Reviewer #1 (Public Review):

The authors have studied the effect of temperature on the interspecific interaction strength of coastal marine fish communities, using eDNA samples. Their introduction describes the state of the art concerning the dynamics of interspecific interactions in ecological communities. This introduction is well written and highly information dense, summarizing all that the reader needs to know to further understand their study setup and execution.

The authors hypothesize that water temperature changes could have an effect on the interspecific interaction strength between marine fishes, and they studied this with a two year long, bi-weekly eDNA sampling campaign at 11 study sites in Japan with different temperature gradients. These 550 water samples were analysed for fish biodiversity through eDNA-metabarcoding using MiFish primers. By using the most abundant fish species as an internal spike in and quantifying the copy numbers from this species by qPCR, the authors were able estimate DNA copy numbers for the total dataset. From the 50 most frequently detected fish species in these samples they showed that temperature affected the interspecific interaction strength between some species. Their work provides a highly relevant approach to perform species-interaction strength analysis based on eDNA biodiversity assessments, and as such provides a research framework to study marine community dynamics by eDNA, which is highly relevant in the study of ecosystem dynamics. The models and analytical methods used are clearly described and made available, enabling application of these methods by anyone interested in applying it to their own site and species group of interest.

Strengths: The authors have a study setup that is suitable to measure the effects of temperature of the eDNA diversity, and have taken a large number of samples and all appropriate controls to be able to accurately measure and describe these dynamics. The applied internal spike in to enable relative eDNA copy number quantification is convincing.

Weaknesses:

The authors were able to find a correlation between water temperature and interaction strengths observed. However, since water temperature is dependent on many environmental variables that are either directly or indirectly influencing ecosystem dynamics, it is hard to prove a direct correlation between the observed changes in community dynamics and the temperature alone

Consensus Public Review:

Ottenheimer et al., present an interesting study looking at the neural representation of value in mice performing a pavlovian association task. The task is repeated in the same animals using two odor sets, allowing a distinction between odor identity coding and value coding. The authors use state-of-the-art electrophysiological techniques to record thousands of neurons from 11 frontal cortical regions to conclude that 1) licking is represented more strongly in dorsal frontal regions, 2) odor cues are represented more strongly in ventral frontal regions, 3) cue values are evenly distributed across regions. They separately perform a calcium imaging study to track coding across days and conclude that the representation of task features increments with learning and remains stable thereafter.Overall, these conclusions are interesting and well supported by the data.

The authors use reduced-rank kernel regression to characterize the 5332 recorded neurons on a cell-by-cell basis in terms of their responses to cues, licks, and reward, with a cell characterized as encoding one of these parameters if it accounts for at least 2% of the observed variance (while at first this seemed overly lenient, the authors present analyses demonstrating low false-positives at this threshold and that the results are robust to different cutoffs).

Having identified lick, reward, and cue cells, the authors next select the 24% of "cue-only" neurons and look for cells that specifically encode cue value. Because the animal's perception of stimulus value can't be measured directly, the authors created a linear model that predicts the amount of anticipatory licking in the interval between odor cue and reward presentations. The session-average-predicted lick rate by this model is used as an estimate of cue value and is used in the regression analysis that identified value cells. (Hence, the authors' definition of value is dependent on the average amount of anticipatory behavior ahead of a reward, which indicates that compared to the CS+, mice licked around 70% as much to the CS50 and 10% as much to the CS-.) The claim that this is an encoding of value is strengthened by the fact that cells show similar scaling of responses to two odor sets tested. Whereas the authors found more "lick" cells in motor regions and more "cue" cells in sensory regions, they find a consistent percentage of "value" cells (that is, cells found to be cue-only in the initial round of analysis that is subsequently found to encode anticipatory lick rate) across all 11 recorded regions, leading to their claim of a distributed code of value.

In subsequent sections, the authors expand their model of anticipatory-licking-as-value by incorporating trial and stimulus history terms into the model, allowing them to predict the anticipatory lick rate on individual trials within a session. They also use 2-photon imaging in PFC to demonstrate that neural coding of cue and lick are stable across three days of imaging, supported by two lines of evidence. First, they show that the correlation between cell responses on all periods except for the start of day 1 is more correlated with day 3 responses than expected by chance (although the correlation is low, the authors attribute this to inherent limitations of the data), and that response for a given neuron is substantially better correlated with its own activity across time than random neurons. Second, they show that cue identity is able to capture the highest unique fraction of variance (around 8%) in day 3 cue cells across three days of imaging, and similarly for lick behavior in lick cells and cue+lick in cue+lick cells. Nonetheless, their sample rasters for all imaged cells also indicate that representations are not perfectly stable, and it will be interesting to see what *does* change across the three days of imaging.

Reviewer #1 (Public Review):

This work describes a novel high-throughput approach to diverse transgenesis which the authors have named TARDIS for Transgenic Arrays Resulting in Diversity of Integrated Sequences. The authors describe the general approach: the generation of a synthetic 'landing pad' for transgene insertion (as previously reported by this group) that has a split selection hygromycin resistance gene, meaning that only perfect integration with the insert confers resistance to the otherwise lethal hygromycin drug. The authors then demonstrate two possible applications of the technology: individually barcoded lineages for lineage tracing and transcriptional reporter lines generated by inserting multiple promoters. In both cases, the authors did a limited 'proof of concept' study including many important controls, showcasing the potential of the method. The conclusions for applications of this method in C. elegans are supported by the data and the authors discuss important observations and considerations. In the discussion, the discuss the potential application of the method beyond C. elegans, although this remains speculative at this point given that a nontrivial aspect of the success of the method in worms is the self-assembly of DNA into heritable extrachromosomal arrays (a feature that is absent in most other systems).

Reviewer #1 (Public Review):

The authors investigated state-dependent changes in evoked brain activity, using electrical stimulation combined with multisite neural activity across wakefulness and anesthesia. The approach is novel, and the results are compelling. The study benefits from in depth sophisticated analysis of neural signals. The effects of behavioral state on brain responses to stimulation are generally convincing.

It is possible that the authors' use of "an average reference montage that removed signals common to all EEG electrodes" could also remove useful components of the signal, which are common across EEG electrodes, especially during deep anesthesia. For example, it is possible (in fact from my experience I would be surprised if it is not the case) that under isoflurane anesthesia, electrical stimulation induces a generalized slow wave or a burst of activity across the brain. Subtracting the average signal will simply remove that from all channels. This does not only result in signals under anesthesia being affected more by the referencing procedure than during waking, but also will have different effects on different channels, e.g. depending on how strong the response is in a specific channel.

Reviewer #1 (Public Review):

The manuscript, "A versatile high-throughput assay based on 3D ring-shaped cardiac tissues generated from human induced pluripotent stem cell-derived cardiomyocytes" developed a unique culture platform with PEG hydrogel that facilitates the in-situ measurement of contractile dynamics of the engineered cardiac rings. The authors optimized the tissue seeding conditions, demonstrated tissue morphology with expressions of cardiac and fibroblast markers, mathematically modeled the equation to derive contractile forces and other parameters based on imaging analysis, and ended by testing several compounds with known cardiac responses.

To strengthen the paper, the following comments should be considered:

1. This paper provided an intriguing platform that creates miniature cardiac rings with merely thousands of CMs per tissue in a 96-well plate format. The shape of the ring and the squeezing motion can recapitulate the contraction of the cardiac chamber to a certain degree. However, Thavandiran et al (PNAS 2013) created a larger version of the cardiac ring and found the electrical propagation revealed spontaneous infinite loop-like cycles of activation propagation traversing the ring. This model was used to mimic a reentrant wave during arrhythmia. Therefore, it presents great concerns if a large number of cardiac tissues experience arrhythmia by geometry-induced re-entry current and cannot be used as a healthy tissue model. It would be interesting to see the impulse propagation/calcium transient on these miniature cardiac rings and evaluate the % of arrhythmia occurrence.

2. The platform can produce 21 cardiac rings per well in 96-well plates. The throughput has been the highest among competing platforms. The resulting tissues have good sarcomere striation due to the strain from the pillars. Now the emerging questions are culture longevity and reproducibility among tissues. According to Figure 1E, there was uneven ring formation around the pillar, which leads to the tissue thinning and breaking off. There is only 50% survival after 20 days of culture in the optimized seeding group. Is there any way to improve it? The tissues had two compartments, cardiac and fibroblast-rich regions, where fibroblasts are responsible for maintaining the attachment to the glass slides. Do the cardiac rings detach from the glass slides and roll up? The SD of the force measurement is a quarter of the value, which is not ideal with such a high replicate number. As the platform utilizes imaging analysis to derive contractile dynamics, calibration should be done based on the angle and the distance of the camera lens to the individual tissues to reduce the error. On the other hand, how reproducible of the pillars? It is highly recommended to mechanically evaluate the consistency of the hydrogel-based pillars across different wells and within the wells to understand the variance.

3. Does the platform allow the observation of non-synchronized beating when testing with compounds? This can be extremely important as the intended applications of this platform are drug testing and cardiac disease modeling. The author should elaborate on the method in the manuscript and explain the obtained results in detail.

4. The results of drug testing are interesting. Isoproterenol is typically causing positive chronotropic and positive inotropic responses, where inotropic responses are difficult to obtain due to low tissue maturity. It is inconsistent with other reported results that cardiac rings do not exhibit increased beating frequency, but slightly increased forces only. Zhao et al were using electrical pacing at a defined rate during force measurement, whereas the ring constructs are not.

Overall, the manuscript is well written and the designed platform presented the unique advantages of high throughput cardiac tissue culture. Besides the contractile dynamics and IHC images, the paper lacks other cardiac functional evaluations, such as calcium handling, impulse propagation, and/or electrophysiology. The culture reproducibility (high SD) and longevity (<20 days) still remain unsolved.

Reviewer #1 (Public Review):

Kou and Kang et al. investigated the role of Notch-RBP-J signaling in regulating monocyte homeostasis. Specifically, they examined how a conditional knockout of Rbpj expression in monocytes through a Rbpjfl/fl Lyz2cre/cre mouse affects the homeostasis of Ly6Chi versus Ly6Clo monocytes. They discovered that Rbpj deficiency did not affect the percentage of Ly6Chi monocytes but instead, led to an accumulation of Ly6Clo monocytes in the peripheral blood. Using a comprehensive number of in vivo techniques to investigate the origin of this increase, the authors revealed that the accumulation of Rbpj deficient Ly6Clo monocytes was not due to an increase in bone marrow egress and that this defect was cell intrinsic. However, EdU-labelling and apoptosis assays revealed that this defect was not due to an increase in proliferation nor conversion of Ly6Chi to Ly6Clo monocytes. Interestingly, it was revealed that Rbpj deficient Ly6Clo monocytes had increased expression of CCR2 and ablation of CCR2 expression reversed the accumulation of these cells in the periphery. Lastly, they discovered that Rbpj deficiency also led to downstream effects such as an accumulation of Ly6Clo monocytes in the lung tissue and increased CD16.2+ interstitial macrophages, presumably due to dysregulated monocyte differentiation and function.

Their findings are interesting and highlight a previously unexplored mechanistic link between Notch-RBP-J signaling and CCR2 expression in monocyte homeostasis, providing further insight into the distinct pathways that regulate Ly6Chi vs Ly6Clo monocyte subsets individually.

The conclusions of this paper are mostly well substantiated from the experimental data. The strengths of this paper include the use of multiple conditional genetic knock out mouse models to explore their hypothesis and the use of sophisticated in vivo techniques to study the major mechanisms involved in monocyte homeostasis.

Reviewer #1 (Public Review):

The manuscript entitled, "Loss of PTPMT1 limits mitochondrial utilization of carbohydrates and leads to muscle atrophy and heart failure," by Zheng, et al., is focused on assessing the role of deletion of PTPMT1, a mitochondria-based phosphatase, in mitochondrial fuel selection. Authors show that the utilization of pyruvate, a key mitochondrial substrate derived from glucose, is inhibited, whereas fatty acid utilization is enhanced. Importantly, while the deletion of PTPMT1 does not impact development of skeletal muscle or heart, the metabolic inflexibility leads to muscular atrophy, heart failure, and sudden death. Mechanistically, authors claim that the prolonged substrate shift from carbohydrates to lipids causes oxidative stress and mitochondrial dysfunction, leading to accumulation of lipids and muscle cell and CM damage in the KO. Interestingly, PTPMT1 deletion from the liver or adipose tissue does not generate any local or systemic defects. Authors conclude that PTPMT1 plays an important role in maintaining mitochondrial flexibility and that the balanced utilization of carbohydrates and lipids is essential for skeletal muscle and heart. While interesting and authors did a ton of experiments for this project, several major concerns exist. First, because both the CKMM- and the MYHC-Cre express early, during development , it seems the effects of the deletion of PTPMT1 are more likely be specific to defects in muscle and cardiac development rather than postnatal, especially since loss of PTPMT1 affects mTOR activity; indeed, previous reports have shown that selective deletion of mTOR or raptor in skeletal muscle during embryonic development leads to a reduction in postnatal growth and the development of late-onset myopathy and premature death around 6 to 8 months of age. The effects of the deletion in muscle seem eerily similar and therefore likely mechanistically function the same -embryonically, as has been previously suggested. This is also true for cardiac abnormalities, where developmental defects can manifest in mice as they age after at least 3-4 months and decreased mTOR activity can lead to significant cardiac dysfunction and failure (similarly to the effects observed here by the authors). To prove one way or another, authors should show developmental data providing evidence that the effects are not occurring at this stage. It is a lot of work, but the right way to differentiate pre- vs post- development functions of PTPMT1 in the muscle and heart, otherwise cannot verify mechanistically what the precise cause for the phenotype may be. Authors could consider generating mice that have inducible Cre drivers. In addition, how is it that the effects of loss of PTPMT1 are similar between muscle and heart given the differences in energy usage and utilization between these two tissues? Increases in AMPK are usually associated with better metabolic outcomes, particularly in the heart. Increased AMPK activation has also been shown to help reduce fat storage, increase insulin sensitivity, reduce cholesterol/triglyceride production, and suppress chronic inflammation. In addition, increases in carnitines are associated with enhanced metabolic function. Carnitines facilitate transport of long-chain fatty acids into the mitochondrial matrix, triggering cardioprotective effects through reduced oxidative stress, inflammation and necrosis of cardiac myocytes. All of these factors are positive, so how do authors explain this discrepancy in their findings which suggest opposing outcomes- as above, I suggest the explanation is that it is due to developmental effects of deletion of PTPMT1.

Authors attribute much of the pathology in the muscle and heart due to increased lipid accumulation in these tissues; but how do authors explain how hearts and muscle have more fat when the mice are smaller than wt? Is there a difference in energy expenditure in the mice? What about changes in white fat, core temperature or browning of fat? Authors do not mechanistically prove that lipid accumulation is the cause of death in these animals. Rescue experiments should be considered.

Public Review:

In this manuscript, Karl et al. explore mechanisms underlying the activation of the receptor tyrosine kinase FGFR1 and stimulation of intracellular signaling pathways in response to FGF4, FGF8, or FGF9 binding to the extracellular domain of FGFR1. Quantitative binding experiments presented in the manuscript demonstrate that FGF4, FGF8, and FGF9 exhibit distinct binding affinities towards FGFRs. It is also proposed that FGF8 exhibits "biased ligand" characteristics that is manifested via binding and activation FGFR1 mediated by "structural differences in the FGF- FGFR1 dimers, which impact the interactions of the FGFR1 trans membrane helices, leading to differential recruitment and activation of the downstream signaling adapter FRS2".

Major points:

1. Previous studies have demonstrated that the variability of signal transduction stimulated by different FGF family members originates from their preferential activation of different members of the FGFR family (Ornitz et al., 1996). For example, it was previously shown that members of the FGF8 subfamily preferentially activate FGFR3c, whereas members of the FGF4 subfamily activate FGFR1c more potently than other FGFs. Moreover, it was shown that FGF18, a member of the FGF8 subfamily, preferentially binds to and activates the FGFR3c isoform. Indeed, this can be seen in the data shown in Figure 3 in this manuscript, where maximum levels of FGFR1 pY653/4 and pFRS2 are reached at different concentrations when stimulated with increasing concentrations of each ligand in HEK293T cells. In order to be sure that the 'biased agonist' described in this manuscript for FGF8 binding is not caused by binding preference towards different FGFR members, the authors should present data comparing cell signaling via FGFR3c stimulated by FGF4, FGF8, and FGF9.

2. It is well-established that FGFR signaling by canonical FGF family members including FGF4, FGF8, and FGF9 is dependent on interactions of heparin or heparan sulfate proteoglycans (HSPG) to the ligand the receptors. Differential contributions of heparin to cell signaling mediated by FGF4, FGF8, and FGF9 binding and activation of different FGFRs expressed in RCS cells as this cell express endogenous HSPG molecules. This question should be addressed by comparing cell signaling via FGFRs ectopically expressed in BAF/3 cells (which do not possess endogenous FGFRs and HSPG) stimulated by FGF4, FGF8, and FGF9 in the absence or presence of different heparin concentrations. This approach has been applied many times in the past to explore and establish the role of heparin in control of ligand induced FGFR activation. It is impossible to interpret the FGFR binding characteristics and cellular activates of FGF4, FGF8, and FGF9 in the absence of information about the role of heparin in their binding and activation.

3. It is not clear how some of the experimental data were analyzed. Blots in Figures 3A and 3B should include controls (total FGFR1 for pY653/4 and total FRS for pFRS2). How are the data shown in Figure 3C normalized? It does look like the level of phosphorylation was all normalized against the strongest signals irrespective of which ligand was used. Each data representing each ligand should be separately normalized.

4. In page 6, authors used the plot shown in Figure 3 for 'FGFR downregulation' to conclude that "the effect of FGF4 on FGFR1 downregulation is smaller when compared to the effects of FGF8 and FGF9. However, it is unclear how the data shown in the plot was normalized - none of the data seem to reach "1.0". Moreover, the plot seems to suggest that FGF4 can strongly downregulate FGFR as it can downregulate FGFR with higher potency.

5. The structural basis of FGFR1 ligand bias and the different dimeric configurations and interactions between the kinase domain of FGFR1 dimers are not warranted (Figure 6). In the absence of any structural experimental data of different forms of FGFR dimers stimulated by FGF ligands the model presents in the manuscript is speculative and misleading.

Reviewer #1 (Public Review):

I feel that this study has potentially high public health significance and should be made known to the public, especially the usefulness of a natural chemical product, oligomeric proanthocyanidins, in preventing SARS-CoV2 infection. The studies are very well designed, using the first 5 figures to compare carefully the effects of tannic acid, punicalagin, and oligomeric proanthocyanidins in disrupting the interaction of the virus with host cells and in inhibiting the enzymatic activity of transmembrane serine protease 2 required for viral entry. I am especially impressed by the work done in Figures 6 and 7 in which the investigators put their efforts into quantitating the amounts of oligomeric proanthocyanidins, tannic acid, and punicalagin present in the grape seed, peel, flesh as well as juice. I also appreciate the translational application in which the investigators prepared grape seed extract capsules (200 mg and 400 mg), recruited healthy human subjects to take these capsules once or twice, and showed that the sera from randomized human subjects taking grape seed extract capsules indeed exert does-dependent and time-dependent activities in suppressing the infection rate of various SARS-CoV2 variants using in vitro studies. The study in Figure 7 is indeed very well-designed and quite elegant. The manuscript is also well-written.

Reviewer #1 (Public Review):

The authors of this manuscript are interested in identifying the molecular mechanisms underlying antidepressant action. Though most antidepressants target the serotonin system, regulation of glutamate neurotransmission has been associated with rapid treatment response. Here the authors find that monoaminergic targeted antidepressants are associated in some patients with expression of a small nucleolar RNA that they go on to show results in alterations to glutamate neurotransmission in a mouse model. These data offer a molecular mechanism that can link traditional monoaminergic targeted antidepressants with glutamatergic regulation and could offer a new way to estimate the efficacy of these drugs.

Reviewer #1 (Public Review):

The authors generated detailed anatomical descriptions and images of the coronary vasculature of mice, quails, zebrafish, Japanese tree frogs, Japanese fire belly newt, African clawed frogs, salmon sharks, Japanese sleeper rays and bird-beak dogfish. Using this data, they are able to show anatomical similarities in the origination points of evolutionary distant vertebrates from the third to fourth brachial arch. Additionally, the authors highlight the additional presence of a coronary vascular plexuses as a unique amniote trait, since it is seen in quail and mice but not xenopus frogs. Based on the presence of the possible homologies, the authors propose that the early developmental amniotic coronary artery is a derived from the ancestral hypobrachial artery. The methods for labeling and imaging the cardiac vessels are robust and congruent with previous studies describing these structures in mice and zebrafish. The study also presents an intriguing hypothesis; however, it could benefit from a more expansive survey of vertebrate coronary diversity using an increased number of species and developmental time points. A more exhaustive surveying of vertebrate diversity is required to demonstrate that the coronary vasculature anatomy observed is from common ancestral states or novel adaptations. The author's claim that a primitive vascular plexus represents a novel amniote phenotype, is reasonable, but could benefit from further confirmation using additional species.

Reviewer #1 (Public Review):<br /> <br /> Lobanov et al. investigated the effects of spatial structure in microbial communities that interact via secreted metabolites. The work builds up on a previous theoretical model by the authors that considered well-mixed populations in which different bacterial species secrete and consume different sets of metabolites, and metabolites in turn modify the growth rates of species. The model considers communities that are periodically exposed to dilutions, and the authors focus on the regime in which bacterial densities do not reach saturation before the next dilution. Analyzing the stable outcome of these dynamics through comparison with well-mixed scenarios, the authors found that space can favor species richness, especially in the case of communities with prevalent facilitative interactions. This positive effect on species coexistence is also more pronounced in situations in which species produce more kinds of metabolites than they consume. On the other hand, the positive effects on coexistence can be reversed when bacterial dispersal becomes relevant over the timescale of the simulations, as well as in cases in which the diffusion of metabolites is too slow - which could even result in less coexistence than in well-mixed scenarios. These results add to an ongoing discussion on the different ways in which spatial effects can impact microbial community dynamics and species richness.

The conclusions of this paper are mostly well supported by the data, but some aspects of the methodology and analysis need to be clarified and extended.

