Reviewer #2 (Public Review):

The authors aim to test the hypothesis that dopamine mediates the evaluation of temporal costs in intertemporal choice in humans, with a specific goal of synthesizing the competing accounts and previous results regarding whether dopamine increases or decreases evaluation of delays in comparing differently delayed future rewards. To do this, they computationally dissect the impact of the drug amisulpride, a D2R antagonist, using a variant of a sequential sampling model, the drift-diffusion model (DDM), that is well established in decision-making literature as a cognitive process model of choice. This model allows the dissociation of starting bias from the rate at which decision evidence is integrated ('drift'), which the authors map to different accounts of the role of dopamine: the temporal proximity of an outcome is proposed to impact bias, while the cost of a delay to impact the drift rate of evidence evaluation/accumulation. Consistent with previous results, and perhaps integrating conflicting findings, the authors find that d2R blockade impacts both bias and drift rate in a cohort of 50 participants, demonstrating dopaminergic action at this receptor is implicated in dissociable components of intertemporal choice, with D2R block reducing the bias towards sooner, more temporally proximate rewards as well as enhancing the contrast between reward magnitudes irrespective of delay, effectively diminishing the effect of delay in the drug condition. These effects are consistent across a small subset of alternative models, confirming the multiple cognitive mechanisms through which D2R block impacts intertemporal choice is a robust feature of decisions on this task.

Overall, this study is a detailed dissection of the specific effects of amisulpride on a type of future-oriented, hypothetical intertemporal choice, and provides consistent evidence integrating conflicting accounts that implicate dopaminergic signaling on evaluation of the cognitive costs, such as a delay, on choice. However the specificity of the empirical intervention and the task design limits the interpretation of the broader dopaminergic mechanisms at play in intertemporal choice, especially given the complexity of receptor specificity of this drug, dopamine precursor availability and individual differences and the specifics of the intertemporal choice in this task. As it stands, the results contribute an interesting, synthesized account of how D2R manipulation can impact evaluation of delays in multiple ways, that will likely be useful for motivating future studies and more detailed computational assessments of the cognitive process-level components of intertemporal choice more generally.

The focus of this study is important, and delineating the role of DA in intertemporal choice is of high relevance given DA disfunction is prevalent in many psychiatric disorders and a key target of pharmacological treatment. While the hypotheses of the current study are framed with respect to "costs", the task used by the authors reduces these to evaluation of a hypothetical delay, one which the participants do not necessarily experience in the context of the task. In some respects this is reasonable, given the prevalence of this task paradigm in testing temporal aspects of choice in humans in an economic sense. However, humans are also notoriously subject to framing effects and the impact of instructions in cognitive tasks like these, which can limit the generality of the conclusions, and in particular the specific ways in which a delay can be interpreted as costly (for eg cost as loss of potential earnings, cost as effortful waiting, cost as computational/simulation cost in future evaluation). Given the hypothesis recruits the idea of cost in assessing the role of dopamine, testing for generality in the effects of amisulpride in related but differently framed tasks seems critical for making this link in a general sense, and in connecting it to the previous studies in the literature the authors point to as demonstrating conflicting effects.

Further, while the study aims to test the actions of dopamine broadly, the empirical manipulation is limited to the action of amisulpride, a D2R anatgonist. There is little to no discussion of, or control for, the relationship between dopaminergic action at D2 receptors (the site of amisulpride effects) and wider mechanisms of dopaminergic action at other sites eg D1-like receptors, and the interplay between activation at these two receptor types alongside baseline levels of dopamine concentration. This is necessary for a comprehensive account of dopamine effects on intertemporal choice as the authors aim to test, as opposed to a specific test of the role of the D2 receptor, which is what the study achieves. On a related note, in some preparations at least, amisulpride also acts at some of the 5-HT receptors, raising the possibility of a non-dopaminergic mechanism by which this drug might impact intertemporal decisions. This possibility, while it would not be expected to act without dopaminergic effects as well, is consistent with established effects of serotonin on waiting behaviors and patience. Granted, the limits of pharmacology in humans does not necessarily mean this can be controlled for, it should be kept in mind with a systemic manipulation such as this.

Overall the modeling methods are robust and appropriate for the specific test of decision impacts of D2R blockade, and include several prima facie variable alternative models for comparison. Some caution is warranted, since there are not many trials per subject, and some trials are discarded as well as outliers, which raises the question of power. Given the models are fit hierarchically, which gives both group-level and individual-level parameter estimates, the elements are there to probe more deeply into individual differences, and to test how reliably this approach can dissociate the dual effects of bias and drift rate at the individual level, and perhaps correlate it with other informative subject measures of either dopamine activity/capacity or other dopamine-dependent behaviors. Alternative DDMs might also capture some of this individual variation, with meaningful differences potentially in model comparison at the individual level. It should be noted that the scope of these models do not exhaust the ways in which proximity (here, temporal) of rewards and contrast between choice options might be incorporated into a cognitive process model account of choice; all alternatives here rest on the same implicit 2-alternative forced choice assumption of the DDM, and the assumptions of this model are not here tested against other accounts of choice, for example the linear ballistic accumulator (LBA) and its derivatives. Further, the concept of proximity as a global feature of a trial (on average, how soon are these options overall?) is never tested on my read of the alternative models.

Reviewer #2 (Public Review):

Richardson et al. characterize through immunophenotyping and high-throughput sequencing humanized mice versus human repertoires using many different immunological/immune repertoire metrics. They find that overall, the naïve Kymouse BCR repertoire is diverse and similar to human repertoires.

Strengths

Overall the study is carefully designed and of broad interest.<br /> - Detailed and established phenotypic and repertoire metrics are used to compare mice and human models.<br /> - Rigorous statistical analysis is mostly used to establish similarity.<br /> - Detailed description of the analyses performed.

Weaknesses

- Improvements could be made in the analyses (at times not far-reaching enough), figures (not self-explanatory enough), and text (too verbose).

Reviewer #2 (Public Review):

This manuscript presents a rather technical modelling analysis of the impact of local lockdowns on Covid-19 hospitalisations in the Netherlands. The major strength of the study is that the authors attempt to calibrate their model to a novel data source, a commercial database of mobility patterns between municipalities. The major weakness is that the model seems overly complicated, many parameters seem to have been 'guessed' without a formal uncertainty analysis, e.g. within a Bayesian framework, so that it is impossible to judge how robust the results and therefore the conclusions are.

Major points:

1) In some aspects the structure of the model presented seems overly complicated: It is not clear why the authors chose the 1:100 population scale and why they didn't go directly for modelling the full population. Artificially reducing the population size has important stochastic effects at the early phase of the epidemic. Also it is not clear what it means when 1:100 of one municipality mixes with 1:100 of another municipality? The authors should at least attempt to see what impact this has on output, i.e. conduct a sensitivity analysis.

2) On the other hand the model goes into (too) much detail regarding mixing behaviour and attempts to model processes during each hour of the day. This does not seem to be informed by actual data, but the data seems to be made up e.g. as in A.6. As an ex-student and a father of a teenager I can tell you that the susceptibility profile guessed in Table 3 does not seem to be very realistic. As it is stated in the appendix, the Mezuro data set only provides daily averages of travelling between communitities, so it is not clear why the hourly resolution is actually needed in the model.

3) It is not clear why the authors rely on only one short period of the Mezuro data set in March 2019 and not investigate the same data source during the actual lockdown in 2020, or even for the full year, as travelling is likely to be very season dependent. This would provide much better estimates of the effects of lockdown on travel patterns. The analysis presented and categorisation into frequent, regular and incidental also need further explanation. It is not clear how international travel is accounted for in the mobility data.

4) Beyond the technical points on the modelling, the main hypothesis of whether local lockdowns may work has also not been sufficiently discussed outside of the Dutch context. The authors fail to mention that this was the approach chosen in Northern Italy at the start of the epidemic (https://en.wikipedia.org/wiki/COVID-19_lockdowns_in_Italy) where it didn't work, as we all know. On the other hand, more recent local lockdowns in China appeared to be successful, albeit at a great societal cost in terms of restrictions to freedom (https://en.wikipedia.org/wiki/COVID-19_lockdown_in_China).

Reviewer #2 (Public Review):

The manuscript entitled "IL-4 and helminth infection downregulate Mincle-dependent macrophage response to mycobacteria and Th17 adjuvanticity" by Schick et al. demonstrate the inhibitory activity of IL-4 and helminth infection on mycobacteria-mediated Th17 immunity. Overall, the authors reported interesting findings with solid data that advance our understanding of CLR function in fungal-bacterial co-infection.

Reviewer #2 (Public Review):

Previous research using GWAS and population genetics approach identified a genetic haplotype on chromosome 3 derived from Neanderthals as the major risk factor for severe COVID-19. However, the specific variants that are causative of the severe COVID-19 phenotype remain unknown. Here, Jagoda et al. aim to identify the causative variants for the severe COVID-19 by leveraging eQTL analysis followed by Massively parallel reporter assays (MPRA). Their datasets and results are unique and novel. Their research is well designed, and will serve as a model strategy for future studies of functional annotation of disease-associated variants. However, there are following critical weaknesses in this manuscript that reduce the impact of this work; (1) The quantitativity of the MPRA output is questionable because of their incomplete definition of MPRA activity, which is based on absolute barcode counts without comparing negative controls. (2) Molecular mechanisms (binding transcription factors, etc.) of causative variants that underly the regulation of CCR1/5 expression and COVID19 severity are not analyzed and validated.

Reviewer #2 (Public Review):

The tongue muscles play a major role in many important behaviors including suckling, swallowing, and ensuring that the upper airway remains open during breathing. Hypoglossal motoneurons innervate tongue muscles and as such play a key role in homeostasis. Previous work has shown that heme-oxygenase-2 (HO-2) null mice have severe airway obstruction. HO-2 forms carbon monoxide, suggesting that CO contributes to hypoglossal motoneuron excitability. In addition to HO-2, the present study also shows that hypoglossal motoneurons express cystathionine ϒ-lyase (CSE), which produces H2S and is regulated by CO. Interestingly, the authors show that H2S reduced transmission of the breathing-related drive to hypoglossal motoneurons. Together these observations suggest that CO and H2S interact to maintain the excitability of hypoglossal motoneurons. An imbalance of these competing influences may underlie tongue muscle dysfunction in conditions such as obstructive sleep apnea and dysphagia. Thus, the novel observations reported here open new avenues that will lead to a better understanding of the highly complex tongue muscle motor system.

The team used brain stem slices containing hypoglossal motoneurons that were receiving rhythmic, breathing-related depolarizing drive from the pre-Botzinger complex, the putative respiratory central pattern generator. Extracellular population activity was recorded from the pre-Botzinger complex and the ipsilateral hypoglossal motor nucleus-and in some experiments-the hypoglossal premotor population located in the ipsilateral reticular formation. In these rhythmic slices, the fidelity between hypoglossal and pre-Botzinger bursts approached 100% and blocking HO-2 with drugs reduced fidelity by about 25%. In addition, HO-2 null mice showed an even larger reduction in pre-Botzinger-hypoglossal bursting fidelity of 40-45%. Since these interventions did not significantly impact the pre-Botzinger population activity, the data show convincingly that CO contributes to hypoglossal motoneuron excitability. While whole cell intracellular recordings of hypoglossal motoneurons showed that blocking HO-2 reduced the magnitude of inspiratory drive currents and the number of action potentials generated in response to the depolarizing drive, these effects were relatively modest, suggesting that the mechanisms that underlie these important observations are unsettled.

The other key part of these experiments was demonstrating that the H2S forming enzyme CSE is expressed in the hypoglossal nucleus, and that exogenous application of NaHS, an H2S donor, reduces the fidelity of pre-Botzinger-hypoglossal coupling. Interestingly, H2S activity was lower in HO-2 null mice, and HO-2-dependent uncoupling could be rescued by bath application of the CO donor CORM-3. Moreover, failed transmission between pre-Botzinger and hypoglossal population bursts was not observed in preparations from mice null for both HO-2 and CSE. These data support excitatory-inhibitory interactions that are triggered by the gases CO and H2S.

Mechanistic experiments showed that blockade of CSE with L552 propargylglycine could restore transmission fidelity, and this was accompanied by a substantial increase in the magnitude of inspiratory-related drive currents in hypoglossal motoneurons. The team also showed that blocking small-conductance potassium channels with apamin in slices where HO-2 was first blocked pharmacologically enhanced inspiratory drive currents, though this observation needs re-examination given that the effect was large in two neurons, but very small in the remaining four (Fig. 8 A3). Finally, similar experiments focused on the ATP-sensitive potassium channel (KATP), which was previously shown to be enhanced by H2S. Blockade of KATP with tolbutamide had no impact on hypoglossal motoneuron output. In conclusion, the experiments reveal a very important contribution of gas-mediated transmitters in setting the balance of excitation and inhibition of hypoglossal motoneuron excitability. More work will be needed to unravel the mechanisms behind these exciting observations.

Reviewer #2 (Public Review):

The authors performed preclinical studies to investigate the underlying mechanism of how the combination of pyrotinib, letrozole and dalpiciclib achieved satisfactory clinical outcomes in the MUKDEN 01 clinical trial (NCT04486911). Mechanistically, using anti-HER2 drugs such as pyrotinib and trastuzumab could degrade HER2 and facilitate the nuclear transportation of ER in HER2+HR+ breast cancer, which enhanced the function of ER signaling pathway. The introduction of dalpiciclib partially abrogated the nuclear transportation of ER and exerted its canonical function as cell cycle blockers, which led to the optimal cytotoxicity effect in treating HER2+HR+ breast cancer. Furthermore, using mRNA-seq analysis and in vivo drug susceptibility test, the authors succeeded in identifying CALML5 as a novel risk factor in the treatment of HER2+HR+ breast cancer.

Reviewer #2 (Public Review):

The purpose of this paper is to consider the utility of the long non-coding RNA PCA3, along with the gene PCA3 in the diagnosis of human prostate cancer. The study extends earlier findings by this group that the PRUNE2 gene product may function as a prostate tumor suppressor. The study employed two separate patient cohorts: one of 107 patients from the University of New Mexico Comprehensive Cancer Center, with organ-confined prostate cancer at their original diagnosis, and one of 497 patients with organ-confined prostate cancer from The Cancer Genome Atlas (TCGA). The authors report an overall increase in PCA levels along with a general decrease in PRUNE2 gene expression. The authors conclude that PRUNE2 functions as a prostate tumor suppressor whose levels negatively correlate with PCA3 levels. They further surmise that PCA3 in turn functions as a dominant-negative oncogene. Consequently, they expect that loss of increased PCA3 levels can lead to loss of PRUNE2 and increased prostate cancer tumor formation.

One interesting observation, consistent with earlier studies, is that PCA3 levels are highest in low-grade tumors, and then decrease as the tumors progress to a higher stage and grade. This suggests that increased PCA3 may be important for early tumor formation while possibly impeding tumor progression. The decreased PCA3 levels seen in later prostate cancer may, the authors hypothesize, be related to alterations in androgen receptor (AR) function in these higher-grade cancers. Thus, while the presence of PCA3 may be an early marker of prostate cancer formation, the results indicate that its presence in early cancers is not, by itself, predictive of future patient outcomes, as tumor progression may actually depend on the later decrease in PCA3 levels.

A strength of this study is the use of two non-redundant patient cohorts to thoroughly analyze the consequence of alterations in PRUNE2 and PCA3 by directly analyzing analyte levels in human tissue samples. The study provides important data supporting the occurrence of a loss of PRUNE2 and gain of PCA3 in organ-confined prostate cancer. The principal takeaway from this report is to highlight the role of the PRUNE2/PCA3 axis in early prostate cancer and to encourage the use of PCA3 antagonists in the prevention and treatment of early prostate cancer. It is unlikely that examination of tissue samples for alterations in PRUNE2 or PCA3 levels will be useful in prostate cancer diagnosis or prognosis as the data do not suggest that these changes in early cancers are predictive of future outcomes. It may be, however, that longitudinal analysis of PCA3 levels in patient plasma or circulating tumor cells could be a useful adjunct to follow the course of tumor progression.

Reviewer #2 (Public Review):

Dipeptide repeat (DPR) proteins produced from both sense GGGGCC (poly-GA, poly-GP and poly-GR) and antisense CCCCGG (poly-PR, poly-PG, poly-PA) repeat RNAs are found C9ORF72-linked ALS/FTD and contribute to neurodegeneration. The translation of the repeat RNA can initiate without the AUG start codon, a process known as repeat associated non-AUG (RAN) translation. In this manuscript, the authors used luciferase reporter construct to show that the translation of PR and PG from the CCCCGG repeats initiated from in-frame AUG in the C9 sequences before the repeats. After mutating candidate AUG codons, the translation can initiate from other AUG, so there is redundancy. But if mutating all the in-frame AUG codons, the luciferase was dramatically reduced, supporting the translation initiated at the AUG start codon. The translation initiation factor eIF2D has been shown to be important for CUG start codon-dependent poly-GA translation from GGGGCC repeats. Here it is shown that eIF2D is not required for poly-PG and poly-PR translation from CCCCGG repeats using both reporter and patient iPS-neurons. The data using luciferase reporter to study antisense repeat translation is solid, the translation initiates from AUG start codon as there are AUG in frame with PG and PR in the constructs containing the antisense sequences.

On the other hand, as the reporter construct includes the sequences containing the AUG codon, it is not surprising that AUG was used. This is canonical translation. Additionally, the AUG-initiated translation of antisense repeats has been reported previously. Therefore, the novelty is limited. How the antisense DPRs are translated endogenously, AUG-canonical translation or RAN translation, depends on whether the AUG is included in the antisense RNA in patients and where the transcription of the antisense starts, upstream or downstream of the AUG start codons. However, this is not considered in the manuscript.

Reviewer #2 (Public Review):

Convergence of cellular/molecular phenotypes across seemingly different types and subtypes of neurodevelopmental disorder represent an exciting frontier to identify effective drug targets. In this study, authors compared early neurodevelopmental processes, namely neurite outgrowth and migration, between a form of autism caused by copy number variation mutation in 16p11.2 (16pdel), which deletes 28 genes, to idopathic autism (I-ASD), in which genetic causes are unknown. All experiments involved neurospheres or neural precursor cells (NPCs) derived from human iPSCs. Three patients with I-ASD and their unaffected siblings as well as three patients with 16pdel were included in the study. Authors then go on to show perturbed migration and neurite length phenotypes shared between I-ASD and 16p11 NPCs. Interestingly they identified two subclasses of I-ASD patients, either with high or low levels of mTOR, and show that change in mTOR level in either direction result in similar migration and neurite extension phenotypes, either at baseline or induced by pro-migratory factors. The study design is particularly strong and communication of sample structure throughout the manuscript is commendable. This study effectively points to the potential of patient-derived in vitro models to uncover novel molecular drivers of disease. I only have a few comments below:

(1) I found that interpreting how differential EF sensitivity is connected to the rest of the story difficult at times. First, it is unclear why these extracellular factors were picked. These are seemingly different in nature (a neuropeptide, a growth factor and a neuromodulator) targeting largely different pathways. This limits the interpretation of the ASD subtype-specific rescue results. One way of reframing that could help is that these are pro-migratory factors instead of EFs broadly defined that fail to promote migration in I-ASD lines due to a shared malfunctioning of the intracellular migration machinery or cell-cell interactions (possibly through tight junction signaling, Fig S2A). Yet, this doesn't explain the migration/neurite phenotypes in 16p11 lines where EF sensitivity is not altered, overall implying that divergent EF sensitivity independent of underlying mTOR state. What is the proposed model that connects all three findings (divergent EF sensitivity based on ASD subtypes, 2 mTOR classes, convergent cellular phenotypes)?

(2) A similar bidirectional migration phenotype has been described in hiSPC-derived human cortical interneurons generated from individuals with Timothy Syndrome (Birey et al 2022, Cell Stem Cell). Here, authors show that the intracellular calcium influx that is excessive in Timothy Syndrome or pharmacologically dampened in controls results in similar migration phenotypes. Authors can consider referring to this report in support of the idea that bimodal perturbations of cardinal signaling pathways can converge upon common cellular migration deficits.

(3) Given that authors have access to 8 I-ASD hiPSC lines, it'd very informative to assay the mTOR state (e.g. pS6 westerns) in NPCs derived from all 8 lines instead of the 3 presented, even without assessing any additional cellular phenotypes, which authors have shown to be robust and consistent. This can help the readers better get a sense of the proportion of high-mTOR vs low-mTOR classes in a larger cohort.

(4) Does the mTOR modulation rescue EF-specific responses to migration as well (Figure 7)?

Reviewer #2 (Public Review):

The authors seek to determine how various species combine their effects on the growth of a species of interest when part of the same community.

To this end, the authors carry out an impressive experiment containing what I believe must be one of the largest pairwise + third-order co-culture experiments done to date, using a high-throughput co-culture system they had co-developed in previous work. The unprecedented nature of this data is a major strength of the paper. The authors also discover that species combine their effect through "dominance", i.e. the strongest effect masks the others. This is important as it calls into question the common assumption of additivity that is implicit in the choice of using Lotka-Volterra models.

A stronger claim (i.e. in the abstract) is that joint effect of multiple species on the growth of another can be derived from the effect of individual species. Unless I am misunderstanding something, this statement may have to be qualified a little, as the authors show that a model based on pairwise dominance (i.e. the strongest pairwise) does a somewhat better job (lower RMSD, though granted, not by much, 0.57 vs 0.63) than a model based on single species dominance. This is, the effect of the strongest pair predicts better the effect of a trio than the effect of the larger species.

This issue makes one wonder whether, had the authors included higher-order combinations of species (i.e. five-member consortia or higher), the strongest-effect trio would have predicted better than the strongest-effect pair, which in turn is better predictor than the strongest-effect species. This is important, as it would help one determine to what extent the strongest-effect model would work in more diverse communities, such as those one typically finds in nature. Indeed, the authors find that the predictive ability of the strongest effect species is much stronger for pairs than it is for trios (RMSD of 0.28 vs 0.63). Does the predictive ability of the single species model decline faster and faster as diversity grows beyond 4-member consortia?

While this may limit the scope of the paper somewhat, it does not subtract from its overall impressiveness. This is a very strong paper that combines state of the art methodology, of a kind that will change the field, with an important question and an intriguing finding that will surely motivate further work. Therefore, it will be of wide interest and appeal to the broad audience of microbial ecologists, and it is an important and compelling step forward in the field.

Reviewer #2 (Public Review):

I am not a specialist in cryo-EM, so cannot comment on the technicalities of the structure reconstruction or methods used. I thus focus on the conclusions and observations that the authors provide in the manuscript and their relevance to functional photosynthesis.

The authors attempt to resolve the structure of PSII from Dunaliella and noticed that three types of PSII could be identified: two conformational states, and a stacked configuration. There is no doubt that these structures add to our current knowledge of PSII and that they exist in abundance upon solubilisation of the sample. My main issue however is the relevance to in vivo conditions, and the efforts to exclude the possibility that pigment loss and conformational states and stacking are a reflection of ex-vivo manipulations.

I see a number of questions pertaining to this work. Starting from the two conformations of PSII, compact and stretched, the authors say that both are highly active based on oxygen measurements at a saturating light intensity. In the meantime, they report large variations in the chl content and positions of the chlorophyll molecules in these structures (also compared to other known PSIIs). This gives the impression that one can lose two chlorophylls, and freely modify the distance between others without losing efficiency, certainly a risky conclusion. Are the samples highly active also in light-limiting conditions? It is thought that even tiny movements and alterations in chl-chl distances alter their coupling and spectral properties, how come the variations in this report are so huge? In other words, the assay tests the charge separation activity of the PSII RC in the preps, but not the light-harvesting efficiency.

How does one ascertain that the lost chlorophyll molecules in CP29 are not a preparation error? Does slightly increasing the detergent concentration impact the proportion of stretched:compact forms?<br /> On a similar note, how do the authors exclude that a certain interaction with this type of grid impacts the distribution of these complexes? Is it identical to a biologically separate preparation of algae? In case of discoveries of this type, it is of high importance to exclude as many possibilities of non-native conditions or influences on the structure.

