for MSH in the regulation of hepatic cholesterol metabolism. This may prove to be a viable therapeutic strategy for the treatment of dyslipidemia. Furthermore, the authors demonstrate an alternative signaling cascade elicited by MSH independent of cAMP, but rather relying on AMPK. This novel interaction between AMPK and MC1R could have more widespread implications beyond the control of hepatic cholesterol metabolism.

For the most part, the conclusions offered by the authors are supported by the data that is presented. There are, however, a number of concerns in the current version of this manuscript detailed below:

1) The authors demonstrate the expression of MC1R in hepatocytes through IHC staining and western blot analysis. Furthermore, the authors show an alteration in systemic bile acid homeostasis in MC1R KO mice. However, no mention of MC1R expression or function in cholangiocytes is discussed. This is important to assess both experimentally and within the discussion given the profound role of the biliary epithelium in modulating bile acid homeostasis. Furthermore, in figure 1 the authors validate the MC1R knockdown only through mRNA expression. Given panels A and C of figure 1 shows there is clearly a functional antibody for MC1R, validation of protein knockdown is needed.

2) Figure 2 demonstrates a steatotic effect of MC1R knockdown in hepatocytes. The authors attempt to provide mechanistic insight into this phenomenon through assessing the mRNA expression of genes involved in cholesterol and fatty acid synthesis. The data provided is modest at the gene level and no protein validation was provided to demonstrate functional alterations of these proteins in MC1R KO mice. Key proteins proposed such as SREBP2 and HMGCR need to be validated via a western blot of IHC analysis.

4) The authors suggest the involvement of AMPK in mediating the cholesterol-lowering effects of MSH. However, MSH is still able to lower free cholesterol levels even in the presence of an AMPK inhibitor. This suggests that MSH does not in fact rely on the activation of AMPK to elicit these cholesterol-lowering effects. The authors' conclusions are stronger than the actual data support. Furthermore, the authors claim LD211 phenocopies the effects of MSH in the presence of an AMPK inhibitor. However, the authors only measured the phosphorylation of Akt as their outcome. This begs the question, does LD211 still lower total cholesterol in the presence of AMPK inhibitors? This experiment is essential to conclude whether or not LD211 phenocopies the effects of MSH.

5) The authors initiate the project by showing high-fat diet disrupts the expression of MC1R. However, all of the subsequent experiments in hepatic MC1R KO mice are performed under normal chow. This begs the question of what is the phenotype of the hepatic MC1R KO mice fed a high-fat diet. Does KO of MC1R in the liver exacerbate HFD-induced obesity, glucose intolerance, and dyslipidemia? Inversely, can WT mice challenged with an HFD be rescued metabolically by treatment with either MSH or LD211? Providing data along these lines of investigation will provide physiological/clinical relevance to their findings.

Reviewer #2 (Public Review):

Keshav Thapa et al. investigated the role of melanocortin 1 receptor (MC1-R) in cholesterol and bile acid metabolism in the liver. First, they observed that MC1-R is present in the mouse liver and that its expression is reduced in response to a cholesterol-rich diet. To determine the role of MC1-R in the liver, they generated hepatocyte-specific MC1-R KO mice (L-Mc1r-/-). These animals exhibited a significant increase in liver weight, lipid accumulation, triglycerides and cholesterol levels, and fibrosis in comparison with control mice. By performing liquid chromatography-mass spectrometry, the authors also found that L-Mc1r-/- mice also have fewer bile acids in the plasma and faeces, but not in the liver. In accordance with these findings, mRNA/protein expression of different genes involved in these processes were altered in L-Mc1r-/- animals.

Secondly, in an attempt to evaluate the underlying mechanisms, they measured the expression of MC1-R in HepG2 cells under different treatments (i.e., palmitic acid, LDL, and atorvastatin). Moreover, they stimulated these cells with the endogenous MC1-R agonist - MSH, where they show that this molecule decreases the free cholesterol content, whereas increasing LDL and HDL uptake, as well as recapitulates some previously observed phenotypes in the proportions of bile acids. These effects were also encountered when using a selective agonist for MC1-R (i.e., LD211), further supporting the specific role of MC1-R. Finally, some experiments indicated that -MSH evokes not one single, but multiple intracellular signalling cascades for which MC1-R activation effects might take place.

Overall, this work provides novel and interesting findings on the role of MC1-R in cholesterol and bile acid metabolism in the liver, which undoubtedly will have some crucial implications for future research. Nevertheless, some experimental details should be better explained for the correct interpretation of the data. Besides, discrepant results exist regarding the molecular mechanisms behind MC1-R action that requires additional experimentation to support the conclusions drawn.

Reviewer #1 (Public Review):

The manuscript described the mechanism of Spermidine modulation of Src kinase on IDO1, accelerating the kinetics of the reaction. Spermidine can act on the backside of the SH2 domain of Src, by the interaction of specific amino acids. Considering the important role of IDO1 in the immune response the results provide proof of principle for the development of molecules that can modulate the kinase activity and the nonenzymatic functions of Src and IDO1 at once. The conclusions of this paper are mostly well supported by data, but some aspects of figure construction and data analysis need to be improved for the sake of clarity.

Reviewer #2 (Public Review):

Src is a well-studied non-receptor protein tyrosine kinase (PTK) with broad impacts on many signal transduction pathways. In this manuscript titled, "A Back-Door Insights into the modulation of Src kinase activity by the polyamine spermidine" Rossini et al investigated the mechanism of spermidine, a natural polyamine, in regulating Src tyrosine kinase activity and complex formation with IDO1, a known Src substrate. These data show a direct binding, and an allosteric binding site in the SH2 domain of Src, for spermidine. Interestingly, the manuscript also shows spermidine bound to Src promotes binding to IDO1, as well as its phosphorylation.

Overall, the molecular glue-like property of spermidine is an interesting finding. That Src substrate binding and phosphorylation for Src substrate is regulated by natural metabolites like spermidine is also a new and interesting finding. These discoveries further strengthen the idea to develop potential allosteric modulators for Src/PTK-mediated pathways.

Reviewer #3 (Public Review):

The manuscript by Rossini et al suggests an interesting novel mechanism for the regulation of tyrosine kinase Src by spermidine. The idea is interesting and some of the data suggest that spermidine may regulate Src activity. However, the manuscript suffers from multiple major shortcomings. The mechanism proposed by the authors is not supported by their studies. Authors tend to overinterpret data and overlook critical information that is missing. Some of the data is insufficient to support the statements that the authors make. Authors tend to use confusing nomenclature without clarifications making it difficult to interpret the data. The extent of Src activation by spermidine should be carefully evaluated by comparing it to the maximum activity of constitutively active Src. Furthermore, the biological significance of this regulation is not demonstrated. Only a few overexpression data are shown.

Reviewer #1 (Public Review):

The authors examine the role of the K700E mutation in the Sf3B1 splicing factor in PDAC and report that this Sf3B1 mutation promotes PDAC by decreasing sensitivity to TGF-b resulting in decreased EMT and decreased apoptosis as a result. They propose that the Sf3b1 K700E mutant causes decreased expression of Map3K7, a known mediator of TGFb signaling and also known to be alternately spliced in other systems by the Sf3b1 K700E mutation. The role of splicing defects in cancer is relatively understudied and could identify novel targets for therapeutic intervention so this work is of potential significance. However, the data is over-interpreted in many instances and it is not clear the authors can make the claims they do based on the data shown. In particular, the data showing that decreased Map3k7 underlies the effects of the Sf3b1K700E mutant is very weak. Does over-expression of Map3k7 promote the EMT signature and induce apoptosis? Do the Map3k7 expressing organoids form tumors more effectively when transplanted into mice? Also, the novelty of the work is a concern since aberrant Map3k7 splicing due to SF3B1 mutation was seen previously in other systems. The authors also do not address the apparent conundrum of Sf3b1 K700E mutation promoting tumorigenesis despite there being less EMT which is also required for progression to metastasis in PDAC.

Major Concerns.<br /> 1. The analysis of the effect of Sf3b1K700E expression on normal pancreas and on PanINs in KC mice and PDAC in KPC mice is superficial and could be enhanced by staining for amylase, cytokeratin-19 and insulin. In particular, the data quantified in figure 1L should be accompanied by staining for CK19, Mucin5AC or some other marker of ductal transformation. Also, are any effects seen at older ages in normal mice?<br /> 2. The invasion assays used are limited and should be complemented by more routine quantification of cell migration and invasion including such assays as a scratch assay, Boyden chamber assays and use of the IncuCyte system to quantify. As it stands the image in Figure 3B is difficult to interpret since it is very poorly described in the figure legend. Additional evidence is needed to make the claims made by the authors.<br /> 3. The authors should show the actual CC3 staining quantified in Suppl. Figure 2G.<br /> 4. The graph in Figure 3L should show WT and Sf3b1K700E expressing organoids number both with and without TGF-b.

Reviewer #2 (Public Review):

The manuscript has several areas of strength; it functionally explores a mutant that is detected in a portion of pancreatic cancers; it conducts mechanistic investigation and it uses human cell lines to validate the findings based on mouse models. Some areas for improvement are described below.

1) TGF-b is known to act as a tumor suppressor early in carcinogenesis, and as a tumor promoter later. The authors should extend their analysis of mouse models to determine whether the effect of SF3B1K700E is specific to promoting initiation (e.g. more, early acinar ductal metaplasia) or faster progression of PanINs following their formation. Another way to address this could be acinar cultures, to determine whether an increased propensity to ADM exists.

2) Given that the effect of SF3B1K700E expression is more prominent in KC mice, rather than in KPC mice, the authors should explain the rationale for using the latter for RNA sequencing.

3) Given that this mutation is found in about 3% of human pancreatic cancer, it would be interesting to know whether these tumors have any unique feature, and specifically any characteristic that could be harnessed therapeutically.

4) It would be interesting to know whether this mutation mutually exclusive to other mutations affecting response to TGF-b. Further, while the data might not be widely available, it would be interesting to know whether in human patients the mutation occurs in precursor lesions (PanIN might be difficult to assess, but IPMN might be doable) or at later stages.

Reviewer #3 (Public Review):

Alternative splicing as a result of mutations in different components of the splicing machinery has been associated with a variety of cancer types, including hematological malignancies where this has been most extensively studied but also for solid tumors such as breast and pancreatic ductal adenocarcinoma (PDAC). Here the authors analyze genome sequencing data in human PDAC samples and identify a recurring mutation in the SF3B1 subunit that substitutes lysine for glutamate at residue 700 (SF3B1K700E) in PDACs. This mutation has been identified and its' molecular role in disease progression in other diseases has been studied, but the mechanism for promoting disease progression in pancreatic cancer has not been as well characterized.

To study how SF3B1K700E contributes to PDAC pathology, the authors generate a novel genetically modified mouse model of a pancreas specific SF3B1K700E mutation and explore its oncogenicity and tumor promoting potential. The authors find that SF3B1K700E is not oncogenic, but potentiates the oncogenic potential of Kras and p53 (KP) driver mutations commonly found in PDAC tumors. The authors then proceed to characterize the molecular mechanisms that might drive this phenotype. By transcriptomic analysis, the authors find KP-SF3B1K700E tumors have downregulation of epithelial-to-mesenchymal transition (EMT) genes compared to KP tumors. The cytokine TGFβ has previously been found to limit PDAC initiation and progression by causing lethal EMT in PDAC and PDAC precursor cells. Thus, the authors propose SF3B1K700E inhibition of EMT blocks the tumor suppressive activity of TGFβ and this underpins the tumor promoting role of SF3B1K700E mutation in PDAC. Consistent with this finding, SF3B1K700E mutation blocks TGFβ-induced toxicity in a variety of cell culture models of PDAC and PDAC precursor models.

Lastly, the authors seek to identify how altered splicing reduces EMT activity in PDAC cells. The authors identify misspliced genes consistent in both KP and human SF3B1K700E mutant cancer samples and find Map3k7 as one of 11 consistently misspliced genes. MAP3K7 has previously been identified as a positive regulator of EMT. Thus the authors speculated Map3k7 missplicing would lead to reduced MAP3K7 activity and a reduction EMT and that this underpins the TGFβ in SF3B1K700E mutant PDAC cells. Consistent with this, the authors find inhibition of MAP3K7 reduces TGFβ toxicity in SF3B1K700E WT cells and overexpression of MAP3K7 in SF3B1K700E mutant PDAC cells induces TGFβ toxicity. Altogether, this suggests activity of Map3k7 is responsible for altered EMT activity and TGFβ sensitivity in SF3B1K700E mutant PDAC.

Altogether, the authors generate a valuable model to study the role of a recurring splicing mutation in PDAC and provide compelling evidence that this mutation is accelerates disease. The authors then perform both: (1) an open-ended investigation of how this mutation alters PDAC cell biology where they identify altered EMT activity and (2) rigorous mechanistic studies showing suppressed EMT provides PDAC cells with resistance to TGFβ, which has previously been shown to be tumor suppressive in PDAC, suggesting a possible mechanism by which SF3B1K700E mutation is oncogenic in PDAC that future animal studies can confirm. This work generates valuable models and datasets to advance the understanding of how mutations in the splicing machinery can promote PDAC progression and suggests alternative splicing of MAP3K7 is one such possible mechanism that altered splicing promotes PDAC progression in vivo.

- One major concern about the manuscript is that the proposed mechanism by which SF3B1K700E mutation accelerates PDAC progression (MAP3K7 inhibition -> EMT inhibition -> reduced TGFb toxicity) is only tested in ex vivo culture models and there is very limited and correlative data to suggest that this is the operative mechanism by which SF3B1K700E mutant tumors are accelerated. This is especially important because of recent findings that IFNa signaling, which the authors also found to be high in SF3B1K700E mutant tumors, also promotes PDAC progression (https://www.biorxiv.org/content/10.1101/2022.06.29.497540v1). Thus, while thoroughly convinced by the rigorous ex vivo work that SF3B1K700E does lead to MAP3K7 inhibition -> EMT inhibition -> reduced TGFb toxicity, further experiments to confirm this mechanism is critical in vivo would be needed to convince me that this mechanism is critical to tumor progression in vivo. For example, would forced expression of MAP3K7 slow orthotopic KP-SF3B1K700E tumor growth while leaving IFNa signaling unperturbed?

Reviewer #1 (Public Review):

This is a nice and elegant genetic study on the role of the Sgs1 and Exo1 factors involved in long DNA resection in the mechanism of double-strand break (DSB) repair by homologous recombination (HR). Most studies have focused on the need for these two factors for the long resection of a DSB to allow efficient HR. Now, this study shows that a major role of the function of long resection mediated by Sgs1 and Exo1 is to activate the DNA damage checkpoint to allow the chromosomal mobility needed to allow the DNA ends to find a distant homologous sequence with which repair via homologous recombination.

Reviewer #2 (Public Review):

A new study by Kimble et al. examines the role of extensive resection in DNA double-strand break repair. Formation of ssDNA at DNA breaks is initiated by Mre11-Rad50-Xrs2 and followed by Exo1 or Sgs1/Dna2, which form longer ssDNA. This ssDNA is used to load recombination and DNA damage checkpoint proteins. Some studies suggested that very short ssDNA by MRX complex is sufficient for DSB repair. Here, the authors look carefully at the role of extensive resection in DSB repair by gene conversion. To address this question they have constructed a large number of new recombination assays. They find that sgs1 exo1 mutants that lack extensive resection are capable of DSB repair when recombining loci are present on a single DNA molecule and within 50 kb from each other. When the template for DSB repair is further away on the same molecule or present on a different chromosome, the repair is reduced by 5-10 folds in the absence of extensive resection. The authors present data suggesting that this defect relates to slower repair kinetics between more distant homologous sequences and the need for a Mec1-mediated DNA damage checkpoint that requires extensive resection. The role of the checkpoint response is likely not limited to simple cell cycle arrest but may also be necessary for the mobility of a broken molecule. Partial suppression of the sgs1 exo1 repair defect is accomplished by activating the checkpoint using an artificial system colocalizing checkpoint proteins on a separate chromosome. Altogether the manuscript addresses an important question, is well-written, and presents interesting data.

