Reviewer #2 (Public review):

Summary:

Using in vitro and in vivo approaches, the authors first demonstrate that BEST4 inhibits intestinal tumor cell growth and reduces their metastatic potential, possibly via downstream regulation of TWIST1.

They further show that HES4 positively upregulates BEST4 expression, with direct interaction with BEST4 promoter region and protein. The authors further expand on this with results showing that negative regulation of TWIST1 by HES4 requires BEST4 protein, with BEST4 required for TWIST1 association with HES4. Reduction of BEST1 expression was shown in CRC tumor samples, with correlation of BEST4 mRNA levels with different clinicopathological factors such as sex, tumor stage and lymph node metastasis, suggesting a tumor-suppressive role of BEST4 for intestinal cancer.

Strengths:

• Good quality western blot data<br /> • Multiple approaches were used to validate the findings<br /> • Logical experimental progression for readability<br /> • Human patient data / In vivo murine model / Multiple cell lines were used, which supports translatability/reproducibility of findings

Weaknesses:

• Figure quality should still be improved<br /> • The discussion should still be improved

Reviewer #2 (Public review):

The authors have addressed most of my concerns sufficiently. There are still a few serious concerns I have. Primarily, the temporal resolution of the technique still makes me dubious about nearly all of the biological results. It is good that the authors have added some vessel diameter time courses generated by their model. But I still maintain that data sampling every 42 seconds - or even 21 seconds - is problematic. First, the evidence for long vascular responses is lacking. The authors cite several papers:

Alarcon-Martinez et al. 2020 show and explicitly state that their responses (stimulus-evoked) returned to baseline within 30 seconds. The responses to ischemia are long lasting but this is irrelevant to the current study using activated local neurons to drive vessel signals.<br /> Mester et al. 2019 show responses that all seem to return to baseline by around 50 seconds post-stimulus.<br /> O'Herron et al. 2022 and Hartmann et al. 2021 use opsins expressed in vessel walls (not neurons as in the current study) and directly constrict vessels with light. So this is unrelated to neuronal activity-induced vascular signals in the current study.

There are other papers including Vazquez et al 2014 (PMID: 23761666) and Uhlirova et al 2016 (PMID: 27244241) and many others showing optogenetically-evoked neural activity drives vascular responses that return back to baseline within 30 seconds. The stimulation time and the cell types labeled may be different across these studies which can make a difference. But vascular responses lasting 300 seconds or more after a stimulus of a few seconds are just not common in the literature and so are very suspect - likely at least in part due to the limitations of the algorithm.

Another major issue is that the time courses provided show that the same vessel constricts at certain points and dilates later. So where in the time course the data is sampled will have a major effect on the direction and amplitude of the vascular response. In fact, I could not find how the "response" window is calculated. Is it from the first volume collected after the stimulation - or an average of some number of volumes? But clearly down-sampling the provided data to 42 or even 21 second sampling will lead to problems. If the major benefit to the field is the full volume over large regions that the model can capture and describe, there needs to be a better way to capture the vessel diameter in a meaningful way.

It still seems possible that if responses are bi-phasic, then depth dependencies of constrictors vs dilators may just be due to where in the response the data are being captured - maybe the constriction phase is captured in deeper planes of the volume and the dilation phase more superficially. This may also explain why nearly a third of vessels are not consistent across trials - if the direction the volume was acquired is different across trials, different phases of the response might be captured.

I still have concerns about other aspects of the responses but these are less strong. Particularly, these bi-phasic responses are not something typically seen and I still maintain that constrictions are not common. The authors are right that some papers do show constriction. Leaving out the direct optogenetic constriction of vessels (O'Herron 2022 & Hartmann 2021), the Alarcon-Martinez et al. 2020 paper and others such as Gonzales et al 2020 (PMID: 33051294) show different capillary branches dilating and constricting. However, these are typically found either with spontaneous fluctuations or due to highly localized application of vasoactive compounds. I am not familiar with data showing activation of a large region of tissue - as in the current study - coupled with vessel constrictions in the same region. But as the authors point out, typically only a few vessels at a time are monitored so it is possible - even if this reviewer thinks it unlikely - that this effect is real and just hasn't been seen.

I also have concerns about the spatial resolution of the data. It looks like the data in Figure 7 and Supplementary Figure 7 have a resolution of about 1 micron/pixel. It isn't stated so I may be wrong. But detecting changes of less than 1 micron, especially given the noise of an in vivo prep (brain movement and so on), might just be noise in the model. This could also explain constrictions as just spurious outputs in the model's diameter estimation. The high variability in adjacent vessel segments seen in Figure 6C could also be explained the same way, since these also seem biologically and even physically unlikely.

I still think the difference in distance-to-nearest-neuron between dilators and constrictors is insignificant. These points were not addressed - the difference in neuronal density between cortical layers and the ~ 5 micron difference in this parameter between dilators and constrictors. Given the concerns raised above, there is very little confidence in even knowing which vessels constricted and which dilated.

All-in-all, I think this is potentially a very useful pipeline for automating numerous tasks which are very time consuming and vulnerable to subjective judgements (which leads to reproducibility problems and others). However, I think the challenge of capturing large volumes at high speed and with high resolution is very real and hasn't been adequately accomplished for the claims the authors want to make about their data. It is encouraging that with the right technology, such data could be captured and this pipeline would be excellent for processing it. But given the limitations in the data collection here, I think that many of the biological claims are hard to fully accept.

Reviewer #2 (Public review):

Summary

This study deepens the former authors' investigations of the mechanisms involved in gating the long-term consolidation of an associative memory (LTM) in Drosophila melanogaster. After having previously found that LTM consolidation 1. costs energy (Plaçais and Préat, Science 2013) provided through pyruvate metabolism (Plaçais et al., Nature Comm 2017) and 2. is gated by the increased tonic activity in a type of dopaminergic neurons ('MP1 neurons') following only training protocol relevant for LTM, i.e. interspaced in time (Plaçais et al., Nature Neuro 2012), they here dig into the intra-cell signalling triggered by dopamine input and eventually responsible for the increased mitochondria activity in Kenyon Cells. They identify a particular PKC, PKCδ, as a major molecular interface in this process and describe its translocation to mitochondria to promote pyruvate metabolism, specifically after spaced training.

Methodological approach

To that end, they use RNA interference against the isozyme PKCδ, in a time-controlled way and in the whole Kenyon cells populations or in the subpopulation forming the α/β lobe. This knock-down decreased the total PKCδ mRNA level in the brain by ca. 30%, and is enough to observe decreased in flies performances for LTM consolidation. Using Pyronic, a sensor for pyruvate for in vivo imaging, and pharmacological disruption of mitochondrial function, the authors then show that PKCδ knock-down prevents high level of pyruvate from accumulating in the Kenyon cells at the time of LTM consolidation, pointing towards a role of PKCδ in promoting pyruvate metabolism. They further identify the PDH kinase PDK as a likely target for PKCδ since knocking down both PKCδ and PDK led to normal LTM performances, likely counterbalancing PKCδ knock-down alone.

To understand the timeline of PKCδ activation and to visualise its mitochondrial translocation in subpart of Mushroom body lobes they imported in fruitfly the genetically-encoded FRET reporters of PKCδ, δCKAR and mitochondria-δCKAR (Kajimoto et al 2010). They show that PKCδ is activated to the sensor's saturation only after spaced training, and not other types of training that are 'irrelevant' for LTM. Further, adding thermogenetic activation of dopaminergic neurons and RNA interference against Gq-coupled dopamine receptor to FRET imaging, they identify that a dopamine-triggered cascade is sufficient for the elevated PKCδ-activation.

Strengths and weaknesses

The authors use a combination of new fluorescent sensors and behavioral, imaging, and pharmacological protocols they already established to successfully identify the molecular players that bridge the requirement for spaced training/dopaminergic neurons MP1 oscillatory activity and the increased metabolic activity observed during long-term memory consolidation.<br /> The study is dense in new exciting findings and each methodological step is carefully designed. The experiments one could think of to make this link have been done in this study and the results seem solid.<br /> The discussion is well conducted, with interesting parallel with mammals, where the possibility that this process takes place as well is yet unknown.

Impact

Their findings should interest a large audience:<br /> They discover and investigate a new function for PKCδ in regulating memory processes in neurons in conjunction with other physiological functions, making this molecule a potentially valid target for neuropathological conditions. They also provide new tools in drosophila to measure PKCδ activation in cells. They identify the major players for lifting the energetic limitations preventing the formation of a long-term memory.

Reviewer #2 (Public review):

Summary:

The authors investigated the mechanisms behind breeding season-dependent feeding behavior using medaka, a well-known photoperiodic species, as a model. Through a combination of molecular, cellular, and behavioral analyses, including tests with mutants, they concluded that AgRP1 plays a central role in feeding behavior, mediated by ovarian estrogenic signals.

Strengths:

This study offers valuable insights into the neuroendocrine mechanisms that govern breeding season-dependent feeding behavior in medaka. The multidisciplinary approach, which includes molecular and physiological analyses, enhances the scientific contribution of the research.

Weaknesses:

While medaka is an appropriate model for studying seasonal breeding, the results presented are insufficient to fully support the authors' conclusions.

Specifically, methods and data analyses are incomplete in justifying the primary claims:<br /> - the procedure for the food intake assay is unclear;<br /> - the sample size is very small;<br /> - the statistical analysis is not always adequate.

Additionally, the discussion fails to consider the possible role of other hormones that may be involved in the feeding mechanism.

Reviewer #2 (Public review):

The manuscript by Shibata proposed a potentially interesting idea that variation in methylcytosine across cells can inform cellular lineage in a way similar to single nucleotide variants (SNVs). The work builds on the hypothesis that the "replication" of methylcytosine, presumably by DNMT1, is inaccurate and produces stochastic methylation variants that are inherited in a cellular lineage. Although this notion can be correct to some extent, it does not account for other mechanisms that modulate methylcytosines, such as active gain of methylation mediated by DNMT3A/B activity and activity demethylation mediated by TET activity. In some cases, it is known that the modulation of methylation is targeted by sequence-specific transcription factors. In other words, inaccurate DNMT1 activity is only one of the many potential ways that can lead to methylation variants, which fundamentally weakens the hypothesis that methylation variants can serve as a reliable lineage marker. With that being said (being skeptical of the fundamental hypothesis), I want to be as open-minded as possible and try to propose some specific analyses that might better convince me that the author is correct. However, I suspect that the concept of methylation-based lineage tracing cannot be validated without some kind of lineage tracing experiment, which has been successfully demonstrated for scRNA-seq profiling but not yet for methylation profiling (one example is Delgado et al., nature. 2022).

(1) The manuscript reported that fCpG sites are predominantly intergenic. The author should also score the overlap between fCpG sites and putative regulatory elements and report p-values. If fCpG sites commonly overlap with regulatory elements, that would increase the possibility that these sites being actively regulated by enhancer mechanisms other than maintenance methyltransferase activity.

(2) The overlap between fCpG and regulatory sequence is a major alternative explanation for many of the observations regarding the effectiveness of using fCpG sites to classify cell types correctly. One would expect the methylation level of thousands of enhancers to be quite effective in distinguishing cell types based on the published single-cell brain methylome works.

(3) The methylation level of fCpG sites is higher in hindbrain structures and lower in forebrain regions. This observation was interpreted as the hindbrain being the "root" of the methylation barcodes and, through "progressive demethylation" produced the methylation states in the forebrain. This interpretation does not match what is known about methylation dynamics in mammalian brains, in particular, there is no data supporting the process of "progressive demethylation". In fact, it is known that with the activation of DNMT3A during early postnatal development in mice or humans (Lister et al., 2013. Science), there is a global gain of methylation in both CH and CG contexts. This is part of the broader issue I see in this manuscript, which is that the model might be correct if "inaccurate mC replication" is the only force that drives methylation dynamics. But in reality, active enzymatic processes such as the activation of DNMT3A have a global impact on the methylome, and it is unclear if any signature for "inaccurate mC replication" survives the de novo methylation wave caused by DNMT3A activity.

(3) Perhaps one way the author could address comment 3 is to analyze methylome data across several developmental stages in the same brain region, to first establish that the signal of "inaccurate mC replication" is robust and does not get erased during early postnatal development when DNMT3A deposits a large amount of de novo methylation.

(4) The hypothesis that methylation barcodes are homogeneous among progenitor cells and more polymorphic in derived cells is an interesting one. However, in this study, the observation was likely an artifact caused by the more granular cell types in the brain stem, intermediate granularity in inhibitory cells, and highly continuous cell types in cortical excitatory cells. So, in other words, single-cell studies typically classify hindbrain cell types that are more homogenous, and cortical excitatory cells that are much more heterogeneous. The difference in cell type granularity across brain structures is documented in several whole-brain atlas papers such as Yao et al. 2023 Nature part of the BICCN paper package.

(5) As discussed in comment 2, the author needs to assess whether the successful classification of cell types (brain lineage) using fCpG was, in fact, driven by fCpG sites overlapping with cell-type specific regulatory elements.

(6) In Figure 5E, the author tried to address the question of whether methylation barcodes inform lineage or post-mitotic methylation remodeling. The Y-axis corresponds to distances in tSNE. However, tSNE involves non-linear scaling, and the distances cannot be interpreted as biological distances. PCA distances or other types of distances computed from high-dimensional data would be more appropriate.

Reviewer #2 (Public review):

Summary:

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

Strengths:

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

Weaknesses:

While the details of the paper are compelling, the authors' presentation of their results is often unclear or incomplete:

(1) The mathematical details of the paper are correct but contain numerous notation errors and are presented as a solid block of subtle equation manipulations. This makes the details of the authors' approach (the main contribution of the paper to the field) highly difficult to understand.

(2) One of the main contributions of the paper is the notion that time cost in decision-making contains an apportionment cost that reflects the allocation of decision time relative to the world. The authors use this cost to pose a hypothesis as to why subjects exhibit sub-optimal behavior in choice decisions. However, the equation for the apportionment cost is never clearly defined in the paper, which is a significant oversight that hampers the effectiveness of the authors' claims.

(3) Many of the paper's figures are visually busy and not clearly detailed in the captions (for example, Figures 6-8). Because of the geometric nature of the authors' approach, the figures should be as clean and intuitive as possible, as in their current state, they undercut the utility of a geometric argument.

(4) The authors motivate their work by focusing on previously-observed behavior in decision experiments and tell the reader that their model is able to qualitatively replicate this data. This claim would be significantly strengthened by the inclusion of experimental data to directly compare to their model's behavior. Given the computational focus of the paper, I do not believe the authors need to conduct their own experiments to obtain this data; reproducing previously accepted data from the papers the authors' reference would be sufficient.

(5) While the authors reference a good portion of the decision-making literature in their paper, they largely ignore the evidence-accumulation portion of the literature, which has been discussing time-based discounting functions for some years. Several papers that are both experimentally-(Cisek et al. 2009, Thurs et al. 2012, Holmes et al. 2016) and theoretically-(Drugowitsch et al. 2012, Tajima et al. 2019, Barendregt et al. 22) driven exist, and I would encourage the authors to discuss how their results relate to those in different areas of the field.

Reviewer #2 (Public review):

Summary:

Mechanically activated ion channels PIEZOs have been widely studied for their role in mechanosensory processes like touch sensation and red blood cell volume regulation. PIEZO in vivo roles are further exemplified by the presence of gain-of-function (GOF) or loss-of-function (LOF) mutations in humans that lead to disease pathologies. Hereditary xerocytosis (HX) is one such disease caused due to GOF mutation in Human PIEZO1, which are characterized by their slow inactivation kinetics, the ability of a channel to close in the presence of stimulus. But how these mutations alter PIEZO1 inactivation or even the underlying mechanisms of channel inactivation remains unknown. Recently, MDFIC (myoblast determination family inhibitor proteins) was shown to directly interact with mouse PIEZO1 as an auxiliary subunit to prolong inactivation and alter gating kinetics. Furthermore, while lipids are known to play a role in the inactivation and gating of other mechanosensitive channels, whether this mechanism is conserved in PIEZO1 is unknown. Thus, the structural basis for PIEZO1 inactivation mechanism, and whether lipids play a role in these mechanisms represent important outstanding questions in the field and have strong implications for human health and disease.

To get at these questions, Shan et al. use cryogenic electron microscopy (Cryo-EM) to investigate the molecular basis underlying differences in inactivation and gating kinetics of PIEZO1 and human disease-causing PIEZO1 mutations. Notably, the authors provide the first structure of human PIEZO1 (hPIEZO1), which will facilitate future studies in the field. They reveal that hPIEZO1 has a more flattened shape than mouse PIEZO1 (mPIEZO1) and has lipids that insert into the hydrophobic pore region. To understand how PIEZO1 GOF mutations might affect this structure and the underlying mechanistic changes, they solve structures of hPIEZO1 as well as two HX-causing mild GOF mutations (A1988V and E756del) and a severe GOF mutation (R2456H). Unable to glean too much information due to poor resolution of the mutant channels, the authors also attempt to resolve MCFIC-bound structures of the mutants. These structures show that MDFIC inserts into the pore region of hPIEZO1, similar to its interaction with mPIEZO1, and results in a more curved and contracted state than hPIEZO1 on its own. The authors use these structures to hypothesize that differences in curvature and pore lipid position underlie the differences in inactivation kinetics between wild-type hPIEZO1, hPIEZO1 GOF mutations, and hPIEZO1 in complex with MDFIC.

Strengths:

This is the first human PIEZO1 structure. Thus, these studies become the stepping stone for future investigations to better understand how disease-causing mutations affect channel gating kinetics.

Weaknesses:

Many of the hypotheses made in this manuscript are not substantiated with data and are extrapolated from mid-resolution structures.

Reviewer #2 (Public review):

Summary:

Prével et al. present an in vivo study in which they reveal an interesting aspect of β-glucan, a known inducer of enhanced immune responses termed trained immunity in sterile inflammation. The authors can show, that β-glucan's can reprogram alveolar macrophages (AMs) in the lungs through neutrophils and IFNγ signaling and independent of Dectin1. This reprogramming occurs at both transcriptional and metabolic levels. After β-glucan training, LPS-induced sterile inflammation exacerbated acute lung injury via enhanced immunopathology. These findings highlight a new aspect of β-glucan's role in trained immunity and its potential detrimental effects when enhanced pathogen clearance is not required.

Strengths:

(1) This manuscript is well-written and effectively conveys its message.

(2) The authors provide important evidence that β-glucan training is not solely beneficial, but depending on the context can also enhance immunopathology. This will be important to the field for two reasons. It shows again, that trained immunity can also be harmful. Jentho et al. 2021 have already provided further evidence for this aspect. And it highlights anew that LPS application is an insufficient infection model.

Weaknesses:

(1) Only a little physiological data is provided by the in vivo models.

(2) The effects in histology appear to be rather weak.

Reviewer #2 (Public Review):

Summary:

This is an interesting study with a lot of data. Some of these ideas are intriguing. But a few major points require further consideration.

Major points:

(1) What disease is this model of whole animal hypoxia supposed to mimic? If one is focused on the brain, can one just use a model of focal or global cerebral ischemia?

(2) If this model subjects the entire animal to hypoxia, then other organs will also be hypoxic. Should one also detect endothelial upregulation and release of extracellular vesicles containing hemoglobin mRNA in non-CNS organs? Where do these vesicles go? Into blood?

(3) What other mRNA are contained in the vesicles released from brain endothelial cells?

(4) Where do the endothelial vesicles go? Only to neurons? Or to other cells as well?

(5) Neurons can express endogenous hemoglobin. Is it useful to subject neurons to hypoxia and then see how much the endogenous mRNA goes up? How large is the magnitude of endogenous hemoglobin gene upregulation compared to the hypothesized exogenous mRNA that is supposed to be donated from endothelial vesicles?

(6) Finally, it may be useful to provide more information and data to explain how the expression of this exogenous endothelial-derived hemoglobin binds to neuronal mitochondria to alter function.

Reviewer #2 (Public review):

Shrestha et al investigated the role of IR receptors in the detection of 3 carboxylic acids in adult Drosophila. A low concentration of either of these carboxylic acids added to 2 mM sucrose (1% lactic acid (LA), citric acid (CA), or glycolic acid (GA)) stimulates the consumption of adult flies in choice conditions. The authors use this behavioral test to screen the impact of mutations within 33 receptors belonging to the IR family, a large family of receptors derived from glutamate receptors and expressed both in the olfactory and gustatory sensilla of insects. Within the panel of mutants tested, they observed that 3 receptors (IR25a, IR51b, and IR76b) impaired the detection of LA, CA, and GA, and that 2 others impacted the detection of CA and GA (IR94a and IR94h). Interestingly, impairing IR51b, IR94a, and IR94h did not affect the electrophysiological responses of external gustatory sensilla to LA, CA, and GA. Thanks to the use of GAL4 strains associated with these receptors and thanks to the use of poxn mutants (which do not develop external gustatory sensilla but still have functional internal receptors), they show evidence that IR94a and IR94h are only expressed in two clusters of gustatory neurons of the pharynx, respectively in the VCSO (ventral cibarial sense organ) and in the VCSO + LSO (labral sense organ). As for IR51b, the GAL4 approach was not successful but RT-PCR made on different parts of the insect showed an expression both in the pharyngeal organs and in peripheral receptors. These main findings are then complemented by a host of additional experiments meant to better understand the respective roles of IR94a and IR94h, by using optogenetics and brain calcium imaging using GCamp6. They also report a failed attempt to co-express IR51b, IR94a, and IR94h into external receptors, a co-expression which did not confer the capability of bitter-sensitive cells (expressing GR33a-GAL4) to detect either of the carboxylic acids. These data complete and expand previous observations made on this group and others, and dot to 2 new IR receptors which show an unsuspected specific expression, into organs that still remain difficult to study.

The conclusions of this paper are supported by the data presented, but it remains difficult to make general conclusions as concerns the mechanisms by which carboxylic acids are detected.

(1) All experiments were done with 1% of carboxylic acids. What is the dose dependency of the behavioral responses to these acids, and is it conceivable that other receptors are involved at other concentrations?

(2) One result needs to be better discussed and hypotheses proposed - which is why the mutations of most receptors lead to a loss of detection (mutant flies become incapable of detecting the acid) while mutations in IR94a and IR94h make CA and GA potent deterrents. Does it mean that CA and GA are detected by another set of receptors that, when activated, make flies actively avoid CA and GA? In that case, do the authors think that testing receptors one by one is enough to uncover all the receptors participating in the detection of these substances?

(3) The paper needs to be updated with a recent paper published by Guillemin et al (2024), indicating that LA is detected externally by a combination of IR94e, IR76b and IR25a. IR25a might help to form a fully functional receptor in GR33a neurons (a former study from Chen et al (2017) indicate that IR25a is expressed in all gustatory neurons of the pharynx).

(4) Although it was not the main focus of the paper, it would have been most interesting if the cells expressing IR94a and IR94h were identified, and placed on the functional map proposed by the group of Dahanukar (Chen et al 2017 Cell Reports, Chen et al 2019 Cell Reports).

Reviewer #2 (Public review):

Summary:

Kirschner and colleagues test whether methamphetamine (MA) alters learning rate dynamics in a validated reversal learning task. They find evidence that MA can enhance performance for low-performers and that the enhancement reflects a reduction in the degree to which these low-performers dynamically up-regulate their learning rates when they encounter unexpected outcomes. The net effect is that poor performers show more volatile learning rates (e.g. jumping up when they receive misleading feedback), when the environment is actually stable, undermining their performance over trials.

Strengths:

The study has multiple strengths including large sample size, placebo control, double-blind randomized design, and rigorous computational modeling of a validated task.

Weaknesses:

The limitations, which are acknowledged, include that the drug they use, methamphetamine, can influence multiple neuromodulatory systems including catecholamines and acetylcholine, all of which have been implicated in learning rate dynamics. They also do not have any independent measures of any of these systems, so it is impossible to know which is having an effect.

Another limitation that the authors should acknowledge is that the fact that participants were aware of having different experiences in the drug sessions means that their blinding was effectively single-blind (to the experimenters) and not double-blind. Relatedly, it is difficult to know whether subjective effects of drugs (e.g. arousal, mood, etc.) might have driven differences in attention, causing performance enhancements in the low-performing group. Do the authors have measures of these subjective effects that they could include as covariates of no interest in their analyses?

Reviewer #2 (Public review):

Summary:

The authors aimed to explore and better understand the complex topographical organization of the human pulvinar, a brain region crucial for various high-order functions such as perception and attention. They sought to move beyond traditional histological subdivisions by investigating continuous 'gradients' of cortical connections along the dorsoventral and mediolateral axes. Using advanced imaging techniques and a comprehensive PET atlas of neurotransmitter receptors, the study aimed to identify and characterize these gradients in terms of structural connections, functional coactivation, and molecular binding patterns. Ultimately, the authors targeted to provide a more nuanced understanding of pulvinar anatomy and its implications for brain function in both healthy and diseased states.

Strengths:

A key strength of this study lies in the authors' effort to comprehensively combine multimodal data, encompassing both functional and structural connectomics, alongside the analysis of major neurotransmitter distributions. This approach enabled a more nuanced understanding of the overarching organizational principles of the pulvinar nucleus within the broader context of whole-brain connectivity. By employing cortex-wide correlation analyses of multimodal embedding patterns derived from 'gradients,' which provide spatial maps reflecting the underlying connectomic and molecular similarities across voxels, the study offers a thorough characterization of the functional neuroanatomy of the pulvinar.

Weaknesses:

Despite its strengths, the current manuscript falls short in presenting the authors' unique perspectives on integrating the diverse biological principles derived from the various neuroimaging modalities. The findings are predominantly reported as correlations between different gradient maps, without providing the in-depth interpretations that would allow for a more comprehensive understanding of the pulvinar's role as a central hub in the brain's network. Another limitation of the study is the lack of clarity regarding the application of pulvinar and its subnuclei segmentation maps to individual brains prior to BOLD signal extraction and gradient reconstruction. This omission raises concerns about the precision and reproducibility of the findings, leaving their robustness less transparently evaluable.

DOI: 10.1038/s44318-024-00213-2

Resource: Network for Pancreatic Organ Donors with Diabetes (RRID:SCR_014641)

Curator: @bandrow

SciCrunch record: RRID:SCR_014641

What is this?