I would further like to encourage the authors to elaborate on the CP29 phosphorylation. What is the proportion of PSIIcomp that are phosphorylated? I assume it is not 100%, as in this case, the authors would propose that this is the effect that modulates between compact and stretched architectures.

In line 290, the authors highlight the structural heterogeneity within the two groups' PSII conformations. I would like to see how does the distribution look like for all the structures together: are the two (stretched and compact) specifically forming two heterogenous distributions? Or is it possible that the distribution between the two is quasi-continuous? In other words, if the structures are not perfectly defined, how do the authors decide that two- and not more or less subtypes exist?

Considering the stacked PSII, I also have a few concerns. Contrary to previous studies the authors do not assign a functional role to the stacking beyond the structural aspect. This could be better backed by a discussion about the closest chlorophyll a molecules across the stacked PSII, which given the rather large distance shown in fig. 4L seems to be too large for any EET across the stromal gap.<br /> There is a report that suggests the presence of some density between the stacked PSII - could the authors comment on the differences between it and their work? Are the angles and positions conserved between these types of stacks? https://doi.org/10.1038/s41598-017-10700-8

Line 387, the authors state that due to the transient nature of the interactions across the stromal gap, the stacks could be "under-detected" in cryo-ET data. This statement is in my opinion misformulated. For once, the transient interaction argument would apply the same (if not more due to changing conditions induced by the purification process) to the single particle analysis performed in this paper. Second, tomographic volumes detect hundreds of PSII in a suspended state. Any transient interaction that adds up to 25% of particle population in a steady state cell should be clearly visible, while the in situ data suggests not more than random cross-stromal-gap orientations. Of course, this can be a specificity of Chlamydomonas or a particular growth condition. The statement used by the authors could be indeed converted into: the PSII stacks are *over-detected in vitro*, and it is certainly a simpler explanation for their presence. It is also important to mention that PSII stacking alone is not the only reason for grana architecture - stacking with the antenna of larger complexes, absent in the authors' preparation could also contribute to grana maintenance; and auxiliary proteins such as CURT help with this issue as well. Here a recent demonstration of the importance of minor antenna should probably be also cited: https://doi.org/10.1101/2021.12.31.474624

Taking these last thoughts, I would like to finish by mentioning one more thing - almost philosophical. The authors are certainly at the forefront of the booming cryoEM revolution in biology which is profoundly changing the way we understand the living. There is absolutely zero doubt that this powerful technique is of the highest interest. But a growing number of structures of photosynthetic complexes remain puzzling, in particular with regard to their abundance in vivo (such as the PSII stacks) and functional relevance. How do we ascertain that these interactions are not due to in vitro preparation (isolation from cells, solubilisation)? Which ways can we use to try to exclude this (simple) hypothesis? I suggest that at least a small extent of biological replicas - experiments performed on separate batches, in different technical conditions, with slightly altered solubilization conditions, and so on - could shed light on the nature of these structures and their occurrence in vivo. Technical reps of the freezing+analysis pipeline could also be tried to see the variability. This would strongly reinforce this manuscript and its conclusions, and while not completely unequivocal (the stacked PSII, for example, could form upon each purification), a quantification of the effects would be of high interest.

Reviewer #2 (Public Review):

The central nucleus of the amygdala (CEA) has been the subject of numerous studies related to the processing of both aversive and pleasurable events; however, prior to this study a comprehensive understanding of the number of molecularly distinct neurons, their location in the CEA and their axonal projections have not been available. This paper provides a rich resource that fills this gap. The results will facilitate a more refined analysis of the roles of specific CEA neurons in mediating mouse behavior and physiology. A major strength of the paper is the application of their three-dimensional spatial profiling methodology of molecularly defined neurons to the CEA and then determining the axonal projections of those neurons to five of the most prominent target brain regions. The data are clearly presented and rigorously analyzed. The are no weaknesses in this valuable contribution.

Reviewer #2 (Public Review):

Overall this is a very interesting and important paper that demonstrates a novel synthetic interaction between nucleoporin inhibition and oncogene-driven hyperproliferation. This work is especially significant because of the paucity of effective treatments for hepatocellular carcinoma (HCC). The authors' demonstration that the Nup inhibitor Selinexor decreases larval liver size in KRAS-overexpressing zebrafish but does not cause toxicity in wild-type animals lays the groundwork for exploiting this class of drugs in HCC treatment. This paper represents an elegant demonstration of the utility of zebrafish models in cancer studies. The relevance of this work to human cancer is supported by the authors' studies using TCGA data, wherein they demonstrate that decreased NUP expression is associated with increased survival in HCC.<br /> Other major strengths of the paper include beautiful pictures demonstrating that ahctf1+/- decreases the density and volume of nuclear pores in TO(kras) larvae and increases the rate of multipolar spindle formation, misaligned chromosomes, and anaphase bridges. The experiments are very well-controlled, including detailed analysis of the effects of ahctf1 heterozygosity and Selinexor on wild-type animals. The inclusion of distinct methods for disruption nucleoporins (ranbp2 heterozygosity and drug treatment) bolsters the authors' conclusion that this represents a viable drug target in HCC.

My major concerns are as follows:

1. The authors state that "the beneficial effect of ahctf1 heterozygosity to reduce tumour burden persists in the absence of functional Tp53, due to compensatory increases in the levels of tp63 and tp73". However, tp63 and tp73 appear similarly upregulated in ahctf1 heterozygotes regardless of tp53 status. The authors do not provide enough evidence that tp63 and tp73 are compensating for tp53 loss. An alternative possibility based on the data presented is that the effects of ahctf1+/- are independent of tp53 family members, and the effects on apoptosis go through a different pathway.

2. The authors state in multiple locations that nucleoporin inhibition decreases tumor burden. In my opinion, this is not strictly correct. The TO(kras) model clearly results in HCC in adults, but it's a little unclear whether the larval liver overgrowth is truly HCC or not based on the original paper by Nguyen et al. (2012 Dis Model Mech).

Reviewer #2 (Public Review):

The goal of this study was to understand population bottlenecks during colonization in the context of different microbial communities. Capsular polysaccharide mutants, diet, and enteric infection were also used paired to short-term monitoring of overall colonization and the levels of specific strains. The major strength of this study is the innovative approach and the significance of the overall research area.

The first major limitation is the lack of clear and novel insight into the biology of B. theta or other gut bacterial species. The title is provocative, but the experiments as is do not definitively show that the microbiota controls the relative fitness of acapsular and wild-type strains or provide any mechanistic insights into why that would be the case. The data on diet and infection seem preliminary. Furthermore, many of the experiments conflict with prior literature (i.e. lack of fitness difference between acapsular and wild-type strain and lack of impact of diet) but satisfying explanations are not provided for the lack of reproducibility.

Another major limitation is the lack of data on the various background gut microbiotas used. As such, describing what microbes are in LCM, OligoMM, or SPF groups is important. The authors seem to assume that the gut microbiota will reflect prior studies without measuring it themselves. I also did not follow the logic of concluding that any differences between SPF and the two other groups are due to microbial diversity, which is presumably just one of many differences. For example, the authors acknowledge that host immunity may be distinct. It is essential to profile the gut microbiota by 16S rRNA amplicon sequencing in all these experiments and to design experiments that more explicitly test the diversity hypotheses vs. alternatives like differences in the membership of each community or other host phenotypes.

Given the prior work on the importance of capsule for phage, I was surprised that no efforts are taken to monitor phage levels in these experiments. Could B. theta phage be present in SPF mice, explaining the results? Alternatively, is the mucus layer distinct? Both could be readily monitored using established molecular/imaging methods.

The conclusion that the acapsular strain loses out due to a difference of lag phase seems highly speculative. More work would be needed to ensure that there is no difference in the initial bottleneck; for example, by monitoring the level of this strain in the proximal gut immediately after oral gavage.

Another major limitation of this paper is the reliance on short timepoints (2-3 days post colonization). Data for B. theta levels over 2 weeks or longer is essential to put these values in context. For example, I was surprised that B. theta could invade the gut microbiota of SPF mice at all and wonder if the early time points reflect transient colonization.

Finally, the number of mice/group is very low, especially given the novelty of these types of studies and uncertainty about reproducibility. Key experiments should be replicated at least once, ideally with more than n=3/group.

Reviewer #2 (Public Review):

In this study, the authors have successfully utilized and compared various supervised machine-learning techniques to identify the risk for the development of diabetic kidney disease. The study was further able to identify some potential novel risk factors for the development of diabetic kidney disease.

The heterogenous population and the identification of novel risk factors for diabetic kidney disease are some of the strengths of this study. Their definition of diabetic kidney disease, however, relies only on the decline in eGFR and is lacking in details of any other major significant events that may have impacted the decline in kidney function during the follow-up time period.

Overall it is an interesting study that advances the field of kidney disease, though its results need to be interpreted with caution due to significant limitations in the study design.

Reviewer #2 (Public Review):

This study by De Virgilio and co-workers examines the role of SNF1, the AMPK ortholog in yeast, in regulating TORC1 activity and cell growth. The authors combine the use of an analog-sensitive allele of SNF1 and SILAC to characterize the yeast phospho-proteome under nutrient-complete and glucose-starved conditions. Using this approach, in addition to confirming previously identified targets of SNF1, many potential new substrates were identified. The authors follow up on two of these: PIB2, a known upstream regulator of TORC1 linked previously to glutamine signaling; and SCH9, an important downstream target that is directly phosphorylated by TORC1. The authors use a combination of mutagenesis and in vitro and in vivo assays to demonstrate that SNF1 is a bona fide kinase for PIB2 and SCH9 and that phosphorylation of these targets impacts TORC1 kinase activity. In general, the data are thorough and convincing, and these findings will be appreciated by the wide readership of this journal.

Specific points to consider:

1. Because PIB2 is a major focus of the manuscript, I was surprised that it was not discussed in the introduction. I think it would be appropriate to discuss prior evidence linking this protein to TORC1.

2. The authors introduce mutations into PIB2 at two sites determined to be phosphorylated by SNF1, at S268 and S309. Somewhat confusing results are obtained, in that the PIB2 null and phosphomimic mutants (S268E and S309E) confer a similar TORC1 phenotype, compared to the S268A S308A mutant. These results require further explanation than simply that "TORC1 inactivation defect in SNF1-compromised cells is due to a defect in PIB1 phosphorylation". This is particularly intriguing given that the opposite results are observed with the SCH9 mutants, where the null and alanine mutants confer a similar phenotype compared to the S to E mutants.

3. The authors conclude, based on the co-IP data in Figure 4H, that interactions between KOG1 and PIB2 are direct. However, it remains possible that interactions between these proteins are mediated by other components of TORC1 or within cells. This should be addressed.

4. The authors demonstrate convincingly that the PIB2 and SCH9 SNF1-specific phospho-site mutants have a detectable effect on TORC1, primarily by examining TORC1-dependent phosphorylation of SCH9. What is unclear is whether phosphorylation at these sites has a significant physiological impact on cells. It appears that the rapamycin hyper-sensitivity displayed in Figure 6E is the only data presented to address this question. It would be appropriate for the authors to comment further on the significance of SNF1-dependent phosphorylation of these two substrates.

Reviewer #2 (Public Review):

The authors describe observations of an innovative food caching behavior attributed to two species of flying squirrels and likened the behavior to architectural joints used by humans. The discovery of nuts stored in the crook of shrub branches, facilitated by indented rings seemingly carved by squirrels, possibly represents an interesting food handling innovation that may function to prevent spoilage in a damp tropical ecosystem.

I applaud the efforts to survey the area multiple times after the initial discovery, and the use of trail cameras to try capture evidence of animal associations. For what is in essence a natural history note, the authors did a great job of trying to gather a variety of supporting evidence. The videos capturing squirrels visiting and retrieving the cached nuts were compelling, and the shaking of the shrubs demonstrating the difficulty in dislodging the nuts helps build the case that the nuts are cached effectively.

The most glaring gap in the evidence is that there is no direct observation of the squirrels actually performing this nut carving behavior, only associating with the nuts after they have been cached. There must be more documentation provided to explicitly link the causality between squirrels and this caching innovation.

The second major weakness is more to do with writing style and could be addressed with significant revisions to phrasing and development of ideas. This is namely to do with the claim that this is somehow an evolved behavior, without providing evidence that 1) it is indeed the squirrels performing this behavior, 2) that is confers some kind of fitness benefit, and 3) hard evidence that this caching method does indeed prevent decomposition/germination in comparison to the more traditional caching methods of these species. Given the limited geographic range of the observations, I wonder how much of this is actually attributable to learning and/or innovation by these individuals. These ideas are not developed fully, and sometimes the writing wanders among learning and evolution without exploring the deep links among the two concepts.

Third, the connection to architecture is attention-grabbing, but I'd like to see this fleshed out a bit more with more text description (and a visual here would help immensely).

Ultimately this work stands to potentially contribute a fascinating piece of evidence into the growing literature on animal cognition, spatial awareness, caching behavior, innovation, and adaptation, but currently, the claims are unsupported by the evidence presented.

Reviewer #2 (Public Review):

Guo et al. have investigated the consequences of a frameshift mutation in the rcsD gene in the Yersinia pseudotuberculosis progenitor that is conserved in modern Y. pestis strains. Interestingly, they identify a start codon with a ribosome binding site that enables production of an Hpt-domain protein from the C-terminus in Y. pestis. Targeted deletion of this Hpt-domain increased biofilm production in Y. pestis. They find that the ancestral RcsDpstb (full length) is a positive regulator of biofilm in Y. pestis while the Hpt-domain version (RcsDYP) represses biofilm in vitro. When fleas were infected with Y. pestis expressing the ancestral RcsDPSTB protein, there was no difference in bacterial survival or rate of proventricular blockage. This strain also killed mice the same rate (in a different Y. pestis strain background). However, replacing RcsDYP with RcsYPTB dramatically increases the frequency of pgm locus deletion (containing Hms ECM and yersiniabactin genes) during flea infection. The authors predict that this would reduce the invasiveness of the bacteria in mammals and/or flea blockage in subsequent flea-rodent-flea transmission cycles. They also measured global gene expression differences between RcsDPSTB compared to the wild-type strain. They argue that the frameshift of RcsD maintaining the Hpt-domain (RcsDYP) was needed to regulate biofilm while limiting loss of the pgm locus.

Loss of the pgm locus was not tested in the Y. pestis rcsD mutant strain (lacking the entire gene or just the C-terminal Hpt domain). Therefore, the claim that maintaining the Hpt-domain protein was important lacks convincing evidence. Additionally, it is possible that the population of rcsDpe::rcsDpstb after in vitro growth for 6 days would still be proficient at infecting and blocking fleas, even though many of the bacteria would have lost the pgm locus. Production of Hms polysaccharide by pgm+ could trans-complement those that are pgm-. The nature of the pgm locus loss is assumed to be due to recombination between IS elements. This is certainly the likeliest explanation but not the only one. The authors checked for pgm loss by phenotype (CR binding) and by two sets of primers, one targeting the hmsS gene and another set that is unspecified. Loss of the entire pgm (especially yersiniabactin genes) should be clarified.

Reviewer #2 (Public Review):

In general, the authors do a thorough exploration of Drosophila larval crawling, specifically looking at where within the crawl cycle changes in speed are manifest. They find a strong correlation between changes in speed and with contraction of transverse muscles. The authors then characterize a neuron (A31c) known to be activated during the time in the crawl cycle where speed is altered. Unlike many neurons that have a wave of activity across the segments of the body during crawling, these neurons are active synchronously in the segments along the anterior-posterior axis. Also, the A31c neurons have synaptic output onto pre-motor neurons (A26f) whose output ultimately controls transverse muscles.

Experimentally, the authors use all the tools at hand to make a compelling case for their conclusions. They look at crawling in freely crawling animals. Although the data on muscle length is obtained in restrained or semi-dissected animals, it is convincing. It would be more convincing if done in intact freely moving animals, but that is a technical reach. To look at neuron morphology they use immunofluorescence and connectomic data in an effective manner. They are able to manipulate the activity of their neurons of interest in order to show that they have control over transverse muscle length and crawling speed.

Finally, the authors claim that the neurons they examine are sufficient and required to alter crawling speed. They appear to be sufficient to alter transverse muscle length and crawling speed, but the data do not support the requirement for these neurons for these processes. One way to show this would be to inhibit or ablate the neurons and find that the larvae were unable to alter the speed.

Reviewer #2 (Public Review):

One of the greatest challenges to the containment of the SARS-CoV-2 pandemic is the generalist nature of this virus and its ability to infect across non-human animal species, and successfully cycle within non-human species. It is, therefore, critical to understand the potential for transmission and evolution of the virus in non-human animal species and draw generalizations from both to help predict the occurrence of new viral variants and their associated risk for secondary spillover events back into human populations. This manuscript describes cross-species transmission between humans and non-human hosts, as well as non-human host-specific SNVs that have arisen presumably due to continued successful transmission cycles in non-human species. Using publicly available SARS-CoV-2 genomic sequences from four animal host species and humans, the study revealed that the highest number of animal-to-human transmission events have occurred between farmed mink populations and humans and that white-tailed deer have the highest number of single nucleotide variants specific to a non-human species from those included in the study. The authors are careful to point out the limitations of the dataset, as there are still too few publicly available SARS-CoV-2 whole genome sequences for non-human animal taxa, making non-human species inclusion impossible in some cases and creating unbalanced datasets that reflect sequencing and sampling effort. The authors could have offered a greater justification of statistical methods employed given this hurdle, both in terms of quantitative mitigation steps or qualitative justification of the methods used, but their methods provide a pipeline for addressing cross-species transmission and the emergence of non-human species-specific SNVs as scientists work to accumulate more genomic sequences from animal taxa. Their results are also largely congruent with another recently published manuscript using SARS-CoV-2 genomic data from the same source and aimed at understanding human-to-animal transmission solely. In addition to the two main goals, cross-species transmission, and species-specific SNVs, the authors have offered an evaluation and discussion of several species-specific SNVs that will aid the scientific community in the future in drawing connections between viral evolution, host biology, and epidemiological patterns related to SARS-CoV-2 across species.

Reviewer #2 (Public Review):

This work provides a method for extracting morphological features of cells and their neighborhoods from EM volumes in a self-supervised manner. The authors generate these MorphoFeatures using a set of neural networks, and show the usefulness of the features for cell type classification, symmetric partner identification, and the automated clustering of cells into morphologically similar groups, tissues and organs.

The main innovation of this method compared to similar studies is the separation of the input into shape, coarse, and fine texture. A combination of an auto-encoder (for texture features) and a contrastive loss (for all features) is used to obtain features without task-specific bias. The learned features are consistent with cell type when compared to manual annotations, and genetic markers. The distinction between shape, coarse, and fine features is not used beyond the development of the method.

The authors later include a descriptor of the cell's neighborhood, with the goal of automatically discovering tissues and organs. Clustering in this MorphoContextFeature space successfully delineates the different parts of the *P. dumerilii* ganglia, and shows some advantages over both manual segmentation and clustering in gene expression space. A detailed analysis of the method on finding tissues in the *P. dumerilii* foregut is given as an additional example.

Strengths

The use of an unsupervised method means that this method can be applied on data where no cell types are known a priori, and the authors have made clear that a cell type classification can be obtained from MorphoFeatures with minimal annotation. Used as a first exploratory pass, this method can help quickly guide and narrow the scope of further analysis.

By separately obtaining features at three levels of resolution, the method has the potential to pinpoint the structural features most predictive of a cell type more precisely than a single-resolution method. Most interestingly, Figure 3 indicates that the learned features are visually meaningful: this would greatly increase the impact of such a method, as it would lead to testable hypotheses.

The training method that the authors suggest for the neural network is sound, and successfully avoids the potential pitfalls of using augmentation with a contrastive loss in a situation where shape is an important signal. Similarly, the authors appropriately choose clustering methods that can discover clusters of varying sizes.

The authors make good use of prior knowledge to confirm the hypotheses generated by clustering cells in MorphoFeature space. They include specific genetic explanations for both expected and unexpected clusters found (figures 5 and 6), and provide clear indication where the gene expression atlas does not give an explanation for a MorphoFeature cluster (Figure 6D). The examples given for clustering in the MorphoContextFeature space are similarly clear and well supported by additional data (figures 8 and 9).

Weaknesses

1. In the section on "visually interpretable" features, I would have liked a more quantitative idea of how many features the authors considered meaningful, and how those can be found. For example, are the six features shown in Figure 3 particularly meaningful, or were they chosen among many? A discussion of the feature selection protocol would be useful for replicating the method on new data. Furthermore, a supplementary figure with some of the features which are not meaningful would give the reader a better idea of the range of interpretability to expect.

2. The section on MorphoContextFeatures is missing a comparison with the MorphoFeatures. This made it unclear to me whether adding the neighborhood information is necessary for the discovery of tissues and organs. This could be remedied with a supplementary figure showing the same analysis as in figures 7 and 8 on the MorphoFeatures without the additional neighborhood information. Alternatively, since the MorphoFeatures are a subset of the MorphoContextFeatures, the authors could run a post-hoc analysis of whether the MorphoFeatures or the neighborhood features best explain the inter-class variance.

3. Finally, some extra guidance is needed to replicate this work on new data. In particular the following points could use more discussion:

3.1. How to choose the size of the MorphoFeatures vector - did the authors attempt a number other than 80 and if so, what was affected by this choice?

3.2. The protocol for when and how to define sub-clusters - were the chosen thresholds based on prior knowledge such as known tissues/organs? What do the authors suggest if this kind of information is missing?

3.3. How to link the obtained clusters back to specific, potentially meaningful, MorphoFeatures. For example, does the distinctive shape of the enteric neurons in cluster 8.3 of figure 5 correspond to an extreme of the cytoplasm shape feature described in figure 3 (lower left)?

Reviewer #2 (Public Review):

Lee, Chen, Kaku, Zhuo et. al. demonstrate that a single injection of ube3a-ASO in a new mutant ube3a mouse model restores Ube3a protein expression and EEG function and sleep patterns. A key feature of these findings is the development of a new mouse model that eliminates any expression of ube3a mRNA. Moreover, they demonstrate that the impact of their treatment can last up to 6 weeks. They determine that the phenotype correction correlates with Ube3a protein level. There is an impressive amount of work that has gone into this study. It does appear, however, that much of this work is derivative of previous studies. It is less clear what is novel. While a new mouse model is introduced, it is unclear whether such a mouse model is any better defining Angelman syndrome than previous models. Several conclusions appear to be a bit too strong based on the modesty of the findings. For example, it is not clear that the current findings constitute a strong enough foundation for future drug studies.

Overall, this study describes another set of potentially interesting findings using ASO to restore Ube3a expression and phenotypic rescue. Not all phenotypes are tested, not every tested phenotype shows truly robust changes that would encourage one to move to clinical trials.

The authors did succeed in describing this new mouse line at the level of ube3a expression, EEG, sleep patterns and poly-spikes. They did so across many brain regions and multiple ages. Within these findings and approaches, there is useful information that can benefit the field. The impact of this work is that the authors may have demonstrated an approach which will have a longer lasting impact on recovery. Such an advance would be a great benefit to the population of those greatly impacted by Angelman syndrome.

Reviewer #2 (Public Review):

It is my opinion that the principle utility of this approach lies in its ability to identify the set of 'easily learnable' stimulus-response mappings from neural data which makes strong behavioral predictions that can be easily evaluated. I envision a simple experiment in which empirically obtained kernel functions are used to rank stimulus-response mappings according to their learnability which can then be plotted against measures of performance like the observed learning rate and saturated performance. Because kernel functions are empirically obtained, there is even the potential for meaningful cross-species comparisons. If behaviorally validated, one could also use this approach to label cortical populations by the set of easily learned stimulus-response mappings for that population. This allows for the identification of task-relevant neurons or regions which can be subsequently manipulated to enhance or degrade learning rates.