Reviewer #3 (Public Review):

This manuscript aims to define the importance of long-range resection for homologous recombination, a relevant and yet unanswered question in the field of genome maintenance. The data shows that long-range resection is required for interchromosomal, but not intrachromosomal, recombination is well-developed and convincing. The claim that the DNA damage checkpoint is crucial for promoting distal recombination is interesting and founded on logical rationale. However, some key points about the proposed role of checkpoint signaling and the presented results need further clarification, mainly regarding the issue of checkpoint activation status in exo1Δ sgs1Δ cells and the attempts of using forced Rad53 activation to rescue interchromosomal recombination defects. Additional experiments would help solidify the proposed model. Nonetheless, the paper establishes the importance of long-range resection for distal recombination and should be considered a significant contribution to the field.

Reviewer #3 (Public Review):

The present study presents a comprehensive exploration of the distinct impacts of Isoflurane and Ketamine on c-Fos expression throughout the brain. To understand the varying responses across individual brain regions to each anesthetic, the researchers employ principal component analysis (PCA) and c-Fos-based functional network analysis. The methodology employed in this research is both methodical and expansive. Notably, the utilization of a custom software package to align and analyze brain images for c-Fos positive cells stands out as an impressive addition to their approach. This innovative technique enables effective quantification of neural activity and enhances our understanding of how anesthetic drugs influence brain networks as a whole.

The primary novelty of this paper lies in the comparative analysis of two anesthetics, Ketamine and Isoflurane, and their respective impacts on brain-wide c-Fos expression. The study reveals the distinct pathways through which these anesthetics induce loss of consciousness. Ketamine primarily influences the cerebral cortex, while Isoflurane targets subcortical brain regions. This finding highlights the differing mechanisms of action employed by these two anesthetics-a top-down approach for Ketamine and a bottom-up mechanism for Isoflurane. Furthermore, this study uncovers commonly activated brain regions under both anesthetics, advancing our knowledge about the mechanisms underlying general anesthesia.

Reviewer #1 (Public Review):

The authors performed a comparative study of the effect of the anesthetics isoflurane and ketamine on whole-brain network activation by mapping whole-brain c-fos expression in mice. Principle component analysis on the normalized Fos density showed opposite effects of the 2 anesthetics, consistent with top-down functioning for ketamine and bottom-up functioning for isoflurane. Based on the network analysis the authors suggest that isoflurane mediates anesthesia through a bottom-up mechanism activating subcortical regions and inactivating cortical regions with the locus coeruleus being the most important region while ketamine produced anesthesia through a top-down mechanism activating the cortex and subcortical nuclei with the somatosensory cortex as the most important region. Overall they show that these two anesthetics have two opposite mechanisms to induce unconsciousness, although they also have overlapping coactivation of central sleep-wake, pain, and neuroendocrine regulating areas. This manuscript highlights some interesting findings through interesting analysis. The results are likely to have a significant impact on the field of anesthesia but also on the much larger field of neuropsychopharmacology as the tools and analyses used in this report will be useful for researchers investigating the effects of any psychoactive drugs on the brain. However, there are several issues that should be addressed to support their conclusions. The two main issues of this report are the lack of behavioral/physiological measures of the depth of anesthesia produced by ketamine/isoflurane and inadequate data analysis/interpretations for some of the results.

Strengths<br /> Comparison of two different anesthetics<br /> Use of single-cell whole-brain imaging<br /> Advanced network analysis

Weaknesses<br /> Lack of behavioral/physiological measures<br /> Interpretation of the data is sometimes confusing/unclear<br /> Some statistical tests are missing and others are not controlled for multiple comparisons

Major concerns<br /> 1. The lack of behavioral/physiological measures of the depth of anesthesia (ventilation, heart rate, blood pressure, temperature, O2, pain reflexes, etc...) combined with the lack of dose-response and the use of different routes of administration makes the data difficult to interpret. Sure, there is a clear difference in network activation between KET and ISO, but are those effects due to the depth of the anesthesia, the route of administration, and the dose used? The lack of behavioral/physiological measures prevents the identification of brain regions responsible for some of the physiological effects and different effects of anesthetics.<br /> 2. Under anesthesia there should be an overall reduction of activity, is that the case? There is no mention of significantly downregulated regions. The authors use multiple transformations of the data to interpret the results (%, PC1 values, logarithm) without much explanation or showing the full raw data in Fig 1. It would be helpful to interpret the data to compare the average fos+ neurons in each region between treatment and control for each drug.<br /> 3. I do not understand their interpretation of the PCA analyses. For instance, in Fig 2 they claim that KET is associated with PC1 while ISO is associated with PC2. Looking at the distribution of points it's clear that the KET animals are all grouped at around +2.5 on PC1 and -2.0 on PC2, this means that KET is associated with both PC1 and PC2 to a similar degree (2 to 2.5). Moreover, I'm confused about why they use PCA to represent the animals/group. PCA is a powerful technique to reduce dimensionality and identify groups of variables that may represent the same underlying construct; however, it is not the best way to identify clusters of individuals or groups.<br /> 4. The actual metric used for the first PCA is unclear, is it the FOS density in each of the regions (some of those regions are large and consist of many subregions, how does that affect the analysis) is it the %-fos, or normalized cells? The wording describing this is variable causing some confusion. How would looking at these different metrics influence the analysis?<br /> 5. Based on Fig 3 the authors concludes that ISO activates the hypothalamic regions and inhibits the cortex, however, Fig 1 shows neither an activation of the hypothalamus in the ISO nor an inhibition of the cortex when compared to home cage control. If anything it suggests the opposite.<br /> 6. Control for isoflurane should be air in the induction chamber rather than home cage. It is possible that Fos activation reflects handling/stress pre-anesthesia in the animals, which would increase Fos expression in the stress-related regions such as the BST, striatum (CeA), hypothalamus (PVH) and potentially the LC.<br /> 7. In the Ket network there are a few anticorrelated regions, most of which are amongst the list of the most activated regions, does this mean that the strong correlation results from an overall decreased activation? And if so, is it possible that the ketamine anesthesia was stronger than the isoflurane, causing a more general reduction in activity?<br /> 8. Since they have established networks it would be easy and useful to look at how the different regions identified (sleep, pain, neuroendocrine, motor-related, ...) work together to maintain analgesia, are they within the same module? Do they become functionally connected and is this core network of functional connections similar for KET and ISO?<br /> 9. The naming of the function of some of the regions is very much debatable. For instance, PL/ILA are named "sleep-wakefulness regulation" regions in the paper. I can think of many more important functions of the PL/IL including executive functions, behavioral flexibility, and emotional control. It is unclear how the functions of all the regions were attributed. I am not sure that this biased labeling of structure-function is useful to the reports, it may instead suggest wrong conclusions.<br /> 10. A point of concern and confusion is the number of brain regions analyzed. In the introduction, it is mentioned that 987 brain regions are considered, but this is reduced to 53 selected brain regions in Figure 2, then 201 brain regions in Figure 3, and reduced again to 63 for the network analysis. The rationale for selecting different brain regions is not clear.<br /> 11. The statistical analysis does not seem appropriate considering the high number of comparisons. They use simple t-tests without correction for multiple comparisons.<br /> 12. There is no statistical analysis in Fig 2C,

Reviewer #2 (Public Review):

In this paper the authors aim to investigate brain-wide activation patterns following administration of the anesthetics ketamine and isoflurane, and conduct comparative analysis of these patterns to understand shared and distinct mechanisms of these two anesthetics.

To this end, they perform Fos immunohistochemistry in perfused brain section to label active nuclei, use a custom pipeline to register images to the ABA framework and quantify Fos+ nuclei, and perform multiple complementary analyses to compare activation patterns across groups.

This is an interesting line of research and a tour de force in brain-wide Fos quantification. However, there are several issues with the analysis, and overall integration that dampen my enthusiasm for the article in its current form.

Major comments:

1- The authors report 987 brain regions in the introduction, but I cannot find any analysis that incorporates these or even which regions they are. Very little rationale is provided for the regions included in any of the analyses and numbers range from 53 in Figure 1, to 201 in Figure 3, to 63 in Figure 6. It would help if the authors could first survey Fos+ counts across all regions to identify a subset that is of interest (significantly changed by either condition compared to control) for follow up analysis.

2- Different data transformations are used for each analysis. One that is especially confusing is the 'normalization' of brain regions by % of total brain activation for each animal prior to PCA analysis in Figures 2 and 3. This would obscure any global differences in activation and make it unlikely to observe decreases in activation (which I think is likely here) that could be identified using the Fos+ counts after normalizing for region size (ie. Fos+ count / mm3) which is standard practice in such Fos-based activity mapping studies. While PCA can be powerful approach to identify global patterns, the purpose of the analysis in its current form is unclear. It would be more meaningful to show that regional activation patterns (measured as counts/mm3) are on separate PCs by group.

3- Critical problem: The authors include a control group for each anesthetic (ketamine vs. saline, isofluorane vs. homecage) but most analyses do not make use of the control groups or directly compare Fos+ counts across the groups. Strictly speaking, they should have compared relative levels of induction by ketamine versus induction by isoflurane using ANOVAs. Instead, each type of induction was separate from the other. This does not account for increased variability in the ketamine versus isoflurane groups. There is no mention in the Statistics section or in Results section that any multiple comparison corrections were used. It appears that the authors only used Students t-test for each region and did not perform any corrections.

4- Figures 4 and 5 show brain regions 'significantly activated' following KET or ISO respectively, but again a subset of regions are shown and the stats seem to be t-tests with no multiple comparisons correction. It would help to show these two figures side by side, include the same regions, and keep the y axis ranges similar so the reader can easily compare the 'activation patterns' across the two treatments. Indeed, it looks like KET/Saline induced activation is an order or magnitude or two higher than ISO/Homecage. I would also recommend that this be the first data figure before any other analyses and maybe further analysis could be restricted to regions that are significantly changed in following KET or ISO here.

5- Analyses in Figure 6 and 7 are interesting but again the choice of regions to include is unclear and makes interpreting the results impossible. For example, in Figure 7 it is unclear why the list of regions in bar graphs showing Degree and Betweenness Centrality are not the same even within a single row?

Reviewer #2 (Public Review):

This represents an important study that demonstrates a high degree of heterogeneity within trailblazer cells in clusters that participate in collective migration. Solid methods highlight this heterogeneity and show that in TNBC cancers, trailblazer cells are defined by vimentin (and not Keratin 14) and are dependent on both TGFbeta and EGFR signaling. Additional, single cell studies would further support this work.

Strengths:

The paper highlights that collective migration, and the nature of trailblazer cells can be highly heterogeneous. This is important as it suggests that the ability to move between states may supersede a singular phenotype.

The paper uses animal models and organoids and in several areas attempts to correlate findings to human tissues.

The experiments are logically described.

Reviewer #1 (Public Review):

The study investigates the nature of "trailblazer" cells in distinct tumor models, including luminal B (MMTV/PyMT) and triple negative (TNBC) tumors (C3-TAg). The authors note that the trailblazer phenotypes in the TNBC model are more complex relative to the Luminal B model and represent distinct EMT programs associated with the expression of distinct EMT-TFs (Zeb1, Zeb2 and Fra-1). They demonstrated that of numerous EMT-TFs, Zeb1 and Fra-1 were required for increased cancer cell migration and invasion. They reveal that TGF-beta and EGF-mediated signaling are required for the diverse EMT states that are required for trailblazer cell activity and increased cell migration/invasion. TGF-beta signaling engaged Zeb 1 and Zeb2 while EGF signaling activated Fra-1. Indeed, inhibitors of either TGF-beta or EGF signaling could impair cell migration/invasion. While both pathways contributed to trailblazer phenotypes, EGF signaling was shown to interfere with certain TGF-beta induced transcriptional response, including the expression of genes encoding extracellular matrix proteins.

One concern was the heavy reliance of the C3-TAg as the sole TNBC model in which the distinct trailblazer phenotypes were described. The data in Fig. 3 of the submission reveals that the phenotypes observed in the C3-TAg model could be recapitulated in a TNBC patient-derived xenograft model (PDX). Using this PDX, the authors were able to show vimentin expression in lung metastatic TNBC cells that were intravascular, those that had extravasated and clusters of cancer cells fully within the lung parenchyma. This was an important addition to the manuscript. The additional experiments to investigate the role of Zeb1 and Zeb1 more fully, beyond the focus on Fra-1 in the initial submission was an additional strength of the new submission. Additional clarifications to the discussion also clarified the concepts articulated in the study. The study employs multiple breast cancer models, utilizes numerous in vitro and in vivo assessments of the trailblazer phenotypes, and the experimental design is rigorous and the interpretation of the data is sound. The manuscript will be of general interest to the research community.

Reviewer #3 (Public Review):

Cancer is a disease of many faces and in particular, the ability of cancers cells to change their phenotypes and cell behaviors - cancer cell plasticity - is a major contributor to cancer lethality and therapeutic challenge of treating this disease. In this study, Nasir, Pearson et al., investigate tumor cell plasticity through the lens of invasive heterogeneity, and in particular in models of triple-negative breast cancer (TNBC), a subtype of breast cancer with particularly poor clinical prognosis and more limited treatment modalities. Using organoid models in a variety of matrix systems, microscopy, and signaling pathway inhibitors, they find that invading TNBC breast tumors, primarily in the C31-Tag genetically engineered mouse model of TNBC, are composed of heterogeneous invasive/"trailblazer" type tumor cells that in many cases express vimentin, a classical intermediate filament marker of epithelial-mesenchymal transition, and reduced keratin-14, another filament marker of basal epithelial cells associated with collective invasion in different breast cancer models. Supportive genetic and pharmacologic evidence is provided that generation of these cells is TGF-beta signaling pathway driven, likely in vivo from the surrounding tumor microenvironment, in accord with published studies in this space. Another important aspect of this study is the good transcriptional evidence for multiple migratory states showing differing degrees of partial overlap with canonical EMT programs, dependent on TGF-beta, and suggestive but at present incomplete understanding of a parallel program involving Egfr/Fra-1 mediated effects on invasion. When taken in context with other recent studies (Grasset et al. Science Translational Medicine 2022), these data are broadly supportive of concept of targeting vimentin-dependent invasion programs in TNBC tumors.

The core conclusions of this paper are generally supported by the data, but there are some conceptual and technical considerations that should be taken into account when interpreting this study. Specific comments:

1) The contribution of the different vimentin-positive trailblazer cells to distant metastasis was not directly confirmed in vivo in this study. Given the limited proliferative potential of many fully EMT'd cells and in light of recent studies indicating that invasion can be uncoupled from metastatic potential, it seems important to directly test whether the different C31-tag isolates, varying in invasive potential in this study, produce metastases and if so do metastases abundance correlate with the invasive potential in 3D culture. The collection of lungs at 34 days post injection described in methods is too short to evaluate metastatic frequency.

2) The invasion of cancer cells is dependent on 3D matrix composition. In other studies, collective cancer invasion is performed in exclusively collagen type 1 gels or in other instances entirely in 3D reconstituted basement membrane gel, e.g. lung cancer invasion studies. In this study, the authors use a mixture composed of both matrices. Given the invasion suppressive effects of matrigel, particularly for epithelial type cells, further studies would be important to determine whether the invasion phenotypes seen in this study are generalizable across matrix environments.

3) TGF-beta is well known to induce EMT. Although this study identifies potential transcriptional mediators of the invasion/trailblazer program, is this program reversible?

Reviewer #1 (Public Review):

The goal of the manuscript is a joint analysis of genetic variation, open chromatin, and gene expression in a genetically diverse population of mouse embryonic stem cells.