Reviewer #2 (Public review):

This study examines monosomies in yeast in comparison to synthetic lethals resulting from combinations of heterozygous gene deletions that individually have a detrimental effect. The survival of monosomies, albeit with detrimental growth defects, is interpreted as positive epistasis for fitness. Gene expression was examined in monosomies in an attempt to gain insight into why monosomies can survive when multiple heterozygous deletions on the respective chromosome do not. In the RNAseq experiments, many genes were interpreted to be increased in expression and some were interpreted as reduced. Those with the apparent strongest increase were the subunits of the ribosome and those with the apparent strongest decreases were subunits of the proteasome.

The initiation and interpretation of the results were apparently performed in a vacuum of a century of work on genomic balance. Classical work in the flowering plant Datura and in Drosophila found that changes in chromosomal dosage would modulate phenotypes in a dosage sensitive manner (for references see Birchler and Veitia, 2021, Cytogenetics and Genome Research 161: 529-550). In terms of molecular studies, the most common modulation across the genome for monosomies is an upregulation (Guo and Birchler, Science 266: 1999-2002; Shi et al. 2021, The Plant Cell 33: 917-939).

It was also apparently performed in a vacuum of results of evolutionary genomics that indicate the classes of genes for which dosage causes fitness consequences. It was from yeast genomics that it was realized that there is a difference in the fate of duplicate genes that are members of molecular complexes following whole genome duplications (WGD) versus small segmental duplications (SSD) with longer retention times from WGD than other genes and an underrepresentation in small scale duplications (e.g. Papp et al. 2003, Nature 424: 194-197; Hakes et al 2007, Genome Biol 8: R209). This pattern arises from negative fitness consequences of deletion of some but not all members of a complex after WGD or the overexpression of individual subunits after SSD (Defoort et al., 2019 Genome Biol Evol 11: 2292-2305; Shi et al., 2020, Mol Biol Evol 37: 2394-2413). In order for this pattern to occur, there must be a reasonably close relationship between mRNA and the respective protein levels. This pattern of retention and underrepresentation has been found throughout eukaryotes (e.g. Tasdighian et al 2017, Plant Cell 29: 2766-2785) indicating that yeast is not an outlier in its behavior.

In the present yeast study, not only are there apparent increases for ribosomal subunits but also for many genes in the GAAC pathway, the NCR pathway, and Msn2p. The word "apparent" is used because RNAseq studies can only determine relative changes in gene expression (Loven et al., 2012, Cell 151: 476-482). Because aneuploidy can change the transcriptome size in general (Yang et al., 2021, The Plant Cell 33: 1016-1041), it is possible and maybe probable that this occurs in yeast monosomies as well. If there is an increase in the general transcriptome size, then there might not be as much reduction of the proteosome subunits as claimed and the increases might be somewhat less than indicated.

Indeed, the authors claim that there is an increased cell volume in the monosomies. Given that cell volume correlates very well with the total transcriptome size (Loven et al., 2012, Cell 151: 476-482; Sun et al 2020, Current Biol 30: 1217-1230; Swaffer et al., 2023, Cell 186: 5254-5268), it could well be that there is an increased transcriptome size in the monosomies. Thus, the interpretation of the relative changes from RNAseq is compromised.

It should be noted that contrary to the claims of the cited paper of Torres et al 2007 (Science 317: 916-924), a reanalysis of the data indicated that yeast disomies have many modulated genes in trans with downregulated genes being more common (Hou et al, 2018, PNAS 115: E11321-E11330). The claim of Torres et al that there are no global modulations in trans is counter to the knowledge that transcription factors are typically dosage sensitive and have multiple targets across the genome. The inverse effect trend is also true of maize disomies (Yang et al., 2021, The Plant Cell 33: 1016-1041), maize trisomies (Shi et al., 2021), Arabidopsis trisomies (Hou et al. 2018), Drosophila trisomies (Sun et al. 2013, PNAS 110: 7383-7388; Sun et al., 2013, PNAS 110: 16514-16519; Zhang et al., 2021, Scientific Reports 11: 19679; Zhang et al., genes 12: 1606) and human trisomies (Zhang et al., 2024, genes 15: 637). Taken as a whole it would seem to suggest that there are many inverse relationships of global gene expression with chromosomal dosage in both yeast disomies and monosomies.

In a similar vein, the authors cite Muenzner et al 2024, Nature 630 149-157 that there is an attenuation of protein levels from aneuploid chromosomes while the mRNA levels correlate with gene dosage. This interpretation also seems to have been made in a vacuum of the evolutionary genomics data noted above and there was no consideration of transcriptome size change in the aneuploids. Also, Muenzner et al make the remarkable suggestion that there is degradation of overproduced proteins from hyperploidy, but for monosomies there is greater degradation of the proteins from the remainder of the genome.

To clarify the claims of this study, it would be informative to produce distributions of the various ratios of individual gene expression in monosomy versus diploid as performed by Hou et al. 2018. This will better express the trends of up and down regulation across the genome and whether there are any genes on the varied chromosome that are dosage compensated. The authors claim in the Abstract that "There is no evidence of increased (compensatory) gene expression on the monosomic chromosomes", but then note after describing the increased cell volume of monosomies that this observation likely signals an increased transcriptome size: "Indeed, one explanation for the observed epistasis for viability could be an ample overproduction of all transcripts, so that even those halved by monosomy are sufficiently abundant". It is not clear to this reviewer what conclusions can be made from this work other than the empirical observation that monosomy does not reflect the cumulative effect of multiple haplo-insufficiencies of individual heterozygous deletions and that there are some RELATIVE changes in gene expression, but it is unclear what the ABSOLUTE PER CELL expression is across the whole genome. Clarifying this issue would be important for understanding the nature of any epistasis and fitness consequences.

Reviewer #2 (Public review):

Summary:

The manuscript by Yang et al. presents a novel and significant investigation into the role of SIRT4 For CCN2 expression in response to TGF-β by modulating U2AF2-mediated alternative splicing and its impact on the development of kidney fibrosis.

Strengths:

The authors' main conclusion is that SIRT4 plays a role in kidney fibrosis by regulating CCN2 expression via pre-mRNA splicing. Additionally, the study reveals that SIRT4 translocates from the mitochondria to the cytoplasm through the BAX/BAK pore under TGF-β stimulation. In the cytoplasm, TGF-β activated the ERK pathway and induced the phosphorylation of SIRT4 at Ser36, further promoting its interaction with importin α1 and subsequent nuclear translocation. In the nucleus, SIRT4 was found to deacetylate U2AF2 at K413, facilitating the splicing of CCN2 pre-mRNA to promote CCN2 protein expression. Overall, the findings are fully convincing. The current study, to some extent, shows potential importance in this field.

Reviewer #2 (Public Review):

New comments are added after authors responses to my initial comments.

Summary:

Zhang et al. performed a proteogenomic analysis of lung adenocarcinoma (LUAD) in 169 female never-smokers from the Xuanwei area (XWLC) in China. These analyses reveal that XWLC is a distinct subtype of LUAD and that BaP is a major risk factor associated with EGFR G719X mutations found in the XWLC cohort. Four subtypes of XWLC were classified with unique features based on multi-omics data clustering.

Strengths:

The authors made great efforts in performing several large-scale proteogenomic analyses and characterizing molecular features of XWLCs. Datasets from this study will be a valuable resource to further explore the etiology and therapeutic strategies of air-pollution-associated lung cancers, particularly for XWLC.

Weaknesses:

[...]

(2) Importantly, while providing the large datasets, validating key findings is minimally performed, and surprisingly there is no interrogation of XWLC drug response/efficacy based on their findings, which makes this manuscript descriptive and incomplete rather than conclusive. For example, testing the efficacy of XWLC response to afatinib combined with other drugs targeting activated kinases in EGFR G719X mutated XWLC tumors would be one way to validate their datasets and new therapeutic options.

Response: We appreciate your suggestion. In reference to testing the efficacy of XWLC response to afatinib combined with drugs targeting kinases, we have planned to establish PDX and organoid models to validate the effectiveness of our therapeutic approach. Due to the extended timeframe required, we intend to present these results in a subsequent study.

Comments: All conclusions in the manuscript made by authors are based on interpretations of large-scale multi-omics data, which should be properly validated by other approaches and methods. Without validation, these are all speculations and any conclusions without supporting evidence are not acceptable. This reviewer suggested an example of validation experiment, and Reviewer #3 also pointed out several data that need to be validated. However, authors do not agree to perform any of these validation experiments without reasonable justification.

(3) The authors found MAD1 and TPRN are novel therapeutic targets in XWLC. Are these two genes more frequently mutated in one subtype than the other 3 XWLC subtypes? How these mutations could be targeted in patients?

Response: Thank you for your question. We have investigated the TPRN and MAD1 mutations in our dataset, identifying five TPRN mutations and eight MAD1 mutations. Among the TPRN mutations, XWLC_0046 and XWLC_0017 belong to the MCII subtype, XWLC_0012 belongs to the MCI subtype, and the subtype of the other three samples is undetermined, resulting in mutation frequencies of 1/16, 2/24, 0/15, and 0/13, respectively. Similarly, for the MAD1 mutations, XWLC_0115, XWLC_0021, and XWLC_0047 belong to the MCII subtype, XWLC_0055 containing two mutations belongs to the MCI subtype, and the subtype of the other three samples is undetermined, resulting in mutation frequencies of 1/16, 3/24, 0/15, and 0/13 across subtypes, respectively. Fisher's test did not reveal significant differences between the subtypes. For targeting novel therapeutic targets such as MAD1 and TPRN, we propose a multi-step approach. Firstly, we advocate for conducting functional in vivo and in vitro experiments to verify their roles during cancer progression. Secondly, we suggest conducting small molecule drug screening based on the pharmacophore of these proteins, which may lead to the identification of potential therapeutic drugs. Lastly, we recommend testing the efficacy of these drugs to further validate their potential as effective treatments.

Comments: Please properly incorporate the above explanation into the main text.

(4) In Figures 2a and b: while Figure 2a shows distinct genomic mutations among each LC cohort, Figure 2b shows similarity in affected oncogenic pathways (cell cycle, Hippo, NOTCH, PI3K, RTK-RAS, and WNT) between XWLC and TNLC/CNLC. Considering that different genomic mutations could converge into common pathways and biological processes, wouldn't these results indicate commonalities among XWLC, TNLC, and CNLC? How about other oncogenic pathways not shown in Figure 2b?

Response: Thank you for your question. Based on the data presented in Fig. 2a, which encompasses all genomic mutations, it appears that the mutation landscape of XWLC bears the closest resemblance to TSLC (Fig. 2a). However, when considering oncogenic pathways (Fig. 2b) and genes (Fig. 2c), there is a notable disparity between the two cohorts. These findings suggest that while XWLC and TSLC exhibit similarities in terms of genomic mutations, they possess distinct characteristics in terms of oncogenic pathways and genes.<br /> Regarding the oncogenic signaling pathways, we referred to ten well-established pathways identified from TCGA cohorts. These members of oncogenic pathways are likely to serve as cancer drivers (functional contributors) or therapeutic targets, as highlighted by Sanchez-Vega et al. in 2018(Sanchez-Vega et al., 2018).

Comments: It is unclear to this reviewer how authors defined "distinct characteristics" in terms of oncogenic pathways and genes. Would 10-20% differences in "Fraction of samples affected" in Fig2b be sufficient to claim significance? How could authors be sure whether mutations in genes involved in each oncogenic pathway are activating or inactivating mutations (rather than benign, thus non-affecting mutations)?

[...]

(6) Supplementary Table 11 shows a number of mutations at the interface and length of interface between a given protein-protein interaction pair. Such that, it does not provide what mutation(s) in a given PPI interface is found in each LC cohort. For example, it fails to provide whether MAD1 R558H and TPRN H550Q mutations are found significantly in each LC cohort.

Response: We appreciate your careful review. In Supplementary Table 11, we have provided significant onco_PPI data for each LC cohort, focusing on enriched mutations at the interface of two proteins. Our emphasis lies on onco_PPI rather than individual mutations, as any mutation occurring at the interface could potentially influence the function of the protein complex. Thus, our Supplementary Table 11 exclusively displays the onco_PPI rather than mutations. MAD1 R558H and TPRN H550Q were identified through onco_PPI analysis, and subsequent extensive literature research led us to focus specifically on these mutations.

Comments: Are authors referring to Table S9 (Onco_PPIs identified in four cohorts) instead of Supplementary Table 11? There is no Table 11 among submitted files. In Table S9, the Column N (length of protein product of gene1) does not make sense: MYO1C (8152), TP53 (3924), EGFR (12961). These should not be the number of amino acids residues of each protein. Then, what do these numbers mean?

(7) Figure 7c and d are simulation data not from an actual binding assay. The authors should perform a biochemical binding assay with proteins or show that the mutation significantly alters the interaction to support the conclusion.

Response: We appreciate your suggestion. The relevant experiments are currently in progress, and we anticipate presenting the corresponding data in a subsequent study.

Comments: The suggested experiment is to support the simulated data. Again, without supporting experimental results, authors could not make a conclusion simply based on simulated data. Where else could the supporting experimental results be presented?

Reviewer #2 (Public review):

Summary:

The article uses a cell-based model to investigate how mutations and cells spread throughout a tumour. The paper uses published data and the proposed model to understand how growth and death mechanisms lead to the observed data. This work provides an insight into the early stages of tumour development. From the work provided here, the results are solid, showing a thorough analysis. The article is well written and presents a very suitable and rigorous analysis to describe the data. The authors did a particularly nice job of the discussion and decision of their "metrics of interest", though this is not the main aim of this work.

Strengths:

Due to the particularly nice and tractable cell-based model, the authors are able to perform a thorough analysis to compare the published data to that simulated with their model. They then used their computational model to investigate different growth mechanisms of volume growth and surface growth. With this approach, the authors are able to compare the metric of interest (here, the direction angle of a new mutant clone, the dispersion of mutants throughout the tumour) to quantify how the different growth models compare to the observed data. The authors have also used inference methods to identify model parameters based on the data observed. The authors performed a rigorous analysis and have chosen the metrics in an appropriate manner to compare the different growth mechanisms.

Context:

Improved mechanistic understanding into the early developmental stages of tumours will further assist in disease treatment and quantification. Understanding how readily and quickly a tumour is evolving is key to understanding how it will develop and progress. This work provides a solid example as to how this can be achieved with data alongside simulated models.

Reviewer #2 (Public review):

Summary:

The authors developed an imaging-based device, that provides both spatial confinement and stiffness gradient, to investigate if and how amoeboid cells, including T cells, neutrophils and Dictyostelium can durotax. Furthermore, the authors showed that the mechanism for the directional migration of T cells and neutrophils depends on non-muscle myosin IIA (NMIIA) polarized towards the soft-matrix-side. Finally, they developed a mathematical model of an active gel that captures the behavior of the cells described in vitro.

Strengths:

The topic is intriguing as durotaxis is essentially thought to be a direct consequence of mechanosensing at focal adhesions. To the best of my knowledge, this is the first report on amoeboid cells that are not dependent on FAs to exert durotaxis. The authors developed an imaging-based durotaxis device that provides both spatial confinement and stiffness gradient and they also utilized several techniques such as quantitative fluorescent speckle microscopy and expansion microscopy. The results of this study have well-designed control experiments and are therefore convincing.

Weaknesses:

Overall this study is well performed but there are still some minor issues I recommend the authors address:<br /> (1) When using NMIIA/NMIIB knockdown cell lines to distinguish the role of NMIIA and NMIIB in amoeboid durotaxis, it would be better if the authors take compensatory effects into account.<br /> (2) The expansion microscopy assay is not clearly described and some details are missed such as how the assay is performed on cells under confinement.<br /> (3) In this study, an active gel model was employed to capture experimental observations. Previously, some active nematic models were also considered to describe cell migration, which is controlled by filament contraction. I suggest the authors provide a short discussion on the comparison between the present theory and those prior models.<br /> (4) In the present model, actin flow contributes to cell migration while myosin distribution determines cell polarity. How does this model couple actin and myosin together?

Reviewer #2 (Public review):

The manuscript by Yorek et al explores the role of fatty acids, particularly unsaturated fatty acids, in lipid droplet accumulation and lipolysis in tumor-associated macrophages (TAMs). Using flow cytometry, immunofluorescent imaging, and TEM, the authors observed that unsaturated fatty acids, such as linoleic acids (LA), tend to induce lipid droplet accumulation in the ER of macrophages, but not in the lysosomes. This phenomenon led them to examine the key enzymes involved in lipid droplet/TAG biosynthesis, where they found incubation of LA upregulates GPAT/DGAT and C/EBPα. In vitro studies, data from public databases, single-cell RNA sequencing of splenic macrophages, and more show that FABP4 emerges as an important mediator for C/EBPα activation. This is further confirmed by FABP4-knockout macrophages, where lipid accumulation and utilization of unsaturated fatty acids were compromised in macrophages through inhibition of LA-induced lipolysis. Using the co-culture system and immunohistochemical analysis, they found that the high FABP4 expression in TAMs, which are observed in metastatic breast cancer tissue, promotes breast cancer cell migration in vitro.

This study is important since the impact of tumor microenvironment is crucial for the development of breast cancer. The individual experiments are well-designed and structured. However, the logic connecting to the next step is a bit difficult to follow, especially when combined with incomplete statistical analysis in some figures, making the conclusion less convincing. For instance, the comparison of macrophage FABP4 expression between breast cancer patients with or without metastasis illustrates the importance of FABP4 expression in metastasis, yet there is no examination of the expression of other key enzymes in the lipolysis or lipid biosynthesis pathway nor there is any correlation with parameters that would reflect patients' consumption of fatty acids. Similarly, an in vivo study comparing FABP4 knockout mice with or without unsaturated fatty acids would yield more compelling evidence. The statistical analysis was largely focused on the sets of unsaturated fatty acids when data from both types of fatty acids were present. In some cases, significant changes are observed in the sets of saturated fat, but there is no explanation of why only the data from unsaturated fats are important for investigation.

Overall, there is solid evidence for the importance of FABP4 expression in TAMs on metastatic breast cancer as well as lipid accumulation by LA in the ER of macrophages. A stronger rationale for the exclusive contribution of unsaturated fatty acids to the utilization of TAMs in breast cancer and a more detailed description and statistical analysis of data will strengthen the findings and resulting claims.

Reviewer #2 (Public review):

Summary:

The authors extend their earlier findings with bacterial adenylyl cyclases to mammalian enzymes. They show that certain aliphatic lipids activate adenylyl cyclases in the absence of stimulatory G proteins and that lipids can modulate activation by G proteins. Adding lipids to cells expressing specific isoforms of adenylyl cyclases could regulate cAMP production, suggesting that adenylyl cyclases could serve as 'receptors'.

Strengths:

This is the first report of lipids regulating mammalian adenylyl cyclases directly. The evidence is based on biochemical assays with purified proteins, or in cells expressing specific isoforms of adenylyl cyclases.

Weaknesses:

It is not clear if the concentrations of lipids used in assays are physiologically relevant. Nor is there evidence to show that the specific lipids that activate or inhibit adenylyl cyclases are present at the concentrations required in cell membranes. Nor is there any evidence to indicate that this method of regulation is seen in cells under relevant stimuli.

Reviewer #2 (Public review):

The manuscript investigates oviductal responses to the presence of gametes and embryos using a multi-omics and machine learning-based approach. By applying RNA sequencing (RNA-seq), single-cell RNA sequencing (sc-RNA-seq), and proteomics, the authors identified distinct molecular signatures in different regions of the oviduct, proximal versus distal. The study revealed that sperm presence triggers an inflammatory response in the proximal oviduct, while embryo presence activates metabolic genes essential for providing nutrients to the developing embryos. Overall, this study offers valuable insights and is likely to be of great interest to reproductive biologists and researchers in the field of oviduct biology. However, further investigation into the impact of sperm on the immune cell population in the oviduct is necessary to strengthen the overall findings.

Reviewer #2 (Public review):

Summary:

Previously, the authors developed a zebrafish model for cerebral cavernous malformations (CCMs) via CRISPR/Cas9-based mosaic inactivation of the ccm2 gene. This model yields CCM-like lesions in the caudal venous plexus of 2 days post-fertilization embryos and classical CNS cavernomas in 8-week fish that depend, like the mouse model, on the upregulation of the KLF2 transcription factor. Remarkably, the morpholino-based knockdown of the gene encoding the Beta1 adrenergic receptor or B1AR (adrb1; a hemodynamic regulator) in fish and treatment with the anti-adrenergic S enantiomer of propranolol in both fish and mice reduce the frequency and size of CMM lesions.

In the present study, the authors aim to test the model that adrb1 is required for CCM lesion development using adrb1 mutant fish (rather than morpholino-mediated knockdown and pharmacological treatments with the anti-adrenergic S enantiomer of propranolol or a racemic mix of metoprolol (a selective B1AR antagonist).

Strengths:

The goal of the work is important, and the findings are potentially highly relevant to cardiovascular medicine.

Weaknesses:

(1) The following figures do not report sample sizes, making it difficult to assess the validity of the findings: Figures 1B and D (the number of scored embryos is missing), Figures 2G and 3B (should report both the number of fish and lesions scored, with color-coding to label the lesions corresponding to individual fish in which they where found).

(2) Figure 4 has a few caveats. First, the use of adrb1 morphants (rather than morphants) is at odds with the authors' goal of using genetic validation to test the involvement of adrb1 in CCM2-induced lesion development.

Second, the authors should clarify if they have validated that the tnnt (tnnt2a) morpholino phenocopies tnnt2a mutants in the context in which they are using it (this reviewer found that the tnnt2a morpholino blocks the heartbeat just like the mutant, but induces additional phenotypes not observed in the mutants).

Third, the data in Figure 4E is from just two embryos per treatment, a tiny sample size. Furthermore, judging from the number of points in the graph, only a few endothelial PCV cells appear to have been sampled per embryo. Also, judging from the photos and white arrowheads and arrows (Figure 4A-D), only the cells at the ventral side of the vessel were scored (if so, the rationale behind this choice requires clarification).

Fourth, it is unclear whether and how the Tg(kdrl:mcherry)is5 endothelial reporter was used to mask the signals from the klf2a reporter. The reviewer knows by experience that accuracy suffers if a cytosolic or cell membrane signal is used to mask a nuclear green signal.

Finally, the text and legend related to Figure 4 could be more explicit. What do the authors mean by a mosaic pattern of endothelial nuclear EGFP intensity, and how is that observation reflected in graph 4E? When I look at the graph, I understand that klf2a is decreased in C-D compared to A-B. Are some controls missing? Suppose the point is to show mosaicism of Klf2a levels upon ccm2 CRISPR. Don't you need embryos without ccm2 CRISPR to show that Klf2a levels in those backgrounds have average levels that vary within a defined range and that in the presence of ccm2 mosaicism, some cells have values significantly outside that range? Also, in 4A-D, what are the white arrowheads and arrows? The legend does not mention them.

Given the practical relevance of the findings to cardiovascular medicine, increasing the strength of the evidence would greatly enhance the value of this work.

Reviewer #2 (Public review):

Summary:

The manuscript by Ma et. al. utilizes a zebrafish melanoma model, single-cell RNA sequencing (scRNA-seq), a mammalian in vitro co-culture system, and quantitative PCR (Q-PCR) gene expression analysis to investigate the role keratinocytes might play within the melanoma microenvironment. Convincing evidence is presented from scRNA-seq analysis showing that a small cluster of melanoma-associated keratinocytes upregulates the master EMT regulator, transcription factor, Twist1a. To investigate how Twist-expressing keratinocytes might influence melanoma development, the authors use an in vivo zebrafish model to induce melanoma initiation while overexpressing Twist in keratinocytes through somatic transgene expression. This approach reveals that Twist overexpression in keratinocytes suppresses invasive melanoma growth. Using a complementary in vitro human cell line co-culture model, the authors demonstrate reduced migration of melanoma cells into the keratinocyte monolayer when keratinocytes overexpress Twist. Further scRNA-seq analysis of zebrafish melanoma tissues reveals that in the presence of Twist-expressing keratinocytes, subpopulations of melanoma cells show altered gene expression, with one unique melanoma cell cluster appearing more terminally differentiated. Finally, the authors use computational methods to predict putative receptor-ligand pairs that might mediate the interaction between Twist-expressing keratinocytes and melanoma cells.

Strengths:

The scRNA-seq approach reveals a small proportion of keratinocytes undergoing EMT within melanoma tissue. The use of a zebrafish somatic transgenic model to study melanoma initiation and progression provides an opportunity to manipulate host cells within the melanoma microenvironment and evaluate their impact on tumour progression. Solid data demonstrate that Twist-expressing keratinocytes can constrain melanoma invasive development in vivo and reduce melanoma cell migration in vitro, establishing that Twist-overexpressing keratinocytes can suppress at least one aspect of tumour progression.

Weaknesses:

While the scRNA-seq analysis of melanoma tissue and RT-PCR analysis of EMT gene expression in isolated keratinocytes provide evidence that a subpopulation of host keratinocytes upregulates Twist and other EMT marker genes and potentially undergoes EMT, the in vivo evidence for keratinocyte EMT within the melanoma microenvironment is based on cell morphology in a single image without detailed characterization and quantification. No EMT marker gene expression was examined in melanoma tissue sections to determine the proportion and localization of Twist+ve keratinocytes within the melanoma microenvironment.

The scRNA-seq UMAP suggests the proportion of EMT keratinocytes within the melanoma microenvironment is very small, raising questions about their precise location and significance within the tumour microenvironment. Although both in vivo and in vitro evidence demonstrates that Twist-expressing keratinocytes can suppress melanoma progression, the conditions modelled by the authors involve over-expression of Twist in all keratinocytes, which do not naturally occur within the melanoma microenvironment and, therefore, might not be relevant to naturally occurring melanoma progression. The author did not test whether blocking EMT through down-regulation of Twist in keratinocytes may influence melanoma development, which would establish the role of Twist expression keratinocytes in the melanoma microenvironment.

To address the potential mechanism by which Twist-expressing keratinocytes suppress melanoma progression, a second scRNA-seq analysis was conducted. However, this analysis is not adequately presented to provide strong evidence for proposed mechanisms for how Twist-expressing keratinocytes suppress melanoma cell invasion. CellChat analysis was used to attempt to identify receptor-ligand pairs that might mediate keratinocyte-melanoma cell interaction, but the interactions between tumour-associated keratinocytes (TAK) and melanoma cells were not included in the analysis. Furthermore, although genetic reporters were used to label both keratinocytes and melanoma cells, no images showing the detailed distribution and positional information of these cells within melanoma tissue are presented in the report. None of the gene expression changes detected through Q-PCR or scRNA-seq were validated using immunostaining or in situ hybridization.