Of course, any theoretical approach is only as good as the underlying assumptions and so while the primary strength is the simplicity and generality of this approach, the primary weakness is its neglect of some very real and very relevant aspects of neural data in particular and statistical learning in general. In particular, the three principle limitations of this work are tied to its reliance on the assumptions that (1) neurons are noiseless, (2) decoders are linear, and (3) learned weights are unbiased.

(1) Within this framework, a realistic stimulus-dependent noise model can be easily introduced and its effects on the kernel and set of easily learned stimulus-response mappings investigated. So while the kernel would be substantially altered via the addition of a realistic noise model, the applications of the approach outlined above would not be affected. The same cannot be said for the efficient coding application described in this manuscript. There, the authors note that rotations and constant shifts of neural activity do not affect the kernel and thus do not affect the generalization error. This kernel invariance is not present when a non-trivial (i.e. non-isotropic) noise model is added. For example, suppose that neurons are independent and Poisson so that noise scales with the mean of the neural response. In this case, adding a baseline firing rate to a population of unimodal neurons representing orientation necessarily reduces the information content of the population while rotations can affect the fidelity with which certain stimulus values are represented. It is important to note, however, that while this particular efficiency result is not compelling, I believe that it is possible to perform a similar analysis that takes into account realistic noise models and focuses on a broad set of 'biologically plausible' kernels instead of particular invariant ones. For example, one could consider noise covariance structures with differential correlations (Moreno-Bote 2014). Since the magnitude of differential correlations controls the redundancy of the population code this would enable an analysis of the role of redundancy in suppressing (or enhancing) generalization error.

(2) Similarly, the linearity assumption is somewhat restrictive. Global linear decoders of neural activity are known to be highly inefficient and completely fail when decoding orientation in the primary visual cortex in the presence of contrast fluctuations. This is because contrast modulates the amplitude of the neural response and doubling the amplitude means doubling an estimate obtained from a linear decoder even when the underlying orientation has not changed. While the contrast issue could be partially addressed by simply considering normalized neural responses, it is not yet clear how to extend this approach to account for other sources of neural variability and co-variability that cause global linear decoders to fail so badly.

(3) This analysis relies on the assumption that decoder weights learned in the presence of finite data are efficient and unbiased. This assumption is problematic particularly when it comes to inductive bias and generalization error. This is because a standard way to reduce generalization error is to introduce bias into the learned decoder weights through a penalization scheme that privileges decoder weights with small magnitudes. This kind of regularization is particularly important when neurons are noisy. Fortunately, this issue could be addressed by parameterizing changes in the kernel function by the degree and type of regularization potentially leading to a more general result.

Finally, I would like to conclude by explicitly stating that while the limitations imposed by the assumptions listed above temper my enthusiasm in regards to conclusions drawn in this work, I do not believe there is some fundamental problem with the general theoretical framework. Indeed, items 1 and 3 above can be easily addressed through straightforward extensions of the authors approach and I look forward to their implementation. Item 2 is a bit more troublesome, but my intuition tells me that an information-theoretic extension based upon Fisher information may be capable of eliminating all three of these limiting assumptions by exploiting the relationship between FI(\theta) and FI(y=f(\theta)).

Reviewer #2 (Public Review):

In the present study, Liu and colleagues set out to assess the mechanisms of the therapeutic action of FGF21 on non-alcoholic steatohepatitis in the setting of obesity and dyslipidemia. They used a liver-targeted adeno-associated virus to overexpress FGF21 as a method for chronic pharmacological-type treatment of the mice. They found that FGF21 overexpression in their mouse model prevented weight gain in high-fat, high-cholesterol (HFC) diet-fed mice, compared to the control virus on the HFC diet. In addition, many of the features of obesity, insulin resistance, and NAFLD are prevented by hepatic FGF21 overexpression in their model. The authors have performed extensive phenotyping and the results leave little doubt of the efficacy of the treatment.

My main concern with the study is the distinction between a therapeutic paradigm and the preventative paradigm employed here. Based on the body-weight curves, one might expect that real liver pathology never occurred in the FGF21-overexpressing animals. In which case, it is difficult to comment on the possibility of reversing these aspects in a therapeutic setting. This point is highly relevant to the ongoing clinical trials of FGF21 analogs for NASH that the authors have referenced.

A second point raised by the authors is the aspect of FGF21 increasing thermogenic adipose tissue activity. Their results showing FGF21-induced expression of UCP1 are not in doubt, but the fact that this increase alone is responsible for the observed phenotype is not clear. For example, FGF21 has been shown to be anorexigenic in certain models (non-human primates: Talukdar, et al. Cell Metab 2016, mini-pigs: Christoffersen, et al. Diabetes Obesity Metabolism 2019, among others). Moreover, there is evidence that some effects of FGF21-driven metabolic improvements do not require UCP1 (Samms, et al. Cell Reports 2015). Given the differences in brown fat activity and physiology between mice and humans, it would be important for the authors to either moderate their comments on the UCP1 dependence of their phenotype or provide more data to clarify to what extent their findings are UCP1-dependent (e.g. food intake in the FGF21 overexpression model and/or evidence of increased energy expenditure).

Reviewer #2 (Public Review):

Optogenetic proteins are important tools for circuit neuroscience. The authors characterize five proteins, GtCCR4, KnCHR2, BeGC1, bPAC, and OaPAC with respect to their ability to suppress normal cell excitability and compare the results to those for the more established GtACR1 and CrChR2[T159]. The study makes use of expression in the zebrafish heart and hindbrain, as well as in a cell line. Electrophysiology in the cell line demonstrates that GtCCR photo-activation induces similar currents as CrChR2 activation and shows less signs of desensitization. Using a transgenic vsx2:Gal4 zebrafish line, immunohistochemistry shows that the tools are expressed. When activated, they triggered the expected behavioral responses (swimming) at short latency (<4s). This was true even for the three tools that are guanylyl or adenylyl cyclases (BeGC1, bPAC, OaPAC) and thus affect cell excitability only indirectly. At the tested light intensity, the Klebsormidium nitens channelrhodopsin (KnChR) had the shortest latency (<0.5 s) and highest (100%) probabilities of inducing locomotion. When expressing the tools in the zebrafish heart, brief illumination (100 ms) induces brief (100 ms - 1500 ms) suppression of the heartbeat. Notably, also tools that evoke depolarization induce heartbeat suppression. Heartbeat movies and calcium imaging demonstrate that this is caused by prolonged cardiomyocyte contraction. The optogenetic guanylyl and adenylyl cyclases were not effective in perturbing zebrafish heartbeat (except for bPAC over longer time scales).

Given the large number of optogenetic proteins available to date and the challenge of employing them in well-controlled neuroscience experiments, this study presents an important contribution for neuroscientists performing optogenetic research in animal models. Two light-gated cation channels, GtCCR4 and KnChR, are tested for the first time in vivo. The evidence supporting the claims regarding heartbeat and induced swimming behavior is solid. Since GtCCR4 is more Na+-selective than other channelrhodopsins, it should allow better control of experimental variables and is a valuable addition to the optogenetic tool box. The created transgenic zebrafish lines will be useful for the zebrafish neuroscience community.

The expression in zebrafish was compared using immunohistochemical staining (of a single Gal4 driver line). From this experiment alone, it is difficult to judge the expression level, the in vivo visibility of the fluorescence under the microscope, and the proportion of target cells that do express the optogenetic gene of interest.

The evidence for optogenetically induced alteration of swimming behavior is compelling. However, the associated neuronal responses and their dependence on different light intensity levels remain uncharacterized. Therefore, if anyone plans to use these tools to investigate a neural circuit in the future, the needed light levels and the specificity of the manipulation would still need to be determined.

For the optogenetic guanylyl and adenylyl cyclases, which clearly were able to alter behavioral responses, the signaling and circuit mechanisms that lead to neuronal depolarization remain unknown, but possible activation pathways are discussed.

Reviewer #2 (Public Review):

The presented study aims at deciphering the physiological function of GPCR signaling in excitable cells. To this end, the authors developed transgenic zebrafish models expressing a selection of Gq- and Gi/o-coupled bistable rhodopsins in either reticulospinal neurons or cardiomyocytes and elucidated behavioral responses (tail movements) or physiological responses (heartbeat) as well as intracellular Ca2+ dynamics following optical stimulation of rhodopsins.

One of the major strengths of the presented study is the functional comparison of five Gq- and five Gi/o-coupled rhodopsins in two major classes of excitable cells, however; the selection of rhodopsins tested remains elusive. More importantly, it is not obvious why some of the effects of rhodopsin activation were assessed in both neurons and cardiomyocytes, while others were only tested in one of the two systems without further explanation. The main chosen experimental readouts (swimming/tail bending or cardiac contractions) have limited informative value regarding GPCR signaling, as they will only report the peak of the iceberg, namely whether movements are elicited or heartbeats inhibited. No analysis on subtle changes in heart rate and contraction force was included, but such modulation of cardiac activity (e.g. positive or negative chronotropic, inotropic, dromotropic, bathmotropic, and/or lusitropic responses) would represent better the physiological modulation of the heart via GPCR and down-stream signaling events. In line, the presented data only represents behavior at one light intensity tested, whereas a light titration of observed effects could provide more meaningful insight into both rhodopsin responses and signaling mechanisms. Also, the potential promiscuity of G protein activation of selected receptors has not been addressed, neither experimentally nor in the discussion part. As a result of the above-mentioned limitations, it is difficult to follow the logic of the study and especially to interconnect the data obtained in reticulospinal neurons (where activation of jumping spider rhodopsin elicited tail bending) to myocyte data (where three Gi-coupled rhodopsins suppressed cardiac activity). Moreover, as such, the study does not provide explanations on why a certain tool might evoke an effect in one system or the other, or not, which could be the main deliverable of such a comparative analysis.

While the presented data is interesting, the graphical presentation and description of the data are insufficient. Most importantly, the current version of the text does not include a quantitative description of effects and statistical analyses (which are found in the figures and legends!). The lack of quantitative description also extends to both the introduction and discussion, which remain general without a specific dissection of observed effects.

One major concern is the selective citation of own work. While single statements in both the introduction and discussion are supported by up to ten own papers, recent studies using rhodopsins for dissecting GPCR signaling in neurons are not sufficiently discussed and new data is not compared to published results by other teams. Moreover, relevant papers on cardiomyocytes (e.g. PMID: 35579776, 35365606, 34987414, 30894542) are not cited at all, despite the use of similar rhodopsins and/or optogenetic activation of the same signaling pathways. Taking into account these published studies may help to better understand the observed responses.

Additional comment: Data were obtained from larvae zebrafish. It would be useful to include a discussion on how GPCR signaling might be different in adult fish compared to larvae, and how to test whether the observed effects are more generally applicable.

Reviewer #2 (Public Review):

The reciprocal adaptation of host immune systems and pathogens leads to complex co-evolutionary dynamics. How this dynamical process shapes host and pathogen diversity is a fundamental question in immunology and virology. To study this question experimentally, the CRISPR-Cas system which some prokaryotes use for adaptive immunity against phages has recently emerged as an important model system. In this system both host and viral adaptation can be read out by sequencing, as CRISPR-Cas immunity is guided by genomic spacers incorporated into the host genome. In this context, the current work presents a welcome deep dive into the dynamical regimes predicted by a simple phenomenological model of the co-evolution between CRISPR loci and phages. Among the notable results are the following: First, diversity primarily depends on a single scalar parameter, and does so in a sublinear manner. Second, different types of cross-reactivity are linked to different shapes of viral phylogenies. Third, comparison of spacer turnover and average immunity between theoretical and experimental timeseries data provides hints as to the operative regime in different CRISPR systems. These results together with the extensive discussion should be greatly useful in guiding further work in this field. There are many avenues for further theoretical work generalizing to less simplifying assumptions, and importantly, many concrete suggestions for future experiments.

Reviewer #2 (Public Review):

In this manuscript, Karsenty et al. describe postnatal development in the rat between P20 and P60 where crests of the cardiomyocyte lateral membranes mature. The authors previously described these crests in a Cardiovascular Res paper, where they highlighted how they facilitate interactions between cardiomyocytes in claudin-5 dependent manner. The authors previously also reported claudin-5 ephrin-b1 interactions on the cardiomyocyte lateral surface. Presently, the authors try to link together the following observations: a) crest height, mitochondrial number and area increase from postnatal day 20 to 60 in rats, and this correlates with increase claudin-5 expression, as well as gene expression accessed by microarray; b) changes in diastolic function occur in rats between days 20 and 60 postnatal life; c) cardiomyocyte-specific knockout of ephrin-b1 leads to diastolic dysfunction and a heart failure with preserved ejection fraction like phenotype.

The major strength of the paper is the detailed analysis of postnatal cardiomyocyte structure using electron microscopy and echocardiography. However, there are multiple major weaknesses of the methodology that should be clarified.

1. Most importantly, it is unclear how these mice are maintained. The authors explain the mice are in a mixed background. If this is the case, it is extremely important that littermate controls are used. Otherwise, it is very difficult to interpret the physiological data if the animals being compared are from two separate crosses.

2. The authors should clarify the echo and cath data in mice and rats. First with respect to the rat data, the end-diastolic pressure of the p60 rats reported in Figure 3 is around 9 mmHg. This is significant and abnormal, and also unexplained. More globally, the authors conclusion that "diastolic maturation" is occurring should be tempered by the fact that loading conditions at these two postnatal days are completely different, as highlighted by the blood pressures of the animals (~70/40 at p20 vs ~120/80 at P60). Third, the heart rates are significantly higher at p60 vs p20 in panel A, but not panel B. The authors report these studies were performed under isofluorane, so I imagine this reflects differences in anesthesia, which can significantly affect the heart rate and thus the diastolic parameters (particularly IVRT), so this should at least be commented on as a significant limitation.

With respect to data interpretation and whether the results are correctly interpreted, the following considerations should be taken into account:

1. The author conclusions in Figure 2d appear overstated. While the methodology of figure 2d is explained in the figure panel, it is generally looked over in the main text. Is there any precedent for utilizing human single-cell sequencing in this purpose - essentially the authors are superimposing the rat P20 and P60 data on the human UMAP plot. The authors walk back the statement in the text and clarify that these genes are expressed in the following cell types in adult human hearts.

2. The ephrin-b1 cardiomyocyte specific knockout mice are not a model of HFpEF. These mice show an accelerated death rate and clear evidence of progressive systolic impairment. Furthermore, it is completely unclear that the murine diastolic parameters are meaningfully different, and hence the overall evidence presented that this is a HFpEF phenotype is weak.

Reviewer #2 (Public Review):

The authors present a compendium of diffusion MR, dynamic contrast-enhanced MR, histological, and other results in AQP4 KO vs. WT mice which suggest that AQP4 deletion results in stagnation of interstitial fluid movement, enlargement of interstitial volume, and an increase in total brain water. The authors also provide evidence that these effects do not arise due to changes in CSF production, perfusion, or vascular density, strengthening the conclusion that AQP4 is specifically involved in modulating parenchymal resistance, rather than another aspect of glymphatic function. While the study of AQP4 deletion using various MR and histological methods is not novel per se, the breadth of concurrent methodological approaches presented here is uncommonly extensive, and thus provides a strong, self-contained case for the conclusion(s) - more so than other works on such mouse models. The key strength and utility of this work lie in the extent of corroborating evidence provided for the conclusions.

Another strength of the paper is the development of what appears to be a robust CSF space segmentation approach, which may be of interest to others aiming to quantify glymphatic function using MR. The source code, however, is not provided at this time.

I have some concerns, specifically about the discussion around transmembrane water exchange - i.e., whether the exchange is truly being measured by the diffusion MR methods - and about the validity of applying an IVIM signal model across the brain. These concerns, however, do not affect the major conclusions of the paper. Indeed, the authors have included analyses using standard ADC fitting which avoids the issues with IVIM. In summary, the paper presents a compelling body of evidence describing the effects of AQP4 deletion in mice.

Reviewer #2 (Public Review):

The manuscript by Niu and colleagues reported that ET after mastectomy did not prolong the DFS of Chinese HR+ DCIS patients, but rather increased adverse effects. For the first time, the authors analyzed the beneficial effect and safety of ET after mastectomy in Chinese patients with HR+ DCIS through the clinical case review. The conclusion of this study is of great significance to guide the choice of appropriate treatment for Chinese patients with HR+ DCIS, and it has obvious benefits to reduce the economic burden of the patient's family and improve the quality of life for patients.

Reviewer #2 (Public Review):

Although many broadly-neutralizing antibodies were discovered against virus accumulating mutations such as HIV, Influenza, and Sars-CoV-2, the methodology to induce such antibodies or design to generate them is highly demanded. The authors take the broadly-neutralizing antibody, CH65 as a model antibody and try to recapitulate the generation of the broadly-neutralizing antibody from an unmutated common ancestor over time. By performing Tite-Seq assays, Epistasis analysis, Pathway analysis, and Affinity measurement, and structural study, the authors proposed a scenario of the evolution of CH65.

Strengths<br /> Combining the models and affinity/structure data, the authors enable us to show the possible track of gaining the breadth of the CH65 antibody from the unmutated repertoire. Using the Tite-Seq assay, the authors took a forward genetics approach which is high-throughput and non-bias and mimics the situation of the evolution of a B cell repertoire in an individual over time. The data is robust, and its outcome will provide an opportunity to build a prediction model to design the antibody in silico. Especially their identification of amino acid positions important for epistasis mode in antibody evolution is valuable. Antigen selection scenarios are decisive in this study.

Weakness<br /> The proposed scenarios cannot be tested using human CH65. The readers would have great interest in how these hypothetical scenarios are fitting to the evolution occurring in vivo situation, especially in a quantitative way. The broadly neutralizing antibodies often react with self-antigens as the authors cite previous work(ref 19). How do these environmental factors affect the evolution of the antibody? These already-known facts could be mentioned and discussed in detail.

Reviewer #2 (Public Review):

Huang Mi, et al. investigated the role of MTIF3, the mitochondrial translation initiation factor 3, in the function of adipocytes. They first detected the expression of the obesity-related MTIF3 variants based on the G5Ex database and found two variants lead to an increase in MTIF3 expression. Then they knockout MTIF3 in differentiated hWAs adipocytes and characterized the mitochondrial function. They found loss of MTIF3 decrease mitochondrial respiration and fatty acid oxidation. They further treated cells with low glucose medium to mimic weight loss intervention and found MTIF3 knockout adipocytes lose fewer triglycerides than control adipocytes. This paper provides new information about MTIF3 in adipocytes and the potential functional role of MTIF3 in mitochondrial function.

1. The authors provided sufficient data to show those two genetic variants increase MTIF3 expression. Their CRISPR/Cas9 knockin cell line is also convincing. But they didn't show if the genetic variants affect adipogenesis. Adipogenesis is an important process for weight gain and fat deposition. In lines 103-107, the authors mentioned that the "allele-edited cells have some problem in differentiated state, e.g. triglyceride or mitochondrial content", so they used an inducible Cas9 system. However, the issue of differentiated allele-edited cells may be the functional effect of MTIF3 genetic variants, such as interrupting adipogenesis, decreasing triglyceride, or affecting mitochondrial number. The authors should provide that information.

2. In Figure 4, the author mentioned that MTIF3 knockout does not affect the expression of adipogenic differentiation markers. They need to provide more evidence to prove their point. Oil-red O staining is a clearer way to quantify adipocyte differentiation in cell culture. In addition, in Fig. 4B western blot, the author should include MTIF3 as a control to show the knockout efficiency. It is not clear the meaning of plus and minus in that panel. The author should also compare the total triglyceride levels in MTIF3 knockout cells and control cells.

3. MTIF3 is a translation initiation factor in mitochondria and is involved in the protein synthesis of mitochondrial DNA-encoding genes. The authors should check protein levels rather than the mRNA levels of mitochondrial DNA-encoding genes (Fig. 6E). It's interesting to see the increase of mRNA levels of ND1 and ND2, which might be feedback of lower translation. Since ND1 and ND2 are in OXPHOS complex I, the expression levels of complex I in MTIF3 KO cells would be worth checking. Additionally, the author should also check the mitochondria copy number.

4. MTIF3 knockout adipocytes retain more triglycerides under glucose restriction is interesting. It may link to the previous result of lower fatty acid oxidation in MTIF3 knockout adipocytes. However, the authors then showed there is no difference in lipolysis. The author should discuss those results in the manuscript. The authors could also check lipolysis in glucose restriction conditions. It's also necessary to include the triglyceride levels of KO cell lines at full medium.

Reviewer #2 (Public Review):

The authors present a manuscript that addresses an important topic of bacterial co-existence. Specifically modeling infection-relevant scenarios to determine how two highly antibiotic-resistant pathogens will develop over time. Understanding how such organisms can persist and tolerate therapeutic interventions has important consequences for the design of future treatment strategies.

A major strength of this paper is the methodical approach taken to assess the dynamics between the two bacterial species. Using carbon sources to regulate growth to test different community structures provides a level of control to be able to directly assess the impact of one dominant pathogen over another.

The modeling aspect of this manuscript provides a basis for testing other disturbances and/or the impact of additional incoming pathogens. This could easily be applied to other infection settings where multiple microbes are observed ( for example viral/bacterial interactions in the lung).

The authors clearly show that by altering the growth rate and metabolism of various carbon sources, population structure can be modified, with one out-competing the other. Both modeling and experimental approaches support this.

The exploration of the role of virulence factors is less clear, for example how strains unable to produce virulence factors are impacted in regard to their overall growth and whether S. aureus is able to sense virulence factors without transcriptional assays here. Although the hypothesis is strong, the experimental data does not fully support this conclusion.

Spatial disturbance has a significant impact on community structure. Although using one approach to assess this, it is not clear if the spatial structure is impacted without the comparable microscopy evaluation.

Overall this paper highlights the use of modeling approaches in combination with wet lab experiments to predict microbial interactions in changing environments.

Reviewer #2 (Public Review):

The idea that decidualization is related to or evolved from wound healing, including fibroblast activation, is old, going back all the way to Creighton 1878 who pointed to the similarity between granulation tissue and decidual tissue, and is supported by the fact that embryo implantation is a compensated form of the endometrial lesion. Nevertheless, the mechanistic connection between FB activation and decidualization is an important fact necessary for understanding decidualization, a fact that is reflected in previous work, for instance, Kim et al., 1999 (Hum Reprod 14 Suppl 2), their reference 20, and Oliver et al., 1999 (Humn Reprod 14), their reference 56 a.o.m. More specifically, a recent single-cell study of in vitro decidualization has shown that a myofibroblast-like cell state is a transient state in the process of decidualization, i.e. decidual cells themselves are not so much activated fibroblasts, but rather decidual cells differentiate after endometrial stromal fibroblasts undergo a FB activation like process, and the decidual re-programming happens from these activated FB like states (Stadtmauer et al., 2021, Biol. of Reprod. 1-18).

The above assessment of how the current study fits into the conceptual landscape of mammalian reproductive biology does not diminish the importance of the paper under consideration. The study contributes a large amount of observational and experimental facts to the understanding of how FB activation and decidualization are related. The authors suggest, in particular, that blastocyst-derived TNF activates the cLPA-producing Arachidonic acid (AA), activating PGI2 and PPARd signaling pathway (more about this later).

Other major comments:

The authors suggest that luminal epithelial cells signal through the release of arachidonic acid (AA) in response to TNF. That is interesting and supported by in vitro experiments inducing decidualization and FB activation by AA. What makes this conclusion a little problematic is that it is known that luminal epithelial cells also express COX2/PTGS2 and thus the synthesis of prostaglandins is already starting in the LE and thus LE can also signal to the stoma via PGE2, PGI2 as well as PGL2 rather than AA directly. The in vitro experiments can not exclude the possibility that the ESF is producing some prostaglandin and then having an autocrine effect.

344: here the authors report that PGE2 has no effect on FB activation marker expression, but the problem with that is, that (at least in human ESF), progesterone is causing a change in the expression of the PGE2 receptors from EP4 to EP2, and it is only the EP2 receptor that activates cAMP/PKA pathway.

