Reviewer #2 (Public Review):

This manuscript uses the t-SNE dimensionality reduction technique to capture the rich dynamics of the pyloric circuit of the crab.

Strengths:<br /> - The integration of a rich data-set of spiking data from the pyloric circuit<br /> - Use of nonlinear dimension reduction (t-SNE) to visualise that data<br /> - Use of clusters from that t-SNE visualisation to create subsets of data that are amenable to consistent analyses (such as using the "regular" cluster as a basis for surveying the types of dynamics possible in baseline conditions)<br /> - Innovative use of the cluster types to describe transitions between dynamics within the baseline state and within perturbed states (whether by changes to exogenous variables, cutting nerves, or applying neuromodulators)

- Some interesting main results:<br /> o Baseline variability in the spiking patterns of the pyloric circuit is greater within than between animals<br /> o Transitions to silent states often (always?) pass through the same intermediate state of the LP neuron skipping spikes

Weaknesses:<br /> - t-SNE is not, in isolation, a clustering algorithm, yet here it is treated as such. How the clusters were identified is unclear: the manuscript mentions manual curation of randomly sampled points, implying that the clusters were extrapolations from these. This would seem to rather defeat the point of using unsupervised techniques to obtain an unbiased survey of the spiking dynamics, and raises the issue of how robust the clusters are<br /> - the main purpose and contribution of the paper is unclear, as the results are descriptive, and mostly state that dynamics in some vary between different states of the circuit; while the collated dataset is a wonderful resource, and the map is no doubt useful for the lab to place in context what they are looking at, it is not clear what we learn about the pyloric circuit, or more widely about the dynamical repertoire of neural circuits<br /> - in some places the contribution is noted as being the pipeline of analysis: unfortunately as the pipeline used here seems to rely in manual curation, it is of limited general use; moreover, there are already a number of previous works that use unsupervised machine-learning pipelines to characterise the complexity of spiking activity across a large data-set of neurons, using the same general approach here (quantify properties of spiking as a vector; map/cluster using dimension reduction), including Baden et al (2016, Nature), Bruno et al (2015, Neuron), Frady et al (2016, Neural Computation).

- Some key limitations are not considered:<br /> o the omission of the PY neuron activity means that the map as given is incomplete: potentially there are many more states, and hence transitions, within or beyond those already found that correspond to changes in PY neuron activity<br /> o The use of long, non-overlapping time segments (20s) - this means, for example, that the transitions are slow and discrete, whereas in reality they may be abrupt, or continuous.<br /> o tSNE cannot capture hierarchical structure, nor has a null model to demonstrate that the underlying data contains some clustering structure. So, for example, distances measured on the map may not be strictly meaningful if the data is hierarchical.<br /> - the Discussion does not include enough insight and contextualisation of the results.

Reviewer #2 (Public Review):

In this study, the authors examine: 1) whether offset responses, where neurons respond upon termination of a stimulus, are behaviorally relevant; 2) whether offset responses are merely inherited from subcortical stations or are generated and amplified in cortex; and 3) whether offset responses simply encode sound termination or if they carry stimulus identity information as well. They show, using a combination of optogenetics and behavior, that suppressing offset responses in auditory field AAF results in an impairment of sound termination detection. They then show, using single- and multi-unit recordings, that the behavioral choice of the animal can be decoded on a trial-by-trial basis from the offset and late response phases. Finally, using antidromic stimulation and using multiple stimuli, the authors show that AAF offset responses are not wholly inherited from the auditory thalamus.

The electrophysiological elements of the study seem solid and well-performed. Some weaknesses of the study include the effectiveness of task acquisition by the behavioral subjects, and behavioral analyses that discard trials with potentially useful information. Some statistical tests may not be appropriate and brings into question the results of the decoding analysis. Very recent and highly relevant publications are not discussed in the study. Additional control analyses would strengthen the manuscript.

Reviewer #2 (Public Review):

Zhao et al. addressed the possibility that Zika virus (ZIKV)-induced pyroptosis (a lytic form of cell death) contributes to ZIKV pathogenesis and adverse outcomes during pregnancy. Using the human choriocarcinoma cell line JEG-3 authors observe that ZIKV infection induced a Gasdermin E (GSDME)-dependent pyroptosis, which they demonstrated by comparing JEG-3 WT and monoclonal GSDME-/- cells. ZIKV was also found to induce a similar cell death in a panel of immortalized cell lines derived from other tissues. A particularly surprising observation by the authors is that the ZIKV untranslated regions of the viral genome was sufficient to induce pyroptosis via the RNA sensor RIG-I. Based on known activators of GSDME, the authors use a panel of caspase or other cell death pathway inhibitors to identify a CASP8/9>CASP3 pathway upstream of GSDME activation. Finally, using an immunocompetent mouse model of ZIKV in utero infection, the authors observed that Gsdme-/- mice were less susceptible than WT mice to congenital ZIKV syndromes (CZS). Taken together, the authors provide considerable evidence that largely supports their interpretations for how ZIKV causes pyroptotic cell death. The primary observation - that ZIKV induces GSDME pyroptosis - is highly impactful. In some areas, surprising findings (e.g., RIG-I-dependent pyroptosis) would be more interpretable by including additional controls or testing additional predictions of the model. In other cases, the reader would benefit by the authors further contextualizing their model relative to preexisting work, and acknowledging alternative hypothesis that may (or may not) occur in other cell types or non-tumor derived cells and potential differences between mouse and human pathways. I attempt to highlight specific strengths and concerns below.

In general, the primary conclusion that ZIKV induces a GSDME-dependent pyroptosis is well supported. In my opinion, aspects of the mechanistic details of the upstream pathway remain uncertain. This stems from a few different experimental choices.

First, the mechanistic workup is completed entirely in immortalized cells. Obtaining primary trophoblasts is recognized as a potentially significant challenge. However, the dependency on immortalized cell lines precludes some of the more generalized conclusions that the authors attempt to draw from their data. The RIG-I>CASP8/9>CASP3>GSDME pathway is also entirely described in the JEG-3 cells using a single ZIKV strain. With the exception of the GSDME-/- JEG-3 cells, all other experiments rely on knockdowns or chemical inhibitors. While these experiments are informative, clean knockouts in at least one other cell line for key aspects of the pathway in question would provide better support for the authors conclusions. This is particularly important for the interesting but surprising claim that the ZIKV genome UTRs are sufficient to induce GSDME pyroptosis in a RIG-I dependent manner. To my knowledge, no such pathway has been described. Hence, a few additional experiments to shore up that observation are merited. For example, one prediction is that other RIG-I agonists should similarly induce pyroptosis. Moreover, RIG-I, MDA5, and MAVS knockouts would allow for clear, genetic determination of whether or not the pathway in question operates similarly to known RIG-I signaling. Another interesting but not fully clear aspect of the pathway is how various caspases contribute to GSDME activation. In this case, authors can partly rely on prior work demonstrating that CASP3 cleaves and activates GSDME. However, the relative contributions of other caspases (e.g., CASP8 and CASP9) are more difficult to discern because the authors exclusively rely on chemical inhibitors, which although largely specific also have known off-target effects. In my opinion, this is a more minor aspect of the manuscript, but should be considered by readers with appropriate discernment.

The reduction in CZS in Gsdme-/- compared to WT mice is a particularly striking observation. This does soften some of my concerns about the generality of the JEG-3 results. However, the JEG-3-defined pathway and the in vivo results are largely correlative. For example, it is not clear from the data presented if ZIKV infection activates mouse GSDME using the same RIG-I>CASP8/9>CASP3>GSDME pathway. The mating scheme utilized by the authors also prevents a determination of the relative maternal versus fetal contributions of GSDME to the phenotype. In addition, littermate and co-housing is not described. Although the placenta is considered a sterile tissue, non-genetic contributions to the phenotype have not been controlled for. An interesting feature of the in vivo infection model is the use of immunocompetent mice. Although this falls outside of the expertise of this reviewer, my understanding was that IFN-competent mice are largely resistant to ZIKV infection. It would be helpful if the authors contextualized their model relative to those previously published.

Another area where additional context would be useful is in considering other aspects of the JEG-3 cells compared to cells used in prior ZIKV studies. Tumor-derived cell lines (like JEG-3) often lose cell death pathways. As the authors recognize, other groups have reported ZIKV activation of the NLRP3 inflammasome. Do JEG-3 cells (and other cells used in the study) accurately mimic the status of the NLRP3 pathway in primary trophoblasts? Is CASP1 expressed in these cells (almost certainly not in HeLa and 293T cells)? Thus, it remains possible that the NLRP3 pathway is active in human primary trophoblasts and contributes to ZIKV pathogenesis in vivo. And although deciphering the relative contributions of these pathways falls outside the context of this work, it again limits the generalization of the data. In addition, the authors should consider multiple reports that CASP3 can cleave and inhibit GSDMD, which seems particularly relevant to their observation.

Reviewer #2 (Public Review):

In this manuscript, Behringer et al. tackle the topic of transitions to siblinghood (TTS), a domain of research dominated by developmental psychology, using comparative evidence. Within psychological research, there is substantial heterogeneity, and controversy, concerning how becoming a sibling affects a child. Looking to address this question with a fresh approach, the authors compile a longitudinal dataset of urine biomarker measurements, as well as some indications of dependence on mothers, in a group of 26 bonobos before and after the birth of their first younger siblings. Urinary cortisol peaks around the time of a sibling's birth, and urinary neopterin drops, with the magnitude of these changes seemingly not moderated by the older sibling's age (within the range of ages observed in this study). While older siblings show relatively diminished interactions with mom when younger siblings are born, this appears to be the consequence of gradual independence that has either been partially or fully realized by the time of birth.