1) This is a model with many parameters and the manuscript should be clearer about how these parameters were used in different scenarios. It is probably a matter of rewriting the text, but I found it hard to understand which parameter values remained the same in scenarios with or without space, as well as how the strength of interactions was assigned, among a few other examples. In other cases, additional analysis (e.g. on how the spatial impact on coexistence depends on the average strength of interactions) would make the work more comprehensive.<br /> 2) To assess stable coexistence and richness, the authors use a criterium in which species have to be almost equally abundant (above 90% of the abundance of the fastest-growing species). It is not clear if the results would change significantly if potentially less abundant species would be classified as coexisting ones.<br /> 3) The majority of the results consider scenarios in which bacteria cannot disperse very effectively so bacterial dynamics is mostly driven by the growth of the initial populations at each region. Expanding on the analysis of higher dispersal rates would be valuable in order to analyze additional realistic scenarios of how bacteria grow and disperse in space.

Reviewer #1 (Public Review):

In this manuscript, Castrillon et al. analyze the heterogeneity of B cells exiting spontaneous germinal center reactions by scRNA-seq in a new mouse model of autoimmunity. In this model, they track the fate of wild-type Aid-Cre ERT2-EYFP B cells in the presence of 564 lgi B cells harboring a BCR specific for RNP. Throughout the manuscript, the authors compared the results obtained in the autoimmune model with those obtained after acute immunization with NP/OVA in Alum. They found extensive clonal overlap among dark/light zone germinal centers, memory B cells, and antibody-secreting cells (ASC). Within the ASC compartment, they found seven clusters. Through pseudotime analysis, they conclude the presence of two early ASC clusters, three intermediate ASC clusters, and two terminal ASC clusters. The two late ASCs have different patterns of gene expression (CD28, Itga4 among them), isotype expression (ASC_Late_1 mostly class-switched while ASC_Late_2 mostly IgM), and potentially different antibody-secreting capacity and metabolic program based on Ig counts and OXPHOS signature. Regarding memory B cells, they found four clusters of memory B cells with similar isotype expression (except for MemB2 which expresses more IgM) but different gene expression patterns (CD83, Fcrl5, Vim, Fcer2a). Finally, the authors found that FCRL5+ and CD23+ memory B cells are located in different areas of the spleen based on confocal microscopy analysis and their accessibility to blood after anti-CD45 iv administration. The data provided by the authors are very attractive and interesting. Yet, I found that the manuscript over relies on scRNA-seq. It will be important that authors back up some of their conclusions made from the scRNA-seq analysis with functional experiments, like measuring the differential antibody-secreting capacity of both terminal ASC subsets or profiling their metabolic status through one of the many metabolic techniques available.

Reviewer #1 (Public Review):

This manuscript reports new findings about the role of the glutamate transporter EAAC1 in controlling neural activity in the striatum. The significance is two-fold - it addresses gaps in knowledge about the functional significance of EAAC1, as well as provides a potential explanation for how EAAC1 mutations contribute to striatal hyperexcitability and OCD-associated behaviors. The manuscript is clearly presented, and the well-designed experiments are rigorously performed and analyzed. The main results showing that EAAC1 deletion increases the dendritic arbor of MSN D1 neurons and increases excitatory synaptic connectivity, as well as reduces D1-to-D1 mediated IPSCs are convincing. These results clearly demonstrate that EAAC1 deletion can alter excitatory and inhibitory synaptic function. Modelling the potential consequences for these changes on D1 MSN neural activity, and the behavior changes are interesting. Minor weaknesses include incomplete support for the conclusions about how EAAC1 regulates GABAergic transmission.

Reviewer #1 (Public Review):

This manuscript made use of a biologically realistic neuronal network model of cortico-basal ganglia-thalamic (CBGT) circuits and a cognitive drift-diffusion model (DDM) to account for both behavioural and functional neuroimaging (fMRI) data and to understand how change in reward contingency in the environment can affect different decision dynamics. They found that the rate of evidence accumulation was most affected, allowing explorative behaviour with a lower drift rate during likely contingency change and exploitative behaviour with a higher drift rate when contingency was likely similar. The multi-pronged approach presented in the manuscript is commendable. The biophysical model was sufficiently realistic with varying ramping firing rates of spiny projection neurons linked to the varying drift rates in the DDM. However, there are a few concerns regarding this work.

The model's cortical neurons had no contralateral encoding, unlike their neuroimaging data. Another concern with this work is that it was unclear why the spiking neuronal network model with so many model parameters was used to account for coarse-scale fMRI data - a simple firing-rate neural population model would perhaps do the work. Moreover, the activity dynamics of the fMRI were not shown. It would have been more rigorous to show the fMRI (BOLD) signals in different (particularly CBGT) brain regions and compare that with the CBGT model simulations.

The association between classier uncertainty and drift rate (by participants) was an order of magnitude difference between the simulated and actual participants (compare Figure 2E with Figure 4B). There was also a weak effect on human reaction times (Supp. Fig. 2).

There were only 4 human participants that performed the experiment - the results would perhaps be better with more human participants.

For such a complex biophysical computational model, there could perhaps have been more model predictions provided.

Overall, this work is interesting and could potentially be a good contribution in the area of computational modelling and neuroscience of adaptive choice behaviour.

Reviewer #1 (Public Review):

In this manuscript, Modi et al present a novel method to analyze brain oscillations. Traditional approaches are typically based on analyzing spectral features on individual oscillations (univariate methods) or the power and phase relationship between two oscillations (bivariate methods). The authors take a different, multivariate, approach to simultaneously analyze interactions between multiple oscillations. This is a better way to study dynamics interactions in a complex system than the more traditional 'reductionist' approach and, so far, few methods exist that allow such multivariate analysis of neural oscillations. The method is well demonstrated in the paper, including several application cases. Several aspects of the results need to be better characterized, a clear discussion of the caveats and limitations of the method is lacking and the advantages over existing methods need to be outlined more clearly. Provided these issues are corrected I believe this would be an important contribution to the field that may have multiple applications.

Reviewer #1 (Public Review):

This manuscript by Bohannon et al. continues a line of work from the Larsson laboratory with fundamental contributions describing the effects of polyunsaturated fatty acids (PUFAs) on the cardiac delayed rectifier potassium channel (IKs) formed by Kv7.1 and KCNE1 heteromers. Although the activating effect of PUFAs on these specific channels has been previously described, the authors now present a novel finding related to PUFAs containing large aromatic tyrosine head groups, showing significant activation effects on IKs, larger than other PUFAs previously studied. A combination of site-directed mutagenesis, electrophysiological and pharmacological approaches are used to dissect the different molecular mechanisms and sites involved in the functional interactions. The main conclusions are: 1) PUFA analogues with Tyr head groups are strong activators of the cardiac IKs channel by action on two previously described mechanisms: left-shift of the voltage-activation curve (by interaction with the voltage-sensor region of Kv7.1); and increased Gmax (by interacting with the pore region). 2) the underlying molecular interactions between PUFA and Kv7.1 are not cation-pi, as shown by the lack of effect of different chemical variations that disrupt the electrostatic surface potential. 3) the presence of electronegative groups on the aromatic ring favors increases in the maximal conductance. 4) the generation of a hydrogen bond with the -OH on the Tyr group seems to selectively impact on IKs voltage dependence of activation. 4) Kv7.1 sites involved in interactions with aromatic PUFAs are similar to the ones previously described for non-aromatic PUFAS, that is: R231 in S4 and K326 in S6. 5) residue T224 is newly identified as a potential site forming a hydrogen bond between the Tyr in the aromatic PUFA and Kv7.1.

The manuscript is very well written and structured. The experiments are solid and lead to mostly well-grounded conclusions. There are some aspects that would benefit from some clarification, which are mainly related to the different effects of the aromatic PUFA variants on IKs voltage dependence and/or conductance.

Reviewer #1 (Public Review):

In this study the authors investigate whether a presumably allosteric P2RX7 activating compound that they previously discovered reduces fibrosis in a bleomycin mouse model. They chose this particular model as publicly available mRNA data indicate that the P2XR7 pathway is downregulated in idiopathic pulmonary fibrosis patients compared to control individuals. The authors first demonstrate that two proxies of lung damage, Ashcroft score and collagen fibers, are significantly reduced in the bleomycin model on HEI3090 treatment. Additional data implicate specific immune cell infiltrates and cytokines, namely inflammatory macrophages and damped release of IL-17A, as potential mechanistic links between their compound and reduced fibrosis. Finally, the researchers transplant splenocytes from WT, NLRP3-KO, and IL-18-KO mice into animals lacking the P2XR7 receptor to specifically ascertain how the transplanted splenocytes, which are WT for P2XR7 receptor, respond to HEI3090 (a P2XR7 agonist). Based on these results, the authors conclude that HEI3090 enhanced IL-18 production through the P2XR7-NLRP3 inflammasome axis to dampen fibrosis.

These findings could be interesting to the field, as there are conflicting results as to whether NLRP3 activation contributes to fibrosis and if so, at what stage(s) (e.g., acute damage phase versus progression). However, major weaknesses of the study include inconsistent and small effect sizes in key outcomes used to measure fibrosis, small animal cohorts that do not empower results, and lack of key experimental controls. For example, damage indicators for the vehicle-treated mice transplanted with splenocytes of various genetic background are markedly different, and there are no statistical tests of these effects because the data are presented as separate graphs. Moreover, the fundamental assumption that HEI3090 acts specifically through the P2XR7 pathway in this model is questionable, as P2XR7 knockout mice are not included in the initial key experiments. These issues must be addressed as stimulating an inflammasome response might lead to pathogenic inflammation, which could counterproductively exacerbate fibrosis in the clinic and harm people.

Experimental concerns:

1. Ashcroft method quantification throughout is outdated and prone to bias. The methods describing quantification are lacking, and only include a citation: there should be mention of researcher blinding, etc. In general, please re-quantify using an automated classifier, and consider staining for additional markers of lung damage that are appropriate in the field.

2. For Figure 2, P2XR7 knockout mice, and an additional P2XR7 activator, should be included (e.g, A74003, AZ10606120, others), to support the hypothesis that HEI3090 acts through this pathway to alleviate fibrosis. Moreover, these data are especially important as the author's conclusions are directly opposed to a previous study demonstrating that the P2XR7 receptor is required for inflammation/fibrosis in this model system (PMID: 20522787). Two-way ANOVA or similar statistical tests on all groups should be examined to see whether genetic knockout of this DAMP receptor alone is protective or exacerbates fibrosis (e.g., comparing the vehicle-alone groups), and whether compounds exert a specific effect through this receptor.

3. Fig. 3A: Please show the individual IFN/IL-17A plots in the supplement, as a ratiometric result might mask variance. Moreover, please conduct a statistical test for the outlier in the HEI3090 condition (to potentially remove it), as this sole data point might skew the entire mean, causing the observed statistical difference between means despite a very modest change. If the results are still significant, please comment on effect size.

4. Fig. 3: How is IL-17A measured and what is the abbreviation GMFI?

5. Fig. 3E: It's unclear how the left and right figures align-it looks like the gates are 45.8 % and 25 %, respectively, but the means on the right are between 2-3%. Also, is this effect size (2 versus 3 %) significant biologically?

6. For Figure 4B-G, the Ashcroft scores for the vehicle mice treated with HEI3090 are at entirely different starting points following adoptive transfer of cells with different genetic background. In Fig. 1, WT mice have starting scores of around 3 following the induction of fibrosis, with a modest decrease of about 0.8 following HEI3090 treatment. Here, there is a much greater effect of the genetic background itself rather than the treatment, with the IL-18 knockout mice having a much lower baseline "vehicle" score (~1) compared to Fig. 1F (both of which are 14 day treatments). In fact, adoptive transfer of WT splenocytes start at a baseline of 1.8 here, which is much lower than Fig. 1F, and NLRP3-KO splenocytes score nearly the same as Fig. 1F following BLM treatment, with a modest reduction following treatment with HEI3090. Please analyze all of these groups together with appropriate multiple hypothesis testing to examine the effect of the genetic background, and please comment on why IL-18-knockout splenocytes might be protective at vehicle baseline while NLRP3-knockout splenocytes might exacerbate the phenotype at vehicle baseline.

7. The variance on Supplemental Figure 5C is quite large. These data have a decrease in mean Ashcroft score between untreated and HEI3090 treatment of around 0.8, which is similar to the WT mice in Figure 1. This is very concerning, as the underlying assumption is that KO of the protein required for HEI3090's on-target effect would completely ablate response, and this would be required for the subsequent adoptive transfer experiments in Figure 4. Please conduct power analysis, comment, and provide additional evidence (other than Ashcroft score).

8. Figure 4: Should quantify collagen fibers or have an additional quantitative metric for lung damage, as in Fig. 2C/J.

9. Figure 4: Should group the quantification of C/E/G and perform a 2-way Anova to assess effects of genetic background versus treatment.

10. Fig. 4H, Supplemental Fig. 6D: Is it reasonable to expect differences in IL-1beta and IL-18 in sera compared to in lung tissue itself?

Reviewer #1 (Public Review):

In this study, Satake and colleagues endeavored to explore the rates and patterns of somatic mutations in wild plants, with a focus on their relationship to longevity. The researchers examined slow- and fast-growing tropical tree species, demonstrating that slow-growing species exhibited five times more mutations than their fast-growing counterparts. The number of somatic mutations was found to increase linearly with branch length. Interestingly, the somatic mutation rate per meter was higher in slow-growing species, but the rate per year remained consistent across both species. A closer inspection revealed a prevalence of clock-like spontaneous mutations, specifically cytosine-to-thymine substitutions at CpG sites. The author suggested that somatic mutations were identified as neutral within an individual, but subject to purifying selection when transmitted to subsequent generations. The authors developed a model to assess the influence of cell division on mutational processes, suggesting that cell-division independent mutagenesis is the primary mechanism.

The authors have gathered valuable data on somatic mutations, particularly regarding differences in growth rates among trees. Their meticulous computational analysis led to fascinating conclusions, primarily that most somatic mutations accumulate in a cell-division independent manner. The discovery of a molecular clock in somatic mutations significantly advances our comprehension of mutational processes that may generate genetic diversity in tropical ecosystems. The interpretation of the data appears to be based on the assumption that somatic mutations can be effectively transmitted to the next generation unless negative selection intervenes. However, accumulating evidence suggests that plants may also possess "effective germlines," which could render the somatic mutations detected in this study non-transmittable to progeny. Incorporating additional analyses/discussion in the context of plant developmental biology, particularly recent studies on cell lineage, could further enhance this study.

Specifically, several recent studies address the topics of effective germline in plants. For instance, Robert Lanfear published an article in PLoS Biology exploring the fundamental question, "Do plants have a segregated germline?" A study in PNAS posited that "germline replications and somatic mutation accumulation are independent of vegetative life span in Arabidopsis." A phylogenetic-based analysis titled "Rates of Molecular Evolution Are Linked to Life History in Flowering Plants" discovered that "rates of molecular evolution are consistently low in trees and shrubs, with relatively long generation times, as compared with related herbaceous plants, which generally have shorter generation times." Another compelling study, "The architecture of intra-organism mutation rate variation in plants," published in PLoS Biology, detected somatic mutations in peach trees and strawberries. Although some of these studies are cited in the current work, a deeper examination of the findings in relation to the existing literature would strengthen the interpretation of the data.

Reviewer #1 (Public Review):

The manuscript by Hayes et al. explored the potential of combining chromosomal instability with macrophage phagocytosis to enhance tumor clearance of B16-F10 melanoma. However, the manuscript suffers from substandard experimental design, some contradictory conclusions, and a lack of viable therapeutic effects.

The authors suggest that early-stage chromosomal instability (CIN) is a vulnerability for tumorigenesis, CD47-SIRPa interactions prevent effective phagocytosis, and opsonization combined with inhibition of the CD47-SIRPa axis can amplify tumor clearance. While these interactions are important, the experimental methodology used to address them is lacking.

Reviewer #1 (Public Review):

The study by Ding et al demonstrated that microbial metabolite I3A reduced western diet induced steatosis and inflammation mice. They showed that I3A mediates its anti-inflammatory activities through AMP-activated protein kinase (AMPK)-dependent manner in macrophages. Translationally, they proposed that I3A could be a potential therapeutic molecule in preventing the progression of steatosis to NASH.

Major strengths<br /> • Authors clearly demonstrated that the Western Diet (WD)-induced steatosis and I3A treatment reduced steatosis and inflammation in pre-clinical models. Data clearly supports these statements.<br /> • I3A treatment rescued WD-altered bile acids as well partially rescued the metabolome, proteome in the liver.<br /> • I3A treatment reduced the levels of enzymes in fatty acid transport, de novo lipogenesis and β-oxidation<br /> • I3A mediates its anti-inflammatory activities through AMP-activated protein kinase (AMPK)-dependent manner in macrophages.

Minor Weakness<br /> Although data strongly support the notion that I3A reduced WD-induced steatosis and I3A treatment reduced steatosis and inflammation, the following concerns need to be addressed.<br /> • Authors suggested that I3A anti-inflammatory activities do not require AhR by using AhR-inhibitor in RAW cell lines. In the literature, studies do show that RAW cells do respond to AhR ligands such as TCDD and FICZ.<br /> • AhR-dependency needs to be confirmed by bone marrow derived macrophages isolated from AhR+/+ and AhR-/- or siRNA/ShRNA knockdown experiments.<br /> • Utilization of known AhR ligands as controls will strengthen the interpretation of the conclusions.

Reviewer #1 (Public Review):

This is an interesting study by Pinos and colleagues that examines the effect of beta carotene on atherosclerosis regression. The authors have previously shown that beta carotene reduces atherosclerosis progress and hepatic lipid metabolism, and now they seek to extend these findings by feeding mice a diet with excess beta carotene in a model of atherosclerosis regression (LDLR antisense oligo plus Western diet followed by LDLR sense oligo and chow diet). They show some metrics of lesion regression are increased upon beta carotene feeding (collagen content) while others remain equal to normal chow diet (macrophage content and lesion size). These effects are lost when beta carotene oxidase (BCO) is deleted. The study adds to the existing literature that beta carotene protects from atherosclerosis in general, and adds new information regarding regulatory T-cells. However, the study does not present significant evidence about how beta-carotene is affecting T-cells in atherosclerosis. For the most part, the conclusions are supported by the data presented, and the work is completed in multiple models, supporting its robustness. However there are a few areas that require additional information or evidence to support their conclusions and/or to align with the previously published work.

Specific additional areas of focus for the authors:<br /> The premise of the story is that b-carotene is converted into retinoic acid, which acts as a ligand of the RAR transcription factor in T-regs. The authors measure hepatic markers of retinoic acid signaling (retinyl esters, Cyp26a1 expression) but none of these are measured in the lesion, which calls into question the conclusion that Tregs in the lesion are responsible for the regression observed with b-carotene supplementation.

There does not appear to be a strong effect of Tregs on the b-carotene induced pro-regression phenotype presented in Figure 5. The only major CD25+ cell dependent b-carotene effect is on collagen content, which matches with the findings in Figure 1 +2. This mechanistically might be very interesting and novel, yet the authors do not investigate this further or add any additional detail regarding this observation. This would greatly strengthen the study and the novelty of the findings overall as it relates to b-carotene and atherosclerosis.

The title indicates that beta-carotene induces Treg 'expansion' in the lesion, but this is not measured in the study.

Reviewer #1 (Public Review):

In this study, Kim et al. investigated the mechanism by which uremic toxin indoxyl sulfate (IS) induces trained immunity, resulting in augmented pro-inflammatory cytokine production such as TNF and IL-6. The authors claim that IS treatment induced epigenetic and metabolic reprogramming, and the aryl hydrocarbon receptor (AhR)-mediated arachidonic acid pathway is required for establishing trained immunity in human monocytes. They also demonstrated that uremic sera from end-stage renal disease (ESRD) patients can generate trained immunity in healthy control-derived monocytes.

These are interesting results that introduce the important new concept of trained immunity and its importance in showing endogenous inflammatory stimuli-induced innate immune memory. Additional evidence proposing that IS plays a critical role in the initiation of inflammatory immune responses in patients with CKD is also interesting and a potential advance of the field. This study is in large part well done, but some components of the study are still incomplete and additional efforts are required to nail down the main conclusions.

Specific comments:<br /> 1) Of greatest concern, there are concerns about the rigor of these experiments, whether the interpretation and conclusions are fully supported by the data. 1) Although many experiments have been sporadically conducted in many fields such as epigenetic, metabolic regulation, and AhR signaling, the causal relationship between each mechanism is not clear. 2) Throughout the manuscript, no distinction was made between the group treated with IS for 6 days and the group treated with the second LPS (addressed below). 3) Besides experiments using non-specific inhibitors, genetic experiments including siRNA or KO mice should be examined to strengthen and justify central suggestions.<br /> 2) The authors showed that IS-trained monocytes showed no change in TNF or IL-6, but increased the expression levels of TNF and IL-6 in response to the second LPS (Fig. 1B). This suggests that the different LPS responsiveness in IS-trained monocytes caused altered gene expression of TNF and IL-6. However, the authors also showed that IS-trained monocytes without LPS stimulation showed increased levels of H3K4me3 at the TNF and IL-6 loci, as well as highly elevated ECAR and OCR, leading to no changes in TNF and IL-6. Therefore, it is unclear why or how the epigenetic and metabolic states of IS-trained monocytes induce different LPS responses. For example, increased H3K4me3 in HK2 and PFKP is important for metabolic rewiring, but why increased H3K4me3 in TNF and IL6 does not affect gene expression needs to be explained.<br /> 3) The authors used human monocytes cultured in human serum without growth factors such as MCSF for 5-6 days. When we consider the short lifespan of monocytes (1-3 days), the authors need to explain the validity of the experimental model.<br /> 4) The authors' ELISA results clearly showed increased levels of TNF and IL-6 proteins, but it is well established that LPS-induced gene expression of TNF and IL-6 in monocytes peaked within 1-4 hours and returned to baseline by 24 hours. Therefore, authors need to investigate gene expression at appropriate time points.<br /> 5) It is a highly interesting finding that IS induces trained immunity via the AhR pathway. The authors also showed that the pretreatment of FICZ, an AhR agonist, was good enough to induce trained immunity in terms of the expression of TNF and IL-6. However, from this point of view, the authors need to discuss why trained immunity was not affected by kynurenic acid (KA), which is a well-known AhR ligand accumulated in CKD and has been reported to be involved in innate immune memory mechanisms (Fig. S1A).<br /> 6) The authors need to clarify the role of IL-10 in IS-trained monocytes. IL-10, an anti-inflammatory cytokine that can be modulated by AhR, whose expression (Fig. 1E, Fig. 4D) may explain the inflammatory cytokine expression of IS-trained monocytes.<br /> 7) The authors need to show H3K4me3 levels in TNF and IL6 genes in all conditions in one figure. (Fig. 2B). Comparing Fig. 2B and Fig. S2B, H3K4me3 does not appear to be increased at all by LPS in the IL6 region.<br /> 8) The authors need to address the changes of H3K4me3 in the presence of MTA.<br /> 9) Interpretation of ChIP-seq results is not entirely convincing due to doubts about the quality of sequencing results. First, authors need to provide information on the quality of ChIP-seq data in reliable criteria such as Encode Pipeline. It should also provide representative tracks of H3K4me3 in the TNF and IL-6 genes (Fig. 2F). And in Fig. 2F, the author showed the H3K4me3 track of replicates, but the results between replicates were very different, so there are concerns about reproducibility. Finally, the authors need to show the correlation between ChIP-seq (Fig. 2) and RNA-seq (Fig. 5).<br /> 10) AhR changes in the cell nucleus should be provided (Fig. 4A).<br /> 11) Do other protein-bound uremic toxins (PBUTs), such as PCS, HA, IAA, and KA, change the mRNA expression of ALOX5, ALOX5AP, and LTB4R1? In the absence of genetic studies, it is difficult to be certain of the ALOX5-related mechanism claimed by the authors.<br /> 12) Fig.6 is based on the correlated expression of inflammatory genes or AA pathway genes. It does not clarify any mechanisms the authors claimed in the previous figures.