The fact that the authors show an effect of PGI2 is interesting because PGI2 receptors are among the strongest expressed PTG receptors in mammalian ESF. Prostacyclin receptor is a GPCR rather than a nuclear receptor. So the question is really why the authors have not pursued the role of prostacyclin receptor and instead have focused on PPARd?

Reviewer #2 (Public Review):

The manuscript of Xu and colleagues examines in detail the regulation of the important transcription factor IRF8 in dendritic cell (DC) subsets. They identify a long noncoding RNA arises from the +32kb enhancer of IRF8 specifically in plasmacytoid DCs (pDCs)and show clearly that this lncIRF8 marks the activity of a region of this enhancer but the RNA itself does not appear to have any function. Deletion of the promoter of the lncIRF8 ablated cDC1 and pDC differentiation using an in vitro cell differentiation model. The authors propose an innovative model that the lncIRF8 promoter sequences act to limit IRF8 expression in cDC1, but are inactive in pDCs, resulting in their characteristically very high IRF8 expression.

This is a conceptually interesting study that makes excellent use of an extensive set of genomic data for the DC subsets. There has been a lot of recent research investigating the regulation of the IRF8 gene in hematopoiesis and this study provides an important new aspect to the work. The use of an in vitro model of DC differentiation is a powerful practical approach to investigating IRF8 regulation, as is the innovative use of CRISPR technology. Perhaps the biggest limitation of this study is that the authors have not conformed to the in-cell system data by creating a mouse strain lacking the lncIRF8 element. Such approaches by others, most notably the Murphy lab, have been instrumental in pushing this field forward. Nevertheless, Xu et al. significantly add to our current knowledge of the regulation of IRF8, a critical step in forming the dendritic cell network.

Reviewer #2 (Public Review):

Slusarczyk et al. investigate the functional impairment of red pulp macrophages (RPMs) during aging. When red blood cells (RBCs) become senescent, they are recycled by RPMs via erythrophagocytosis (EP). This leads to an increase in intracellular heme and iron both of which are cytotoxic. The authors hypothesize that the continuous processing of iron by RPMs could alter their functions in an age-dependent manner. The authors used a wide variety of models: in vivo model using female mice with standard (200ppm) and restricted (25ppm) iron diet, ex vivo model using EP with splenocytes, and in vitro model with EP using iRPMs. The authors found iron accumulation in organs but markers for serum iron deficiency. They show that during aging, RPMs have a higher labile iron pool (LIP), decreased lysosomal activity with a concomitant reduction in EP. Furthermore, aging RPMs undergo ferroptosis resulting in a non-bioavailable iron deposition as intra and extracellular aggregates. Aged mice fed with an iron restricted diet restore most of the iron-recycling capacity of RPMs even though the mild-anemia remains unchanged.

Overall, I find the manuscript to be of significant potential interest. But there are important discrepancies that need to be first resolved. The proposed model is that during aging both EP and HO-1 expression decreases in RPMs but iron and ferroportin levels are elevated. In their model, the authors show intracellular iron-rich proteinaceous aggregates. But if HO-1 levels decrease, intracellular heme levels should increase. If Fpn levels increase, intracellular iron levels should decrease. How does LIP stay high in RPMs under these conditions? I find these to be major conflicting questions in the model.

Reviewer #2 (Public Review):

Xie et al. investigated the medial temporal lobe (MTL) circuitry contributions to pattern separation, a neurocomputational operation to distinguish neutral representations of similar information. This presumably engages both long-term memory (LTM) and working memory (WM), bridging the gap between the working memory (WM) and long-term memory (LTM) distinction. Specifically, the authors combined an established retro-cue orientation WM task with high-resolution fMRI to test the hypothesis that the entorhinal-DG/CA3 pathway retains visual WM for a simple surface feature. They found that the anterior-lateral entorhinal cortex (aLEC) and the hippocampal DG/CA3 subfield both retained item-specific WM information that is associated with fidelity of subsequent recall. These findings highlight the contribution of MTL circuitry to item-specific WM representation, against the classic memory models.

I am a long-term memory researcher with expertise in representational similarity analysis, but not in inverted encoding modeling (IEM). Therefore, I cannot verify the correctness of these models and I will leave it to the other reviewers and editors. However, after an in-depth reading of the manuscript, I could evaluate the significance of the present findings and the strength of evidence supporting these findings. The conclusions of this paper are mostly well supported by data, but some aspects of image acquisition and data analysis need to be clarified. I would like to list several strengths and weaknesses of this manuscript:

Strengths:<br /> • Methodologically, the authors addressed uncertainty in previous research resulting from several challenges. Namely, they used a high-resolution fMRI protocol to infer signals from the MTL substructures and an established retro-cue orientation WM task to minimize the task load.<br /> • The authors selected a control ROI - amygdala - irrelevant for the experimental task, and at the same time adjacent to the other MTL ROIs, thus possibly having a similar signal-to-noise ratio. The reported effects were observed in the aLEC and DG/CA3, but not in the amygdala.<br /> • Memory performance, quantified as recall errors, was at ceiling - an average recall error of 12 degrees was only marginally away from the correct grating towards the closest incorrect grating (predefined with min. 20 degrees increments). However, the authors controlled for the effects of recall fidelity on MTL representations by comparing the IEM reconstructions between precise recall trials and imprecise recall trails (resampled to an equal number of trials). The authors found that precise recall trails have yielded better IEM reconstruction quality.<br /> • The author performed a control analysis of time-varying IEM to exclude a possibility that the mid-delay period activity in the aLEC-DG/CA3 contains item-specific information that could be attributed to perceptual processing. This analysis showed that the earlier TR in the delay period contains information for both cued and uncued items, whereas the mid-delay period activity contains the most information related to the cued, compared to uncued, item.

Weaknesses:<br /> • The authors formulate their main hypothesis building on an assumption related to the experimental task. This task requires correctly selecting the cued grating orientation while resisting the interference from internal representations of the other orientation gratings. The authors hypothesize that if this post-encoding information selection function is supported by the MTL-s entorhinal-DG/CA3 pathway, the recorded delay-period activity should contain more information about the cued item that the uncued item (even if both are similarly remembered). Thus, the assumption here is that resolving the interference would be reflected by a more distinct representation in MTL for the cued item. Could it be the opposite, namely the MTL could better represent the unresolved interference, for example by the mechanism of hippocampal repulsion (Chanales et al., 2017). It could strengthen the findings if the authors comment on the contrary hypothesis as well.<br /> • It is not clear for me why the authors chose the inverted encoding modelling approach and what is its advantage over the others multivoxel pattern analysis approaches, for example representational similarity analysis also used in this study. How are these two complementary? Since the IEM is still a relatively new approach, maybe a little comment in the manuscript could help emphasizing the strength of the paper? Especially that this paper is of interest to researchers in the fields of both working memory and long-term memory, the latter being possibly not familiar with the IEM.

Overall, this work can have a substantial impact of the field due to its theoretical and conceptual novelty. Namely, the authors leveraged an established retro-cue task to demonstrate that a neurocomputational operation of pattern separation engages both working-memory and long-term memory, both mediated by the MTL circuitry, beyond the distinction in classic memory models. Moreover, on the methodological side, using the multivariate pattern analyses (especially the IEM) to study neural computations engaged in WM and LTM seems to be a novel and promising direction for the field.

Reviewer #2 (Public Review):

This paper reports that neonatal CD43- B cells produce IL-10 upon BCR stimulation, which inhibits TNF-alpha secretion from the peritoneal macrophage. In the neonatal CD43- B cells, the BCR-mediated signal transmitted Stat5 activation and induced IL-6 production, and subsequently, the secreted IL-6 activated Stat3 finally leading to IL-10 production. The authors identified a unique signaling pathway leading to IL-10 production and revealed the different responses between CD43+ and CD43- B cells against BCR crosslinking. A weakness of this study is that the neonatal CD43- B cell subset secreting IL-10 has not been characterized and discussed as well. BCR expression levels between adult CD43- B cells and neonatal CD43- B cells have been overlooked to explain the different reactivity. Clarity on these points would substantially enhance the impact of the manuscript.

Reviewer #2 (Public Review):

The Kaiser lab has been on the forefront in understanding the mechanism of dopamine release in central mammalian neurons. assessing dopamine neuron function has been quite difficult due to the limited experimental access to these neurons. Dopamine neurons possess a number of unique functional roles and participate in several pathophysiological conditions, making them an important target of basic research. This study here has been designed to describe the proteome of the dopamine release apparatus using proximity biotin labeling via active zone protein domains fused to BirA, to test in which ways its proteome composition is similar or different to other central nerve terminals. The control experiments demonstrating proper localization as well as specificity of biotinylation are very solid, yielding in a highly enriched and well characterized proteome data base. Several new proteins were identified and the data base will very likely be a very useful resource for future analysis of the protein composition of synapse and their function at dopamine and other synapses.

Major comment:

The authors find that loss of RIM leads to major reduction in the number of synaptically enriched proteins, while they did not see this loss of number of enriched proteins in the Syt1-KO's, arguing for undisrupted synaptome. Maybe I missed this, but which fraction of proteins and synaptic proteins are than co-detected both in the Syt1 and control conditions when comparing the Venn diagrams of Fig2 and Fig 3 Suppl. 2? This analysis may provide an estimate of the reliability of the method across experimental conditions.

Reviewer #2 (Public Review):

This paper identifies the need for improved pre-clinical models for the study of human primordial germ cells (PGCs) and suggests the common marmoset (Callithrix jacchus) as a suitable primate model. In vitro gametogenesis offers an alternative method to generate germ cells from pluripotent stem cells for study and potential pre-clinical applications. Therefore, the authors aimed to take the first steps toward developing this technology for the marmoset. Here, iPSCs have been derived from the marmoset and differentiated to PGC like-cells (PGCLCs) in vitro that have similarities in gene expression with PGCs identified from single-cell studies of marmoset embryos, as demonstrated through immunofluorescence and RT-qPCR approaches, as well as RNA-sequencing.

The authors have successfully developed a protocol that produces PGCLCs from marmoset iPSCs. These are shown to express key germline gene markers and are further shown to correlate in gene expression with PGCs from the marmoset. This study uses a 2D culture system for further expansion of the PGCLCs. When cultured with mouse testicular cells in a xenogeneic reconstituted testis culture, evidence is provided that cjPGCLCs have the capacity to develop further, expressing marker genes for later germline differentiation. However, the efficiency of generating these prospermatogonia-like cells in culture is unclear. Nonetheless, with the importance of developing protocols across species for in vitro gametogenesis, this paper takes a key step towards generating a robust preclinical system for the study of germ cells in the marmoset.

The claims of the authors are generally justified by the data provided; however, some conclusions should be clarified. In particular, the authors have failed to show convincingly that cjPGCLCs are a distinct cell type to the iPSCs that generated them. cjiPSCs cultured in feeder conditions (OF) with IWR1 are reported to cluster closely with the derived cjPGCLCs using principal component analysis of RNA-Seq data. This contrasts with the cjiPSCs cultured in feeder-free (FF) conditions which maintain a more undifferentiated/less primed state, and are not capable of differentiating to the germline lineage. Therefore, the OF/IWR1 cjiPSCs could rather be an intermediate cell-state between iPSCs and cjPGCLCs.

The reasons behind improved germline competence of iPSCs in the different media conditions are unclear. The authors reject the idea that this is due to the presence of IWR1, since this condition has not affected FF iPSCs. However, the efficiency of differentiation was greatly increased in OF conditions when IWR1 was used, indicating inhibition of WNT does indeed have a positive effect on induction to the germline lineage. This area requires further clarification.

Another area requiring clarification is the reporting of RNA sequencing data as representative of a developmental trajectory, without defining which cell lines produced clusters, or defining the stages of this trajectory. The authors refer to the identification of four clusters representative of a developmental trajectory, however, they provide unclear information as to what this refers to. Importantly, detailed transcriptomic comparisons between in vivo-derived PGCs and in vitro PGCLCs are not provided.

Functional validation of iPSC lines generated in the study is not provided besides confirming that the cells express pluripotency markers OCT3/4, SOX2, and NANOG. It is important to confirm tri-lineage differentiation of iPSCs, e.g., through an embryoid body assay. Since FF cjiPSCs were unable to differentiate into cgPGCLCs, it is even more important to confirm cells are genuine iPSCs.

In summary, although there are issues surrounding clarity, this paper is generally justified in its conclusions. The authors present an optimised protocol for the derivation of PGCLCs from marmoset iPSC-like cells, with defined expansion conditions and evidence of further differentiation to prospermatogonia-like cells.

Reviewer #2 (Public Review):

Many cancers, including pancreatic tumors, host microbes that have the ability to metabolize anti-cancer drugs, thus altering cancer response to these treatments. However, many anti-cancer drugs also are quite toxic to bacteria. Thus, the authors first investigate how a model bacterium that could live pancreatic tumors can become resistant to the pancreatic chemotherapy gemcitabine. Second, they investigate how bacteria that are resistant to gemcitabine impact cancer cell response to this therapy compared to bacteria that are not resistant. By answering these two questions, the authors hope to determine how bacterial evolution to chemotherapy can impact how well chemotherapy works in pancreatic cancer.

To answer the first question, the authors perform both genetic screens and laboratory evolution experiments of E. coli bacteria exposed to gemcitabine. Both the genetic screen and laboratory evolution experiments identified mutation of the bacterial protein nupC as mediating bacterial resistance to gemcitabine. NupC is the transporter protein that bacteria use to take up gemcitabine. Thus, the authors conclude that loss of ability to take up gemcitabine would likely underlay bacterial evolution to gemcitabine in pancreatic tumors.

To answer the second question, the authors take either control of nupC mutant bacteria and expose these to gemcitabine. They then take the bacterial media with its residual gemcitabine and treat mouse colorectal cancer cells with these media. They find the amount of gemcitabine is higher in nupC mutant media and media from these mutants cause correspondingly higher killing of cancer cells.

Thus, the authors conclude that bacteria become resistant to gemcitabine by not taking it up, leaving more gemcitabine around in tumors to kill the cancer cells. The findings of the first question are a major strength of the manuscript - the complementary genetic screen and laboratory evolution experiment convincingly show that loss of nupC is likely a major genetic route for bacteria to become resistant to gemcitabine. Excellent biochemical studies delineate mechanistically how the different mutations including nupC contribute to gemcitabine resistance in the bacteria.

However, a major weakness of the manuscript is the extension to how this laboratory evolved nupC resistance to gemcitabine influences tumor response to gemcitabine. The only experiments done to assess this are performed in colorectal cell culture models in vitro. Importantly, these in vitro models do not recapitulate chemotherapy resistance observed in pancreas cancer and utilize levels of bacteria and gemcitabine that are likely not relevant to tumor physiology. Thus, additional experiments assessing in vivo if nupC mutations become prevalent in the pancreatic tumor microbiome and how much mutations affect tumor gemcitabine levels and response will be necessary to fully answer the authors second question of how bacterial evolution to gemcitabine affects tumor response to this agent.

Reviewer #2 (Public Review):

The paper provides a natural extension of 2D multiphase field models for cell monolayers to 3D, addressing cell deformations, cell-cell interaction, cell-substrate interactions and active components for the cells. As known from 2D, the cell arrangement leads to positional (hexatic) defects and if the elongation of the cells is coarse-grained to define a global nematic order also to orientational (nematic) defects. These defects are characterized, see Figure 2. However, this is done in 2D and it remains unclear if the projected basal or apical side is considered in this figure and the following statistics. The authors identify correlations between orientational defects and extrusion events. In terms of positional defects such statistics seem not to be considered and the relation between positional defects and cell extrusion events remains vague. Also in-plane and out-of-plane stresses are computed. These results confirm a mechanical origin for cell extrusions. However, these are the only 3D information provided. The final claim that the results clearly demonstrate the existence of a mechanical route related with hexatic and nematic disclinations is not clear to me. 3D vertex models for such systems e.g. showed the importance of different mechanical behavior of the apical and basal side and identified scutoids as an essential geometric 3D feature in cell monolayers. These results are not discussed at all. A comparison of the 3D multiphase field model with such results would have been nice.

Reviewer #2 (Public Review):

Skeletal muscle is the main regulator of glycemia in mammals and a major puzzle in the field of diabetes is the mechanism by which skeletal muscle (as well as other tissues) become insensitive to insulin or decrease glucose intake. the authors had proposed in a previous publication that high intracellular calcium, by means of calpain activation, could cleave and decrease the availability of GLUT4 glucose transporters. In this manuscript, the authors identify two additional targets of calpain activation. One of them is GSK3β, a specialized kinase that when cleaved, inhibits glycogen synthase and impairs glucose utilization. The second target is junctophilin 1, a protein involved in the structure of the complex responsible for E-C coupling in skeletal muscle. The authors succeeded in showing that a fragment of junctophilin1 (JPh44) moves from the triad to other cytosolic regions including the nuclei and they show changes in gene expression under these conditions, some of them linked to glucose metabolism.

Overall, the manuscript shows a novel and audacious approach with a careful treatment of the data (that was not always easy nor obvious) that allow sensible conclusions and definitively constitutes a step forward in this field.

Reviewer #2 (Public Review):

This paper investigates the maintenance and function of memory follicular helper T (Tfh) cell subsets using in vitro approaches, murine immunization models and vaccine-challenged humans. Murine Tfh cell subsets (Tfh1, Tfh2, Tfh17) were generated using in vitro polarization (iTfh1, iTfh2, iTfh17), and then tested for support of humoral response following adoptive transfer or adoptive transfer with resting in vivo for 35 days. iTfh17 cells were statistically better than iTfh1 and iTfh2 cells in promoting GC B cell and plasma cell maturation after resting in vivo, although all 3 populations were capable of B cell help. Tfh17 cells were comparatively enriched among blood borne Tfh central memory cells in humans, and were enriched at the memory phase of vaccination with hepatitis B and influenza vaccines, compared to effector phase, suggesting the possibility they are comparatively superior in Tfh cell memory formation, with greater persistence in aged individuals.

Significance<br /> The enrichment of Tfh17 cells in Tfh cell central memory compartment and the dominance of Tfh17 cell population and the Tfh17 transcriptional signature in circulating Tfh cells at the memory phase are nicely demonstrated, and may well be helpful for understanding the heterogeneity of memory Tfh cells and potentially providing clues for vaccine design. The in vitro differentiation system for mouse Tfh cells also provides a strategy for others to build upon in dissection of Tfh cell development and function.

Points to consider<br /> 1. Even though Tfh17 cells are more likely to persist at memory timepoints in mice and in humans, or produce more GC B cells or plasma cells following transfer, all subsets can do this. Is GC output otherwise distinguishable following transfer of the individual subsets, or is their effect (cytokine related perhaps) pre-GC with differential CSR? It is also not clear if the individual subsets populate the GC and assuming they do so, if their respective phenotypes persist when they become GC Tfh cells.

2. iTfh17 cells induce more GC B cells and antibodies after resting and antigen challenge (Figures 1, 2). However, it's not clear whether this effect is a consequence of comparatively enhanced iTfh17 survival during resting (as suggested by latter figures), or better expansion or differential skewing to Tfh differentiation during challenge (as suggested by Figure 1 J,K). The total number of remaining adoptively-transferred cells right before challenge and 7 days post challenge will be helpful to understand that.

3. The authors tried to address whether Tfh17 cells have better ability to survive till memory phase or Tfh17 cells with memory potential are generated at higher frequency at the effector phase of vaccination (Figure 5); however, the experiment is not conclusive. The cTfh population 7 days post vaccination is a mixed population with effector Tph cells and Tfh memory precursors. The increased frequency of Th17 cells at day 28 compared to day 7 could be a consequence of superior survival ability, or Tfh memory precursors with Tfh17 signature are better generated.

4. Experiments to confirm expansion ability of the human subsets or their B cell helper ability were not performed.

Reviewer #2 (Public Review):

This study addresses the ways in which bacteriophages antagonize or coopt the DNA restriction or recombination functions of the bacterial RecBCD helicase-nuclease.

The strength of the paper lies in the marriage of biochemistry and structural biology.

A cryo-EM structure of the RecBCD•gp5.9 complex establishes that gp5.9 is a DNA-mimetic dimer composed of an acidic parallel coiled coil that occupies the dsDNA binding site on the RecB and RecC subunits. The structure of gp5.9 is different from that of the RecBCD-inhibiting DNA mimetic protein phage λ Gam.

Cryo-EM structures of Abc2 are solved in complex with RecBCD bound to a forked DNA duplex, revealing that Abc2 interacts with the RecC subunit. A companion structure is solved containing PPI that copurifies with RecBCD•Abc2.

Whereas the gp5.9 structure fully rationalizes the effect of gp5.9 on RecBCD activity, the Abc2 structure - while illuminating the docking site on RecBCD, a clear advance - does not clarify how Abc2 impacts RecBCD function.

The authors speculate that Abc2 binding prevents RecA loading on the unwound DNA 3' strand while favoring the loading of the phage recombinase Erf.

Does the structure provide impetus and clues for further experiments to elaborate on that question and, if so, how?

Reviewer #2 (Public Review):

The molecular changes of the aged tendon are not well understood. Loiselle et al previously established a mouse model that mimics aging tendon, where they depleted Scleraxis lineage (Scxlin) cells from tendon by injecting diptheria toxin (DT) in mice expressing the DT receptor under the control of the Scx promoter (DTR mice). In this manuscript, the authors demonstrate that the tendons from DTR mice resemble tendons from aged WT mice, in that they both have decreased cellularity, altered collagen organization (via SHG imaging), and impaired biomechanical properties. Proteomic analysis of WT, DTR, and aged WT tendons show that both DTR and aged WT tendons have decreased expression of extracellular matrix proteins (ECM). Corresponding with this, single RNA seq analysis of tendons from these three groups of mice showed that while WT tendons are enriched for genes related to collagen and ECM synthesis and also inflammation, DTR tendons express genes associated with ECM organization and structure and aged tendons express genes that regulate inflammation. The authors point out that this supports designing therapies to prevent tendon cell death to prevent the changes seen in aging tendon.

These data enhances the understanding of the protein and gene changes associated with aging in the tendon and in particular characterizes the importance of Scx+ cells to tendon organization and the aging process. The conclusions are supported by the data presented.

The manuscript would be strengthened by:<br /> 1) Improved clarity of figures presented<br /> 2) More details on the methodology used for biomechanical testing<br /> 3) Clarification if the decrease in ECM protein expression is due to decreased cellularity in the tendons of the DTR and aged mice, or decreased expression per cell<br /> 4) Providing more details on genes that are downregulated in comparison between groups

Reviewer #2 (Public Review):

These discoveries are strongly supported by a large amount of clear and convincing data. Thus, the expression of seven distinct pol III-transcribed genes covering all types of promoter is shown to increase in three cell lines when STAT3 is overexpressed and to decrease when endogenous STAT3 is depleted. The proliferation of HepG2 liver cancer cells can be increased by STAT3 overexpression and decreased by STAT3 depletion. Crucially, proliferative induction by STAT3 is dependent on increased pol III activity, as it can be blocked using a pol III-specific inhibitor at a concentration that allows normal levels of pol III activity, but prevents further elevation. Growth of HepG2 xenograft tumours in mice is also slowed significantly when STAT3 is depleted. The effects of STAT3 on pol III output are indirect, mediated by miR-106a-5p. Thus, the knockdown of miR-106a-5p reverses the drop in pol III product expression following STAT3 depletion; conversely, pol III output is stimulated by a miR-106a-5p mimic. Elevated levels of miR-106a-5p correlate with significantly worse prognosis for patients with liver cancer. A key target for miR-106a-5p is a sequence in the 3'-UTR of the mRNA encoding TP73. Complementarity to this sequence allows miR-106a-5p to deplete the expression of TP73 and this is shown to be crucial for STAT3 to regulate the proliferation of HepG2 cells. Furthermore, TP73 is revealed to be a direct repressor of pol III-mediated transcription, an activity not previously known. TP73 is shown to inhibit the assembly of TFIIIB, the factor that is responsible for recruiting pol III to all of its genetic templates. A clear and convincing causal flow can therefore be traced: STAT3 induces miR-106a-5p, which depletes TP73, thereby removing a brake that limits pol III output and cell proliferation.