In terms of strengths, the technical details of the assays and statistical models are largely clear and well-supported. The main findings are intriguing, particularly the large jump in cortisol, which has not been documented before in an ape. While the authors briefly discuss several interpretations of this result, they appear to favor the conclusion that 'a cortisol jump shows the transition to siblinghood is ubiquitously stressful in bonobos'-I see this as a fair paraphrase, given for instance manuscript lines 372-377. It is clear the authors see this cortisol effect as the most impactful part of their manuscript. Unfortunately, it is not at all clear whether this central finding constitutes solid evidence for their favored conclusion. Romero and Beattie (2021; https://doi.org/10.1002/jez.2459), in their paper about "myths of glucocorticoid function", provide a succinct summary of how equating elevated cortisol to stress is problematic: "Glucocorticoid concentrations provide no predictive value in determining whether a wild animal is or is not chronically stressed ... Not only will many wild animals suffering from chronic stress show no changes in glucocorticoid concentrations, but decreases may also reflect chronic stress. A diagnosis of chronic stress requires other corroborating evidence, such as weight loss, changes in fitness, etc." In other words, without accompanying behavioral and/or physical evidence of stress, it is equally plausible to interpret cortisol increases as evidence of TTS being stressful, or it being an occasion for ecological adjustment that does not manifest in stress. Either end of this interpretive axis has support in the developmental psych literature (e.g., Volling, 2012, which the authors cite).

I was really hoping to see some of this corroborating evidence in the present manuscript-for instance, some behavioral measures from the sibling that would indicate distress-but this important element is missing. The existing behavioral measures, which concern dependency on the mother, are interesting, but on their own they are not nearly enough to support claims like "our results on wild bonobos support ... that the birth of a sibling is a highly stressful event for the older offspring" (lines 374-375). The limited scope of available behavioral data also raises additional interpretative questions. Cortisol increases for a circumscribed period of time-seven months, according to the authors--after which levels are indistinguishable from pre-birth concentrations (line 186). The authors attribute this to behavioral adaptation, but we have no idea whether/how bonobos in fact behaviorally adjust to their new conditions or their siblings.

In sum, the manuscript presents some very interesting patterns, but a number of important limitations must be overcome before it can speak to evolutionary and developmental theories of TTS.

Reviewer #2 (Public Review): 

In this work, Professor Bellio and her colleagues provide compelling evidence to show unusually strong induction of cytotoxic CD4 T cells (CD4CTLs) in Trypanosoma cruzi-parasitized mice. Using genetic models and mixed bone marrow chimeras they dissect the signals responsible for CD4CTL induction in this infection and identify T cell-intrinsic IL-18R/MyD88 signaling as the key inducer. The CD4CTLs that clonally expand in T. cruzi infection outnumber CD4 cells with typical Th1 profile (IFN-γ secretion) and bear the hallmarks of CD4CTLs described in other model systems and in humans. Utilizing GzmbCreERT2/ROSA26EYFP reporter mice, the authors show that adoptive transfer of CD4 cells that have made GzB can increase the survival of T. cruzi parasitized l18ra-/- mice. Finally, the authors describe a clear correlation between the frequency of CD4CTLs the circulation of patients with T. cruzi-induced chronic Chagas cardiomyopathy, implying a pathogenic role for these cells in chronic disease. 

The findings reported here are an important addition to the understanding of both the origin of CD4CTLs and their potential role in host protection or disease. The evidence provided in support of the main claims is very strong and the association between CD4CTLs and Chagas disease quite intriguing. There are, however, some aspects of the work that would benefit from further clarification or experimental support, so that alternative interpretations of the data can be excluded. 

The defining characteristic of CD4CTLs that separates them from other CD4 subsets is the production of granzymes and perforin and, by extension, the ability to kill target cells in a granzyme/perforin-dependent manner. In contrast, all T cells can kill target cells via alternative mechanisms that are not dependent on granzyme/perforin, for example through expression of TNF family members. It would appear that much, if not most, of the killing activity of T. cruzi-induced CD4CTLs can be attributed to FasL (Fig. 1B). FasL-mediated killing is not restricted to CD4CTLs and as the title of one of the cited studies (Kotov et al., 2018) states, "many Th cell subsets have Fas ligand-dependent cytotoxic potential". It would be important to ascertain if expression of granzyme/perforin by CD4CTLs in T. cruzi infection is also associated with granzyme/perforin-dependent cytotoxicity. This affects the direct and indirect in vitro cytotoxicity assays, as well as the interpretation of in vivo protection. 

Similarly, the protective effect of transferring GzmbCreERT2/ROSA26EYFP reporter-positive cells to Il18ra-/- mice may not be necessarily mediated in a granzyme/perforin-dependent manner or by CD4CTLs for that matter. The reporter will mark cells that express GzB at the time of tamoxifen administration but does not guarantee that these cells will continue to express GzB or that they will prolong survival of recipients in a granzyme/perforin-dependent manner. 

While the authors provide evidence that GzB-producing cells are largely distinct from IFN-γ-producing cells, the reporter-positive cells may still contain genuine Th1 cells. Given Th1 cells have been previously found necessary for protection of Il18ra-/- mice in the T. cruzi model, can a role for Th1 cells in this transfer model be formally excluded? The authors do convincingly demonstrate that IFN-γ itself is not essential for protection, but that does not leave granzyme/perforin-dependent as the only other alternative. For example, the experiment described in Fig. 6G lacks an important control, the transfer of reporter-negative cells. What would the conclusion be if reporter-negative (but T. cruzi-specific) cells proved as protective as reporter-positive cells?

Reviewer #2 (Public Review):

This manuscript focuses on elucidating conformational changes in the structure of the manganese-binding R2b subunit of a Class 1b ribonucleotide reductase in complex with the NrdI flavin-binding protein induced by different oxidation states of the flavin cofactor. Using XFEL to avoid the effects of photoreduction that hindered these goals in previous work, the authors determine structures of the complex in two oxidation states. Analysis of these structures and others reveals that the complex locks the FMN cofactor into a more linear conformation. The authors conclude that the conformational strain induced on the cofactor within the complex drives generation of superoxide radicals by lowering its reduction potential.

Strengths<br /> The major strengths of this study are the use of XFEL to determine structures of the R2b-NrdI complex in multiple oxidation states, which reveals oxidation-induced conformational changes to the FMN cofactor. The authors provide a compelling rationale for their use of the specific methods and analysis they chose that makes the paper understandable to a wide audience.<br /> The structural studies will not only be of impact to people in the field of flavoproteins and ribonucleotide reductases, but also include creative approaches to challenging problems in structural biology.<br /> Beyond the high quality of the structural data and its analysis, the paper is very well-written and also includes a nice discussion of the structures of the manganese dependent enzyme that is the focus of their work to the closely related iron-dependent enzymes.

Weaknesses<br /> The hypotheses regarding the mechanism of superoxide generation come entirely from examination of crystal structures, rather than direct experimental measurements

Reviewer #2 (Public Review):

This study aims to disentangle the contributions of genetic and species diversity to tree community fitness. It confirms the role of genetic diversity in functional and ecological traits but shows how these effects change when plant species diversity is increased, which can potentially add to our understanding of the interplay between plant diversity at various levels and community and ecosystem functions. It would be desirable to make emphasis whether differences between the effects of genetic and species diversity are comparable since they can act at complementary but different levels. It is hard to establish whether the effects of species diversity override the effects of genetic diversity by shared mechanisms; or whether a high species diversity reduces plant intraspecific interactions and the consequent effects of genetic diversity by density-dependent effects. However, this point has to be emphasized in the discussion.

The experimental design has to be explained in more detail, in particular how plants were planted in the species monocultures. It is not stated whether the same or different species were used in the plots or in subplots. The design lacks proper replication for the treatment with high genetic diversity in species monocultures (n=2) which could lead to a biased result, especially if those plots were located in the same area.

Reviewer #2 (Public Review):

Using the Cav3.2-eGFP-flox knock-in mice, the authors showed that the expression of Cav3.2 in APT overlaps well with PV. Most of them are bursting neurons with enhanced activities after spared nerve injury (SNI). The authors provided evidence that Ni-sensitive Cav3.2 current contributes to the bursting activity of the PV+ neurons in APT. Deletion of Cav3.2 in APT attenuated mechanical and cold allodynia in SNI mice. These results support the role of supra-spinal Cav3.2 in neuropathic pain. Understanding the role of Cav3.2 in the bursting of APT neurons and in neuropathic pain is of general interest. The experimental approaches are elegant, but some proper controls are missing. Whether Cav3.2 underlies SNI-induced enhancement of bursting is not directly tested. The relative contributions of APT and spinal/peripheral Cav3.2 to neuropathic pain remains unclear.

Reviewer #2 (Public Review):

The authors examine whether their CD19/47 bispecific can potentiate ADCC and ADCP mediated killing in preclinical lymphoma models.