This is an important manuscript that links gene expression to genetic variants and regions of open chromatin. The mechanisms of genetic gene regulation are essential to understanding how standing genetic variation translates to function and phenotype. This data set has the ability to add substantial insight into the field. In particular, the authors show how the relationships between variants, chromatin, and genes are spatially constrained by topologically associated domains.

The description of the results is hard to follow, specific terms are not well-defined, and the methods section lacks detail. Several fundamental approaches cannot be understood easily without going to references (particularly #6, #15, and #33). The manuscript will benefit from efforts to improve readability.

In addition, the CTCF binding data (ChIP-seq) gets too little attention. The fundamental question of whether regulatory domains vary between individuals is not directly addressed.

Reviewer #2 (Public Review):

The experiments described in the manuscript are well designed and executed. Most of the data presented are of high quality, convincing, and in general support the conclusions made in the manuscript. This manuscript should be of great interest to the field of mammalian gene regulation and the approaches used here can have broader applications in studying genetic and epigenetic regulations of gene expression. The key finding reported here, the importance of 3D chromatin structure in controlling gene expression, although not unexpected, offers a better understanding of the physiological roles of TADs.

Given the complexity of the data and analysis, some clarification is needed to guide readers to better understand the results.

Reviewer #1 (Public Review):

In this manuscript, the authors are building on their previous work showing Delta-Notch regulates the entrance and exit from embryo-larval quiescence of neural stem cells of the central brain (called CB neuroblasts (NB) (PMID: 35112131)). Here they show that continuous depletion of Notch in NBs from early embryogenesis leads to cycling NBs in the adult. This - cycling NBs in the adult - is not seen in controls. The assumption here is that these Notch-RNAi NBs in adults are those that did not undergo terminal differentiation in pupal development. The authors show that Notch is activated by its ligand Delta which is expressed on the GMC daughter cell and on cortex glia. They determine that the temporal requirement for Notch activity is 0-72 hours after larval hatching (ALH) (i.e., 1st instar through mid-3rd instar at 25C). In NBs/GMCs depleted for Notch, early temporal markers were still expressed at time points when they should be off and late markers were delayed in expression. These effects were observed in ~20-40% of NBs (Figures 5 and 6). Through mining existing data sets, they found that the early temporal factor Imp - an RNA binding protein - can bind Delta mRNA. They state that Delta transcripts decrease over time (without any reference to a Figure or to published work), leading to the hypothesis that Delta mRNA is repressed by the late temporal factors. Over-expressing late factors Syp or E93 earlier in development leads to downregulation of a Delta::GFP protein trap. These results lead to a model in which Notch regulates expression of early temporal factors and early temporal factors regulate Notch activity through translation of Delta mRNA.

There are several strengths of this study. The authors report rigorous measurements and statistical analyses throughout the study. Their conclusions are appropriate for the results. Data mining revealed an important mechanism - that Imp binds Delta mRNA - supporting the model that early temporal factors promote Delta expression, which in turn promotes Notch signaling.

There are also several weaknesses:<br /> 1. The activation of Notch in NBs by Delta in GMCs was already shown by this group in their Dev 2022 paper, reducing some of the impact of this study.<br /> 2. The authors do not explain their current results in context of their prior paper (2022 Dev) until the Discussion, but this would be useful to read in the Introduction. Similarly, it would be good to mention that in the 2022 paper, they find a significant number of wor>Notch RNAi NBs at 2 AHL that are cycling. Are the adult Notch RNAi in this study descended from those NBs at 2 hours ALH in the 2022 study? In other words, how does the early requirement for Notch between 0-72 hours ALH reported in the current study relate to the Notch-depleted NBs identified in the 2022 paper?<br /> 3. Most of the experiments rely upon continuous depletion of Notch from embryonic stage 8 until adulthood using the wor-GAL4 driver. There is no lineage tracing of this driver and there is no citation about the published expression pattern of this driver. The inclusion of these details is important for a broad audience journal.<br /> 4. Most of the experiments utilize a single RNAi transgene for Notch, Delta, Imp, Syp, E93. There are no experiments demonstrating the efficacy of the RNAi lines and no references to prior use and/or efficacy of these lines.

An appraisal: The authors use temperature shifts with Gal80TS to show that Notch is required between 0-72 hours ALH. They show with the use of known markers of the temporal factors and Delta protein trap, that Imp promotes Delta protein expression and the later temporal factors reduce Delta, although the molecular mechanisms are not clearly delineated. Overall, these data support their model that the reduction of Delta expression during larval development leads to a loss of Notch activity.

As noted in the Discussion, this study raises many questions about what Notch does in larval CB NBs. For example, does it inhibit Castor or Imp? Is Notch required in certain neural lineages and not others. These studies will be of interest in the community of developmental neurobiologists.

Reviewer #2 (Public Review):

Embryonic stem cells extensively proliferate to generate the necessary number of cells that are required for organogenesis, and their proliferation must be timely terminated to allow for proper patterning. Thus, timely termination of stem cell proliferation is critical for proper development. Numerous studies have suggested that cell-extrinsic changes in the surrounding niche environment drive the termination of stem cell proliferation. By contrast, cell-intrinsic mechanisms that terminate stem cell proliferation remain poorly understood. Fruit fly larval brain neuroblasts provide an excellent model for mechanistic investigation of intrinsic control of stem cell proliferation due to the wealth of information on molecular marks, gene functions and lineage hierarchy. Sood et al. conducted a genetic screen to identify genes that are required for the termination of neuroblast proliferation in metamorphosis and found that Notch and its ligand Delta contribute to their exit from cell cycle. They showed that knocking down Notch or delta function in larval neuroblasts allows them to persist into adulthood and remain proliferative when no neuroblasts can be detected in wild-type adult brains. By carrying out a well-designed temperature-shift experiment, the authors showed that Notch is required early during larval development to promote timely exit from cell cycle in metamorphosis. The authors went on to show that attenuating Notch signaling prolongs the expression of temporal identity genes castor and seven-up perturbing the switch from Imp to Syp/E93. Finally, they showed that knocking down Imp function or overexpressing E93 can restore the elimination of neuroblasts in Notch/delta mutant brains.

Overall, the experiments are well conceived and executed, and the data are clear. However, the data reported in this study represent incremental progress in improving our mechanistic understanding of the termination of neuroblast proliferation. Some of the data seem to represent more careful analyses of previously published observations described in the Zacharioudaki et al., Development 2016 paper while others seem to contradict to the results in this study. Gaultier et al., Sci. Adv. 2022 suggested that Grainyhead is required for the termination of neuroblast proliferation in a neuroblast tumor model, and grainyhead is a direct target of Notch signaling. Thus, Grainyhead should be a key downstream effector of Notch signaling in terminating castor and seven-up expression. Identical to Notch signaling, Grainyhead is also expressed through larval development. Grainyhead can function as a classical transcription factor as well as a pioneer factor raising the possibility that temporal regulation of neurogenic enhancer accessibility might be at play in allowing Notch signaling in early larval development to set up termination of castor and seven-up expression in metamorphosis. Diving deeper into how dynamic changes in chromatin in neurogenic enhancers affect the termination of neuroblast proliferation will significantly improve our understanding of termination of stem cell proliferation in diverse developing tissue.

Reviewer #3 (Public Review):

In this study, the authors investigate the effects of Notch pathway inactivation on the termination of Drosophila neuroblasts at the end of development. They find that termination is delayed, while temporal patterning progression is slowed down. Forcing temporal patterning progression in a Notch pathway mutant restores the correct timing of neuroblast elimination. Finally, they show that Imp, an early temporal patterning factor promotes Delta expression in neuroblast lineages. This indicates that feedback loops between temporal patterning and lineage-intrinsic Notch activity fine tunes timing of early to late temporal transitions and is important to schedule NB termination at the end of development.<br /> The study adds another layer of regulation that finetunes temporal progression in Drosophila neural stem cells. This mechanism appears to be mainly lineage intrinsic - Delta being expressed from NBs and their progeny, but also partly niche-mediated - Delta being also expressed in glia but with a minor influence. Together with a recent study (PMID: 36040415), this work suggests that Notch signaling is a key player in promoting temporal progression in various temporal patterning system. As such it is of broad interest for the neuro-developmental community.

Strengths<br /> The data are based on genetic experiments which are clearly described and mostly convincing. The study is interesting, adding another layer of regulation that finetunes temporal progression in Drosophila neural stem cells. This mechanism appears to be mainly lineage intrinsic - Delta being expressed from NBs and their progeny, but also partly niche-mediated - Delta being also expressed in glia but with a minor influence. A similar mechanism has been recently described, although in a different temporal patterning system (medulla neuroblasts of the optic lobe - PMID: 36040415). It is overall of broad interest for the neuro-developmental community.

Weaknesses<br /> The mechanisms by which Notch signaling regulates temporal patterning progression are not investigated in details. For example, it is not clear whether Notch signaling directly regulates temporal patterning genes, or whether the phenotypes observed are indirect (for example through the regulation of the cell-cycle speed). The authors could have investigated whether temporal patterning genes are directly regulated by the Notch pathway via ChIP-seq of Su(H) or the identification of potential binding sites for Su(H) in enhancers. A similar approach has been recently undertaken by the lab of Dr Xin Li, to show that Notch signaling regulates sequential expression of temporal patterning factors in optic lobes neuroblasts (PMID: 36040415), which exhibit a different temporal patterning system than central brain neuroblasts in the present study. As such, the mechanistic insights of the study are limited.

Reviewer #1 (Public Review):

The authors set out to investigate the hypothesis that mirror neurons in ventral premotor area F5 code actions in a common motor representation framework. To achieve this, they trained a linear discriminant classifier on the neural discharge of three types of action trials and test whether the thus trained classifier could decode the same categories of actions when observed. They showed that codes were fully matched for a small subset of neurons during the action epoch, while a wider set of "mirror neurons" showed only poorly matched codes for different epochs.

The authors controlled for potential visual object confounds by having identical objects be manipulated in three different ways and by having the animal carry out the motor execution in the dark. The main strength of the study lies in the clever decoding approach testing the matched tuning to behavioural categories in a model-free way. The central result is in the identification of the small sub-group of mirror neurons that show true matching during the execution epoch, which can dissociate the three types of action almost perfectly. This aligns well with some previous work while offering a novel avenue to identify and investigate those neurons.

The underlying neuronal mechanism and behavioural relevance of these neurons remain an open question. It would have been interesting to understand better whether the specific motor representations at a recording site, for instance identified through microstimulation prior to recording (see Methods), the reaction times on individual trials or the specific gaze targets (object/hand) had a bearing on the decoding performance for a neuron/trial. Ultimately, the uncovered matched mirror representations should in future experiments be tested with causal interventions and linked trial-by-trial to action selection performance.

The authors put the focus of their discussion on the wider, less well-matched neuronal pool to support an action selection framework, which is of course a valid view and well established in motor representations. From a sensory perspective, sparse coding, as suggested by the small group of "true" mirror neurons identified with the decoding approach, should also be considered as the basis for a possible neuronal mechanism. A particular strength of the paper is that it could give new data and impetus to the important discussion about how motor and sensory coding frameworks come together in cortical processing.

Reviewer #2 (Public Review):

The paper by Pomper and coworkers is an elegant neurophysiological study, generally sound from a methodological point of view, which presents extremely relevant data of considerable interest for a broad audience of neuroscientists. Indeed, they shed new light on the mirror mechanism in the primate brain, trying to approach its study with a novel paradigm that successfully controls for some important factors that are known to impact mirror neuron response, particularly the target object. In this work, a rotating device is used to present the very same object to the monkey or the experimenter, in different trials, and neurons are recorded while the monkey (motor response) or the experimenter (visual response) performed a different action (twist, shift, lift) cued by a colored LED.

The results show that there is a small set of neurons with congruent visual and motor selectivity for the observed actions, in line with classical mirror neuron studies, whereas many more cells showed temporally unstable matched or even completely non-matched tuning for the observed and executed actions. Importantly, the population codes allow to accurately decode both executed and observed actions and, to some extent, even to cross-decode observed actions based on the coding principles of the executed ones.

In my view, however, the original hypothesis that an observer understands the actions of others by the activation of his/her motor representations of the observed actions constitutes circular reasoning that cannot be challenged or falsified, as the author may want to claim. Indeed, 1) there is no causal evidence in the paper favoring or ruling out this hypothesis (and there couldn't be), 2) there is no independent definition (neither in this paper nor in the literature) of what "action understanding" should mean (or how it should be measured). Instead, the findings provide important and compelling evidence to the recently proposed hypothesis that observed actions are remapped onto (rather than matched with) motor substrates, and this recruitment may primarily serve, as coherently hypothesized by the authors, to select behavioral responses to others (at least in monkeys).

1) One of the main problems of this manuscript is, in my view, a theoretical one. The authors follow a misleading, though very influential, proposal, advanced since the discovery of mirror neurons: if there are (mirror) neurons in the brain of a subject with an action tuning that is matched between observation and execution contexts, then the subject "understands" the observed action. This is clearly circular reasoning because the "understanding" hypothesis uniquely derives from the neuron firing features, which are what the hypothesis should explain. In fact, there is no independent, operational definition of the term "understanding". Not surprisingly there is no causal evidence about the role of mirror neurons in the monkey, and the human studies that have claimed to provide causal evidence of "action understanding" ended up using, practically, operational definitions of "recognition", "match-to-sample", "categorization", etc. Thus, "action understanding" is a theoretical flaw, and there is no way "to challenge" a theoretical flaw with any methodologically sound experiment, especially when the flaw consists of circular reasoning. It cannot be falsified, by definition: it must simply be abandoned.<br /> On these bases, I strongly encourage the authors to rework the manuscript, from the title to the discussion, by removing any useless attempt to falsify or challenge a circular concept and, instead, constructively shed new light on how mirror neurons may work and which may be their functional role.

2) An important point to be stressed, strictly related to the previous one, concerns the definition of "mirror neuron". I premise that I am perfectly fine with the definition used by the authors, which is in line with the very permissive one adopted in most studies of the last 20 years in this field. However, it does not at all fulfill the very restrictive original criteria of the study in which "action understanding" concept was proposed (see Gallese et al. 1996 Brain): no response to object, no response to pantomimed action or tool actions, activation during execution in the dark and during the observation of another's action. If the idea (which I strongly disagree with) was to simply challenge a (very restrictive) definition of mirroring (a very out-of-date one, indeed, and different from the additional implication of "action understanding"), the original definition of this concept should be at least rigorously applied. In the absence of additional control conditions, only the example neuron in Figure 2A could be considered a mirror neuron according to Gallese et al. 1996. Permissive criteria implies that more "non-mirror" neurons are accepted as "mirror": simply because they are permissively named "mirror", does not imply they are mirroring anything as initially hypothesized (Example neuron in Fig 2B, for example, could be related to mouth, rather than hand, movements, since it responds strongly and similarly around the reward delivery also during the observation task, when the monkey should be otherwise still). Clearly, these concerns impact all the action preference analyses. To practically clarify what I mean, it should be sufficient to note that 74% (reported in this study) is the highest percentage ever reported so far in a study of neurons with "mirror" properties in F5 (see Kilner and Lemon 2013, Curr Biol) and it is similar to the 68% recently reported by these same authors (Pomper et al. 2020 J Neurophysiol) with very similar criteria. Clearly, there is a bias in the classification criteria relative to the original studies: again, no surprise if by rendering most of the recorded neurons "mirror by definition" then they don't "mirror" so much. I suggest keeping the authors' definition but removing the pervasive idea to challenge the (misleading) concept of understanding.