Reviewer #2 (Public Review):

Summary:<br /> Dominant mutations in the gene encoding LIS1 cause lissencephaly, a severe developmental brain disorder. LIS1 regulates the multisubunit microtubule motor, cytoplasmic dynein 1, which can exist in an autoinhibited (closed) form and an activatable (open) form. Dynein is only active when bound to another complex, dynactin, and one of several known cargo adaptors. Because dynactin and cargo adaptors only interact with the open form, the local ratio of open to closed dynein can potentially dictate the proportion of "activatable" motors. The current view is that LIS1 stimulates dynein by reducing the autoinhibited closed form, and by recruiting two dynein motors to the active complex, which is thought to increase speeds and run lengths. LIS1 is highly conserved across animal and fungal species. The budding yeast LIS1 ortholog, called Pac1, is around 43% identical to human LIS1. Both Pac1 and LIS1 regulate dynein but there have been intriguing differences in their effect on dynein processivity in assays with purified proteins. The authors of the current manuscript recently published high resolution cryo-EM studies of Pac1 bound to yeast dynein (Gilles 2022). Based on their models they tested several mutations predicted to impact Pac1 binding to dynein and showed these mutations disrupted the single dynein dependent process in budding yeast, translocation of the mitotic spindle. However, mutations in yeast dynein that impacted LIS1 binding apparently only modestly impacted human dynein, prompting the current study that compares cryo-EM studies of human LIS1 bound to human dynein with the previously published studies using yeast proteins. The work points to subtle differences in how yeast and human LIS1 interact with the stem and loop regions of yeast and human dynein heavy chains and reveal an intriguing difference in the residues predicted to be important for the interaction between the two LIS1 propeller structures in the LIS1 dimer. They also report map known disease causing mutations in LIS1 and dynein on the structures and find three that might impact residues involved in protein-protein interaction.

Methods:<br /> This group has been able to use innovative methods to increase the resolution of CryoEM images to 3-4 Å, allowing them to make more accurate predictions about residues involved in protein-protein interactions. They have substantial expertise in the analysis of the resultant data, as demonstrated by past peer review studies. These are very labor-intensive experiments that allow a level of detail not possible with standard biochemical or cell biological analyses.

Results:<br /> The studies revealed subtle, but potentially important, differences between the yeast and human proteins.

Based on their analyses, the authors predicted specific residues that are likely to be important for human LIS1-dynein interactions with the stem region of dynein (sitestem) and with dyneins AAA domain containing ring (sitering). They also predicted specific residues that are likely to be important for an interaction between the two LIS1 beta-propellers, which in the yeast protein is apparently critical for dynein regulation.

The prediction that K147 could be important in the interaction between beta-propellers is very intriguing, given evidence that a K147A mutation disrupts LIS1 binding to dynein, but not to NDEL1, another interacting protein.

Impact

The predictions set out in this manuscript, if they hold up, could inform the design of tools to study LIS1 in the context of human disease. It seems likely from the data that at least some of the indicated residues will be important for human LIS1/dynein interactions

Reviewer #2 (Public Review):

The authors have provided a large dataset of ribosomal RNA sequences to assist in the molecular identification of rare and unstudied medically important mosquitoes in four locations with high biodiversity and mosquito-borne virus circulation, Cambodia, French Guiana, Madagascar, and the Central African Republic. This was accomplished using a non-traditional approach, rRNA seq, which could help in the identification of novel potential vectors of disease in hotspots of transmission. Their method uses previously published insect and non-insect-specific rRNA sequences from multiple locations to perform "depletion" of interfering rRNA. This method allowed the authors to create both 28s and 18s sequences for the identification of novel species of mosquito vectors with high reliability based on phylogenetic analysis and utility where traditional cytochrome oxidase subunit I sequences are not available for systematics.

Strengths:<br /> The non-traditional approach used is well described and provides novel guidance for researchers undertaking similar studies.

The depletion method described allowed the authors to identify mosquito rRNA sequences even in the instance of non-target RNA being present.

Weaknesses:<br /> The author's approach, as with traditional approaches to molecular identification of vector species, relies on expert entomologists capable of identifying mosquitoes in the field which is rare in most places. The authors do not provide citations for the taxonomic keys used for morphological identification, which in many places are outdated or unavailable for specific locations.

While next-generation sequencing is becoming more available, it is still largely unobtainable for researchers lacking resources and infrastructure which is common in locations similar to those the authors provide these data for.

The authors give no explanation as to why they chose rRNA-seq as their method of next-generation sequencing, which is most commonly used for transcriptomics, instead of traditional DNA-based metagenomics which is more commonly used to define community relationships as would be more appropriate for this study.

Reviewer #2 (Public Review):

I agree with the authors (line 421) that their "findings provide a remarkable example of how carbohydrate metabolism dictates the relative importance of different sources of actin filaments for CAR dynamics during cellular division." The scope of the work is very broad, and the manuscript reports dozens of interesting phenotypes with high-quality experimental data. However, most points are not investigated in depth.

My main reservation is the presentation of the work. The writing style is conversational and expansive, which makes it challenging for the reader. Furthermore, long paragraphs shift from one topic to the next rather than using separate paragraphs with strong topic sentences to cover each topic. I suggested a few places to start new paragraphs, but many more paragraphs could be divided. I edited one paragraph to illustrate how the text might be cut in half.

Most of the figures are also overly complicated. I did not attempt to edit one of them, but I am sure that findings will be much clearer with about half of the panels moved to supplemental materials, so the reader can concentrate on the most important data.

Line 873: Fig 1C and many other figures. The legend says the error bars are SD's but they include far less than 2/3 of the measurements, so something is wrong. In Fig 4A and other figures, three data points are insufficient to verify a normal distribution, a prerequisite for using the Student's T-test. Furthermore, the T-test requires equal SD's.

Reviewer #2 (Public Review):

Starrett et al performed whole genome and transcriptome sequencing of bladder cancers from 43 organ transplant recipients. They found that most of these tumors contained DNA from one of four viruses (BKPyV, JCPyV, HPV, and TTV). Viral genomes are most often integrated into the genomes of these tumor cells and the authors provide evidence that the integration utilized the POL theta-mediated end joining pathway. In most cases, viral RNA was detected in tumors with viral DNA. This suggests that the viruses are actively altering the cellular environment. Frequently, this resulted in similarities for overall gene expression patterns in the tumors that were grouped by the type of virus present in the tumor. Moreover, the changes in expression linked with viral gene expression were found in genes relevant to tumorigenesis. Immunohistochemical detection of viral proteins in these tumors also demonstrated active viral gene expression. However, the presence of viral proteins was heterogenous within the tumor, with between 1 and 100% of the tumor staining positive for BKPyV large T antigen. An analysis of mutational signatures in these tumors indicate that the viruses are also shaping the tumor genome by inducing mutations. Evidence that specific viruses are contributing to tumorigenesis in organ transplant patients has fundamental implications for preventing tumorigenesis in these patients.

The conclusions of this paper are generally well supported by the data provided. Indeed, there is little doubt that viral infections are more likely in these tumors. However, there are aspects of the paper that could be improved and or clarified. Most importantly, despite the strong evidence that the viruses are altering the tumor cell environment, it is unclear if these changes are necessary for tumorigenesis or less excitingly the result of an even more immune suppressive environment within the tumor. The heterogeneity of the LT expression suggests that the presence of the viral DNA and RNA may not be enough to assess whether it is actively contributing to the tumor. Is an increased frequency of viral protein staining linked with any evidence of an active contribution to tumorigenesis (fewer tumor-suppressor/oncogene mutations). that they reduced mutations in tumor suppressors. This might be easiest to assess with the tumors that have oncogenic HPV DNA. If those tumors lacked p53 and RB mutations, it would support a causative role for the virus.

Reviewer #2 (Public Review):

Synaptic transmission is a fundamental process of communication in the brain. How and where neurotransmitter release occurs is still an open question. This study addresses an interesting question about the spatiotemporal location of neurotransmitter release in a synapse. This has important implications for postsynaptic signaling and neural excitability in general. The work provides valuable additions to recently uncovered discrepancies in the nanometer scale organization of the two primary forms of evoked vesicle fusion (synchronous and asynchronous) in the synapse from two very different methods. Essentially demonstrating convincingly that synchronous and asynchronous release sites are unshared. The study utilizes tools of super-resolution measurements of synaptic transmission that were previously developed in their lab, which help bridge the discrepancies using a convincing number of experimental paradigms. Limits in the speed of optical resolution opened a few questions of interpretation. However, this study greatly expands our knowledge of synaptic architecture and function of different forms of release. A further claim of different coupling of vesicle fusion and retrieval kinetics is made that at present seems incomplete due to temporal limitation of the super-resolution method.

Reviewer #2 (Public Review):

In this work entitled "Live imaging reveals chromatin compaction transitions and dynamic transcriptional bursting during stem cell differentiation in vivo" the authors use a combination of genetic and imaging tools to characterize dynamic changes in chromatin compaction of cells undergoing epidermal stem cell differentiation and to relate chromatin compaction to transcriptional regulation in vivo. They track this phenomenon by imaging the epithelium at the ear of live mice, thus in a physiological context. By following individual nuclei expressing H2B-GFP along time ranges of hours and up to 3 days, they develop a strategy to quantify the profile of chromatin compaction across different epidermal layers based on normalized intensity profiles of H2B-GFP. They observe that cells belonging to the basal stem cell layer display a considerable level of internuclear variability in chromatin compaction that is cell-cycle independent. Instead, intercellular variability in chromatin compaction appears more related to the differentiation status of the cells as it is stable in the hours range but dynamic in the days range. The authors show that differentiated nuclei in the spinous layer exhibit higher chromatin compaction. They also identified a subset of cells in the basal stem layer with an intermediate profile of chromatin compaction and with the dynamic expression of the early differentiation marker keratin 10. Lastly, they show that the expression of keratin-10 precedes the chromatin compaction establishing relevant temporal relationships in the process of epidermal differentiation.

This work includes a number of challenging approaches and techniques since it is carried out in living mice. Also, it provides nice tools and methods to study chromatin structure in vivo during multiple days and within a differentiation physiological system. On the other hand, the results are descriptive and, in some respect, expected in line with previous observations.

Reviewer #2 (Public Review):

This submission seeks to detect changes in the rate of selfing through pairwise comparison of haplotypes sampled from a population. It begins, as did a previous paper by a subset of the authors (Sellinger et al. 2020), with the well-known theoretical finding that partial selfing increases the rate of coalescence and decreases the rate of crossing-over events in genealogical histories.

I am supportive of pitching this contribution as primarily theoretical, with the very short discussion of the Arabidopsis data provided as a worked example. This perspective increases my enthusiasm, compared to an initial reading. My comments are intended to encourage development.

Some thematic characteristics reduce the impact of the submission. Among these are:<br /> (1) a rather less than a scholarly perspective on previous literature;<br /> (2) tendency to avoid theoretical development in favor of computation;<br /> (3) little interpretation of results of their only analysis of real data.

Reviewer #2 (Public Review):

The paper has two key messages: the discovery and the function of LncSox17. Claims of gene discovery are today untrivial, given the large number of genome-wide datasets. Of course, I understand the authors cannot check everything but I feel some more clear and deep analysis of current databases is lacking. Also, the exact coordinates of the lncRNA are not easy to find in the manuscript.

Many statistical analyses are rather lacking. In particular I did not find details of how the DEGs were identified during differentiation (FDR? How many replicates?).

The results of the smFISH are surprising, since the level of expression seems rather low in comparison to the qPCR (only 4 times less expressed than Sox17) or the RNA-seq.

Reviewer #2 (Public Review):

The X-ray crystal structure of the K. lactis Rad6-Bre1 interaction solved by Shi et al. adds an important piece to the puzzle of how H2B mono-ubiquitination is deposited. The primary strength of this work is the new structural information on the Rad6-Bre1 interaction, which reveals contacts of the E3 (Bre1) to the backside of the E2 (Rad6). Through mutagenesis and biochemical experiments, Shi et al. probe the importance of these contacts for the Rad6-Bre1 interaction, active site accessibility, and Rad6 catalytic activity. In general, the functional data support the structural model and confirm the importance of Bre1 in stimulating Rad6 catalytic activity in vitro and H2Bub1 in yeast. In comparison to the structural data, some of the functional data are not as robust and are at times over-interpreted. However, in general, the conclusions drawn by the authors about the importance of the newly revealed Rad6-Bre1 interface are appropriate and substantiated by the data.

Reviewer #2 (Public Review):

The manuscript by Sun et al., investigates the synaptic plasticity underlying visuo-auditory association. Through a series of in vivo and ex vivo electrophysiology recordings, the authors show that high-frequency stimulation (HFLS) of the cholecystokinin (CCK) positive neurons in the entorhino-auditory projection paired with an auditory stimulus can evoke long-term potentiation (LTP) of the visuo-auditory projection. However, LTP of the visuo-auditory projection could not be elicited by HFLS of the visuo-auditory projection itself or by an unpaired stimulus. They further demonstrate that auditory stimulus pairing with CCK is required to elicit LTP of the visuo-auditory projection as well as visuo-auditory association in a fear conditioning behavioral experiment. As they found elevated expression of CCK in entorhinal neurons which project to the auditory cortex, they conclude that HFLS of the entorhino-auditory projection causes CCK release.

Strengths:

The authors use an elegant approach with Chrimson and Chronos to stimulate different auditory inputs in the same mouse in vivo and also in slice and demonstrate that potentiation of the visuo-auditory projection is dependent on HFLS of the entorhino-auditory projection paired with auditory stimulus. Furthermore, they test several parameters in a systematic fashion, generating a comprehensive analysis of the plasticity changes that regulate visuo-auditory association.

Weaknesses:

In their previous publications (Chen et al., 2019; Li et al., 2014; Zhang et al., 2020), it has been established that HFLS of the entorhino-auditory projection and CKK release are important for visuo-auditory association via electrophysiology and behavioral experiments. The Chrimson and Chronos approach was applied by Zhang et al., 2020, where they already found that the visuo-auditory projection was potentiated through HFLS of entorhino-neocortical fibers. This manuscript extends those findings by testing different parameters of pairing, which may not represent a major conceptual advance. Unlike the electrophysiological recordings, drug infusion is used in behavioral manipulations to show that HFLS of the entorhino-auditory projection is important for visuo-auditory association. While the use of drugs to inhibit CKK receptors is important, it does not directly demonstrate that CCK release from the entorhino-auditory is necessary.

Reviewer #2 (Public Review):

Zhao et al., set out to investigate the molecular mechanisms controlling the timing between training tasks that leads to proactive interference (Pro-I) buildup (i.e. formation) and consequently interference in the retrieval of the newly learned memory.

During the time-dependent stabilization of newly acquired memory (i.e. memory consolidation), the memory traces are vulnerable to disruption by a variety of amnestic influences. When multiple learning events occur in rapid succession, competition occurs between consolidating memories. However, the factors that regulate what memory is remembered or forgotten are unknown. Two interference models of forgetting are proposed in the literature: events occurring prior to learning cause forgetting through proactive interference (Pro-I), or events occurring after learning cause forgetting through retroactive interference (Retro-I).

The most common explanation for Pro-I and its buildup is that this phenomenon emerges due to the competition between two differing task memories (e.g. aversive memories) for storage in overlapping brain areas. The behavioural consequence of this Pro-I buildup is that the recall of newly learned information is impaired when is preceded by a similar learning task. On the other hand, several accounts are used to describe the release from Pro-I (i.e. the reduction of proactive interference): a) having a more distinctive target task compared to the interference task (either different material or relying on different neural circuits), b) prolonging the lag between training tasks and c) contextual changes between the two learnings. Drosophila is an ideal model for the study of these questions, given the detailed knowledge base of how different types of memories are encoded, consolidated, and retrieved and the effects of context changes in these memories.

In this study, the authors use the classic aversive conditioning paradigm, where flies learn to associate an odor A with shock (in the target task), this task is preceded by a proactive task or is followed by a retroactive task, where odor X is paired with a shock. Taking advantage of the known molecular pathways for the more well-characterized model of interference (Retro-I), the authors extended the knowledge for these types of interference models. To uncover the mechanisms underlying the timing of Pro-I, the authors genetically manipulated the activity of a key phosphatase (Corkscrew) and its downstream pathway (Raf/MAPk). This phosphatase was chosen given its known role in controlling the appropriate training intervals for the induction of long-term memory in flies.

A strength of the manuscript is that the authors showed the unique and exclusive role of Corkscrew in regulating Pro-I and its temporal dynamics. Furthermore, the authors described that Corkscrew regulates Pro-I via a single subset (γ) of the intrinsic cells (i.e. Kenyon cells) of the mushroom body, which is the centre of learning and memory in Drosophila. However, the manuscript would have been improved had they characterized the Pro-I task more thoroughly. This is because behaviourally what the authors are observing might look like Pro-I buildup, but other scenarios can also explain the data (e.g. passive decay of the first memory, memory storage limitations, attentional deficits). This would be solved by applying known Pro-I release protocols and, in this way, would be more comparable to the known Pro-I literature.

Interestingly in the mammalian field, phosphatase activity is also known as a key regulator of long-term depression and memory formation. Taken together, this data implies the conserved role of phosphatase activity and its subsequent plasticity during the process of learning a new task. Furthermore, this work shows the importance of phosphatase activity in facilitating memory consolidation of newly learned information, which might occur by suppressing any potential interference from old memories in the same neuronal circuits.

Reviewer #2 (Public Review):

The authors used both pharmacological inhibition and genetic TPL2 kinase dead (KD) mice to test the hypothesis, that inhibition of TPL2 attenuates the microglia inflammatory response to stimuli such as LPS and in the context of chronic (tau mouse model) and acute (optic nerve crush/stroke) neurodegenerative models. The use of TPL2 kinase dead mice rather than KO mice is elegant and important because of the non-enzymatic role of TPL2 in stabilization of its interacting partner ABIN-2. The authors convincingly demonstrated that pharmacological and genetic inhibition of TLP2 in primary microglia reduced the production of pro-inflammatory cytokines, chemokines, and iNOS and consequently reduced neuronal cell death in neuronal-microglial cocultures. Genetic inhibition of TLP2 reduced partially the inflammatory response of microglia in the PS31 tau model. Furthermore, the authors observed reduced infiltration of T cells and dendritic cells. Notably, TLP2 inhibition rescued behavioral deficits in PS31 mice. Overall, these studies support the possibility that inhibition of TPL2 kinase may have translational potential in prevention or treatment of tau-driven neurodegeneration. One aspect of the study that merits further investigation is the alteration in the population structure of myeloid cells in the brain under the various conditions that were evaluated using single cell RNA seq. Very high representation of microglia was observed in TauP301S mice at nine months of age. These findings could reflect bias in recovery of cells for the single cell RNA sequencing assay and independent validation of microglia cellularity by immunohistochemistry would address this question.

Reviewer #2 (Public Review):

Mecp2 is the causative gene for RTT and MDS, but the Mecp2 driven pathogenesis is not clearly defined. While Mecp2 is a regulator of gene expression, identifying downstream genes that are robustly regulated by Mecp2 have been a challenge. The authors utilized computational approach to identify Mecp2 regulated genes using previously published differentially expressed genes in hippocampi of MDS mice treated with Mecp2-specific ASO (Shao et. al., 2021). Through this analysis, the authors shortlisted Gdf11, which also validated in an additional 20 transcriptional profiles for Mecp2 perturbed rat, mouse, and human brain samples.

The transcriptional regulation of Gdf11 by Mecp2 was confirmed using genetic murine models, including Mecp2 -knockout, Gdf11 mutant and Mecp2-tg1.<br /> Finally, the CUT and RUN analysis showed increased Mecp2 binding upstream of the Gdf11 TSS in Mecp2-tg1 hippocampi, which was lost in Mecp2 knockout hippocampus. Mecp2 loss increases H3K27me3, which suggested Mecp2 prevents transcriptional silencing of Gdf11. While these results provide mechanistic insight into the transcriptional control of Gdf11 by Mecp2, it remains unclear how Mecp2, which is generally a transcriptional suppressor increases Gdf11.

The author elegantly demonstrates that normalization of Gdf11 levels in Mecp2-tg1 mice crossed with Gdf11 improves several behavioral deficits in the MDS mice model. In contrast, loss of one copy of gdf11 in mice caused neurobehavioral deficits using a battery of behavioral tests, such as elevated plus maze, rotarod, anxiety tests and shock-tone conditioning.

Finally, the authors show that loss of one copy of gdf11 does not alter proliferation in the adult mouse SGZ or no gross changes in brain anatomy or volume of the dentate gyrus.

Overall, the authors demonstrate that gdf11 is robustly regulated by mecp2, which coup provide new therapeutic options for Mecp2-related diseases, such as RTT and MDS. As discussed in the paper, additional studies are needed to test whether Gdf11 can rescue behavioral deficit in symptomatic RTT murine models.

Reviewer #2 (Public Review):

This manuscript explores the importance of the plastid-hosted SUF iron-sulfur cluster synthesis pathway for plastid maintenance and for the viability of blood stages of the human parasite Plasmodium falciparum. The authors convincingly demonstrate that while most of the proteins of the SUF pathway are essential to P. falciparum survival only one, the cysteine desulfurase SufS, also leads to the loss of the plastid. The authors then explore the possibility that SufS may be providing sulfur to a plastid-localised putative tRNA modifying enzyme, MnmA. They demonstrate that, like when SufS is depleted, specific depletion of MnmA impairs parasite viability and causes plastid loss. They also elegantly complement this phenotype with bacterial MnmA expressed together with a bacterial cysteine desulfurase or even alone, suggesting that SufS from the parasite is able to directly transfer sulfur to the bacterial MnmA.

Overall, this is a well-conducted and well-controlled study, for which I do not have any major criticism, although tRNA purification, identification, and quantification in the SufS and MnmA mutants would bring more compelling evidence that tRNA thiolation is affected in these mutants.

Reviewer #2 (Public Review):

In this manuscript, Li et al. sought to identify tumor suppressor proteins in mesenchymal stem cell conditioned media in which PKA signaling was up-regulated by treatment with a small molecule, and in osteosarcoma-enriched transcripts, to provide alternative treatment strategies to combat osteosarcoma. They identified several proteins that when forcibly expressed both in vitro and in vivo, can suppress osteosarcoma viability, growth, and motility. This manuscript presents a substantial amount of data, is well organized, and provides a novel approach to addressing osteosarcomas. The data is thorough and convincing and provides an alternative approach to developing cancer therapeutics.

Reviewer #2 (Public Review):

The study by Smela et al describes the direct differentiation of human "Granulosa-like cells" via the overexpression of a limited number of transcription factors in pluripotent cells. This approach builds on other contemporary work to produce functional support cells of the mammalian gonad.

The work does succeed to establish cultured cells that retain some characteristics of these ovarian support cells, including the expression of granulosa cell markers, steroid biosynthesis in response to stimulation, and some evidence of acute germline support. The study also marks an important technological development towards the production of in vitro conditions for the production of human gametes from iPS cells. Prior efforts using human germline cells have mostly focussed on xeno-organoid approaches, and so the human-human nature of the present study represents a useful advance. Of particular note, the present study identifies a remarkably fast acquisition of DDX4 and DAZL-positive cells when both germline and support cells are both derived from a human source. This is an intriguing finding, as other groups have reported a substantial delay in acquiring this germline state when cells from mixed species are used. While these findings are of key technological importance towards ongoing efforts to create in vitro gametes, there appear to be some issues of reproducibility, and a lack of deep functional characterisation.