The ability of CD47 blockade to synergize with an alternative CD20 (Rituximab) is already established in preclinical models (Choa et al. Cell 2010) and the combination has been deployed in patients (Advani et al NEJM 20018). The novelty of the current study CD47 blockade is now targeted exclusively to CD19 positive B cells . The rationale for this being that it might reduce toxicity to non-B lineages such as the erythroid lineage, since anemia was a significant toxicity in previous studies of CD47 blockade.

Using a single CD19 positive and single CD19 negative cell line the authors confirm CD19-dependent blockade of CD47 at a dose of 2ng/ml.

In vitro assays for phagocytosis in a panel of 5 lymphoma cell lines show increased phagocytosis in all cell lines treated with eat CD19/47 antibody. In a single cell line (Raji), phagocytosis is then increased further by the addition of the umbralisib/ublituximab combo (U2). The weakness here that it is not clear if the effect seen in Raji represents synergy or additive killing, and moreover phagocytosis compared to CD19/47 alone is only seen in one of five cell lines. ADCC assays are also shown but it is not clear from the methods section how these assays distinguish effector cell-mediated killing from direct apoptosis induction.

Xenografting of a single cell line (Raji) shows that tumor growth is suppressed by the CD19/47 and appears to be suppressed further by addition of U2. Some data is presented for percent of mice tumor-free after a further 35 days, but any difference seems not to achieve statistical significance.

Therefore the data presented in figure 1 provide only limited support for authors' conclusions that there is synergy between CD19/47 and U2, and the data that any potentiation of cell killing is all due to the induction of a cell-mediated response rather than apoptosis is not compelling.

Using gene expression, the authors then identify upregulation of GPR183 in cells treated with TG108 plus U2 versus TG108 alone. They show that GPR183 loss abolishes M1 macrophage infiltration in Raji organoids and abolishes phagocytosis, the latter effect being partly recapitulated by pharmacological inhibition. From the current experimental design, it is not clear if GPR183 is induced by the CD20 engagement or by the PI3K/CK1E inhibition, or whether it even requires the presence of CD47 engagement at all. However, the implication of this pathway in regulating ADCP is important and will spur further investigation.

Reviewer #2 (Public Review):

Siller et al seek to define underlying mechanisms by which the R-type calcium channel Cav2.3 may contribute to calcium-dependent pacemaking in dopaminergic neurons. The premise for the work is based on prior observations from this research team, particularly the finding that Cav2.3 is the most abundant Cav expressed in dopaminergic neurons and that it may contribute to activity-dependent calcium oscillations in these cells. Because of the known biophysical properties of Cav2.3, the authors propose a distinctive regulation of Cav2.3 by different accessory beta subunits that may contribute to calcium-dependent pacemaking in dopaminergic neurons. To test this, they first confirmed the sensitivity of spontaneous firing activity to the R-type calcium channel blocker SNX in midbrain dopaminergic neurons. They also recorded SNX-sensitive inward currents suspected to be R-type currents. Electrophysiology in tsA-201 cells expressing Cav2.3, a2d and different beta subunit isoforms and splice variants revealed unique biophysical properties. More importantly, it was found that the b2a and b2e subunits could slow the activity-dependent inactivation time course of the Cav2.3 channels and shift the voltage-dependent of inactivation toward more positive potentials. Subsequent molecular biology experiments revealed the presence of several b subunit splice variants in dopaminergic neurons. An unexpected but appreciated observation is that b2a subunits prevent/ameliorate the rundown of Cav2.3 currents in response to a train of square pulses and simulated neuronal pacemaking protocol in tsA-201 cells. An effort is made to record R-type currents from dopaminergic neurons, and the authors show that these currents activate at more positive voltages than total calcium currents. In general, the data seem of very high quality and support the conclusions that different splice variants of the beta subunit distinctive modulate Cav2.3 activity. Importantly, these changes could help explain a role for Cav2.3-containing b2a/b2e channels in calcium-dependent pacemaking in dopaminergic neurons. The problem examined is of wide interest and the conclusions may have implications that span from the regulation of Cav2.3 channels in dopaminergic neurons to the conceivable involvement of the Cav2.3-b2a-e complex in Parkinson's disease to therapeutic opportunities. Thus, it is likely that this work will be of interest to a broad audience.

This reviewer is very enthusiastic about the work but notes that most of the conclusions are based on data obtained by overexpressing Cav2.3 and accessory subunits in a heterologous expression system. The authors make a good argument for cross-correlation between data in tsA-201 cells and dopaminergic neurons, but it is unclear that the results will translate from one system to another. More data may be needed to do so (the reviewer does understand that these are challenging experiments), which the authors acknowledge in a section about the study's limitations. Based on this, it seems that the title is misleading without additional data supporting the role of Cav2.3 in dopaminergic neurons. Along the prior line, statements linking the study results to potential pathological implications seem a big stretch not supported by current data, and therefore should be eliminated.

An issue with this manuscript is that the narrative and organization of the data are difficult to follow. The reviewer understands that the authors are weaving a complex story that involves using multiple techniques and approaches. Still, the way the data is organized and described makes the reader go back and forward to compare and contrast results constantly. This is further complicated by the fact that some experiments are done in dopaminergic neurons and others in tsA-201 cells (the identity of the cell type used should be made clearer), the order of some figures is not appropriate (Supp Fig 1 for example) and some figure panels are not discussed (Supp Fig 5E to 5J).

Reviewer #2 (Public Review):

We are in a golden age for comparative genomics and this is a prime example of the utility of the field. "Vision-related convergent gene losses reveal SERPINE3's unknown role in the eye" details the discovery of a function for a previously uncharacterized gene in regulating organ development in evolution. The authors intersect patterns of gene loss, quantified as the percentage of intact coding sequence, with visual acuity scores across Mammalia. This analysis identified 26 significant genes that have undergone convergent loss with phenotypic decreases of vision. Many of those genes have previously been annotated in the eye, indicating the analysis was successful and suggesting the uncharacterized genes may also have roles there.

The authors ruled out the top hit due to its specific expression in the testis, and instead performed an in-depth characterization of the second hit, SERPINE3. This included an impressive breadth of comparative genomics across 430 placental mammals, carefully describing the many and diverse genetic perturbations of SERPINE3 in lineages with low visual acuity. These results are persuasive that SERPINE3 is involved in vision, and it is a great example and description of gene loss in adaptation.

Critically, the authors validated the role of SERPINE3 in eye structure by confirming expression patterns in the eye, and characterizing its knockout in zebrafish, demonstrating both qualitative and quantitative impairments to eye structure. This is particularly satisfying as many comparative genomics make such associations but never validate the result. Here, validation of SERPINE3 was an undeniable success and puts a functional annotation to a previously uncharacterized gene. The utility of comparative genomics and zebrafish genetic models has been expertly capitalized upon and there is no doubt our knowledge of eye genetics has increased.

While these end results are certainly valuable to the community, details regarding the statistics and filters underlying the initial convergence analysis are too sparse to interpret. The impressive false discovery rate of the top hits is called into question when the top hit (corrected p-value < 1.1E-15 with visual acuity < 2) is subsequently skipped due to its specific expression in the testes. Given this disconnect, and without knowing the rationale and consequences of the various filters, it is difficult to get a sense of the accuracy and robustness of these p-values. Plots of p-value distributions across the dataset would demonstrate the method is statistically sound and would provide the backdrop to interpret the top hits of interest. Notes on how many genes pass each filter, and what kinds of genes, would allow interpretation of possible bias in those filters and how they interact with the convergence analysis. For instance, the slight changes in visual acuity cutoffs have non-obvious operational consequences for vision, yet large impacts on the resulting gene lists, making it difficult to interpret how the measure is functioning. Most importantly, a negative control in the convergence analysis, demonstrating a null p-value distribution with the same filters, would assuage most concerns.

With that said, the primary conclusion that SERPINE3 is involved in eye structure is strong. The extended mining of orthologues across new genomes is impressive, the zebrafish characterization is compelling, and readers should have no doubt SERPINE3 is involved in eye development. These results will be valuable for research into eye disease, understanding eye development, and unraveling the evolution of vision loss in diverse models. This paper will be a reference for all future investigations in these areas and oft cited.

Reviewer #2 (Public Review):

dendritic cells (DCs) are critical for initiating immune response and can initiate or accelerate autoimmune diseases. The authors are trying to better define the CD1c population in human autoimmune uveitis which was previously indicated to be involved in the disease. Thus, it is important to understand the role of dendritic cells in autoimmune uveitis.

the authors identified a population of CD1c in blood based on the combination of markers CD36 and CX3CR1 that is reduced in Uveitis.

the reviewer appreciate the difficulty in getting these patient samples. however, there are some technical issues with the analysis of the cells and lack of sufficient functional assays prevent the deep understanding of the biology of these cells.

if their reduction contributes to the diseases than a better understanding how to boost it would be beneficial and impactful.

Reviewer #2 (Public Review):

Zhou et al. investigate a robust estimation for the median-effect equation and develop a freely accessible web-based analytic tool to facilitate the quantitative implementation of the proposed approach for the scientific community. In the paper, substantive simulation studies under various scenarios are carried out to show that the proposed approach consistently provides robust estimation for the median-effect equation, particularly when there are extreme outcome observations. The proposed approach also provides a narrower confidence interval, suggesting a higher power in statistical testing. The case studies provide the visualization of the dose-response curves for different drugs or under different conditions, and the case studies also show the usefulness of the proposed method.