3) It would be useful to provide more information on the task. Panel B in Figure 1 is the unique information concerning the type of actions performed by the monkey and the experimenter. Although I am quite convinced of the generally low visuomotor congruence, there are no kinematics data nor any other evidence of the statement "the experimental monkey was asked to pay attention to the same actions carried out by a human actor". First, although the objects were the same, the same object cannot be grasped or manipulated in the same way by a human and a macaque, even just because of the considerable difference in the size of their hands; this certainly changes the way in which monkeys' and experimenter's hands interact with the same object, and this is a quantifiable (but not quantified) source of visuomotor difference between observed and executed actions and a potential source of reduced congruency. Second, there is little information about monkey's oculomotor behavior in the two conditions, which is known to affect mirror neuron activity when exploratory eye movements are allowed (Maranesi et al. 2013 Eur J Neurosci), potentially influencing the present findings: a {plus minus}7 (vertical) and {plus minus}5 (horizontal) window at 49 cm implies that the monkey could explore a space larger than 10 cm horizontally and 14 cm vertically, which is fine, but certainly leaves considerable freedom to perform different exploratory eye movements, potentially different among observed actions and hence capable to account for different "attention" paid by the monkey to different conditions and hence a source of neural variability, in addition to action tuning.

4) Information about error trials and their relationship with action planning. The monkey cannot really "make errors" because, despite the cue, each object can be handled in a unique way. The monkey may not pay attention to the cue and adjust the movement based on what the object permits once grasped, depending on online object feedback. From the behavioral events and the times reported in Table 1, I initially thought that "shift" action was certainly planned in advance, whereas "lift" and "twist" could in principle be obtained by online adjustments based on object feedback; nonetheless, from the Methods section it appears that these times are not at all informative because they seem to depend on an explicit constraint imposed by the experimenters (in a totally unpredictable way). Indeed, it is stated that "to motivate the monkey even more to use the LED in the execution task, another timeout was active in 30% (rarely up to 100%) of trials for the time period between touch of object to start moving the object: 0.15 (rarely 0.1) for a twist and shift, 0.35 (rarely 0.3s) for a lift". This is totally confusing to me; I don't understand 1) why the monkey needed to be motivated, 2) how can the authors be sure/evaluate that the monkeys were actually "motivated" in this way, and 3) what kind of motor errors the monkey could actually do if any. If there is any doubt that the monkeys did actually select and plan the action in advance based on the cue, there is no way to study whether the activity during action execution truly reflects the planned action goal or a variety of other undetermined factors, that may potentially change during the trials. Please clarify.

5) Classification analysis. There seems to be no statistical criterion to establish where and when the decoding is significantly higher than chance: the classifier performance should be formally analyzed statistically. I would expect that, in this way, both the exe-obs and the obs-exe decoding may be significant. Together with the considerations of the previous point 2 about the permissive inclusion criteria for mirror neurons, this is a remarkable (even quite unexpected) result, which would prove somehow contrary to what the authors claim in the title of the paper. The fact that in any classification the "within task" performance is significantly better than the "between task" performance does not appear in any way surprising, considering both the inclusive selection criteria for "mirror neurons" and the unavoidably huge different sources of input (e.g. proprioceptive, tactile, top-down, etc. afferences) between execution and observation. So, please add a statistical criterion to establish and show in the figures when and where the classifications are significantly above chance.

6) "As the concept of a mirror mechanism posits that the observation performance can be led back to an activation of a motor representation, we restricted this analytical step to a comparison of the exe-obs and the obs-obs discrimination performance". I don't understand the rationale of this choice. The so-called "concept" of mirror mechanism in classical terms posits that mirror neurons have a motor nature and hence their functioning during observation should follow the same principle as during action execution. But this logical consideration has never been demonstrated directly (it is indeed costated by several papers), and when motor neurons are concerned (e.g. pyramidal tract neurons, see Kraskov et al. 2009) their behavior during action observation is by far more complex (e.g. suppression vs facilitation) than that hypothesized for classical "mirror neurons". Furthermore, when across-task decoding for execution and observation code has been used, both in neurophysiological (e.g. Livi et al. 2019, PNAS) and neuroimaging (Fiave et al. 2018 Neuroimage) data, the visual-to-motor direction typical produce better performance than the opposite one. Thus, I don't see any good reason not to show also (if not even just) the obs-exe results. Furthermore, I wonder whether it is considered the possible impact of a rescaling in the single neuron firing rate across contexts, as the observation response is typically less strong than the execution response in basically all brain areas hosting neurons with mirror properties, and this should not impact on the matching if the tuning for the three actions remains the same (e.g. see Lanzilotto et al. 2020 PNAS). The analysis shown in Figures 4 and 5 is, for the rest, elegant and very convincing - somehow surprising to me, as the total number of "congruent" neurons (7.5%) is even greater than in the original study by Gallese et al. (5.4%).

7) The discussion may need quite deep revision depending on the authors' responses and changes following the comments; for sure it should consider more extensively the numerous recent papers on mirror neurons that are relevant to frame this work and are not even mentioned.

Reviewer #3 (Public Review):

Mirror neurons are a big deal in the neuroscience literature and have been for thirty years. I (and many others) remain skeptical of whether they serve the functions often attributed to them - specifically, whether they are motor planning neurons that contribute to understanding the actions of others. Testing their functions, therefore, is of great interest and importance. The present study, however, is not a cogent or convincing test. I do not think this study helps to answer the questions surrounding mirror neurons. It purports to provide a crucial test, that comes out mostly against the mirror neuron hypothesis, but the test has too many weaknesses to be convincing.

First, consider that the motor tuning and the visual tuning match "poorly." How poor or good must the match be before the mirror neuron hypothesis is rejected? I do not know, and the study does not help here. Even a "poor" match could contribute significantly to a social perception function.

Second, the results remind me in some ways of other multi-modal responses in the brain. For example, in the visual area MST, neurons are tuned to optic flow fields that imply specific directions of self-motion. Many of the same neurons are tuned to vestibular signals that also imply specific directions of self-motion. But the optic flow tuning and the vestibular tuning are not perfectly matched. There is considerable slop and complexity in how the two tunings compare within individual neurons. That complexity is not evidenced against multi-modal tuning. Instead, it suggests a hidden-layer complexity that is simply not fully understood yet. Just so here, the fact that the apparent motor tuning and apparent visual tuning match "poorly" is not evidence against both a motor planning and a visual encoding function.

Third, the animals are massively over-trained in three actions. They perform these actions and see them performed thousands of times toward the same object. Surely, if I were in the place of the monkey, every time I saw the object, I'd mentally imagine all three actions. As I saw a person act on the object, I'd mentally imagine the alternative two actions at the same time. Even if the mirror neuron hypothesis is strictly correct, this experiment might still find a confusion of signals, in which neurons that normally might respond mainly to one action begin to respond in a less predictable way during all three trial types.

Fourth, the experiment relies on a colored LED that acts as an instructional cue, telling the monkey which action to perform. What is to stop the neurons from developing a cue-sensitive response, as in classic studies from Steve Wise and others in the premotor cortex? Perhaps the neuronal signal that the experimenters are trying to measure is partly obscured by other, complex responses influenced in some manner by the instructional cue?

Fifth, finally, and most importantly, the fundamental problem with this study is that it is correlational. Studies that purport to test the function of a set of neurons, and do so by use of correlational measurements, cannot provide strong answers. There are always half a dozen different interpretations and caveats, such as the ones I raised here. Both sides of a debate can always spin the results, and the arguments are never resolved. To test the mirror neuron hypothesis properly would require a causal study. For example, lesion area F5 and test if the monkey is less able to discriminate the actions of others. Or, electrically microstimulate in area F5 and test if the stimulation interferes (either constructively or destructively) with the task of discriminating the actions of others. Only in this way will it be possible to answer the question: do mirror neurons functionally participate in understanding the actions of others? The present study does not answer that question.

Reviewer #1 (Public Review):

Cedillo et al. address the critically important question of how biguanides exert their positive effects on longevity using the powerful C. elegans model. Biguanides metformin and phenformin have been widely prescribed in the clinic to address metabolic challenges of diabetes; more recently the value of metformin in addressing specific cancers has emerged, and testing for impact on healthy human aging is getting underway. The need to understand the mechanism of biguanide action and the metabolic consequences of biguanide administration is clear.

The authors report that three genes that suppress longevity associated with metformin or phenformin treatment affect a common pathway for ether lipid biosynthesis; this ether lipid biosynthesis pathway is required for mitochondrial lifespan extension, eat-2 mediated dietary restriction longevity, and TOR inhibition-associated longevity, but not insulin pathway mediated longevity. Authors document with lipid profiling how ether lipids and some other lipids are impacted by phenformin vs. genetic disruption of ether lipid biosynthesis, define the tissue primarily responsible for the ether lipid biosynthesis, show that over-expression of enzyme fard-1 is sufficient to confer most of the phenformin effect, and implicate conserved stress transcription factor SKN-1 as a downstream outcome of the ether lipid change.

Strengths include the exploitation of the nematode model to address requirements not readily discerned in other models, the rigor of genetic documentation, the inclusion of metabolic profiling, the testing of multiple potential pathways that have been in the general discourse regarding metformin action, and the elaboration of a reasonably supported model that ether lipid biosynthesis is required for phenformin to activate longevity-promoting metabolic defenses downstream of conserved stress-responsive transcription factor SKN-1/NRF2. The novelty includes that ether lipids are directly linked to lifespan, ether lipid biosynthesis is needed for specific longevity pathways, and that ether lipids might play a role in a shift to pro-longevity metabolism.

There are some points that require clarification and could benefit from additional study, some wording and presentation issues, and a few missing points of potential discussion.

Overall, the data reported in this paper contribute a highly valuable advance in the biguanide field and adds stimulating hypotheses to the scientific community for moving forward in this biomedically important area.

Reviewer #2 (Public Review):

This manuscript pulls together a series of integrated genetic and metabolomic data sets to examine the molecular basis for biguanide action in C. elegans. Biguanides such as Metformin are important anti-diabetic drugs as well as being explored as a therapeutic mechanism for increasing human longevity. Understanding the molecular basis of biguanide action is of general interest to those in the ageing and age-related health fields as well as to those studying metabolism and obesity. The work here has been carried out in C. elegans but the work can be picked up by those working in mammalian systems. More could be done to highlight the conserved aspects of the mechanisms involved to assist with this translatability.

The methodology used is in general standard in the field and experiments are reported in detail. The successful use of metabolomics in C. elegans and its associated protocols is helpful as more labs expand to do this type of work.

Strengths: In general all the experiments presented are logical and well executed with the conclusions supported by the data. I am convinced that: 1) Metformin and Phenformin extend C. elegans lifespan (although that has previously been shown), 2) biguanides induce changes in ether lipids, 3) genes required for ether lipid biogenesis are required for the lifespan incurred with biguanide treatment and, in the case of fard-1 oe, can also promote longevity when levels are increased, 4) ether lipid biogenesis is also needed for other specific key longevity processes to extend lifespan, and 5) that some key ageing regulators (skn-1, aak-2 and daf-16) are required for fard-1 oe to extend lifespan.

Weaknesses: I was less convinced by the fat accumulation data and felt that the link between skn-1 gain of function and ether lipid genes was not clear and that the results were more correlative than mechanistic. If age-associated somatic depletion of fat is important for the lifespans seen here then this is interesting and important and identifying an epistatic, genetic link between the implicated genes and fat levels is desirable. Additionally, biguanides are reported to have major effects on the metabolism and growth of bacteria. As C. elegans grows on and eats E. coli, it is important that the biguanides in question do not alter the worm's food source. If bacterial growth is restricted or metabolically altered this would have a major impact on fat metabolism and the other outputs examined here (see Cabreiro et al 2013). Therefore the impact of these biguanide treatments on the C. elegans foods used here should be clearly addressed. Additionally, biguanide treatment is subject to dose dependence. Different concentrations of biguanide are used for different types of experiments to make correlative points e.g. growth inhibition at 160mM metformin, and metformin uptake measured in C. elegans treated with 50mM. It is not clear why, or whether this could impact the results. Can the authors be sure that these different doses do not alter metformin action and/or uptake either by the worms or the way the bacteria metabolise it? I appreciate that it is interesting and important to understand what biguanides are doing in the organism irrespective of whether this is a direct or indirect effect but knowing how the effects are achieved could be important for treatment strategies moving forwards.

Reviewer #1 (Public Review):

The authors expand upon prior findings and show that basolateral amygdala (BLA) activity is necessary for defensive responses elicited by both innate and learned threats. The authors also show that a projection from the auditory thalamus (MGM thalamic nucleus) mediates these effects.

Learned threats were modelled with auditory fear conditioning. The authors finding showing that the MGM-BLA pathway is required for auditory fear learning is largely a replication of prior results.

The novelty in this paper is that the authors show that the auditory MGM-BLA pathway is involved in defense evoked by a visual looming stimulus.

Overall, this is a reasonably designed study. The main weakness is that the loss of function manipulations use either caspase-induced lesions or contralateral chemogenetic disconnection studies, which lack temporal resolution.

Reviewer #2 (Public Review):

Khalil et al. aimed to gain insights into similarities and differences between circuits processing innate and learned threats. For this, they investigated a circuit that is well established to have a critical role in auditory associative threat learning, the projection from the medial geniculate nucleus (MGN) to the basolateral amygdala (BLA), and carried out a side-by-side comparison of its role in conditioned and innate threat.

Although the MGN is part of the main auditory stream, the neurons that project to BLA are multimodal. Khalil et al. took advantage of this to use visual looming stimuli to evoke innate threat. The authors showed that the MGN-BLA pathway processes both innate freezing responses to looming black circles and threat-conditioned freezing responses to tones. The disruption of the pathway impairs freezing in both cases, and the pathway is activated mostly in the presence of freezing. This suggests that the MGN-BLA processes threat independently of the sensory modality and of whether the threat is learnt or not. This further suggests that these different forms of threat may share similar mechanisms.

Nonetheless, the fact that MGN-BLA circuit disruptions were done during the conditioning phase of associative threat learning, and not during the recall phase only, complicates the side-by-side comparison: it could be argued that in this case what is disturbed is the processing of the unconditioned innately aversive stimulus in the task, the foot shock, instead of the learnt threat of the sound. Still, this would go in hand with one of the main conclusions of the study, which is that the MGN-BLA processes innate threats.

There are alternative interpretations of the results though, which are beyond the scope of the study: the circuit might be relevant for processing salient stimuli beyond threatening stimuli, for instance for positive valence stimuli as well; or this circuit might be relevant for processing the freezing response to threat in particular. To target the MGN-BLA circuit, the authors employ viral-vector mediated expression of proteins in mice. This way they delete, inhibit, or image either the activity of the neurons (or the axons) that project from MGN to BLA, or the BLA neurons themselves. They combine this with fiber-photometry and behavioural quantifications. Targeting these small and deep nuclei in the mouse brain bilaterally is challenging, which increases the value of the presented data. Conversely, it is important that the authors support more explicitly the specificity of their targeting methods and quantifications throughout the manuscript.

Overall, the main conclusions of this paper are mostly supported by data, but important methodological aspects need to be clarified, data analysis extended and the interpretation of results discussed further. The question of whether innate and learnt responses to stimuli share common mechanisms is timely. This study places the MGN-BLA pathway as a suitable model circuit to investigate this and paves the way for future work to dig into the implicated mechanisms.

Specific comments (strengths):<br /> a) The authors use two methods to interrupt the MGN-BLA pathway, a reversible one (chemogenetics) and an irreversible one (neuronal deletion via caspase 3 expression), obtaining consistent results that strengthen the evidence supporting their conclusions.<br /> b) The authors demonstrate the efficacy of their MGN-BLA pathway interruption methods with in vivo recordings.<br /> c) The approach of addressing the same behavioural output (freezing) in the two conditions (innate and learnt threat) helps the interpretability of results.

Specific comments (weaknesses):<br /> e) There are not enough analysis and method descriptions to demonstrate the specificity of the targeting approach, which is in some cases neither reflected in the pictures of the main figures. These include quantifications of the extension of expression/deletions in the brain and placement of viral-vector injections. In particular, these should show that i) protein expression does not extend beyond the BLA or MGN; ii) the MGN cells projecting to the striatum (right above the BLA) are not implicated, iii) that neurons in the visual thalamus are not affected by the manipulations. These are critical points that need to be addressed.<br /> f) There is a lack of digging into the mechanisms that could be enhanced with further analysis and discussion. For example, to start addressing this question, the authors administer blockers of beta-adrenergic receptors systemically. This reveals differences between MGN-BLA projecting neurons, BLA neurons, and innate and learnt threat, but the mechanistic implications are not clear and should be discussed. Also, the interpretation of the pathway's role in behaviour and its relation to neuronal activity could be deepened with further analysis.