Several conclusions of the paper need to be described in much greater detail. For example, the regulatory effects of the over-expression of transcription factors are stated in Figures 1 and 2, but how this regulatory logic was assembled is not presented, and the methods by which this logic was experimentally probed are not presented. Second, the abstract highlights two transcription factors that are both necessary and sufficient for granulosa-like cell production. While sufficiency is tested through the overexpression of the transcription factors, necessity is not conventionally assessed through a genetic approach. The upregulation of factors in response to transcription factor overexpression does not seem appropriately described. Third, the transcriptional comparison of granulosa-like cells with cancer cell lines that do not reflect normal granulosa cells should be reconsidered.

The study contributes an important step towards the production of functional human granulosa cells from pluripotent cells, though the central conclusions would benefit from a more robust interrogation of the cell status achieved.

Reviewer #2 (Public Review):

This manuscript details the role of the rILN to the DS pathway in the onset of operant behavior that promotes the delivery of a reward and in the ultimate acquisition of that reward. The strengths of the paper are in the detailed fiber photometry study that encompasses several behavioral domains that correlate to the signal observed in the rILN to DS pathway. I am especially interested in how the "encoding" shifts across time as the animals refine their behavior both in a temporal sense and in the magnitude of the signal. Further, the authors demonstrate then that this is dependent on action, as they do not observe signals in a Pavlovian behavioral task, but do observe reward-based signals in a "free consumption" task (the strawberry milk). The examination into devaluation also enhances the understanding of this pathway, even though there were no differences between a valued and devalued task. Finally, the authors examine bi-directional optogenetic manipulation of the pathway, and its impact on how the trials are completed, omitted, or incomplete. They find that manipulation alters the % completed trials and regulates trial omission. This paper really does not have any glaring weaknesses to point out, however, the physiological assessment does seem to have a few strong trends and even though the studies are well powered, and included both sexes, sex as a biological variable was not commented on that I could find. My estimation of the data doesn't suggest strong sex differences in any metric measured. Additionally, the data that included projections to the rILN were very interesting, and future studies looking into the physiology of these neurons, and/or how the physiology of these neurons adapt after operant training may be very interesting to understand plasticity within the adaptation across the training from FR1 to FR5 with time limits.

Reviewer #2 (Public Review):

The present study from Xiaorui Shi's lab investigated the effect of pericyte depletion on spiral ganglion neurons and auditory function. Results in in vitro culture system proposed that pericyte-derived exosomes contain VEGF, and promote not just vascular stability but neuronal survival through Flk1. This study is an extension of their previous study showing pericyte depletion causes auditory dysfunction, which is ameliorated by VEGF gene therapy (Zhang et al., JCI insight 2021). Overall, the data are clear and sophisticated and promote our understanding of the biological roles of pericytes in neuronal function. Several points should be thoroughly discussed or supported by definitive experiments like analysis of neuron-specific Flk1 KO mice.

Reviewer #2 (Public Review):

In this work, Illingworth et al. investigate the effectiveness of ribavirin and favipiravir on the treatment of a paediatric patient with chronic RSV. These drugs cause mutations and the authors tested whether they could observe this effect through deep sequencing viruses from nasal aspirates over the course of treatment. They found an increase in mutations caused by ribavirin but favipiravir appeared to have no additional mutagenic effect. Despite the lack of change in viral load, the authors suggest that the ribavirin reduced viral fitness and did not lead to adaptive escape mutations. The authors modelled how generation time and fitness interacted with mutational load. They also estimated fitness for different haplotypes generated from the mutational data.

Strengths of the paper:

Using mutagenic drugs to treat viruses is generally accepted but results have been mixed with severe viral infections and specific evidence of the precise effects of the drugs is often lacking. This paper is especially valuable for demonstrating that despite in vitro evidence that favipiravir had some effect against RSV, there was no evidence for favipiravir having an effect in a patient. This differs from the authors previous work showing a clear clinical benefit to favipiravir in treating influenza. This paper also appears to be the first to sequence RSV from a patient having been exposed to ribavirin which is important for demonstrating that the drug is having a measurable effect.

Weaknesses in the paper:

I think there is a conceptual problem with the paper. Ribavirin is supposed to increase the mutational rate of the virus which would increase the mutational load. Mutational load has been calculated by summing up the frequencies of minor alleles. However, if a particular mutation rises in frequency, it does not mean that ribavirin has caused additional mutations at the same site but rather viruses containing the mutation have risen in frequency. If a subpopulation containing mutations rises through drift or selection to a relatively high percentage that will bias the mutational load. The authors provide ~75 mutations which were at significant percentages across multiple different timepoints. It seems that these mutations contribute significantly to the mutational load but changes in mutation percentages between samples do not reflect changes in mutational events but changes in viral haplotypes/subpopulations. In a previous study Lumby et al. 2020, the authors removed mutations at >5% from their analysis but there is no indication that they performed this step similarly here. Summing many small changes will give an indication of background mutational rate (though counting only a single mutation at each locus is perhaps the only method to remove the effect of viral clonal expansion).

While ribavirin appears to have shown an effect, many questions remain. Why does the mutational load only increase for 3 points before plateauing? The authors would likely argue that this is the new saturation point for mutation load but they don't test it. Sequencing points from after the cessation of treatment would be expected to show lower mutational load but this data was not collected. Furthermore, questions remain over the methodology. It is thought that Ribavirin should only increase transitions and a transition/transversion ratio for the different samples would have been helpful. The absolute numbers of many mutation classes appear to have increased including transversions e.g AU. There isn't a good reason why nucleoside analogues should have caused this effect and perhaps it is an artefact.

I don't think that the authors can reasonably determine how many haplotypes there are in the population from short read sequencing data. I think that the sequencing data very clearly shows subpopulations due to the large changes in mutation frequencies between different time points. The authors say that their analysis assumes a well-mixed population which is clearly not the case. Therefore, determining fitness of different haplotypes or mutations is likely not accurate.

The authors construct a model to estimate viral fitness and suggest that viral fitness decreased with the drug. This is somewhat problematic to me as viral load has not changed so it would be reasonable to say that viral fitness was likely unaffected by the drug. The authors define fitness in terms of the number of mutations that each virus likely has and assumes that these mutations are deleterious. The authors then use this to claim that mutagenic drugs reduce fitness. This seems very circular to me. If the drugs reduce fitness, it should be observed as a property of the virus population. As the only measure was viral load, which didn't change, it is difficult to claim ribavirin reduced viral fitness. There are other reasons why there could be an increase in the number of mutations e.g. sequencing more subpopulations which would have nothing to do with fitness.

At various points, the paper assumes that there is no selection taking place but immunoglobulin was being applied weekly and palivizumab monthly. The timing of when these drugs were given should be included. How did the palivizumab affect selection? The K272E mutation seems to go up and down but it is not clear if this was in response to drug infusion timing or if this mutation was present in a subpopulation.<br /> I think the main impact of the paper will be that favipiravir will not be used in the future to treat RSV. Given that the EC50 of favipiravir against RSC is ~100x that of influenza, favipiravir was unlikely to reach a therapeutic level in the patient. Nucleoside analogues have a mixed record at treating serious viral infections. Hopefully, this work will spur on future studies to precisely measure the effect that ribavirin has on RSV.

Reviewer #2 (Public Review):

The authors aimed to determine the mode of inhibition of the serotonin transporter SERT as a by-product of MDMA synthesis (ECSI#6). They present a thorough kinetic analysis, using different experimental techniques (binding and transport inhibition) and kinetic modelling. They also test the predicted pharmocophore effect of the compound. In my view, the authors provide compelling evidence for an uncompetitive inhibition mechanism, in which the compound most likely binds to the inward-facing and K+-bound state. Inhibitors of this type may have the potential for therapeutic use.

Reviewer #2 (Public Review):

This manuscript applied the SAXS data analysis of protein self-assembly by implementing the simultaneous fitting of intra- and inter-molecular motions/conformations against SAXS data at a series of oligomerization states/concentrations. Despite several major assumptions hinted, a diverse pool of conformational and oligomeric candidates was generated from CG simulations, and more importantly, these candidates were fitted into these SAXS data to reach a reasonable agreement, suggesting a somewhat convergence (even if the ensemble-fitting could well be at a local minimal). This is considered a technical advance, given the fairly large numbers of both the oligomer fraction phi_i (i=1, ..., N) and the conformational weight w_k (k=1, ..., n), where N is the number of oligomers and n is the number of internal conformational states.

Central is optimizing phi_i and w_k, simultaneously. The former has been illustrated in Fig. 4 and SI-Fig. 7 for the total number of 60-mers. The latter relies on an overfitting-preventing strategy, as shown in SI_Fig. 1, where an effective fraction cutoff was used from 0.1 to 1.0, as opposed to the number of conformational states. What are the numbers of conformational states for these oligomers? This should be quantifiable, e.g., defining the conformational differences by chi_2.

Reviewer #2 (Public Review):

Using live cell imaging, this article describes the oscillation of a tip localized protein, SofT, to hyphal tips during growth of a nematode-trapping fungus, independently of the oscillation of this protein during chemotropic interactions prior to cell fusion. The authors observe oscillation of SofT, which becomes entrained as opposing oscillations at hyphal tips during chemotropic interactions, a process that requires calcium signaling. The authors build on a previously developed mathematical model describing oscillation of proteins to fusion tips during chemotropic interactions with a transition period from single hyphal tip oscillation to coordinated oscillation during chemotropic interactions.

Reviewer #2 (Public Review):

When I was asked to review this paper, I was quite excited, as the analysis seemed very timely. Many of us in biomedical science feel like we are at an inflection point in our field. The combined impact of the pandemic on both people's outlook and on the supply chain, the sharply rising costs of living in major metropolitan areas, and the increasing gap in potential salaries between industry and stipends for graduate students and postdocs are shaking our field. The need to increase salaries for PhD students and postdocs is colliding with a 20+ year stagnation in the size of a non-modular R01, creating major challenges for many basic science labs.

However, having read the piece, I am quite disappointed at what seems to be a missed opportunity. The scientific community at large, and particularly the basic science community is hungry for data like this, to use to try and convince Congress and NIH as a whole to address the issues above. However, as far as I can tell, the authors are not writing for this audience-in fact I was puzzled about their view of for what audience this was intended. I will note several major issues-all could be addressed but would require an effort to tell this story in a much more comprehensible and complete way

1. The manuscript assumes an understanding of both economic terminology and statistical approaches that will not be familiar to most of the audience, if I am a representative example. This begins in the abstract, much of which I found incomprehensible. I still am not sure about the definition of "nominal costs ", and I certainly have no idea what they mean by a "wholly non-parametric machine learning regression". This continues throughout-presenting much of the data as Log10-transformed costs means that many of the graphs become impossible for a normal mortal like me to interpret.

2. The version presented is written like some early outline draft. Rather than using narrative to guide the reader through the data, it reads like a series of Figure legends. For example, I literally thought the text on page 4 were the Figure legends, but they are not. "Figure 2 shows...." "Table 1 shows...". The Discussion is similarly difficult to follow. Given the complexity and importance of the data they present, this is a major missed opportunity

3. What will most interest my own part of the NIH-community is the assertion that "real dollar adjusted" grant funding has not decreased, but has instead remained flat. Few people I know will believe this. The authors address in a less-than-clear fashion some of the reasons for this-solicited versus non-solicited awards, clinical trials, etc, but do not dig into their own data to identify what are likely to be other issues. I doubt any one of the 20+ NIH-funded researchers in my Department (predominantly NIGMS funded) has a grant that reaches the "median level"-I do not after 32 years of continuous NIH-funding. Most new NIGMS-funded researchers, including many in my Department, are coming in funded by MIRA grants, which at $250K are half the median grant size. They do spend a few moments on disparities in Figure 7, but much more could be pulled out of this data set. Digging into issues like this-distributions in different NIH Institutes, at different career levels, etc, would make this work much more impactful.

As one example, this analysis from NIGMS suggests the median grant was likely under $225K, a year when their data suggest the median grant overall was $400k<br /> https://loop.nigms.nih.gov/2016/05/distribution-of-nigms-r01-award-sizes/

My bottom line-this study addresses a key question, but as currently written does so in a way that will minimize its impact

Reviewer #2 (Public Review):

The manuscript aims to define in detail the role of the LIM homeodomain transcription factor isl2 in the acquisition of cardinal spinal motor neuron identities. The authors, by using a number of different and complementary techniques, analyze Isl2 expression in motor neuron subtypes and describe the consequences of its loss on motor neuron generation, positional organization, sensorimotor connectivity, and function. While the importance of Isl2 for the development of axial and visceral motor neurons was already known, the data presented here convincingly show that Isl2 has a previously unappreciated role in controlling differentiation of a subset of motor neurons innervating proximal hindlimb muscles by regulating the expression of the ETS transcription factor Pae3.

Reviewer #2 (Public Review):

Understanding the molecular mechanism of obesity-associated OA is highly in clinical demand. Overall, the current study is well-designed and illustrated that down-regulated GAS6 impairs synovial macrophage efferocytosis and promotes obesity-associated osteoarthritis. Based on the patient's sample, the data indicated synovial tissues are highly hyperplastic in obese OA patients and infiltrated with more polarized M1 macrophages than in non-obese OA patients. Further authors proved that obesity promotes synovial M1 macrophage accumulation and GAS6 was inhibited in synovitis during OA development in mice models. The sample size, data collection, and quality of the IHC and immunofluorescent histological sections are outstanding. The results were well presented with appropriate interpretation. But the following major questions should be addressed.

Major:<br /> 1. Animal model: Ten-week-old animals received DMM surgery and were fed a standard/HFD diet for 4 or 8 weeks prior to specimen harvest. Since Wang J and other studies have shown that male ApoE(-/-) and C57BL/6J wild-type (WT) mice fed with a high-fat diet for 12 or 24 weeks, and the ApoE(-/-) mice gained less body weight and had less fat mass and lower triglyceride levels with better insulin sensitivity and lower levels of inflammatory markers in skeletal muscle than WT (Wang J, et al. Atherosclerosis. 2012 Aug;223(2):342-9. PMID: 22770993; Hofmann SM, et al. Diabetes. 2008 Jan;57(1):5-12. PMID: 17914034; Kypreos KE, et al. J Biomed Res. 2017 Nov 1;32(3):183-90. PMID: 29770778). Thus, it is very important to provide the data on the final body weight gained in your groups and provide a relative background of the animal model chosen in the introduction or discussion. Please explain why ApoE-/- mouse model, and how this animal model is clinically relevant. Does a high-fat diet induced obsess OA available in C57BL/6 WT?<br /> 2. Control group: The DMM surgery was performed on the right leg, and the contralateral knee joint should be used as a baseline to show the level of M1 macrophage infiltration under the obsess microenvironment.

Reviewer #2 (Public Review):

The manuscript from Harrington and colleagues describes the development and characterization of two new mouse resources that report MHC class I and class II expression. In these mice the tomato reporter gene was embedded into the gene encoding beta 2-microglobulin, to report class I expression, and separately in the CD74 gene, to report class II expression. The group highlights the need for such reporters by describing the growing interest in MHC expression by oligodendrocyte lineage cells in inflammatory CNS disorders, and they nicely demonstrate the utility of these reporters using mouse models of multiple sclerosis. There is also an emerging appreciation that immune cell infiltration into the CNS occurs in myriad neurological disorders, such that these models will likely have wide utility. The paper is clearly written and will be of wide interest.

Reviewer #2 (Public Review):

Here the authors tackle the problem of identifying which parts of a TMS-evoked response are local to the stimulation site versus driven by reverberant activity from other regions. To do this they use a dataset of EEG recorded simultaneously with TMS pulses, and examine virtual lesions of a network of neural masses fitted to the data. The fitting uses a very recent model inversion method developed by the authors, able to fit time series directly rather than just summary statistics thereof. And it apparently works rather well indeed, at least after the first ~50 ms post-stimulus. I expect many readers will be keen to try this fitting method in their own work.

Reviewer #2 (Public Review):

The authors use a genetically encoded calcium indicator to measure Ca in flagella to establish that Ca influx correlates with flagellar length. (Despite this correlation, there is so much noise that it is dubious that Ca level can regulate the flagella's length.) Then, they show that reduced Ca decreases the rate of IFT trains entering flagella, which ruins the ion-current model of regulating flagella's length. (Ca can still be one of the factors that sets the target length.) Ca does not seem to change the disassembly rate either. There are also no correlations between Ca influx spikes and IFT injection events. Curiously, these spikes broke pauses of retrograde IFT trains, but that still did not affect IFTs entering dynamics.

Some other possibilities like Ca regulating unloading rates are discussed and convincingly rejected.

The study ends with an interesting Discussion, which talks about other possible models, and concludes that the only model not easily rejected so far is the mechanism relying on diffusion time for kinesins from flagella to the cell body being greater in longer flagella.

The paper is well written, very thorough, contains significant results.

Reviewer #2 (Public Review)

This paper seeks to contribute new empirical insight into the (potential) energetic benefits of schooling. Toward this aim, the authors establish an experimental setup in which brook trout swim in a thrust wake generated by an oscillating airfoil. By combining measurements of body motion and particle image velocimetry, the authors successfully detail how brook trout respond to an incoming thrust wake.

Strengths:<br /> • The idea of using an airfoil that oscillates in the sway and yaw direction is original and a valuable contribution to the simulation of thrust wakes using simplified mechanical systems.<br /> • The experiments are executed with a high level of accuracy and detail, offering important insight into animal locomotion in a thrust wake. In particular, acquiring experimental data on the flow physics (velocity and pressure) for this kind of problem is a major endeavor, which the authors have successfully and originally addressed.<br /> • Performing experiments on the same animals twice is an excellent idea to explore the role of body size, without inflating the number of animals needed for experiments.

Weaknesses:<br /> • The novelty of the robotics-based experimental approach is overstated; several studies have studied the response of live fish to thrust wakes, generated by pitching airfoils or robotic fish.<br /> • The length of the test section for the experiments is very much comparable with the body length of the animals, thereby raising doubts regarding the confounding role of wall interactions. Likewise, the role of 3D effects is elusive; experimental data are in 2D and no discussion is included about the extent to which such an approximation is valid and how it impacts quantitative measurements of vorticity and pressure included in the paper.<br /> • Other sensory modalities (such as touch and the vestibular system) and their integration are not examined in the paper, limiting the understanding of the reader of the way in which fish appraise their surrounding to obtain hydrodynamic advantage from thrust wakes.

Findings of the research can offer valuable insight into the hydrodynamic mechanisms at the basis of schooling, stimulating further interdisciplinary research at the interface of biology and engineering (fluid mechanics and robotics).

Reviewer #2 (Public Review):

- Aim of the study:

Agip et al. studied the structure of respiratory complex I from Drosophila melanogaster, an important model organism with well-developed genetic toolkit and sufficiently close phylogenetic relationship to mammals. They isolated the complex and analyzed its structure by single-particle electron cryo-microscopy (cryo-EM). They also used mass spectrometry to characterize new subunits. So far, the structures of complex I have been reported for several organisms, including mammals, plants, ciliates, fungi and bacteria, but ones from insects have been missing. This study aims to fill this gap and shed light on some of the key questions pertaining complex I biology, such as 1) the conservacy of supernumerary subunits, 2) the mechanisms and physiological relevance of active/deactive transition and 3) the correspondence between the structurally defined closed/open conformations and the biochemically defined active/deactive states.

- Strengths:

The study provides the first structure of complex I from insects, the organisms at an important phylogenetic branch that has diverged from mammals more recently than other eukaryotic species such as plants and fungi. Using purification methods they developed for mammalian enzymes previously, the authors successfully purified the insect enzyme with high quality - a monodisperse peak in gel filtration, the NADH oxidation activity comparable to mammalian enzymes, and the homogenous subunit composition as confirmed by single-particle analyses. It is noteworthy that the authors used state-of-the art tools in model building and validation, such as ISOLDE and MapQ, which makes this model of high standard. In my opinion such careful validation is particularly important for modelling such a gigantic complex, since without cares one can easily misinterpret the density and draw wrong conclusions.

The resolution is 3.3 Angstrom for the best class (Dm1), which allowed modelling side chains and comparing between the observed 3D classes and to the known structures. The model confirms the presence of 43 subunits, akin to mammalinan enzymes, composed of 14 conserved core subunits, 28 supernumerary subunits that have close homologs in mammals, and one supernumerary subunit CG9034 that has not been predicted. They are also structurally similar to mammalian enzymes except for minor local differences. The two supernumerary subunits (NDUFC1 and NDUFA2) that are present in mammals are missing. The authors discuss evidence that NDUFC1 is absent from the Drosophila genome and NDUFA2 is genomically present but its expression is restricted to the male germline. Together, the overall similarity to the mammalian enzyme underlines the use of Drosophila complex I as a model system.

One of the remarkable findings is that common biochemical treatments that are used to deactivate mammalian complex I - heat treatment or NEM treatment - did not reveal deactive state of Drosophila complex I. This is in agreement with their observation that most structural elements are in the active state. The major Dm1 conformation shows all structural features in the active conformation, whereas Dm2 state shows two features in the deactive conformations. Here the author raises an interesting point that the structural elements formerly believed to behave in a consorted manner are actually not coupled, providing new perspective in interpreting complex I structures presented so far and in future. Notably, the authors adopted the same purification procedure for bovine and murine samples. This is a particular strength that they applied a similar procedure for but still observed different behaviors for Drosophila (the absence of the deactive state).

- Weaknesses:

As the authors point out in Discussion, the biochemical statuses of the two described conformations, Dm1 and Dm2, are uncertain. If we assume that Dm1 is a ready-to-go active state, Dm2 could represent several of the possible states; a partially broken state due to delipidation by detergent, a meta-stable state during enzyme turnover, an intermediate towards "full deactiving" structural transition (which the authors argue is unlikely to occur), or a fully reversible state that is in equilibrium to Dm1. Despite these uncertainties, the structure will serve as an excellent starting point to address many open questions in the complex I field in future.

In the final 3D classification the number of classes was set to 3 (K = 3). This is an arbitrary human decision and implicitly forces particles to separate into 3 descrete classes. It would have been great to mention if the authors had tried different classification parameters and, if so, whether that had led to similar classification results. There are different methods available to dissect conformational heterogeneity other than simple 3D classification. For example, focused classification can differentiate local structural features. MultiBody refinement and 3D variabitlity can analyze continuous conformational changes. The simple 3D classification with local angular sampling employed here may lead to over-simplification of the more complex structural heterogeneity.

Although 37 degrees heat treatment and NEM treatment did not reveal any sign of deactivation in Drosophila complex I, it does not rule out the possibility that insect complex I has different ways to deactivate the enzyme, to prevent ROS production. It is probably the limitation of applying existing assays that are originally for mammalian and fungal enzymes to the study of insect enzymes.

- Whether they achieved the aims and whether the conclusions are supported by the results:

Overall, they successfully isolated the active enzyme and determined its structure at 3.3 A resolution, which meets the current state-of-the-art for single-particle cryo-EM and provided an atomic picture of the enzyme composition. The study confirms that the Drosophila complex I is structurally similar to mammalian complex I, but biochemically different in that it does not show the deactive state. It still does not exclude the possibility that Drosophila complex I can transition into a currently unknown state that prevents reverse electron transfer. This question however can be tackled in future by mutagenesis analyses as Drosophila is a genetically tractable organism.

- Impact to the field and utility of the data to the community:

Complex I is important not only for human health but also for understanding universal principles of biological respiration, because of its universal presence in most organisms on Earth. This study provides a basis for relating mammalian complex I with those from other branches of organisms. The current structures will allow Drosophila researchers to interpret and design any mutations that affect complex I functions, and relate them to behavioral, developmental and metabolical changes at tissues, organs and individuals levels.

Reviewer #2 (Public Review):

This work characterizes the diversity of Fruitless-expressing neurons in developing, mid-pupal Drosophila brains using single-cell sequencing. This was a reasonably in-depth effort to characterize sexually specific cell types during neural development. The use of single-cell sequencing tools to understand developmental mechanisms and not just adult function is appreciated. Some of the recent broader efforts, such as a recent whole-head atlas, contained limited numbers of cells for many cell types and have likely missed rare cell types. Sorting cells of an interesting category in order to enrich their representation in the set, with specific questions in mind, is in some ways a stronger and more targeted approach.