Reviewer #2 (Public Review):

The present paper presents an impressive meta-analyze on handedness for a bimanual coordinated tube task (which has been considered in the literature as a robust and reliable task to assess hand preference in nonhuman primates) in about 38 primate species including new sets of data collected by the authors themselves. The work that has been done to compile exhaustively all the available data is considerable and very valuable. The authors presented also, in the introduction, a very nice and useful review and clarification of the different existing evolutionary theories that have previously been proposed in the literature to try to interpret the discrepancy of findings reported across primate species. For instance, different hypotheses are contrasted such as (1) the one highlighting the role of the tool use emergence, (2) the one highlighting the role of brain size, and (3) the postural origin hypothesis (i.e., the predominance of right-handedness evolved with the emergence of anthropoid primates, regardless of ecology), or (4) the "novel (corrected) postural origin hypothesis" that I have been proposed with coauthors (i.e., the predominance of right-handedness for bimanual actions is related to terrestrial ecology whereas predominance of left-handedness is related to arboreal ecology, regardless of phylogeny). Such an exhaustive review of handedness data in bimanual tasks across the largest comparative approach ever done allows the authors to evaluate those several hypotheses by testing the effect of their related factors (phylogeny, ecology, emergence of tool use, brain size) on the pattern of handedness. Using quantitative phylogenetic methods, the authors found that none of those factors are actually predictive of the direction of population-level handedness in non-human primates questioning seriously each of those existing hypotheses.

I believe this large review and study is very important and relevant for investigating the evolution of handedness, although I questioned the strong claim (supported by the lake of findings resulting from the quantitative phylogenetic methods) that the dichotomy of arboreal versus terrestrial lifestyle has nothing to do with the direction of population-level handedness in a non-human primate. A significant difference in direction of handedness between these two lifestyles seems still robust when considering clade-level (not species-level), an effect driven by overrepresented species for which high sample sizes have been included. The question of sample size and statistical power for evaluating and inferring population-level of handedness is thus a potential critical factor that should be discussed for evaluating different evolutionary theories. It might be indeed not excluded that the lake of results at the species level is equivocal given the lack of statistical power in most species (related to a poor sample size of subjects).

Nevertheless, I congratulate the authors for this amazing and considerable work. I had such a pleasure reading it and hope my comments and questions were useful.

Reviewer #2 (Public Review):

The study by Cai et al. sought to identify novel actionable candidates towards the development of therapeutic treatments for metastatic triple negative breast cancer (TNBC), a subtype with poor prognosis. The authors performed inducible knockdown of a focussed library of 69 candidate epigenetic regulators using a cell model of lung-metastatic TNBC (MDA-MB-231-LM2 cells), using both in vitro (cell proliferation) and in vivo (xenograft lung metastasis) screens. This identified several candidate genes including WDR5, whose depletion was found to limit TNBC tumour growth and metastasis in both models. The requirement for functional WDR5 was further validated across other BCa cell lines using shRNA knockdown, or pharmacological inhibition/degradation of WDR5 in a range of standard assays. Transcriptome profiling revealed that depletion of WDR5 reduced global translation efficiency and specifically impacted expression of ribosomal proteins, suggesting a mechanism for its role in promoting TNBC. Rescue experiments using WT and mutant WDR5 proteins revealed that recruitment of the canonical KMT2 complexes via the WIN domain is not critical for breast cancer cell growth or ribosomal gene expression, and this was supported by shRNA knockdown of individual components of the KMT2A/B, SET1A and SET1B complexes. In contrast, WDR5 proteins carrying substitution mutations in the WBM domain (involved in binding to cMYC and RBBP5) failed to efficiently rescue growth phenotype and ribosomal gene expression. It was shown that these mutants retained the ability to be recruited to ribosomal gene promoters, and had little effect on H3K4me3 levels, thus the mechanism requires further investigation. Finally, the effects of WDR5 alone or in combination with MTOR pathway inhibitors was assessed. The overall conclusions here were that MTOR and WDR5 are likely to promote protein synthesis via distinct mechanisms and that targeting both pathways had at least additive effects. Moreover, inhibitors that target both mTORC1 and mTORC2 were more effective than everolimus when combined with WDR5 depletion.

Strengths: Overall the study is very thorough and well-executed with appropriate controls and validatory experiments. The data are convincing and clearly presented, and generally support the conclusions. The use of parallel complementary screens is a strength, as is inclusion of other cell lines and subtypes to support the model.

Reviewer #2 (Public Review):

The overall conclusions of this work are: i) p52 homodimers are able to recognize kB sites with a G at the central position by naturally fitting the wider minor groove found in those sites, ii) binding affinity of p52 to kB sites is poorly correlated with transcriptional activity but the entropic contribution to binding is correlated, iii) higher on and off rates for p52/kB binding are associated with more transcriptionally active kB sites. The results are very interesting and address important questions that underlie mechanisms of transcriptional regulation.

The authors provide data to support their conclusions, but in some cases, the data and interpretations are not entirely convincing. The structural data support a wider minor groove for the PSel kB site, but it is not clear how p52 recognizes this difference. The loss of cross-strand hydrogen bonds near the center of the site is noted, but the addition of a canonical Arg-Gua interaction is shown but not discussed. A higher level of asymmetry in the dimer-DNA interface is described, but it is not clear how this relates to the central 3 bp in question.

The colorimetric studies are fascinating. A range of binding enthalpies from -5 to -15 kcal/mol are reported for the four kB sites studied and a range of -5 to +5 kcal/mol for the enthalpic contribution to binding (TΔS). The more favorable entropic free energy of binding is associated with kB sites that are more transcriptionally active. It is unclear what the source of these wide variations might be; the authors do not attempt to explain the results in light of the structural models.

Binding kinetic studies are also revealing and interesting. The more transcriptionally active kB sites (e.g., PSel kB) have faster on-rates and faster off-rates. The least active kB sites (e.g., MHC) have lower on-rates and lower off-rates. The authors suggest that increased resident time of p52/Bcl3 on the promoter is associated with lower transcriptional activity; a possible reason is that longer times allow the recruitment of co-repressors. The binding affinities derived from BLI experiments are more than 50-fold lower than those measured by ITC. Assuming that the ITC values are correct, this raises questions about what aspects of the kinetic measurements are valid and which might not be.

Overall, I think this is an interesting and important study, but the connections between the structural studies and the binding experiments need to be strengthened and there are several questions/issues about the individual experiments and interpretations that need to be resolved.

Reviewer #2 (Public Review):

The manuscript is well written, and clearly presented. The results are of general interest and present an attractive perspective on manipulating HOTAIR in breast cancer patients that could help to design a novel drug for treatments. However, some important description and characterization are needed to complete the full interpretation of the data, especially concerning the absence of epigenetic memory followed by the interruption of HOTAIR expression. As they stand, loss of epigenetic memory has to be further demonstrated, especially for non-chromatin epigenetic status. More detailed experiments are required to make firm conclusions on this aspect of the study. In addition, despite a great and fully documented phenotypical description, using a large variety of approaches, the analyses of human HOTAIR expression in ES cells and/or cancer cells plus mice primary tumors would have benefited from in situ RNA localization experiments both at subcellular compartments and chromatin loci level.

Reviewer #2 (Public Review):

In the inner ear, the cochlea transforms sound-induced vibrations into electrical signals that are sent to the brain. Cochlear outer hair cells (OHCs) are thought to amplify these vibrations, but it is unclear how amplification works. Sound-induced vibrations modulate the current entering an OHC, which drive its receptor potential, causing the OHC to change length. The change in length owing to the receptor potential variation, known as the OHC's electromotile response, depends on the size of the receptor potential. However, the receptor potential decreases with increasing sound frequency, because of the resistance (R) and capacitance (C) of the OHC's membrane. This paper addresses the RC problem, limitations on high-frequency amplification owing to the OHC's receptor potential decreasing with frequency.

The authors use a well-known simplification of the RC problem and some back-of-the-envelope calculations to argue that OHCs can amplify sufficiently well at high frequencies to match experimental data, despite the decrease in their receptor potentials. They argue that changes to OHC properties along the cochlea allow them to amplify at high frequencies and that OHCs reduce noise and distortion. They argue against OHCs as being cochlear impedance regulators and that OHCs do not limit cochlear tuning.

Figure 1 and Equations 1-6 are useful teaching tools but are not novel. The back-of-the-envelope calculations use these equations and a limited number of data points from the literature. There are many prior models that show amplification despite the RC problem, but they are not analyzed or discussed in much detail.

How RC OHC filtering reduces noise without reducing the signal is not explained. The type of noise calculation done in Appendix 1 is well-known and the application is again a rough back-of-the-envelope calculation. Most of the statements about noise are not fleshed out or supported by calculations.

The discussion about tonotopic variations has little new data. Fig. 2 uses two data points from the literature and an unpublished data point from a colleague. The fact that BM displacement is smaller at the base than at the apex is well known. There is speculation that reduced OHC motion is "effectively counteracted" by gradients in OHC capacitance and MET current, but no evidence is presented.

The discussion about distortions is pedagogical but is again speculation without new or strong-supporting evidence. Fig. 3 argues that OHCs might reduce high-frequency distortions, but don't limit the cochlear amplifier. The plots shown are either well-known consequences of filtering or a summary of the authors' previous model data.

The arguments against OHCs as regulators and that they don't limit tuning are not well flushed out, speculative, and unsupported by new calculations or data.

This paper does not clarify OHC operation or the RC problem, because it mixes speculation, limited data, and topics that are not clearly related to the problem.