Reviewer #3 (Public Review):

Khalil et al. investigated the role of medial geniculate nuclei -> basolateral amygdala pathway in the processing of innate and learned threats. Using looming stimuli and cued fear conditioning the authors show that both the BLA and MGN projections to the BLA respond to learned and innately threatening stimuli and that their activation is necessary to generate adequate fear responses. Lastly, Khalil et al. highlight a possible role of adrenergic signaling in modulating threat-induced BLA (but not MGN) activity. The manuscript is well conceived, the statistical analysis is solid, and the methodology is appropriate. The strength of this paper is that the hypothesis is tested using multiple experimental strategies that all nicely converge to demonstrate the involvement of the MGN-BLA pathway in threat processing. However, a more detailed analysis of fiber photometry data in relation to the presented stimuli and to behavioral responses would help to clarify whether this MGN-BLA pathway is involved in processing sensory stimuli per se or directly generates behavioral responses.

Reviewer #1 (Public Review):

It has been shown previously that there are relationships between a transdiagnostic construct of anxious-depression (AD), and average confidence rating in a perceptual decision task. This study sought to investigate these results, which have been replicated several times but only in cross-sectional studies. This work applies a perceptual decision-making task with confidence ratings and a transdiagnostic psychometric questionnaire battery to participants before and after an iCBT course. The iCBT course reduced AD scores in participants, and their mean confidence ratings increased without a change in performance. Participants with larger AD changes had larger confidence changes. These results were also shown in a separate smaller group receiving antidepressant medication. A similar sized control group with no intervention did not show changes.

The major strength of the study is the elegant and well-powered data set. Longitudinal data on this scale is very difficult to collect, especially with patient cohorts, so this approach represents an exciting breakthrough. Analysis is straightforward and clearly presented. However, no multiple comparison correction is applied despite many different tests. While in general I am not convinced of the argument in the citation provided to justify this, I think in this case the key results are not borderline (p<0.001) and many of the key effects are replications, so there are not so many novel/exploratory hypothesis and in my opinion the results are convincing and robust as they are. The supplemental material is a comprehensive description of the data set, which is a useful resource.

The authors achieved their aims, and the results clearly support the conclusion that the AD and mean confidence in a perceptual task covary longitudinally.

I think this study provides an important impact to the project of computational psychiatry.Sspecifically, it shows that the relationship between transdiagnostic symptom dimensions and behaviour is meaningful within as well as across individuals.

Reviewer #2 (Public Review):

The authors of this study investigated the relationship between (under)confidence and the anxious-depressive symptom dimension in a longitudinal intervention design. The aim was to determine whether confidence bias improves in a state-like manner when symptoms improve. The primary focus was on patients receiving internet-based CBT (iCBT; n=649), while secondary aims compared these changes to patients receiving antidepressants (n=82) and a control group (n=88).

The results support the authors' conclusions, and the authors convincingly demonstrated a weak link between changes in confidence bias and anxious-depressive symptoms (not specific to the intervention arm)

The major strength and contribution of this study is the use of a longitudinal intervention design, allowing the investigation of how the well-established link between underconfidence and anxious-depressive symptoms changes after treatment. Furthermore, the large sample size of the iCBT group is commendable. The authors employed well-established measures of metacognition and clinical symptoms, used appropriate analyses, and thoroughly examined the specificity of the observed effects.

However, due to the small effect sizes, the antidepressant and control groups were underpowered, reducing comparability between interventions and the generalizability of the results. The lack of interaction effect with treatment makes it harder to interpret the observed differences in confidence, and practice effects could conceivably account for part of the difference. Finally, it was not completely clear to me why, in the exploratory analyses, the authors looked at the interaction of time and symptom change (and group), since time is already included in the symptom change index.

This longitudinal study informs the field of metacognition in mental health about the changeability of biases in confidence. It advances our understanding of the link between anxiety-depression and underconfidence consistently found in cross-sectional studies. The small effects, however, call the clinical relevance of the findings into question. I would have found it useful to read more in the discussion about the implications of the findings (e.g., why is it important to know that the confidence bias is state-dependent; given the effect size of the association between changes in confidence and symptoms, is the state-trait dichotomy the right framework for interpreting these results; suggestions for follow-up studies to better understand the association).

Reviewer #3 (Public Review):

This study reports data collected across time and treatment modalities (internet CBT (iCBT), pharmacological intervention, and control), with a particularly large sample in the iCBT group. This study addresses the question of whether metacognitive confidence is related to mental health symptoms in a trait-like manner, or whether it shows state-dependency. The authors report an increase in metacognitive confidence as anxious-depression symptoms improve with iCBT (and the extent to which confidence increases is related to the magnitude of symptom improvement), a finding that is largely mirrored in those who receive antidepressants (without the correlation between symptom change and confidence change). I think these findings are exciting because they directly relate to one of the big assumptions when relating cognition to mental health - are we measuring something that changes with treatment (is malleable), so might be mechanistically relevant, or even useful as a biomarker?

This work is also useful in that it replicates a finding of heightened confidence in those with compulsivity, and lowered confidence in those with elevated anxious-depression.

One caveat to the interest of this work is that it doesn't allow any causal conclusions to be drawn, and only measures two timepoints, so it's hard to tell if changes in confidence might drive treatment effects (but this would be another study). The authors do mention this in the limitations section of the paper.

Another caveat is the small sample in the antidepressant group.

Some thoughts I had whilst reading this paper: to what extent should we be confident that the changes are not purely due to practice? I appreciate there is a relationship between improvement in symptoms and confidence in the iCBT group, but this doesn't completely rule out a practice effect (for instance, you can imagine a scenario in which those whose symptoms have improved are more likely to benefit from previously having practiced the task).

Relatedly, to what extent is there a role for general task engagement in these findings? The paper might be strengthened by some kind of control analysis, perhaps using (as a proxy for engagement) the data collected about those who missed catch questions in the questionnaires.

I was also unclear what the findings about task difficulty might mean. Are confidence changes purely secondary to improvements in task performance generally - so confidence might not actually be 'interesting' as a construct in itself? The authors could have commented more on this issue in the discussion.

To make code more reproducible, the authors could have produced an R notebook that could be opened in the browser without someone downloading the data, so they could get a sense of the analyses without fully reproducing them.

Rather than reporting full study details in another publication I would have found it useful if all relevant information was included in a supplement (though it seems much of it is). This avoids situations where the other publication is inaccessible (due to different access regimes) and minimises barriers for people to fully understand the reported data.

Reviewer #1 (Public Review):

The authors consider data by the Heisenberg group on rheological properties of non-confluent tissue in zebrafish embryos. These data had shown a steep increase and subsequent saturation in viscosity with cell density. The authors introduce a physical agent-based model of such tissues that accounts for the dispersion in cell size and the softness of the cells. The model is inspired by previous models to study glassy dynamics and reveals essential physical features that can explain the observed behavior. It goes beyond previous studies that had analysed the observations in terms of a percolation problem. The numerics are thoroughly done and could have a deep impact on how we describe non-confluent tissues.

A major weakness of the manuscript is the way it is written, which gives the impression to have been done rather carelessly. Several quantities are not properly introduced and at places physical jargon is used that makes the work difficult to access for readers without a background in soft matter.

Reviewer #2 (Public Review):

This paper explores how minimal active matter simulations can model tissue rheology, with applications to the in vivo situation of zebrafish morphogenesis. The authors explore the idea of active noise, particle softness and size heterogeneity cooperating to give rise to surprising features of experimental tissue rheologies (in particular an increase and then a plateau in viscosity with fluid fraction). In general, the paper is interesting from a theoretical standpoint, by providing a bridge between concepts from jamming of particulate systems and experiments in developmental biology. The idea of exploring a free space picture in this context is also interesting.

However, I'm still unsure right now though of how much it can be applied to the specific system that the authors refer to - which could be fixed either by considering other experimental systems/models reported in the recent literature or by doing the following theoretical checks:

- Take your current simulations and smoothly change the ratio of polydispersity from 8 to 0 to see exactly how much dispersity is needed to explain viscosity plateauing, and at which point the transition occurs.

- Cellular self-propulsion does not seem to play a role in zebrafish blastoderm, see Ref. [14]. Active noise has been proposed to play key roles in other systems and you could check whether such active noise could replace self-propulsion in your model, see for example Kim & Campas, Nat Phys, 2021.

- Could you simulate realistic rheological deformations to see how much they match both your expectation and the data?

Reviewer #3 (Public Review):

The authors successfully explain the sharp rise and subsequent saturation of the viscosity in dependence of cell packing fraction in zebrafish blastoderm with the help of a 2d model of soft deformable, polydisperse and self-propelled (active) disks. The main experimental observations can be reproduced and the unusual dependence of the viscosity on packing fraction can be explained by the available free area and the emergent motility of small sized cells facilitating multi-cell rearrangement in a highly jammed environment.

The paper is very well written, the results (experimental as well theoretical) are original and scientifically valid. This is an important contribution to understand rheological properties of non-confluent tissues linking equilibrium and transport properties.

Reviewer #1 (Public Review):

Many drugs have off-target effects on the gut microbiota but the downstream consequences for drug efficacy and side effect profiles remain unclear. Herein, Wang et al. use a mouse model of liver injury coupled to antibiotic and microbiota transplantation experiments. Their results suggest that metformin-induced shifts in gut microbial community structure and metabolite levels may contribute to drug efficacy. This study provides valuable mechanistic insights that could be dissected further in future studies, including efforts to identify which specific bacterial species, genes, and metabolites play a causal role in drug response. Importantly, although some pilot data from human subjects is shown, the clinical relevance of these findings for liver disease remain to be determined.

The major strength of this work is its scope, including detailed mouse phenotyping, inter-disciplinary methods, and numerous complementary experiments. The antibiotic depletion and FMT experiments provide support for a role of the gut microbiota in this mouse model.

A major limitation is the lack of studies narrowing down which microbes are responsible. Sequencing data is shown, but no follow-up studies are done with bacterial isolates or defined communities.

The link to GABA is also somewhat tenuous. While it does match the phenotypic data, there are no targeted experiments in which GABA producing microbial communities/strains are compared to a control community/strain. As such, it seems difficult to know how much of the effects in this model are due to GABA vs. other metabolites.

My major recommendation would be to revise the title, abstract, and discussion to provide more qualification and to consider alternative interpretations.

Some key controls are also missing, which could be addressed by repeat experiments in the mouse model. The antibiotic depletion experiment would be improved by testing the effect of antibiotics in the absence of metformin, to see if the effect is just driven by the model itself as opposed to an interaction between metformin and antibiotics. The FMT experiment lacks a control group and suffers from pseudoreplication: multiple donors from metformin treated and untreated mice could be used to colonize separate groups of recipient mice.

Reviewer #2 (Public Review):

The authors examine the use of metformin in the treatment of hepatic ischemia/reperfusion injury (HIRI) and suggest the mechanism of action is mediated in part by the gut microbiota and changes in hepatic ferroptosis. While the concept is intriguing, the experimental approaches are inadequate to support these conclusions.

The histological and imaging studies were considered a strength and reveal a significant impact of metformin post-HIRI.

Weaknesses largely stem from the experimental design. First, use of the iron chelator DFO would be strengthened using the ferroptosis inhibitor, liproxstatin. Second, the impact of metformin on the microbiota is profound resulting in changes in bile acid, lipid, and glucose homeostasis. Throughout the manuscript no comparisons are made with metformin alone which would better capture the metformin-specific effects. Lastly, the absence of proper controls including germ free mice, metformin treated mice, FMT treated mice, etc make it difficult to understand the outcomes and to properly reproduce the findings in other labs.

Overall, while the concept is interesting and has the potential to better understand the pleiotropic functions of metformin, the limitations with the experimental design and lack of key controls make it challenging to support the conclusions.

Reviewer #3 (Public Review):

The study presented in this paper explores the role of gut microbiota in the therapeutic effect of metformin on HIRI, as supported by fecal microbiota transplantation (FMT) experiments. Through high throughput sequencing and HPLC-MS/MS, the authors have successfully demonstrated that metformin administration leads to an increase in GABA-producing bacteria. Moreover, the study provides compelling evidence for the beneficial impact of GABA on HIRI.

Reviewer #1 (Public Review):

This manuscript provides important evidence on the association between sleep regularity and mortality in the UK Biobank, which is a popular topic in recent sleep and circadian research in population-based studies. The analysis reported robust associations between sleep irregularity and increased total, CVD and cancer mortality, and provided evidence to support the role of sleep and circadian health in disease progression and longevity in human populations. The Sleep Regularity Index (SRI) used in this study is a novel metric that quantifies the consistency in rest-activity rhythms over consecutive 24 hour periods, thus providing objective assessment of potential circadian disruption. The study is based on a large accelerometer study with validated follow-up of incident diseases and deaths. The data quality and large sample size strengthen the credibility of the conclusion. Overall, the analyses are appropriately done and the manuscript is clearly written. Additional justification for the assessment of nonlinearity and further subgroup analyses would further improve the manuscript.

Reviewer #2 (Public Review):

This interesting research commendably revealed the association between sleep regularity and mortality. However, as authors acknowledged, the analysis can not accurately identify the cause and effect. In my opinion, the causality is important for this topic, cuz, sleep regularity and health (e.g. chronic disease) were long-term simultaneous status, especially given the participants are older. I suggest that the author could utilize MR analysis to find out for more evidence.

Joint Public Review

In the presence of predators, animals display attenuated foraging responses and increased defensive behaviors that serve to protect them from potential predatory attacks. Previous studies have shown that the basolateral nucleus of the amygdala (BLA) and the periaqueductal gray matter (PAG) are necessary for the acquisition and expression of conditioned fear responses. However, it remains unclear how BLA and PAG neurons respond to predatory threats when animals are foraging for food. The authors employed single-unit recording of BLA and PAG neurons and optogenetic tools to address this question in an 'approach food-avoid predator' paradigm.

The authors observed that rats exhibited a significant increase in the latency to obtain the food pellets and a reduction in the pellet success rate when the predator robot was activated. A subpopulation of PAG neurons showing increased firing rate in response to the robot activation did not change its activity in response to food pellet retrieval during the pre- or post-robot sessions. Optogenetic stimulation of PAG neurons increased the latency to procure the food pellet in a frequency- and intensity-dependent manner, similar to what was observed during the robot test. Combining optogenetics with single-unit recordings, the authors demonstrated that photoactivation of PAG neurons increased the firing rate of 10% of BLA cells. A subsequent behavioral test in three of these same rats demonstrated that BLA neurons responsive to PAG stimulation displayed higher firing rates to the robot than BLA neurons nonresponsive to PAG stimulation. Next, because the PAG does not project monosynaptically to the BLA, the authors used a combination of retrograde and anterograde neural tracing to identify possible regions that could convey robot-related information from PAG to the BLA. They observed that neurons in specific areas of the paraventricular nucleus of the thalamus (PVT) that are innervated by PAG fibers contained neurons that were retrogradely labeled by the injection of CTB in the BLA. In addition, PVT neurons showed increased expression of the neural activity marker cFos after the robot test, suggesting that PVT may be a mediator of PAG signals to the BLA.

Strengths

Overall, the idea that the PAG interacts with the BLA via the midline thalamus during a predator vs. foraging test is new and quite interesting. The authors have used appropriate tools to address their questions. The major impact in the field would be to add evidence to claims that the BLA can be downstream of the dPAG to evoke defensive behaviors. The study also adds to a body of evidence that the PAG mediates primal fear responses.