Reviewer #1 (Public Review):

The manuscript by Park et. al. examines the interaction of macrophages with SARS-CoV-2 spike protein and subsequent inflammatory reactions. The authors demonstrate that following intranasal delivery of spike it rapidly accumulates in alveolar macrophages. Inflammation associated with internalized spike recruits neutrophils to the lung, where they undergo a cell death process consistent with NETosis. The authors demonstrate that modifications spike to contain high mannose reduces uptake of spike protein and limits the inflammation induced. This finding could have implications on vaccine development, as vaccines containing modified spike could be safer and better tolerated.

The authors use a number of different techniques, including in vivo modeling, imaging, human and murine systems to interrogate their hypotheses. These systems provide robust supporting information for their conclusions. There are two key aspects from the current manuscript which would add key evidence. The authors suggest that neutrophils exposed to spike protein undergo a process of NETosis. To confirm this hypothesis inhibitors of NETosis should be used to demonstrate that the cell death is prevented. Additionally, vaccination of a murine model with the modified spike protein would add additional support to the conclusion that modified spike protein would be less inflammatory while maintaining its utility as a vaccine antigen.

Reviewer #1 (Public Review):

In the present work the authors explore the molecular driving events involved in the establishment of constitutive heterochromatin during embryo development. The experiments have been carried out in a very accurate manner and clearly fulfill the proposed hypotheses.

Regarding the methodology, the use of: i) an efficient system for conversion of ESCs to 2C-like cells by Dux overexpression; ii) a global approach through IPOTD that reveals the chromatome at each stage of development and iii) the STORM technology that allows visualization of DNA decompaction at high resolution, helps to provide clear and comprehensive answers to the conclusion raised.

The contribution of the present work to the field is very important as it provides valuable information on chromatin-bound proteins at key stages of embryonic development that may help to understand other relevant processes beyond heterochromatin maintenance.

The study could be improved through a more mechanistic approach that focuses on how SMARCAD1 and TOPBP1 cooperate and how they functionally connect with H3K9me3, HP1b and heterochromatin regulation during embryonic development. For example, addressing why topoisomerase activity is required or whether it connects (or not) to SWI/SNF function and the latter to heterochromatin establishment, are questions that would help to understand more deeply how SMARCAD1 and TOPBP1 operate in embryonic development.

Reviewer #1 (Public Review):

The paper from Hsu and co-workers describes a new automated method for analyzing the cell wall peptidoglycan composition of bacteria using liquid chromatography and mass spectrometry (LC/MS) combined with newly developed analysis software. The work has great potential for determining the composition of bacterial cell walls from diverse bacteria in high-throughput, allowing new connections between cell wall structure and other important biological functions like cell morphology or host-microbe interactions to be discovered. In general, I find the paper to be well written and the methodology described to be useful for the field. However, there are areas where the details of the workflow could be clarified. I also think the claims connecting cell wall structure and stiffness of the cell surface are relatively weak. The text for this topic would benefit from a more thorough discussion of the weak points of the argument and a toning down of the conclusions drawn to make them more realistic.

Specific points:

1) It was unclear to me from reading the paper whether or not prior knowledge of the peptidoglycan structure of an organism is required to build the "DBuilder" database for muropeptides. Based on the text as written, I was left wondering whether bacterial samples of unknown cell wall composition could be analyzed with the methods described, or whether some preliminary characterization of the composition is needed before the high-throughput analysis can be performed. The paper would be significantly improved if this point were explicitly addressed in the main text.

2) The potential connection between the structure of different cell walls from bifidobacteria and cell stiffness is pretty weak. The cells analyzed are from different strains such that there are many possible reasons for the change in physical measurements made by AFM. I think this point needs to be explicitly addressed in the main text. Given the many possible explanations for the observed measurement differences (lines 445-448, for example), the authors could remove this portion of the paper entirely. Conclusions relating cell wall composition to stiffness would be best drawn from a single strain of bacteria genetically modified to have an altered content of 3-3 crosslinks.

Reviewer #1 (Public Review):

In this manuscript, "Diminishing neuronal acidification by channelrhodopsins with low proton conduction" by Hayward and colleagues, the authors report on the properties of novel optogenetic tools, PsCatCh2.0 and ChR2-3M, that minimize photo-induced acidification. The authors point out that acidification is an undesirable side-effect of many optogenetic approaches that could be minimized using the new tools. ChRs are known to acidify cells, while Arch are known to alkalize cells. This becomes particularly important when optical stimulation is prolonged and pH changes can become significant. pH is known to affect neuronal excitability, vesicular release, and more. To develop novel optogenetic tools with minimal proton conductances, the authors combined channelrhodopsin stimulation with a red-shifted pH sensor to measure pH during optogenetic stimulation. The authors report that optogenetic activation of CheRiff caused slow cellular acidification. 150 seconds of illumination caused a 3-fold increase in protons or approximately a 0.6 unit pH change that returned to baseline very slowly. They also found that pH changes occurred more rapidly, and recovered more rapidly, in dendrites. The authors go on to robustly characterize PsCatCh2.0 and ChR2-3M in terms of their proton conductances, photocurrent, kinetics, and more. They convincingly show that these constructs induced reduced acidification while maintaining robust photocurrents. In sum, this manuscript shows important findings that convincingly characterizes 2 optogenetic tools that have reduced pH artifacts that may be of broad interest to the field of neuroscience research and optogenetic therapies.

Reviewer #1 (Public Review):

The blood-brain barrier separates neural tissue from blood-borne factors and is important for maintaining central nervous system health and function. Endothelial cells are the site of the barrier. These cells exhibit unique features relative to peripheral endothelium and a unique pattern of gene expression. There remains much to be learned about how the transcriptome of brain endothelial cells is established in development and maintained throughout life.

The manuscript by Sadanandan, Thomas et al. investigates this question by examining transcriptional and epigenetic changes in brain endothelial cells in embryonic and adult mice. Changes in transcript levels and histone marks for various BBB-relevant transcripts, including Cldn5, Mfsd2a and Zic3 were observed between E13.5 and adult mice. To perform these experiments, endothelial cells were isolated from E13.5 and adult mice, then cultured in vitro, then sequenced. This approach is problematic. It is well-established that brain endothelial cells rapidly lose their organotypic features in culture (https://elifesciences.org/articles/51276). Indeed, one of the primary genes investigated in this study, Cldn1, exhibits very low expression at the transcript level in vivo but is strongly upregulated in cultured ECs.

(https://elifesciences.org/articles/36187 ; https://markfsabbagh.shinyapps.io/vectrdb/)

This undermines the conclusions of the study.

An additional concern is that for many experiments, siRNA knockdowns are performed without validation of the efficacy of the knockdown.

Some experiments in the paper are promising, however. For example, the knockout of HDAC2 in endothelial cells resulting in BBB leakage was striking. Investigating the mechanisms underlying this phenotype in vivo could yield important insights.

Reviewer #1 (Public Review):

Martinez-Gutierrez and colleagues presented a timeline of important bacteria and archaea groups in the ocean and based on this they correlated the emergence of these microbes with GOE and NOE, the two most important geological events leading to the oxygen accumulation of the Earth. The whole study builds on molecular clock analysis, but unfortunately, the clock analysis contains important errors in the calibration information the study used, and is also oversimplified, leaving many alternative parameters that are known to affect the posterior age estimates untested. Therefore, the main conclusion that the oxygen availability and redox state of the ocean is the main driver of marine microbial diversification is not convincing.

Basically, what the molecular clock does is to propagate the temporal information of the nodes with time calibrations to the remaining nodes of the phylogenetic tree. So, the first and the most important step is to set the time constraints appropriately. But four of the six calibrations used in this study are debatable and even wrong.

(1) The record for biogenic methane at 3460 Ma is not reliable. The authors cited Ueno et al. 2006, but that study was based on carbon isotope, which is insufficient to demonstrate biogenicity, as mentioned by Alleon and Summons 2019.

(2) Three calibrations at Aerobic Nitrososphaerales, Aerobic Marinimicrobia, and Nitrite oxidizing bacteria have the same problem - they are all assumed to have evolved after the GOE where the Earth started to accumulate oxygen in the atmosphere, so they were all capped at 2320 Ma. This is an important mistake and will significantly affect the age estimates because maximum constraint was used (maximum constraint has a much greater effect on age estimates and minimum constraint), and this was used in three nodes involving both Bacteria and Archaea. The main problem is that the authors ignored the numerous evidence showing that oxygen can be produced far before GOE by degradation of abiotically-produced abundant H2O2 by catalases equipped in many anaerobes, also produced by oxygenic cyanobacteria evolved at least 500 Ma earlier than the onset of GOE (2500 Ma), and even accumulated locally (oxygen oasis). It is well possible that aerobic microbes could have evolved in the Archaean.

Once the phylogenetic tree is appropriately calibrated with fossils and other time constraints, the next important step is to test different clock models and other factors that are known to significantly affect the posterior age estimates. For example, different genes vary in evolutionary history and evolutionary rate, which often give very different age estimates. So it is very important to demonstrate that these concerns are taken into account. These are done in many careful molecular dating studies but missing in this study.

https://www.frontiersin.org/articles/10.3389/fpsyg.2020.01358/full

The Pastoral Origin of Semiotically Functional Tonal Organization of Music Nikolsky, A. 2020

Reviewer #1 (Public Review):

The paper describes a robotic system that can be used for prolonged recording of forced activity in crawling Drosophila larvae. This is mostly intended to be a proof of principle description of a tool potentially useful for the community. The system - whose value lies completely in its reproducibility and adoption - is only superficially described in the paper, but a more detailed description is made available through Github, along with the software used for the collection and analysis of data.

There is good, convincing evidence this can work as some sort of "larval conveyor belt", used to artificially prolong food crawling behaviour in the animals. More could be said about the ecological implications of the assay (for instance: how relevant is it to an animal's natural behaviour? Does the system introduce artifactual distortions in the analysis, driven by the fact that animals crawl greater distances than they would normally crawl in nature? Will this extensive activity affect their development to pupation or adulthood?).

Reviewer #1 (Public Review):

This manuscript provides a structural analysis of bushy cells in the mouse cochlear nucleus. The analysis uses volume electron microscopy techniques to describe bushy cell-auditory nerve synapses and bushy cell dendrites. The analysis takes a morphological analysis of bushy cells to a new level, and the computational modeling is well done. The models are used to predict busy cell behavior, which leads to a major concern. The authors make reasonable assertions, but all of these need to be validated by electrophysiological studies before they can be treated as fact. Instead, they should be treated as predictions. For example, in the conclusions from the model section, that endbulb size does not strictly predict synaptic efficacy should be modified from an assertion to a prediction.

Reviewer #1 (Public Review):

Ichinose et al., utilize a mixture of cultured hippocampal neurons and non-neuronal cells to identify the role of the transmembrane protein teneurin-2 (TEN-2) in the formation of inhibitory synapses along the dendritic shaft. First, they identify distinct clusters of gephyrin that are either actin-rich, microtubule-rich or contain neither actin nor microtubules and find that TEN-2 is enriched in microtubule-rich gephyrin clusters. This leads the authors to hypothesize that TEN-2 recruits microtubules (MTs) through the plus end binding protein EB1 when successfully matched with a pre-synaptic partner, and perform a variety of experiments to test this hypothesis. The authors then extend this finding to state quite strongly throughout the paper, including in the title, that TEN-2 acts as a signpost for the unloading of cargo from motor proteins without providing any supporting evidence. They use previous work to justify this conclusion, but without actual experiments to back up the claim, it seems like a reach.

The strength of the paper lies in the various lines of evidence that the authors employ to assess the role of TEN-2 in MT recruitment and synaptogenesis. They have also been very thorough in validating the expression and functionality of various knock-in constructs, knock-down vectors and antibodies that were generated during the study. However, there are some discrepancies in the findings that have not been addressed satisfactorily, as well as some instances where the data presented is not of sufficient quality to support the conclusions derived from them.<br /> 1. The emphasis placed on the clustering analysis presented in figure 1 and the two associated supplementary figures is puzzling, since the conclusion derived from the results presented would be that Neuroligin 2 (NLGN2) is the strongest candidate to test for a relationship to MT recruitment at inhibitory post synapses. Instead, the authors cite prior evidence to exclude NLGN2 from subsequent analysis and choose to focus on TEN2 instead.<br /> 2. It is difficult to reach the same conclusion as the authors from the images and intensity plot shown on Figure 2 E and F. While there seems to be an obvious reduction in expression levels between the TEN2N-L and TEN2TM constructs, neither seem to co-localize with EB1.<br /> 3. The authors mimic the activity of TEN-2 at the inhibitory post synapse in non-neuronal cells by immobilizing HA- tagged TEN constructs in COS-7 cells as a proxy for synaptic partner matching. Using this model, they find that by immobilizing TEN2N-L, which contains EB1 binding motifs, MTs are excluded from the cell periphery (Figure 3D). This contradicts their conclusion that MTs are recruited through EB1 by TEN-2 on synaptic partner matching. Later in the paper, when they use the same TEN2N-L construct as a dominant negative in neuronal cells, they find that MTs are recruited the membrane, even if TEN2N-L is not immobilized by synaptic partner matching (Figure 6C). Taken together, these findings call into question the sequence of events driven by TEN-2 during synaptogenesis.<br /> 4. It is unclear how the authors could conclude that TEN-2 is at the semi-periphery (?) of inhibitory post synapses from the STORM data that is presented in the paper. Figure 4D and 4F show comparisons of Bassoon and TEN-2 localization vs TEN-2 and gephyrin, but the image quality is not sufficient to adequately portray a strong distinction in the distance of center of mass, which is also only depicted for the TEN2-Gephyrin pair and not the TEN2-Bassoon pair in Figure 4J.<br /> 5. The authors do not satisfactorily explain why gephyrin appears to have completely disappeared in the TEN2N-L condition (Figure 6A), instead of appearing uniformly distributed as one would expect if MTs are indiscriminately recruited to the membrane by the dominant negative construct that remains unanchored.<br /> 6. In a similar critique to that of Figure 2E and F, the distinction that the authors wish to portray between the effect of TEN2TM and TEN2N-L constructs on EGFP-TEN-2 and MAP2 colocalization (Figure 6 E and F) appear to be driven by a difference in overall expression levels of EGFP-TEN2 rather that a true difference in localization of TEN-2 and MTs.

Reviewer #1 (Public Review):

Wu et al. sought to investigate the biological role of GPR110 in modulating hepatic lipid metabolism. The authors demonstrate a pathological role of GPR110 in promoting hepatic steatosis and generalized metabolic syndrome in a mouse model of diet-induced obesity. Furthermore, the authors identify enhanced SCD1 expression as an underlying mechanism promoting GPR110-induced metabolic dysfunction. Finally, the authors provide clinically relevant human data demonstrating a positive correlation between GPR110 expression and degree of hepatic steatosis. The strengths of this study include the rigorous design and execution of experiments, the utilization of gain and loss of function as well as pharmacological and genetic approaches, and the clinically relevant human data presented. The claims are supported by robust data. These findings have the potential to impact the field of metabolism in general, given their findings indicate targeting GPR110 can reverse diet induced obesity and metabolic syndrome. Only minor weaknesses were noted in regard to further interpretation of the data.

Reviewer #1 (Public Review):

The first defined that FAM76B inhibited the NF-κB-mediated inflammation by modulating translocation of hnRNPA2B1 to cytosol, where hnRNPA2B1 bound to IKK and released active NFkB that translocated into nuclear and initiated inflammation.

Reviewer #1 (Public Review):

The authors have investigated the effect of aerobic exercise on the decline in cerebral blood flow and cognitive function in old mice. Using appropriately two-photon microscopy and optical coherence tomography they found that aerobic exercise restored capillary blood flow and oxygenation in the white matter more than in the grey matter in old female mice. Interestingly, this aerobic exercise also ameliorated cognitive performance in these mice. The data obtained strongly supports the hypothesis and supports the conclusion of the study. Nevertheless, it would be important to compare the effects of aerobic exercise in old mice to its effects in young animals. It will be also interesting to know if the protective effect of exercise is similar in male mice.

This work brings new insights into the comprehension of the age-associated changes in cerebral microcirculation and in the protective effects of aerobic exercise.

Reviewer #1 (Public Review):

The manuscript by Huang, Li, et al. describes the identification of variants in the gene coding for p31 comet, a protein required for silencing the spindle assembly checkpoint or SAC, in women with recurrent pregnancy loss upon IVF. In three families mutations affecting splicing or expression of full-length protein were identified. The authors show that oocytes of the patients arrest in meiosis I, are most likely to fail to inactivate the SAC without a fully functional p31 comet. Indeed, the metaphase I arrest occurring in mouse oocytes upon overexpression of Mad2 can be rescued by overexpression of wild-type p31 comet, but not a truncated version. Injection of wt p31 comet into 6 human oocytes from one patient rescued the meiosis I arrest.

Main points:

The fact that inactivation of the SAC is required for anaphase I onset in human oocytes is not novel. Biallelic mutations of TRIP13 were shown to lead to the same phenotype (Zhang et al. Am J. Hum Gen., 2020).

No new mechanistic insights are obtained.

The authors propose a role for female fertility, however, also a male patient with a p31 comet variant is sterile.

The fact that the C-terminus of p31 comet is required for interaction with Mad2 and hence, turning off the SAC, is already known.

Reviewer #1 (Public Review):

This work reports an important demonstration of how to predict the mutational pathways to antimicrobial resistance (AMR) emergence, particularly in the enzyme DHFR (dihydrofolate reductase). Epistasis, or non-additive effects of mutations due to their background dependence, is a major confounding factor in the predictability of protein evolution, including proteins that confer antimicrobial resistance. In the first approach, they used the Rosetta to predict the mutant DHFR-drug binding affinity and the resulting selection coefficient, which then became inputs to a population genetics model. In the second approach, they use the observed clinical/environmental frequency of the variants to estimate the selection coefficient. Overall, this work is a compelling demonstration that a mechanistic model of the fitness landscape could recapitulate AMR evolution; however, considering that the number of mutations and pathways is small, a more compelling description of the robustness of the results and/or limitations of the model is needed.

Major strengths:<br /> 1. This is a compelling multi-disciplinary work that combines a mechanistic fitness landscape of DHFR (previously articulated in literature and cited by the authors), Rosetta to determine the biophysical effects of mutations, and a population genetics model.<br /> 2. The study takes advantage of extensive data on the clinical/environmental prevalence of DHFR mutations.<br /> 3. Provides a careful review of the surrounding literature.

Major weakness:<br /> 1. Considering that the number of mutations and pathways being recapitulated is rather small, I would suggest a more detailed description of the robustness of the results. For example:<br /> a. Please report the P-value for the correlation of the predicted DDG_{binding, theory} and DDG_{binding, experimental}. If interested in showing the correct assignment of mutational effects, perhaps use a contingency matrix to derive a P-value.<br /> b. Although the DDG_binding calculation in Rosetta seems to converge (Appendix figures 3 and 4), I do not think the DDG values before equilibration should be included in the final DDG estimate. In practice, there is a "burn in" number of runs where the force field optimizes the calculation to account for potential clashes in the structure, etc. This is particularly important since the starting structures are modeled from homology. Consequently, the distributions of DDG that include the equilibration runs are multimodal (Appendix figure 2), which means that calculating an average may be inappropriate.<br /> 2. The geographical areas over which the mutational pathways are independently estimated are not isolated, allowing for the potential that an AMR variant in one region arose due to "migration" from another area. For example, the S58R-S117N is the most frequent double mutant of PvDHFR in geographically proximate Southern/Southeastern Asia (Fig. 4). To a certain extent, similar mutational patterns occur for PfDHFR in Southern/Southeastern Asia (Fig. 3). Although accounting for mutant migration in the model may be beyond the scope of the study, a clear argument for the validity of the "isolated island" assumption is needed.

Reviewer #1 (Public Review):

This work develops new and improved methods for tracking and quantifying yeast cells in time-lapse microscopy. Overall, the manuscript presents exceedingly clever solutions to many practical data analysis problems that arise in microfluidics, some of which may be useful in other image analysis settings.

I find the manuscript is at times very dense and technical and is missing context for a general audience. Hard to know what are the most important contributions, and the authors assume the reader is familiar with many details of their previous work/field. Claims are made with little explanation, context or scientific logic.