Reviewer #2 (Public Review):

This report describes the generation of two quail Tcf/beta catenin signalling reporter lines that differ in their exact makeup and are designed to enhance specifically sensitivity and dynamics of the response. Initial experiment are presented to try to asses these features. A few experiments are described to show that the activity of the reporter coincides with known areas of Wnt signalling activity in E2.5-3.5 embryos, such as the AER of limb buds, Pharyngeal arches, somites and the cephalic neural crest. Some activity is seen is area not previously described to be associated with Wnt signalling, which is interpreted as Wnt independent beta catenin signalling, while in other places known to be areas of canonical Wnt signalling such as the neural tube roof plate are devoid of reporter signal. Importantly it shown that the fluorescent protein expression is strong enough for live imaging in at least some cases. There is a nice demonstration of the aggregation of the precursors of the AER in the developing limb bud. In essence the paper describes the development of two transgenic Tcf/beta catenin reporter lines and provides evidence that they detect signals at least in some in places where activity is expected, providing the expectation that this will be a very useful tool for future studies.

More thorough and quantitative characterization of the reporter lines would have strengthened the paper.

Reviewer #2 (Public Review):

Motile cilia generate rhythmic beating or rotational motion to drive cells or produce extracellular fluid flow. Cilia is made of nine microtubule doublets forming a spoke-like structure and it is known that dynein motor proteins, which connects adjacent microtubule doublet, are the driving force of ciliary motion. However the molecular mechanism to generate motion is still unclear. The authors proved that a pair of microtubules stably linked by DNA-origami and driven by outer dynein arms (ODA) causes beating motion. They employed in vitro motility assay and negative stain TEM to characterize this complex. They demonstrated stable linking of microtubules and ODAs anchored on the both microtubules are essential for oscillatory motion and bending of the microtubules.

Strength<br /> This is an interesting work, addressing an important question in the motile cilia community: what is the minimum system to generate a beating motion? It is an established fact that dynein power stroke on the microtubule doublet is the driving force of the beating motion. It was also known that the radial spoke and the central pair are essential for ciliary motion under the physiological condition, but cilia without radial spokes and the central pair can beat under some special conditions (Yagi and Kamiya, 2000). Therefore in the mechanistic point of view, they are not prerequisite. It is generally thought that fixed connection between adjacent microtubules by nexin converts sliding motion of dyneins to bending, but it was never experimentally investigated. Here the authors successfully enabled a simple system of nexin-like inter-microtubule linkage using DNA origami technique to generate oscillatory and beating motions. This enables an interesting system where ODAs form groups, anchored on two microtubules, orienting oppositely and therefore cause tag-of-war type force generation. The authors demonstrated this system under constraints by DNA origami generates oscillatory and beating motions.<br /> The authors carefully coordinated the experiments to demonstrate oscillations using optical tweezers and sophisticated data analysis (Fourier analysis and a step-finding algorithm). They also proved, using negative stain EM, that this system contains two groups of ODAs forming arrays with opposite polarity on the parallel microtubules.<br /> The manuscript is carefully organized with impressive movies. Geometrical and motility analyses of individual ODAs used for statistics are provided in the supplementary source files. They appropriately cited similar past works from Kamiya and Shingyoji groups (they employed systems closer to the physiological axoneme to reproduce beating) and clarify the differences from this study.

Weakness<br /> The authors claim this system mimics two pairs of doublets at the opposite sites from 9+2 cilia structure by having two groups of ODAs between two microtubules facing opposite directions within the pair. It is not exactly the case. In the real axoneme, ODA makes continuous array along the entire length of doublets, which means at any point there are ODAs facing opposite directions. In their system, opposite ODAs cannot exist at the same point (therefore the scheme of Dynein-MT complex of Fig.1B is slightly misleading). If they want to project their result to the ciliary beating model, more insight/explanation would be necessary. For example, arrays of dyneins at certain positions within the long array along one doublet are activated and generate force, while dyneins at different positions are activated on another doublet at the opposite site of the axoneme. This makes the distribution of dyneins and their orientations similar to the system described in this work. Such a localized activation, shown in physiological cilia by Ishikawa and Nicastro groups, may require other regulatory proteins.<br /> They attempted to reveal conformational change of ODAs induced by power stroke using negative stain EM images, which is less convincing compared to the past cryo-ET works (Ishikawa, Nicastro, Pigino groups) and negative stain EM of sea urchin outer dyneins (Hirose group), where the tail and head parts were clearly defined from the 3D map or 2D averages of two-dynein ODAs. Probably three heavy chains and associated proteins hinder detailed visualization of the tail structure. Because of this, Fig.2C is not clear enough to prove conformational change of ODA. This reviewer imagines refined subaverage (probably with larger datasets) is necessary. It is not clear, from the inset of Fig.2 supplement3, how to define the end of the tail for the length measurement, which is the basis for the authors to claim conformational change (Line263-265). The appearance of the tail would be altered, seen from even slightly different view angles. Comparison with 2D projection from apo- and nucleotide-bound 3-headed ODA structures from EM databank will help.

In Fig.5B (where the oscillation occurs), the microtubule was once driven >150nm unidirectionally and went back to the original position, before oscillation starts. Is it always the case that relatively long unidirectional motion and return precede oscillation? In Fig.7B, where the authors claim no oscillation happened, only one unidirectional motion was shown. Did oscillation not happen after MT returned to the original position?

Line284-290: More characterization of bending motion will be necessary (and should be possible). How high frequency is it? Do they confirm that other systems (either without DNA-origami or without ODAs arraying oppositely) cannot generate repetitive beating?

Reviewer #2 (Public Review):

The manuscript describes the development of a laboratory-based assay as a tool designed to identify individuals who have developed broadly cross-reactive antibodies with specificity for regions that are common to multiple variants of a given protein (VAR2CSA) of Plasmodium falciparum, the parasite that causes malaria. The assay has potential application in other diseases for which the question of acquisition of antibody-mediated immunity, either through natural exposure or through vaccination, remains unresolved.

From a purely technical/methodological viewpoint, the work described is of high quality, relying primarily on the availability of custom-designed, in-house-derived protein and antibody reagents that had, for the most part, been validated through use in earlier studies. The authors demonstrate a high degree of rigour in the assay development steps, culminating in a convincing demonstration of the ability to accurately and reproducibly quantify cross-reactive antibody types under controlled conditions using well-characterized monoclonal antibodies.

In a final step, the authors used the assay to assess the content of broadly cross-reactive antibodies in samples from a small number of malaria-exposed African men and women. Given that VAR2CSA is a parasite-derived protein that is exclusively and intimately involved in the manifestation of malaria during pregnancy, with specific localisation to the maternal placental space, the premise is that antibodies - including those with cross-reactive specificities - should be almost exclusively detectable in samples from women, either pregnant at the time of sampling or having been pregnant at least once. The assay functioned technically as expected, identifying antibodies predominantly in women rather than men, but it failed to identify broadly cross-reactive antibodies in the women's samples used, only revealing antibodies with specificity for just one of the different variants used. The latter result could have two mutually non-exclusive explanations. On the one hand, the small number of women's samples (7) screened in the assay could simply be insufficient, demanding the use of a much larger panel. On the other hand, for technical reasons the assay involves the use of only relatively restricted parts of the VAR2CSA protein, and this particular aspect may represent its primary limitation. In earlier work, the authors did identify broadly cross-reactive antibodies in samples from African women, but that work relied on the use of the whole VAR2CSA protein present in its natural state embedded in the membrane of the infected red cell, or as a complete protein produced in the laboratory. The important point being that the whole protein likely interacts with antibodies that recognize protein structures that the isolated smaller parts of the whole protein used in the assay fail to reproduce, and that the cross-reactive antibodies identified recognize these structures that are conserved across different VAR2CSA variants. The authors recognize these potential weaknesses in their discussion of the results. It is also possible that VAR2CSA variants expressed by parasites from geographically-distinct regions (Africa, Asia, South America) are themselves distinct, and this aspect could also have affected the outcome, since the variant protein sequences used in the assay were derived from parasites originating in these different regions.

The assay could find application in the malaria research field in the specific context of assessments of antibody responses to a range of different parasite proteins that are, or have been, considered candidates for vaccine development but for which their extensive inherent allelic polymorphism has effectively negated such efforts.

Reviewer #2 (Public Review):

The manuscript by Chambers et al. seeks to address adenosine production, which is an immunosuppressive mechanism employed by many solid tumors. To do this, the authors chose to target CD73, which plays an important role in adenosine accumulation in the tumor microenvironment. The authors used natural killer (NK) cells genetically engineered with a chimeric antigen receptor (CAR) designed to target CD73, with the aim to increase NK cell anti-tumor activity against CD73+ lung adenocarcinoma. Major strengths of the manuscript are that the authors show successful modification of primary human NK cells using two methods (electroporation and transduction. Also, the CAR NK cells are tested in vivo in a mouse model and show decreased tumor burden in mice treated with their CD73 CAR-NK cells. Some weaknesses of the manuscript are that data are not always displayed in a manner that makes them easy to access for the reader and are, in some cases, incorrectly described. It is also not clear why the differences between unmodified NK cells have almost as strong anti-tumor activities as CAR-NK cells (e.g. figures 3+4). In total, the idea is of interest for the field of cancer immunotherapy.