Overall, the data presented in this report draw attention to a less-studied host cell type within the tumour microenvironment, the keratinocytes, which, similar to well-studied immune cells and fibroblasts, could play important roles in either promoting or constraining melanoma development.

Counterintuitively, the authors show that Twist-expressing EMT keratinocytes can constrain melanoma progression. While the detailed mechanisms remain to be uncovered, this is an interesting observation.

Reviewer #2 (Public review):

Summary:

This is important work that helps to uncover how the process of autophagy is initiated - via structural analyses of the initiating ULK1 complex. High-resolution structural details and a mechanistic insight of this complex have been lacking and understanding how it assembles and functions is a major goal of a field that impacts many aspects of cell and disease biology. While we know components of the ULK1 complex are essential for autophagy, how they physically interact is far from clear. The work presented makes use of AlphaFold2 to structurally predict interaction sites between the different subunits of the ULK1 complex (namely ULK1, ATG13, and FIP200). Importantly, the authors go on to experimentally validate that these predicted sites are critical for complex formation by using site-directed mutagenesis and then go on to show that the three-way interaction between these components is necessary to induce autophagy in cells.

Strengths:

The data are very clear. Each binding interface of ATG13 (ATG13 with FIP300/ATG13 with ULK1) is confirmed biochemically with ITC and IP experiments from cells. Likewise, IP experiments with ULK1 and FIP200 also validate interaction domains. A real strength of the work in in their analyses of the consequences of disrupting ATG13's interactions in cells. The authors make CRISPR KI mutations of the binding interface point mutants. This is not a trivial task and is the best approach as everything is monitored under endogenous conditions. Using these cells the authors show that ATG13's ability to interact with both ULK1 and FIP200 is essential for a full autophagy response.

Weaknesses:

I think a main weakness here is the failure to acknowledge and compare results with an earlier preprint that shows essentially the same thing (https://doi.org/10.1101/2023.06.01.543278). Arguably this earlier work is much stronger from a structural point of view as it relies not only on AlphaFold2 but also actual experimental structural determinations (and takes the mechanisms of autophagy activation further by providing evidence for a super complex between the ULK1 and VPS34 complexes). That is not to say that this work is not important, as in the least it independently helps to build a consensus for ULK1 complex structure. Another weakness is that the downstream "functional" consequences of disrupting the ULK1 complex are only minimally addressed. The authors perform a Halotag-LC3 autophagy assay, which essentially monitors the endpoint of the process. There are a lot of steps in between, knowledge of which could help with mechanistic understanding. Not in the least is the kinase activity of ULK1 - how is this altered by disrupting its interactions with ATG13 and/or FIP200?

Reviewer #2 (Public review):

Summary:

The authors tried to determine how PA28g functions in oral squamous cell carcinoma (OSCC) cells. They hypothesized it may act through metabolic reprogramming in the mitochondria.

Strengths:

They found that the genes of PA28g and C1QBP are in an overlapping interaction network after an analysis of a genome database. They also found that the two proteins interact in coimmunoprecipitation and pull-down assays using the lysate from OSCC cells with or without expression of the exogenous genes. They used truncated C1QBP proteins to map the interaction site to the N-terminal 167 residues of C1QBP protein. They observed the levels of the two proteins are positively correlated in the cells. They provided evidence for the colocalization of the two proteins in the mitochondria, the effect on mitochondrial form and function in vitro and in vivo OSCC models, and the correlation of the protein expression with the prognosis of cancer patients.

Weaknesses:

Many data sets are shown in figures that cannot be understood without more descriptions, either in the text or the legend, e.g., Figure 1A. Similarly, many abbreviations are not defined.

Some of the pull-down and coimmunoprecipitation data do not support the conclusion about the PA28g-C1QBP interaction. For example, in Appendix Figure 1B the Flag-C1QBP was detected in the Myc beads pull-down when the protein was expressed in the 293T cells without the Myc-PA28g, suggesting that the pull-down was not due to the interaction of the C1QBP and PA28g proteins. In Appendix Figure 1C, assume the SFB stands for a biotin tag, then the SFB-PA28g should be detected in the cells expressing this protein after pull-down by streptavidin; however, it was not. The Western blot data in Figure 1E and many other figures must be quantified before any conclusions about the levels of proteins can be drawn.

The immunoprecipitation method is flawed as it is described. The antigen (PA28g or C1QBP) should bind to the respective antibody that in turn should binds to Protein G beads. The resulting immunocomplex should end up in the pellet fraction after centrifugation and be analyzed further by Western blot for coprecipitates. However, the method in the Appendix states that the supernatant was used for the Western blot.

To conclude that PA28g stabilizes C1QBP through their physical interaction in the cells, one must show whether a protease inhibitor can substitute PA28q and prevent C1QBP degradation, and also show whether a mutation that disrupts the PA28g-C1QBP interaction can reduce the stability of C1QBP. In Figure 1F, all cells expressed Myc-PA28g. Therefore, the conclusion that PA28g prevented C1QBP degradation cannot be reached. Instead, since more Myc-PA28g was detected in the cells expressing Flag-C1QBP compared to the cells not expressing this protein, a conclusion would be that the C1QBP stabilized the PA28g. Figure 1G is a quantification of Western blot data that should be shown.

The binding site for PA28g in C1QBP was mapped to the N-terminal 167 residues using truncated proteins. One caveat would be that some truncated proteins did not fold correctly in the absence of the sequence that was removed. Thus, the C-terminal region of the C1QBP with residues 168-283 may still bind to the PA29g in the context of full-length protein. In Figure 1I, more Flag-C1QBP 1-167 was pulled down by Myc-PA28g than the full-length protein or the Flag-C1QBP 1-213. Why?

The interaction site in PA28g for C1QBP was not mapped, which prevents further analysis of the interaction. Also, if the interaction domain can be determined, structural modeling of the complex would be feasible using AlphaFold2 or other programs. Then, it is possible to test point mutations that may disrupt the interaction and if so, the functional effect

Reviewer #2 (Public review):

Summary:

In this study, Gao et al. use RNA-seq to identify Hspa2 as one of the earliest transcripts heterogeneously distributed between blastomeres. Functional studies are performed using siRNA knockdown showing Hspa2 may bias cells toward the ICM lineage via interaction with the known methyltransferase CARM1.

Strengths:

This study tackles an important question regarding the origins of the first cell fate decision in the preimplantation embryo. It provides novelty in its identification of Hspa2 as a heterogeneous transcript in the early embryo and proposes a plausible mechanism showing interactions with Carm1. Multiple approaches are used to validate their functional studies (FISH, WB, development rates, proteomics). Given only 4 other transcripts/RNA have been identified at or before the 4-cell stage (LincGET, CARM1, PRDM14, HMGA1), this would be an important addition to our understanding of how TE vs ICM fate is established.

Weaknesses:

The RNA-seq results leading the authors to focus on Hspa2 are not included in the manuscript. This dataset would serve as an important resource but is neither included nor discussed. Nor is it mentioned whether Hspa2 was identified in prior RNA-seq embryos studies (for example Deng Science 2014).

In addition, the functional studies are centered on Hspa2 knockdown at the zygote (1-cell) stage, which would largely target maternal transcript. Given the proposed mechanism relies on Hspa2 heterogeneity post-ZGA (late 2-cell stage), the knockdown studies don't necessarily test this and thus don't provide direct support to the authors' conclusions. The relevance of the study would be improved if the authors could show that zygotic knockdown leads to symmetric Hspa2 levels at the late 2-cell and/or 4-cell stage. It may be possible that zygotic knockdown leads to lower global Hspa2 levels, but that asymmetry is still generated at the 4-cell stage.

Furthermore, the authors show that Hspa2 knockdown at the 1-cell stage lowers total Carm1 levels at the 4-cell stage. However, it is unclear how total abundance within the embryo alters lineage specification within blastomeres. The authors go on to propose a plausible mechanism involving Hspa2 and Carm1 interaction, but do not discuss how expression levels may be involved.

Reviewer #2 (Public review):

Summary:

This manuscript by Bisson et al describes the role of GATA6 to regulate cardiac progenitor cell (CPC) specification and cardiomyocyte (CM) generation using human embryonic stem cells (hESCs). The authors found that GATA6 loss-of-function hESC exhibits early defects in mesendoderm and lateral mesoderm patterning stages. Using RNA-seq and CUT&RUN assays the genes of the Wnt and BMP programs were found to be affected by the loss of GATA6 expression. Modulating Wnt and BMP during early cardiac differentiation can partially rescue CPC and CM defects in GATA6 hetero- and homozygous mutant hESCs.

Strengths:

The studies performed were rigorous and the rationale for the experimental design was logical. The results obtained were clear and supported the conclusions that the authors made regarding the role of GATA6 on Wnt and BMP pathway gene expression.

Weaknesses:

Given the wealth of studies that have been performed in this research area previously, the amount of new information provided in this study is relatively modest. Nevertheless, the results and quite clear and should make a strong contribution to the field.

Reviewer #2 (Public Review):

Summary:

If synaptic input is functionally clustered on dendrites, nonlinear integration could increase the computational power of neural networks. But this requires the right synapses to be located in the right places. This paper aims to address the question of whether such synaptic arrangements could arise by chance (i.e. without special rules for axon guidance or structural plasticity), and could therefore be exploited even in randomly connected networks. This is important, particularly for the dendrites and biological computation communities, where there is a pressing need to integrate decades of work at the single-neuron level with contemporary ideas about network function.

Using an abstract model where ensembles of neurons project randomly to a postsynaptic population, back-of-envelope calculations are presented that predict the probability of finding clustered synapses and spatiotemporal sequences. Using data-constrained parameters, the authors conclude that clustering and sequences are indeed likely to occur by chance (for large enough ensembles), but require strong dendritic nonlinearities and low background noise to be useful.

Strengths:

(1) The back-of-envelope reasoning presented can provide fast and valuable intuition. The authors have also made the effort to connect the model parameters with measured values. Even an approximate understanding of cluster probability can direct theory and experiments towards promising directions, or away from lost causes.

(2) I found the general approach to be refreshingly transparent and objective. Assumptions are stated clearly about the model and statistics of different circuits. Along with some positive results, many of the computed cluster probabilities are vanishingly small, and noise is found to be quite detrimental in several cases. This is important to know, and I was happy to see the authors take a balanced look at conditions that help/hinder clustering, rather than to just focus on a particular regime that works.

(3) This paper is also a timely reminder that synaptic clusters and sequences can exist on multiple spatial and temporal scales. The authors present results pertaining to the standard `electrical' regime (~50-100 µm, <50 ms), as well as two modes of chemical signaling (~10 µm, 100-1000 ms). The senior author is indeed an authority on the latter, and the simulations in Figure 5, extending those from Bhalla (2017), are unique in this area. In my view, the role of chemical signaling in neural computation is understudied theoretically, but research will be increasingly important as experimental technologies continue to develop.

Weaknesses:

(1) The paper is mostly let down by the presentation. In the current form, some patience is needed to grasp the main questions and results, and it is hard to keep track of the many abbreviations and definitions. A paper like this can be impactful, but the writing needs to be crisp, and the logic of the derivation accessible to non-experts. See, for instance, Stepanyants, Hof & Chklovskii (2002) for a relevant example.

It would be good to see a restructure that communicates the main points clearly and concisely, perhaps leaving other observations to an optional appendix. For the interested but time-pressed reader, I recommend starting with the last paragraph of the introduction, working through the main derivation on page 7, and writing out the full expression with key parameters exposed. Next, look at Table 1 and Figure 2J to see where different circuits and mechanisms fit in this scheme. Beyond this, the sequence derivation on page 15 and biophysical simulations in Figures 5 and 6 are also highlights.

(2) I wonder if the authors are being overly conservative at times. The result highlighted in the abstract is that 10/100000 postsynaptic neurons are expected to exhibit synaptic clustering. This seems like a very small number, especially if circuits are to rely on such a mechanism. However, this figure assumes the convergence of 3-5 distinct ensembles. Convergence of inputs from just 2 ensembles would be much more prevalent, but still advantageous computationally. There has been excitement in the field about experiments showing the clustering of synapses encoding even a single feature.

(3) The analysis supporting the claim that strong nonlinearities are needed for cluster/sequence detection is unconvincing. In the analysis, different synapse distributions on a single long dendrite are convolved with a sigmoid function and then the sum is taken to reflect the somatic response. In reality, dendritic nonlinearities influence the soma in a complex and dynamic manner. It may be that the abstract approach the authors use captures some of this, but it needs to be validated with simulations to be trusted (in line with previous work, e.g. Poirazi, Brannon & Mel, (2003)).

(4) It is unclear whether some of the conclusions would hold in the presence of learning. In the signal-to-noise analysis, all synaptic strengths are assumed equal. But if synapses involved in salient clusters or sequences were potentiated, presumably detection would become easier? Similarly, if presynaptic tuning and/or timing were reorganized through learning, the conditions for synaptic arrangements to be useful could be relaxed. Answering these questions is beyond the scope of the study, but there is a caveat there nonetheless.

Reviewer #2 (Public review):

Summary:

In the present work, the authors present an engineering solution to sample preparation in 96-well plates for high-throughput super resolution microscopy via Expansion Microscopy. This is not a trivial problem, as the well cannot be filled with the gel, which would prohibit expansion of the gel. They thus engineered a device that can spot a small droplet of hydrogel solution and keep it in place as it polymerises. It occupies only a small portion space at the center of each well, the gel can expand into all directions and imaging and staining can proceed by liquid handling robots and an automated microscope.

Strengths:

In contrast to Reference 8, the authors system is compatible with standard 96 well imaging plates for high-throughput automated microscopy and automated liquid handling for most parts of the protocol. They thus provide a clear path towards high throughput exM and high throughout super resolution microscopy, which is a timely and important goal.

Addition upon revision:

The authors addressed this reviewer's suggestions.

Reviewer #2 (Public Review):

Summary:

This important work by Meisner et al., developed an automated apparatus (MarmoAPP) to collect a wide array of behavioral data (lever pulling, gaze direction, vocalizations) in marmoset monkeys, with the goal of modernizing collection of behavioral data to coincide with the investigation of neurological mechanisms governing behavioral decision making in an important primate neuroscience model. The authors show a variety of "proof-of-principle" concepts that this apparatus can collect a wide range of behavioral data, with higher behavioral resolution than traditional methods. For example, the authors highlight that typical behavioral experiments on primate cooperation provide around 10 trials per session, while using their approach the authors were able to collect over 100 trials per 20-minute session with the MarmoAAP.

Overall the authors argue that this approach has a few notable advantages:

(1) It enhances behavioral output which is important for measuring small or nuanced effects/changes in behavior;

(2) Allows for more advanced analyses given the higher number of trials per session;

(3) Significantly reduces the human labor of manually coding behavioral outcomes and experimenter interventions such as reloading apparatuses for food or position;

(4) Allows for more flexibility and experimental rigor in measuring behavior and neural activity simultaneously.

Strengths:

The paper is well-written and the MarmoAPP appears to be highly successful at integrating behavioral data across many important contexts (cooperation, gaze, vocalizations), with the ability to measure significantly many more behavioral contexts (many of which the authors make suggestions for).

The authors provide substantive information about the design of the apparatus, how the apparatus can be obtained via a long list of information Apparatus parts and information, and provide data outcomes from a wide number of behavioral and neurological outcomes. The significance of the findings is important for the field of social neuroscience and the strength of evidence is solid in terms of the ability of the apparatus to perform as described, at least in marmoset monkeys. The advantage of collecting neural and freely-behaving behavioral data concurrently is a significant advantage.

Reviewer #2 (Public review):

Summary:

In this work, the authors propose an extension to some of the last author's previous work, where a compositional restricted Boltzmann machine was considered as a generative model of neuron-assembly interaction. They augment this model by recurrent connections between the Boltzmann machine's hidden units, which allow them to explicitly account for temporal dynamics of the assembly activity. Since their model formulation does not allow the training towards a compositional phase (as in the previous model), they employ a transfer learning approach according to which they initialise their model with a weight matrix that was pre-trained using the earlier model so as to essentially start the actually training in a compositional phase. Finally, they test this model on synthetic and actual data of whole-brain light-sheet-microscopy recordings of spontaneous activity from the brain of larval zebrafish.

Strengths:

This work introduces a new model for neural assembly activity. Importantly, being able to capture temporal assembly dynamics is an interesting feature that goes beyond many existing models. While this work clearly focuses on the method (or the model) itself, it opens up an avenue for experimental research where it will be interesting to see if one can obtain any biologically meaningful insights considering these temporal dynamics when one is able to, for instance, relate them to development or behaviour.

Weaknesses:

For most of the work, the authors present their RTRBM model as an improvement over the earlier cRBM model. Yet, when considering synthetic data, they actually seem to compare with a "standard" RBM model. This seems odd considering the overall narrative and that when considering whole-brain zebrafish data, the comparisons were made between RTRBM and cRBM models. For that, the RTRBM model was initialised with the cRBM weight matrix to overcome the fact that RTRBM alone does not seem to converge to a compositional phase, so to cite the latter as reason does not really make sense.

Furthermore, whether the clusters shown in Figure 3E can indeed be described as "spatially localized" is debatable. Especially in view of clusters 3 and 4, this seems a stretch. If receptive fields are described as "spatially localized", arguably, one would expect that they are contained in some small (compared to the overall size of the brain) or specific anatomical brain region. However, this is clearly not the case here.

In addition, the performance comparison for the temporal dynamics of the hidden units actually suggests that the RTRBM (significantly) underperforms where the text says (Line 235f) it outperforms the cRBM model.

Reviewer #2 (Public Review):

Summary:

This article explores the regenerative effects of recombinant PTH analogues on osteogenesis.

Strengths:

Although PTH has known to induce the activity of osteoclasts, accelerating bone resorption, paradoxically its intermittent use has become a common treat for osteoporosis. Previous studies successfully demonstrated this phenomenon in vivo, but most of them used rodent animal models, inevitably having a limitation. In this article, the authors tried to address this, using a beagle model, and assessed the osseointegrative effect of recombinant PTH analogues. As a result, the authors clearly observed the regenerative effects of PTH analogues, and compared the efficacy, using histologic, biochemical, and radiologic measurement for surgical-endocrinal combined large animal models. The data seem to be solid, and has potential clinical implications.

Weaknesses:

All the issues that I raised have been resolved in the revision process.

Overall, this paper is well-written and has clarity and consistency for a broader readership.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors follow up on their previous work showing that in the absence of the Sir2 deacetylase the MCM replicative helicase at the rDNA spacer region is repositioned to a region of low nucleosome occupancy. Here they show that the repositioned displaced MCMs have increased firing propensity relative to non-displaced MCMs. In addition, they show that activation of the repositioned MCMs and low nucleosome occupancy in the adjacent region depend on the chromatin remodeling activity of Fun30.

Strengths:

The paper provides new information on the role of a conserved chromatin remodeling protein in regulation of origin firing and in addition provides evidence that not all loaded MCMs fire and that origin firing is regulated at a step downstream of MCM loading.

Weaknesses:

The relationship between the authors results and prior work on the role of Sir2 (and Fob1) in regulation of rDNA recombination and copy number maintenance is not explored, making it difficult to place the results in a broader context. Sir2 has previously been shown to be recruited by Fob1, which is also required for DSB formation and recombination-mediated changes in rDNA copy number. Are the changes that the authors observe specifically in fun30 sir2 cells related to this pathway? Is Fob1 required for the reduced rDNA copy number in fun30 sir2 double mutant cells?

Reviewer #2 (Public review):

Summary:

Kisspeptin neurons of the arcuate nucleus (ARC) are thought to be responsible for the pulsatile GnRH secretory pattern and to mediate feedback regulation of GnRH secretion by estradiol (E2). Evidence in the literature, including the work of the authors, indicates that ARC kisspeptin coordinate their activity through reciprocal synaptic interactions and the release of glutamate and of neuropeptide neurokinin B (NKB), which they co-express. The authors show here that E2 regulates the expression of genes encoding different voltage-dependent calcium channels, calcium-dependent potassium channels and canonical transient receptor potential (TRPC5) channels and of the corresponding ionic currents in ARC kisspeptin neurons. Using computer simulations of the electrical activity of ARC kisspeptin neurons, the authors also provide evidence of what these changes translate into in terms of these cells' firing patterns. The experiments reveal that E2 upregulates various voltage-gated calcium currents as well as 2 subtypes of calcium-dependent potassium currents, while decreasing TRPC5 expression (an ion channel downstream of NKB receptor activation), the slow excitatory synaptic potentials (slow EPSP) elicited in ARC kisspeptin neurons by NKB release and expression of the G protein-associated inward-rectifying potassium channel (GIRK). Based on these results, and on those of computer simulations, the authors propose that E2 promotes a functional transition of ARC kisspeptin neurons from neuropeptide-mediated sustained firing that supports coordinated activity for pulsatile GnRH secretion to a less intense burst-like firing pattern that could favor glutamate release from ARC kisspeptin. The authors suggest that the latter might be important for the generation of the preovulatory surge in females.

Strengths:

The authors combined multiple approaches in vitro and in silico to gain insights into the impact of E2 on the electrical activity of ARC kisspeptin neurons. These include patch-clamp electrophysiology combined with selective optogenetic stimulation of ARC kisspeptin neurons, reverse transcriptase quantitative PCR, pharmacology and CRISPR-Cas9-mediated knockdown of the Trpc5 gene. The addition of computer simulations for understanding the impact of E2 on the electrical activity of ARC kisspeptin cells is also a strength.

The authors add interesting information on the complement of ionic currents in ARC kisspeptin neurons and on their regulation by E2 to what was already known in the literature. Pharmacological and electrophysiological experiments appear of the highest standards and robust statistical analyses are provided throughout. The impact of E2 replacement on calcium and potassium currents is compelling. Likewise, the results of Trpc5 gene knockdown do provide good evidence that the TRPC5 channel plays a key role in mediating the NKB-mediated slow EPSP. Surprisingly, this also revealed an unsuspected role for this channel in regulating the membrane potential and excitability of ARC kisspeptin neurons.

Weaknesses:

The manuscript also has weaknesses that obscure some of the conclusions drawn by the authors.

One is that the authors compare here two conditions, OVX versus OVX replaced with high E2, that may not reflect the physiological conditions under which the proposed transition between neuropeptide-dependent sustained firing and less intense burst firing might take place (i.e. the diestrous [low E2] and proestrous [high E2] stages of the estrous cycle). This is an important caveat to keep in mind when interpreting the authors' findings. Indeed, that E2 alters certain ionic currents when added back to OVX females, does not mean that the magnitude of all of these ionic currents will vary during the estrous cycle.<br /> In addition, although the computational modeling indicates a role of the various E2-modulated conductances in causing a transition in ARC kisspeptin neuron firing pattern, their role is not directly tested in physiological recordings, weakening the link between these changes and the shift in firing patterns.

Overall, the manuscript provides interesting information about the effects of E2 on specific ionic currents in ARC kisspeptin neurons and some insights into the functional impact of these changes. However, some of the conclusions of the work, with regard, in particular, to the role of these changes in ion channels and to their implications for the LH surge, are not fully supported by the findings.

Reviewer #2 (Public review):

Summary:

This is an interesting work where Wen et al. aimed to shed light on the mechanisms driving the protective role of soluble uric acid (sUA) toward avoiding excessive inflammation. They present biochemical data to support that sUA inhibits the enzymatic activity of CD38 (Figures 1 and 2). In a mouse model of acute response to sUA and using mice deficient in CD38, they find evidence that sUA increases the plasma levels of nicotinamide nucleotides (NAD+ and NMN) (Figure 3) and that sUA reduces the plasma levels of inflammasome-driven cytokines IL-1b and IL-18 in response to endotoxin, both dependent on CD38 (Figure 4). Their work is an important advance in the understanding of the physiological role of sUA, with mechanistic insight that can have important clinical implications.

Strengths:

The authors present evidence from different approaches to support that sUA inhibits CD38, impacts NAD+ levels, and regulates inflammatory responses through CD38.

Weaknesses:

The authors investigate macrophages as the cells affected by sUA in promoting immunoregulation, proposing that sUA's inhibition of CD38 and the resulting increase in NAD+ promotes inflammasome inhibition through a previously established mechanism of NLRP3 regulation by NAD+-dependent sirtuins. However, they were unable to validate their in vivo findings using murine bone marrow-derived macrophages, a standard model for assessing inflammasome activation, due to the low uptake of sUA in these cells. Pharmacological blockage in THP-1 cells provides mechanistic evidence that sUA inhibits NLRP3-mediated secretion of IL-1β through CD38, but genetic evidence and direct assessment of the activation of inflammasome components would be necessary to fully validate the model.

Reviewer #2 (Public review):

Summary / Strengths:

In this manuscript, Klemm et al., build on past published findings (Klemm et al., 2021) to characterize caspase activation in distal cells following necrotic tissue damage within the Drosophila wing imaginal disc. Previously in Klemm et al., 2021, the authors describe necrosis-induced-apoptosis (NiA) following the development of a genetic system to study necrosis that is caused by the expression of a constitutive active GluR1 (Glutamate/Ca2+ channel), and they discovered that the appearance of NiA cells were important for promoting regeneration.

In this manuscript, the authors aim to investigate how tissues regenerate following necrotic cell death. They find that:<br /> (1) the cells of the wing pouch are more likely to have non-autonomous caspase activation than other regions within the wing imaginal disc (hinge and notum),<br /> (2) two signaling pathways that are known to be upregulated during regeneration, Wnt (wingless) and JAK/Stat signaling, act to prevent additional NiA in pouch cells, and may explain the region specificity,<br /> (3) the presence of NiA cells promotes regenerative proliferation in late stages of regeneration,<br /> (4) not all caspase-positive cells are cleared from the epithelium (these cells are then referred to as Necrosis-induced Caspase Positive (NiCP) cells), these NiCP cells continue to live and promote proliferation in adjacent cells,<br /> (5) the caspase Dronc is important for creating NiA/NiCP cells and for these cells to promote proliferation. Animals heterozygous for a Dronc null allele show a decrease in regeneration following necrotic tissue damage.