Weaknesses

The two most significant weaknesses relate to a) anatomical concerns related to the subregions of the BLA and PAG that were targeted by manipulations and analyses and b) the correlational nature of the PVT measures and the lack of any causal role demonstrated. Other concerns are also detailed below.

Anatomical concerns:

1. The authors claim that the recordings were performed in the dorsal PAG (dPAG), but the histological images in Fig. 1B and Supplementary S2 for example show the tip of the electrode in a different subregion of PAG (ventral/lateral). They should perform a more careful histological analysis of the recording sites and explain the histological inclusion and exclusion criteria. Diagrams showing the sites of all PAG and BLA recordings, as well as all fiber optics, would be helpful.<br /> 2. Prior studies investigating the role of BLA neurons during a foraging vs. robot test similar to the one used in this study should be also cited and discussed (e.g., Amir et al 2019, PMID: 30840520; Amir et al 2015, PMID: 26400931). These two studies demonstrated that most neurons in the basal portion of the BLA exhibit inhibitory activity during foraging behavior and only a small fraction of neurons (~4%) display excitatory activity in response to the robot (in contrast to the 25% reported in the present study). A very accurate histological analysis of BLA recording sites should be performed to clarify whether distinct subregions of the BLA encode foraging and predator-related information, as previously shown in the two described studies.<br /> 3. An important claim of this study that the PAG sends predator-related signals to BLA via the PVT (Fig. 4). The authors stated that PVT neurons labeled by intra-BLA injection of the retrograde tracer CTB were activated by the predator, but a proper immunohistochemical quantification with a control group was not provided to support this claim. To provide better support for their claim, the authors should quantify the double-labeled PVT neurons (cFos plus CTB positive neurons) during the robot test.<br /> 4. The AVV anterograde tracer deposit spread to a large part of the PAG, including dorsolateral and lateral PAG, and supraoculomotor regions (Fig. 4B). Is the projection to the PVT from the dPAG or other regions of the PAG?

Concerns about the strength of the evidence supporting a role for the PVT:

5. The authors conclude in the discussion section that the dPAG-amygdala pathway is involved in generating antipredatory defensive behavior. However, the current results are entirely based on correlational analyses of neural firing rate and there is no direct demonstration that the PAG provides information about the robot to the BLA. Therefore, the authors should tone down their interpretation or provide more evidence to support it by performing experiments applying inhibitory tools in the dPAG > PVT > BLA pathway and examining the impact on behavior and downstream neural firing.

Other concerns:

6. One of the main findings of this study is the observation that BLA neurons that are responsive to PAG photostimulation are preferentially recruited during the foraging vs. robot test (Fig. 3). However, the experimental design used to address this question is problematic because the laser photostimulation of PAG neurons preceded the foraging vs. robot test. Prior photoactivation of PAG may have caused indirect short-term synaptic plasticity in BLA cells, which would favor the response of these cells to the robot. Please see Oishi et al, 2019 PMID: 30621738, which demonstrated that 10 trains of 20Hz photoactivation (300 pulses each) was sufficient to induce LTP in brain slices.<br /> 7. The authors should perform a longitudinal analysis of the behavioral responses of the rats across the trials to clarify whether the animals habituate to the robot or not. In Figure 1E, it appears that PAG neurons fire less across the trials, which could be associated with behavioral habituation to the predator robot. If that is the case, the activity of many other PAG and BLA neurons will also most likely vary according to the trial number, which would impact the current interpretation of the results.<br /> 8. In Figure 1, it is unclear why the authors compared the activity of neurons that respond to the robot activation against the activity of the neurons during the retrieval of the food pellets in the pre-robot and post-robot sessions. The best comparison would be aligning the cells that were responsive to the activation of the robot with the moment in which the animals run back to the nest after consuming the pellets during the pre-robot or post-robot sessions. This would enable the authors to demonstrate that the PAG responses are directly associated with the expression of escaping behavior in the presence of the robot rather than associated with the onset of goal-directed movement in direction to the next during the pre- and post-robot sessions. A graphic showing the correlation between PAG firing rate and escape response would be also informative.

Reviewer #1 (Public Review):

This EEG study probes the prediction of a mechanistic account of P300 generation through the presence of underlying (alpha) oscillations with a non-zero mean. In this model, the P300 can be explained by a baseline shift mechanism. That is, the non-zero mean alpha oscillations induce asymmetries in the trial-averaged amplitudes of the EEG signal, and the associated baseline shifts can lead to apparent positive (or negative) deflections as alpha becomes desynchronized at around P300 latency. The present paper examines the predictions of this model in a substantial data set (using the typical P300-generating oddball paradigm and careful analyses). The results show that all predictions are fulfilled: the two electrophysiological events (P300, alpha desynchronization) share a common time course, anatomical sources (from inverse solutions), and covariations with behaviour; plus relate (negatively) in amplitude, while the direction of this relationship is determined by the non-zero-mean deviation of alpha oscillations pre-stimulus (baseline shift index, BSI). This is indicative of a tight link of the P300 with underlying alpha oscillations through a baseline shift account, at least in older adults, and hence that the P300 can be explained in large parts by non-zero mean brain oscillations as they undergo post-stimulus changes.

Reviewer #2 (Public Review):

The authors attempt to show that event-related changes in the alpha band, namely a decrease in alpha power over parieto/occipital areas, explain the P300 during an auditory target detection task. The proposed mechanism by which this happens is a baseline-shift, where ongoing oscillations which have a non-zero mean undergo an event-related modulation in amplitude which then mimics a low frequency event-related potential. In this specific case, it is a negative-mean alpha-band oscillation that decreases in power post-stimulus and thus mimics a positivity over parieto-occipital areas, i.e. the P300. The authors lay out 4 criteria that should hold if indeed alpha modulation generates the P300, which they then go about providing evidence for.

Strengths:<br /> - The authors do go about showing evidence for each prediction rigorously, which is very clearly laid out. In particular, I found the 3rd section connecting resting-state alpha BSI to the P300 quite compelling.<br /> - The study is obviously very well-powered.<br /> - Very well-written and clearly laid out. Also, the EEG analysis is thorough overall, with sensible analysis choices made.<br /> - I also enjoyed the discussion of the literature, albeit with certain strands of P300 research missing.

Weaknesses:<br /> In general, if one were to be trying to show the potential overlap and confound of alpha-related baseline shift and the P300, as something for future researchers to consider in their experimental design and analysis choices, the four predictions hold well enough. However, if one were to assert that the P300 is "generated" via alpha baseline shift, even partially, then the predictions either do not hold, or if they do, they are not sufficient to support that hypothesis. This general issue is to be found throughout the review. I will briefly go through each of the predictions in turn:

1. The matching temporal course of alpha and P300 is not as clear as it could be. Really, for such a strong statement as the P300 being generated by alpha modulation, one would need to show a very tight link between the signals temporally. There are many neural and ocular signals which occur over the course of target detection paradigms: P300, alpha decrease, motor-related beta decrease, the LRP, the CNV, microsaccade rate suppression etc. To specifically go above and beyond this general set of signals and show a tighter link between alpha and P300 requires a deeper comparison. To start, it would be a good idea to show the signals overlapping on the same plot to really get an idea of temporal similarity. Also, with the P300-alpha correlation, how much of this correlation is down to EEG-related issues such as skull thickness, cortical folding, or cognitive issues such as task engagement? One could perhaps find another slow wave ERP, e.g. the Lateralised Readiness Potential, and see if there is a similar strength correlation. If there is not, that would make the P300 relationship stand out.

In Figure 3, it is clear that alpha binning does not account for even 50% of the variance of P300 amplitude. Again, if there is such a tight link between the two signals, one would expect the majority of P300 variance to be accounted for by alpha binning. As an aside, the alpha binning clearly creates the discrepancy in the baseline period, with all alpha hitting an amplitude baseline at approx. 500ms. I wonder if could you NOT, in fact, baseline your slow wave ERP signal, instead using an appropriate high pass filter (see "EEG is better left alone", Arnaud Delorme, 2023) and show that the alpha binning creates the difference in ERP at the baseline which then is reinterpreted as a P300 peak difference after baselining.

2. The topographies are somewhat similar in Figure 4, but not overwhelmingly so. There is a parieto-occipital focus in both, but to support the main thesis, I feel one would want to show an exact focus on the same electrode. Showing a general overlap in spatial distribution is not enough for the main thesis of the paper, referring to the point I make in the first paragraph re Weaknesses. Obviously, the low density montage here is a limitation. Nevertheless, one could use a CSD transform to get more focused topographies (see https://psychophysiology.cpmc.columbia.edu/software/csdtoolbox/), which apparently does still work for lower-density electrode setups (see Kayser and Tenke, 2006).

3. Very nice analysis in Figure 6, probably the most convincing result comparing BSI in steady state to P300, thus at least eliminating task-related confounds.

4. Also a good analysis here, wherein there seem to be similar correlation profiles across P300 and alpha modulation. One analysis that would really nail this down would be a mediation analysis (Baron and Kenny, 1986; https://davidakenny.net/cm/mediate.htm), where one could investigate if e.g. the relationship between P300 amplitude and CERAD score is either entirely or partially mediated by alpha amplitude. One could do this for each of the relationships. To show complete mediation of P300 relationship with a cog task via alpha would be quite strong.

One last point, from the methods it appears that the task was done with eyes closed? That is an extremely important point when considering the potential impact of alpha amplitude modulation on any other EEG component due to the well-known substantial increase in alpha amplitude with eyes closed versus open. I wonder, would we see any of these effects with eyes opened?

Overall, there is a mix here of strengths of claims throughout the paper. For example, the first paragraph of the discussion starts out with "In the current study, we provided comprehensive evidence for the hypothesis that the baseline-shift mechanism (BSM) is accountable for the generation of P300 via the modulation of alpha oscillations." and ends with "Therefore, P300, at least to a certain extent, is generated as a consequence of stimulus-triggered modulation of alpha oscillations with a non-zero mean." In the limitations section, it says the current study speaks for a partial rather than exhausting explanation of the P300's origin. I would agree with the first part of that statement, that it is only partial. I do not agree, however, that it speaks to the ORIGIN of the P300, unless by origin one simply means the set of signals that go to make up the ERP component at the scalp-level (as opposed to neural origin).

Again, I can only make these hopefully helpful criticisms and suggestions because the paper is very clearly written and well analysed. Also, the fact that alpha amplitude modulation potentially confounds with P300 amplitude via baseline shift is a valuable finding.

Reviewer #1 (Public Review):

The present study by Berger et al. analyzes to what extent memory formation is dependent on available energy reserves. This has been dealt with extensively in the case of aversive memory formation, but only very sparsely in the case of appetitive memory formation. It has long been known that an appetitive memory in flies can only be formed by starvation. However, the authors here additionally show that not only the duration of starvation plays a role, but also determines which form of memory (short- or long-term memory) is formed. The authors demonstrated that internal glycogen stores play a role in this process and that this is achieved through insulin-like signaling in octopaminergic reward neurons that integrates internal energy stores into memory formation. Here, the authors suggest that octopamine plays a role as a negative regulator of different forms of memory.

The study sheds light on an old question, to what extent the octopaminergic neuronal system plays a role in the formation of appetitive memory, since in recent years only the dopaminergic system has been in focus. Furthermore, the data are an interesting contribution to the ongoing debate whether insulin receptors play a role in neurons themselves or in glial cells. The experiments are very well designed and the authors used a variety of behavioural experiments, genetic tools to manipulate neuronal activity and state-of-the-art imaging techniques. In addition, they not only clearly demonstrated that octopamine is a negative regulator of appetitive memory formation, but also proposed a mechanism by which the insulin receptor in octopaminergic neurons senses the internal energy status and then controls the activity of those neurons. The conclusions are mostly supported by the data, but some aspects related to the experimental design, some explanations and literature references need more clarification and revision.

1. Usually, long-term memory (LTM) is tested 24 hours after training. Here, the authors usually refer to LTM as a memory that is tested 6 hours after training. The addition of a control experiment to show that LTM that the authors observe here lasts longer would increase the power of this study immensely.

2. The authors define here another consolidated memory component as ARM, when they applied a cold-shock 2 hours after training. However, some publications showed that LTM is formed after only one training cycle (Krashes et al 2008, Tempel et al 1983). This makes it difficult to determine, whether appetitive ARM can be formed. Furthermore, one study showed that appetitive ARM is absent after massed training (Colomb et al 2009). Therefore, the conclusion could be also, that different starvation protocols, would lead to different stabilities of LTM. Therefore, additional experiments could help to clarify this opposing explanation. From these results, it can then be concluded either that different stable forms of LTM are formed depending on the starvation state, or that two differently consolidated memory phases (LTM, ARM) are formed, as has already been shown for aversive memory. This is also important for other statements in the manuscript, and therefore the authors should address this. For example, the findings about the insulin receptor (is it two opposing memories or different stabilities of LTM).

Reviewer #2 (Public Review):

How organism physiological state modulates establishment and perdurance of memories is a timely question that the authors aimed at addressing by studying the interplay between energy homeostasis and food-related conditioning in Drosophila. Specifically, they studied how starvation modulates the establishment of short-term vs long-term memories and clarified the role of the monoamine Octopamine in food-related conditioning, showing that it is not per se involved in formation of appetitive short-term memories but rather gates memory formation by suppressing LTM when energy levels are high. This work clarifies previously described phenotypes and provides insight about interconnections between energy levels, feeding and formation of short-term and long-term food-related memories. In the absence of population-specific manipulation of octopamine signaling, it however does not reach a circuit-level understanding of how these different processes are integrated.

Strengths<br /> - Previous studies have documented the impact of Octopamine on different aspects of food-related behaviors (regulation of energy homeostasis, feeding, sugar sensing, appetitive memory...), but we currently lack a clear understanding of how these different functions are interconnected. The authors have used a variety of experimental approaches to systematically test the impact of internal energy levels in establishment of appetitive memory and the role of Octopamine in this process.

- The authors have used a range of approaches, performed carefully controlled experiments and produced high quality data.

Weaknesses<br /> 1- In the tbh mutant flies, Tyramine -to- Octopamine conversion is inhibited, resulting not only in a lack of Octopamine, but also in elevated levels of Tyramine. If and how elevated levels of Tyramine contributes to the described phenotypes is unclear. In the current version of the manuscript, only one set of experiments (Figure 2) has been performed using Octopamine agonist. This is particularly important in light of recent published data showing that starvation modifies Tyramine levels.

2- Octopamine (and its precursor Tyramine) have been implicated in numerous processes, complicating the analysis of the phenotypes resulting from a general inhibition of tbh.

3- The manuscript explores various aspects of the impact of energy levels on food-related behaviors and the underlying sensing and effector mechanism, both in wild-type and tbh mutants, making it difficult to follow the flow of the results.

Reviewer #3 (Public Review):

In this manuscript, Berger et al. study how internal energy storage influence learning and memory. Since in Drosophila melanogaster, octopamine (OA) is involved in the regulation of energy homeostasis they focus on the roles of OA. To do so they use the tyramine-β-hydroxylase (Tbh) mutant that is lacking the neurotransmitter OA and study short term memory (STM), long-term memory (LTM) and anesthesia-resistant memory (ARM). They show that the duration of starvation affects the magnitude of both short- and long-term memory. In addition, they show that OA has a suppressive effect on learning and memory. In terms of energy storage, they show that internal glycogen storage influences how long sucrose is remembered and high glycogen suppresses memory. Finally, they show that insulin-like signaling in octopaminergic neurons, which is also related to internal energy storage, suppresses learning and memory.

This is an important study that extends our knowledge on OA activity in learning and memory and the effects the metabolic state has on learning and memory. The authors nicely use the genetic tools available in flies to try and unravel the complex circuitry of metabolic state level, OA activity and learning and memory.<br /> Nevertheless, I do have some comments that I think require attention:

1. The authors use RNAi to reduce the level of glycogen synthase or glycogen phosphorylase. These manipulations are expected to affect the level of glycogen. Using specific drivers the authors attempt to manipulate glycogen level at the muscles and fat bodies and examine how this affects learning and memory. The conclusions of the authors arise solely from the manipulation intended (i.e. the genetics). However, the authors also directly measured glycogen levels at these organs and those do not follow the manipulation intended, i.e. the RNAi had very limited effect on the glycogen level. Nevertheless, these results are ignored.