Reviewer #1 (Public Review):

Extracellular vesicles (EVs) are emerging as important mediators of cell-to-cell signaling. In this paper the authors aim to demonstrate that Stranded at second (Sas), a Drosophila cell surface protein, binds to dArc1 and Ptp10D to mediate intercellular transport of dArc1 via EVs. dArc1 protein has been shown to form virus-like capsids that carry dArc1 mRNA from neurons to muscle, but little is known about this new intercellular communication pathway. Similarly, not much is known generally about how EVs are targeted to specific cell types, or how specific EV cargo can be delivered. Thus, this work is of interest to cell biologists and neuroscientists. However, the jumbled description of the results and general lack of rigor of experiments diminish the impact and interpretability of the conclusions. Moreover, almost all experiments rely on gain-of-function and over-expression of Sas, thus the relevance to normal physiological signaling is unclear.

Major strengths:<br /> 1. The data showing that Sas is released into EVs and delivered to cells is strong.<br /> 2. The EM data showing Sas localization to EVs is clear.

Major weaknesses:<br /> The description of the results omits some data in the figures and is not in a logical order. This made it hard to read and follow. There is also a lack of rigor and quantification in some experiments. Specifically:

1. Figure 2: Description of dArc1 putative capsids is absent from the results section (2f,g) until describing fig 4 data (line 362). Given that there is no immuno-EM labeling of dArc1 protein, it is not clear if Sas and dArc1 are localized to the same EVs. Nor is it clear if the double membrane EVs are actually EVs that contain capsids. Overall, the EM data lacks quantification. How many EVs on average show Sas labeling? How many EVs have double membranes? The dense protein staining surrounding EVs seems unusual, is this due to artifact of the purification? EV kits are generally non-specific and isolate non-EV membranes, corroboration using ultracentrifugation or size exclusion chromatography methods would be beneficial. SAS-FL overexpression results in more EVs, which confounds subsequent experiments suggesting that Sas targets EVs to specific cell types/regions.

2. Figure 3: There are no data showing the expression of Sas in SG cells using the GAL4 lines. Is this expression restricted to just SG cells? The results jump from a-b to f-g. c-e are out of order. The quantification in g should be broken into two and paired with the actual data (c-e, and f). It is not clear how the quantification in g was performed. How many WBs were analyzed? There seems to be a bubble in the first lane of f, which would preclude quantification. Why is d not quantified and there seems to be an overall increase in background staining in e that is not specific to discs. The source data files are not labelled and these data should be incorporated into annotated supplemental figures. Is transfer in a-b due to Ptp10D? How many WBs were quantified in g?

3. Figure 4: C and d, IP data has no inputs for IPs, no sizing markers, and no IgG controls for antibody specificity. These data would also be more convincing if done with FL Sas and included co-Ips from cell lysates.

4. In general, the WBs in the figures show very white backgrounds with high contrast, which suggests the images may have been manipulated. Total protein controls are also missing.

5. Figure 5: Ashley et al (Cell 2018) showed that dArc1 mRNA transfer required the 3'UTR so it is puzzling that the authors used heterologous UTRs. The results using FISH on endogenous dArc1 mRNA are dramatic. The authors should show definitively that their probe does not pick up over-expressed dArc1.

6. Many of the conclusions would be strengthened by the loss of function experiments, especially showing a requirement for Sas in dArc1 transfer.

Reviewer #1 (Public Review):

The authors of this manuscript address the question of whether vagal and sacral neural crest make distinct contributions to the enteric nervous system (ENS). The ENS regulates intestinal motility and many intestinal homeostatic functions; mutations in genes involved in ENS development lead to defects that can range from mild to catastrophic. The best studied of the ENS neuropathies is Hirschsprung disease, which is thought to result from failure of vagal neural crest cells to migrate properly into the distal intestine to differentiate into ENS neurons and glia. However, sacral neural crest cells are known to contribute to the distal ENS and have to migrate a considerably shorter distance. Thus, understanding whether there are distinct vagal and sacral contributions to the ENS provides insights into basic ENS biology as well as the basis of human disease. Previous transplantation and ablation studies have already revealed that vagal and sacral neural crest have differing ENS developmental potentials, although this has not been directly correlated with discrete cell types. Here the authors combine single cell RNA sequencing and a viral lineage tracing technique that is new to avians to gain insight into the different ENS cell types generated by vagal and sacral neural crest along the length of the intestine. They find that vagal and sacral neural crest exhibit distinct transcriptional profiles and contribute both similar and different progeny to the ENS. For example, both vagal and sacral crest contribute to progenitor cells, connective tissue and neurons, but most secretomotor neurons are vagal crest-derived whereas most adrenergic neurons and melanocytes in the distal intestine are sacral-crest derived. The authors also suggest a role of the local environment in determining the fate of vagal and sacral derivatives. The data presented in this manuscript provide a multitude of hypotheses about similarities and differences between vagal and sacral derived ENS cells. However, a shortcoming of the manuscript is that all of these hypotheses remain untested.

Reviewer #1 (Public Review):

In this project, the authors used a single-cell RNA sequencing technique, created a cell atlas of normal and diseased human anterior cruciate ligaments of 49,356 cells from 8 patients, explored the variations of the cell subtypes' spatial distributions, and found their associations with ligamental degeneration. Using the single-cell RNA sequencing data, the authors identified fibroblast subsets unique to normal and diseased tissues, revealed two processes of acute and chronic disease outcome in ligamental degeneration and found immune cell and stromal cell subclusters changed the extracellular matrix in ligament and contributed to the disease. Combined with spatial transcriptome sequencing, they found the spatial distribution of immune and stromal cells associated with the disease and demonstrated cell-cell communications among endothelial cells, macrophages, and fibroblasts.

Reviewer #1 (Public Review):

It has been previously shown that defective autophagy and disorganized microtubule network contribute to the pathogenesis of Duchenne muscular dystrophy (DMD). The authors previously reported that nitrite oxide synthase 2 (NOX2) regulates these alterations. It was also shown that acetylated tubulin facilitates autophagosome-lysosome fusion and thus autophagy. In the present study, the authors showed that autophagy is differentially regulated by redox and acetylation modifications in dystrophic mdx mice. The ablation of Nox2 in mdx mice activated the autophagosome maturation but not its fusion with the lysosome. On the other hand, the inhibition of histone acetylase 6 (HDAC6) restored microtubule acetylation, promoted autophagosome-lysosome fusion, and improved muscle function in mdx mice. The strength of this paper is the combination of different approaches to decipher the mechanism, including the evaluation of the level and interaction of several proteins involved in the maturation of autophagosomes and in the fusion between autophagosomes and lysosomes.

This study reveals an important molecular mechanism by which increasing microtubule acetylation improves autophagy and muscle function in dystrophic mice. This has a translational impact on several diseases in which autophagy is impaired. The improvement of autophagosome-lysosome fusion with HDAC6 inhibitor is supported by several data, but some parts merit further analysis:

1) To add appropriate controls (e.g. without antibodies) to support protein-protein interaction for all co-immunoprecipitation assays.<br /> 2) The simple evaluation of the protein levels of p62 and LC3-II is not sufficient to claim autophagy improvement after HDAC6 inhibition. It would be good to evaluate the autophagic flux in vivo in all groups of mice (to treat the mice with or without autophagy inhibitor and evaluate whether the difference in the level of LC3-II between the two conditions is higher with HDAC6 inhibitor than without in the mdx mice).

Reviewer #1 (Public Review):

The purpose of this study was to investigate within the diverse Multiethnic Cohort (MEC) study on how COVID-19 impacted access to cancer screenings and treatment through a cross-sectional survey in this study population.

Major strengths were leveraging existing participants in a cohort study that contained a diverse population. The MEC cohort participants have been studied since the 90's. The investigators used a well-designed survey and performed analysis on responses focused on cancer screening attendance. Weaknesses of this study are low response rates that make the results not generalizable to other populations, especially younger populations, and possible bias of specific types of individuals responding.

This study found associations with racial/ethnic, age, comorbidities, and education to be key factors associated with cancer-related screening and healthcare seeking during the COVID-19 pandemic.

Whether the associations observed by the investigators would remain over time is unknown, as health care seeking changed as the pandemic evolved and prevention tools (including mass testing and vaccination) became available. It is important to note that this is a snapshot in time, so while it is informative, it will be important to monitor whether certain groups/populations that may be at high risk for cancer may need to be targeted for early diagnosis and screening.

Reviewer #1 (Public Review):

This study provided evidence to interpret and understand the aging and developmental processes in children. The main strength of the study is it measures a set of biological age measures and a set of developmental measures, thus providing multi-faceted evidence to explain the associations between aging and development in children. The main weakness of this study is that how to measure and test the aging hypothesis of "a buildup of biological capital model" and "wear and tear" is not well-explained. Why the observed associations between biological age measures and developmental measures could support the aforementioned aging theories?

1. Abstract - conclusion: The aging hypothesis of "a buildup of biological capital model" and "wear and tear" were mentioned in the conclusion without an explanation of these theories in the previous section. Readers who are not experts in the field may not understand the logic.<br /> 2. Result - Biological age marker performance: the correlation between transcriptome age and chronological age is very strong (r =0.94). I am afraid that very little age-independent information could be captured by the transcriptome age. Is it possible to down-regulate the age dependency of the transcriptome age in the training process?<br /> 3. The study population comes from several cohorts, which might influence the results. How the cohort effects were controlled for in the analyses?<br /> 4. Figure 3 only showed the number of p values. Can the author also provide the number of point estimates and 95% confidence intervals, perhaps in the supplemental table?

Reviewer #1 (Public Review):

In the manuscript, titled "Comparative single-cell profiling reveals distinct cardiac resident macrophages essential for zebrafish heart regeneration," Wei et al. perform bulk and single-cell RNA-sequencing on uninjured and injured zebrafish hearts with or without prior macrophage depletion by clodronate. For the single-cell RNA sequencing, the authors sort macrophages and neutrophils prior to sequencing by using fluorescent reporters for each of the two lineages. The authors characterize the differential gene expression between injured and uninjured hearts with and without prior macrophage depletion. The single-cell analyses allow the characterization of nine discrete subpopulations of macrophages and two distinct neutrophil types. The manuscript is largely descriptive with lots of discussion of specific differentially expressed genes. The authors conclude that tissue-resident macrophages are important for heart regeneration through the remodeling of the microenvironment and by promoting revascularization. Circulating monocyte-derived macrophages cannot adequately replace the resident macrophages even after recovery from clodronate depletion.

The manuscript presents a very large catalog of useful gene expression data and further characterizes the diversity of macrophages and neutrophils in the heart following injury. Although the conclusions that resident macrophages are important for regeneration and that circulating macrophages cannot adequately substitute for them are not particularly novel, this manuscript provides additional support for those ideas and extends that work by providing a wealth of gene expression data from the different macrophage sub-populations in the zebrafish and how they respond to and promote regeneration. The authors also present a nice analysis supporting the interactions of macrophages with neutrophils via comparing receptors and ligands (from gene expression data) on the two populations - this should be a useful resource.

Reviewer #1 (Public Review):

In the current work, the authors aimed to investigate the genetic and non-genetic factors that impact structural asymmetry.

A major strength is the number of data samples included in the study to assess brain structural asymmetry. A consequence of the inclusion of many samples is then also the sample size. Given that the authors also work with longitudinal data, it would be nice to be able to appreciate the individual effects across time points, this is now a little unclear. A possible less well-developed approach is the genetic basis, as this was stated as the main question, here the investigations are not that deep and may only touch upon the question. Moreover, the association with cognition, handedness, sex, and ICV is somewhat interesting yet seems also a bit minimal to fully grasp its implications.

To some extent, the aim of the study could still be written with more clarity. However, the authors have in part achieved their aims - assuming it is found a consensus on the brain asymmetry patterns in humans as is stated in the abstract. Overall the results support the conclusions, yet the strong interpretation of early life factors in particular is not empirically investigated as far as I gather.

Overall this is a nice and thorough work on asymmetry that may inform further work on brain asymmetry, its genetic basis, development, environmentally induced change, and link to behavioural variation.

Reviewer #1 (Public Review):

This manuscript puts forward the concept that there is a specific time window during which YAP/TAZ driven transcription provides feedback for optimal endothelial cell adhesion, cytoskeletal organization and migration. The study follows up on previous elegant findings from this group and others which established the importance of YAP/TAZ-mediated transcription for persistent endothelial cell migration. The data presented here extends the concept at two levels: first, the data may explain why there are differences between experimental setups where YAP/TAZ activity are inhibited for prolonged times (e.g. cultures of YAP knockdown cells), versus experiments in which the transient inhibition of YAP/TAZ and (global) transcription affects endothelial cell dynamics prior to their equilibrium.

All experiments are convincing, clearly visualized and quantified. I have some questions that the authors may address to strengthen this exciting new concept:

• Point for more elaborate discussion: Apparently the timescale of negative feedback signals is conserved between endothelial cell migration in vitro (with human cells) and endothelial migration during the formation of ISVs in zebrafish. What do you think might be an explanation for such conserved timescales? Are there certain processes within cytoskeletal tension build up that require this quantity of time to establish? Or does it relate to the time that is needed to begin to express the YAP/TAZ target genes that mediate feedback?<br /> • Do you expect different timescales for slower endothelial migratory processes (e.g. for instance during fin vascular regeneration which takes days) ?<br /> • Is the ~4hrs and 8hrs feedback time window a general property or does it differ between specific endothelial cell types? In the veins the endothelial cells generate less stress fibers and adhesions compared to in the arteries. Does this mean that there might be a difference in the feedback time window, or does that mean that certain endothelial cell types may not have such YAP/TAZ-controlled feedback system?<br /> • The experiments are based on perturbations to prove that transcriptional feedback is needed for endothelial migration. What would happen if the feedback systems is always switched on? An experiment to add might be to analyse the responsiveness of endothelial cells expressing constitutively active YAP/TAZ.<br /> • To investigate the role of YAP-mediated transcription in an accurate time-dependent manner the authors may consider using the recently developed optogenetic YAP translocation tool: https://doi.org/10.15252/embr.202154401

Reviewer #1 (Public Review):

The authors set out to develop an organoid model of the junction between early telencephalic and ocular tissues to model RGC development and pathfinding in a human model. The authors have succeeded in developing a robust model of optic stalk(OS) and optic disc(OD) tissue with innervating retinal ganglion cells. The OS and OD have a robust pattern with distinct developmental and functional borders that allow for a distinct pathway for pathfinding RGC neurites.

This study falls short on a thorough analysis of their single cell transcriptomics (scRNAseq). From the scRNAseq it is unclear the quality and quantity of the targeted cell types that exist in the model. A comparative analysis of the scRNAseq profiles of their cell-types with existing organoid protocols, to determine a technical improvement, or with fetal tissue, to determine fidelity to target cells, would greatly improve the description of this model and determine its utility. This is especially necessary for the RGCs developed in this protocol as they recommend this as an improved model to study RGCs.

Future work targeting RGC neurite outgrowth mechanisms will be exciting.

Reviewer #1 (Public Review):

In this article, the authors found a distinct fibroblast subpopulation named AG fibroblasts, which are capable of regulating myeloid cells, T cells and ILCs, and proposed that AG fibroblasts function as a previously unrecognized surveillant to orchestrate chronic gingival inflammation in periodontitis. Generally speaking, this article is innovative and interesting, however, there are some problems that need to be addressed to improve the quality of the manuscript.

Results:

1) It is recommended to add HE staining and immunohistochemistry staining to observe the inflammation, tissue damage, and repair status from 0 to 7 days, so that readers can understand cell phenotype changes corresponding to the periodontitis stage. The observation index can include inflammation and vascular related indicators.

2) Figure 1A-1D can be placed in the supplementary figure.

3) I suggest the authors to put the detection of the existence of AG fibroblasts before exploring its relationship with other types of cells.

4) The layout of the picture should be closely related to the topic of the article. It is recommended to readjust the layout of the picture. Figure 1 should be the detection of AG cells and their proportion changes from 0 to 7 days. In other figures, the authors can separately describe the proportion changes of myeloid cells, T cells and ILCs, and explored the association between AG fibroblasts and these cell types.

Methods:

It is recommended to separately list the statistical methods section. The statistical method used in the article should be one-way ANOVA.

Reviewer #1 (Public Review):

Overall, I find the work performed by the authors very interesting. However, the authors have not always included literature that seems relevant to their study. For instance, I do not understand why two papers Dunican et al 2013 and Dunican et al 2015, which provide important insight into Lsh/HELLS function in mouse, frog and fish were not cited. It is also important that the authors are specific about what is known and in particular about what is not known about CDCA7 function in DNA methylation regulation. Unless I am mistaken, there is currently only one study (Velasco et al 2018) investigating the effect of CDCA7 disruption on DNA methylation levels (in ICF3 patient lymphoblastoid cell lines) on a genome-wide scale (Illumina 450K arrays). Unoki et al 2019 report that CDCA7 and HELLS gene knockout in human HEK293T cells moderately and extremely reduces DNA methylation levels at pericentromeric satellite-2 and centromeric alpha-satellite repeats, respectively. No other loci were investigated, and it is therefore not known whether a CDCA7-associated maintenance methylation phenotype extends beyond (peri)centromeric satellites. Thijssen et al performed siRNA-mediated knockdown experiments in mouse embryonic fibroblasts (differentiated cells) and showed that lower levels of Zbtb24, Cdca7 and Hells protein correlate with reduced minor satellite repeat methylation, thereby implicating these factors in mouse minor satellite repeat DNA methylation maintenance. Furthermore, studies that demonstrate a HELLS-CDCA7 interaction are currently limited to Xenopus egg extract (Jenness et al 2018) and the human HEK293 cell line (Unoki et al 2019). Whether such an interaction exists in any other organism and is of relevance to DNA methylation mechanisms remains to be determined. Therefore, in my opinion, the conclusion that "Our co-evolution analysis suggests that DNA methylation-related functionalities of CDCA7 and HELLS are inherited from LECA" should be softened, as the evidence for this scenario is not very compelling and seems premature in the absence of molecular data from more species.

The authors used BLAST searches to characterize the evolutionary conservation of CDCA7 family proteins in vertebrates. From Figure 2A, it seems that they identify a LEDGF binding motif in CDCA7/JPO1. Is this correct and if yes, could you please elaborate and show this result? This is interesting and important to clarify because previous literature (Tesina et al 2015) reports a LEDGF binding motif only in CDCA7L/JPO2.

To provide evidence for a potential evolutionary co-selection of CDCA7, HELLS and the DNA methyltransferases (DNMTs) the authors performed CoPAP analysis. Throughout the manuscript, it is unclear to me what the authors mean when referring to "DNMT3". In the Material and Methods section, the authors mention that human DNMT3A was used in BLAST searches to identify proteins with DNA methyltransferase domains. Does this mean that "DNMT3" should be DNMT3A? And if yes, should "DNMT3" be corrected to "DNMT3A"? Is there a reason that "DNMT3A" was chosen for the BLAST searches?

CoPAP analysis revealed that CDCA7 and HELLS are dynamically lost in the Hymenoptera clade and either co-occurs with DNMT3 or DNMT1/UHRF1 loss, which seems important. Unfortunately, the authors do not provide sufficient information in their figures or supplementary data about what is already known regarding DNA methylation levels in the different Hymenoptera species to further consider a potential impact of this observation. What is "the DNA methylation status" of all these organisms? This information cannot be easily retrieved from Table S2. A clearer presentation of what is actually known already would improve this paragraph.

Furthermore, A. thaliana DDM1, and mouse and human Lsh/Hells are known to preferably promote DNA methylation at satellite repeats, transposable elements and repetitive regions of the genome. On the other hand, DNA methylation in insects and other invertebrates occurs in genic rather than intergenic regions and transposable elements (e.g. Bewick et al 2017; Werren JH PlosGenetics 2013). It would be helpful to elaborate on these differences.

Reviewer #1 (Public Review):

The manuscript focused on roles of a key fatty-acid synthesis enzyme, acetyl-coA-carboxylase 1 (ACC1), in the metabolism, gene regulation and homeostasis of invariant natural killer T (NKT_ cells and impact on these T cells' roles during asthma pathogenesis. The authors presented data showing that the acetyl-coA-carboxylase 1 enzyme regulates the expression of PPARg then the function of NKT cells including the secretion of Th2-type cytokines to impact on asthma pathogenesis. The results are clearcut and data were logically presented.

Major concerns:

1. This study heavily relied on the CD4-CreACC1fl/fl mice. While using of a-GalCer stimulation and Ja18KO mice mitigated the concern, it is still a major concern that at least some of the phenotype were due to the effect on conventional CD4 T cells. For example, the deletion of ACC1 gene seems also decreased the numbers of conventional CD4 T cells (Fig. 2D, Fig. S1D). Previously there were reports showing ACC1 gene in conventional CD4 T cells also plays a role in lung inflammation (Nakajima et al., J. Exp. Med. 218, 2021). If the authors believe the phenotype observed was mainly due to iNKT cells, rather than conventional CD4 T cells, a compare/contrast of the two studies should be discussed to explain or reconcile the results.

2. The overall significance of the manuscript is related to the potential clinical suppression of ACC1 in human asthma patients. However, the authors only showed the elevated ACC1 genes in these patients, not even in vitro data demonstrating that suppression of ACC1 genes in the iNKT cells from patients could have potential therapeutic effect or suppression of the relevant cytokines.

3. The authors report that a-GalCer administration can induce the AHR, however, in the cited paper (Hachem et al., Eur J. Immunol. 35, 2793, 2005), iNKT cell activation seems to have the opposite effect to inhibit AHR. Did the authors mean to cite different papers?

Reviewer #1 (Public Review):

In the study by Venkat et al. the authors expand the current knowledge of allosteric diversity in the human kinome by c-terminal splicing variants using as a paradigm DCLK1. In this work, the authors provide evolutionary and some mechanistic evidence about how c-terminal isoform specific variants generated by alternative splicing can regulate catalytic activity by means of coupling specific phosphorylation sites to dynamical and conformational changes controlling active site and substrate pocket occupancy, as well as interfering with protein-protein interacting interfaces that altogether provides evidence of c-terminal isoform specific regulation of the catalytic activity in protein kinases.