The study has the potential to be broadly interesting due to the insights into how tissues differentially respond to necrosis as compared to apoptosis to promote regeneration.

Weaknesses:

However, here are some of my current concerns for the manuscript in its current version:

(1) The presence of cells with activated caspase that don't die (NiCP cells) is an interesting biological phenomenon but is not described until Figure 5. How does the existence of NiCP cells impact the earlier findings presented? Is late proliferation due to NiA, NiCP, or both? Does Wg and JAK/STAT signaling act to prevent the formation of both NiA and NiCP cells or only NiA cells? Moreover, the authors are able to specifically manipulate the wound edge (WE) and lateral pouch cells (LP), but don't show how these manipulations within these distinct populations impact regeneration. The authors provide evidence that driving UAS-mir(RHG) throughout the pouch, in the LP or the WE all decrease the amount of NiA/NiCP in Figure 3G-O, but no data on final regenerative outcomes for these manipulations is presented (such as those presented for Dronc-/+ in Fig 7M). The manuscript would be greatly enhanced by quantification of more of the findings, especially in describing if the specific manipulations that impacted NiA /NiCP cells disrupt end-point regeneration phenotypes.

(2) How fast does apoptosis take within the wing disc epithelium? How many of the caspase(+) cells are present for the whole 48 hours of regeneration? Are new cells also induced to activate caspase during this time window? The author presented a number of interesting experiments characterizing the NiCP cells. For the caspase sensor GC3Ai experiments in Figure 5, is there a way to differentiate between cells that have maintained fluorescent CG3Ai from cells that have newly activated caspase? What is the timeline for when NiA and NiCP are specified? In addition, what fraction of NiCP cells contribute to the regenerated epithelium? Additional information about the temporal dynamics of NiA and NiCP specification/commitment would be greatly appreciated.

(3) The notum also does not express developmental JAK/STAT, yet little NiA was observed within the notum. Do the authors have any additional insights into the differential response between the pouch and notum? What makes the pouch unique? Are NiA/NiCP cells created within other imaginal discs and other tissues? Are they similarly important for regenerative responses in other contexts?

Reviewer #2 (Public review):

Summary:

The authors inspect the stability and compensatory plasticity in the retinotopic mapping in patients with congenital achromatopsia. They report an increased cortical thickness in central (eccentricities 0-2 deg) in V1 and the expansion of this effect to V2 (trend) and V3 in a cohort with an average age of adolescents.

In analyzing the receptive fields, they show that V1 had increased receptive field sizes in achromats, but there were no clear signs of reorganization filling in the rod-free area.<br /> In contrast, V3 showed an altered readout of V1 receptive fields. V3 of achromats oversampled the receptive fields bordering the rod-free zone, presumably to compensate and arrive at similar receptive fields as in the controls.

These findings support a retention of peripheral-V1 connectivity, but a reorganization of later hierarchical stages of the visual system to compensate for the loss, highlighting a balance between stability and compensation in different stages of the visual hierarchy.

Strengths:

The experiment is carefully analyzed, and the data convey a clear and interesting message about the capacities of plasticity.

Weaknesses:

The existence of unstable fixation and nystagmus in the patient group is alluded to, but not quantified or modeled out in the analyses. The authors may want to address this possible confound with a quantitative approach.

Reviewer #2 (Public review):

Summary:

A simple and effective method for combinatorial assembly of microbes in synthetic communities of <12 species.

Strengths:

Overall this manuscript is a useful contribution. The efficiency of the method and clarity of the presentation is a strength. It is well-written and easy to follow. The figures are great, the pedagogical narrative is crisp. I can imagine the method being used in lots of other contexts too.

Weaknesses:

The authors could better clarify what HOIs mean. They could address challenges with assaying community function. However, neither of these "weaknesses" affects the primary goal of the paper which is methodological.

Reviewer #2 (Public review):

Summary:

A gustatory receptor and neuron enhances an olfactory behavioral response, proboscis extension.

This manuscript clearly establishes a novel mechanism by which a gustatory receptor and neuron evokes an olfactory-driven behavioral response. The study expands recent observations by Dweck and Carlson (2023) that suggest new and remarkable properties among GRNs in Drosophila. Here, the authors articulate a clear instance of a novel neural and behavioral mechanism for gustatory receptors in an olfactory response.

Strengths:

The systematic and logical use of genetic manipulation, imaging and physiology, and behavioral analysis makes a clear case that gustatory neurons are bona fide olfactory neurons with respect to proboscis extension behavior.

Weaknesses:

No weaknesses were identified by this reviewer.

Reviewer #2 (Public review):

Summary:

In this study, Hill and colleagues use a novel reinforcement-based motor learning task ("RML"), asking how aspects of RML change over the course of development from toddler years through adolescence. Multiple versions of the RML task were used in different samples, which varied on two dimensions: whether the reward probability of a given hand movement direction was deterministic or probabilistic, and whether the solution space had continuous reach targets or discrete reach targets. Using analyses of both raw behavioral data and model fits, the authors report four main results: First, developmental improvements reflected 3 clear changes, including increases in exploration, an increase in the RL learning rate, and a reduction of intrinsic motor noise. Second, changes to the task that made it discrete and/or deterministic both rescued performance in the youngest age groups, suggesting that observed deficits could be linked to continuous/probabilistic learning settings. Overall, the results shed light on how RML changes throughout human development, and the modeling characterizes the specific learning deficits seen in the youngest ages.

Strengths:

(1) This impressive work addresses an understudied subfield of motor control/psychology - the developmental trajectory of motor learning. It is thus timely and will interest many researchers.

(2) The task, analysis, and modeling methods are very strong. The empirical findings are rather clear and compelling, and the analysis approaches are convincing. Thus, at the empirical level, this study has very few weaknesses.

(3) The large sample sizes and in-lab replications further reflect the laudable rigor of the study.

(4) The main and supplemental figures are clear and concise.

Weaknesses:

(1) Framing.<br /> One weakness of the current paper is the framing, namely w/r/t what can be considered "cognitive" versus "non-cognitive" ("procedural?") here. In the Intro, for example, it is stated that there are specific features of RML tasks that deviate from cognitive tasks. This is of course true in terms of having a continuous choice space and motor noise, but spatially correlated reward functions are not a unique feature of motor learning (see e.g. Giron et al., 2023, NHB). Given the result here that simplifying the spatial memory demands of the task greatly improved learning for the youngest cohort, it is hard to say whether the task is truly getting at a motor learning process or more generic cognitive capacities for spatial learning, working memory, and hypothesis testing. This is not a logical problem with the design, as spatial reasoning and working memory are intrinsically tied to motor learning. However, I think the framing of the study could be revised to focus in on what the authors truly think is motor about the task versus more general psychological mechanisms. Indeed, it may be the case that deficits in motor learning in young children are mostly about cognitive factors, which is still an interesting result!

(2) Links to other scholarship.<br /> If I'm not mistaken a common observation in studies of the development of reinforcement learning is a decrease in exploration over-development (e.g., Nussenbaum and Hartley, 2019; Giron et al., 2023; Schulz et al., 2019); this contrasts with the current results which instead show an increase. It would be nice to see a more direct discussion of previous findings showing decreases in exploration over development, and why the current study deviates from that. It could also be useful for the authors to bring in concepts of different types of exploration (e.g. "directed" vs "random"), in their interpretations and potentially in their modeling.

(3) Modeling.<br /> First, I may have missed something, but it is unclear to me if the model is actually accounting for the gradient of rewards (e.g., if I get a probabilistic reward moving at 45˚, but then don't get one at 40˚, I should be more likely to try 50˚ next then 35˚). I couldn't tell from the current equations if this was the case, or if exploration was essentially "unsigned," nor if the multiple-trials-back regression analysis would truly capture signed behavior. If the model is sensitive to the gradient, it would be nice if this was more clear in the Methods. If not, it would be interesting to have a model that does "function approximation" of the task space, and see if that improves the fit or explains developmental changes. Second, I am curious if the current modeling approach could incorporate a kind of "action hysteresis" (aka perseveration), such that regardless of previous outcomes, the same action is biased to be repeated (or, based on parameter settings, avoided).

(4) Psychological mechanisms.<br /> There is a line of work that shows that when children and adults perform RL tasks they use a combination of working memory and trial-by-trial incremental learning processes (e.g., Master et al., 2020; Collins and Frank 2012). Thus, the observed increase in the learning rate over development could in theory reflect improvements in instrumental learning, working memory, or both. Could it be that older participants are better at remembering their recent movements in short-term memory (Hadjiosif et al., 2023; Hillman et al., 2024)?

Reviewer #2 (Public review):

Summary:

This work introduces a novel framework to systematically learn the latent dimensions of single-cell data, grounded in the theory of the Riemannian manifold. The authors demonstrate how this framework can be applied to various important tasks, such as estimating intrinsic dimensionalities, annotating cell types, etc. They did a great job of tackling an important but not yet established problem in the field and approaching it with a theoretically sound and novel approach. I think after a more rigorous and comprehensive validation, this work could be impactful.

Strengths:

(1) Dimensionality reduction is a routine step in analyzing many high-dimensional data, such as molecular data. While the downstream analysis results depend heavily on this step, existing methods rely on strong assumptions and are sometimes heuristic. The authors present a novel, theoretically grounded approach to address this important problem.

(2) The authors demonstrated its usability in downstream analysis in a comprehensive manner. In particular, they show evidence suggesting novel T-cell subpopulations.

(3) I commend the authors for releasing and maintaining their software well with comprehensive documentation. This significantly increases the usability and accessibility of the method.

Weaknesses:

(1) To encourage the single-cell community to adopt this method, the authors should more clearly demonstrate its advantages over existing methods. There are many single cell analysis algorithms that are proposed in each task and some of them are widely used by biologists. However, the comparison in this work is somewhat limited. For example, Even methods mentioned in the relevant work paragraph (2nd paragraph) on page 2 are not all compared, or the reason why they are not included is not discussed. Also, I am curious how PC dimensions are determined. The choice of 300 PCs on page 11 seems arbitrary. Furthermore, the usefulness of dimension-reduced data also depends a lot on the preceding processing steps, such as highly variable gene selection. I understand it is hard to control all those factors, but I think there is room for improvement.

(2) The paper lacks experiments that validate the results. It would be beneficial to see additional evaluation settings with better-established ground truths to more strongly demonstrate the method's effectiveness.

(3) The effect of various parameters, such as those involved in k-nearest neighbors (KNN) or choosing the appropriate Laplacian operator, is not comprehensively explored. How can we ensure the analysis is not overly sensitive to these parameters?

(4) Batch effects are prevalent in single-cell data. The paper does not adequately address how the proposed method handles this issue.

Reviewer #2 (Public review):

Summary:

In a previous study, the investigators had identified through genetic analysis of lines derived from natural populations that lectin-24A was an important gene required for protection against the parasitoid wasp Leptopilina boulardii, albeit only in a specific genetic context depending on an unidentified locus on the third chromosome (Arunkumar, et al., PNAS, 2023). They had documented that the gene is induced upon wasp infection and that the corresponding Lectin-24A binds to the wasp egg prior to hemocyte, mediating a faster encapsulating cellular response. They had identified a polymorphism in susceptible lines that correlated with a 21 nt deficiency in the lectin-24A promoter that removed a proximal NF-kappaB binding site. Here, they follow up this work by first performing a transgenic dissection of this promoter, including the mutations of putative transcription factor binding sites (TFBS) of the JAK-STAT, the Toll pathway, and the GATA family transcription factors. Secondly, they directly affect the expression of genes of the JAK-STAT pathway, of the DIF or Dorsal NF-kappaB transcription factors (and also Relish), and of pannier, the one induced gene of five GATA family members. Of note, the lectin is preferentially expressed in the posterior part of the fat body.

Strengths:

The combination of the analysis of the expression of the lectin-24A gene in cis through mutations in putative TFBS for three families of transcription factors and the analysis in trans of either the genetic pathway (JAK-STAT) or the STAT/DIF/Dorsal/Pannier transcription factors provides a fine-grained description of the regulation of the expression of a humoral effector gene that is induced by parasitoid wasp infestation. Thus, this work goes much beyond the bioinformatics analysis by using a rather thorough experimental approach. The finding of an induction of lectin-24A in the posterior rather than the anterior fat body is interesting yet puzzling. Is it known whether this species of parasitoid wasps deposits its eggs preferentially in the posterior part of the larva?

Weaknesses:

There are some discrepancies between the "cis" and "trans" approaches as regards their effects on basal or induced expression of lectin-24A:

JAK-STAT:<br /> Figure 4D shows that mutating three of six predicted STAT TFBS in the 314 bp promoter leads to a reduction of both basal and induced lectin-24A expression levels, with the gene still being inducible. In contrast, knocking down or out the Drosophila JAK and STAT genes abolished the inducibility of the lectin-24A reporter down or close to basal levels. Conversely, the overactivation of the JAK-STAT pathway led to basal levels that increased to those of induced ones.

Toll pathway:<br /> Figure 4D shows that mutating the proximal Dif-Dorsal TFBS reduces both basal and induced levels of the reporter gene to a common level that is below that of the wild-type basal activity. These data suggest that NF-kappaB signaling is required for both basal and induced expression of Lectin-24A. Affecting either Dif or dorsal gene expression led to opposite changes essentially in the basal expression level of the lectin-24A reporter. Conversely, dorsal overexpression in the fat body and other tissues (hemocytes) led to an enhanced basal expression of the lectin gene.

GATA:<br /> The mutation of the single GATA TFBS in the promoter led to a reduced expression phenotype very similar to that of JAK-STAT TFBS mutations. In contrast, ubiquitous somatic KO mutations of pannier did not affect the basal or induced lectin-24A expression levels. The overactivation of pannier using an allele that cannot be negatively regulated leads to a higher induction of Lectin-24A gene expression, strikingly with basal expression going up to induced levels.

DOI: 10.1038/s41467-024-51496-2

Resource: RRID:Addgene_1864

Curator: @olekpark

SciCrunch record: RRID:Addgene_1864

What is this?

DOI: 10.1038/s41467-024-51620-2

Resource: RRID:Addgene_85430

Curator: @olekpark

SciCrunch record: RRID:Addgene_85430

What is this?

DOI: 10.1038/s41467-024-51909-2

Resource: RRID:Addgene_67975

Curator: @olekpark

SciCrunch record: RRID:Addgene_67975

What is this?

DOI: 10.1038/s41467-024-51860-2

Resource: RRID:Addgene_39481

Curator: @olekpark

SciCrunch record: RRID:Addgene_39481

What is this?

DOI: 10.1038/s41467-024-51828-2

Resource: RRID:Addgene_41393

Curator: @olekpark

SciCrunch record: RRID:Addgene_41393

What is this?

Reviewer #2 (Public review):

Summary:

Through a serial of four experiments, Yuan, Wang and Jiang examined pupil size responses to emotion signals in point-light motion stimuli. Experiment 1 examined upright happy, sad and neutral point-light biological motion (BM) walkers. The happy BM induced a significantly larger pupil response than the neutral, whereas the sad BM evoked a significantly smaller pupil size than the neutral BM. Experiment 2 examined inverted BM walkers. Experiment 3 examined BM stimuli with acceleration removed. No significant effects of emotion were found in neither Experiment 2 nor Experiment 3. Experiment 4 examined scrambled BM stimuli, in which local motion features were preserved while the global configuration was disrupted. Interestingly, the scrambled happy and sad BM led to significant greater pupil size than the scrambled neutral BM at a relatively early time, while no significant difference between the scrambled happy and sad BM was found. Thus, the authors argue that these results suggest multi-level processing of emotions in life motion signals.

Strengths:

The experiments were carefully designed and well-executed, with point-light stimuli that eliminate many potential confounding effects of low-level visual features such as luminance, contrast, and spatial frequency.

Overall, I think this is a well-written paper with solid experimental results that support the claim of the authors, i.e., the human visual system may process emotional information in biological motion at multiple levels. Given the key role of emotion processing in normal social cognition, the results will be of interest not only to basic scientists who study visual perception, but also to clinical researchers who work with patients of social cognitive disorders. In addition, this paper suggests that examining pupil size responses could be a very useful methodological tool to study brain mechanisms underlying emotion processing.

Reviewer #2 (Public review):

Summary:

Sharninghausen et al use a generic screening platform to search for short (5 amino acid) degrons that function in the lumen of the endoplasmic reticulum (ER) of budding yeast. The screen did indeed identify a number of sequences which increased the rate of degradation of their test proteins. Although the effect of the single degron was rather modest the authors could show that by mutimerising the sequence (4x) they obtained degrons that functioned fairly efficiently. Further characterisation indicated that the degrons only functioned when placed at the N-terminus of the target protein and, were dependent on both the proteasome and the segregase Cdc48 (p97) for degradation. The authors also demonstrated that degradation was via the ERAD pathway.

Strengths:

In general, the data presented is supportive of the conclusions drawn and the authors have thus identified a sequence that can be appended onto other ER targeted proteins to mediate their degradation within the lumen of the ER. How useful this will be to the community remains to be seen.

Weaknesses:

While the observation that such mutimerised sequences can act as degrons is an interesting curiosity, it is not clear that such sequences function in vivo. In fact the DegV1 sequence used throughout the paper is not present in any yeast or fungal proteins and the fact that it has to be located at the N-terminus of the protein to induce degradation is at odds with the idea that proteins to be degraded need to be unfolded. Thus, the role of such sequences in vivo is questionable.

Comments on revised manuscript:

Although the role of such degron sequences remains to be determined in vivo, it is clear that the authors have developed a tool that could be useful to the scientific community. The specific points raised were appropriately addressed by the authors.

Reviewer 2 (Public Review):

Accumulating data suggests that the presence of immune cell infiltrates in the meninges of the multiple sclerosis brain contributes to the tissue damage in the underlying cortical grey matter by the release of inflammatory and cytotoxic factors that diffuse into the brain parenchyma. However, little is known about the identity and direct and indirect effects of these mediators at a molecular level. This study addresses the vital link between an adaptive immune response in the CSF space and the molecular mechanisms of tissue damage that drive clinical progression. In this short report the authors use a spatial transcriptomics approach using Visium Gene Expression technology from 10x Genomics, to identify gene expression signatures in the meninges and the underlying brain parenchyma, and their interrelationship, in the PLP-induced EAE model of MS in the SJL mouse. MRI imaging using a high field strength (11.7T) scanner was used to identify areas of meningeal infiltration for further study. They report, as might be expected, the upregulation of genes associated with the complement cascade, immune cell infiltration, antigen presentation, and astrocyte activation. Pathway analysis revealed the presence of TNF, JAK-STAT and NFkB signaling, amongst others, close to sites of meningeal inflammation in the EAE animals, although the spatial resolution is insufficient to indicate whether this is in the meninges, grey matter, or both.

UMAP clustering illuminated a major distinct cluster of upregulated genes in the meninges and smaller clusters associated with the grey matter parenchyma underlying the infiltrates. The meningeal cluster contained genes associated with immune cell functions and interactions, cytokine production, and action. The parenchymal clusters included genes and pathways related to glial activation, but also adaptive/B-cell mediated immunity and antigen presentation. This again suggests a technical inability to resolve fully between the compartments as immune cells do not penetrate the pial surface in this model or in MS. Finally, a trajectory analysis based on distance from the meningeal gene cluster successfully demonstrated descending and ascending gradients of gene expression, in particular a decline in pathway enrichment for immune processes with distance from the meninges.

Reviewer #2 (Public Review):

In the present study, Gardeux et al provide a web-based tool for curated association mapping results from DRP studies. The tool lets users view association results for phenotypes and compare mean phenotype ~ phenotype correlations between studies. In the manuscript, the authors provide several example utilities associated with this new resource, including pan-study summary statistics for sex, traits, and loci. They highlight cross-trait correlations by comparing studies focused on longevity with phenotypes such as oxphos and activity. Strengths: -Considerable efforts were dedicated toward curating the many DRG studies provided. -Available tools to query large DRP studies are sparse and so new tools present appeal Weaknesses: The creation of a tool to query these studies for a more detailed understanding of physiologic outcomes seems underdeveloped. These could be improved by enabling usages such as more comprehensive queries of meta-analyses, molecular information to investigate given genes or pathways, and links to other information such as in mouse rat or human associations.

Reviewer #2 (Public Review):

This work tests the hypothesis that water coordination in WNK kinases is linked to allosteric control of activity. It is proposed that dimeric WNK is inactive and bound to some conserved water molecules, and that monomerization/activation involves departure of these waters. New data here include a crystal structure of monomeric WNK1 which shows missing waters compared to the dimeric structure, in support of the hypothesis. Mutant proteins of a different isozyme (WNK3) designed to disrupt water coordination were produced, and activity and quaternary structure were measured.

Comments on latest version:

The authors have largely addressed my concerns by making sure collection of mutants analyzed for autophosphorylation in Figure 6 are consistent with the measurement of osmotic sensitivity in Figure 7. The other changes in response to reviews have made a stronger manuscript in my opinion.

Reviewer #2 (Public review):

Summary:

Drawing from tools of synthetic biology, Mihajlovic et al. use a cleverly designed experimental system to dissect Ohno's hypothesis, which describes the evolution of functional novelty on the gene-level through the process of duplication & divergence.<br /> Ohno's original idea posits that the redundancy gained from having two copies of the same gene allows one of them to freely evolve a new function. To directly test this, the authors make use of a fluorescent protein with two emission maxima, which allows to apply different selection regimes (e.g. selection for green AND blue, or, for green NOT blue). To achieve this feat without being distracted by more complex evolutionary dynamics caused by the frequent recombination between duplicates, the authors employ a well-controlled synthetic system to prevent recombination: Duplicates are placed on a plasmid as indirect repeats in a recombination-deficient strain of E.coli. The authors implement their directed evolution approach through in vitro mutagenesis and selection using fluorescent-activated cell sorting. Their in-depth analysis of evolved mutants in single-copy versus double-copy genotypes provides clear evidence for Ohno's postulate that redundant copies experience relaxed purifying selection. In contrast to Ohno's original postulate, however, the authors go on to show that this does not in fact lead to more rapid phenotypic evolution, but rather, the rapid inactivation of one of the copies.

Strengths:

This paper contributes with great experimental detail to an area where the literature predominantly leans on genomics data. Through the use of a carefully-designed, well-controlled synthetic system the authors are able to directly determine the phenotype & genotype of all individuals in their evolving populations and compare differences between genotypes with a single or double copy of coGFP. With it they find clear evidence for what critics of Ohno's original model have termed "Ohno's dilemma", the rapid non-functionalization by predominantly deleterious mutations.

Including an expressed but non-functional coGFP in (phenotypically) single copy genotypes provides an especially thoughtful control that allows determining a baseline dN/dS ratio in the absence of selection. All in all the study is an exciting example of how the clever use of synthetic biology can lead to new insights.

Weaknesses:

In the revised version of the paper, the authors now discuss one potential weakness of their study, which is tied to its biggest strength (as often in experimental biology there is a trade-off between 'resolution' and 'realism').<br /> The experimental set-up leaves out an important component of the evolutionary process in order to disentangle dosage effects from other effects that carrying two copies might have on their evolution. Specifically, by employing a recombination-deficient strain and constructing their duplicates as inverted repeats their experimental design completely abolishes recombination between the two copies. This was pointed out in my first review to be problematic for two reasons:

(i) In nature, new duplicates do not arise as inverted, but rather as direct (tandem) repeats and - as the authors correctly point out - these are very unstable, due to the fact that repeated DNA is prone to recA-dependent homologous recombination (which arise orders of magnitude more frequently than point mutations).

(ii) This instability often leads to further amplification of the duplicates under dosage selection both in the lab and in the wild (e.g. Andersson & Hughes, Annu. Rev. Genet. 2009), and would presumably also be an outcome under the current experimental set-up if it was not prevented from happening?

In their revised version, the authors now address this point and with much clarity explain why their experimental system is so powerful to study the fate of a gene duplicate, not despite lacking recombination, but *because* it lacks recombination.

Reviewer #2 (Public review):

Summary:

This study investigated the role of the Caspar (Casp) gene, a Drosophila homolog of human Fas-associated factor-1. It revealed that maternal loss of Casp led to centrosomal and cytoskeletal abnormalities during nuclear cycles in Drosophila early embryogenesis, resulting in defective gastrulation. Moreover, Casp regulates PGC numbers, likely by regulating the levels of Smaug and then Oskar. They demonstrate that Casp protein levels are linearly correlated to the PGC number. The partner protein TER94, an ER protein, shows similar but slightly distinct phenotypes. Based on the deletion mutant analysis, TER94 seems functionally relevant for the observed Casp phenotype. Additionally, it is likely involved in regulating protein degradation during PGC specification.

Strengths:

This paper uncovers a new function of the Casper (Casp) gene, previously known for its role in immune response regulation and NF-kB signaling inhibition. This new function includes nuclear division and PGC formation in early fly embryos. The findings provide crucial insights into how this pathway contributes to the proper establishment of both somatic cells and the germline, particularly in the context of early embryogenesis. This research is therefore of significant interest to cell and developmental biologists.

Future Research:

While this study has made significant strides in understanding the role of the Casp gene in early embryogenesis, the functional relationships among molecules shown here (Casp, TER94, Osk) and other genes previously known to regulate these processes remain unclear. This underscores the need for future studies to delve deeper into these relationships and their implications.

Reviewer #2 (Public review):

Summary:

The authors have collected a significant amount of data from the literature on the flow regimes associated with microorganisms whose propulsion is achieved through the action of cilia or flagella, with particular interest in the competition between sessile and motile lifestyles. They then use several distinct hydrodynamic models for the cilia-driven flows to quantify the nutrient uptake and clearance rate, reported as a function of the Peclet number. Among the interesting conclusions the authors draw concerns the question of whether, for certain ciliates, there is a clear difference in nutrient uptake rates in the sessile versus motile forms. The authors show that this is not the case, thereby suggesting that the evolutionary pressure associated with such a difference is not present. The analysis also includes numerical calculations of the uptake rate for spherical swimmers in the regime of large Peclet numbers, where the authors note an enhancement due to advection-generated thinning of the solutal boundary layer around the organism.

Strengths:

In addressing the whole range of organism sizes and Peclet numbers the authors have achieved an important broad perspective on the problem of nutrient uptake of ciliates, with implications for understanding evolutionary driving forces toward particular lifestyles (e.g. sessile versus motile).