Reviewer #2 (Public Review):

I am confused about the nature of Poisson models. If I am correct, the Poisson(a+b) is the sum of the two Poisson(a) and Poisson(b), that is, Poisson(a+b) = Poisson(a) + Poisson(b). Then, the mixture and intermediate models are very similar, identical if a*lambda_A and (1-a)*lambda_B happen to be integer numbers.

It is unclear why the 'outside' model predicts responses outside the range if neurons were to linearly sum the A and B responses.

It is also unclear why the 'single' hypothesis would indicate a winner-take-all response. If I understand correctly, under this model, the response to A+B is either the rate A or B, but not the max between lambda_A and lambda_B. Also, this model could have given an extra free parameter to modulate its amplitude to the stimulus A+B.

The concept of "coarse population coding" can be misleading, as actual population coding can represent stimulus with quite good precision. The authors refer to the broad tuning of single cells, but this does not readily correspond to coarse population coding. This could be clarified.

As a complement to the correlation analysis, one could check whether, on a trial-by-trial basis, the neuronal response of a single neuron is closer to the A+B response average, or to either the A or B responses. This would clearly indicate that the response fluctuates between representing A or B, or simultaneously represents A+B. I am trying to understand why this is not one of the main analyses of the paper instead of the correlation analysis, which involves two neurons instead of one.

In the discussion about noise correlations, the recent papers Nogueira et al., J Neuroscience, 2020 and Kafashan et al, Nat Comm, 2021 could be cited. Also, noise correlations can also be made time-dependent, so the distinction between the temporal correlation hypotheses and noise correlations might not be fundamental.

It would be interesting to study the effect of contrast on the mixed responses. Is it reasonable to predict that with higher contrast the mixture responses would be more dominant than the single ones? This could be the case if the selection mechanism has a harder time suppressing one of the object responses. This would also predict that noise correlations will go down with higher contrast.

What is the time bin size used for the analysis? Would the results be the same if one focuses on the early time responses or on the late time responses? At least from the units shown in Fig. 2, it looks that there is always an object response that is delayed respect to the other, so it would seem interesting to test noise correlations in those two temporal windows.

Reviewer #2 (Public Review):

The authors recently found that the phylogenetically reconstructed ancestral beta1 subunit (betaAnc) can insert two copies in the human muscle nAChR, replacing both the (modern) beta and delta subunits.

The channels thus expressed had heterogeneous behaviour, with a subpopulation of much larger openings (16 vs 10 pA). The larger channels became scarcer when the amount of betaAnc transfected was reduced, and this suggests they are homopentamers of betaAnc.<br /> This is well supported by the fact that they appear in isolation when only betaAnc is transfected. Their pentameric nature is convincingly confirmed by high quality single channel conductance fingerprinting (mixing high and low conductance variants of the subunit and counting the conductance classes). This is surprising in view of the fact that the muscle nAChR has a robust heteromeric composition.

Another surprise is that the homomeric betaAnc channels are spontaneously active in the absence of the agonist ACh.

The betaAnc homopentamers channels display features similar to those seen in muscle nAChRs, including open channel block by ACh and by the blocker QX222. The features of the block (rates, equilibrium constants) are quite similar for the two channels.

In addition to that, the spontaneous bursts of the homopentamers show more than one closed state, suggesting the presence of activation intermediates (as in other pLGIC channels).

A point of strength of this study comes from a final set of experiments that shows that an alternative ancestral beta, betaAncS, reconstructed using a different phylogenetic tree, also expressed functional homomeric receptors that open spontaneously. These have a somewhat different kinetics, that allows the detection of more closed primed activation intermediates.

These results open up many questions on the evolution of muscle nAChR: did muscle nicotinics start as spontaneously opening homomers? When in evolution did they stop opening spontaneously?

Reviewer #2 (Public Review):

Sliding clamps and clamp loaders are essential macromolecular complexes that enable DNA synthesis, as well as a diverse collection of other DNA maintenance reactions. Sliding clamps are toroidal ensembles (in eukaryotes, they are trimers termed PCNA) that bind to DNA via topology (in addition to biochemical interactions). The closed protein PCNA clamp rings require specialized catalysts, known as a clamp loader for assembly onto DNA. Clamp loaders are five-membered AAA+ ATPase machines that couple ATP binding and hydrolysis to crack open the clamp, select and insert the correct DNA substrates into the opened ring. The clamp loader then resets itself via ATP hydrolysis and release of the closed clamp. Remarkably, the structure and function of sliding clamps and clamp loaders are conserved in all domains of life.

The eukaryotic clamp loader is comprised of five unique subunits (termed: RFC1, RFC2, RFC3, RFC4, and RFC5). Each feature shared as well as unique domains. Each RFC subunit contains the AAA structural module (referred to as AAA-ATP and AAA-lid). The heteropentameric RFC clamp loader is held together, so to speak, by a rigid collar formed out of helical domains contributed by each subunit. The eukaryotic sliding clamp is a trimer of identical PCNA subunits. The RFC clamp loader has been previously found to prefer 3' recessed primer-template junctions onto which the PCNA trimer is loaded. Primer-template junctions are appropriate substrates for supporting, enabling, and stimulating DNA synthetic processes. Remarkably, however, the RFC loader is not the only clamp loader described in eukaryotes. It has been known for nearly 20 years that the substitution of RFC1 for another RFC1-like subunit creates a new entity with apparently disparate biochemical properties. For example, the substitution of Rad24, an RFC1-like protein, for RFC1 creates a loader ensemble with properties distinct from the archetypical RFC loader. Unlike the RFC loader, the RAD24 loader binds to 5' recessed DNA, but not 3' recessed DNA, for loading the 911 clamp, but not the PCNA clamp.

Insightful and thoughtful studies by many groups over the past decades have painted a reasonably detailed picture of the structure and function of clamps and clamp loaders. Notably, Kelch and coworkers produced a series of structures of yeast RFC bound to PCNA and primer-template DNA (eLife, 2022). These structures show, inter alia, the details of the primer-template DNA within the loader and the double-stranded portion of the DNA within the PCNA ring. Also, Remus, Hite and co-workers and O'Donnell/Li and co-workers recently published analyses of the Rad24 clamp loader bound to the 911 clamp. An important overall finding of the Rad24 studies was the discovery of a novel DNA binding mode. The Rad24 loader bound the 5' recessed DNA, not within the loader and the clamp, but 'above' (in a specific reference pose) the 911 ring.

As a follow-up to the 2022 study by Kelch, Liu et al made the fortuitous observation that a second primer-template DNA molecule binds to RFC, in addition to the primer-template molecule that binds within the loader. Remarkably, the second primer-template molecule binds above the PCNA ring in a manner reminiscent of the position occupied by DNA in the Rad24 loader.

To be sure, biochemical evidence did exist that the picture of DNA binding by RFC provided by prior structural biology was incomplete. Notably, Susan Hardin and coworkers (1998) and Gregg Siegel and coworkers (2006/2010) had investigated the BRCT domain found at the N-terminus of the RFC1 subunit (Drosophila and Human) and had found that, in isolation, this domain bound to one DNA molecule with a preference for a recessed 5' DNA structure. The finding that RFC had binding sites for 3' and 5' recessed DNA was not accommodated in the extant crystal and EM structures.

To review this manuscript, I considered the narrative, 6 figures, 2 supplementary tables, 11 supplementary figures, 4 sets of coordinates and PDB validation reports, and 4 sets of accompanying EM density maps.

This manuscript encompasses the following items:<br /> 1) 4 atomic models of the RFC-clamp loader determined using cryo-EM<br /> a. RFC bound to PCNA, ATPgS, and two primer-template DNA molecules (3.4 Å)<br /> b. RFC-PCNA-ATPgS-5-nt-gap (3.0 Å);<br /> c. RFC-PCNA-ATPgS-6nt-gap (3.0 Å);<br /> d. RFC-PCNA-ATPgS-singly-nicked-DNA 3.7 Å.

Supplementary table 1 and the PDB validation reports speak to the high-quality cryo-EM analyses performed by Liu and co-workers.

The fortuitous finding of two primer-template molecules in the RFC structure also revealed the structure and role of the BRCT domain found at the N-terminus of RFC1. The first primer-template molecule binds with the RFC loader and extends into the central chamber of the PCNA clamp.

On the other hand, the second primer-template molecule binds above the PCNA ring (in a certain RFC pose). The binding site of the second molecule is situated entirely on the RFC1 subunit. Contacts to the duplex portion of the primer template arise from the 'top' of the AAA-ATP, the AAA-lid, and the collar domains of RFC1 as well as the ordered BRCT domain. This is the first time that the BRCT domain has been visualized in any RFC structure. The ssDNA segment of the primer-template molecule is directed into the so-called A-gate and into the RFC loader.

In addition to a previously described 'separation pin' within the RFC loader that separates the very 3' end of the primer-template junction, the authors identify a second 'separation pin' that appears to separate the DNA strands of the second molecule; this second pin is located on the collar domain.

Comparison to the previously determined yeast RFC structures from the Kelch lab led the authors to conclude that the internal site must bind DNA first; binding triggers a series of structural changes that create the binding site for the second DNA molecule.

2) A 2 amino-purine fluorescence-based DNA melting assay is used to show that both 3' and 5' recessed DNA molecules (with ATPgS) exhibit an increase in fluorescence interpreted to mean that melting occurred (Supplementary Figure 1.4).