The paper is overall well written, the rationale and the fundamental questions are clear and well explained, the evolutionary and MD analyses are very detailed and well explained. The methodology applied in terms of the biochemical and biophysical tools falls a bit short in some places and some comments and suggestions are given in this respect. If the authors could monitor somehow protein auto-phosphorylation as a functional readout would be very useful by means of using phospho-specific antibodies to monitor activity. Overall I think this is a study that brings some new aspects and concepts that are important for the protein kinase field, in particular the allosteric regulation of the catalytic core by c-terminal segments, and how evolutionary cues generate more sophisticated mechanisms of allosteric control in protein kinases. However a revision would be recommended.

Reviewer #1 (Public Review):

Original review:

This manuscript by Walker et. al. explores the interplay between the global regulators HapR (the QS master high cell density (HDC) regulator) and CRP. Using ChIP-Seq, the authors find that at several sites, the HapR and CRP binding sites overlap. A detailed exploration of the murPQ promoter finds that CRP binding promotes HapR binding, which leads to repression of murPQ. The authors have a comprehensive set of experiments that paints a nice story providing a mechanistic explanation for converging global regulation. I did feel there are some weak points though, in particular the lack of integration of previously identified transcription start sites, the lack of replication (at least replication presented in the manuscript) for many figures, some oddities in the growth curve, and not reexamining their HapR/CRP cooperative binding model in vivo using ChIP-Seq.

Review of revised version:

This revised manuscript by Walker et. al. addresses some of the editorial points and conceptual discussion, but in general, most of my suggestions (as the previous reviewer #1) for additional experimentation or addition were not addressed as discussed below. Therefore, my overall review has not changed.

1) For example, in point 1, the suggested analysis was not performed because it is not trivial. My reason for making this suggestion is that the original manuscript was limited to Vibrio cholerae, and the impact of the manuscript would increase if the findings here were demonstrated to be more broadly applicable. I expect papers published in eLife to have such broad applicability. But no changes were made to the manuscript in this regard. The revised version is still limited to only Vibrio cholerae.

2) For point 2, the activity of FLAG-tag luxO could have been simply validated in a complementation assay. Yes, they demonstrated DNA binding, but that is not the only activity of LuxO.

3) For point 7, the transcriptional fusions were not explored at different times or different media, which is also something that was hinted at by other reviewers. In regard to exploring expression at different time points, this seems particularly relevant for QS regulated genes.

4) For point 13, the authors express that doing an additional CHIP-Seq is outside of the scope of this manuscript. Perhaps that is the case, but the point of the comment is to validate the in vitro binding results with an in vivo binding assay. A targeted CHIP-Seq approach specifically analyzing the promoters where cooperative binding was observed in vitro could have addressed this point.

Reviewer #1 (Public Review):

The manuscript describes that cultured mammalian cells adapt to chronic stress by increasing their size and protein translation through Hsp90. The authors extensively use Hsp90 knockout cells and mass spectrometry to provide solid evidence that chronic heat shock response is accompanied by cell size changes and stress resistance in large cells. The major strength of the work is the authors ability to document the heat shock response in detail, while the main weakness is that the cell size changes appear not to be quantitative making it difficult to assess how much the cell density is changed in chronic stress. Nevertheless, the increased stress resistance of large cells is conceptually important and provides one potential explanation why cells need to control their size. This work adds to our understanding of how cellular stress is managed, and while stress responses have been observed previously in relation to cell size, this work provides evidence for increased stress resistance in larger cells.

Reviewer #1 (Public Review):

"MAGIC" was introduced by the Rong Li lab in a Nature letters article in 2017. This manuscript is an extension of this original work and uses a genome wide screen the Baker's yeast to decipher which cellular pathways influence MAGIC. Overall, this manuscript is a logical extension of the 2017 study, however the manuscript is challenging to follow, complicated by the data often being discussed out of sequence. Although the manuscripts makes claims of a mechanism being pinpointed, there are many gaps and the true mechanisms of how the factors identified in the screen influence MAGIC is not clear. A key issue is that there are many assumptions drawn on previous literature, but central aspects of the mechanisms being proposed are not adequately shown.

Key comments:

[1] Reasoning and pipelines presented in the first two sections of the results are disordered and do not follow figure order. In some instances, the background to experimental analyses such as detailing the generation of spGFP constructs in the YKO mutant library, or validation of Snf1 activation are mentioned after respective results are discussed. This needs to be fixed.<br /> [2] In general there is a lack of data to support microscopy data and supporting quantification analysis. The validity of this data could be significantly strengthened with accompanying western blots showing accumulation of a given constructs in mitochondrial sub compartments (as was the case in the labs original paper in 2017).<br /> [3] Much of the mechanisms proposed relies on the Snf1 activation. This is however not shown, but assumed to be taking place. Given that this activation is central to the mechanism proposed this should be explicitly shown here - for example survey the phosophorylation status of the protein.

Joint Public Review:

Smirnova et al. present a cryo-EM structure of human SIRT6 bound to a nucleosome as well as the results from molecular dynamics simulations. The results show that the combined conformational flexibilities of SIRT6 and the N-terminal tail of histone H3 limit the residues with access to the active site, partially explaining the substrate specificity of this sirtuin-class histone deacetylase. The cryo-EM analysis in its current form is incomplete, lacking aspects of validation such as angular distribution information and other standard measurements of the quality of the reconstruction. Biochemical validation of the structural findings is inadequate, relying primarily on previous publications. Importantly, two other groups have recently published cryo-EM structures of SIRT6:nucleosome complexes. This manuscript by Smirnova et al., therefore, confirms and complements these previous findings, with the addition of some novel insights into the role of structural flexibility in substrate selection.

Reviewer #1 (Public Review):

Gehr and colleagues used an elegant method, using neuropixels probes, to study retinal input integration by mouse superior collicular cells in vivo. Compared to a previous report of the same group, they opto-tagged inhibitory neurons and defined the differential integration onto each group. Through these experiments, the author concluded that overall, there is no clear difference between the retina connectivity to excitatory and inhibitory superior colliculus neurons. The exception to that rule is that excitatory neurons might be driven slightly stronger than inhibitory ones. Technically, this work is performed at a high level, and the plots are beautifully conceived, but I have doubts if the interpretation given by the authors is solid. I will elaborate below.

Some thoughts about the interpretation of the results.

My main concern is the "survivor bias" of this work, which can lead to skewed conclusions. From the data set acquired, 305 connections were measured, 1/3 inhibitory and 2/3 excitatory. These connections arise from 83 RGC onto 124 RGC (I'm interpreting the axis of Fig.2 C). Here it is worth mentioning that different RGC types have different axonal diameters (Perge et al., 2009). Here the diameter is also related to the way cells relay information (max frequencies, for example). It is possible that thicker axons are easier to measure, given the larger potential changes would likely occur, and thus, selectively being picked up by the neuropixels probe. If this is the case, we would have a clear case of "survival bias", which should be tested and discussed. One way to determine if the response properties of axonal termini are from an unbiased sample is to make a rough functional characterization as generally performed (see Baden et al. 2006). This is fundamental since all other conclusions are based on unbiased sampling.

One aspect that is not clear to me is to measure of connectivity strength in Figure 2. Here it seems that connectivity strength is directly correlated with the baseline firing rate of the SC neuron (see example plots). If this is a general case, the synaptic strength can be assumed but would only differ in strength due to the excitability of the postsynaptic cell. This should be tested by plotting the correlation coefficient analysis against the baseline firing rate.

My third concern is the assessment of functional similarity in Fig. 3. It is not clear to me why the similarity value was taken by the arithmetic mean. For example, even if the responses are identical for one connected pair that exclusively responds either to the ON or OFF sparse noise, the maximal value can only be 0.67. Perhaps I misunderstood something. Secondly, correlations in natural(istic) movies can differ dramatically depending on the frame rate that the movie was acquired and the way it is displayed to the animal. What looks natural to us will elicit several artifacts at a retinal level, e.g., due to big jumps between frames (no direction-selective response) or overall little modulation (large spatial correlations). I would rather opt for uniform stimuli, as suggested previously. Of course, these are also approximations but can be easily reproduced by different labs and are not subjected to the intricacies of the detailed naturalistic stimulus used.

Fourth. It is important to control the proportion of inhibitory cells activated optogenetically across the recording probe. Currently, it is not possible to assess if there are false negatives. One way of controlling for this would be to show that the number of inhibitory interneurons doesn't vary across the probe.

Fifth. In Fig. 4, the ISI had a minimal bound of 5 ms. Why? This would cap the firing rate at 200Hz, but we know that RGC in explants can fire at higher frequencies for evoked responses. I would set a lower bound since it should come naturally from the after-depolarization block. Another aspect that remains unclear is to what extent the paired-spike ratio depends on the baseline firing rate. This would change the interpretation from the particular synaptic connection to the intrinsic properties of the cell and is plausible since the bassline firing rate varies tremendously. One related analysis would be to plot the change of PSR depending on the ISI. It would be intuitive to make a scatter plot for all paired spikes of all recorded neurons (separated into inhibitory and excitatory) of ISI vs. PSR.

Panel 4E is confusing to me. Here what is plotted is efficacy 1st against PSR (which is efficacy 2nd/efficacy 1st). Given that you have a linear relation between efficacy 1st and efficacy 2nd (panel 4C), you are essentially re-plotting the same information, which should necessarily have a hyperbolic relationship: [ f(x) = y/x ]. Thus, fitting this with a linear function makes no sense and it has to be decaying if efficacy 2nd > efficacy1st as shown in 4C.

Finally, in Figure 5, the perspective is inverted, and the spike correlations are seen from the perspective of SC neurons. Here it would also be good to plot the cumulative histograms and not look at the averages. Regarding the similarity index and use of natural stats, please see my previous comments. Also, would it be possible to plot the contribution v/s the firing rate with the baseline firing rate with no stimulation or full-field stimulation? This is important since naturalistic movies have too many correlations and dependencies that make this plot difficult to interpret.

Overall, the paper only speaks from excitatory and inhibitory differences in the introduction and results. However, it is known that there are three clear morphologically distinct classes of excitatory neurons (wide-field, narrow-field, and stellate). This topic is touched in the discussion but not directly in the context of these results. Smaller cells might likely be driven much stronger. Wide-field cells would likely not be driven by one RGC input only and will probably integrate from many more cells than 6.

Reviewer #1 (Public Review):

Segas et al. present a novel solution to an upper-limb control problem which is often neglected by academia. The problem the authors are trying to solve is how to control the multiple degrees of freedom of the lower arm to enable grasp in people with transhumeral limb loss. The proposed solution is a neural network based approach which uses information from the position of the arm along with contextual information which defines the position and orientation of the target in space. Experimental work is presented, based on virtual simulations and a telerobotic proof of concept.

The strength of this paper is that it proposes a method of control for people with transhumeral limb loss which does not rely upon additional surgical intervention to enable grasping objects in the local environment. A challenge the work faces is that it can be argued that a great many problems in upper limb prosthesis control can be solved given precise knowledge of the object to be grasped, its relative position in 3D space and its orientation. It is difficult to know how directly results obtained in a virtual environment will translate to real world impact. Some of the comparisons made in the paper are to physical systems which attempt to solve the same problem. It is important to note that real world prosthesis control introduces numerous challenges which do not exist in virtual spaces or in teleoperation robotics.

The authors claim that the movement times obtained using their virtual system, and a teleoperation proof of concept demonstration, are comparable to natural movement times. The speed of movements obtained and presented are easier to understand by viewing the supplementary materials prior to reading the paper. The position of the upper arm and a given target are used as input to a classifier, which determines the positions of the lower arm, wrist and the end effector. The state of the virtual shoulder in the pick and place task is quite dynamic and includes humeral rotations which would be challenging to engineer in a real physical prosthesis above the elbow. Another question related to the pick and place task used is whether or not there are cases where both the pick position and the place position can be reached via the same, or very similar, shoulder positions? i.e. with the shoulder flexion-extension and abduction-adduction remaining fixed, can the ANN use the remaining five joint angles to solve the movement problem with little to no participant input, simply based on the new target position? If this was the case, movements times in the virtual space would present a very different distribution to natural movements, while the mean values could be similar. The arguments made in the paper could be supported by including individual participant data showing distributions of movement times and the distances travelled by the end effector where real movements are compared to those made by an ANN.

In the proposed approach users control where the hand is in space via the shoulder. The position of the upper arm and a given target are used as input to a classifier, which determines the positions of the lower arm, wrist and the effector. The supplementary materials suggest the output of the classifier occurs instantaneously, in that from the start of the trial the user can explore the 3D space associated with the shoulder in order to reach the object. When the object is reached a visual indicator appears. In a virtual space this feedback will allow rapid exploration of different end effector positions which may contribute to the movement times presented. In a real world application, movement of a distal end-effector via the shoulder is not to be as graceful and a speed accuracy trade off would be necessary to ensure objects are grasped, rather than knocked or moved.

Another aspect of the movement times presented which is of note, although it is not necessarily incorrect, is that the virtual prosthesis performance is close too perfect. In that, at the start of each trial period, either pick or place, the ANN appears to have already selected the position of the five joints it controls, leaving the user to position the upper arm such that the end effector reaches the target. This type of classification is achievable given a single object type to grasp and a limited number of orientations, however scaling this approach to work robustly in a real world environment will necessitate solving a number of challenges in machine learning and in particular computer vision which are not trivial in nature. On this topic, it is also important to note that, while very elegant, the teleoperation proof of concept of movement based control does not seem to feature a similar range of object distance from the user as the virtual environment. This would have been interesting to see and I look forward to seeing further real world demonstrations in the authors future work.

Reviewer #1 (Public Review):

In this study, Drougard et al. examined the consequences of an acute high fat diet (HFD) on microglia in mice. 3-day HFD influenced the regulation of systemic glucose homeostasis in a microglia-dependent and independent manner, as determined using microglial depletion with PLX5622. 3-day HFD increased microglial membrane potential and the levels of palmitate and stearate in cerebrospinal fluid in vivo. Using confocal imaging, respirometry and stable isotope-assisted tracing in primary microglial cultures, the authors suggest an increase in mitochondrial fission and metabolic remodelling occurs when exposed to palmitate, which increases the release of glutamate, succinate and itaconate that may alter neuronal metabolism. This acute microglial metabolic response following acute HFD is subsequently linked to improved higher cognitive function (learning and memory) in a microglia and DRP1-dependent manner.

Strengths:<br /> Overall, this study is interesting and novel in linking acute high fat diet to changes in microglia and improved learning and memory in mice. The role for microglia and DRP1 in regulating glucose homeostasis and memory in vivo appears to be supported by the data.

Weaknesses:<br /> The authors suggest that utilisation of palmitate by microglia following HFD is the driver of the acute metabolic changes and that the release of microglial-derived lactate, succinate, glutamate and itaconate are causally linked to improvements in learning and memory.<br /> A major weakness is that the authors provide no mechanistic link between beta-oxidation of palmitate (or other fatty acids) in microglia and the observed systemic metabolic and memory phenotypes in vivo. Pharmacological inhibition of CPT1a could be considered or CPT1a-deficient microglia.

Another major weakness is that the authors also suggest that 3-day HFD microglial response (increase membrane potential) is likely driven by palmitate-induced increases in itaconate feedforward inhibition of complex II/SDH. Whilst this is an interesting hypothesis, the in vitro metabolic characterisation is not entirely convincing. The authors suggest that acute palmitate appears to rapidly compromise or saturate complex II activity. Succinate is a membrane impermeable dicarboxylate. It can enter cells via MCT transporters at acidic pH. It is not clear that I) Succinate is taken up into microglia, II) If the succinate used was pH neutral sodium succinate or succinic acid, and III) If the observed changes are due to succinate oxidation, changes in pH or activation of the succinate receptor SUCNR1 on microglia. In the absence of these succinate treatments, there are no alterations in mitochondrial respiration or membrane potential following palmitate treatment, which does not support this hypothesis. Intracellular itaconate measurements and quantification are lacking and IRG1 expression is not assessed. There also appears to be more labelled itaconate in neuronal cultures from control (BSA) microglia conditioned media, which is not discussed. What is the total level of itaconate in neurons from these conditioned media experiments? No evidence is provided that the in vivo response is dependent on IRG1, the mitochondrial enzyme responsible for itaconate synthesis, or itaconate. To causally link IRG1/itaconate, IRG1-deficient mice could be used in future work.

While microglial DRP1 is causally implicated the role of palmitate is not convincing. Mitochondrial morphology changes are subtle including TOMM20 and DRP1 staining and co-localization - additional supporting data should be provided. Electron microscopy of mitochondrial structure would provide more detailed insight to morphology changes. Western blot of fission-associated proteins Drp1, phospho-Drp1 (S616), MFF and MiD49/51. Higher magnification and quality confocal imaging of DRP1/TOMM20. Drp1 recruitment to mitochondrial membranes can be assessed using subcellular fractionation. No characterisation of primary microglia from DRP1-knockout mice is performed with palmitate treatment. Authors demonstrate an increase in both stearate and palmitate in CSF following 3-day HFD. Only palmitate was tested in the regulation of microglial responses, but it may be more informative to test stearate and palmitate combined.

Reviewer #1 (Public Review):

In this study, Fang H et al. describe a potential pathway, ITGB4-TNFAIP2-IQGAP1-Rac1, that may involve in the drug resistance in triple negative breast cancer (TNBC). Mechanistically, it was demonstrated that TNFAIP2 bind with IQGAP1 and ITGB4 activating Rac1 and the following drug resistance. The present study focused on breast cancer cell lines with supporting data from mouse model and patient breast cancer tissues. The study is interesting. The experiments were well controlled and carefully carried out. The conclusion is supported by strong evidence provided in the manuscript. The authors may want to discuss the link between ITGB4 and Rac 1, between IQGAP1 and Rac1, and between TNFAIP2 and Rac1 as compared with the current results obtained. This is important considering some recent publications in this area (Cancer Sci 2021, J Biol Chem 2008, Cancer Res 2023). In addition, some key points need to be addressed in order to support their conclusion in full.

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Reviewer #1 (Public Review):

In this manuscript by Douglas et al, the investigative team seeks to identify Staphylococcus aureus genes (and associated polymorphisms) that confer altered susceptibility to human serum, with the hypothesis that such genes might contribute to the propensity of a strain to cause bacteremia, invasive disease, and/or death. Using an innovative GWAS-like approach applied to a bank of over 300 well-characterized clinical S. aureus isolates, the authors discover SNPs in seven different staphylococcal genes that confer increased survival in the setting of serum exposure. The authors then mainly focus on one gene, tcaA, and illustrate a potential mechanism whereby modification of peptidoglycan structure and WTA display leads to altered susceptibility to serum, serum-derived antimicrobial compounds, and antibiotics. One particularly significant finding is that the identified tcaA SNP is significantly associated with patient mortality, in that patients infected with the SNP bearing isolate are less likely to die from infection. It is therefore hypothesized that this SNP represents an adaptive mutation that promotes serum survival while decreasing virulence and host mortality. In a murine model of infection, the strain bearing the WT allele of tcaA is significantly more virulent than the tcaA mutant, suggesting that the role of tcaA in bacteremia is infection-phase dependent.

This manuscript has many strengths. The triangulation of genomic analysis, patient outcomes data, and in vitro and in vivo mechanistic testing adds to the significance of the findings in terms of human disease. Testing the impact of mutating tcaA in multiple staphylococcal lineages and backgrounds also increases the rigor of the study. The identification of bacterial loci that impact susceptibility to both host antimicrobial compounds and commonly used antibiotics is also a strength of this work, given the evolutionary and treatment implications for such genes.

One moderate weakness is that the impact of the identified SNP in tcaA is only tested in some of the assays, whereas the majority of the testing is performed with a whole gene knockout. In some cases this results in more speculative conclusions that will require further testing to validate. All in all, this is an exciting manuscript that will be of interest to the broader research communities focused on staphylococcal pathogenesis, bacterial evolution, and host-pathogen interactions, as well as to clinicians who care for patients with invasive staphylococcal infection.

Reviewer #1 (Public Review):

Using an immobilised metal affinity chromatography (IMAC)-based assay coupled with Western blot immunodetection analysis, SbtB, the regulatory protein for SbtA activity, is shown in itself to be regulated by the local adenylate energy charge (AEC), with inhibitory binding of SbtB to SbtA disfavoured at high ATP:ADP ratios. Such conditions are expected to be encountered during steady-state photosynthesis with the associated cellular demand for Ci and SbtA activity.

By homology with ATP-binding PII proteins, ATP is proposed to interact with a loop region of SbtB, changing its conformation on binding and inhibiting the formation of the (inactive) SbtA:SbtB complex. On the basis of this, the authors propose that SbtB acts an AEC-sensing 'curfew' protein for SbtA activity, tuning bicarbonate import by this protein for situations when carbon fixation would be physiologically (and energetically) advantageous. As SbtA is a HCO3-/Na+ symporter, Na+ homeostasis would also be controlled by regulation of this transporter.

The IMAC assay used to monitor SbtA:SbtB complex stability as a function of AEC seems robust, is relatively straightforward and may be of interest to other researchers investigating adenylate-sensing protein reaction partners (with the usual caveats on extrapolating in vitro results to living systems, as noted by the authors).

In this study, SbtA regulation was also investigated in vivo in a Synechococcus HCO3- transporter knockout mutant via measurement of labelled HCO3- uptake and overall photosynthetic performance (MIMS-monitored O2 evolution as a function of PAR). Here, SbtB was inferred to regulate SbtA activity during the induction of photosynthesis (i.e. at low ATP:ADP) and not when photosynthesis was fully activated and in a steady-state condition. SbtA inactivation on a light-dark transition was also demonstrated in vivo irrespective of the presence SbtB, indicative of additional regulatory pathways affecting the activity of this transporter. These conclusions seem to be well-supported by the presented data.

Reviewer #1 (Public Review):

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

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

Complementary to these data, they show that the stability of the individual complex members is affected in mutants supporting that they are stabilized through complex formation.<br /> Furthermore, the authors then show that kar4 has additional roles in mating that are separable from its role through the m6A complex in meiosis.<br /> The authors employ appropriate methodology throughout to address their aims and present convincing evidence for their claims. The evidence presented here reinforces that the m6A complex is evolutionary and highly conserved, with a broad scope for its functional analysis in humans and model organisms.