2. The authors claim in the summary that OA is not required for STM. However, according to one experiment OA is required for STM as Tbh mutants cannot form STM. In another experiment OA is suppressive to STM as wt flies fed with OA cannot form STM. Therefore, it is very difficult to appreciate the actual role of OA on STM.

3. The authors use t-test and ANOVA for most of the statistics, however, they did not perform normality tests. While I am quite sure that most datasets will pass normality test, nevertheless, this is required.

4. While it is logical to assume that OA neurons are upstream to R15A04 DA neurons, I am not sure this really arises from the experiment that is presented here. It is well established that without activity in R15A04 DA neurons there is no LTM. Since OA acts to decrease LTM, can one really conclude anything about the location of OA effect when there is no learning?

5. It is unclear how expression of a dominant negative form of insulin receptor (InR) in OA neurons can rescue the lack of OA due to the Tbh mutation. If OA neurons cannot release anything to the presumably downstream DA neurons, how can changing their internal signaling has any effect?

While I stressed some comments that need to be addressed, the overall take-home message of the manuscript is supported and the authors do show that the metabolic state of the animal affects learning and memory. I do think though, that some more caution is required for some of the conclusions.

Reviewer #1 (Public Review):

She et al studied the evolution of gene expression reaction norms when individuals colonise a new environment that exposes them to physiologically challenging conditions. Their objective was to test the "plasticity first" hypothesis, which suggest that traits that are already plastic (their value changes when facing a new environment compared to the original environment) facilitates the colonisation of novel environments, which, if true, would be predicted to result in the evolution of gene expression values that are similar in the population that colonised the new environment and evolved under these particular selection pressures. To test this prediction, they studied gene expression in cardiac and muscle tissues in individuals originating from three conditions: lowland individuals in their natural environment (ancestral state), lowland individuals exposed to hypoxia (the plastic response state), and a highland population facing hypoxia for several generations (the coloniser state). They classified gene expression patterns as maladaptive or adaptive in lowland individuals responding to short term hypoxia by classifying gene expression patterns using genes that differed between the ancestral state (lowland) and colonised state (highland). Genes expressed in the same direction in lowland individuals facing hypoxia (the plastic state) as what is found in the colonised state are defined as adaptative, while genes with the opposite expression pattern were labelled as maladaptive, using the assumption that the colonised state must represent the result of natural selection. Furthermore, genes could be classified as representing reversion plasticity when the expression pattern differed between the plasticity and colonised states and as reinforcement when they were in the same direction (for example more expressed in the plastic state and the colonised state than in the ancestral state). They found that more genes had a plastic expression pattern that was labelled as maladaptive than adaptive. Therefore, some of the genes have an expression pattern in accordance with what would be predicted based on the plasticity-first hypothesis, while others do not.

As pointed out by the authors themselves, the fact that temperature was not included as a variable, which would make the experimental design much more complex, misses the opportunity to more accurately reflect the environmental conditions that the colonizer individuals face at high altitude. Also pointed out by the authors, the acclimation experiment in hypoxia lasted 4 weeks. It is possible that longer term effects would be identifiable in gene expression in the lowland individuals facing hypoxia on a longer time scale. Furthermore, a sample size of 3 or 4 individuals per group depending on the tissue for wild individuals may miss some of the natural variation present in these populations. Stating that they have a n=7 for the plastic stage and n= 14 for the ancestral and colonized stages refers to the total number of tissue samples and not the number of individuals, according to supplementary table 1.

Impact of the work:

There has been work showing that populations adapted to high altitude environments show changes in their hypoxia response that differs from the short-term acclimation response of lowland population of the same species. For example, in humans, see Erzurum et al. 2007 and Peng et al. 2017, where they show that the hypoxia response cascade, which starts with the gene HIF (Hypoxia-Inducible Factor) and includes the EPO gene, which codes for erythropoietin, which in turns activates the production of red blood cell, is LESS activated in high altitude individuals compared to the activation level in lowland individuals (which gives it its name). The present work adds to this body of knowledge showing that the short-term response to hypoxia and the long term one can affect different pathways and that acclimation/plasticity does not always predict what physiological traits will evolve in populations that colonize these environments over many generations and additional selection pressure (UV exposure, temperature, nutriment availability).

Altogether, this work provides new information on the evolution of reaction norms of genes associated with the physiological response to one of the main environmental variables that affects almost all animals, oxygen availability. It also provides an interesting model system to study this type of question further in a natural population of homeotherms.

Erzurum, S. C., S. Ghosh, A. J. Janocha, W. Xu, S. Bauer, N. S. Bryan, J. Tejero et al. "Higher blood flow and circulating NO products offset high-altitude hypoxia among Tibetans." Proceedings of the National Academy of Sciences 104, no. 45 (2007): 17593-17598.

Peng, Y., C. Cui, Y. He, Ouzhuluobu, H. Zhang, D. Yang, Q. Zhang, Bianbazhuoma, L. Yang, Y. He, et al. 2017. Down-regulation of EPAS1 transcription and genetic adaptation of Tibetans to high-altitude hypoxia. Molecular biology and evolution 34:818-830.

Reviewer #2 (Public Review):

This is a well-written paper using gene expression in tree sparrow as model traits to distinguish between genetic effects that either reinforce or reverse initial plastic response to environmental changes. Tree sparrow tissues (cardiac and flight muscle) collected in lowland and highland populations subject to hypoxia treatment were profiled for gene expression and compared in 1) highland birds; 2) lowland birds under normal conditions to test for differences in directions of changes between initial plastic response and subsequent colonized response.

The authors clarified several points and made revisions according to my comments. It is good to know that the highland and lowland samples were collected and processed at the same time and the previous publication reported part of the data. My concerns regarding the conclusions about reversal versus reinforcement remain even after the additional analyses. Further studies are needed to confirm these results.

Reviewer #1 (Public Review):

The authors were seeking to improve understanding of how wind and wave action affect the use of energetically demanding wing flapping and running by albatross engaged in takeoff flight. To accomplish this in the complex and challenging environment in which albatross live, the authors sought to use accelerometry and geographic positioning to infer patterns of locomotion, flight orientation relative to the prevailing wind, and wave height during takeoff.

The major strength of the methods and results is that the use of accelerometry and novel interpretations of data from a geographic positioning system provides new insight into the use of waves by albatross and how the effects of wave magnitude interact with wind to modulate energy demands during takeoff. Weaknesses of the approach are due to the challenging environmental conditions in which albatross live. The interpretation of accelerometry data was not validated using a subset of the sample synchronized with video (prior validation was cited for shearwaters). The interpretation of wind direction relative to flight path is based on the behavior of the bird without concurrent measures of local wind velocity.

The authors achieved their aims, and their results support their conclusions.

Although it is generally understood that albatross and many other birds choose to takeoff into the wind to reduce energetic costs, the authors provide novel quantitative data on this behavior. Their results on the effects of wave height and the interactions between wave height and wind provide novel insight into how albatross harvest energy from their complicated and dynamic environment to reduce the energy they must output to get into the air. In particular, the new insight into the effects of wave height should revise understanding among ornithologists, ocean ecologists and those who study the mechanics of animal locomotion. The use of accelerometry and geographic positioning systems to measure flight behavior and ocean ecology should inspire other researchers to adopt similar methods.

Albatross live in a complex and poorly understood environment that is likely to be threatened by climate change. This research provides worthwhile new insight into how wind and wave action affect takeoff in albatross, and can therefore improve insight into how changes in these variables with climate change may affect the distribution of albatross populations.

Reviewer #2 (Public Review):

The authors used cutting-edge bio-telemetry technology to decipher the roles of wind speed and wave height on the take-off of albatrosses from the water surface. They revealed that each of these factors contributes to take-off in a unique way with interesting interactions of the two factors. The authors achieved their objectives and their results support their conclusions. This work will set new standards in integrating information about bird movement and environmental conditions experienced by the bird in a comprehensive, integrative and hypothesis-driven framework. The approach of the authors is highly advanced, providing heuristic insights for many additional systems where organisms are influenced by, and respond to small-scale environmental conditions.

Reviewer #3 (Public Review):

The present study used novel data logging devices to record the foraging behavior of wandering albatrosses. Specifically, the authors showed how localized winds and wave heights influence their ability to take off from the sea surface, which is the most expensive behavior they engage in while foraging. There is no better platform for this initial work because these birds are so large, the equipment they can carry without creating significant impact is tremendous.

The results were impressive, presented well, and the paper generally written in an accessible way to readers with less knowledge. The authors provide a convincing set of results that support the aims and conclusions. The theory and application could be used to inform our understanding of flight behavior in other seabirds.

Although the idea of taking off from the sea surface may sound trivial, it is essential to understand that albatrosses and other soaring seabirds have wings that are adapted for soaring (i.e. long and narrow). The trade off however, is that powered flight through wing flapping is energetically expensive because the wings have a shallow amplitude and generate less power compared to a shorter, wider wing. Thus, wind is everything and this study shows how wind facilitates the ability of the birds to gain flight using wind and waves. Awesome!

Reviewer #1 (Public Review):

The manuscript provides analyses on a very complete dataset on weight and length growth, as well as several physiological markers related to growth, in bonobos. Moreover, there is a good overview of the presence of adolescent growth spurts in non-human primates, by reviewing published data, in comparison to their own dataset. They discuss the need to consider scaling laws when interpreting and comparing growth curves of different species and variables.

The manuscript is very well written, the sample is large, and the methods are well explained. It seems they have analyzed a very complete dataset. Also, the discussion and the references supporting the findings are complete.

The main weakness of this manuscript is that they do not provide a direct comparison with previously analyzed datasets in other species, using their own method (in part maybe because there is not available data, but just published figures).

On the other side, conclusions are well supported by the results, and the previously published datasets are discussed in the manuscript, although not in detail.

Reviewer #2 (Public Review):

This work sheds new light on the growth trajectory of Bonobo and contributes heavily to the discussion of the exclusivity of certain aspects of growth in modern humans. These results are also interesting as long as they are based on the study of the largest sample ever considered in the study of the growth of this species by including morphometric measurements as well as endocrinological factors.

The authors approach the study of the presence of growth spurs (GS) in Bonobo on the basis that GS are exclusive to the growth in modern humans. This idea is fairly widespread, however studies on non-human primates have shown an acceleration of growth during adolescence in several species, these works are recalled, presented and discussed by the authors. The originality of this work lies in highlighting the importance of scaling in studies of growth trajectories. The absence of GS in Bonobo but also in other primate species may result from not considering the conjunction of weight and height in the analysis of growth, because the pronounced changes in the speed of the height are in relation to the speed of changes in weight and this is modified according to the size/age. The authors apply scaling corrections to their results and the GS become evident (or more obvious) in Bonobo. Thus, the exclusivity of GS in growth in modern humans may in fact result only by the application of analytical approach not very appropriate in non-human primates.

Reviewer #1 (Public Review):

This paper describes the discovery, functional analysis and structure of TcaP, a protein encoded by the Vibrio phage satellite PLE that forms a size-determining scaffold around PLE procapsids made from helper phage ICP1 structural proteins. The system displays a fascinating similarity to the P2/P4 system, which had previously been unique in its use of a size-determining external scaffolding protein, Sid. The work is interesting, comprehensive and of high quality. The presentation could be improved as listed in the suggestions below.

An interesting observation is that PLE appears to be dependent on small capsids for efficient transduction. This is not completely surprising if the element uses a cos site type mechanism for packaging, since this requires an integer number of genomes to be packaged when the capsid is full, and this might be more difficult to accomplish when the helper capsid is much larger than the satellite, as is the case with ICP1. The authors mention in a few places that this is the first known satellite to have this requirement. However, this is not quite correct: a similar defect was seen in phi12/SaPIbov5, where the large phi12 capsid was not quite the right size for either two or three copies of the wild-type ("unevolved") SaPIbov5 (Carpena et al. 2016).

The authors present several micrographs showing capsids formed in the presence or absence of wildtype or mutant TcaP and CP (Fig. 1, Fig 2., Fig 3). However, each micrograph shows only a handful of particles of the "correct" size, in addition to a few shells that are aberrant or of a different size. I miss a more statistically rigorous enumeration of shells of different size (PLE or ICP1 sized, or different), empty vs. full, aberrant shells etc. This could be presented as a size distribution graph, a histogram or in table form.

In the abstract, the term "divergent satellite P4" is vague and unclear. Divergent from what? Probably they mean distinct from or unrelated to PLE. Please clarify.

How do they know that gp123 is a decoration protein? Was this previously determined, does it have (sequence) similarity to other known decoration proteins, or is it simply the most likely designation based on its position in the genome?

Although the reconstruction and modeling statistics are good, it is difficult to assess the quality of the map and the model from the presented figures. Details of the density and FSC curves (half-map and model-to-map) should be shown. It is also difficult to see the TcaP structure and how it compares to Sid from the figures presented.

Introduction, Paragraph 3: "...which is the number of coat proteins divided by 60" is not strictly speaking the definition of T number. The T number corresponds to the number of subtriangles that one triangular face of the icosahedron is divided into. It corresponds to the number of coat proteins divided by 60 in the canonical case, but in tailed phages, 5 copies are removed to make way for the portal protein. (Other viruses could be described as having architecture corresponding to a specific T number, but with divergent numbers of subunits, e.g. adenoviruses or polyomaviruses.)

Reviewer #2 (Public Review):

Phage satellites are fascinating elements that have evolved to hijack phages for induction, packaging, and transfer, promoting their widespread dissemination in nature. It is remarkable how different satellites use conserved strategies of parasitism, utilising unrelated proteins that perform similar roles in their cognate elements. In the current manuscript, Dr. Seed and coworkers elucidated the mechanism used by one family of satellites, the PLEs, to produce small capsids, a process that inhibits phage reproduction while increasing PLE transmission. The work is presented beautifully, and the results are astonishing. The authors identified the gene responsible for generating the small capsids, characterised its role in the PLE transfer and phage inhibition, and determined the structure of the PLE-sized small capsids. It is a truly impressive piece of work.

Reviewer #3 (Public Review):

The manuscript by Boyd and co-authors "A Vibrio cholerae viral satellite maximizes its spread and inhibits phage by remodelling hijacked phage coat proteins into small capsids" reports important results related to self-defending mechanisms that bacteria are used against phages that infect them. It has been shown previously that bacteria produce phage-inducible chromosomal island-like elements (PLE) that encode proteins that are integrated into bacterial genome. These proteins are used by bacteria to amend the phage capsids and to create phage-like particles (satellites) that move between cells and transfer the genetic material of PLE to another bacteria. That study highlights the interactions between a PLE-encoded protein, TcaP, and capsid proteins of the phage ICP1.

The manuscript is well written, provides a lot of new information and the results are supported by biochemical analysis.

Reviewer #1 (Public Review):

This is a paper describing in detail the seasonal movements of a vole-eating raptor, the rough-legged buzzard, from their Arctic breeding areas to the temperate wintering areas and back, in an annual cycle perspective. The basis of the descriptions (using satellite tags) is state of the art, and so are the analyses on aspects of time and space. Of particular relevance is the degree in which this study successfully pinpoints the ecological shaping factors, food availability of course, in this case strongly affected by snow cover (which can be remotely sensed over large areas). The authors claim a new migration pattern called 'foxtrot' with phases with rapid and phases with slower migration movements.

My concern with this paper is the framing. A story on the how and why of these continental movements in response to snow and other habitat features would be a grand contribution.