Reviewer #4 (Public review):

Summary:

Wilmes and colleagues develop a model for the computation of uncertainty modulated prediction errors based on an experimentally inspired cortical circuit model for predictive processing. Predictive processing is a promising theory of cortical function. An essential aspect of the model is the idea of precision weighting of prediction errors. There is ample experimental evidence for prediction error responses in cortex. However, a central prediction of the theory is that these prediction error responses are regulated by the uncertainty of the input. Testing this idea experimentally has been difficult due to a lack of concrete models. This work provides one such model and makes experimentally testable predictions.

Strengths:

The model proposed is novel and well-implemented. It has sufficient biological accuracy to make useful and testable predictions.

Weaknesses:

One key idea the model hinges on is that stimulus uncertainty is encoded in the firing rate of parvalbumin positive interneurons. This assumption, however, is rather speculative and there is no direct evidence for this.

Reviewer #2 (Public review):

In this study, Nguyen et al. showed that cat saliva can robustly induce freezing behavior in mice. This effect is mediated through accessory olfactory system as it requires physical contact and is abolished in Trp2 KO mice. The authors further showed that V2R-A4 cluster is responsive to cat saliva. Lastly, they demonstrated c-Fos induction in AOB and VMHdm/c by the cat saliva. The c-Fos level in the VMHdm/c is correlated with freezing response.

Strength:

The study opens an interesting direction. It reveals the potential neural circuit for detecting cat saliva and driving defense behavior in mice. The behavior results and the critical role of accessory olfactory system in detecting cat saliva are clear and convincing.

Weakness:

The findings are relatively preliminary. The identities of the receptor and the ligand in the cat saliva that induces the behavior remain unclear. The identity of VMH cells that are activated by the cat saliva remains unclear. There is a lack of targeted functional manipulation to demonstrate the role of V2R-A4 or VMH cells in the behavioral response to the cat saliva.

Here are some specific comments:

(1) This result suggests that V2R-A4 may be the dominant VR for mice to detect cat saliva. Future studies should determine the identity of the receptor and the ligand in the cat saliva. Additionally, the functional importance of V2R-A4 remains unclear. It is important to knockout the receptor and test changes in cat saliva-induced freezing.

(2) AOB does not project to VMH directly. Other known important nodes for the predator defense circuit includes MeApv, BNST, PMd, AHN and PAG. It will be helpful to provide c-Fos data in those regions (especially MEA and BNST as they are between AOB and VMH) to provide a complete picture regarding how the brain process cat saliva to induce the behavior change.

(3) It is interesting that activation level difference in the VNO by old and fresh cat saliva does not transfer to AOB. It could be informative to examine correlation between VNO and AOB p6/c-Fos cell number and AOB and VMH c-Fos cell number across animals to understand whether the activation level across those regions are related. If they are not correlated, it could be helpful to add a discussion regarding potential reasons, e.g. neuromodulatory inputs to the AOB.

(4) Please indicate n in all figure plots and specify what individual dots means. In Figure 4h, there are 7 dots in old saliva group, presumably indicating 7 animals. In Figure 6b, there appear to be more than 7 dots for old cat saliva group. Are there more than 7 animals? If so, why are they not included in Figure 4h? If not, what does each dot mean? Note that each dot should represent independent sample. One animal should not contribute more than one dot.

(5) The identification of a cluster of VMHdm cells uniquely activated by fresh cat saliva urine is interesting. It will be important to identify the molecular handle of the cells to facilitate further investigation. This could be achieved using either activity dependent RNAseq or double in situ of saliva-induced c-Fos and candidate genes (candidate gene may be identified based on the known gene expression pattern).

Reviewer #2 (Public review):

Schwintek et al. investigated whether a geological setting of a rock pore with water inflow on one end and gas passing over the opening of the pore on the other end could create a non-equilibrium system that sustains nucleic acid reactions under mild conditions. The evaporation of water as the gas passes over it concentrates the solutes at the boundary of evaporation, while the gas flux induces momentum transfer that creates currents in the water that push the concentrated molecules back into the bulk solution. This leads to the creation of steady-state regions of differential salt and macromolecule concentrations that can be used to manipulate nucleic acids. First, the authors showed that fluorescent bead behavior in this system closely matched their fluid dynamic simulations. With that validation in hand, the authors next showed that fluorescently labeled DNA behaved according to their theory as well. Using these insights, the authors performed a FRET experiment that clearly demonstrated the hybridization of two DNA strands as they passed through the high Mg++ concentration zone, and, conversely, the dissociation of the strands as they passed through the low Mg++ concentration zone. This isothermal hybridization and dissociation of DNA strands allowed the authors to perform an isothermal DNA amplification using a DNA polymerase enzyme. Crucially, the isothermal DNA amplification required the presence of the gas flux and could not be recapitulated using a system that was at equilibrium. These experiments advance our understanding of the geological settings that could support nucleic acid reactions that were key to the origin of life.

The presented data compellingly supports the conclusions made by the authors. To increase the relevance of the work for the origin of life field, the following experiments are suggested:

(1) While the central premise of this work is that RNA degradation presents a risk for strand separation strategies relying on elevated temperatures, all of the work is performed using DNA as the nucleic acid model. I understand the convenience of using DNA, especially in the latter replication experiment, but I think that at least the FRET experiments could be performed using RNA instead of DNA.

(2) Additionally, showing that RNA does not degrade under the conditions employed by the authors (I am particularly worried about the high Mg++ zones created by the flux) would further strengthen the already very strong and compelling work.

(3) Finally, I am curious whether the authors have considered designing a simulation or experiment that uses the imidazole- or 2′,3′-cyclic phosphate-activated ribonucleotides. For instance, a fully paired RNA duplex and a fluorescently-labeled primer could be incubated in the presence of activated ribonucleotides +/- flux and subsequently analyzed by gel electrophoresis to determine how much primer extension has occurred. The reason for this suggestion is that, due to the slow kinetics of chemical primer extension, the reannealing of the fully complementary strands as they pass through the high Mg++ zone, which is required for primer extension, may outcompete the primer extension reaction. In the case of the DNA polymerase, the enzymatic catalysis likely outcompetes the reannealing, but this may not recapitulate the uncatalyzed chemical reaction.

Reviewer #2 (Public review):

The current study by Lejeune et al. investigates factors that allow for persistent MRSA infection in the GI tract. They developed an intriguing model of intestinal MRSA infection that does not use the traditional antibiotic approach, thereby allowing for a more natural infection that includes the normal intestinal microbiota. This model is more akin to what might be expected to be observed in a healthy human host. They find that biological sex plays a clear role in bacterial persistence during infection but only in mice bred at an NYU Facility and not those acquired from Jackson Labs. This clearly indicates a role for the intestinal microbiome in affecting female bacterial persistence but not male persistence which was unaffected by the origin of the mice and thus the microbiome. Through a series of clever microbiome-specific transfer experiments, they determine that the NYU-specific microbiome plays a role in this sexual dimorphism but is not solely responsible. Additional experiments indicate that Th17 cells, estrogen, and neutrophils also participate in the resistance to persistent infection. Notably, they assess the role of sex chromosomes (X/Y) using the established four core genotype model and find that these chromosomes appear to play little role in bacterial persistence.

Overall, the paper nicely adds to the growing body of literature investigating how biological sex impacts the immune system and the burden of infectious disease. The conclusions are mostly supported by the data although there are some aspects of the data that could be better addressed and clarified.

(1) There is something of a disconnect between the initial microbiome data and the later data that analyzes sex hormones and chromosomes. While there are clearly differences in microbial species across the two sites (NYU and JAX) how these bacterial species might directly interact with immune cells to induce female-specific responses is left unexplored. At the very least it would help to try and link these two distinct pieces of data to try and inform the reader how the microbiome is regulating the sex-specific response. Indeed, the reader is left with no clear exploration of the microbiota's role in the persistence of the infection and thus is left wanting.

(2) While the authors make a reasonable case that Th17 T cells are important for controlling infection (using RORgt knockout mice that cannot produce Th17 cells), it is not clear how these cells even arise during infection since the authors make most of the observations 2 days post-infection which is longer before a normal adaptive immune response would be expected to arise. The authors acknowledge this, but their explanation is incomplete. The increase in Th17 cells they observe is predicated on mitogenic stimulation, so they are not specific (at least in this study) for MRSA. It would be helpful to see a specific restimulation of these cells with MRSA antigens to determine if there are pre-existing, cross-reactive Th17 cells specific for MRSA and microbiota species which could then link these two as mentioned above.

(3) The ovariectomy experiment demonstrates a role for ovarian hormones; however, it lacks a control of adding back ovarian hormones (or at least estrogen) so it is not entirely obvious what is causing the persistence in this experiment. This is especially important considering the experiments demonstrating no role for sex chromosomes thus demonstrating that hormonal effects are highly important. Here it leaves the reader without a conclusive outcome as to the exact hormonal mechanism.

(4) The discussion is underdeveloped and is mostly a rehash of the results. It would greatly enhance the manuscript if the authors would more carefully place the results in the context of the current state of the field including a more enhanced discussion of the role of estrogen, microbiome, and T cells and how the field might predict these all interact and how they might be interacting in the current study as well.

Reviewer #2 (Public review):

Summary:

The authors aimed to determine whether goal-directed and cue-driven attentional strategies (goal- and sign-tracking phenotypes) were associated with variation in cued motor responses and dorsomedial striatal (DMS) glutamate transmission. They used a treadmill task in which cues indicated whether rats should turn or stop to receive a reward. They collected and analyzed several behavioral measures related to task performance with a focus on turns (performance, latency, duration) for which there are more measures than for stops. First, they established that goal-trackers perform better than sign-trackers in post-criterion turn performance (cued turns completed) and turn initiation. They used glutamate sensors to measure glutamate transmission in DMS. They performed analyses on glutamate traces that suggest phasic glutamate DMS dynamics to cues were primarily associated with successful turn performance and were more characteristic of goal-trackers (ie. rats with "goal-directed" attentional strategy). Smaller and more frequent DMS glutamate peaks were associated with other task events, cued misses (missed turns), cued stops, and reward delivery and were more characteristic of sign-trackers (i.e. rats with "cue-driven" attentional strategies). Consistent with the reported glutamate findings, chemogenetic inhibition of prelimbic-DMS glutamate transmission had an effect on goal-trackers' turn performance without affecting sign-trackers' performance in the treadmill task.

Strengths:

The power of the sign- and goal-tracking model to account for neurobiological and behavioral variability is critically important to the field's understanding of the heterogeneity of the brain in health and disease. The approach and methodology are sound in their contribution to this important effort.

The authors establish behavioral differences, measure a neurobiological correlate of relevance, and then manipulate that correlate in a broader circuitry and show a causal role in behavior that is consistent with neurobiological measurements and phenotypic differences.

Sophisticated analyses provide a compelling description of the authors' observations.

Weaknesses:

It is challenging to assess what is considered the "n" in each analysis (trial, session, rat, trace (averaged across a session or single trial)). Representative glutamate traces (n = 5 traces (out of hundreds of recorded traces)) are used to illustrate a central finding, while more conventional trial-averaged population activity traces are not presented or analyzed. The latter would provide much-needed support for the reported findings and conclusions. Digging deeper into the methods, results, and figure legends, provides some answers to the reader, but much can be done to clarify what each data point represents and, in particular, how each rat contributes to a reported finding (ie. single trial-averaged trace per session for multiple sessions, or dozens of single traces across multiple sessions).

Representative traces should in theory be consistent with population averages within phenotype, and if not, discussion of such inconsistencies would enrich the conclusions drawn from the study. In particular, population traces of the phasic cue response in GT may resemble the representative peak examples, while smaller irregular peaks of ST may be missed in a population average (averaged prolonged elevation) and could serve as a rationale for more sophisticated analyses of peak probability presented subsequently.

Reviewer #2 (Public review):

Summary:

The manuscript describes an interesting observation and provides initial steps towards understanding the underlying molecular mechanism.

The manuscript describes that the majority of non-tumorigenic mammary gland epithelial cells (MCF-10A) in suspension initiate entosis. A smaller fraction of cells form a single giant unilocular vacuole (hereafter referred to as a GUVac). GUVac appeared to be empty and did not contain invading (entotic) cells. The formation of GUVac could be promoted by disrupting actin polymerisation with LatB and CytoD. The formation of GUVacs correlated with resistance to anoikis. GUVac formation was detected in several other epithelial cells from secretory tissues.

The authors then use electron microscopy and super-resolution imaging to describe the biogenesis of GUVac. They find that GUVac formation is initiated by a micropinocytosis-like phenomenon (that is independent of actin polymerisation). This process leads to the formation of large plasma membrane invaginations, that pinch off from the PM to form larger vesicles that fuse with each other into GUVacs.

Inhibition of actin polymerisation in suspended MCF-10a leads to the recruitment of Septin 6 to the PM via its amphipathic helix. Treatment with FCF (a septin polymerisation inhibitor) blocked GUVac biogenesis, as did pharmacological inhibition of dynamin-mediated membrane fission. The fusion of these vesicles in GUVacs required (perhaps not surprisingly) PI3P.

Strengths:

The authors have made an interesting and potentially important observation. They describe the formation of an endo-lysosomal organelle (a giant unilocular vacuole - GUVac) in suspended epithelial cells and correlate the formation of GUVacs with resistance to aniokis.

Comments on revised version:

Additional experiments, including a better characterization of GUVac biogenesis, as well as knockdown and knock out of class II PI3Kα (PI3K-C2α) or class III PI3K (VPS34), have improved the manuscript.

Reviewer #2 (Public review):

Summary:

In this report Abidi et al. use an antibody against Jag2, a Notch1 ligand, to inhibit its activity in skin. A single dose of this treatment leads to an impairment of sebocyte differentiation and an accumulation of basal sebocytes. Consistently Notch1 activity, measured as cleaved form of the Notch1 intracellular domain, is detected in basal sebocytes together with the expression of Jag2. Interestingly the phenotype caused by the antibody treatment is reversible.

Strengths:

The quality of the histological data with a clear phenotype, together with the quantification represents a solid base for the authors claims.<br /> This work identifies that the ligand Jag2 is the Notch1 ligand required for sebocyte differentiation.<br /> From a therapeutic point of view, it is interesting that the treatment with the anti-Jag2 is reversible.

Weaknesses:

The authors use a single approach to support their claims.<br /> Future in vitro studies will be needed to understand how Notch signaling induces sebocyte differentiation (i.e. a cell-autonomous mechanism, a mechanism based on cell competition, etc.).

Reviewer #2 (Public review):

Summary:

The authors identify a novel protein, FipA, which facilitates recruitment of FlhF to the membrane at the cell pole together with the known recruitment factor HupB. This finding is key to understanding the mechanism of polar localization. By comparing the role of FipA in polar flagellum assembly in three different species from Vibrio, Shewanella and Pseudomonas, they discover that, while FipA is required in all three systems, evolution has brought different nuances that open avenues for further discoveries.

Strengths:

The discovery of a novel factor for polar flagellum development. A significant contribution to our understanding of flagellar evolution. The solid nature and flow of the experimental work.

Weaknesses:

All my concerns have been addressed. I find no weaknesses. A nice, solid piece of work.

Reviewer #2 (Public Review):

Summary:

Zeng et al. investigated the role of LDH in determining the metabolic fate of pyruvate in HeLa and 4T1 cells. To do this, three broad perturbations were applied: knockout of two LDH isoforms (LDH-A and LDH-B), titration with a non-competitive LDH inhibitor (GNE-140), and exposure to either normoxic (21% O2) or hypoxic (1% O2) conditions. They show that knockout of either LDH isoform alone, though reducing both protein level and enzyme activity, has virtually no effect on either the incorporation of a stable 13C-label from a 13C6-glucose into any glycolytic or TCA cycle intermediate, nor on the measured intracellular concentrations of any glycolytic intermediate (Figure 2). The only apparent exception to this was the NADH/NAD+ ratio, measured as the ratio of F420/F480 emitted from a fluorescent tag (SoNar).

The addition of a chemical inhibitor, on the other hand, did lead to changes in glycolytic flux, the concentrations of glycolytic intermediates, and in the NADH/NAD+ ratio (Figure 3). Notably, this was most evident in the LDH-B-knockout, in agreement with the increased sensitivity of LDH-A to GNE-140 (Figure 2). In the LDH-B-knockout, increasing concentrations of GNE-140 increased the NADH/NAD+ ratio, reduced glucose uptake, and lactate production, and led to an accumulation of glycolytic intermediates immediately upstream of GAPDH (GA3P, DHAP, and FBP) and a decrease in the product of GAPDH (3PG). They continue to show that this effect is even stronger in cells exposed to hypoxic conditions (Figure 4). They propose that a shift to thermodynamic unfavourability, initiated by an increased NADH/NAD+ ratio inhibiting GAPDH explains the cascade, calculating ΔG values that become progressively more endergonic at increasing inhibitor concentrations.

Then - in two separate experiments - the authors track the incorporation of 13C into the intermediates of the TCA cycle from a 13C6-glucose and a 13C5-glutamine. They use the proportion of labelled intermediates as a proxy for how much pyruvate enters the TCA cycle (Figure 5). They conclude that the inhibition of LDH decreases fermentation, but also the TCA cycle and OXPHOS flux - and hence the flux of pyruvate to all of those pathways. Finally, they characterise the production of ATP from respiratory or fermentative routes, the concentration of a number of cofactors (ATP, ADP, AMP, NAD(P)H, NAD(P)+, and GSH/GSSG), the cell count, and cell viability under four conditions: with and without the highest inhibitor concentration, and at norm- and hypoxia. From this, they conclude that the inhibition of LDH inhibits the glycolysis, the TCA cycle, and OXPHOS simultaneously (Figure 7).

Strengths:

The authors present an impressively detailed set of measurements under a variety of conditions. It is clear that a huge effort was made to characterise the steady-state properties (metabolite concentrations, fluxes) as well as the partitioning of pyruvate between fermentation as opposed to the TCA cycle and OXPHOS.

A couple of intermediary conclusions are well supported, with the hypothesis underlying the next measurement clearly following. For instance, the authors refer to literature reports that LDH activity is highly redundant in cancer cells (lines 108 - 144). They prove this point convincingly in Figure 1, showing that both the A- and B-isoforms of LDH can be knocked out without any noticeable changes in specific glucose consumption or lactate production flux, or, for that matter, in the rate at which any of the pathway intermediates are produced. Pyruvate incorporation into the TCA cycle and the oxygen consumption rate are also shown to be unaffected.

They checked the specificity of the inhibitor and found good agreement between the inhibitory capacity of GNE-140 on the two isoforms of LDH and the glycolytic flux (lines 229 - 243). The authors also provide a logical interpretation of the first couple of consequences following LDH inhibition: an increased NADH/NAD+ ratio leading to the inhibition of GAPDH, causing upstream accumulations and downstream metabolite decreases (lines 348 - 355).

Weaknesses:

Despite the inarguable comprehensiveness of the data set, a number of conceptual shortcomings afflict the manuscript. First and foremost, reasoning is often not pursued to a logical conclusion. For instance, the accumulation of intermediates upstream of GAPDH is proffered as an explanation for the decreased flux through glycolysis. However, in Figure 3C it is clear that there is no accumulation of the intermediates upstream of PFK. It is unclear, therefore, how this traffic jam is propagated back to a decrease in glucose uptake. A possible explanation might lie with hexokinase and the decrease in ATP (and constant ADP) demonstrated in Figure 6B, but this link is not made.

The obvious link between the NADH/NAD+ ratio and pyruvate dehydrogenase (PDH) is also never addressed, a mechanism that might explain how the pyruvate incorporation into the TCA cycle is impaired by the inhibition of LDH (the observation with which they start their discussion, lines 511 - 514).

It was furthermore puzzling how the ΔG, calculated with intracellular metabolite concentrations (Figures 3 and 4) could be endergonic (positive) for PGAM at all conditions (also normoxic and without inhibitor). This would mean that under the conditions assayed, glycolysis would never flow completely forward. How any lactate or pyruvate is produced from glucose, is then unexplained.

Finally, the interpretation of the label incorporation data is rather unconvincing. The authors observe an increasing labelled fraction of TCA cycle intermediates as a function of increasing inhibitor concentration. Strangely, they conclude that less labelled pyruvate enters the TCA cycle while simultaneously less labelled intermediates exit the TCA cycle pool, leading to increased labelling of this pool. The reasoning that they present for this (decreased m2 fraction as a function of DHE-140 concentration) is by no means a consistent or striking feature of their titration data and comes across as rather unconvincing. Yet they treat this anomaly as resolved in the discussion that follows.

Reviewer #2 (Public review):

Summary:

The authors are trying to test the hypothesis that ATP bursts are the predominant driver of antibiotic lethality of Mycobacteria.

Strengths:

This reviewer has not identified any significant strengths of the paper in its current form.

Weaknesses:

A major weakness is that M. smegmatis has a doubling time of three hours and the authors are trying to conclude that their data would reflect the physiology of M. tuberculossi which has a doubling time of 24 hours. Moreover, the authors try to compare OD measurements with CFU counts and thus observe great variabilities.

If the authors had evidence to support the conclusion that ATP burst is the predominant driver of antibiotic lethality in mycobacteria then this paper would be highly significant. However, with the way the paper is written, it is impossible to make this conclusion.

Reviewer #2 (Public review):

In this study, the authors investigate the role of caspases in neuronal modulation through non-lethal activation. They analyze proximal proteins of executioner caspases using a variety of techniques, including TurboID and a newly developed monitoring system based on Gal4 manipulation, called MASCaT. They demonstrate that overexpression of Fas3G promotes the non-lethal activation of caspase Dronc in olfactory receptor neurons. In addition, they investigate the regulatory mechanisms of non-lethal function of caspase by performing a comprehensive analysis of proximal proteins of executioner caspase Drice. It is important to point out that the authors use an array of techniques from western blot to behavioral experiments and also that the generated several reagents, from fly lines to antibodies.

This is an interesting work that would appeal to readers of multiple disciplines. As a whole these findings suggest that overexpression of Fas3G enhances a non-lethal caspase activation in ORNs, providing a novel experimental model that will allow for exploration of molecular processes that facilitate caspase activation without leading to cell death.

Reviewer #2 (Public review):

Summary:

The compass network is a higher-order circuit in insects that integrates sensory cues, like the angle of polarized light, with self-motion information to estimate the animal's angular position in space. This paper by Rother et al. uses share electrode recordings to measure intracellular voltage activity from individual compass neurons while polarization patterns are presented to the bee. They present patterns that rotate with variable speed or simulate the sensory experience created by a flight trajectory. The authors discover that at low rotational speeds, TL neuron responses diverge from the tuning expected from a systematic synaptic delay, suggesting that recent experience (history) impacts TL responses. A population model of 180 TL neurons is then used to argue that having cells that are impacted by spiking history could be advantageous for estimating heading. The model activity showed an anticipation of polarization angle for rapid turns that followed prolonged straight flights or turns in the opposite direction. The model also had reduced spiking activity during translational straight flight.

Strengths:

One strength of this paper is that it focuses on a question that is underexplored in the field: How does the compass network handle the processing delay caused by multi-synaptic relay from the DRA to the sensory input neurons (TL) to the compass network why the insect is turning rapidly and thus sampling distinct polarization angles in rapid succession? Another strength is the fact that they were able to present neurons with both simulated naturalistic polarization patterns that could occur during flight and synthetic stimuli with a range of rotational velocities. This provides an important data set where these responses can be compared. Another strength is the exploration of how adding a history term to a model of a population of TL neurons can lead to the population coding of polarization angle to vary in how delayed it is from changes to the sensory stimuli. They find that angular coding is more anticipatory (shorter delay) following prolonged periods of fixating a single angle, such as what occurs during translation movement, or following turns in the opposite direction of the current turn.

Weaknesses:

A challenge for this experimental approach is the relatively low power for data sets in some of the experimental conditions. Low throughput is expected for this experimental approach, as intracellular recordings are a challenging and time-consuming method. A weakness of the manuscript in its current form is that the data from all cells that were able to be recorded is not always presented or quantified. For example, only a single neuron example is used to show the impact of history on preferred polarization and how this tuning varied with rotation velocity. This is also true for the claim that TL3 neurons exhibit post-inhibitory excitation and post-excitatory inhibition. Another concern is regarding the use of the term "spiking-history" as potentially confusing to readers who might assume this process is cell intrinsic. The authors presented data shows evidence of an effect of stimulus history on the responses of the neurons. However as the authors describe in the discussion this current data set does not distinguish between an effect that occurs in the recorded neurons (e.g. an effect of intrinsic excitability) vs adaptation elsewhere in the circuit or DRA photoreceptors. A final challenge for this approach, shared with other studies that measure neural responses from an insect fixed in place, is that it assumes that these TL neurons are purely sensory and that their response properties (or those upstream of them) do not change when the bee performs a motor action or maneuver. This caveat should be considered when interpreting these data, however these data still represent novel information and important progress in exploring this question.

DOI: 10.1242/dev.201163

Resource: RRID:ZFIN_ZDB-GENO-240529-2

Curator: @olekpark

SciCrunch record: RRID:ZFIN_ZDB-GENO-240529-2

What is this?

DOI: 10.1016/j.ydbio.2024.09.008

Resource: (ZFIN Cat# ZDB-GENO-141031-2,RRID:ZFIN_ZDB-GENO-141031-2)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-GENO-141031-2

What is this?

DOI: 10.1016/j.ydbio.2024.09.008

Resource: (ZFIN Cat# ZDB-GENO-071003-2,RRID:ZFIN_ZDB-GENO-071003-2)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-GENO-071003-2

What is this?

Reviewer #2 (Public review):

Summary:

The authors combined time-lapse microscopy with biophysical modeling to study the mechanisms and timescales of gliding and reversals in filamentous cyanobacterium Fluctiforma draycotensis. They observed the highly coordinated behavior of protein complexes moving in a helical fashion on cells' surfaces and along individual filaments as well as their de-coordination, which induces buckling in long filaments.

Strengths:

The authors provided concrete experimental evidence of cellular coordination and de-coordination of motility between cells along individual filaments. The evidence is comprised of individual trajectories of filaments that glide and reverse on surfaces as well as the helical trajectories of membrane-bound protein complexes that move on individual filaments and are implicated in generating propulsive forces.