Reviewer #1 (Public Review):

The current study was designed to test the hypothesis that neural circuit plasticity during adolescence can be targeted to restore cortical function under conditions of developmental disruptions that are relevant to psychiatric disorders. Specifically, the authors targeted the mesofrontal cortical dopamine system in 2 genetic mouse models of schizophrenia and performed optical recordings in combination with behavior and chemogenetic manipulations. Major findings and strengths include that stimulation of frontal dopaminergic projections in a limited adolescent time window can stably reverse defects in cortical neuronal activity and cognitive control in adulthood in 2 genetic mouse models of psychiatric disorders. While the precise postsynaptic mechanisms underlying the positive impact of adolescent mesofrontal dopamine stimulation were not address, another strength of this study is that the authors performed key manipulations using age and dose/intensity as dependent variables to show that the level of neural circuit activation during adolescence follows an inverted U-shape pattern. Collectively, this is a well-design study with many strengths and novel findings that are likely to positively impact a widespread of disciplines within the biological psychiatry and neuroscience field.

Reviewer #1 (Public Review):

The authors aimed to contrast the effects of pharmacologically enhanced catecholamine and acetylcholine levels versus the effects of voluntary spatial attention on decision making in a standard spatial cueing paradigm. Meticulously reported, the authors show that atomoxetine, a norepinephrine reuptake inhibitor, and cue validity both enhance model-based evidence accumulation rate, but have several distinct effects on EEG signatures of pre-stimulus cortical excitability, evoked sensory EEG potentials and perceptual evidence accumulation. The results are based on a reasonable sample size (N=28) and state-of-the art modeling and EEG methods.

Although the authors draw a few partial conclusions that are not fully supported by the data (see below), I think that the authors' EEG findings provide sufficient support for the overall conclusion that "selective attention and neuromodulatory systems shape perception largely independently and in qualitatively different ways". This is an important conclusion because neuromodulatory systems and selective spatial attention are both known to regulate the neural gain of task-relevant single neurons and neural networks. Apparently, these effects on neural gain affect decision making in dissociable ways.

The effects of donepezil, a cholinesterase inhibitor, were generally less strong than those of atomoxetine, and in various analyses went in the opposite direction. The authors fairly conclude that more work is necessary to determine the effects of cholinergic neuromodulation on perceptual decision making.

1) I believe that the following partial conclusions are not fully supported by the data:

a) In the results section on page 6, the authors conclude that "Attention and ATX both enhanced the rate of evidence accumulation towards a decision threshold, whereas cholinergic effects were negligible." I believe "negligible" is wrong here: the corresponding effects of donepezil had p-values of .09 (effect of donepezil on drift rate), .07 (effect of donepezil on the cue validity effect on drift rate) and .09 (effect of donepezil on non-decision time), and were all in the same direction as the effects of atomoxetine, and would presumably have been significant with a somewhat larger sample size. I would say the effects of donepezil were "in the same direction but less robust" (or at the very least "less robust") instead of "negligible".

b) "In the results section on page 8, the authors conclude that "Summarizing, we show that drug condition and cue validity both affect the CPP, but they do so by affecting different features of this component (i.e. peak amplitude and slope, respectively)."<br /> This conclusion is a bit problematic for two reasons. First, drug condition had a significant effect not only on peak amplitude but also on slope. Second, cue validity had a significant effect not only on slope but also on peak amplitude. It may well be that some effects were more significant than others, but I think this does not warrant the authors' conclusion.

c) In the discussion section on page 11, the authors conclude that "First, although both attention and catecholaminergic enhancement affected centro-parietal decision signals in the EEG related to evidence accumulation (O'Connell et al., 2012; Twomey et al., 2015), attention mainly affected the build-up rate (slope) whereas ATX increased the amplitude of the CPP component (Figure 3D-F)."<br /> As I wrote above, I believe it is not correct that "attention mainly affected the build-up rate or slope", given that the effect of cue-validity on CPP slope was also significant. Also, while the authors' data do support the conclusion that ATX increased the amplitude and not the slope of the CPP component, a previous study in humans found the opposite: ATX increased the slope but did not affect the peak amplitude of the CPP (Loughnane et al 2019, JoCN, https://pubmed.ncbi.nlm.nih.gov/30883291/). Although the authors cite this study (as from 2018 instead of 2019), they do not draw attention to this important discrepancy between the two studies. I encourage the authors to dedicate some discussion to these conflicting findings.

2) On page 12 and page 14 the authors suggest a selective effect of ATX on *tonic* catecholamine activity, but to my knowledge the exact effects of ATX on phasic vs. tonic catecholamine activity are unknown. Although microdialysis studies have shown that a single dose of atomoxetine increases catecholamine concentrations in rodents, it is unknown whether this reflects an increase in tonic and/or phasic activity, due to the limited temporal resolution of microanalysis. Thus, atomoxetine may affect tonic and/or phasic catecholamine activity, and which of these two effects dominates is still unknown, I think.

Reviewer #1 (Public Review):

Ruby et al. have investigated patterns of age-specific mortality in the exceptionally long-lived naked mole-rat (NMR), under captive conditions. The authors first visited this topic five years previously with an unprecedently large data set and concluded that naked mole-rats are 'non-aging': because analyses of their survival did not detect an increasing mortality hazard with age. This result has obvious applied interest in humans because of its implications for maintaining health into later life. One criticism directed at this previous work was that a limited number 'old-aged' individuals in their data set (individuals in what might be expected to be the latter half of the life course) reduced the power with which to detect an age-related increase in mortality - or to convincingly demonstrate its absence. The current study revisits this topic with a larger sample across the life course. The authors also provide additional analyses that explore various predictors of mortality, including breeding status, body weight and colony size, and now also make direct comparisons to mortality patterns in other species of African mole-rat from the Fukomys clade (which share many convergent social and life history features). I found the analyses of Fukomys mortality particularly illuminating. However, while these additional analyses provide some useful context and can generate interesting discussion points about ageing patterns in an extremely unusual species, the principal issue at hand whether the absence of Gompertzian mortality in NMR is a robust pattern.

In this respect, a major limitation of the current study is that only 11% of the animals (n = 755) had died at the point of its conclusion- the remaining 89% being right-censored (n = 6138). This means that, as in the previous analysis, there are still relatively small numbers of individuals that have died in the older age classes (see Fig 1 for the high level of right-censoring between 15-20 years and the low numbers of deaths after this point, also Supp 1 for the raw data): the part of the life course where one would predict mortality rates to increase from an evolutionary perspective. Thus, while the authors claim very generally that the "demographic data has doubled", this in no way reflects whether the new data is informative to the question at hand, which relies on an ability to estimate death rates in older individuals accurately. If one looks more closely at the numbers which do matter, then one can see that the number of deaths in the data set has shifted from 447 in the former treatment (Ruby et al. 2018) to 755 currently, but that the number of later-stage deaths remains somewhat modest (and that this is probably reflected in the large confidence intervals for the mortality hazards at this time). I therefore remain unconvinced that the current study can rule out an exponential increase in hazard in older individuals.

The authors have also not provided any statistical evidence that the mortality hazard changes with age (or not), instead relying on visual comparisons of aggregated data. This is a fundamental problem and demands a more thorough treatment that compares survival models with different shape profiles. If anything, it seems that the hazard rate is declining with age - see Figures 1B & 2C, and while this may strengthen the authors argument if supported statistically, I would still wonder whether the higher mortality in early life - say 6 months to 3 years of age - is a consequence of the costs of early life development and that this is not a useful baseline against which to compare 'adult' mortality. It would also not overcome the data limitations identified above.

An additional concern is that the paper is selective in its presentation of previous work, with the authors focussing on results which support their main interpretations and glossing over those that don't. For example, the study refers to the fact that NMRs are resistant to various age-related diseases and do not show many age-related declines in physiology. Yet, while this argument of negligible senescence might hold generally, the literature contains various reports of later life declines in NMR physiology (Andziak et al. 2006; Edrey et al., 2011). Referring to work from your own group, Braude et al. (2021) write "several typical mammalian age-related lesions of muscles, bone, heart, liver, and eye, including sarcopenia, osteoarthritis, a decline in articular cartilage thickness of the condyles, lipofuscin accumulation in several organs, eye cataracts, and kidney fibrosis have been described in naked mole-rats older than 26 years (Edrey et al., 2011)". A more balanced treatment of physiology in extremely old individuals would prove constructive.

Another way in which the study fails to fully represent the literature is with respect to the divergence in ageing rates between breeders and non-breeders. This pattern has proved seductive for various mole-rat researchers because of its similarities to social insects and the suggestion that it is reproduction itself which delays ageing. While this is a clear possibility with some empirical support, it is important to also consider the question from the other way: which is to ask why non-breeders die at higher rates than breeders. For other cooperative breeders such as meerkats, the answer is clear: dominant, breeding individuals evict subordinates and once evicted from the group, the chances that these individuals will survive plummets (e.g. Cram et al. 2028). Is it possible that a similar form of dominance control might contribute the shorter life span of non-breeders in captivity? You reference Toor et al. (2020) elsewhere and this is relevant here again.<br /> Captivity also prevents non-breeders from dispersing when they would otherwise ordinarily do so (Braude 2000): is it possible that this also affects their mortality in captivity? Perhaps not being able to disperse induces chronic stress (see for example the discussion in Novikov et al. 2015). The idea that breeders show a lower intrinsic rate of aging is attractive, but many factors could contribute to this and alternatives should be considered unless they can be strongly refuted.

Lastly, it would be very beneficial to have more information on how individuals become breeders in the captive population/s. For the purposes of the analyses, individuals have been categorised as a breeder or a non-breeder based on whether they bred or not at some point in their life (i.e., they are a "breeder" for their whole life for the purposes of the Kaplan Meier curves and the estimation of mortality hazards). I think it is therefore important to rule out the possibility that only high-quality individuals become breeders and that this is what drives the contrast in breeder and non-breeder mortality. In short, is it the case that most breeders are created through the random pairing of a male and a female? Or do new breeders inherit the position once the old queen dies? The latter could lead to breeders being of generally higher quality, which might affect their mortality hazard independently of status.

Overall, I think that the authors can confidently conclude that any onset of actuarial senescence is heavily delayed in naked mole-rats, but the main conclusion that naked mole-rats "defy Gompertzian mortality" is based on inadequate evidence. It seems very possible that the inability to detect an increasing mortality hazard in such a long-lived species arises from data limitations. The central finding of the study should therefore be viewed very critically.

Refs:<br /> Anziak et al. (2006) Aging Cell 5:463-471.<br /> Braude et al. (2021) Biological Reviews 96: 376-293.<br /> Cram et al. (2018) Current Biology 28: 1-6.<br /> Edrey et al. (2011) ILAR Journal 52:41-53.<br /> Novikov et al. (2015) Biogerontology 16: 723-732.<br /> Toor et al. (2020) Animal Behaviour 168: 45-58.

Reviewer #1 (Public Review):

This is a well-written manuscript, aiming to seek experimental evidence to establish anatomical and functional connectivity between the cerebellum and the nucleus accumbens (NAc). The authors combined anatomical, neural tracing, and electrophysiological approaches with electrical stimulation and optogenetics and provided a novel and solid set of data supporting the existence of disynaptic connections between the cerebellum and the NAc. The results are convincing and the main conclusion is supported by the data. Overall, this was a well-conceived project, and the experiments were conducted carefully, though some gaps remain to be filled. The knowledge generated from this manuscript will build a foundation for further research focusing on the interaction between cerebellum and limbic system as well as the role of such interaction in controlling motivated behavior.

Overall, this is a well-conceived project. The experiments were conducted carefully. The results support the conclusion of the existence of disynaptic circuits from the cerebellum to the NAc.

Reviewer #1 (Public Review):

In this work, Vezina et al. present Bactabolize, a rapid reconstruction tool for the generation of strain-specific metabolic models. Similar to other reconstruction pipelines such as CarveMe, Bactabolize builds a strain-specific draft reconstruction and subsequently gap-fills it. The model can afterwards be used to predict growth in any defined medium the user specifies. The authors constructed a pan-model of the Klebsiella pneumoniae species complex (KpSC) and used it as input for Bactabolize to construct a genome-sale reconstruction of K. pneumoniae KPPR1. They compared the generated reconstruction with a reconstruction built through CarveMe as well as a manually curated reconstruction for the same strain. They then compared predictions of carbon, nitrogen, phosphor, and sulfur sources and found that the Bactabolize reconstruction had the overall highest accuracy. Finally, they built draft reconstructions for 10 clinical isolates of K. pneumoniae and evaluated their predictive performance. Overall, this is a useful tool, the data is well-presented, and the paper is well-written. However, the predictions are only compared with two existing reconstruction tools though more have been recently published.

Reviewer #1 (Public Review):

In this manuscript, the authors aimed to provide information about the likely function of uncharacterised genes in fission yeast. The authors highlight the bias in the literature to well-studied genes/proteins and the fact that the functions of many proteins that are conserved from yeast to humans remain unknown. Initial functional characterisation could provide the impetus for researchers to dedicate time and resources to detailed investigations of protein function. The authors subject the fission yeast deletion set to a battery of perturbations (drug treatments etc) and measured the resultant colony size. In total, 131 conditions were analysed for nearly 3,500 mutants, representing a rich dataset. Clustering analysis was then used to identify common phenotype patterns and thereby infer protein functions using a "guilt by association approach. To assign potential GO terms to uncharacterised proteins, the authors developed a new computational approach (NET-FF) which combined two previous approaches, which they validated against curated annotations on the S. pombe database Pombase. Finally, the authors chose a group of genes which their analysis predicted to be involved in cellular ageing for experimental validation, cross-validating a priority unstudied novel gene (SPAC23C4.09c) to be involved in this process. Overall, the functional analysis performed in this manuscript is rigorous, thorough and incorporates some novel approaches leading to new insights and predicted protein functions. It will be an important resource for the fission yeast community.

Joint Public Review:

The manuscript by Lolicato and colleagues characterizes the role of FGF2 dimerization in the unconventional secretion of this signaling molecule using a combination of cell-based and in vitro assays. FGF2 is secreted from the cell via an unconventional mechanism because it lacks a signal sequence. Previous studies by the same group have established a compelling model in which FGF2 forms an oligomer in a PIP2-dependent manner at the plasma membrane, which drives its translocation to the cell exterior. The same group also identified two cysteine residues (C77 and C95) critical for FGF2 oligomerization and secretion.

In this study, the authors analyzed the impact of single cysteine to alanine substitution on the oligomerization and secretion of FGF2. They found that C95 but not C77 is required for PIP2-dependent membrane binding, FGF2 oligomerization, and secretion. On the other hand, C77 regulates the interaction of FGF2 with the plasma membrane Na, K-ATPase, which is thought to enhance the FGF2-PIP2 interaction. Using a set of bi-functional crosslinkers, the authors were able to capture an FGF2 homo-dimer whose formation is dependent on C95.

They propose that FGF2 forms a disulfide-bridged dimer via C95, the building block for FGF2 oligomerization in the plasma membrane.

While most experiments were carefully designed and the data are of high quality, a few issues need further clarification.

A significant concern is a need for more direct evidence for the proposed disulfide-bridged FGF2 dimer in the cytoplasm despite multiple assays highlighting the critical role of C95 in FGF2 oligomerization and secretion. The crosslinking experiments only suggest that C95 is close to another C95 in crosslinked FGF2 dimers. Given that the reducing cytosolic environment does not usually support disulfide bond formation and that no electron acceptor has been identified to support this unusual model, the reviewers feel that the authors should consider an alternative and more plausible explanation for their observations, which is that the C95A mutation disrupts the dimerization interface. This is actually the author's explanation for why the C77A FGF2 mutant fails to bind Na, K-ATPase. For these reasons, the reviewers feel it is an overstatement to claim that FGF2 forms a disulfide dimer in the cytoplasm.

Furthermore, the authors propose that FGF2 dimers can assemble into a transient higher-order FGF2 oligomer to form a toroidal pore for protein secretion. This is supported by a computational simulation study, which suggests that FGF2 dimers exhibit a higher affinity for PI(4,5)P2 than monomers. However, the model would be much stronger if the authors could provide additional experimental validation.

Additionally, the authors propose that C95-dependent FGF2 dimerization may generate a signaling module. They cited a few structure papers on page 9 (Plotnikov et al., 1999; Plotnikov et al., 2000; Schlessinger et al., 2000), suggesting that the FGF2 dimer reported here may be the primary signaling unit. However, this statement may mislead the reader, as it has been clearly stated in these papers that FGF2 does not form a dimer directly. Instead, heparin facilitates the dimerization of the FGF receptor, which results in the recruitment of two FGF2 molecules.

Reviewer #1 (Public Review):

This fascinating paper by A.L. Schneider et al. describes voyAGEr, a shiny-based interface for easy exploration of the GTEx dataset by non- or novice programmers. Importantly, voyAGEr is open source and available from github, which could greatly accelerate additional development and further uses of this interesting tool.

The authors developed a pipeline for modeling age-related changes in gene expression in the GTEx data called ShARP-LM, fitting a linear model for age, sex, and age&sex interaction terms. This pipeline underlies the later analyses that can be applied within voyAGEr. These analyses are labeled by tissue so that users can easily begin a query based on a tissue or a gene of possible interest.

voyAGEr implements many kinds of interesting R-based tools such as pathway overrepresentation analysis and gene co-expression module analysis, in a way that makes these approaches accessible to non-bioinformaticist aging researchers.

As the tidal wave of publicly available large, high-dimensional datasets such as transcriptomes continues to grow exponentially, the usefulness of tools such as voyAGEr will only increase. While test users may be able to imagine features or refinements they wish were already present, due to the open source approach they or anyone else including but not limited to the present authors can implement additional features in the future. I look forward to using this tool and to staying abreast of its future development.

Overall, this study describes a new tool of interest to the field. The manuscript is clearly written overall. The figures and supplementary information are all clear and all add to the manuscript.

Reviewer #1 (Public Review):

This study by Sokač et al. entitled "GENIUS: GEnome traNsformatIon and spatial representation of mUltiomicS data" presents an integrative multi-omics approach which maps several genomic data sources onto an image structure on which established deep-learning methods are trained with the purpose of classifying samples by their metastatic disease progression signatures. Using published samples from the Cancer Genome Atlas the authors characterize the classification performance of their method which only seems to yield results when mapped onto one out of four tested image-layouts.

Major recommendations:

- In its current form, GENIUS analysis is neither computationally reproducible nor are the presented scripts on GitHub generic enough for varied applications with other data. The GENIUS GitHub repository provides a collection of analysis scripts and not a finished software solution (e.g. command line tool or other user interface) (the presented scripts do not even suffice for a software prototype). In detail, the README on their GitHub repository is largely incomplete and reads analogous to an incomplete and poorly documented analysis script and is far from serving as a manual for a generic software solution (this claim was made in the manuscript). The authors should invest substantially into adding more details on how data can be retrieved (with example code) from the cited databases and how such data should then be curated alongside the input genome to generically create the "genomic image". In addition, when looking at the source code, parameter configurations for training and running various modules of GENIUS were hard-coded into the source code and users would have to manually change them in the source code rather than as command line flags in the software call. Furthermore, file paths to the local machine of the author are hard-coded in the source code, suggesting that images are sourced from a local folder and won't work when other users wish to replicate the analysis with other data. I would strongly recommend building a comprehensive command line tool where parameter and threshold configurations can be generically altered by the user via command line flags. A comprehensive manual would need to be provided to ensure that users can easily run GENIUS with other types of input data (since this is the claim of the manuscript). Overall, due to the lack of documentation and hard-coded local-machine folder paths it was impossible to computationally reproduce this study or run GENIUS in general.

- In the Introduction the authors write: "To correct for such multiple hypothesis testing, drastic adjustments of p-values are often applied which ultimately leads to the rejection of all but the most significant results, likely eliminating a large number of weaker but true associations.". While this is surely true for any method attempting to separate noise from signal, their argument fails to substantiate how their data transformation will solve this issue. Data transformation and projection onto an image for deep-learning processing will only shift the noise-to-signal evaluation process to the postprocessing steps and won't "magically" solve it during training. In addition, multiple-testing correction is usually done based on one particular data source (e.g. expression data), while their approach claims to integrate five very different genomic data sources with different levels and structures of technical noise. How are these applications comparable and how is the training procedure able to account for these different structures of technical noise? Please provide sufficient evidence for making this claim (especially in the postprocessing steps after classification).

- I didn't find any computational benchmark of GENIUS. What are the computational run times, hardware requirements (e.g. memory usage) etc that a user will have to deal with when running an analogous experiment, but with different input data sources? What kind of hardware is required GPUs/CPUs/Cluster?

- A general comment about the Methods section: Models, training, and validation are very vaguely described and the source code on GitHub is very poorly documented so that parameter choices, model validation, test and validation frameworks and parameter choices are neither clear nor reproducible. Please provide a sufficient mathematical definition of the models, thresholds, training and testing frameworks.

- In chapter "Latent representation of genome" the authors write: "After successful model training, we extracted the latent representations of each genome and performed the Uniform Manifold Approximation and Projection (UMAP) of the data. The UMAP projected latent representations into two dimensions which could then be visualized. In order to avoid modeling noise, this step was used to address model accuracy and inspect if the model is distinguishing between variables of interest.". In the recent light of criticism when using the first two dimensions of UMAP projections with omics data, what is the evidence in support of the author's claim that model accuracy can be quantified with such a 2D UMAP projection? How is 'model accuracy' objectively quantified in this visual projection?

- In the same paragraph "Latent representation of genome" the authors write: "We observed that all training scenarios successfully utilized genome images to make predictions with the exception of Age and randomized cancer type (negative control), where the model performed poorly (Figure 2B).". Did I understand correctly that all negative controls performed poorly? How can the authors make any claims if the controls fail? In general, I was missing sufficient controls for any of their claims, but openly stating that even the most rudimentary controls fail to deliver sufficient signals raises substantial issues with their approach. A clarification would substantially improve this chapter combined with further controls.

Reviewer #1 (Public Review):

Gametocytes are erythrocytic sexual stages of the malaria-causing parasite Plasmodium, and are essential for parasite transmission and reproduction in the mosquito vector. In this study, Murata et al investigated the mechanisms of gene regulation in female gametocytes in the rodent malaria model parasite Plasmodium berghei. According to current views, gene regulation in Plasmodium parasites is dominated by the family of AP2 transcription factors (TFs), such as the AP2-G TF, which drives sexual commitment. The same authors previously identified one AP2 TF, called AP2-FG, as an essential TF mediating differentiation of female gametocytes. Here, they identified a novel protein, called PFG (for partner of AP2-FG), which cooperates with AP2-FG to regulate a subset of female gametocyte genes.