I am surprised that the authors observed so much overlap between Fruitless-expressing cells of the same type in males and females and so few sex-specific cell types, which is interesting. Of course, cells of the same overall "type" could have differential wiring and function given the expression of Fruitless. This study suggests that such a modification may not require a wholesale change in gene expression profiles and may be enabled via a restricted set of changes in target gene expression. Overall, while the outcome is a bit descriptive, these efforts produced some interesting biological insights, and this dataset should serve as a resource for future efforts.

Reviewer #2 (Public Review):

The application of AlphaFold to the prediction of the peptide TCR recognition process is not without challenge; at heart, this is a multi-protein recognition event. While Alphafold does very well at modelling single protein chains its handling of multi-chain interactions such as those of antibody-antigens pairs have performed substantially lower than for other targets (Ghani et al. 2021). This has led to the development of specialised pipelines that tweak the prediction process to improve the prediction of such key biological interactions. Prediction of individual TCR:pMHC complexes shares many of the challenges apparent within antibody-antigen prediction but also has its own unique possibilities for error.

One of the current limitations of AlphaFold Multimer is that it doesn't support multi-chain templating. As with antibodies, this is a major issue for the prediction of TCR:pMHC complexes as the nearest model for a given pMHC, TRAV, or TRBV sequence may be in entirely different files. Bradley's pipeline creates a diverse set of 12-hybrid AlphaFold templates to circumvent this limitation, this approach constrains inter-chain docking and therefore speeds predictions by removing the time-consuming MSA step of the AlphaFold pipeline. This adapted pipeline produces higher-quality models when benchmarked on 20 targets without a close homolog within the training data.

The challenge to the work is of course not generating predictions but establishing a functional scoring system for the docked poses of the pMHC:TCR and most importantly clearly understanding/communicating when modelling has failed. Thus, importantly Bradley's pipeline shows a strong correlation between its predicted and observed model accuracy. To this end, Bradley uses a receiver operating characteristic curve to discriminate between a TCR's actual antigen and 9 test decoys. This is an interesting testing regime, which appears to function well for the 8 case studies reported. It certainly leaves me wanting to better understand the failure mode for the two outliers - have these correctly modelled the pMHC but failed to dock the TCRs for example or visa versa?

The real test of the current work, or its future iteration, will be the ability to make predictions from large tetramer-sorted datasets which then couple with experimental testing. The pipeline's current iteration may have some utility here but future improvements will make for exciting changes to current experimental methods. Overall the work is a step towards applying structural understanding to the vast amount of next-generation TCR sequence data currently being produced and improves upon current AlphaFold capability.

Reviewer #2 (Public Review):

A major challenge to studying the ABC transporter dynamics "in situ" is the lack of precise measurement of various structural conformers that correspond to intermediate states during the ATP-catalytic or substrate-transport cycle. The use of the conformation-specific antibody 5D3 has recently enabled structural biology to experimentally visualize a specific structural fold that corresponds to an apo and inward-facing (IF) state of ABCG2. In this study, Gyöngy et al aimed to develop a mammalian cell-based system for ABCG2 to investigate how nucleotide or drug ligands regulate the transporter's alternating nature of its inward- and outward-facing (OF) conformations. The authors exploited the nature of 5D3 to only recognize ABCG2' IF conformers and combined flow cytometry and confocal microscopy to systematically analyze the IF-OF switches in the presence of nucleotides, drug substrates, ATPase inhibitors, and a known ABCG2 inhibitor Ko143. The authors find that nucleotide binding alone is sufficient to decrease the propensity of IF conformation, as well as to drive the high-to-low drug substrate transformation, and subsequently the drug-induced ATP hydrolysis resets the transporter to the IF and 5D3-bound state. These data provide solid cell-based evidence that adds to the ongoing discussion about the allosteric regulation of ABCG2 by both nucleotide and transport substrate ligands. Most importantly, the results support several lines of functional implications that could not be fully addressed by recent high-profile cryo-EM structures of ABCG2.

Strengths:<br /> The development of the methodology is a tour-de-force effort, as well as the biggest strength of this study. The results and the experimental protocol will likely provide a significant impact on how scientists design experiments to address structural questions without using large-scale purified systems and conventional structural biology approaches.

The validity of using the GFP-tagged ABCG2 variant is supported by several lines of functional characterizations, including protein expression, 5D3 reactivity, the responsiveness of nucleotide analogs, and mitoxantrone (MX) accumulation analysis. The application of such a strategy is particularly exemplified by the systematic treatment of various nucleotide analogs, which is sufficient to establish kinetic analysis by looking into apparent nucleotide affinities. These initial works add confidence in performing experiments by using either transport substrates or ABCG2 inhibitors. It is very compelling to see candidly the drug-coupled stimulation of ATP hydrolysis, given that both ATP and ADP decrease the 5D3-bound population.

The development of fluorescence correlation spectroscopy (FCS), the first in such a study, allows the measurement of colocalization of both fluorescence-labeled transporter and transport substrates. As illustrated by MX binding to ABCG2, the data supports the notion that nucleotide binding drives substrate release from the transporters, which in this case, can be explained by the high-to-low substrate binding affinity or IF-OF conformational switch of the transporter. Moreover, such an assay will be likely used as part of a high-throughput pipeline in search of therapeutic drugs against ABCG2.

Weakness:<br /> Although the paper presents solid and compelling cell-based evidence describing the relationship between structural changes of ABCG2 and ligand bindings, the enthusiasm is slightly dampened by the fact that this study seems mostly used to support the hypotheses that were proposed by recent cryo-EM structures. It is unclear from this study whether new insight into ABCG2's working mechanism can be proposed based on the data in this manuscript.

In addition, the IF-OF switch represents the transformation of two extreme conformations in ABCG2. The authors do not address the intermediate states, such as occluded conformers, in this study, which makes one wonder whether this is a limitation of the methodology presented in this manuscript. Moreover, interdomain crosstalk is highlighted in this manuscript to address the communication between NBD and TMD. However, it is not clear how the data could say anything about the crosstalk between NBD and TMD. For example, one limitation of recording 5D3 sensitivity on WT proteins may not allow us to pinpoint how structural motifs at the NBD-TMD interface (e.g., Q-loop, triple-helix bundle, polar relay, etc) transmit signals that cause IF-OF switch. The authors do not address how the strategy described here can address such a gap.

Lastly, the authors illustrate the conformational change of 5D3 epitope in the extracellular domain (ECD) by using atomic models in the presence and absence of the antibody. The dynamic information of how the ECD transforms to non-5D3 reactive is limited through this study; for instance, what the timing is to set loose of antibodies upon nucleotide binding, or to what degree of drug binding, IF starts to transit to OF under the physiological condition. Despite this, it is worth noting that 30% of MX-ABCG2 colocalization was still observed in untreated cells, perhaps suggesting a dynamic equilibrium between substrate-bound IF and other conformers.

back to life, revenge, trophy, head, speaking animal with second life, the deer also fights back

first half is type 1, first half is type 2

get out use of deer ... chris, black resistance, fables...taxidermy hidden in plain sight, coded/only chris to understand

slavery fables weak/vermin intro get out deer...wits and taxidermy

speaking animals ... speaking through eyes/perspective

Reviewer #2 (Public Review):

"The cellular architecture of memory modules in Drosophila supports stochastic input integration" is a classical biophysical compartmental modelling study. It takes advantage of some simple current injection protocols in a massively complex mushroom body neuron called MBON-a3 and compartmental models that simulate the electrophysiological behaviour given a detailed description of the anatomical extent of its neurites.

This work is interesting in a number of ways:

- The input structure information comes from EM data (Kenyon cells) although this is not discussed much in the paper<br /> - The paper predicts a potentially novel normalization of the throughput of KC inputs at the level of the proximal dendrite and soma<br /> - It claims a new computational principle in dendrites, this didn't become very clear to me

Problems I see:

- The current injections did not last long enough to reach steady state (e.g. Figure 1FG), and the model current injection traces have two time constants but the data only one (Figure 2DF). This does not make me very confident in the results and conclusions.<br /> - The time constant in Table 1 is much shorter than in Figure 1FG?<br /> - Related to this, the capacitance values are very low maybe this can be explained by the model's wrong assumption of tau?<br /> - That latter in turn could be because of either space clamp issues in this hugely complex cell or bad model predictions due to incomplete reconstructions, bad match between morphology and electrophysiology (both are from different datasets?), or unknown ion channels that produce non-linear behaviour during the current injections.<br /> - The PRAXIS method in NEURON seems too ad hoc. Passive properties of a neuron should probably rather be explored in parameter scans.

Questions I have:

- Computational aspects were previously addressed by e.g. Larry Abbott and Gilles Laurent (sparse coding), how do the findings here distinguish themselves from this work<br /> - What is valence information?<br /> - It seems that Martin Nawrot's work would be relevant to this work<br /> - Compactification and democratization could be related to other work like Otopalik et al 2017 eLife but also passive normalization. The equal efficiency in line 427 reminds me of dendritic/synaptic democracy and dendritic constancy<br /> - The morphology does not obviously seem compact, how unusual would it be that such a complex dendrite is so compact?<br /> - What were the advantages of using the EM circuit?<br /> - Isn't Fig 4E rather trivial if the cell is compact?

Overall, I am worried that the passive modelling study of the MBON-a3 does not provide enough evidence to explain the electrophysiological behaviour of the cell and to make accurate predictions of the cell's responses to a variety of stochastic KC inputs.

Reviewer #2 (Public Review):

The paper entitled "International Multicenter Study Comparing Cancer to Non-Cancer Patients with COVID-19: Impact of Risk Factors and Treatment Modalities on Survivorship" by Raad et al. is a multi-center, international, matched cohort, with a relatively large sample size. The aim of this work is to determine independent risk factors that impact survival in the setting of "novel treatment modalities" like Remdesivir. It enrolled patients with COVID-19 and cancer and compared them to cancer-negative controls. The authors conclude that cancer increases mortality from COVID-19 and that Remdesivir can reduce all-cause mortality in a subset of patients receiving low-flow oxygen and the results support their conclusions. Overall, this paper adds to the growing body of literature that implicates cancer as a worse predictor of survival among patients with COVID-19. The use of a matched cohort makes it unique and strengthens the findings of this study. The potential weaknesses of this study are its retrospective nature and lack of data on the effect of vaccination in this population since the study was conducted prior to the introduction of vaccines.

Reviewer #2 (Public Review):

This is a well written manuscript that provides a useful analysis on using PCT for guiding antibiotics use among cancer patients with COVID19, a very common issue with COVID 19 patients in general but more challenging in the cancer population. Analysis is relatively straight forward. Results support the claim that antibiotics for more than 72 hours may be unnecessary for cancer patients with negative cultures and PCT<0.25. This is can be useful clinically to limit unnecessary antibiotic use, however would only apply this as a very broad generalization. It would be interesting to see what outcomes are and if this applies for more specific and challenging but not uncommon clinical scenarios with cancer patients (i.e neutropenic patients, patients undergoing active therapy, ICU admission) where clinicians may favor longer use of antibiotics.

Reviewer #2 (Public Review):

In this paper, Diehl and Redish recorded simultaneously from multiple medial frontal cortical regions while rats are performing a restaurant-row task. Their results provide insights into how neurons in the different regions may represent different aspects of the decision-making process.

The strength of the study is the experimental design. The restaurant-row task is an excellent and rich paradigm for evaluating decision-making, with specific unique components that may be relatable to economic subjective choices. The other strength is the electrophysiological approach, which enables the author to simultaneously record from multiple medial frontal cortical regions. This leads to a large data set of >3,000 single units recorded during behavior. A weakness of this study is the insistence to dissect the results and assign each region to specific behaviors, while the data seem to suggest that similar signals can be observed across multiple regions, albeit to different degrees. The framework of distributed vs. gradient vs. subregions seems like a strawman idea that does not help with the interpretation of the results, whereas the actual data are already quite rich and interesting.

Reviewer #2 (Public Review):

This work by Martis illustrates, in a predator-prey or parasite-host eco-evolutionary context, the classical idea of bet hedging or biological insurance: where a single population would fluctuate and perhaps risk extinction, summing over multiple sub-populations with asynchronous dynamics (some going up while others go down) allows a stabler total abundance.

Here the sub-populations are various genotypes of one predator and one prey species, fluctuations are due to their ecological interactions, their dynamics are more asynchronous when predation is more specialized (i.e. the various predator genotypes differ more in which prey types they can eat), and mutations allow the regeneration of genotypes that have gone extinct, thus ensuring that the diversity of subpopulations is not lost (corresponding to a "clonal interference" regime with multiple coexisting genotypes).

While the general idea of bet hedging has been explored in many settings, the devil is usually in the details: for instance, sub-populations should be connected enough to allow the rescue of those going extinct, but a too strong connection would simply synchronize their temporal dynamics and lose the benefit of bet hedging. In some cases, connections between sub-populations could even be destabilizing (e.g. Turing instabilities in space).

In a recent surge of physics-inspired many-species theories, where fluctuations arise from ecological dynamics, these details are notably starting to be understood in the case of spatial bet hedging, i.e. genetically identical subpopulations in multiple patches connected by migration (see e.g. Roy et al PLoS Comp Bio 2020 or Pierce et al PNAS 2020).

In the non-spatial eco-evolutionary setting considered here, the connecting flux is one of mutations rather than migrations, and a predator genotype can in principle interact with all prey genotypes (whereas in usual spatialized models, interactions cannot occur between different patches). Another possibly important detail here is that similar genotypes do not have similar interaction phenotypes, meaning there is no risk of evolution being confined in a neighborhood of similar phenotypes. According to the author and my own cursory exploration of the relevant eco-evo literature (with which I am less familiar than pure ecology), this setting has yet to see many developments in the spirit of the many-species theories mentioned above.

These differences make this new inquiry worthwhile and I applaud the author for undertaking it. From a theoretical perspective, three results emerging from the simulations stand out in this article as potentially very interesting:<br /> - rather sharp transitions in extinction probability and strain diversity as mutation flux and predator specialization increase.<br /> - how mutation rate and interaction strength combine, notably in power-law expressions for total population abundance<br /> - the discussion of susceptibilities, i.e. how predator and prey populations respond to perturbations, as a key ingredient in understanding the previous results, in particular with counter-intuitive negative susceptibilities indicating positive feedback loops.

It is a bit unfortunate that these more novel points are only briefly explored in the main text: while they are more developed in appendices, these arguments are not always as complete, polished and distilled as they might have been in a main text, so an article focusing entirely on explaining them deeply and intuitively would have been far more exciting to me.

Finally, I will note that I am not convinced by the framing of the current manuscript as a counterpoint to Robert May's idea of destabilizing diversity - in many ways I think this is a less relevant context than that of bet hedging, and it does a worse job at showcasing what is genuinely interesting and original here; I would thus encourage readers to read this paper in the framing I propose above.

Reviewer #2 (Public Review):

Coronary heart disease (CHD) is a major form of cardiovascular disease, the first cause of mortality in the world. The etiology of CHD is multifactorial and polygenic, with atherosclerosis as the main cause of coronary stenosis and ischemic events. Evidence from basic research in small animal models and clinical trials aiming at lowering proinflammatory cytokines such as IL-1β implicated low-grade inflammation in atherosclerosis pathogenesis. Genetic studies in humans report large numbers of risk variants and genes related to macrophages, monocytes and T-lymphocytes biology supporting further immunity and inflammation in CHD risk. The study conducted by this group reports the results of the investigation of the potential association between 22 persistent or frequently recurring pathogen infections with the risk of CHD in a CoLaus|PsyCoLaus study, a prospective population-based and urban cohort of European ancestry. The authors accessed data over 12 years and assessed the association between traditional risk factors through the SCORE2 estimation of risk, a recently validated score specifically developed to predict cardiovascular risk in European countries, genetic risk scores based on GWAS findings, and seropositivity to infections. They were able to confirm the utility of the application of SCORE2 in their population, and report a significant association of the genetic score with the incidence of CHD, both traditional and genetic factors being independent predictors, which was expected. An intriguing result regards reported seropositivity with F. nucleatum to significantly predict incident CHD. This a commensal bacterium that belongs to the normal oral microbiome reported playing an important role in the development and progression of gingivitis (gum inflammation) and periodontitis (infection of the gums). There are several existing lines of evidence connecting oral infections as an independent risk factor for CHD. The results reported by this study provide support for the increased risk of CHD in oral infection through seropositivity to F. nucleatum. However, the direct clinical implications, through the recommendation to search for prior infection with this bacterium as a predicting biomarker of this disease are not on the clinical application agenda yet. The infection seropositivity was measured only at the beginning of the study, with no information on how the oral seropositivity to this pathogen may have evolved over time. And given the novelty of this association, these results need to be replicated in independent cohorts with similar designs (prospective cohorts) before recommendation to screen for seropositivity could be recommended.

Reviewer #2 (Public Review):

Despite previous studies, regulation of the genes required for galactose metabolism in Candida albicans has remained murky. For example, previous work had highlighted Rtg1 and Rtg3 as the key regulator components, an interesting finding given that these factors are important for glucose not galactose regulation in S. cerevisiae. As galactose metabolism is one of the best-understood regulatory systems, the evolutionary difference in the regulation of the galactose response has the potential to teach us about regulatory evolution in general.

The authors initially sought to understand how GlcNAc signaling cross-reacted with galactose gene induction, but they quickly discovered that Reg1, the mediator of GlcNAc signaling was essential for galactose metabolism while Rtg1 and Rtg3 were not. Overturning previous work requires strong evidence, and the authors deliver with a series of growth assays, qPCR, and chromatin IP in wt and mutant backgrounds.

The authors go further to demonstrate that the factor itself interacts with galactose based on isothermal calorimetry (although it would be nice to have seen if this was specific to galactose over glucose or GlcNAc). They show glucose regulation occurs by Reg1 recruiting Cga1 in a manner independent of the activation domain of Reg1 (immunoprecipitation, reporter assays, and chromatin IP). In contrast, Reg1 activation mediated by GlcNAc requires Reg1's activation domain and employs Rgs1. Once again, the experimental evidence for these two regulatory mechanisms is strong.

Evolutionary analysis shows that this specific instantiation of this mechanism, the combination of Reg1 and Cga1, is probably restricted to the CTG clade. While the paper does not explain how these regulatory changes happen, it sets the foundation for future work to tease this apart; work that before this paper would have been unlikely to have been successful.

Reviewer #2 (Public Review):

The study by Nunez et al. builds upon structural work from the MacKinnon lab and the authors' labs to characterize how Ca2+, via calmodulin, interacts with Kv7 channels to mediate redox sensitivity. Using FRET experiments to support electrophysiology, the authors demonstrate an interaction defined by calmodulin, the helixA-helixB fork, and the S2-S3 linker. The experiments are well performed and the conclusions drawn are appropriate. These experiments help further define the redox signaling for Kv7 channels. A weakness is that the model in Figure 7 seems speculative, as the data provided do not appear to explain how the VSD is engaged/disengaged from the pore. Rather, most of the data concentrate on biochemical interactions and structural interpretations (via FRET signals, etc.) of conformational changes in the presence of calcium. Further, the model as presented is not informative. The illustrations do not demonstrate successfully what the authors wish to claim, and the illustrations/models are not sufficiently supported by the data presented.

Reviewer #2 (Public Review):

Kato, Jenkins, et al. investigates cell-intrinsic and environmental determinants of diverse modes of collective cancer cell invasion in mucosal squamous cell carcinoma (muSCC). To explore this large parameter space, the authors develop a Cellular Potts model recapitulating two distinct in vitro muSCC - cancer-associated fibroblast (CAF) co-culture models: an organotypic platform containing an air/extracellular matrix (ECM) interface and a spheroid model mimicking dermal invasion and confinement by 3D ECM. Integrating between in silico predictions and quantitative assessment of the two experimental platforms, the authors make several interesting observations regarding determinants of the mode of collective SCC invasion. Of these, the most significant include the ability of SCCs to invade with deletion of β1 integrin in their organotypic model although invasion phenotype is altered, and identification of a synergistic dependence on cell-cell adhesion and matrix proteolysis for controlling strand width and growth within the invading cohort. Cell-cell adhesions are essential for maintaining supracellular actomyosin coupling to coordinate the invading cohort, while matrix proteolysis is necessary for creating physical space that supports both invasion and cell growth within confined space.

Overall, despite some concerns regarding support for specific claims, alternative considerations, and clarity in presentation, this study is rigorous and of high quality, and should serve as an important technical and conceptual resource that provides new insight into multicellular coordination in SCC invasion. More broadly, it illustrates the utility of coupling computational models with advanced 3D cell culture platforms to parse multifactorial control over complex forms of tissue morphogenesis.

Reviewer #2 (Public Review):

The authors consider the application of Granger causality (GC) analysis to calcium imaging data and identify several challenges therein and provide methodological approaches to address them. In particular, they consider case studies involving fluorescence recordings from the motoneurons in embryonic zebrafish and the brainstem and hindbrain of larval zebrafish to demonstrate the utility of the proposed solutions in removing the spurious links that the naive GC identifies.

The paper is well-written and the results on the chosen case studies are compelling. However, the proposed work would benefit from discussing the contributions of this work in the context of existing and relevant literature and clarifying some of the methodological points that require more rigorous treatment. I have the following comments:

Major comments:

1) I would like to point out recent literature that adapts the classical GC for both electrophysiology data and calcium imaging data:

[1] A. Sheikhattar et al., "Extracting Neuronal Functional Network Dynamics via Adaptive Granger Causality Analysis", PNAS, Vol. 115, No. 17, E3869-E3878, 2018.

[2] N. A. Francis et al., "Small Networks Encode Decision-Making in Primary Auditory Cortex", Neuron, Vol. 97, No. 4, 2018.

[3] N. A. Francis et al., "Sequential Transmission of Task-Relevant Information in Cortical Neuronal Networks", Cell Reports, Vol. 39, No. 9, 110878, 2022.

In reference [1], a variation of GC based on GLM log-likelihoods is proposed that addresses the issues of non-linearity, non-stationarity, and non-Gaussianity of electrophysiology data. In [2] and [3], a variation of GC using sparse multi-variate models is introduced with application to calcium imaging data. In particular, all three references use the sparse estimation of the MVAR parameters in order to mitigate overfitting and also use corrections for multiple comparisons that also reduce the number of spurious links (see my related comments below). I suggest discussing these relevant references in the introduction (paragraphs 2 and 3) and discussion.

2) A major issue of GC applied to calcium imaging data is that the trials are typically limited in duration, which results in overfitting of the MVAR parameters when using least squares (See references [2] and [3] above, for example). The authors mention on page 4 that they use least squares to estimate the parameters. However, for the networks of ~10 neurons considered in this work, stationary trials of a long enough duration are required to estimate the parameters correctly. I suggest that the authors discuss this point and explicitly mention the trial durations and test whether the trial durations suffice for stable estimation of the MVAR parameters (this can be done by repeating some of the results on the synthetic data and using different trial lengths and then assessing the consistency of the detected GC links).

3) The definition of the "knee" of the average GC values as a function of the lag L needs to be a bit more formalized. In Fig. 2H using the synthetic data, the "knee" effect is more clear, but in the real data shown in Fig. 2I, the knee is not obvious, given that the confidence intervals are quite wide. Is there a way to quantify the "knee" by comparing the average GC values as well as their confidence bounds along the lag axis?

4) While the measures of W_{IC} and W_{RC} form suitable guiding principles for the pipeline presented in this work, it would be helpful if the authors discuss how such measures can be used for other applications of GC to calcium imaging data in which a priori information regarding the left/right symmetry or the rostrocaudal flow of information is missing.

5) Removing the "strange" neurons discussed in Section C5 is definitely an important pre-processing step in applying GC. However, the criterion for identifying the strange neurons seems a bit ad hoc and unclear. Could this be done by clustering the neurons into several categories (based on their time courses) and then removing a "strange" cluster? Please clarify.