Limitations:

The biophysical model is one-dimensional and thus does not capture the buckling observed in long filaments. I expect that the buckling contains useful information since it reflects the competition between bending rigidity, the speed at which cell synchronization occurs, and the strength of the propulsion forces.

Future directions:

The study highlights the need to identify molecular and mechanical signaling pathways of cellular coordination. In analogy to the many works on the mechanisms and functions of multi-ciliary coordination, elucidating coordination in cyanobacteria may reveal a variety of dynamic strategies in different filamentous cyanobacteria.

Reviewer #2 (Public Review):

Boocock and colleagues present an approach whereby eQTL analysis can be carried out by scRNA-Seq alone, in a one-pot-shot experiment, due to genotypes being able to be inferred from SNPs identified in RNA-Seq reads. This approach obviates the need to isolate individual spores, genotype them separately by low-coverage sequencing, and then perform RNA-Seq on each spore separately. This is a substantial advance and opens up the possibility to straightforwardly identify eQTLs over many conditions in a cost-efficient manner. Overall, I found the paper to be well-written and well-motivated, and have no issues with either the methodological/analytical approach (though eQTL analysis is not my expertise), or with the manuscript's conclusions.

Reviewer #2 (Public review):

Summary:

Using the crustacean stomatogastric nervous system (STNS), the authors present an interesting study wherein the contribution of the Ih current to temperature-induced changes in the frequency of a rhythmically active neural circuit is evaluated. Ih is a hyperpolarization-activated cation current that depolarizes neurons. Under normal conditions, increasing the temperature of the STNS increases the frequency of the spontaneously active pyloric rhythm. Notably, under normal conditions, as temperature systematically increases, the concomitant increase in pyloric frequency is smooth (i.e., monotonic). By contrast, blocking Ih with extracellular cesium produces temperature-induced pyloric frequency changes that follow a characteristic sawtooth response (i.e., non-monotonic). That is, in cesium, increasing temperature initially results in a transient drop in pyloric frequency that then stabilizes at a higher frequency. Thus, the authors conclude that Ih establishes a mechanism that ensures smooth changes in neural network frequency during environmental disturbances, a feature that likely bestows advantages to the animal's function.

The study describes several surprising and interesting findings. In general, the study's primary observation of the cesium-induced sawtooth response is remarkable. To my knowledge, this type of response has not yet been described in neurobiological systems, and I suspect that the unexpected response will be of interest to many readers.

At first glance, I had some concerns regarding the use of extracellular cesium to understand network phenomena. Yes, extracellular cesium blocks Ih. But extracellular cesium has also been shown to block astrocytic potassium channels, at least in mammalian systems (i.e., K-IR, PMID: 10601465), and such a blockade can elevate extracellular potassium. I was heartened to see that the authors acknowledge the non-specificity of cesium (lines 320-325) and I agree with the authors' contention that "a first approximation most of the effects seen here can likely be attributed to Cs+ block of Ih". Upon reflecting on the potential confound, I was also reassured to see that extracellular cesium alone does not in fact increase pyloric frequency, an effect that might be expected if cesium indirectly raises [K+]outside. If the authors agree, then I suggest including that point in their discussion.

In summary, the authors present a solid investigation of a surprising biological phenomenon. In general, my comments are fairly minor. Thanks for contributing an interesting study.

Strengths:

A major strength of the study is the identification of an ionic conductance that mediates stable, monotonic changes in oscillatory frequency that accompany changes in the environment (i.e., temperature).

Weaknesses:

A potential experimental concern stems from the use of extracellular cesium to attribute network effects specifically to Ih. Previous work has shown that extracellular cesium also blocks inward-rectifier potassium channels expressed by astrocytes, and that such blockade may also elevate extracellular potassium, an action that generally depolarizes neurons. Notably, the authors address this potential concern in the discussion.

Reviewer #2 (Public review):

Summary:

In this study, Sharma et al. demonstrated that Ly6G+ granulocytes (Gra cells) serve as the primary reservoirs for intracellular Mtb in infected wild-type mice and that excessive infiltration of these cells is associated with severe bacteremia in genetically susceptible IFNγ-/- mice. Notably, neutralizing IL-17 or inhibiting COX2 reversed the excessive infiltration of Ly6G+Gra cells, mitigated the associated pathology, and improved survival in these susceptible mice. Additionally, Ly6G+Gra cells were identified as a major source of IL-17 in both wild-type and IFNγ-/- mice. Inhibition of RORγt or COX2 further reduced the intracellular bacterial burden in Ly6G+Gra cells and improved lung pathology.

Of particular interest, COX2 inhibition in wild-type mice also enhanced the efficacy of the BCG vaccine by targeting the Ly6G+Gra-resident Mtb population.

Strengths:

The experimental results showing improved BCG-mediated protective immunity through targeting IL-17-producing Ly6G+ cells and COX2 are compelling and will likely generate significant interest in the field. Overall, this study presents important findings, suggesting that the IL-17-COX2 axis could be a critical target for designing innovative vaccination strategies for TB.

Weaknesses:

However, I have the following concerns regarding some of the conclusions drawn from the experiments, which require additional experimental evidence to support and strengthen the overall study.

Major Concerns:

(1) Ly6G+ Granulocytes as a Source of IL-17: The authors assert that Ly6G+ granulocytes are the major source of IL-17 in wild-type and IFN-γ KO mice based on colocalization studies of Ly6G and IL-17. In Figure 3D, they report approximately 500 Ly6G+ cells expressing IL-17 in the Mtb-infected WT lung. Are these low numbers sufficient to drive inflammatory pathology? Additionally, have the authors evaluated these numbers in IFN-γ KO mice?

(2) Role of IL-17-Producing Ly6G Granulocytes in Pathology: The authors suggest that IL-17-producing Ly6G granulocytes drive pathology in WT and IFN-γ KO mice. However, the data presented only demonstrate an association between IL-17+ Ly6G cells and disease pathology. To strengthen their conclusion, the authors should deplete neutrophils in these mice to show that IL-17 expression, and consequently the pathology, is reduced.

(3) IL-17 Secretion by Mtb-Infected Neutrophils: Do Mtb-infected neutrophils secrete IL-17 into the supernatants? This would serve as confirmation of neutrophil-derived IL-17. Additionally, are Ly6G+ cells producing IL-17 and serving as pathogenic agents exclusively in vivo? The authors should provide comments on this.

(4) Characterization of IL-17-Producing Ly6G+ Granulocytes: Are the IL-17-producing Ly6G+ granulocytes a mixed population of neutrophils and eosinophils, or are they exclusively neutrophils? Sorting these cells followed by Giemsa or eosin staining could clarify this.

Reviewer #2 (Public review):

Summary:

Homan et al. examined the effect of macrophage- or Kupffer cell-specific C3aR1 KO on MASLD/MASH-related metabolic or liver phenotypes.

Strengths:

Established macrophage- or Kupffer cell-specific C3aR1 KO mice.

Weaknesses:

Lack of in-depth study; flaws in comparisons between KC-specific C3aR1KO and WT in the context of MASLD/MASH, because MASLD/MASH WT mice likely have a low abundance of C3aR1 on KCs.

Homan et al. reported a set of observation data from macrophage or Kupffer cell-specific C3aR1KO mice. Several questions and concerns as follows could challenge the conclusions of this study:

(1) As C3aR1 is robustly repressed in MASLD or MASH liver, GAN feeding likely reduced C3aR1 abundance in the liver of WT mice. Thus, it is not surprising that there were no significant differences in liver phenotypes between WT vs. C3aR1KO mice after prolonged GAN diet feeding. It would give more significance to the study if restoring C3aR1 abundance in KCs in the context of MASLD/MASH.

(2) Would C3aR1KO mice develop liver abnormalities after a short period of GAN diet feeding?

(3) What would be the liver macrophage phenotypes in WT vs C3aR1KO mice after GAN feeding?

(4) In Fig 1D, >25wks GAN feeding had minimal effects on female body weight gain. These GAN-fed female mice also develop NASLD/MASH liver abnormalities?

(5) Would C3aR1KO result in differences in liver phenotypes, including macrophage population/activation, liver inflammation, lipogenesis, in lean mice?

(6) The authors should provide more information regarding the generation of KC-specific C3aR1KO. Which Cre mice were used to breed with C3aR1 flox mice?

Reviewer #2 (Public review):

In this study, Cai and colleagues investigate how one component of the m6A methyltransferase complex, the WTAP protein, responds to IFNb stimulation. They find that viral infection or IFNb stimulation induces the transition of WTAP from aggregates to liquid droplets through dephosphorylation by PPP4. This process affects the m6A modification levels of ISG mRNAs and modulates their stability. In addition, the WTAP droplets interact with the transcription factor STAT1 to recruit the methyltransferase complex to ISG promoters and enhance m6A modification during transcription. The investigation dives into a previously unexplored area of how viral infection or IFNb stimulation affects m6A modification on ISGs. The observation that WTAP undergoes a phase transition is significant in our understanding of the mechanisms underlying m6A's function in immunity. However, there are still key gaps that should be addressed to fully accept the model presented.

Major points:

(1) More detailed analyses on the effects of WTAP sgRNA on the m6A modification of ISGs:<br /> a. A comprehensive summary of the ISGs, including the percentage of ISGs that are m6A-modified.<br /> b. The distribution of m6A modification across the ISGs.<br /> c. A comparison of the m6A modification distribution in ISGs with non-ISGs.

In addition, since the authors propose a novel mechanism where the interaction between phosphorylated STAT1 and WTAP directs the MTC to the promoter regions of ISGs to facilitate co-transcriptional m6A modification, it is critical to analyze whether the m6A modification distribution holds true in the data.

(2) Since a key part of the model includes the cytosol-localized STAT1 protein undergoing phosphorylation to translocate to the nucleus to mediate gene expression, the authors should focus on the interaction between phosphorylated STAT1 and WTAP in Figure 4, rather than the unphosphorylated STAT1. Only phosphorylated STAT1 localizes to the nucleus, so the presence of pSTAT1 in the immunoprecipitate is critical for establishing a functional link between STAT1 activation and its interaction with WTAP.

(3) The authors should include pSTAT1 ChIP-seq and WTAP ChIP-seq on IFNb-treated samples in Figure 5 to allow for a comprehensive and unbiased genomic analysis for comparing the overlaps of peaks from both ChIP-seq datasets. These results should further support their hypothesis that WTAP interacts with pSTAT1 to enhance m6A modifications on ISGs.

Minor points:

(1) Since IFNb is primarily known for modulating biological processes through gene transcription, it would be informative if the authors discussed the mechanism of how IFNb would induce the interaction between WTAP and PPP4.

(2) The authors should include mCherry alone controls in Figure 1D to demonstrate that mCherry does not contribute to the phase separation of WTAP. Does mCherry have or lack a PLD?

(3) The authors should clarify the immunoprecipitation assays in the methods. For example, the labeling in Figure 2A suggests that antibodies against WTAP and pan-p were used for two immunoprecipitations. Is that accurate?

(4) The authors should include overall m6A modification levels quantified of GFPsgRNA and WTAPsgRNA cells, either by mass spectrometry (preferably) or dot blot.

Reviewer #2 (Public review):

Summary:

This manuscript is about using different analytical approaches to allow ancestry adjustments to GWAS analyses amongst admixed populations. This work is a follow-on from the recently published ITHGC multi-population GWAS (https://doi.org/10.7554/eLife.84394), with a focus on the admixed South African populations. Ancestry adjustment models detected a peak of SNPs in the class II HLA DPB1, distinct from the class II HLA DQA1 loci significant in the ITHGC analysis.

Strengths:

Excellent demonstration of GWAS analytical pipelines in highly admixed populations. Further confirmation of the importance of the HLA class II locus in genetic susceptibility to TB.

Weaknesses:

Limited novelty compared to the group's previous existing publications and the body of work linking HLA class II alleles with TB susceptibility in South Africa or other African populations. This work includes only ~100 new cases and controls from what has already been published. High-resolution HLA typing has detected significant signals in both the DQA1 and DPB1 regions identified by the larger ITHGC and in this GWAS analysis respectively (Chihab L et al. HLA. 2023 Feb; 101(2): 124-137).

Despite the availability of strong methods for imputing HLA from GWAS data (Karnes J et Plos One 2017), the authors did not confirm with HLA typing the importance of their SNP peak in the class II region. This would have supported the importance of this ancestry adjustment versus prior ITHGC analysis.

The populations consider active TB and healthy controls (from high-burden presumed exposed communities) and do not provide QFT or other data to identify latent TB infection.

Important methodological points for clarification and for readers to be aware of when reading this paper:

(1) One of the reasons cited for the lack of African ancestry-specific associations or suggestive peaks in the ITHGC study was the small African sample size. The current association test includes a larger African cohort and yields a near-genome-wide significant threshold in the HLA-DPB1 gene originating from the KhoeSan ancestry. The investigation is needed as to whether the increase in power is due to increased African samples and not necessarily the use of the LAAA model as stated on lines 295 and 296?

(2) In line 256, the number of SNPs included in the LAAA analysis was 784,557 autosomal markers; the number of SNPs after quality control of the imputed dataset was 7,510,051 SNPs (line 142). It is not clear how or why ~90% of the SNPs were removed. This needs clarification.

(3) The authors have used the significance threshold estimated by the STEAM p-value < 2.5x10-6 in the LAAA analysis. Grinde et al. (2019 implemented their significance threshold estimation approach tailored to admixture mapping (local ancestry (LA) model), where there is a reduction in testing burden. The authors should justify why this threshold would apply to the LAAA model (a joint genotype and ancestry approach).

(4) Batch effect screening and correction (line 174) is a quality control check. This section is discussed after global and local ancestry inferences in the methods. Was this QC step conducted after the inferencing? If so, the authors should justify how the removed SNPs due to the batch effect did not affect the global and local ancestry inferences or should order the methods section correctly to avoid confusion.

Reviewer #2 (Public review):

Piersma et al. continue to work on deciphering the role and function of Ly49 NK cell receptors. This manuscript shows that a single inhibitory Ly49 receptor is sufficient to license NK cells and eliminate MHC-I-deficient target cells in mice. In short, they refined the mouse model ∆Ly49-1 (Parikh et al., 2020) into the Ly49KO model in which all Ly49 genes are disrupted. Using this model, they confirmed that NK cells from Ly49KO mice cannot be licensed, produce lower levels of IFN-gamma, and cannot reject MHC-I-deficient cells. To study the effect of a single Ly49 receptor in the function of NK cells, the authors backcrossed Ly49KO mice to H-2Dd transgenic KODO (D8-KODO) Ly49A knock-in mice in which a single inhibitory Ly49A receptor that recognizes H-2Dd ligands is expressed. By doing so, they demonstrate that a single inhibitory Ly49 receptor expressed by all NK cells is sufficient for licensing and missing-self killing.

While the results of the study are largely consistent with the conclusions, it is important to address some discrepancies. For instance, in the title of Figure 1, the authors state that NK cells in Ly49KO mice compared to WT mice have a less mature phenotype , which is not consistent with the corresponding text in the Results section (lines 170-171) that states there is no difference in maturation. These differences are not evident in Figure 1, panel D. It is crucial to acknowledge these inconsistencies to ensure a comprehensive understanding of the research findings.

In the legend of Figure 2. the text related to panel C indicates the use of dyes to label the splenocytes, and CFSE, CTV, and CTFR were mentioned. However, only CTV and CTFR are shown on the plots and mentioned in the corresponding text in the Results section. Similarly, in the legend of Figure 4, which is related to panel C, the authors write that splenocytes were differentially labeled with CFSE and CTV as indicated; however, in Figure 4, C and the Results section text, there is no mention of CFSE.

The authors should clarify why they assume that KLRG1 expression is influenced by the expression of inhibitory Ly49 receptors and not by manipulations on chromosome 6, where the genes for both KLRG1 and Ly49 receptors are located. However, a better explanation for the possible influence of other inhibitory NK cell receptors still needs to be included. In the study by Zhang et al. (doi: 10.1038/s41467-019-13032-5 the authors showed the synergized regulation of NK cell education by the NKG2A receptor and the specific Ly49 family members. Although in this study, Piersma and colleagues show the control of MHC-I deficient cells by Ly49A+ NKG2A-NK cells in Figure 4., this receptor is not mentioned in the Results or in the Discussion section, so its role in this story needs to be clarified. Therefore, the reader would benefit from more information regarding NKG2A receptor and NKG2A+/- populations in their results.

Reviewer #2 (Public review):

Summary:

The authors utilized a "ligand-first" targeted covalent inhibition approach to design potent inhibitors of carbonic anhydrase IX (CAIX) based on a known non-covalent primary sulfonamide scaffold. The novelty of their approach lies in their use of a protected pre(pro?)-vinylsulfone as a precursor to the common vinylsulfone covalent warhead to target a nonstandard His residue in the active site of CAIX. In addition to a biochemical assessment of their inhibitors, they showed that their compounds compete with a known probe on the surface of HeLa cells.

Strengths:

The authors use a protected warhead for what would typically be considered an "especially hot" or even "undevelopable" vinylsulfone electrophile. This would be the first report of doing so making it a novel targeted covalent inhibition approach specifically with vinylsulfones.

The authors used a number of orthogonal biochemical and biophysical methods including intact MS, 2D NMR, x-ray crystallography, and an enzymatic stopped-flow setup to confirm the covalency of their compounds and even demonstrate that this novel pre-vinylsulfone is activated in the presence of CAIX. In addition, they included a number of compelling analogs of their inhibitors as negative controls that address hypotheses specific to the mechanism of activation and inhibition.

The authors employed an assay that allows them to assess target engagement of their compounds with the target on the surface of cells and a fluorescent probe which is generally a critical tool to be used in tandem with phenotypic cellular assays.

Weaknesses:

While the authors show that the pre-vinyl moiety is shown biochemically to be transformed into the vinylsulfone, they do not show what the fate of this -SO2CH2CH2OCOR group is in a cellular context. Does the pre-vinylsulfone in fact need to be in the active site of CAIX on the surface of the cell to be activated or is the vinylsulfone revealed prior to target engagement?

I appreciate the authors acknowledging the limitations of using an assay such as thermal shift to derive an apparent binding affinity, however, it is not entirely convincing and leaves a gap in our understanding of what is happening biochemically with these inhibitors, especially given the two-step inhibitory mechanism. It is very difficult to properly understand the activity of these inhibitors without a more comprehensive evaluation of kinact and Ki parameters. This can then bring into question how selective these compounds actually are for CAIX over other carbonic anhydrases.

The authors did not provide any cellular data beyond target engagement with a previously characterized competitive fluorescent probe. It would be critical to know the cytotoxicity profile of these compounds or even how they affect the biology of interest regarding CAIX activity if the intention is to use these compounds in the future as chemical probes to assess CAIX activity in the context of tumor metastasis.

Reviewer #2 (Public review):

In this study, a methodology called QSPACE is developed and presented. It integrates structural information for a specific organism, here E. coli. The process entails the gathering of individual structures, including oligomeric information/stoichiometry, the incorporation of data on transmembrane regions, and the utilization of the resulting dataset for the analysis of mutation effects and the allocation of proteomes.

This work aims high, setting an ambitious goal of modeling the quaternary structure of a proteome. The method could be applied to other organisms in the future and has value in that respect. At the same time, the work tries to cover (too?) much ground and some of the results/analyses don't measure up. There are indeed a number of shortcomings and/or inconsistencies in the results presented. The comments below will help improve the work and its usefulness.

(1) It is described that "QSPACE then finds the 3D coordinate file (i.e. "structure") that best reflects the user-defined (input #2) multi-subunit protein assembly". What is meant by "best reflects"? What if two different structures with the same stoichiometry are available? Which one is picked?

(2) There appears to be a significant under-estimation of oligomer formation: it is reported that "31% (1,334/4,309) of E. coli genes participate in 1,047 oligomeric complexes, 667 genes are annotated as monomers, and 2,308 genes are not included". However, it is generally observed that ~50% of E coli genes form homo-oligomers (see PMID 10940245 or more recently 38325366), and adding hetero-oligomers on top of that should increase the fraction of oligomers further. In that respect, the estimate forming the basis of this work (31% of genes participating in oligomeric complexes) seems incorrect. It is unclear why the authors did not identify more proteins as adopting a quaternary structure. It is generally hard to grasp details of the dataset, for example, the simple statistic of how many genes participate in homo- versus hetero- oligomer. Such information is partially presented in panels 2c & 2d, but it is very small and hard to see (I would suggest removing the structures of the ABC transporters to make space to present this with more detail).

(3) There are a number of misleading statements/overstatements that I encourage the authors to revise. For example (not exhaustive):<br /> "to our knowledge this result is the most advanced genome-scale structural representation of the E. coli proteome and de facto represents a major advancement in genome annotation."<br /> "angstrom-level subcellular compartmentalization" - Can we really talk about sub-atomic precision when even side chains can move by several angstroms?<br /> "we provide a global accounting of all functionally important regions" - "all" is not justified<br /> "Incorporated into genome-scale models that compute protein expression" - what does that mean? There are gene expression & protein abundance datasets, why is the "compute" necessary?<br /> "Likewise, sequence-based prediction software (e.g., DeepTMHMM49) and structure-based prediction software (e.g., OPM50) are agnostic to membrane orientation and can also generate erroneous results" - what does "erroenous results" mean in this context? Those tools are not supposed to predict orientation.

(4) What was the benchmark used to estimate the accuracy of orientation assignments?

(5) It is not clear why structural information is required to calculate the volume taken up by different proteins across the proteome. For each protein, the expression level (copy number) is expected to have a significant effect, but I'm unsure of why oligomerization is considered key here. It will modulate the volume exclusion associated with interface contact areas, but isn't this negligible compared to other factors, in particular expression?

(6) Models aiming at predicting deleterious effects of mutations typically use sequence conservation, but I do not see such information used in Figure 4. Assessing the added value of structural information should include such evolutionary information (residue-level sequence conservation) in the baseline.

(7) The "proteome allocation" analysis is presented as an important result, but I did not find details of equations used to conduct this analysis. I assume that "proteome allocation" is based solely on expression, and that "cell volume" uses structural information on top of it. There is a significant difference between "proteome allocation" and "cell volume" as reflected in the proteomaps shown in panels 4e & 4f, but there is no explanation for it. Are the proteins' identities the same in these two panels? Were only proteins counted or was RNA considered as well? Clarifications are needed for RNA, for example, how were volumes calculated in structures containing RNAs? Datasets used to derive these maps should also be provided to enable reproducing them.

(8) I did not see that the structures generated are available - they should be deposited on a permanent repository with a DOI.

Reviewer #2 (Public review):

Summary:

The authors aimed to elucidate the role of Ctla-4 in maintaining intestinal immune homeostasis by using a novel Ctla-4-deficient zebrafish model. This study addresses the challenge of linking CTLA-4 to inflammatory bowel disease (IBD) due to the early lethality of CTLA-4 knockout mice. Four lines of evidence were shown to show that Ctla-4-deficient zebrafish exhibited hallmarks of IBD in mammals:<br /> (1) impaired epithelial integrity and infiltration of inflammatory cells;<br /> (2) enrichment of inflammation-related pathways and the imbalance between pro- and anti-inflammatory cytokines;<br /> (3) abnormal composition of immune cell populations; and<br /> (4) reduced diversity and altered microbiota composition. By employing various molecular and cellular analyses, the authors established ctla-4-deficient zebrafish as a convincing model of human IBD.

Strengths:

The characterization of the mutant phenotype is very thorough, from anatomical to histological and molecular levels. The finding effectively established ctla-4 mutants as a novel zebrafish model for investigating human IBD. Evidence from the histopathological and transcriptome analysis was very strong and supported a severe interruption of immune system homeostasis in the zebrafish intestine. Additional characterization using sCtla-4-Ig further probed the molecular mechanism of the inflammatory response and provided a potential treatment plan for targeting Ctla-4 in IBD models.

Weaknesses:

Since CTLA-4 is one of the most well-established immune checkpoint molecules, it is not clear whether the ctla-4 mutant zebrafish exhibits inflammatory phenotypes in other tissues than the intestine. Although the evidence for intestinal phenotypes is clear and similar to human IBD, it can be ambiguous whether the mutant is a specific model for IBD, or abnormal immune response in general.

To probe the molecular mechanism of Ctla-4, the authors used a spectrum of antibodies that target Ctla-4 or its receptors. The phenotype assayed was lymphocyte proliferation, while it was the composition rather than the number of in immune cell number that was observed to be different in the scRNASeq assay. Although sCtla-4 has an effect of alleviating the IBD-like phenotypes, I found this explanation a bit oversimplified.

Reviewer #3 (Public review):

Summary:

In this manuscript, the authors investigate the optical properties of brochosomes produced by leafhoppers. They hypothesize that brochosomes reduce light reflection on the leafhopper's body surface, aiding in predator avoidance. Their hypothesis is supported by experiments involving jumping spiders. Additionally, the authors employ a variety of techniques including micro-UV-Vis spectroscopy, electron microscopy, transcriptome and proteome analysis, and bioassays. This study is highly interesting, and the experimental data is well-organized and logically presented.

Strengths:

The use of brochosomes as a camouflage coating has been hypothesized since 1936 (R.B. Swain, Entomol. News 47, 264-266, 1936) with evidence demonstrated by similar synthetic brochosome systems in a number of recent studies (S. Yang, et al. Nat. Commun. 8:1285, 2017; L. Wang, et al., PNAS. 121: e2312700121, 2024). However, direct biological evidence or relevant field studies have been lacking to directly support the hypothesis that brochosomes are used for camouflage. This work provides the first biological evidence demonstrating that natural brochosomes can be used as a camouflage coating to reduce the leafhoppers' observability of their predators. The design of the experiments is novel.

Weaknesses:

(1) The observation that brochosome coatings become sparse after 25 days in both male and female leafhoppers, resulting in increased predation by jumping spiders, is intriguing. However, since leafhoppers consistently secrete and groom brochosomes, it would be beneficial to explore why brochosomes become significantly less dense after 25 days.

(2) The authors demonstrate that brochosome coatings reduce UV (specular) reflection compared to surfaces without brochosomes, which can be attributed to the rough geometry of brochosomes as discussed in the literature. However, it would be valuable to investigate whether the proteins forming the brochosomes are also UV absorbing.