Given the structure-based finding that the first molecule must bind first to enable binding of the second molecule, is it surprising that the 5' recessed molecule on its own is bound and melted (i.e., without the 3' recessed molecule binding first)?

3) The finding that RFC binds to two DNA molecules leads the authors to 'link' the two molecules and explore the substrate requirements of the resulting single DNA molecule, which features a series of gaps or a single nick. Using ATPase and 2 AP fluorescence assays, the authors examine the relationship between gap size and ATPase and base-melting activity. This series of experiments suggest that a gap size of 6 might be the appropriate length to link the internal and external DNA binding sites, but that a gap size of 4 experienced the greatest extent of base melting.

4) To gain further insights into the RFC-PCNA-extended DNA complex, the authors performed three additional structure determinations this time with a single DNA scaffold, but which included 5, 6 nt gaps, and a single nick. The structures with the 5/6 gapped DNA molecule resembled the two-DNA RFC-PCNA complexes, with an additional ssDNA segment that linked the DNAs in the two sites. The finding that both structures featured a 6 NT gap implied that the 5 NT gap structure had experienced melting of a base pair. Together, these structures provide crucial support for the idea that RFC, PCNA can natively bind an extended DNA molecule and that molecules with small gaps were physiological substrates for RFC.

The structural effort that encompassed the nicked DNA goes on to probe the idea that melting takes place at the second, external, DNA binding site. The nick-containing DNA structure overall resembles the others from an overall perspective. However, this structure also featured a five NT segment that appeared to be stretched relative to its counterparts in the gapped DNA structures. Moreover, both the internal and external DNA molecules show signs of having been melted by the internal and external separation pins; 3 bp at the internal site and 1 bp at the external are disrupted; the sum (4 nt) leaves one nucleotide unseen in the density maps. The DNA melted at the internal site is directed towards a channel near/underneath the collar domain.

5) The authors start the process of testing their structural models by examining the response of yeast whose RFC1 lacks the BRCT domain. The growth of such a yeast strain is challenged by three DNA damaging agents (MMS, HU, and UV light) with distinct mechanisms of action. Of these, only the DNA methylating agent methylmethane sulphonate (MMS) reveals any type of yeast growth defect. The other agent: hydroxyurea, which damages DNA by compromising nucleotide pools and UV light appears to show no growth defects. This finding points to the involvement of RFC in aspects of base excision repair (BER), which repairs methylation damage. This study is undoubtedly the first of many by Kelch and other groups.

Liu et al synthesize their current and prior findings, and those of other groups, into a structure-based model to explain how RFC could recognize and load PCNA onto nicked DNA. Their structural work also establishes a previously unrecognized link to the DNA binding mode exhibited by the Rad24 clamp loader.<br /> Overall, the data in the manuscript are of high quality and the accompanying narrative and figures are well presented.

Reviewer #2 (Public Review):

Ivica et al., conducted a series of electrophysiological and cryo-electron microscopy studies to investigate what differentiates partial agonist versus full agonist effects at the glycine receptor, a member of the cys-loop receptor superfamily. To this end, they used aminomethanesulfonic acid (AMS), a novel partial agonist that possesses efficacy intermediate between the high efficacy agonist glycine and the partial agonists beta-alanine and taurine. AMS was shown to possess a maximal channel open probability of 0.85, compared to 0.96 for glycine and only 0.12 for taurine. Cryo-EM structures of glycine receptors that had bound glycine, AMS, or taurine differed, with only glycine and AMS yielding a compact conformation that differed from that seen after taurine binding. This is thought to be partially responsible for the different efficacies of these ligands. This study was performed meticulously, with compelling evidence provided supporting the authors' primary hypothesis.

The authors should consider defining what they mean by glycine being a "full agonist". In previous publications, they have argued that, since efficacy is a ratio of rates of transitions among different states of receptors, what anyone currently defines as a full agonist is in reality just the highest efficacy ligand discovered to date. There isn't any problem with the use of the term "full agonist" per se, since it is a concise way of comparing the high efficacy of glycine versus other ligands at the GlyR, but the reader would be served by having this clarified.

Is there a qualitative rather than just a quantitative difference between high and low efficacy agonists at glycine receptors, in that only low efficacy compounds can interact with the loop B serine 174 residue and only high efficacy ligands yield compact binding pockets? In other words, should ligand efficacy be considered a continuum at the GlyR, or should it be considered more quantal in nature, with different agents occupying discrete categories? Explicitly addressing this issue would likely be of interest to the reader.

Reviewer #2 (Public Review):

Translational control is critical for adaptation to environmental stresses, such as those inflicting oxidative damage and these regulatory mechanisms are suggested to involve the interplay of proteins associating with ribosomes or translating mRNAs. This manuscript uses the yeast model system and an unbiased proteomics approach to measure proteins associating with monosomes and heavy ribosomes (measures of robust mRNA translation) to measure this interplay in response to oxidative stress (acute hydrogen peroxide exposure). The manuscript identifies clusters of proteins that are enriched with polysomes, some differentially bound, in response to the oxidative stress. The study provides a thoughtful analysis of the clusters of proteins that that differentiall engage with the ribosomes and their regulatory meaning. One protein aspartate amino transferase (Aat2) was determined with be associated with heavy polysome duyring oxidative stress and this association was genetically determined to be independent of its metabolic activity and show to moderate Gcn2 activation and the integrated stress response (aka yeast general amino acid control). Deletion of AAT2 conferred sensitivity to H2O2 and had an accompanying enhanced Gcn2 phosphorylation of eIF2 and translational control, showing its in vivo significance in translational control. Overall, this is a significant manuscript that provides insights into the dynamics of changing protein associations with ribosomes and their implications for translational control. The manuscript is well organized, generally clearly presented, and experiments are appropriately interpreted. The manuscript would be of broad interest. There are some concerns involving clarification of some text and figures.

Reviewer #2 (Public Review):

The authors present a new platform for constructing and sharing fMRI analyses, specifically geared toward analyzing publicly-available naturalistic datasets using automatically-extracted features. Using a web interface, users can design their analysis and produce an executable package, which they can then execute on their local hardware. After execution, the results are automatically uploaded to NeuroVault. The paper also describes several examples of analyses that can be run using this system, showing how some classical feature-sensitive ROIs can be derived from a meta-analysis of naturalistic datasets.

The Neuroscout system is impressive in a number of ways. It provides easy access to a number of publicly-available datasets (though I would like to see the current set of 13 datasets increase in the future), has a wide variety of machine-learning features precomputed on the video and audio features of these stimuli, and builds on top of established software for creating and sandboxing analysis workflows. Performing meta-analyses across multiple datasets are challenging both practically and statistically, but this kind of multi-dataset analysis is easy to specify using Neuroscout. It also allows researchers to easily share a reproducible version of their pipeline simply by pointing to the publicly-available analysis package hosted on Neuroscout. The platform also provides a way for researchers to upload their own custom models/predictors to extend those available by default.

The case studies described in the paper are also quite interesting, showing that traditional functional ROIs such as PPA and VWFA can be defined without using controlled stimuli. They also show that, running a contrast for faces does not produce FFA until speech (and optionally adaptation) is properly controlled for, and that VWFA shows relationships to lexical processing even for speech stimuli.

I have some questions about the intended workflow for this tool: is Neuroscout meant to be used for analysis development in addition to sharing a final pipeline? The fact that the whole analysis is packaged into a single command is excellent for reproducibility but seems challenging to use when iterating on a project. For example, if we wanted to add another contrast to a model, it appears that this would require cloning the analysis and re-starting the process from scratch. I'm also unsure about how versioning of the input datasets and the predictors is planned to be handled by the platform; if datasets have been processed with multiple versions of fmriprep, will all of those options be available to choose from? If the software used to compute features is updated, will there be multiple versions of the features to choose from? I also had some difficulty attempting to test out the platform, so additional user testing may be necessary to ensure that novice users are able to successfully run analyses.

Reviewer #2 (Public Review):

Hart et al. examine how cells maintain proliferation in the context of SDH inhibition. A major strength of this study is the interesting observation that ETC complex I inhibition restores proliferation in SDH-deficient cells, which could have relevance for evolution of SDH-deficient tumors. The authors also demonstrate that SDH-inhibition is not coupled to a decrease in NAD+/NADH ratio. For the most part, the authors rigorously tested these observations using a number of genetic and chemical perturbations. However, a major weakness of the paper is the unclear physiological relevance of the findings and the tendency to overstate results, especially with regards to the dependence on aspartate biosynthesis.

Reviewer #2 (Public Review):

There have been several estimates of the generation time and serial interval published for SARS-CoV-2, but as the authors note, estimates can be subject to biases including shifted event timing depending on the phase of the epidemic, correlation in characteristics between infector and infectee, and impact of control measures on truncating potential infectiousness. This study, therefore, has several strengths. It first collates data on transmission events from the earliest phase of the COVID-19 pandemic, then makes adjustments for these potential biases to estimate the generation time in absence of control measures, and finally discusses implications for transmission.

Given many subsequent aspects of the COVID-19 pandemic have been defined relative to earlier phases (e.g. relative transmissibility of variants, relative duration of infectiousness), understanding the baseline characteristics of the infection is crucial. I thought this paper makes a useful contribution to this understanding, generating adjusted estimates for infectiousness (which is longer than previous estimates) and corresponding values for the reproduction number (which is remarkably similar to earlier estimates, presumably because of the different sources of bias in the growth rate and generation time distribution somehow end up cancelling each other out).