Reviewer #2 (Public Review):

This preprint by Pokrovsky and coworkers is a descriptive study reporting on non-breeding itinerant behaviour of an intrapalearctic migratory raptor, the rough-legged buzzard, and relating such non-breeding movements to snow cover across the European non-breeding range. The article is based on long-term GPS tracking data from a relatively large sample of individuals (n=43) that were equipped with state-of-the-art tracking devices in the Russian Arctic during 2013-2019. The results show that, upon breeding, buzzards migrated rapidly to southern non-breeding areas, located in open areas north of the Black and Caspian seas, where they perform continuous directional movements at a slower pace, initially moving SW (Oct to Jan) and then progressively moving NE (Feb to Apr) before embarking on rapid spring migration. It is suggested that such itinerant behaviour follows variation (expansion and retreat) of snow cover across the non-breeding range.

The results are definitely useful for researchers investigating the ecological drivers of bird movement patterns. The paper is generally well-written and the analytical framework is solid. However, there are significant weaknesses in the theoretical framework, unwarranted claiming of novelty, and interpretation of the data. Below are key points that the authors may wish to consider.

1) The authors underemphasize the fact that what they term 'fox-trot' migration is actually a well-known pattern for many other migratory species, both in the Nearctic and in the Afro-Palearctic migration systems. Such behaviour has previously been identified as 'itinerant', involving an alternation of stopovers and movements between different short-term non-breeding residency areas, and it seems that the pattern the authors report for this particular species is perfectly in line with such previous evidence. For instance, this is well-documented among migratory raptors, such as the Montagu's harrier, a lesser kestrel or black kite, that exploit Sahelian savannahs, where large spatio-temporal variation in greenness and hence resource availability occurs. And, besides the mentioned cuckoos and nightingales, there are studies of red-backed shrikes suggesting the same, as well as of tree swallows in the Nearctic. Therefore, the authors should avoid claiming novelty for this study and introducing unnecessary and confusing new terms in the literature (i.e. the 'fox-trot' migration patterns) when these are definitely not strictly needed as they have been previously observed and defined otherwise. Reference to all this previous body of literature is only hinted at and should be considerably expanded. The final sentence of the abstract, involving a general recommendation for future work, is definitely not warranted. Sentences such as 'We used the rough-legged buzzard as a model..." are also similarly unwarranted. This is simply a descriptive study reporting on such behaviour in yet another migratory species. The predictions paragraph is also overlong and could be considerably condensed.

2) The term 'migration' associated to so-called 'fox-trot' movements (see Fig. 1) is also highly confusing and possibly incorrect, as it is not in line with the commonly accepted definition of 'migration' (i.e. mass back and forth movements from the same areas). Apparently, the authors do not provide any evidence that the birds are moving back and forth from the same areas during the non-breeding period (i.e., there is no mention of site fidelity between early and late wintering areas, but judging from fall and spring migration distances it seems this is definitely not the case). 'Non-breeding itinerancy' is clearly a more appropriate term to describe this behaviour. More generally, the reference to 'winter migration', which is often mentioned in the manuscript, is not correct and should be amended.

3) The current title is unnecessarily general (it may recall rather a review or meta-analysis) and not adequately describing the content of the manuscript. It is not at all clear how the terms 'Conservation' and 'Anthropocene' are related to the content of the study (unless one believes that this is because any study of wildlife is aimed at its conservation, which is of course untrue, and that the study has been performed in the Anthropocene, which is the case for all wildlife studies carried out after 1950-1960). In order to be informative, the title should more tightly reflect the content of the article. A valid alternative would be 'Itinerant non-breeding behaviour of an intra-Palaearctic migratory raptor', far more adequate and informative. Although it might be worthwhile mentioning the association between movements and snow cover (or ecological conditions more generally) already in the title, perhaps that link is too indirect as currently reported in the manuscript. There are several possibilities to provide a more direct link between movements and snow cover, such as e.g. performing habitat selection analysis with respect to snow cover. Plotting temporal progression of snow cover (average) against movements (e.g. by showing monthly home ranges against snow cover) would help visualizing the association between snow cover and movement patterns.

4) The text, particularly the Introduction and (even more so) the Discussion, would benefit from profound reframing in light of the above comments. Any link to conservation is too weak and should be removed or considerably toned down. Moreover, the species is not of conservation interest (IUCN = Least Concern), as it has an extremely large range and population size, with largely fluctuating and non-declining populations (whose dynamics are related to Arctic small rodent cycles). Unless the authors are able to make prediction on how these movements will be affected by climate change (e.g. by using species distribution models or similar approaches), the link to the Anthropocene and to conservation is mostly unwarranted. In general, reference to 'winter' should be avoided and replaced with 'non-breeding season', which is a more general term.

Reviewer #1 (Public Review):

The authors Wang et al. present a study of a mouse model K74R that they claim can extend the life span of mice, and also has some anti-cancer properties. Importantly, this mechanism seems to be mediated by the hematopoietic system, and protective effects can be transferred with bone marrow transplantation.

The authors need to be more specific in the title and abstract as to what is actually novel in this manuscript (a single tumor model), and what relies on previously published data (lifespan). Because many of these claims derive from previously published data, and the current manuscript is an extension of previously published work. The authors need to be more specific as to the actual data they present (they only use the B16 melanoma model) and the actual novelty of this manuscript.

Especially experiments on life span are published and not sufficiently addressed in this actual paper, as the title would suggest.

Reviewer #2 (Public Review):

The manuscript by Wang et al. follows up on the group's previous publication on KLF1 (EKLF) K47R mice and reduced susceptibility to tumorigenesis and increased life span (Shyu et al., Adv Sci (Weinh). Sep 2022;9(25):e2201409. doi:10.1002/advs.202201409). In the current manuscript, the authors have described the dependence of these phenotypes on age, gender, genetic background, and hematopoietic translation of bone marrow mononuclear cells. Considering the current study is centered on the phenotypes described in the previous study, the novelty is diminished. Further, there are significant conceptual concerns in the study that make the inferences in the manuscript far less convincing. Major concerns are listed below:

1. The authors mention more than once in the manuscript that KLF1 is expressed in range of blood cells including hematopoietic stem cells, megakaryocytes, T cells and NK cells. In the case of megakaryocytes, studies from multiple labs have shown that while EKLF is expressed megakaryocyte-erythroid progenitors, EKLF is important for the bipotential lineage decision of these progenitors, and its high expression promotes erythropoiesis, while its expression is antagonized during megakaryopoiesis. In the case of HSCs, the authors reference to their previous publication for KLF1's expression in these cells- however, in this study nor in the current study, there is no western blot documented to convincingly show that KLF1 protein is expressed at detectable levels in these cells. For T cells, the authors have referenced a study which is based on ectopic expression of KLF1. For NK cells, the authors reference bioGPS: however, upon inspection, this is also questionable.

2. The current study rests on the premise that KLF1 is expressed in HSCs, NK cells and leukocytes, and the references cited are not sufficient to make this assumption, for the reasons mentioned in the first point. Therefore, the authors will have to show both KLF1 mRNA and protein levels in these cells, and also compare them to the expression levels seen in KLF1 wild type erythroid cells along with knockout erythroid cells as controls, for context and specificity.

3. To get to the mechanism driving the reduced susceptibility to tumorigenesis and increased life span phenotypes in EKLF K74R mice, the authors report some observations- However, how these observations are connected to the phenotypes is unclear.<br /> a. For example, in Figure S3, they report that the frequency of NK1.1+ cells is higher in the mutant mice. The significance of this in relation to EKLF expression in these cells and the tumorigenesis and life span related phenotypes are not described. Again, as mentioned in the second point, KLF1 protein levels are not shown in these cells.<br /> b. In Figure 4, the authors show mRNA levels of immune check point genes, PD-1 and PD-l1 are lower in EKLF K74R mice in PB, CD3+ T cells and B220+ B cells. Again, the questions remain on how these genes are regulated by EKLF, and whether and at what levels EKLF protein is expressed in T cells and B cells relative to erythroid cells. Further, while the study they reference for EKLF's role in T cells is based on ectopic expression of EKLF in CD4+ T cells, in the current study, CD3+ T cells are used. Also, there are no references for the status of EKLF in B cells. These details are not discussed in the manuscript.

4. The authors perform comparative proteomics in the leukocytes of EKLF K74R and WT mice as shown in Figure S5. What is the status of EKLF levels in the mutant lysate vs wild type lysates based on this analysis? More clarity needs to be provided on what cells were used for this analysis and how they were isolated since leukocytes is a very broad term.

5. In the discussion the authors make broad inferences that go beyond the data shown in the manuscript. They mention that the tumorigenesis resistance and long lifespan is most likely due to changes in transcription regulatory properties and changes in global gene expression profile of the mutant protein relative to WT leukocytes. And based on reduced mRNA levels of Pd-1 Pd-l1 genes in the CD3+ T cells and B220+ B cells from mutant mice, they "assert" that EKLF is an upstream regulator of these genes and regulates the transcriptomes of a diverse range of hematopoietic cells. The lack of a ChIP assay to show binding of WT EKLF on genes in these cells and whether this binding is reduced or abolished in the mutant cells, make the above statements unsubstantiated.

6. Where westerns are shown, the authors need to show the molecular weight ladder, and where qPCR data are shown for EKLF, it will be helpful to show the absolute levels and compare these levels to those in erythroid cells, along the corresponding EKLF knock out cells as controls.

7. Figure S1D does not have a figure legend. Therefore, it is unclear what the blot in this figure is showing. In the text of the manuscript where they reference this figure, they mention that the levels of the mutant EKLF vs WT EKLF does not change in peripheral blood, while in the figure they have labeled WBCs for the blot, and the mRNA levels shown do seem to decrease in the mutant compared to WT peripheral blood.

Reviewer #3 (Public Review):

Hung et al provide a well-written manuscript focused on understanding how Eklf mutation confers anticancer and longevity advantages in vivo. The work is fundamental and the data is convincing although several details remain incompletely elucidated. The major strengths of the manuscript include the clarity of the effect and the appropriate controls. For instance, the authors query whether Eklf (K74R) imparts these advantages in a background, age, and gender dependent manner, demonstrating that the findings are independent. In addition, the authors demonstrate that the effect is not the consequence of the specific amino acid substitution, with a similar effect on anticancer activity. Furthermore, the authors provide some evidence that PD-1 and PDL-1 are altered in Eklf (K74R) mice.

Finally, they demonstrate that the effects are transferrable with BMT. Several weaknesses are also evidence. For instance, only melanoma is tested as a model of cancer such that a broad claim of "anti-cancer activity" may be somewhat of an overreach. It is also unclear why a homozygous mutation is needed when only a small fraction of cells during BMT can confer benefit. It is also difficult to explain how transplanted donor Eklf (K74R) HSCs confer anti-melanoma effect 7 and 14 days after BMT. Furthermore, it would be useful to see whether there are virulence marker alterations in the melanoma loci in WT vs Eklf (K74R) mice. Finally, the data in Fig 4c is difficult to interpret as decreased PD-1 and PDL-1 after knockdown of EKLF in vitro is not a useful experiment to corroborate how mutation without changing EKLF expression impacts immune cells. The work is impactful as it provides evidence that healthspan and lifespan may be modulated by specific hematological mutation but the mechanism by which this occurs is not completely elucidated by this work.

Reviewer #1 (Public Review):

In this manuscript, Bockorny, Muthuswamy, and Huang et al. performed proteomics analysis of plasma extracellular vesicles (EVs) from pancreatic ductal adenocarcinoma (PDAC) patients and patients with benign pancreatic diseases (chronic pancreatitis and intraductal papillary mucinous neoplasm, IPMN) to develop a 7-EV protein signature that predicts PDAC. Moveover, the authors identified PSMB4, RUVBL2, and ANKAR as being associated with metastasis. These studies provide important insight into alterations of EVs during PDAC progression and the data supporting predict PDAC with EV protein signatures are solid. However, there are certain concerns regarding the rigor and novelty of the data analysis and interpretation, as well as the clinical implications, as detailed below.

1. Plasma EVs were characterized by transmission electron microscopy and nanoparticle tracking analysis to confirm their morphology and size. The authors should also include an analysis of putative EV markers (e.g., tetraspanins, syntenin, ALIX, etc.) to confirm that the analyzed particles are EVs.

2. The authors identified multiple over-expressed proteins in PDAC based on their fold change and p-value; however, due to the heterogeneity of PDAC, it is necessary to show a heatmap displaying their abundance in all samples. High fold change does not necessarily indicate consistently high abundance in all PDAC samples.

3. PSMB4, RUVBL2, and ANKAR were identified as being associated with metastasis. The authors state that they intended to distinguish early and late-stage cancer samples, but it is unclear why they chose to compare metastatic and non-metastatic samples, as the non-metastatic group also includes late-stage cancer samples. This sentence should be rephrased to more accurately reflect the sample types profiled.

4. Non-metastatic and metastatic patients were separated based on global protein abundance. The samples within each group display significant heterogeneity with, some samples displaying similar patterns although they were classified into different groups (Figure 3A), and the samples within the same group, particularly the metastasis group, did not consistently exhibit similar patterns of protein abundance. The authors should clarify this point.

5. The authors performed the survival analysis on a set of EV proteins but did not specify the origin of these markers or how many markers were examined. The authors should show their abundances across different groups, such as different stages and metastasis status.

6. The classification model yielded a 100% accuracy, which may refer to AUC, in their discovery cohort, but it decreased to 89% in the independent cohort. This suggests that the authors have encountered overfitting issues with their model, where it performed well on the discovery cohort but did not generalize well to the independent cohort. The authors should clarify this point. The AUC score of the 7-EV signature is 0.89 and is not equivalent to prediction accuracy. In order to demonstrate prediction accuracy, the authors should show the confusion matrix of training and testing data as well as other evaluation metrics, such as accuracy, precision, and recall.

7. The authors should include more details of their model and the process of selection of signatures to enhance the reproducibility and transparency of their methods.

Reviewer #2 (Public Review):

The authors intended to identify a protein signature in extracellular vesicles of serum to distinguish pancreatic ductal adenocarcinoma from benign pancreatic diseases.

A major strength of the work presented is the valuable profiling of a significant number of patient samples, with a rich cohort of patients with pancreatic cancer, benign pancreatic diseases, and healthy controls. However, despite the strong cohorts presented, the numbers of patient samples for benign pancreatic diseases as well as controls were very limited.

Also, the method used to isolate vesicles, EVTrap, recognizes double bilayers, which means that it can detect cellular debris and apoptotic bodies, which are very common in the circulation of patients that are undergoing chemotherapy. It would be important to identify the patients that are therapy naïve and the ones that are not because of this possible bias. Additionally, the transmission electron microscopy data reflect this heterogeneity of the samples, also with little identification of double bilayered vesicles. It would be important to identify some extracellular vesicles markers in those preparations to strengthen the quality of the samples analysed. What is more, previously published work with this same methodology identifies around 2000 proteins per sample. It would be important to explain why in this study there seems to be a reduction in more than 50% of the amount of proteins identified in the vesicles.

One of the proteins that constantly surges on the analysis is KRT20. It would be important to proceed with the analysis by first filtering out possible contaminants of the proteomics, of which keratins are the most common ones. Finally, none of the 7-extracellular vesicle protein signatures has been validated by other techniques, such as western blot, in extracellular vesicles isolated by other, standard, methods, such as size exclusion chromatography.

A distinct technique for protein analysis was done but not a different method of isolation of these vesicles. This would strengthen the results and the origin of the proteins.

The conclusions that are reached do not fully meet the proposed aims of the identification of a protein signature in circulating extracellular vesicles that could improve early detection of the disease. The authors did not demonstrate the superiority of detection of these proteins in extracellular vesicles versus simply performing an ELISA, nor their superiority with respect to the current standard procedure for diagnosis.

The authors also suggest that profiling of circulating extracellular vesicles provides unique insights into systemic immune changes during pancreatic cancer development. How is this better than a regular hemogram is not clear.

Finally, it would be important to determine how this signature compares with many others described in the literature that have the exact same aim. Why and how would this one be better?