(3) The experiments with jumping spiders show that brochosomes help leafhoppers avoid predators to some extent. It would be beneficial for the authors to elaborate on the exact mechanism behind this camouflage effect. Specifically, why does reduced UV reflection aid in predator avoidance? If predators are sensitive to UV light, how does the reduced UV reflectance specifically contribute to evasion?

(4) An important reference regarding the moth-eye effect is missing. Please consider including the following paper: Clapham, P. B., and M. C. Hutley. "Reduction of lens reflection by the 'Moth Eye' principle." Nature 244: 281-282 (1973).

(5) The introduction should be revised to accurately reflect the related contributions in literature. Specifically, the novelty of this work lies in the demonstration of the camouflage effect of brochosomes using jumping spiders, which is verified for the first time in leafhoppers. However, the proposed use of brochosome powder for camouflage was first described by R.B. Swain (R.B. Swain, Notes on the oviposition and life history of the leafhopper Oncometopta undata Fabr. (Homoptera: Cicadellidae), Entomol. News. 47: 264-266 (1936)). Recently, the antireflective and potential camouflage functions of brochosomes were further studied by Yang et al. based on synthetic brochosomes and simulated vision techniques (S. Yang, et al. "Ultra-antireflective synthetic brochosomes." Nature Communications 8: 1285 (2017)). Later, Lei et al. demonstrated the antireflective properties of natural brochosomes in 2020 (C.-W. Lei, et al., "Leafhopper wing-inspired broadband omnidirectional antireflective embroidered ball-like structure arrays using a nonlithography-based methodology." Langmuir 36: 5296-5302 (2020)). Very recently, Wang et al. successfully fabricated synthetic brochosomes with precise geometry akin to those natural ones, and further elucidated the antireflective mechanisms based on the brochosome geometry and their role in reducing the observability of leafhoppers to their predators (L. Wang et al. "Geometric design of antireflective leafhopper brochosomes." Proceedings of the National Academy of Sciences 121: e2312700121 (2024))

Reviewer #2 (Public review):

Summary:

The authors report that Arabidopsis short HSFs S-HsfA2, S-HsfA4c, and S-HsfB1 confer extreme heat. They have truncated DNA binding domains that bind to a new heat-regulated element. Considering Short HSFA2, the authors have highlighted the molecular mechanism by which S-HSFs prevent HSR hyperactivation via negative regulation of HSP17.6B. The S-HsfA2 protein binds to the DNA binding domain of HsfA2, thus preventing its binding to HSEs, eventually attenuating HsfA2-activated HSP17.6B promoter activity. This report adds insights to our understanding of heat tolerance and plant growth.

Strengths:

(1) The manuscript represents ample experiments to support the claim.<br /> (2) The manuscript covers a robust number of experiments and provides specific figures and graphs in support of their claim.<br /> (3) The authors have chosen a topic to focus on stress tolerance in a changing environment.

Weaknesses:

(1) One s-HsfA2 represents all the other s-Hsfs; S-HsfA4c, and S-HsfB1. s-Hsfs can be functionally different. Regulation may be positive or negative. Maybe the other s-hsfs may positively regulate for height and be suppressed by the activity of other s-hsfs.

(2) Previous reports on gene regulations by hsfs can highlight the mechanism.

(3) The Materials and Methods section could be rearranged so that it is based on the correct flow of the procedure performed by the authors.

(4) Graphical representation could explain the days after sowing data, to provide information regarding plant growth.

(5) Clear images concerning GFP and RFP data could be used.

Reviewer #2 (Public review):

Summary:

In this study, authors have hypothesized that mitochondrial injury in HIE is caused by OXPHOS-uncoupling, which is the cause of secondary energy failure in HI. In addition, therapeutic hypothermia rescues secondary energy failure. The methodologies used are state-of-the art and include PAM technique in live animal , bioenergetic studies in the isolated mitochondria, and others.

Strengths:

The study is comprehensive and impressive. The article is well written and statistical analyses are appropriate.

Weaknesses:

(1) The manuscript does not discuss the limitation of this animal model study in view of the clinical scenario of neonatal hypoxia-ischemia.

(2) I see many studies on Pubmed on bioenergetics and HI. Hence, it is unclear what is novel and what is known.

(3) What are the limitations of ex-vivo mitochondrial studies?

(4) PAM technique limits the resolution of the image beyond 500-750 micron depth. Assessing basal ganglia may not be possible with this approach.

(5) Hypothermia in present study reduces the brain temperature from 37 to 29-32 degree centigrade. In clinical set up, head temp is reduced to 33-34.5 in neonatal hypoxia ischemia. Hence a drop in temperature to 29 degrees is much lower relative to the clinical practice. How the present study with greater drop in head temperature can be interpreted for understanding the pathophysiology of therapeutic hypothermia in neonatal HIE. Moreover, in HIE model using higher temperature of 37 and dropping to 29 seems to be much different than the clinical scenario. Please discuss.

(6) NMR was assessed ex-vivo. How does it relate to in vivo assessment. Infants admitted in Neonatal intensive Care Unit, frequently get MRI with spectroscopy. How do the MRS findings in human newborns with HIE correlate with the ex-vivo evaluation of metabolites.

Reviewer #2 (Public review):

Summary:

The authors utilize a new technique to measure mitochondrial respiration from frozen tissue extracts, which goes around the historical problem of purifying mitochondria prior to analysis, a process that requires a fair amount of time and cannot be easily scaled up.

Strengths:

A comprehensive analysis of mitochondrial respiration across tissues, sexes, and two different ages provides foundational knowledge needed in the field.

Weaknesses:

While many of the findings are mostly descriptive, this paper provides a large amount of data for the community and can be used as a reference for further studies. As the authors suggest, this is a new atlas of mitochondrial function in mouse. The inclusion of a middle aged time point and a slightly older young point (3-6 months) would be beneficial to the study.

Reviewer #2 (Public Review):

Summary:

The manuscript by Bomba-Warczak et al. applied multi-isotope imaging mass spectrometry (MIMS) analysis to identify the long-lived proteins in mouse ovaries during reproductive aging, and found some proteins related to cytoskeletal and mitochondrial dynamics persisting for 10 months.

Strengths:

The manuscript provides a useful dataset about protein turnover during ovarian aging in mice.

Weaknesses:

The study is pretty descriptive and short of further new findings based on the dataset. In addition, some results such as the numbers of follicles and ovulated oocytes in aged mice are not consistent with the published literature.

Comments on revised version:

The authors did not fully address my previous concerns, especially regarding the verification of the identified proteins, and follow-up functional experiments. In addition, it is still unacceptable for me that the number of ovulated oocytes in mice at 6 months of age is only one third of young mice (10 vs 30; Fig. S1E). The most of published literature show that mice at 12 months of age still have ~10 ovulated oocytes. Moreover, based on the follicle counting method used in the present study (Fig. S1D), there are no antral follicles observed in mice at 6 months and 10 months of age, which is not reasonable.

Reviewer #2 (Public review):

Summary:

This study takes advantage of multiple methodological advances to perform layer-specific staining of cortical neurons and tracking of their axons to identify the pattern of their projections. This publication offers a mesoscale view of the projection patterns of neurons in the whisker primary and secondary somatosensory cortex. The authors report that, consistent with the literature, the pattern of projection is highly different across cortical layers and subtype, with targets being located around the whole brain. This was tested across 6 different mouse types that expressed a marker in layer 2/3, layer 4, layers 5 (3 sub-types) and layer 6.

Looking more closely to the projections from primary somatosensory cortex into the primary motor cortex, they found that there was a significant spatial clustering of projections from topographically separated neurons across the primary somatosensory cortex. This was true for neurons with cell bodies located across all tested layers/types.

Strengths:

This study successfully looks at the relevant scale to study projection patterns, which is the whole brain. This is acheived thanks to an ambitious combination of mouse lines, immuno-histochemistry, imaging and image processing, which results in a standardized histological pipeline that processes the whole-brain projection patterns of layer-selected neurons of the primary and secondary somatosensory cortex.<br /> This standardization means that comparisons between cell-types projection patterns are possible and that both the large scale structure of the pattern and the minute details of the intra-areas pattern are available.<br /> This reference dataset and the corresponding analysis code are made available to the research community.

Weaknesses:

One major question raised by this dataset is the risk of missing axons during the post-processing step. Following the previous review round, my concerns have been addressed regarding this point.

Reviewer #2 (Public review):

This study assess the subcellular distribution of a major G protein subunit (Gβ1) when expressed at an endogenous level in a well-studied model cell system (293 cells). The approach elegantly extends a gene editing strategy described by Leonetti's group and combines it with a FRET-based proximity assay to detect the presence of endogenously tagged Gβ1 on membrane compartments of 293 cells. The authors achieve their goal, and the data are convincing and interesting. The authors do a nice job of integrating their results with previous work in the field. The methods are now sufficiently well-described to enable other investigators to apply or adapt them in future studies.

Reviewer #2 (Public review):

Summary:

In the manuscript by Rincon-Torroella et al, the authors evaluated the therapeutic potential of ME3BP-7, a microencapsulated formulation of 3BP which specifically target MCT-1 high tumor cells, in pancreatic cancer models. The authors showed that, compared to 3BP, ME3BP-7 exhibited much enhanced stability in serum. In addition, the authors confirmed the specificity of ME3BP-7 toward MCT-1 high tumor cells and demonstrated the in vivo anti-tumor effect of ME3BP-7 in orthotopic xenograft of human PDAC cell line and PDAC PDX model.

Strengths:

(1) The study convincingly demonstrated the superior stability of ME3BP-7 in serum.<br /> (2) the specificity of ME3BP-7 and 3BP toward MCT-1 high PDAC cells was clearly demonstrated with CRISPR-mediated knockout experiments.<br /> (3) The advantage of ME3BP-7 over 3BP under in vivo situation is highlighted in the revised manuscript.

Reviewer #2 (Public Review):

Summary:

Utilizing transgene expression of Wnd in sensory neurons in Drosophila, the authors found that Wnd is enriched in axonal terminals. This enrichment could be blocked by preventing palmitoylation or inhibiting Rab1 or Rab11 activity. Indeed, subsequent experiments showed that inhibiting Wnd can prevent toxicity by Rab11 loss of function.

Strengths:

This paper evaluates in detail Wnd location in sensory neurons, and identifies a novel genetic interaction between Rab11 and Wnd that affects Wnd cellular distribution.

Weaknesses:

The authors report low endogenous expression of wnd, and expressing mutant hiw or overexpressing wnd is necessary to see axonal terminal enrichment. It is unclear if this overexpression model (which is known to promote synaptic overgrowth) would be relevant to normal physiology.

Palmitoylation of the Wnd orthologue DLK in sensory neurons has previously been identified as important for DLK trafficking in a cell culture model.

Reviewer #2 (Public review):

Summary:

Fargeot et al. investigated the relative importance of genetic and species diversity on ecosystem function and examined whether this relationship varies within or between trophic-level responses. To do so, they conducted a well-designed field survey measuring species diversity at 3 trophic levels (primary producers [trees], primary consumers [macroinvertebrate shredders], and secondary consumers [fishes]), genetic diversity in a dominant species within each of these 3 trophic levels and 7 ecosystem functions across 52 riverine sites in southern France. They show that the effect of genetic and species diversity on ecosystem functions are similar in magnitude, but when examining within-trophic level responses, operate in different directions: genetic diversity having a positive effect and species diversity a negative one. This data adds to growing evidence from manipulated experiments that both species and genetic diversity can impact ecosystem function and builds upon this by showing these effects can be observed in nature.

Strengths:

The study design has resulted in a robust dataset to ask questions about the relative importance of genetic and species diversity of ecosystem function across and within trophic levels.

Overall, their data supports their conclusions - at least within the system that they are studying - but as mentioned below, it is unclear from this study how general these conclusions would be.

Weaknesses:

(1) While a robust dataset, the authors only show the data output from the SEM (i.e., effect size for each individual diversity type per trophic level (6) on each ecosystem function (7)), instead of showing much of the individual data. Although the summary SEM results are interesting and informative, I find that a weakness of this approach is that it is unclear how environmental factors (which were included but not discussed in the results) nor levels of diversity were correlated across sites. As species and genetic diversity are often correlated but also can have reciprocal feedbacks on each other (e.g., Vellend 2005), there may be constraints that underpin why the authors observed positive effects of one type of diversity (genetic) when negative effects of the other (species). It may have also been informative to run SEM with links between levels of diversity. By focusing only on the summary of SEM data, the authors may be reducing the strength of their field dataset and ability to draw inferences from multiple questions and understand specific study-system responses.

(2) My understanding of SEM is it gives outputs of the strength/significance of each pathway/relationship and if so, it isn't clear why this wasn't used and instead, confidence intervals of Z scores to determine which individual BEFs were significant. In addition, an inclusion of the 7 SEM pathway outputs would have been useful to include in an appendix.

(3) I don't fully agree with the authors calling this a meta-analysis as it is this a single study of multiple sites within a single region and a specific time point, and not a collection of multiple studies or ecosystems conducted by multiple authors. Moreso, the authors are using meta-analysis summary metrics to evaluate their data. The authors tend to focus on these patterns as general trends, but as the data is all from this riverine system this study could have benefited from focusing on what was going on in this system to underpin these patterns. I'd argue more data is needed to know whether across sites and ecosystems, species diversity and genetic diversity have opposite effects on ecosystem function within trophic levels.

Reviewer #2 (Public Review):

The focus of this manuscript was to investigate whether Kv1.8 channels, which have previously been suggested to be expressed in type I hair cells of the mammalian vestibular system, are responsible for the potassium conductance gK,L. This is an important study because gK,L is known to be crucial for the function of type I hair cells, but the channel identity has been a matter of debate for the past 20 years. The authors have addressed this research topic by primarily investigating the electrophysiological properties of the vestibular hair cells from Kv1.8 knockout mice. Interestingly, gK,L was completely abolished in Kv1.8-deficient mice, in agreement with the hypothesis put forward by the authors based on the literature. The surprising observation was that in the absence of Kv1.8 potassium channels, the outward potassium current in type II hair cells was also largely reduced. Type II hair cells express the largely inactivating potassium conductance g,K,A, but not gK,L. The authors concluded that heteromultimerization of non-inactivating Kv1.8 and the inactivating Kv1.4 subunits could be responsible for the inactivating gK,A. Overall, the manuscript is very well written and most of the conclusions are supported by the experimental work. The figures are well described, and the statistical analysis is robust.

Reviewer #2 (Public review):

Summary:

In this study, Vicaro et al. aimed to quantify and characterize mosaic mutations in human sporadic Alzheimer's disease (AD) brain samples. They focused on three broad classes of brain cells, neurons that express the marker NeuN, microglia that express the marker PU.1, and double-negative cells that presumably comprise all other brain cell types, including astrocytes, oligodendrocytes, oligodendrocyte progenitor cells, and endothelial cells. The authors find an enrichment of potentially pathogenic somatic mutations in AD microglia compared to controls, with MAPK pathway genes being particularly enriched for somatic mutations in those cells. The authors report a striking enrichment for mutations in the gene CBL and use in vitro functional assays to show that these mutations indeed induce MAPK pathway activation.

The current state of the AD and somatic mutation fields puts this work into context. First, AD is a devastating disease whose prevalence is only increasing as the population of the U.S. is aging, necessitating the investigation of novel features of AD to identify new therapeutic opportunities. Second, microglia have recently come into focus as important players in AD pathogenesis. Many AD risk genes are selectively expressed in microglia, and microglia from AD brain samples show a distinct transcriptional profile indicating an inflammatory phenotype. The authors' previous work shows that a genetic mouse model of mosaic BRAF activation in macrophages (including microglia) displays a neurodegenerative phenotype similar to AD (Mass et al., 2017, doi:10.1038/nature23672). Third, new technological developments have allowed for identifying mosaic mutations present in only a small fraction of or even single cells. Together, these data form a rationale for studying mosaic mutations in microglia in AD. In light of the authors' findings regarding MAPK pathway gene somatic mutations, it is also important to note that MAPK has previously been implicated in AD neuroinflammation in the literature.

Strengths:

The study demonstrated several strengths. Firstly, the authors used two methods to identify mosaic mutations: 1) deep (~1,100x) DNA sequencing of a targeted panel of >700 genes they hypothesized might, if mutated somatically, play a role in AD, and 2) deep (400x) whole-exome sequencing (WES) to identify clonal mosaics outside of those genes. A second strength is the agreement between these experiments, where WES found many variants identified in the panel experiment, and both experiments revealed somatic mutations in MAPK pathway genes. Third, the authors demonstrated in several in vitro systems that many mutations they identified in MAPK genes activate MAPK signaling. Finally, the authors showed that in some human brain samples, single-cell gene expression analysis revealed that cells bearing a mosaic MAPK pathway mutation displayed dysregulated inflammatory signaling and dysregulation in other pathways. This single-cell analysis was in agreement with their in vitro analyses.

Weaknesses:

The study also showed some weaknesses. The sample size (45 AD donors and 44 controls) is small, reflected in the relatively modest effect sizes and p-values observed. This weakness is partially ameliorated by the authors' extensive molecular and functional validation of mutation candidates. Secondly, as the authors point out, this study cannot conclude whether microglial mosaic mutations cause AD or are an effect of AD. Future studies may shed more light on this important question.

Conclusions and Impact:

Considering the study's aims, strengths, and weaknesses, I conclude that the authors achieved their goal of characterizing the role of mosaic mutations in human AD. Their data strongly suggest that mosaic MAPK mutations in microglia are associated with AD. The impacts of this study remain to be seen, but they could include attempts to target CBL or other mutated genes in the treatment of AD. This work also suggests a similar approach to identifying potentially causative somatic mutations in other neurodegenerative diseases.

Reviewer #2 (Public review):

This manuscript examines how humans walk over uneven terrain and use vision to decide where to step. There is a huge lack of evidence about this because the vast majority of locomotion studies have focused on steady, well-controlled conditions, and not on decisions made in the real world. The author team has already made great advances in this topic by pioneering gaze recordings during locomotion, but there has been no practical way to map the gaze targets, specifically the 3D terrain features in naturalistic environments. The team has now developed a way to integrate such measurements along with gaze and step tracking. This allows quantitative evaluation of the proposed trade-offs between stepping vertically onto vs. stepping around obstacles, along with how far people look to decide where to step. The team also introduces several new analysis techniques to accompany these measurements. They use machine learning techniques to examine whether retinocentric depth helps predict footholds and develop simulations to assess possible alternative footholds and walking paths. The technical achievement is impressive.

This study addresses several real-world questions not normally examined in the laboratory. First, do humans elect to walk around steeper footholds rather than over them? Second, is there a quantifiable benefit to walking around, such as allowing for a flatter path? Third, does visual depth of terrain contribute to selection of footholds? Fourth, are there scale effects, where for example a tall adult can easily walk over an obstacle that a toddler must walk around. One might superficially answer yes to all of these questions, but it is highly nontrival to answer them quantitatively. As for the conclusions, my feelings are mixed. I find strengths in answers to two of the questions, and weaknesses in the other two.

Strengths:

I consider the evidence strongest for the first of the main questions. The results show subjects walking with more laterally deviating paths, measured by a quantity called "tortuosity," when the direct straight-ahead paths appear to have steeper ups and downs (Fig. 9). The measure of straight-ahead steepness is fairly complicated (discussed below), but is shown to be well correlated with tortuosity, effectively predicting when subjects will not walk straight ahead.

There is also good evidence for the third question, showing that retinocentric depth is predictive of chosen footholds. Retinocentric depth was computed by a series of steps, starting with scene capture to determine a 3D terrain mesh, projecting that mesh into the eye's perspective, and then discarding all but the depth information. This highly involved process is only the beginning, because the depth was then used to train a neural network classifier with chosen footholds. That network was found to predict footholds better than chance, using a test set independent from the training set, each using half the recorded data. The results are strong and are best interpreted along with a previous study (Bonnen et al. 2021) showing that subjects gaze nearer ahead on rougher terrain, and slightly more so when binocular vision was disrupted. Depth information seems important for foothold selection.

As an aside, humans presumably also select footholds and estimate depth from a number of monocular visual cues, such as shading, shadows, color, and self-motion information. Interestingly, the terrain mesh and depth data here were computed from monocular images, suggesting that monocular vision can in principle be predictive of both depth and footholds. Binocular human vision presumably improves on monocular depth estimation, and so it would be interesting to see whether binocular scene cameras would predict footholds better. In an earlier review, I had suggested other avenues for exploration, but these are not weaknesses so much as opportunities not yet taken. I believe much could be learned from deeper analysis of the neural network, and future experiments using variations of this technique.

There is much to be appreciated about this study. I was impressed by the overarching outlook and ambitiousness of the team. They seek to understand human decision-making in real-world locomotion tasks, a topic of obvious relevance to the human condition but not often examined in research. The field has been biased toward well-controlled, laboratory studies, which have undeniable scientific advantages but are also quite different from the real world. The present study discards all of the usual advantages of the laboratory, yet still finds a way to explore real-world behaviors in a quantitative manner. It is an exciting and forward-thinking approach, used to tackle an ecologically relevant question.

I also appreciate the numerous technical challenges of this study. The state of the art in real-world locomotion studies has largely been limited to kinematic motion capture. This team managed to collect and analyze an unprecedented, one-of-a-kind dataset. They applied a number of non-trivial methods to assess retinocentric depth, simulate would-be walking paths and steepness, and predict footholds from neural network. Any of these could and probably will merit individual papers, and to assemble them all at once is quite beyond other studies I am aware of. I hope this study will spur more inquiries of this type, leveraging mobile electronics and modern machine learning techniques to answer questions that were previously only addressable qualitatively.

Weaknesses:<br /> Although I am highly enthusiastic about this study, I was not entirely convinced by the evidence for the second and fourth questions. Some of this is because I was confused by aspects of the analysis, limiting my understanding of the evidence. But I also question some of the basic conclusions, whether the authors indeed proved that (from Abstract, emphasis mine) "[walkers] change direction TO AVOID taking steeper steps that involve large height changes, instead of [sic] choosing more circuitous, RELATIVELY FLAT paths." (I interpret the "of" as a typo that should have been omitted.) I think it is more objective to say, "walkers changed direction more when straight-ahead paths seemed to have steeper height changes."

I say "seemed" because it is unknown whether humans would have experienced greater height changes if they walked straight ahead (the second main question). The comparison shown is between human tortuous paths taken and simulated straight-ahead paths never experienced by human. Ignoring questions about the simulations for now (discussed below), it is not an apples-to-apples comparison, say between the tortuous paths humans preferred and straight-ahead paths they didn't. The authors determined a measure of steepness, "straight path slope" (Fig. 9), that predicts when humans circuitously, but that is the same as the steepness that humans would actually experience if they had walked straight ahead. That could have been measured with an appropriate control condition, for example asking subjects to walk as straight ahead as they can manage. That also would have eliminated the need for simulations, because the slope of each step actually taken could simply have been measured and compared between conditions. Instead, two different kinds of simulations are compared, where steeper paths are fully simulated, and the circuitous paths are partially simulated but partially based on data. It seems that every fifth circuitous step coincides with a human foothold, but the intervening ones are somewhat random. I don't find this especially strong evidence that the chosen paths were indeed relatively flatter. I would prefer to be convinced by hard data than by unequal simulations.

I also have trouble accepting "TO AVOID" because it implies a degree of intent not evident in the data. I suppose conscious intent could be assessed subjectively by questionnaire, but I don't know how unconscious intent could be tested objectively. I believe my suggested interpretation above is better supported by evidence.

My limited acceptance is due in part to confusion about the simulations. I was especially confused about the connection between feasible steps drawn from the distribution in Figure 7, and the histograms of Figure 8. The feasible steps have clear peaks near zero slope, unity step length, and zero step direction (let's call them Flat). If 5-step simulations of Figure 8 draw from that distribution, why is there zero probability for the 0-3 deg bin (which is within {plus minus}3 deg due to absolute values)? It seems to me that Flat steps were eminently available, so why were they completely avoided? It seems that the simulations were probabilistic (and not just figurative) random walks, which implies they should have had about the same mean as Figure 7 but a wider variance, and then passed through absolute value. They look like something else that I cannot understand. This is important because the RELATIVELY FLAT conclusion is based on the chosen walks apparently being skewed flatter than random simulated walks. I have trouble accepting those distributions because Flat steps were unaccountably never taken by either simulation or human. (This issue is less concerning for Figure 9, because one can accept that some simulation measure is predictive of tortuosity even if the measure is hard to understand.)

I was also confused why Figure 7 distances and directions are nearly normally distributed and not more uniform. The methods only mention constraints to eliminate steps, which to me suggests a truncated uniform distribution. It is not clear to me why the terrain should have a high peak at unity step length, which implies that the only feasible footholds were almost exclusively straight ahead and one step length away. It is possible that the "feasible" footholds are themselves drawn from a "likely" normal distribution, perhaps based on level walking data. It could be argued that simulated steps should be performed by drawing from typical step distributions for level ground, eliminating non-viable footholds, and then repeating that across multiple steps. That would explain the normality, but it is not stated in the Methods, and even if they were "feasible and likely" it would not explain the distributions of Figure 8.

I had some misgivings about the fourth question, where Figure 10 suggests that shorter subjects had greater correlation between straight-path slope and tortuosity than taller ones, who tended to walk straighter ahead. I agree with the authors' rebuttal to my previous review that "the data are the data" but I still have doubts. Now supplied as suggested by another reviewer, Figure 18 provides more detail of the underlying data, with considerably lower correlations. I now suspect that Figure 10 benefits from some statistical artifacts due to binning and other operations, and the weaker correlations of Fig. 18A are closer to reality. I am rather suspicious of correlations of correlations (Figure 18B), which lose some statistical grounding because the second correlation treats all data on equal footing, effectively whitewashing the first correlations of their varying significance (p-values 0.008 to 1e-9).

Furthermore, I am also unsure about Figure 10's comparison of tortuosity vs. straight path slope against leg length. Both tortuosity and straight path slope are already effectively dimensionless and therefore already seem to eliminate scale. It is my understanding that the simulated paths were recomputed for each subject's parameters, and the horizontal axis, slope, is already an angular measure that should affect short and tall people similarly. Shouldn't all subjects equally avoid steep angles, regardless of their dimensional height? If there is indeed a scale effect, then I would expect it to be demonstrated with a dimensional measure (vertical axis) that depends on leg length.