PFG was identified among AP2-G targets, but possesses no known DNA binding or other characterized domain. The authors show that PFG-knockout P. berghei parasites can form male and female gametocytes yet cannot transmit to mosquitoes, due to a defect in female gametocyte development. Using RNA-seq, they show that many female-specific genes are down-regulated in PFG(-)parasites. Chromatin immunoprecipitation combined with DNA sequencing (ChIP-seq) revealed that PFG colocalizes with AP2-FG on a ten-base motif that is enriched upstream of female-specific genes. Importantly, the ChIP-seq profile of PFG is unchanged in the absence of AP2-FG, suggesting that PFG binds to DNA independently of AP2-FG. Mutation of the ten-base motif in one target gene using CRISPR-Cas9 demonstrates that this motif is required for PFG localization at the gene locus. The data also show that binding of AP2-FG is affected in the absence of PFG, with disruption of AP2-FG interaction with the ten-base motif, but conservation of AP2-FG binding to distinct five-base motifs. Using a recombinant AP2 domain from AP2-FG, the authors demonstrate that the AP2 domain of AP2-FG binds to the five-base motifs. Using CRISPR they show that disruption of the five-base motifs in the genome abrogates AP2-FG binding, and using a reporter expression system they confirm that these motifs act as a cis-activating promoter element.

Through the analysis of target genes based on the presence of the ten- versus five-base motifs, the authors propose a model where AP2-FG can function in two forms, associated or not with PFG, and acting on the ten- or five-base motifs, respectively, to regulate distinct gene subsets during development of female gametocyte development.

The paper is very well written, with a clear narrative, and the work is very well performed, relying on robust molecular approaches. Generally the conclusions and the model proposed by the authors are well supported by the data. Nevertheless, the study as it stands raises a number of questions. First, it is unclear how the authors selected PFG as a candidate protein as the protein lacks any known DNA binding or regulatory domain. Detailing the reasoning that led to the identification of PFG would make the entire study more appealing. While the data convincingly show that PFG and AP2-FG cooperate to regulate the expression of a subset of female-specific genes, the paper does not show whether the two proteins actually interact with each other to form a complex. Finally, how PFG binds to DNA and whether the protein has transactivating activity remains elusive, as the protein apparently possesses no known DNA-binding or activating domain. These points could be discussed in more detail in the manuscript and/or be the subject of follow up studies.

In summary, this work reveals the essential role of a Plasmodium protein with no known DNA binding or regulatory domain, illustrating that unknown facets remain to be uncovered in this fascinating pathogen.

Reviewer #1 (Public Review):

Thermogenic adipocyte activity associate with cardiometabolic health in humans, but decline with age. Identifying the underlying mechanisms of this decline is therefore highly important.

To address this task, Holman and co-authors investigated the effects of two major determinants of thermogenic activity: cold, which induce thermogenic de novo differentiation as well as conversion of dormant thermogenic inguinal adipocytes: and aging, which strongly reduce thermogenic activity. The authors study young and middle-aged mice at thermoneutrality and following cold exposure.

Using linage tracing, the authors conclude that the older group produce less thermogenic adipocytes from progenitor differentiation. However, they found no differences between thermogenic differentiation capacity between the age groups when progenitors are isolated and differentiated in vitro. This finding is consistent with previous findings in humans, demonstrating that progenitor cells derived from dormant perirenal brown fat of humans differentiate into thermogenic adipocytes in vitro. Taken together, this underscores that age-related changes in the microenvironment rather than autonomous alterations in the ASPCs explain the age related decline in thermogenic capacity, This is an important finding in terms of identifying new approaches to switch dormant adipocytes into an active thermogenic phenotype.

To gain insight into the age-related changes, the authors use single cell and single nuclei RNA sequencing mapping of their two age groups, comparing thermoneutral and cold conditions between the two groups. Interestingly, where the literature previously demonstrated that de novo lipogenesis (DNL) occurs in relation to thermogenic activation, the authors show that DNL in fact is activated in a white adipocyte cell type, whereas the beige thermogenic adipocytes form a separate cluster.

Considering recent findings, that adipose tissue contains several subtypes of ASPCs and adipocytes, mapping the changes at single cell resolution following cold intervention provides an important contribution to the field, in particular as an older group with limited thermogenic adaptation is analyzed in parallel with a younger, more responsive group. This model also allowed for detection of microenvironment as a determining factor of thermogenic response.

The use of only two time points (young and middle-aged) along the aging continuum limits the conclusions that can be made on aging as the only driver of the observed differences between the groups. It should for example be noted that the older mice had higher weights and larger fat depots, thus the phenotype is complex and this should be taken into consideration when interpreting the data.

In conclusion, this study provides an important resource for further studies on how to reactivate dormant thermogenic fat and potentially improve metabolic health.

Reviewer #1 (Public Review):

The proposed study provides an innovative framework for the identification of muscle synergies taking into account their task relevance. State-of-the-art techniques for extracting muscle interactions use unsupervised machine-learning algorithms applied to the envelopes of the electromyographic signals without taking into account the information related to the task being performed. In this work, the authors suggest including the task parameters in extracting muscle synergies using a network information framework previously proposed. This allows the identification of muscle interactions that are relevant, irrelevant, or redundant to the parameters of the task executed.

The proposed framework is a powerful tool to understand and identify muscle interactions for specific task parameters and it may be used to improve man-machine interfaces for the control of prostheses and robotic exoskeletons.

With respect to the network information framework recently published, this work added an important part to estimate the relevance of specific muscle interactions to the parameters of the task executed. However, the authors should better explain what is the added value of this contribution with respect to the previous one, also in terms of computational methods.

In general, the method proposed relies on several hyperparameters and cost functions that have been optimized for the specific datasets. A sensitivity analysis should be performed, varying these parameters and reporting the performance of the framework.

It is not clear how the well-known phenomenon of cross-talk during the recording of electromyographic muscle activity may affect the performance of the proposed technique and how it may bias the overall outcomes of the framework.

Reviewer #1 (Public Review):

Despite numerous studies on quinidine therapies for epilepsies associated with GOF mutant variants of Slack, there is no consensus on its utility due to contradictory results. In this study Yuan et al. investigated the role of different sodium selective ion channels on the sensitization of Slack to quinidine block. The study employed electrophysiological approaches, FRET studies, genetically modified proteins and biochemistry to demonstrate that Nav1.6 N- and C-tail interacts with Slack's C-terminus and significantly increases Slack sensitivity to quinidine blockade in vitro and in vivo. This finding inspired the authors to investigate whether they could rescue Slack GOF mutant variants by simply disrupting the interaction between Slack and Nav1.6. They find that the isolated C-terminus of Slack can reduce the current amplitude of Slack GOF mutant variants co-expressed with Nav1.6 in HEK cells and prevent Slack induced seizures in mouse models of epilepsy. This study adds to the growing list of channels that are modulated by protein-protein interactions, and is of great value for future therapeutic strategies.

I have a few comments with regard to how Nav1.6 sensitize Slack to block by quinidine.

It is not clear to me if the Slack induced current amplitude varies depending on the specific Nav subtype. To this end, it would be valuable to test if Slack open probability is affected by the presence of specific Nav subtypes. Nav induced differences in Slack current amplitude and open probability could explain why individual Nav subtypes show varied ability to sensitize Slack to quinidine blockade.

It has previously been shown that INaP (persistent sodium current) is important for inducing Slack currents. Here the authors show that INaT (transient sodium current) of Nav1.6 is necessary for the sensitization of Slack to quinidine block whereas INaP surprisingly has no effect. The authors then show that the N-tail together with C-tail of Nav1.6 can induce same effect on Slack as full-length Nav1.6 in presence of high intracellular concentrations of sodium. However, it is not clear to me how the isolated N- and C-tail of Nav1.6 can induce sensitization of Slack to quinidine by interacting with C-terminus of Slack, while sensitization also is dependent on INaT. The authors speculate on different slack open conformation, but one could speculate if there is a missing link, such as an un-identified additional interacting protein that causes the coupling.

Reviewer #1 (Public Review):

With genephys, the author provides a generative model of brain responses to stimulation. This generative model allows mimicking of specific parameters of a brain response at the sensor level, to test the impact of those parameters on critical analytic methods utilized on real M/EEG data. Specifically, they compare the decoding output for differently set parameters to the decoding pattern observed in a classical passive viewing study in terms of the resulting temporal generalization matrix (TGM). They identify that the correspondence between the mimicked and the experimental TGM depends on an oscillatory component that spans multiple channels, frequencies, and latencies of response; and an additive, slower response with a specific (cross-frequency) relation to the phase of the oscillatory, faster component.

A strength of the article is that it considers the complexity of neural data that contributes to the findings obtained in stimulation experiments. An additional strength is the provision of a Python package that allows scientists to explore the potential contribution of different aspects of neural signals to obtained experimental data and thereby to potentially test their theoretical assumptions critical parameters that contribute to their experimental data.

A weakness of the paper is that the power of the model is illustrated for only one specific set of parameters, added in a stepwise manner and the comparison to on specific empirical TGM, assumed to be prototypical; And that this comparison remains descriptive. (That is could a different selection of parameters lead to similar results and is there TGM data which matches these settings less well.) It further remained unclear to me, which implications may be drawn from the generative model, following from the capacities to mimic this specific TGM (i) for more complex cases, such as the comparison between experimental conditions, and (ii) about the complex nature of neural processes involved.

Towards this end, I would appreciate (i) a more profound explanation of the conclusions that can be drawn from this specific showcase, including potential limitations, as well as wider considerations of how scientists may empower the generative model to (ii) understand their experimental data better and (iii) which added value the model may have in understanding the nature of underlying brain mechanism (rather than a mere technical characterization of sensor data).

Reviewer #1 (Public Review):

The paper by Dongsheng Xiao, Yuhao Yan and Timothy H Murphy presents a timely approach to record neuronal activity at multiple temporal and spatial scales. Such approaches are at the forefront of system neuroscience and a few examples include, among others, fMRI alongside electrophysiology (Logothetis et al, 2021. Nature) or widefield calcium imaging (Lake et al, 2020. Nat Meth) , or functional ultrasound imaging and multi unit recording (Claron et al, 2023 Cell Reports), The method presented here combines "low resolution" (i.e. cortical regions) widefield calcium imaging across most of the dorsal portions of the murine cortex combined with electrical recording of single neurons in specific cortical and subcortical locations (as a matter of fact, this later components can be used everywhere in the murine brain).

The method presented here is straightforward to implement and very well documented. Examples of novel insights that this approach can generate are well presented and demonstrate the strength of the presented approach, some aspects of the analysis require clarification.

For example, the author reveal Spike-Triggered average cortical activation Maps (STMs) linked to the activity of single neurons (Figs 4 and 5) This allows to directly asses the functional connectivity between cortical and sub-cortical areas. It nevertheless unclear what is the stability of the established relationships. The nature of the "recordings" in Fig 4. is unclear. It looks like these are imaging sessions on the same day, the length of these recordings as well as the interval between them is not stated. It will be fundamental to build a metric to compare STMs variability across sessions/recordings/days; a root-mean-square from an average map across all recordings could provide a starting point.

Also with respect to the STMs analysis, the data-driven choice of 10 clusters might need a bit more explorations. While the silhouette clustering accuracy peaks at 10 (Fig 5A), this metrics comes without a confidence intervals making it difficult to know if a difference of less than 10% (i.e. 11 or 13 clusters) should be deemed different. Maybe a bootstrapping approach could be used here to build such confidence intervals. Another approach to reach the number of cluster to use could be based on "consensus" between different partitioning algorithms (e.g. Strehl, A. & Ghosh, J. itions. J. Mach. Learn. Res. 3, 583-617 (2001). A much stronger argument should be provided to use the 0.3 correlation cutoff value which seems to be arbitrarily low. The main point here is that the authors should show that their conclusions hold within a range of parameter values (number of clusters and correlation threshold).

Reviewer #1 (Public Review):

In this study, Hoops et al. showed that Netrin-1 and UNC5c can guide dopaminergic innervation from nucleus accumbens to cortex during adolescence in rodent models. They found that these dopamine axons project to the prefrontal cortex in a Netrin-1 dependent manner and knocking down Netrin-1 disrupted motor and learning behaviors in mice. Furthermroe, the authors used hamsters, a seasonal model that is affected by the length of daylight, to demonstrate that the guidance of dopamine axons is mediated by the environmental factor such as daytime length and in sex dependent manner. While this study highlighted the important roles of two neurodevelopmental markers, netrin-1 and UNC5C, in the projection of dopaminergic azons in the adolescence/adult brain, the major weakness is that the data are quite superficial and do not establish any definitive evidence to support the causal relationship between the expression of netrin-1 and UNC5C in the projection of dopaminergic axons remain unclear.<br /> Below are several major concerns regarding the data presented in this manuscript:

1. Despite the well-established role of Netrin-1 and UNC5C axon guidance during embryonic commissural axons, it remains unclear which cell type(s) express Netrin-1 or UNC5C in the dopaminergic axons and their targets. For instance, the data in Figure 1F-G and Figure 2 are quite confusing. Does Netrin-1 or UNC5C express in all cell types or only dopamine-positive neurons in these two mouse models? It will also be important to provide quantitative assessments of UNC5C expression in dopaminergic axons at different ages.

2. Figure 1 used shRNA to knockdown Netrin-1 in the Septum and these mice were subjected to behavioral testing. These results, again, are not supported by any valid data that the knockdown approach actually worked in dopaminergic axons. It is also unclear whether knocking down Netrin-1 in the septum will re-route dopaminergic axons or lead to cell death in the dopaminergic neurons in the substantia nigra pars compacta?

3. Another issue with Figure1J. It is unclear whether the viruses were injected into a WT mouse model or into a Cre-mouse model driven by a promoter specifically expresses in dorsal peduncular cortex? The authors should provide evidence that Netrin-1 mRNA and proteins are indeed significantly reduced. The authors should address the anatomic results of the area of virus diffusion to confirm the virus specifically infected the cells in dorsal peduncular cortex.

4. The authors need to provide information regarding the efficiency and duration of knocking down. For instance, in Figure 1K, the mice were tested after 53 days post injection, can the virus activity in the brain last for such a long time?

5. In Figure 1N-Q, silencing Netrin-1 results in less DA axons targeting to infralimbic cortex, but why the Netrin-1 knocking down mice revealed the improved behavior?

6. What is the effect of knocking down UNC5C on dopamine axons guidance to the cortex?

7. In Figures 2-4, the authors only showed the amount of DA axons and UNC5C in NAcc. However, it remains unclear whether these experiments also impact the projections of dopaminergic axons to other brain regions, critical for the behavioral phenotypes. What about other brain regions such as prefrontal cortex? Do the projection of DA axons and UNC5c level in cortex have similar pattern to those in NAcc?

8. Can overexpression of UNC5c or Netrin-1 in male winter hamsters mimic the observations in summer hamsters? Or overexpression of UNC5c in female summer hamsters to mimic the winter hamster? This would be helpful to confirm the causal role of UNC5C in guiding DA axons during adolescence.

9. The entire study relied on using tyrosine hydroxylase (TH) as a marker for dopaminergic axons. However, the expression of TH (either by IHC or IF) can be influenced by other environmental factors, that could alter the expression of TH at the cellular level.

10. Are Netrin-1/UNC5C the only signal guiding dopamine axon during adolescence? Are there other neuronal circuits involved in this process?

11. Finally, despite the authors' claim that the dopaminergic axon project is sensitive to the duration of daylight in the hamster, they never provided definitive evidence to support this hypothesis.

Reviewer #1 (Public Review):

This paper describes the development and initial validation of an approach-avoidance task and its relationship to anxiety. The task is a two-armed bandit where one choice is 'safer' - has no probability of punishment, delivered as an aversive sound, but also lower probability of reward - and the other choice involves a reward-punishment conflict. The authors fit a computational model of reinforcement learning to this task and found that self-reported state anxiety during the task was related to a greater likelihood of choosing the safe stimulus when the other (conflict) stimulus had a higher likelihood of punishment. Computationally, this was represented by a smaller value for the ratio of reward to punishment sensitivity in people with higher task-induced anxiety. They replicated this finding, but not another finding that this behavior was related to a measure of psychopathology (experiential avoidance), in a second sample. They also tested test-retest reliability in a sub-sample tested twice, one week apart and found that some aspects of task behavior had acceptable levels of reliability. The introduction makes a strong appeal to back-translation and computational validity, but many aspects of the rationale for this task need to be strengthened or better explained. The task design is clever and most methods are solid - it is encouraging to see attempts to validate tasks as they are developed. There are a few methodological questions and interpretation issues, but they do not affect the overall findings. The lack of replicated effects with psychopathology may mean that this task is better suited to assess state anxiety, or to serve as a foundation for additional task development.

Reviewer #1 (Public Review):

Sensory neurons of the mechanosensory bristles on the head of the fly project to the sub esophageal ganglion (SEZ). In this manuscript, the authors have built on a large body of previous work to comprehensively classify and quantify the head bristles. They broadly identify the nerves that various bristles use to project to the SEZ and describe their region-specific innervation in the SEZ. They use dye-fills, clonal labelling, and electron microscopic reconstructions to describe in detail the phenomenon of somatotopy - conserved peripheral representations within the central brain - within the innervation of these neurons. In the process they develop novel tools to access subsets of these neurons. They use these to demostrate that groups of bristles in different parts of the head control different aspects of the grooming sequence.

Reviewer #1 (Public Review):

This important study reveals the structure of human STEAP2 for the first time and suggests the electron transport pathway, but some questions remain regarding the interpretation of the in vitro electron transport experiments, the lack of available redox couples, and potential alternative hypotheses that would if addressed, strengthen the claims in the manuscript.

Strengths

One of the clear strengths of the manuscript that stands out is the determination of the structure of human STEAP2. The structures of some other homologs are known, but STEAP2's structure was not, and STEAP2 seems to have an unusually low activity towards certain metal chelates. The approach of producing the human STEAP2 in insect cells with the supplementation of cofactor biogenesis components nicely results in cofactor-replete protein. The structure of STEAP2 reveals a domain-swapped trimer, with the NADPH-binding domain of the neighboring protomer within electron-transport distance of the FAD-heme axis. The FAD has an interesting and somewhat unusual extended conformation and abuts a Leu residue that may regulate electron transport. Another strength of the manuscript is the demonstration that STEAP1, which does not have the internal NADPH binding domain, can interact modestly and shuttle electrons to the heme in STEAP1 through FAD. These experiments nicely expand information on the function of STEAP1 and provide a structural basis for electron transport in STEAP2.

Weaknesses

A major weakness in the manuscript lies with the kinetics data and how the data, as presented, are unclear to the reader regarding their impact and their connection to the purported electron transport scheme. While multiple sets of data are reported, the analysis in all cases is simply the reduction of a hexacoordinate heme and its related spectra and kinetic parameters. In most cases, it's unclear to the reader which part of the electron pathway is being tested in which experiment. Simple diagrams would be helpful in each case. However, it's also unclear if all of the potential order of addition experiments were actually performed; i.e., flavin but no NADPH; NADPH but no flavin; flavin before NADPH; flavin after NADPH, etc. As there are multiple permutations that should be tested to demonstrate the electron transport pathway, presenting the data in a way that makes it clear to the reader is challenging. Particularly missing are the determined redox potentials of the hemes in both STEAP1 and STEAP2. Could differences in these heme redox potentials be drivers of the difference in metal reduction rates? Also, the text indicates that STEAP2 does not show a reduction rate dependence on the [Fe3+-NTA], but Figure 1A shows a difference in rates dependent on [Fe3+-NTA], and the shape of the reduction curve also changes based on [Fe3+-NTA]. This discrepancy should be rectified.

A second major weakness is the lack of any verification of the relevance of the STEAP2 oligomerization to its in vivo function. Is the same domain-swapped trimer known to exist in vivo? If the protein were prepared in other detergents, is the oligomerization preserved? It is alluded to in the text that another STEAP protein is also a trimer. Was this oligomerization verified in vivo? Could this oligomerization be disrupted to impede or abrogate electron transport to underscore the oligomerization relevance? This point is germane, as it would further suggest that the domain-swapped trimer observed in the STEAP2 cryo-EM structure is physiologically relevant, especially given how far the distance between the NADPH and the FAD would otherwise be to support electron transport.

Beyond these two areas in which the manuscript could be improved there are a couple of minor considerations. First, the modest resolution of the STEAP2 structure prevents assigning the states of NADP+/NADPH and FAD/FADH2 with confidence. An orthogonal measure would be useful for modeling the accurate states in the structure. Finally, the BLI b5R/STEAP1 binding/unbinding fits seem somewhat poor, especially at high concentrations of b5R in the dissociation regime, which likely influences the derived value of Kd. A different fitting equilibrium might yield better agreement between the experimental and theoretical results. Moreover, whether this binding strength is influenced by the reduction state of the NADPH would be helpful in understanding and contextualizing the weak binding affinity.

this could help me

Reviewer #1 (Public Review):

This study aims to identify the existence of hedonic feeding and to distinguish it from homeostatic feeding, in Drosophila. The authors use direct observation of feeding events, a novel automated feeding event detector, inventive behavioral assays, and genetics to separate out the ways that the Drosophila interacts with food. Using two choice assays, the authors find an increased duration of interactions with high-concentration sugars under conditions of expected satiety, which is considered to be hedonic feeding.

The technical advances in the measurement of animal interactions with food will help advance the understanding of feeding behavior and motivational states. The correlation of specific types of food interactions across satiation state, sex, and circadian time will help drive forward the understanding of the scope of an animal's goals with feeding, and likely their relation between species and eating disorders. The assessment of mushroom body circuitry in a type of food interaction is helpful for understanding the coding of feeding control in the brain.

The bulk of the feeding data presented in the manuscript are from the interactions of individual flies with a source of liquid food, where interaction is defined as 'physical contact of a specific duration.' Although the assay they use allows for measurements to be made at high temporal resolution, the authors include some data showing that solid food consumption follows the same trend.