6) Another key element of existing GC methods applied to large-scale networks is dealing with the issue of multiple comparisons: for instance, in Figures 2, 3, 4, 6, 7, and 8, it seems like all arrows corresponding to all possible links are shown, where the colormap indicates the GC value. However, when performing multiple statistical tests, many of these links can be removed by a correction such as the Benjamini-Hochberg procedure. It seems that the authors did not consider any correction of multiple comparisons; I suggest doing so and adding this to your pipeline.

7) The authors use TV denoising and also mention that it is a global operator, and changes the values of a time series at time t based on both the past and future values of the process. As such, it is not clear how TV denoising could affect the "causal" relations of the time series. In particular, TV denoising would significantly change the \Gamma_{ii} coefficients in Eq. (8). Is it possible to apply a version of TV denoising that only uses the information from the past to denoise the process at time t? In other words, using a "filter" as opposed to a "smoother". Please clarify.

8) The idea of using an adaptive threshold as in Section C8 is interesting; but this problem was previously considered in [30] (in the manuscript) and reference [1] above, in which new test statistics based on log-likelihoods are used that have well-known asymptotic null distributions (i.e., chi-square distributions). In particular, reference [1] above identifies and applies the required rescaling for the asymptotic null distributional assumptions to hold. I suggest discussing your work regarding the adaptive thresholds in the context of these existing results.

9) Related to the previous comment, given that the authors use a shuffling procedure to obtain the null, it is not clear why fitting the F-distribution parametrically and using its quantiles for testing would provide further benefits. In fact, as shown in Figure S9B, the rescaled F-distribution does not fully match the empirical null distribution, so it may be worth using the empirical null to obtain the non-parametric quantiles for testing. Please clarify.

10) In Figure 5C, the values of W_IC for the MV cases seem to be more than 1, whereas by definition they should be less than or equal to 1. Please clarify.

11) Is there evidence that the lateralized and rostrocaudal connectivity of the motoneurons occurs at the time-scale of ~750 ms? Given that this time scale is long enough for multiple synapses, it could be the case that some contralateral and non-rostrocaudal connections could be "real", as they reflect multi-hop synaptic connections. Please clarify.

12) While it is useful to see the comparison of the BV and MV cases shown in Figs. 1 and 2, given extensive evidence in the GC literature on the shortcomings of the BV version of GC, it seems unnecessary to report the BV results in Figs. 3 onward. I suggest discussing the shortcoming of the BV case when presenting figures 1 and 2 and removing the BV results from the subsequent results.

Reviewer #2 (Public Review):

The antiporter AdiC is a member of the amino-acid and polyamine organocation (APC) transporter superfamily. It imports the single-charged arginine (Arg+) and exports the double-charged agmatine (Agm2+). Thus, it increases the intracellular pH, helping some pathogenic enterobacteria survive in acidic environments. The APC transporters are known to sample 4 major conformations in the transport cycle. Monitoring the conformational transitions is important for understanding the transport mechanism, but methods detecting multi-state conformational changes are very limited. The authors use high-resolution polarization microscopy to resolve 4 different states in substrate-free (Apo) or substrate-bound conditions. This work further demonstrates the power of fluorescence polarization microscopy in studying protein dynamics. The authors introduced an interesting normalization step in data processing to average results obtained for different protein particles. However, the 4 states could be identified from single traces and the normalization from trace to trace could not be done without the pre-identified states on single traces. Thus, the improvement provided by the normalization compared to the published work (NSMB 2019a, 2019b, 2019c) is relatively limited.

Reviewer #2 (Public Review):

The manuscript by Park et al. reports a new structure of the mechanosensitive channel MscS of E. coli in the open state and the results of extensive coarse grained and atomistic molecular dynamics (MD) simulations of MscS and the related channel MSL1 of plant mitochondria in presumed closed and open states. The major new finding is that in the closed state, the lipid bilayer contacting the channel is severely distorted. In the open state, this distortion is not present. The MD simulations forming the basis of this finding have been carefully executed and the finding is interesting and relevant for the understanding of channel mechanosensation. The MD simulations are ideally suited to probe the lipid interactions of the channel in a state-dependent manner and to identify possible membrane distortions. However there are some issues that should be addressed.

1) Are the structures stable in the membrane also without the weak restraints on the dihedral angles? Continuing at least one of the atomistic simulations without restraints for about 1 microsecond in a tension-free membrane would address a possible concern that the severe membrane distortion could go away by a more extensive relaxation of the channel structure.

2) Does the observed effect occur also in membranes with physiologically relevant PE lipids? Performing a simulation with a lipid mix closer to that in E. coli (and thus high in PE) would address a possible concern that the observed effect is not physiologically relevant.

3) Please include a figure showing that the lipid positions in the MD simulations match the lipid densities in the cryo-EM maps.

4) Is the reported mobility of helices TM2-TM3 of MSL1, as deduced from a comparison of different cryo-EM structures (ref 18), sufficient to impact the lipid organisation?

5) Did the initial lipid configuration in atomistic MD simulations already contain the deformations of the inner leaflet, or did these form spontaneously both in coarse-grained and atomistic simulations?

6) Did the earlier MD simulations of the closed-state structure 6PWN of MscL give any indications on the membrane deformation?

7) Are there distinct interactions between the headgroups of distorted inner-leaflet lipids with charged amino acids? If so, are these amino acids conserved?

Reviewer #2 (Public Review):

The authors present a set of simulations that show how hippocampal theta sequences may be combined with spike time-dependent plasticity to learn a predictive map - the successor representation - in a biologically plausible manner. This study addresses an important question in the field: how might hippocampal theta sequences be combined with STDP to learn predictive maps? The conclusions are interesting and thought-provoking. However, there were a number of issues that made it hard to judge whether the conclusions of the study are justified. These concerns mainly surround the biological plausibility of the model and parameter settings, the lack of any mathematical analysis of the model, and the lack of direct quantitative comparison of the findings to experimental data.

While the model uses broadly realistic biological elements to learn the successor representation, there remain a number of important concerns with regard to the biological plausibility of the model. For example, the model assumes that each CA3 cell connects to exactly 1 CA1 cell throughout the whole learning process so that each CA1 cell simply inherits the activity of a single CA3 cell. Moreover, neurons in the model interact directly via their firing rate, yet produce spikes that are used only for the weight updates. Certain model parameters also appeared to be unrealistic, for example, the model combined very wide place fields with slow running speeds. This leaves open the question as to whether the proposed learning mechanism would function correctly in more realistic parameter settings. Simulations were performed for a fixed running speed, thereby omitting various potentially important effects of running speed on the phase precession and firing rate of place cells. Indeed, the phase precession of CA1 place cells was not shown or discussed, so it is unclear as to whether CA1 cells produce realistic patterns of phase precession in the model.

The fact that a successor-like representation emerges in the model is an interesting result and is likely to be of substantial interest to those working at the intersection between neuroscience and artificial intelligence. However, because no theoretical analysis of the model was performed, it remains unclear why this interesting correspondence emerges. Was it a coincidence? When will it generalise? These questions are best answered by mathematical analysis of the model (or a reduced form of it).

Several aspects of the model are qualitatively consistent with experimental data. For example, CA1 place fields clustered around doorways and were elongated along walls. While these findings are important and provide some support for the model, considerable work is required to draw a firm correspondence between the model and experimental data. Thus, without a quantitative comparison of the place field maps in experimental data and the model, it is hard to draw strong conclusions from these findings.

Overall, this study promises to make an important contribution to the field, and will likely be read with interest by those working in the fields of both neuroscience and artificial intelligence. However, given the above caveats, further work is required to establish the biological plausibility of the model, develop a theoretical understanding of the proposed learning process, and establish a quantitative comparison of the findings to experimental data.

Reviewer #2 (Public Review):

In 'Molecular characterization of cell types in the squid Loligo vulgaris', the authors study profile cell types of the squid brain, using single cell RNAseq and FISH for anatomical localization. They reveal many different cell types, some of which have correspondences in other organisms and some of which reflect cephalopod-specific innovations. The current study is one of 4 recent preprints (Styfhals et al. 2022, Songco-Casey et al. 2022, Gavriouchkina et al. 2022) profiling cephalopod tissues using scRNAseq and FISH-based anatomical localization. Together these studies begin to reveal the cellular complexity of these fascinating animals.

Defang the hierarchy! Flattening all the management levels and leadership.

Reviewer #2 (Public Review):

The authors motivate this study by the medical need to develop brain-machine interfaces (BMIs) to restore lost arm and hand function, for example through functional electrical stimulation. More specifically, they are interested in developing BMI decoding algorithms that work across a variety of "contexts" that a BMI user would encounter out in the real world, for example having their hand in different postures and manipulating a variety of objects. They note that in different contexts, the motor cortex neural activity patterns that produce the desired muscle outputs may change (including neurons' specific relationship to different muscles' activations), which could render a static decoder trained in a different context inaccurate.

To test whether this potential challenge is indeed the case, this study tested BMI control of virtual (on-screen) fingers by two rhesus macaques trained to perform 1 or 2 degree-of-freedom non-grasping tasks either by moving their fingers, or just controlling the virtual finger kinematics with neural activity. The key experimental manipulations were context shifts in the form of springs on the fingers or flexion of the wrist (or both). BMI performance was then evaluated when these context changes were present, which builds on this group's previous demonstration of accurate finger BMI without any context shifts.

The study convincingly shows the aforementioned context shifts do cause large changes in measured firing rates. When neural decoding accuracy (for both muscle and position/velocity) is evaluated across these context changes, reconstruction accuracy is substantially impaired. The headline finding, however, is that that despite this, BMI performance is, on aggregate, not substantially reduced. Although: it is noteworthy that in a second experiment paradigm where the decoder was trained on the spring or wrist-manipulated context and tested in a normal context, there were quite large performance reductions in several datasets as quantified by multiple performance measures; this asymmetry in the results is not really explored much further.

The changes in neural activity due to context shifts appear to be relatively modest in magnitude and can be fit well as simple linear shifts (in the neural state space), and the authors posit that this would make it feasible (in future work) to find context-invariant neural readouts that would result in more robust muscle activity decoders.

An additional novel contribution of this study is showing that these motor cortical signals support quite accurately decode muscle activations during non-prehensile finger movements (and also that the EMG decoding was more negatively affected by context shifts than kinematics decoding); previous work decoded finger kinematics but not these kinetics. Note that this was demonstrated with just one of the two monkeys (the second did not have muscle recordings).

This is a rigorous study, its main results are well-supported, and it does not make major claims beyond what the data support. One of its limitations is that while the eventual motivating goal is to show that decoders are robust across a variety of tasks of daily living, only two specific types of context shifts are tested here, and they are relatively simple and potentially do not result in as strong a neural change as could be encountered in real-world context shifts. This is by no means a major flaw (simplifying experimental preparations are a standard and prudent way to make progress). But the study could point this out a bit more prominently that their results do not preclude that more challenging context shifts will be encountered by BMI users, and this study in its current form does not indicate how strong a perturbation the tested context shifts are relative to the full possible range of hand movement context shifts that would be encountered during human daily living activities.

A second limitation is that while the discrepancy between large offline decoding performance reduction and small online performance reduction are attributed to rapid sensorimotor adaptation, this process is not directly examined in any detail. Third, the assessment of how neural dynamics change in a way that preserves the overall shape of the dynamics is rather qualitative rather than quantitative, and that this implementation of a more context-agnostic finger BMI is left for future work.

Reviewer #2 (Public Review):

Chakrabarti et al. aimed to investigate exocytosis from ribbon synapses of cochlear inner hair cells with high-resolution electron microscopy with tomography. Current methods to capture the ultrastructure of the dynamics of synaptic vesicle release in IHCs rely on the application of potassium for stimulation, which constrains temporal resolution to minutes rather than the millisecond resolution required to analyse synaptic transmission. Here the authors implemented a high-pressure freezing method relying on optogenetics for stimulation (Opto-HPF), granting them both high spatial and temporal resolutions. They provide an extremely well-detailed and rigorously controlled description of the method, falling in line with previously use of such "Opto-HPF" studies. They successfully applied Opto-HPF to IHCs and had several findings at this highly specialised ribbon synapse. They observed a stimulation-dependent accumulation of docked synaptic vesicles at IHC active-zones, and a stimulation-dependent reduction in the distance of non-docked vesicles to the active zone membrane; while the total number of ribbon-associated vesicles remained unchanged. Finally, they did not observe increases in diameter of synaptic vesicles proximal to the active zone, or other potential correlates to compound fusion - a potential mode of multivesicular release. The conclusions of the paper are mostly well supported by data, but some aspects of their findings and pitfalls of the methods should be better discussed.

Strengths:

While now a few different groups have used "Opto-HPF" methods (also referred to as "Flash and Freeze) in different ways and synapses, the current study implemented the method with rigorous controls in a novel way to specifically apply to cochlear IHCs - a different sample preparation than neuronal cultures, brain slices or C. elegans, the sample preparations used so far. The analysis of exocytosis dynamics of IHCs with electron microscopy with stimulation has been limited to being done with the application of potassium, which is not physiological. While much has been learned from these methods, they lacked time resolution. With Opto-HPF the authors were successfully able to investigate synaptic transmission with millisecond precision, with electron tomography analysis of active zones. I have no overall questions regarding the methodology as they were very thoroughly described. The authors also employed electrophysiology with optogenetics to characterise the optical simulation parameters and provided a well described analysis of the results with different pulse durations and irradiance - which is crucial for Opto-HPF.

Further, the authors did a superb job in providing several tables with data and information across all mouse lines used, experimental conditions, and statistical tests, including source code for the diverse analysis performed. The figures are overall clear and the manuscript was well written. Such a clear representation of data makes it easier to review the manuscript.

Weaknesses:

There are two main points that I think need to be better discussed by the authors.

The first refers to the pitfalls of using optogenetics to analyse synaptic transmission. While ChR2 provides better time resolution than potassium application, one cannot discard the possibility that calcium influx through ChR2 alters neurotransmitter release. This important limitation of the technique should be properly acknowledged by the authors and the consequences discussed, specifically in the context in which they applied it: a single sustained pulse of light of ~20ms (ShortStim) and of ~50ms (LongStim). While longer, sustained stimulation is characteristic for IHCs, these are quite long pulses as far as optogenetics and potential consequences to intrinsic or synaptic properties.

The second refers to the finding that the authors did not observe evidence of compound fusion (or homotypic fusion) in their data. This is an interesting finding in the context of multivesicular release in general, as well as specifically for IHCs. While the authors discussed the potential for "kiss-and-run" and/or "kiss-and-stay", it would be valuable if they could discuss their findings further in the context of the field for multivesicular release. For example, the evidence in support of the potential of multiple independent release events. Further, as far as such function-structure optical-quick-freezing methods, it is not unusual to not capture fusion events (so-called omega-shapes or vesicles with fusion pores); this is largely because these are very fast events (less than 10 ms), and not easily captured with optical stimulation.

Reviewer #2 (Public Review):

This manuscript studied potential cellular mechanisms that generate ultrafast oscillations (250-600Hz) in the cortex. These oscillations correlate with sensory stimulation and might be relevant for the perception of relevant sensory inputs. The authors combined ex-vivo whole-cell patch-clamp recordings, local field potential (LFP) recordings, and optogenetic stimulation of thalamocortical afferents. In a technical tour de force, they recorded pairs of fast-spiking (FS)-FS and FS-regular-spiking (RS) neurons in the cortex and correlated their activity with the LFP signal.

Optogenetic activation of thalamic afferents generated ripple-like extracellular waveforms in the cortex, which the authors referred to as ripplets. The timing of the peaks and troughs within these ripplets was consistent across slices and animals. Activation of thalamic inputs induced precisely timed FS spike bursts and RS spikes, which were phase-locked to the ripplet oscillation. The authors described the sequences of RS and FS neuron discharge and how they phase-locked to the ripplet, providing a model for the cellular mechanism generating the ripplet.

The manuscript is well-written and guides the reader step by step into the detailed analysis of the timing of ripplets and cellular discharges. The authors appropriately cite the known literature about ultrafast oscillations and carefully compare the novel ripplets to the well-known hippocampal ripples. The methods used (ex-vivo patch-clamp and LFP) were appropriate to study the cellular mechanisms underlying the ripplets.

Overall, this manuscript develops means for studying the role of cortical ultrafast oscillations and proposes a coherent model for the cellular mechanism underlying these cortical ultrafast oscillations.

Reviewer #2 (Public Review):

This paper focuses on an important topic. It explores how the activation loop conformations affect the type II inhibitor binding in Tyr and Ser/Thr kinases. The comprehensive computational results agree with the available experimental data. It is a remarkably comprehensive, high quality paper.

Reviewer #2 (Public Review):

The goal of this study is to find a minimal model that produces both theta and gamma rhythms in the hippocampus CA1, based on the full-scale model (FSM) of Bezaire et al, 2016. The FSM here is treated as equivalent to biological data. This seems to be a second part of a study that the same authors published in 2021, and is extensively cited here. The study reduces the FSM to a neural rate model with 4 neurons, which is capable of producing both rhythms. This model is then simulated and its parameter dependencies are explored.

The authors succeed in producing a rate model, based on 4 neuron types, that captures the essence of the two rhythms. This model is then analyzed at a descriptive level to claim that the synapse from one interneuron type (CCK) to another (PV+) is more effective than its reciprocal counterpart (PV+ to CCK synapse) to control theta rhythm frequency.

The results fall short on several fronts:<br /> The conclusions rely exclusively on the assumption that the FSM is in fact able to faithfully reflect the biological circuits involved, not just in its output, but in response to a variety of perturbations. Although the authors mention and discuss this assumption, in the end, the reader is left with a (reduced) model of a (complex) model, but no real analysis based on this reduction. In fact, the reduced model is treated in a manner that could have been done with the full one. Thus the significance of the work is greatly reduced not by what the authors do, but by what they fail to do, which is to properly analyze their own reduced model. Consequently, the impact of this study on the field is minimal.<br /> Related to the first point, throughout the manuscript, multiple descriptive findings, based on the authors' observations of the model output, are presented as causal relationships. Even the main finding of the study (that one synapse has a larger effect on theta than another) is not quantified, but just simply left as a judgment call by the authors and reader of comparing slopes on graphs.

Reviewer #2 (Public Review):

In this manuscript, Taylor et al. analyzed the role of the Polo-like kinase PLK-1 during female meiosis in the C. elegans oocyte. By temporally inhibiting an analogue-sensitive PLK-1 mutant (bypassing the PLK-1 requirement for nuclear envelope breakdown) they demonstrate that PLK-1 is involved in meiotic spindle assembly and/or stability, chromosome alignment and polar body extrusion. Consistent with its role in these processes, the authors demonstrate that PLK-1 localizes to multiple regions of the meiotic spindle: the spindle poles, chromosome arms, kinetochores and midbivalent region between the homologous chromosomes during meiosis I. They further dissected the mechanism recruiting PLK-1 to these structures and showed that CENP-CHCP-4 recruits PLK-1 to the chromosome arms while BUB-1 recruits PLK-1 to the midbivalent and kinetochores. The interaction between PLK-1 and its partners is mediated by phosphorylation of a Polo-docking site (consensus STP) in BUB-1 and CENP-CHCP-4. Finally, the authors show that both PLK-1 recruitment pathways are critically required for PLK-1 function in female meiosis.

This fundamental work substantially advances our understanding of PLK-1 function during female meiosis.<br /> Overall, the data presented are of very high quality and support the major conclusions of the paper with one or two exceptions.

Reviewer #2 (Public Review):

The impact of the work will be for yeast researchers in the clear and careful presentation of a case study wherein phenotypes might be ascribed to the knockout of a particular gene but instead derive from effects on a neighboring gene. In this case, a transcript expressed from within or adjacent to a knockout of DBP1 by a selectable marker towards the adjacent gene MRP51 interferes with the adjacent gene's normal transcription start sites. Furthermore, although neighboring MRP51 ORF is present on the longer mRNA isoform that is generated, it is not efficiently translated. The authors expand on this phenotypic observation to demonstrate that a substantial fraction of selectable marker insertions can generate transcription adjacent to or within and going away from, selectable markers.

The strengths of the work are that the derivation of the observed phenotypes for the dpb1∆ alleles is clearly and carefully elucidated and the creation of new selectable marker cassettes that overcome the potential for cryptic transcript emanation from or near to the selectable markers. This is valuable for the community as a clear demonstration of how only the exact right experiments might detect underlying mechanisms for potentially misattributed phenotypes and that many times these experiments may not be performed. While understandable in terms of how the experiments likely played out, the manuscript seems in between biology and tool development, as the biology in question was related to a gene that is not the focus of this lab. The tool development is likely to be useful but potentially non-optimal. The mechanism for interference identified in this example case (via a long undecoded transcript isoform (LUTI) has already been described for other loci and in a number of species, including in work from the Brar lab. The concept of marker interference with neighboring genes has also been increasingly appreciated by a number of other studies.

Reviewer #2 (Public Review):

Activation of SK channels by calcium through calmodulin (CaM) is physiologically important in tuning membrane excitability. Understanding the molecular mechanism of SK activation has therefore been a high priority in ion channel biophysics and calcium signaling. The prevailing view is that the C-terminal lobe of CaM serves as an immobile Ca2+-independent tether while the N-lobe acts as a sensor whose binding activates the channel. In the present study, the authors undertake extensive biophysical/biochemical analysis of CaM interaction with SK channel peptide and rigorous electrophysiological experiments to show that Ca2+ does bind to the C-lobe of CaM and this potentially evokes conformational changes that may be relevant for channel gating. Beyond SK channels, the approach and findings here may bear important implications for an expanding number of ion channels and membrane proteins that are regulated by CaM.

A strength of the study is that the electrophysiological recordings are innovative and of high quality. Given that CaM is ubiquitous in nearly all eukaryotes, dissecting the effects of mutants particularly on individual lobes is technically challenging, as endogenous CaM can overwhelm low-affinity mutants. The excised patch approach developed here provides a powerful methodology to dissect fundamental mechanisms underlying CaM action. I imagine this could be adaptable for studying other ion channels. Armed with this strategy authors show that both N- and C-lobe of CaM are essential for maximal activation of SK channels. This revises the current model and may have physiological importance.

The major weakness is that nearly all biochemical inferences are made from analysis of isolated peptides that do not necessarily recapitulate their arrangement in an intact channel. While the use of MALS provides new evidence of the potentially complex conformational arrangement of CaM on the C-terminal SK peptide (SKp), it is not fully clear that these complexes correspond to functionally relevant states. Lastly, perhaps as a consequence of these ambiguities, the overarching model or mechanism is not fully clear.

Reviewer #2 (Public Review):

This is an extremely thorough investigation of the role of cadherins in generating a functional motor circuit. The work represents a major step forward in the field as it addresses several outstanding questions and verifies anatomical data with functional outcomes. First, the data show that a combination of type I (N) and type II (6, 9, 10) cadherins is needed to generate normal connectivity and function. This is novel as prior work has suggested that the two types do not work collaboratively to generate circuits. Second, the data show that cell body position (in this case) is modulated by N-cadherin but in a manner that is independent from the impact of N-cadherin on connectivity. While position and connectivity have been shown to be separable in some cases, the data support that N-cadherin plays important but separate roles toward both actions, and type II cadherins, mainly in connectivity. These findings also underscore that cadherin roles reported for hippocampus, retina, and spinal cord motor neuron pools are not generalizable across circuits. Third, while the data show that type I and type II cadherins are required for VRG to phrenic motor neuron connectivity, they also show that there are some outcomes controlled only by N-cadherin. Finally, the data reveal much about a very poorly understood and essential circuit. The approaches are sound and range from the standard (in situ, immuno, diI, breathing measurements) to the difficult (rabies-based tracing) to the impressive (challenging ephys preps, and some painstaking mouse crosses), and they incorporated strong and creative strategies for comparison and quantification. Minor questions do not detract from a really impressive piece of work.