I certainly agree with the hypothetical prior that tall adults walk straight over obstacles that shorter adults (or children) walk around. But I feel that simpler tests would better evidence, perhaps in future work. Did shorter subjects walk with greater tortuosity than taller ones on the same terrain? Did shorter subjects take relatively more steps even after normalizing for leg length? A possible comparison would be (number of steps)*(leg length)/(start to end distance). I feel that the evidence from this study is not that strong.

Although it is a strength of this study that so much can be learned from pure observation, that does not mean controlled conditions are not scientifically helpful. As mentioned earlier, a helpful control could have been to ask subjects to walk straighter but less preferred paths on the same terrain, treating human paths as an independent variable. Another would be to treat terrain as an independent variable, by using level ground and intermediate terrain conditions. This would make it easier to test whether taller subjects walk straighter ahead on more uneven terrain than shorter subjects. Indeed, the data set already includes some patches of flatter terrain, not included here. Additional and simpler tests might be possible based on existing data.

Conclusion

This is an ambitious undertaking, presenting a wealth of unprecedented data to quantitatively test basic ecological questions that have long been unanswered. There are a number of considerable strengths that merit appreciation, especially the ability to quantitatively predict when humans will walk more circuitously. The weaknesses are about limitations in the conclusions that can be drawn thus far rather than the correctness of the study. I consider this to be a first step that will hopefully enable and inspire a long line of future work that will address these questions more in depth.

Reviewer #2 (Public Review):

The authors had two aims in this study. First, to develop a tool that lets them quantify the synaptic strength and sign of upstream neurons in a large network of cultured neurons. Second, they aimed at disentangling the contributions of excitatory and inhibitory inputs to spike generation.

For the quantification of synaptic currents, their methods allows them to quantify excitatory and inhibitory currents simultaneously, as the sign of the current is determined by the neuron identity in the high-density extracellular recording. They further made sure that their method works for nonstationary firing rates, and they did a simulation to characterize what kind of connections their analysis does not capture. They assume that dendritic integration is linear, which is reasonable for synaptic currents measured using voltage-clamp.

As suggested in a previous review, they have partitioned the explained variance into frequency bands and are able to account for most of the variance in the 3-200Hz range of expected synaptic activity.

For the contributions of excitation and inhibition to neuronal spiking, the authors found a clear reduction of inhibitory inputs and increase of excitation associated with spiking when averaging across many spikes. And interestingly, the inhibition shows a reversal right after a spike and the timescale is faster during higher network activity. These findings provide further support that their method is working. In the revised version the authors now also provide an analysis of which synaptic event is associated with postsynaptic spiking. The large datasets from this study are well-suited to examining these points.

For the first part, the authors achieved their goal in developing a tool to study synaptic inputs driving subthreshold activity at the soma and characterizing such connections. For the second part, they found an effect of EPSCs on firing, and in the revision they have quantified its relevance.

With the availability of Neuropixels probes, there is certainly use for their tool in in vivo applications, and their statistical analysis provides a reference for future studies.<br /> The relevance of excitatory and inhibitory currents on spiking has now been examined in the updated version of the manuscript.

In the following, there is a suggestion on improving Figure 6. Many other suggestions for Fig 6 and 7 have been taken up in the revision and it is OK to consider this as future work:

Figure 6B is useful, but could be done better: The autocovariance of a shotnoise process is a convolution of the autocovariance of the underlying point process and the autocovariance of the EPSC kernel. So one would want to separate those to obtain a better temporal resolution. But a shotnoise process has well defined peaks, and the time of these local maxima can be estimated quite precisely. Now if I would do a peak triggered average instead of the full convolution, I would do half of the deconvolution and obtain a temporally asymmetric curve of what is expected to happen around an EPSC. Importantly, one could directly see expected excitation after inhibition or expected inhibition after excitation, and this visualization could be much better and more intuitive compared to panel 6E.

As a suggestion for further analysis, though I am well aware that this is likely beyond the scope of this manuscript, I'd suggest the following analysis:<br /> I would split the data into the high and low activity states. Then I would compute the average of E/(E+I) values for spikes. Assuming that spikes tend to happen for local maxima of E/(E+I) I would find local maxima for periods without spikes such that their average is equal to the value for actual spikes. Finally, I would test for a systematic difference in either excitation or inhibition.<br /> If there is no difference, you can make the claim that synaptic input does not guarantee a spike, and compare it to a global average of E/(E+I).

Reviewer #2 (Public review):

The study presents valuable findings on self-citation rates in the field of Neuroscience, shedding light on potential strategic manipulation of citation metrics by first authors, regional variations in citation practices across continents, gender differences in early-career self-citation rates, and the influence of research specialization on self-citation rates in different subfields of Neuroscience. While some of the evidence supporting the claims of the authors is solid, some of the analysis seems incomplete and would benefit from more rigorous approaches.

Reviewer #2 (Public Review):

The manuscript by Berrocal et al. asks if shared bursting kinetics, as observed for various developmental genes in animals, hint towards a shared molecular mechanism or result from natural selection favoring such a strategy. Transcription happens in bursts. While transcriptional output can be modulated by altering various properties of bursting, certain strategies are observed more widely. As the authors noted, recent experimental studies have found that even-skipped enhancers control transcriptional output by changing burst frequency and amplitude while burst duration remains largely constant. The authors compared the kinetics of transcriptional bursting between endogenous and ectopic gene expression patterns. It is argued that since enhancers act under different regulatory inputs in ectopically expressed genes, adaptation would lead to diverse bursting strategies as compared to endogenous gene expression patterns. To achieve this goal, the authors generated ectopic even-skipped transcription patterns in fruit fly embryos. The key finding is that bursting strategies are similar in endogenous and ectopic even-skipped expression. According to the authors, the findings favor the presence of a unified molecular mechanism shaping even-skipped bursting strategies. This is an important piece of work. Everything has been carried out in a systematic fashion.

Reviewer #2 (Public Review):

The paper by Giese and coworkers is quite an intense reading. The manuscript is packed with data pertaining to very different aspects of MET apparatus function, scales, and events. I have to praise the team that combined molecular genetics, biochemistry, NMR, microscopy, functional physiology, in-vivo tests for vestibulo-ocular reflexes, and other tests for vestibular dysfunction with molecular modeling and simulations. The authors nicely show the way CIBs are associated with TMCs to form functional MET channels. The authors clarify the specificity of associations and elucidate the functional effects of the absence of specific CIBs and their partial redundancy.

Comments on revised version:

I appreciate the author's effort to address my comments. The revised paper 'Complexes of vertebrate TMC1/2 and CIB2/3 proteins 1 form hair-cell mechanotransduction cation channels' by Giese and coworkers is definitely cleaner but remains a compendium of related but very uneven parts. By saying 'uneven,' I mean that the grounding of the experimental and computational parts is different, and the firmness of conclusions, respectively, is not matched.

My conclusion is that this is a great collaborative project. However, in its present form, different components pull the emphasis in several directions with little cross-talk. It is worth splitting into two papers.

Reviewer #2 (Public review):

Summary:

Marylin Alves de Almeida et al. developed a novel mouse cross via conditionally depleting functional SMN protein in the liver (AlbCre/+;Smn2B/F7). This mouse model retains a proportion of SMN in the liver, which better recapitulates SMN deficiency observed in SMA patients and allows further investigation into liver-specific SMN deficiency and its systemic impact. They show that AlbCre/+;Smn2B/F7 mice do not develop an apparent SMA phenotype as mice did not develop motor neuron death, neuromuscular pathology or muscle atrophy, which is observed in the Smn2B/- controls. Nonetheless, at P19, these mice develop mild liver steatosis, and interestingly, this conditional depletion of SMN in the liver impacts cells in the pancreas.

Strengths:

The current model has clearly delineated the apparent metabolic perturbations which involve a significantly increased lipid accumulation in the liver and pancreatic cell defects in AlbCre/+;Smn2B/F7 mice at P19. Standard methods like H&E and Oil Red-O staining show that in AlbCre/+;Smn2B/F7 mice, their livers closely mimic the livers of Smn2B/- mice, which have the full body knockout of SMN protein. Unlike previous work, this liver-specific conditional depletion of SMN is superior in that it is not lethal to the mouse, which allows an opportunity to investigate the long-term effects of liver-specific SMN on the pathology of SMA.

Weaknesses: Given that SMA often involves fatty liver, dyslipidemia and insulin resistance, using the current mouse model, the authors could have explored the long-term effects of liver-specific depletion of SMN on metabolic phenotypes beyond P19, as well as systemic effects like glucose homeostasis. Given that the authors also report pancreatic cell defects, the long-term effect on insulin secretion and resistance could be further explored. The mechanistic link between a liver-specific SMN depletion and apparent pancreatic cell defects is also unclear.

Discussion:

This current work explores a novel mouse cross in order to specifically deplete liver SMN using an Albumin-Cre driver line. This provides insight into the contribution of liver-specific SMN protein to the pathology of SMA, which is relevant for understanding metabolic perturbations in SMA patients. Nonetheless, given that SMA in patients involve a systemic deletion or mutation of the SMN gene, the authors could emphasize the utility of this liver-specific mouse model, as opposed to using in vitro models, which have been recently reported (Leow et al, 2024, JCI). Authors should also discuss why a mild metabolic phenotype is observed in this current mouse model, as opposed to other SMA mouse models described in literature.

Reviewer #2 (Public review):

Summary:

In this study, Lamba and colleagues suggest a molecular mechanism to explain cell heterogeneity in cell specification during pre-implantation development. They show that embryo polarization is asynchronous. They propose that reduced CARM1 activity and upregulation of its substrate BAF155 promote early polarization and trophectoderm specification.

Strengths:

The authors use appropriate and validated methodology to address their scientific questions. They also report excellent live imaging. Most of the data are accompanied by careful quantifications.

Weaknesses:

I think this manuscript requires some more quantification, increased number of embryos in their evaluations and clearly stating the number of embryos evaluated per experiments.

Here are some points:

(1) It should be clearly stated in all figure legends and in the text how many cells from how many embryos were analyzed.

(2) I think that the number of embryos sometimes are too low. These are mouse embryos easily accessible and the methods used are well established in this lab, so the authors should make an effort to have at least 10/15 embryos per experiment. For example "In agreement with this, hybridization chain reaction (HCR) RNA fluorescence in situ hybridization of early 8-cell stage embryos revealed that the number of CDX2 mRNA puncta was higher in polarized blastomeres with a PARD6-positive apical domain than in unpolarized blastomeres, for 5 out of 6 embryos with EP cells (Figure 3A, B)".. or the data for Figure 4, we know how many cells but now how many embryos.

(3) It would be useful to see in Figure 4 an example of asymmetric cell division as done for symmetric cell division in panel 4B. This could really help the reader to understand how the authors assessed this.

(4) Figure 5C there is a big disproportion of the number of EP and LP identified. Could the authors increase the number of embryos quantified and see if they can increase EP numbers?

(5) Could the authors give more details about how they mount the embryos for live imaging? With agarose or another technique? In which dishes? Overlaid with how much medium and oil? This could help other labs that want to replicate the live imaging in their labs. Also, was it a z-stack analysis? If yes, how many um per stack? Ideally, if they also know the laser power used (at least a range) it would be extremely useful.

Reviewer #2 (Public review):

Summary:

The paper by Zhang et al. has two parts.

The first one presents a comprehensive study of the nucleosome pKs, including their shifts from reference values in solution. They also explore changes in the protonation states of the histone residue in response to the formation of various nucleosome complexes, including higher-order nucleosome structures. The overall conclusion is that pH-induced changes in histone residue protonation states modulate nucleosome surface electrostatic potentials, and influence nucleosome-partner protein interactions. Proton uptake or release often accompanied by nucleosome-partner protein interactions affects their binding processes.

In the second part, the authors study the effect of 1266 recurrent histone cancer mutations on the nucleosome surface electrostatics: they show a significant subset of these has a major effect on the nucleosome-partner interactions, with the potential to regulate nucleosome self-association, thereby affecting higher-order chromatin structures.

Strengths:

The main strengths of this work are its technical rigor, comprehensive nature, and novelty of several of its aspects. For example, I am not aware of another work that analyzed pK shifts in the nucleosome in such level of detail, and on for so many different structures. The same for pK shifts upon nucleosome-partner binding. The analysis of pK shifts in nucleosome-nucleosome binding is likely completely new. The authors use an established methodology, check it against experiment at least in some instances, and, very importantly, base their conclusions on many different structures. The specific pK-related numbers they report are believable.

Regarding the second part of the work: the specific connection made between a subset of cancer-associated mutations and the major electrostatic changes in the nucleosome is novel and should be of interest to a broad community. The authors conclude that cancer mutations can also regulate nucleosome self-association, modulating the organization and dynamics of higher-order chromatin structures.

The detailed and comprehensive analysis of the cancer-associated mutations, including their partitioning into multiple relevant categories, is of value in its own right.

Weaknesses:

The main weakness of the first (pK-related) part of this work is the lack of relevance to specific conditions in most living cells of higher eukaryotes. The problem is that the nucleosome resides in the nucleus, where the pH is very tightly controlled, and for good reasons. See e.g. Casey, J., Grinstein, S., and Orlowski, J. ``Sensors and regulators of intracellular pH." Nature Rev. Mol. Cell. Biology. (2009). Parker, M. D., and Boron, W. F. ``The divergence, actions, roles, and relatives of sodium-coupled bicarbonate transporters.", Physiol. Rev. (2013). While intracellular pH does deviate from about 7.2, the naturally occurring deviations are only of the order of 0.3 pH units. In that respect, what the authors call "physiological" range of 6.5 to 7.5 is still too broad, let alone the "slightly basic (pH 5 to 6.5) or ``slightly acidic" (pH 7.5 to 9) conditions, as defined by the authors. It is hard to imagine a situation where intra-nuclear pH changes from e.g. "slightly acidic" to neutral in a live cell nucleus.

This said, there is nothing wrong with studying the response of the nucleosome structures to these large variations of pH, which can be reproduced in-vitro. It is the relevance of the findings to in-vivo conditions that are highly questionable.

The second part of the work - the effect of cancer mutations - is free from this major defect. In the opinion of this reviewer, it can (and should) stand on its feet, as a separate work.

However, the lack of specific, testable (preferably quantitative) biologically relevant predictions is a weakness of both parts. For example, in "Discussion" the authors state that "Histone ionizable residues are highly sensitive to cellular pH fluctuations, leading to changes in their protonation states and consequent alterations in nucleosome surface electrostatic potentials and interactions." This statement is certainly true, based on what is already known about the effect of pH on protein-DNA (or protein-protein) association, from previous works. But what are the specific predictions here?

Reviewer #2 (Public review):

Summary:

The manuscript by Hanna et al., addresses the question of energy metabolism in the retina, a neuronal tissue with an inordinately high energy demand. Paradoxically, the retina appears to employ to a large extent glycolysis to satisfy its energetic needs, even though glycolysis is far less efficient than oxidative phosphorylation (OXPHOS). The focus of the present study is on the early development of the retina and the retinal progenitor cells (RPCs) that proliferate and differentiate to form the seven main classes of retinal neurons. The authors use different genetic and pharmacological manipulations to drive the metabolism of RPCs or the retina towards higher or lower glycolytic activity. The results obtained suggest that increased glycolytic activity in early retinal development produces a more rapid differentiation of RPCs, resulting in a more rapid maturation of photoreceptors and photoreceptor segment growth. The study is significant in that it shows how metabolic activity can determine cell fate decisions in retinal neurons.

Strengths:

This study provides important findings that are highly relevant to the understanding of how early metabolism governs the development of the retina. The outcomes of this study could be relevant also for human diseases that affect early retinal development, including retinopathy of maturity where an increased oxygenation likely causes a disturbance of energy metabolism.

Weaknesses:

The restriction to only relatively early developmental time points makes it difficult to assess the consequences of the different manipulations on the (more) mature retina. Notably, it is conceivable that early developmental manipulations, while producing relevant effects in the young post-natal retina, may "even out" and may no longer be visible in the mature, adult retina.

Reviewer #2 (Public review):

Summary.

Mitochondrial dysfunction is associated with a wide spectrum of genetic and age-related diseases. Healthy mitochondria form a dynamic reticular network and constantly fuse, divide, and move. In contrast, dysfunctional mitochondria have altered dynamic properties resulting in fragmentation of the network and more static mitochondria. It has recently been reported that different types of mitochondrial stress or dysfunction activate kinases that control the integrated stress response, including HRI, PERK, and GCN2. Kinase activity results in decreased global translation and increased transcription of stress response genes via ATF4, including genes that encode mitochondrial protein chaperones and proteases (HSP70 and LON). In addition, the ISR kinases regulate other mitochondrial functions including mitochondrial morphology, phospholipid composition, inner membrane organization, and respiratory chain activity. Increased mitochondrial connectivity may be a protective mechanism that could be initiated by pharmacological activation of ISR kinases, as was recently demonstrated for GCN2.

A small molecule screening platform was used to identify nucleoside mimetic compounds that activate HRI. These compounds promote mitochondrial elongation and protect against acute mitochondrial fragmentation induced by a calcium ionophore. Mitochondrial connectivity is also increased in patient cells with a dominant mutation in MFN2 by treatment with the compounds.

Strengths:

(1) The screen leverages a well-characterized reporter of the ISR: translation of ATF4-FLuc is activated in response to ER stress or mitochondrial stress. Nucleoside mimetic compounds were screened for activation of the reporter, which resulted in the identification of nine hits. The two most efficacious dose-response tests were chosen for further analysis (0357 and 3610). The authors clearly state that the compounds have low potency. These compounds were specific to the ISR and did not activate the unfolded protein response or the heat shock response. Kinases activated in the ISR were systematically depleted by CRISPRi revealing that the compounds activate HRI.

(2) The status of the mitochondrial network was assessed with an Imaris analysis pipeline and attributes such as length, sphericity, and ellipsoid principal axis length were quantified. The characteristics of the mitochondrial network in cells treated with the compounds were consistent with increased connectivity. Rigorous controls were included. These changes were attenuated with pharmacological inhibition of the ISR.

(3) Treatment of cells with the calcium ionophore results in rapid mitochondrial fragmentation. This was diminished by pre-treatment with 0357 or 3610 and control treatment with thapsigargin and halofuginone

(4) Pathogenic mutations in MFN2 result in the neurodegenerative disease Charcot-Marie-Tooth Syndrome Type 2A (CMT2A). Patient cells that express Mfn2-D414V possess fragmented mitochondrial networks and treatment with 0357 or 3610 increased mitochondrial connectivity in these cells.

Weaknesses:

The weakness is the limited analysis of cellular changes following treatment with the compounds.

(1) Unclear how 0357 or 3610 alter other aspects of cellular physiology. While this would be satisfying to know, it may be that the authors determined that broad, unbiased experiments such as RNAseq or proteomic analysis are not justified due to the limited translational potential of these specific compounds.

(2) There are many changes in Mfn2-D414V patient cells including reduced respiratory capacity, reduced mtDNA copy number, and fewer mitochondrial-ER contact sites. These experiments are relatively narrow in scope and quantifying more than mitochondrial structure would reveal if the compounds improve mitochondrial function, as is predicted by their model.

Reviewer #2 (Public review):

Summary:

This work by Dong and colleagues investigates the directed migration of tracheal stem cells in Drosophila pupae, essential for tissue homeostasis. These cells, found in two nearby groups, migrate unidirectionally along the dorsal trunk towards the posterior to replenish degenerating branches that disperse the FGF mitogen. The authors show that inter-organ communication between tracheal stem cells and the neighboring fat body controls this directionality. They propose that the fat body-derived cytokine Upd2 induces JAK/STAT signaling in tracheal progenitors, maintaining their directional migration. Disruption of Upd2 production or JAK/STAT signaling results in erratic, bidirectional migration. Additionally, JAK/STAT signaling promotes the expression of planar cell polarity genes, leading to asymmetric localization of Fat in progenitor cells. The study also indicates that Upd2 transport depends on Rab5- and Rab7-mediated endocytic sorting and Lbm-dependent vesicle trafficking. This research addresses inter-organ communication and vesicular transport in the disciplined migration of tracheal progenitors.

Strengths:

This manuscript presents extensive and varied experimental data to show a link between Upd2-JAK/STAT signaling and tracheal progenitor cell migration. The authors provide convincing evidence that the fat body, located near the trachea, secretes vesicles containing the Upd2 cytokine. These vesicles reach tracheal progenitors and activate the JAK-STAT pathway, which is necessary for their polarized migration. Using ChIP-seq, GFP-protein trap lines of planar cell polarity genes, and RNAi experiments, the authors demonstrate that STAT92E likely regulates the transcription of planar cell polarity genes and some apicobasal cell polarity genes in tracheal stem cells, which seem to be necessary for unidirectional migration.

Weaknesses:

Directional migration of tracheal progenitors is only partially compromised, with some cells migrating anteriorly and others maintaining their posterior migration.<br /> Additionally, the authors do not examine the potential phenotypic consequences of this defective migration.

It is not clear whether the number of tracheal progenitors remains unchanged in the different genetic conditions. If there are more cells, this could affect their localization rather than migration and may change the proposed interpretation of the data.

Upd2 transport by vesicles is not convincingly shown.

Data presentation is confusing and incomplete.

Reviewer #2 (Public review):

Summary:

This manuscript presents a new approach for non-invasive, MRI-based measurements of cerebral blood volume (CBV). Here, the authors use ferumoxytol, a high-contrast agent, and apply specific sequences to infer CBV. The authors then move to statistically compare measured regional CBV with the known distribution of different types of neurons, markers of metabolic load, and others. While the presented methodology captures an estimated 30% of the vasculature, the authors corroborated previous findings regarding the lack of vascular compartmentalization around functional neuronal units in the primary visual cortex.

Strengths:

Non-invasive methodology geared to map vascular properties in vivo.

Implementation of a highly sensitive approach for measuring blood volume.

Ability to map vascular structural and functional vascular metrics to other types of published data.

Weaknesses:

The key issue here is the underlying assumption about the appropriate spatial sampling frequency needed to capture the architecture of the brain vasculature. Namely, ~7 penetrating vessels / mm2 as derived from Weber et al 2008 (Cer Cor). The cited work begins by characterizing the spacing of penetrating arteries and ascending veins using a vascular cast of 7 monkeys (Macaca mulatta, same as in the current paper). The ~7 penetrating vessels / mm2 are computed by dividing the total number of identified vessels by the area imaged. The problem here is that all measurements were made in a "non-volumetric" manner and only in V1. Extrapolating from here to the entire brain seems like an over-assumption, particularly given the region-dependent heterogeneity that the current paper reports.

Reviewer #2 (Public review):

Summary:

In this study by Sánchez-León and colleagues, the authors attempted to determine the influence of neuronal orientation on the efficacy of cerebellar tDCS in modulating neural activity. To do this, the authors made recordings from Purkinje cells, the primary output neurons of the cerebellar cortex, and determined the inter-dependency between the orientation of these cells and the changes in their firing rate during cerebellar tDCS application.

Strengths:

(1) A major strength is the in vivo nature of this study. Being able to simultaneously record neural activity and apply exogenous electrical current to the brain during both an anesthetized state and during wakefulness in these animals provides important insight into the physiological underpinnings of tDCS.

(2) The authors provide evidence that tDCS can modulate neural activity in multiple cell types. For example, there is a similar pattern of modulation in Purkinje cells and non-Purkinje cells (excitatory and inhibitory interneurons). Together, these data provide wholistic insight into how tDCS can affect activity across different populations of cells, which has important implications for basic neuroscience, but also clinical populations where there may be non-uniform or staged effects of neurological disease on these various cell types.

(3) There is a systematic investigation into the effects of tDCS on neural activity across multiple regions of the cerebellum. The authors demonstrate that the pattern of modulation is dependent on the target region. These findings have important implications for determining the expected neuromodulatory effects of tDCS when applying this technique over different target regions non-invasively in animals and humans.

Weaknesses:

(1) In the introduction, there is a lack of context regarding why neuronal orientation might be a critical factor influencing the responsiveness to tDCS. The authors allude to in vitro studies that have shown neuronal orientation to be relevant for the effects of tDCS on neural activity but do not expand on why this might be the case. These points could be better understood by informing the reader about the uniformity/non-uniformity of the induced electric field by tDCS. In addition, there is a lack of an a priori hypothesis. For example, would the authors have expected that neuronal orientation parallel or perpendicular to the electrical field to be related to the effects of tDCS on neural activity?

(2) It is unclear how specific stimulation parameters were determined. First, how were the tDCS intensities used in the present experiments determined/selected, and how does the relative strength of this induced electric field equate to the intensities used non-invasively during tDCS experiments in humans? Second, there is also a fundamental difference in the pattern of application used here (e.g., 15 s pulses separated by 10 s of no stimulation) compared to human studies (e.g., 10-20 min of constant stimulation).

(3) In their first experiment, the authors measure the electric field strength at increasing depths during increasing stimulation intensities. However, it appears that an alternating current rather than a direct current, which is usually employed in tDCS protocols, was used. There is a lack of rationale regarding why the alternating current was used for this component. Typically, this technique is more commonly used for entraining/boosting neural oscillations compared to studies using tDCS which aim to increase or decrease neural activity in general.

Reviewer #2 (Public review):

Summary:

The authors aimed to investigate how noradrenergic and glucocorticoid activity after retrieval influence subsequent memory recall with a 24-hour interval, by using a controlled three-day fMRI study involving pharmacological manipulation. They found that noradrenergic activity after retrieval selectively impairs subsequent memory recall, depending on hippocampal and cortical reactivation during retrieval.

Overall, there are several significant strengths of this well-written manuscript.

Strengths:

(1) The study is methodologically rigorous, employing a well-structured three-day experimental design that includes fMRI imaging, pharmacological interventions, and controlled memory tests.

(2) The use of pharmacological agents (i.e., hydrocortisone and yohimbine) to manipulate glucocorticoid and noradrenergic activity is a significant strength.

(3) The clear distinction between online and offline neural reactivation using MVPA and RSA approaches provides valuable insights into how memory dynamics are influenced by noradrenergic and glucocorticoid activity distinctly.

Weaknesses:

(1) One potential limitation is the reliance on distinct pharmacodynamics of hydrocortisone and yohimbine, which may complicate the interpretation of the results.

(2) Another point related above, individual differences in pharmacological responses, physiological and cortisol measures may contribute to memory recall on Day 3.

(3) Median-splitting approach for reaction times and hippocampal activity should better be justified.