Reviewer #1 (Public Review):

The authors use a combination of crop modeling and field experiments to argue that drought during seedling establishment likely severely impacts the yield of pearl millet, an important but understudied cereal crop, and that rapid seedling root elongation could play a major role in mitigating this. They further argue that this trait has a strong genetic basis and that major polymorphisms in candidate genes can be identified using standard methods from modern genetics and genomics. Finally, they use homology with the model plant Arabidopsis thaliana to argue that the function of one putatively causal gene is to regulate root cell elongation.

The major strength of this paper is that it convincingly demonstrates how modern methods from plant breeding and model organisms can be combined to address questions of great practical importance in important but poorly understood crops. The notion that it is possible to connect single-locus polymorphism and cellular biology to drought tolerance and crop yield in pearl millet is not a trivial one.

The weakness is obvious: while the argument made is convincing, it must be recognized that the strength of the evidence is by no means of the level expected in a model organism. Conclusions could easily be wrong, and there is no direct evidence that regulatory variation in PgGRXC9 leads to higher crop yield via cell elongation and seedling drought tolerance. However, generating such evidence in a poorly studied crop would be a monumental undertaking, and should probably not be the priority of people working on pearl millet!

The utility of this work is that it suggests that it is practicable to gain valuable insight into crop adaptation by clever use of modern methods from a variety of sources.

Reviewer #1 (Public Review):

Specifically controlling the level of proteins in bacteria is an important tool for many aspects of microbiology, from basic research to protein production. While there are several established methods for regulating transcription or translation of proteins with light, optogenetic protein degradation has so far not been established in bacteria. In this paper, the authors present a degradation sequence, which they name "LOVtag", based on iLID, a modified version of the blue-light-responsive LOV2 domain of Avena sativa phototropin I (AsLOV2). The authors reasoned that by removing the three C-terminal amino acids of iLID, the modified protein ends in "-E-A-A", similar to the "-L-A-A" C-terminus of the widely used SsrA degradation tag. The authors further speculated that, given the light-induced unfolding of the C-terminal domain of iLID and similar proteins, the "-E-A-A" C-terminus would become more accessible and, in turn, the protein would be more efficiently degraded in blue light than in the dark.

Indeed, several tested proteins tagged with the "LOVtag" show clearly lower cellular levels in blue light than in the dark. While the system works efficiently with mCherry (10-20x lower levels upon illumination), the effect is rather modest (2-3x lower levels) in most other cases. Accordingly, the authors propose to use their system in combination with other light-controlled expression systems and provide data validating this approach. Unfortunately, despite the claim that the "LOVtag" should work faster than optogenetic systems controlling transcription or translation of protein, the degradation kinetics are not consistently shown; in the one case where this is done, the response time and overall efficiency are similar or slightly worse than for EL222, an optogenetic expression system.

The manuscript and the figures are generally very well-composed and follow a clear structure. The schematics nicely explain the underlying principles. However, limitations of the method in its main proposed area of use, protein production, should be highlighted more clearly, e.g., (i) the need to attach a C-terminal tag of considerable size to the protein of interest, (ii) the limited efficiency (slightly less efficient and slower than EL222, a light-dependent transcriptional control mechanism), and (iii) the incompletely understood prerequisites for its application. In addition, several important controls and measurements of the characteristics of the systems, such as the degradation kinetics, would need to be shown to allow a comparison of the system with established approaches. The current version also contains several minor mistakes in the figures.

Joint Public Review:

The manuscript presented by Pabba et al. studied chromatin dynamics throughout the cell cycle. The authors used fluorescence signals and patterns of GFP-PCNA (GFP tagged proliferating cell nuclear antigen) and CY3-dUTP (which labels newly synthesized DNA but not the DNA template) to determine cell cycle stages in asynchronized HeLa (Kyoto) cells and track movements of chromatin domains. PCNA binds to replication forks and form replication foci during the S phase. The major conclusions are: (1) Labeled chromatin domains were more mobile in G1/G2 relative to the S-phase. (2) Restricted chromatin motion occurred at sites in proximity to DNA replication sites. (3) Chromatin motion was restricted by the loading of replisomes, independent of DNA synthesis. This work is based on previous work published in 2015, entitled "4D Visualization of replication foci in mammalian cells corresponding to individual replicons," in which the labeling method was demonstrated to be sound. Although interesting, reduced chromatin mobility in S relative to G1 phase is not new to the field. The genome in HeLa cells is greatly abnormal with heterogeneous aneuploidy, which makes quantification complicated and weakens the conclusions.

Reviewer #1 (Public Review):

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

As pointed out by the authors themselves, the fact that temperature was not included as a variable, which would make the experimental design much more complex, misses the opportunity to more accurately reflect the environmental conditions that the colonizer individuals face at high altitude. Also pointed out by the authors, the acclimation experiment in hypoxia lasted 4 weeks. It is possible that longer term effects would be identifiable in gene expression in the lowland individuals facing hypoxia on a longer time scale. Furthermore, a sample size of 3 or 4 individuals per group depending on the tissue for wild individuals may miss some of the natural variation present in these populations. Stating that they have a n=7 for the plastic stage and n= 14 for the ancestral and colonized stages refers to the total number of tissue samples and not the number of individuals, according to supplementary table 1. Finally, I could not find a statement indicating that the lowland individuals placed in hypoxia (plastic stage) were from the same population as the lowland individuals for which transcriptomic data was already available, used as the "ancestral state" group (which themselves seem to come from 3 populations Qinghuangdao, Beijing, and Tianjin, according to supplementary table 2) nor if they were sampled in the same time of year (pre reproduction, during breeding, after, or if they were juveniles, proportion of males or females, etc). These two aspects could affect both gene expression (through neutral or adaptive genetic variation among lowland populations that can affect gene expression, or environmental effects other than hypoxia that differ in these populations' environments or because of their sexes or age). This could potentially also affect the FST analysis done by the authors, which they use to claim that strong selective pressure acted on the expression level of some of the genes in the colonised group.

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

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

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

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

Reviewer #1 (Public Review):

In this paper, authors used IL-33KO and ILC2KO mice to generate evidence for pregnancy specific enrichment of ILC2s and their unique molecular signatures. They documented that uterine ILC2s are distinct from the ILC2s residing in lung and lymph nodes. They have provided solid evidence that although litter size did not change, but fetuses from ILC2KO mice showed growth restriction. In the absence of ILC2s, LPS injections lead to increased abortion rates and fetal loss suggesting the critical role of ILC2s in protection against infection induced pathology. Most of the results presented in the paper support the conclusion, but in some instances the evidence is indirect. Some clarifications on experimental interpretations are required as below.

• The immunohistology experiments revealed that IL-33 predominately co-localizes with ILC2 in the myometrium, but the staining appears to be diffused throughout the myometrium. It is difficult to pinpoint ILC2 specific IL-33 colocalization. Is the decidual expression of IL-33 largely restricted to ILC2s? Also, IL-33 is produced by a variety of other cell types including endothelial cells, which is difficult to ascertain from the images in Fig 1.<br /> • Authors report that ILC2s are responsible for fetal growth restriction (FGR) noted in the ILC2 KO mice. They attribute FGR to utero-placental abnormalities but the experimental evidence, including spiral arterial remodelling and glucose transporter gene expression are indirect. Is there any compensation from other cell types such as macrophages in the absence of ILC2s as they reported increased dendritic cells, neutrophils, and macrophages in ILC2KO mice. Clarify whether IL-33 levels were consistent between WT and ILC2KO mice. How do these other increased numbers of macrophages, DCs and neutrophils fit in the FGR context besides gene expression changes they captured in DCs and macrophages.<br /> • They captured spiral arterial wall to lumen ratio alterations in ILC2KO mice suggesting sub-optimal vascular changes in ILC2KO mice. They did not find any changes in the uNK cells or IFN-production between WT and ILC2KO. What would be the mechanistic link between ILC2 and spiral arterial vascular changes. They indirectly link it to the IL1B gene expression.<br /> • In the LPS induced abortion in ILC2 KO mice experiments, how do they reconcile the predominant role of macrophages and LPS induced TNF-a in the pathology? They did not find any differences in the gene expression in the LPS induced signature cytokine, TNF-a despite increased numbers of macrophages in ILC2 KO mice. Clarification is required on whether these inflammatory alterations that they captured directly linked to utero-placental insufficiency between WT and ILC2KO. The type 2 cytokines were barely detectable in ILC2KO mice, which likely predispose them for utero-placental alterations.

Reviewer #1 (Public Review):

In this study Guss and colleagues identify a requirement of the ECM component Perlecan for the maintenance of neuronal structures. The authors convincingly demonstrate that the absence of Perlecan (in the entire organism) causes a severe perturbation of the ECM-based neural lamella, a support structure surrounding axon bundles and, to a lesser extent, the neuromuscular junction (NMJ). Likely because of these ECM perturbations, axons and even entire nerve bundles break at sites prior to the innervation of the peripheral muscles. Within hemisegments all affected motoneurons show signs of degeneration and synapses are retracted (degenerate). Through targeted genetic approaches in combination with immunohistochemical and electrophysiological approaches the authors aim to elucidate cell specific requirements of Perlecan. Interestingly, knock down of Perlecan in single tissues but also in combinations of tissues (neurons, glia and muscles) was not sufficient to recapitulate the phenotypes observed after ubiquitous knock down. Similarly, a rescue of these phenotypes via motoneuron expression in null mutants was not successful.

The authors very convincingly demonstrate that in the absence of Perlecan synaptic terminals degenerate and that axon and neural lamella morphology and structure is perturbed. All processes were analyzed using multiple and complementary approaches including live-imaging and electrophysiology. The precise correlation of these phenotypes and especially the careful classification into degenerated and non-affected NMJs revealed that the cause for all phenotypes is likely the disruption of the neural lamella that - through thus far unknown mechanisms - cause axonal breakage and subsequently synaptic retractions.

This study highlights the importance of the ECM to maintain neuronal structures, however, the precise source of Perlecan and the precise cause of axonal breakage remains still unresolved.

Further rescue experiments would be necessary to resolve the source of Perlecan. This requires a first demonstration that a rescue is possible with the available tools using a ubiquitous-expression analogous to the RNAi-experiments.<br /> In addition, a careful longitudinal analysis of the integrity of individual axons (e.g. MN1 or MN4) combined with an ECM analysis may provide insights into the place and cause of the axonal breakages that are likely causal for all other observed phenotypes. As pointed out in the discussion a disruption of the blood-brain barrier at specific (?) vulnerable sites seems currently the most reasonable explanation for the observed effects. Surprisingly, the authors did not observe any rescue effect after the inhibition of Wallarian degeneration mechanisms highlighting that the cellular mechanisms underlying these two forms of degeneration in which axons are disrupted may be different.

Reviewer #1 (Public Review):

We conclude that this descriptive study has some strengths but additionally, we propose several ways in which to increase its potential impact and to strengthen some of the claims. This study describes the remodeling of Merkel cells and their innervating sensory axons in the skin. By using transgenic mouse lines in which these cells were genetically fluorescently labeled, the authors performed a series of analyses mostly focusing on the number and location of Merkel cells and the sensory axons that innervate them.

One of the major strengths of the study is the establishment of intravital imaging techniques to investigate the dynamic simultaneous behavior of Merkel cells and their innervation during homeostasis and hair regeneration. However, how the findings integrate into the existing knowledge of skin development is unfortunately only partially addressed.

To the best of our understanding, a few technical limitations of the study define its major weaknesses: First, Merkel cell loss is dramatic and it's unclear whether this reduction is part of a developmentally controlled reduction in cell number, or whether additional cells are expected to be integrated into the system. Longer windows of imaging might help here. Second, the depilation agent might be too aggressive and lead to cell death and thus better controls might be suggested. Similarly, ablating Merkal cells throughout development might cause developmental issues that might mask the proposed homeostasis analyses. A controlled adult specific ablation might be suggested. Finally, the TrkC based transgenic mouse is expected to be heterozygous - could that be an issue? Either better controls, or a textual addressing of this topic are advised.

All in all, we think this study has the potential to establish a high resolution description of Merkel cells - sensory axon dynamic interactions. We hope that the authors will be encouraged to improve the paper based on our comments, something that will likely improve its potential significance and impact.

Reviewer #1 (Public Review):

In the manuscript, the authors tried to explore the molecular alterations of adipose tissue and skeletal muscle in PCOS by global proteomic and phosphorylation site analysis. In the study, the samples are valuable, while there are no repeats for MS and there are no functional studies for the indicted proteins, phosphorylation sites. The authors achieved their aims to some extent, but not enough.

Reviewer #1 (Public Review):

In the submitted manuscript, Port et al. investigated the host and viral factors influencing the airborne transmission of SARS-CoV-2 Alpha and Delta variants of concern (VOC) using a Syrian hamster model. The authors analyzed the viral load profiles of the animal respiratory tracts and air samples from cages by quantifying gRNA, sgRNA, and infectious virus titers. They also assessed the breathing patterns, exhaled aerosol aerodynamic profile, and size distribution of airborne particles after SARS-CoV-2 Alpha and Delta infections. The data showed that male sex was associated with increased viral replication and virus shedding in the air. The relationship between co-infection with VOCs and the exposure pattern/timeframe was also tested. This study appears to be an expansion of a previous report (Port et al., 2022, Nature Microbiology). The experimental designs were rigorous, and the data were solid. These results will contribute to the understanding of the roles of host and virus factors in the airborne transmission of SARS-CoV-2 VOCs.

Reviewer #1 (Public Review):

Holzinger et al. investigated potential antimicrobial compounds for cystic fibrosis (CF) infection with similarity to a host-derived antimicrobial, bactericidal permeability-increasing protein (BPI). Human BPI (huBPI) is neutralised by anti-BPI antibodies, rendering it ineffective at eradicating Pseudomonas aeruginosa infection in a large proportion of people with cystic fibrosis. BPI produced by mice (muBPI), scorpionfish (scoBPI), and oysters (oyBPI) was evaluated on their anti-inflammatory, bactericidal, and immunogenic potency. The authors showed that each BPI orthologue evaded recognition by anti-BPI. The cationic BPI orthologues also reduced bacterial burden in vitro, reducing the expression of proinflammatory cytokines (IL-6 and TNF) and significantly decreasing cell culture density in the laboratory and multidrug-resistant P. aeruginosa strains. ScoBPI was the most potent, with greater anti-inflammatory and bactericidal activity than huBPI and all other orthologues.

This study investigates the action of BPI orthologues as potential CF antimicrobials. While scoBPI appears significantly more effective as an anti-inflammatory and bactericidal agent compared to huBPI, the orthologue has not been tested in environments that model the CF lung environment. The authors describe the cationic BPI as binding to the LPS via electrostatic interaction. This interaction could be limited in vivo, as anionic extracellular DNA, cationic metal ions and polyamines, and other charged substances may impede interaction. Further, delivery of scoBPI to the infection site may be detrimentally impacted, due to the viscous mucous in the lungs and the biofilm mode of growth of P. aeruginosa. The discussion of the study could be improved by describing important considerations for future development. These could include in vitro testing against P. aeruginosa biofilms in relevant sputum-mimicking media, and in vivo validation in Galleria mellonella, and CF and non-CF mouse models.

Overall, the authors present an interesting study that provides a compelling basis for a potential novel antimicrobial for CF chronic airway infection. The authors' claims are well supported by their data, which they present in a clear, logical manner. To build on these findings, the authors could test scoBPI in models that recapitulate core factors of the CF environment.

Reviewer #1 (Public Review):

In the present study, Yasuko Isoe, Ryohei Nakamura & colleagues follow a lineage analysis study aiming at identifying the clonal organization of the dorsal telencephalon. The authors use the teleost fish medaka to conduct their experiments since it displays a clearly delineated dorsal pallium. After identifying the clonal units that constitute the dorsal telencephalon, they analyze the epigenetic landscape in each unit. The authors identify then differential open chromatin patterns that they relate to functional aspects of each unit, and additionally, use the epigenetic landscape to infer the identity of transcription factors operating as putative regulators. Overall, the study consists of an impressive amount of data that shed light on the organization of a central brain region in vertebrates.

The findings in the manuscript are organized into two main sections: lineage analysis and epigenetic organization. The authors combine genetic tools with laser dissections of specific clones and ATAC-seq and RNA-seq analysis in multiple samples, an approach that is very elegant and follows high technical standards. For lineage analysis, the authors used a basic, but appropriate, tool to induce and follow clones generated in early embryos, with the side note that lineages are followed using a non-ubiquitous promoter so that the authors restrict their analysis to neural progenitors. My overall impression is that the authors have collected a massive amount of high-quality data, which unfortunately is not properly integrated or discussed in the manuscript. There is only a superficial effort in incorporating the two main findings, which contrasts with the depth of acquired data.

The observation of clonal sectors in the pallium is a great finding that deserves a more detailed analysis in terms of their developmental and evolutionary origin: How may progenitors are used to set up the entire pallium? What is the smallest clone that contributes to it? Is there any laterality bias in the clonal architecture? Is the clonal architecture exclusive for progenitors or does it extend to neurons as well? How has the clonal architecture impacted the morphological diversity of the pallium among teleosts? What are possible evolutionary paths to explain this phenomenon? The authors' discussion on this point circles around one concept, illustrated in the following sentence: " (The clonal architecture) ... possibly explains how the difference in diversity between the pallium and subpallium has emerged: the subpallium is conserved because cells belong to various clonal units intertwined with each other, which has constrained their modification during evolution; whereas the pallium is diverse because of the modular nature of the clonal units which allows for the emergence of diversity". This is the concept that I have the most problems with. The authors' reason that a more defined clonal structure (pallium) makes a system more prone to evolutionary novelties, while a region where clones intermingle (subpallium) is more rigid and therefore more conserved between species.  Is there experimental data that backs up this statement in any other systems? If there is, I urge the authors to share these here. If this is just a speculation, then the argument would benefit from an explanation of how this clonal organization allows for evolutionary novelty. Would it happen by the appearance of more clones at the early stages of development? The authors leave this central point untouched even when discussing the evolutionary origin of the pallium in teleosts.

Having shown the clonal architecture of the pallium and conducted a detailed epigenetic analysis in clones, the authors could also speculate on what is special about this type of organisation. Particularly, how they envision that cells belonging to the same clone inherit a common epigenetic landscape that will define their function later on. There is little analysis of the cellular organization of each clone, mainly because the authors labeled only a subset of the real, genetic clone. The authors present images of entire brains and optical horizontal and transverse sections, which largely sustain their claims for a clonal organization. The difference in the clonal arrangements between the Dld and the Vd is clear, but the authors could provide a higher-resolution image of some clones in the telencephalon to get an idea of the cellular composition of the regions they use for their analysis. What is the extent of non-GFP cells in the regions they use for RNAseq and ATACseq? From the images shown it is very difficult to realize whether all cells in the clonal sector do indeed belong to the clone.

Reviewer #1 (Public Review):

In this paper, the authors use patch-clamp recordings of immature (4w and 5w) and mature granule cells (GC) in hippocampal slices to study stimulus-response properties at different cell ages. First analyzing spike trains generated by a fluctuating stimulus, they show that the reliability of spiking responses increases with cell age. They then fit a Spike Response Model (SRM), a type of GLM that translates inputs to membrane potential and then membrane potential to spikes. Using this model they compare the model parameters from different cells. Time constants for the input-voltage filter are faster for the mDGCs than the 4w, with 5w intermediate, and time constants across all cells appear to be faster when reliability is higher. They analyze stimulus reconstruction and stimulus-response information using the recordings and then extend this to pseudo-populations to test how heterogeneous properties contribute to coding efficacy. They find that mixed pools of neurons, including cells of multiple ages, decode stimuli more accurately.

Overall, this is a cleverly designed study with sound methodology. A major contribution of the paper is demonstrating with precise, quantitative methods how a degree of heterogeneity that naturally arises in neural populations may be beneficial to decoding the stimulus, despite the fact that some of the heterogeneity arises from variability in single cells. This is an intriguing result showing how neural coding and decoding may actually benefit from heterogeneous response properties rather than only be hindered by variation.

The paper has a couple of weaknesses. First, it is difficult to assess how meaningful the effects that the authors measure are. For example, is a 3% improvement in decoding (Fig. 4H) with mixed populations of GCs substantial? A second issue not currently addressed in the paper is the relative roles of age-dependent variability and within-group variability: how much of the improvement in stimulus decoding/information encoding is achieved by heterogeneity across model parameters that appears in each age group? Further analyses and clarifications in this vein are suggested.

Reviewer #1 (Public Review):

This manuscript by Toshima et al. describes a study of the organization of traffic in the endomembrane system of the budding yeast Saccharomyces cerevisiae. The authors address the relation between endocytosis and the Golgi (TGN: a collection of maturing membrane elements derived from the trans-Golgi). The study builds on a previous article by the group of Benjamin Glick. In that study (Day et al., 2018), it was postulated that the TGN is the first destination for yeast endocytic traffic after internalization from the plasma membrane. Additionally, Day et al. had shown that endocytic recycling traffic towards the plasma membrane departs from the TGN as well. Therefore, early endosome and recycling endosome compartments would be identical to the TGN or contained within it. Here, Toshima et al. use super-resolution confocal live imaging microscopy (SCLIM) to refine a model of endocytic pathway organization. This powerful imaging technology allows them to show that out of two partially overlapping TGN markers, namely Tlg2 and Sec7, the syntaxin Tlg2 correlates better with the arrival of fluorescently labeled endocytic cargo than alternative TGN marker Sec7. Building on this main finding, the authors conclude that a specific part of the TGN (an "independent sub-compartment") functions as the early endosome. Further experiments in mutants for GGA clathrin adaptors, required for departure of endocytic cargo from the TGN to the Rab5-positive prevacuolar endosome, show again that endocytosed cargo accumulation correlates better with Tlg2 than with Sec7. Furthermore, in GGA mutants the overlap between Tlg2 and Sec7 is decreased, suggesting that GGA is required for maturation of this Tlg2 sub-compartment.

The study is well conducted and its main conclusion that a Tlg2 subregion within the TGN functions as the early endosome seems well supported by the superb live imaging and the analysis of GGA mutants.

Although a technical feat in live superresolution imaging, this single kind of data (moving, shape-shifting blobs of fluorescently-labeled proteins) does not totally fill with meaning the terms "compartment", "sub-compartment", or "independent sub-compartment". This, I think, is the main limitation of the study. Are these compartments or sub-compartments individuated membrane elements, collections of vesicles, regions of the same cisterna or saccule? For this, electron microscopy would be needed.