However, there are some weaknesses at present. The study correctly flags several potential sources of bias in estimates, but in making adjustments uses estimates from the literature that themselves could suffer from these biases, e.g. the distribution of incubation period from a 2021 meta-analysis. Although the authors conduct some sensitivity analysis it would be worth including some more explicit consideration of whether they would expect any underlying bias to propagate through their calculations. The authors also conduct some sensitivity analysis around the underlying data (e.g. ordering of transmission pairs), but again it would be useful to know whether there could be systematic biases in these early data. Specifically, the paper references Tsang et al (2020), which highlighted variability in early case definitions - is it possible that early generation times are estimated to be longer because intermediate cases in the transmission chain were more likely to go undetected than later in the epidemic?

It would also be helpful to have some clarifications about methodology, particularly in how the main results about generation time are subsequently analysed. For example, estimates such as the conversion of generation time to R0 and VOC scalings are described very briefly, so it is currently unclear exactly how these calculations are being performed.

Reviewer #2 (Public Review):

In this work, Babina et al. address a central question in molecular evolution that is only partially answered: how does cellular novelty emerge in evolution? The authors focus here on small proteins, whose importance to various cellular functions has become more appreciated recently. Babina et al. ask if functional small proteins can emerge from random sequences, a question that is mostly unresolved with only a small number of examples in the published literature for such functions. In this study, the authors demonstrate that proteins selected from random, synthetic libraries can rescue auxotrophy in E. coli. Namely, the authors find three small, random proteins (<50 amino acids) that allow E. coli cells with a ΔserB genetic background to grow in a medium without the amino-acid serine. They then show that this rescue is based on the up-regulation of HisB, an enzyme that can compensate for the serB deletion. Finally, using different molecular biology techniques, the authors propose a model in which up-regulation of HisB is achieved by physical interactions between the random proteins and the his operator that regulates the transcription of the his operon in E. coli.

Notably, as the authors themselves point out, a previous study has already shown that semi-random proteins can result in up-regulation of HisB levels to rescue ΔserB cells. Thus, most of the novelty comes from the attempt to figure out the molecular mechanism of the three random proteins. The idea that a random protein binds the 5' of an mRNA which results in up-regulated expression levels is interesting and can benefit the field. However, some clarification on existing data and additional control experiments are needed to support the authors' claims:

1) Growth data are not presented in the current form of the manuscript, which makes it impossible to evaluate many of its claims. Especially, the extent of rescue and fitness gain achieved by these random proteins compared to cells harboring the serB gene.

2) The authors have screened their library on other auxotrophic strains, however, they could only find random proteins that rescue growth in the ΔserB background. Currently, they do not address this point, but it might be relevant to the molecular mechanism of those random proteins.

3) Central to the authors' claims is the up-regulation of HisB, however, they mostly work with an alternative LacZ system to assess the effects of the random proteins on expression. The paper will benefit from some more work measuring actual HisB levels as expressed by the various constructs used along the paper. The authors did provide an important proteomic analysis to show that HisB (along with other proteins in the his operon) is up-regulated as a result of the expression of one of the random proteins. However, it is unclear if the reported ~3-fold increase in HisB levels is enough to allow the growth of ΔserB cells in a medium without serine.

4) It is unclear how noisy and statistically significant some of the critical experiments in the manuscript are, especially the EMSA and T1-digestion experiments. The authors should try to find a different operator with a similar RNA structure and attenuation function, but a different nucleotide sequence, to the his operator, and show that this control operator is unaffected by the random proteins. Demonstrating the lack of phenotypes using the LacZ system, EMSA experiments, and T1-digestion patterns will much support the authors' claims.

Reviewer #2 (Public Review):

In the current study, the authors provide a detailed examination of the potential atheroprotective role of semaphorin 3F (SEMA3F). The semaphorin signaling pathway and other members of the semaphorin family are significantly associated with coronary heart disease in humans. Additionally, several studies have linked semaphorin proteins to atheroprotection. However, the potential causal or protective roles of SEMA3F had not been studied in atherosclerosis. Rattanasopa et al, have used a combination of chow-fed, or western-type diet(WTD)-fed Ldlr-/- mice, and Sema3f-/- mice, combined with injection of recombinant SEMA3F protein, and a partial ligation model, to study the contribution of SEMA3F in atherosclerotic plaque formation and assess changes in monocyte recruitment and intracellular signaling events. These data were supported through the use of primary human coronary artery endothelial cells. The authors find that SEMA3F administration can reduce atherosclerotic lesion size and increase lesion stability in hyperlipidemic mice. Conversely, loss of SEMA3F in the Sema3f-/-, had the opposite effect in increasing lesion size and decreasing endothelial cell stability while increasing smooth muscle actin expression. Critically, loss of SEMA3F enhanced monocyte adhesion, likely due to increased VCAM1 and ICAM1 expression in endothelial cells. Additionally, SEMA3F enhanced smooth muscle cell migration and contraction. Combined, the studies provide fresh insight into the possible protective effect of SEMA3F peptide, through reduction of PI3K signaling and collagen deposition.

The conclusions of the study are generally supported by the data but would benefit from additional supportive controls, greater clarity of descriptions for imaging methodologies, and clearer image representation.

1) The authors show multiple important data sets that support the hypotheses, but to fully confirm the conclusions additional controls would be required. Specifically, the dissection of the signaling pathways downstream of SEMA3F and the control of mTOR, PI3K, NFkB, and the subsequent regulation of monocyte adhesion via VCAM1 or ICAM1. Limited controls were used and strong conclusions were drawn from small differences, this impacted the potential interpretation of the data

2) The authors use quantification of multiple histological images throughout the manuscript. Quantifying staining or fluorescent intensity to define the possible role of SEMA3F on atherosclerotic progression. There are some concerns with these experiments. Firstly, the descriptions of how plaque sections are chosen are not detailed enough in the methods. i.e how have the authors controlled for where in the plaque the sections have been collected, and how did they ensure to compare similar sections between conditions and clarity for how many individual repeats were used. Secondly, the methods are not detailed enough to fully assess how the samples were quantified. Finally, in some images (Figures 1C,1F, 2B, 3E, 5C-F, and 7A-D) it is difficult to see the difference claimed by the authors as currently presented. Combined, as these data are critical to testing the authors' hypothesis.

Reviewer #2 (Public Review):

In the manuscript "Genomic Landscape of Lymphatic Malformations: A Case Series and Response to the PI3Kα Inhibitor Alpelisib in an N-of-One Clinical Trial" by Shaheen et al., the authors performed genomic profiling in 30 patients with lymphatic malformations (LM). They performed hybrid capture next-generation sequencing of exons from a panel of >300 cancer-related genes and introns from 36 genes on resected tissue from the LM. The LM had a low mutation burden, with PIK3CA (n = 20) and NRAS (n = 5) being the most frequent, and mutually exclusive. In four patients, the LM had kaposiform pathology and each of these patients had NRAS mutations, suggesting a correlation between phenotype and genotype. Finally, one patient with PIK3CA mutation was treated with the PI3Kalpha inhibitor alpelisib, resulting in a radiological shrinking of the size of the LM at 6 weeks and 6 months. The in vitro growth of lymphatic endothelial cells carrying PIK3CA mutation could be inhibited with alpelisib.

Strengths:

1. This is a large cohort of patients for such a rare disease, and thus the identification of mutations in the majority of these lymphatic abnormalities is of significant clinical importance.<br /> 2. Kaposiform lymphangiomatosis is rare and this study shows it is present in 4 of the 5 patients with activating NRAS mutations, suggesting a phenotype-genotype correlation.<br /> 3. Their single patient treated with the PIK3CA inhibitor alpelisib had a radiologic response with shrinkage of the LM, consistent with a prior study showing similar results in 6/6 patients, and treatment of lymphatic endothelial cells carrying PIK3CA mutations with alpelisib showed reduced growth in vitro.

Weaknesses:

1. This is not the first demonstration of somatic activating NRAS mutation associated with Kaposiform lymphangiomatosis. A prior study demonstrated that 10/11 patients with Kaposiform lymphangiomatosis had NRAS mutation (PMID 30542204).<br /> 2. This is not the first demonstration of somatic activating PIK3CA patients exhibiting malformation shrinkage with alpelisib and they only had a single treated patient. A prior study showed similar results in 6/6 patients treated with alpelisib for 6 months (PMID 34613809).<br /> 3. The effects of alpelisib on cell growth in vitro were tested on lymphatic cells from one patient, and the results would have been strengthened if cells from 2 or more patients had been tested.<br /> 4. For the RNA-seq experiments, the significance of the gene expression remains unclear, especially given the numerous cell types present in their tissues.

Overall, this manuscript will have a clinical impact on the field of lymphatic abnormalities and the results support the conclusions.

Reviewer #2 (Public Review):

The goal of this study is to examine the transmission of mosaic genetic variants identified in sperm. The authors first perform genome sequencing of DNA from sperm (and blood) at 300x depth to identify putative mosaic variants. They then validate each and simultaneously test blastocysts obtained via IVF using ddPCR to determine whether/which variants were transmitted.

This study differs from previous studies in that mosaic variants are first identified in sperm, rather than identifying de novo variants in offspring and retrospectively testing for germline mosaicism in the parent(s). The experimental approach is solid, though the depth of coverage is modest at 300x. The overall findings are consistent with expectations: they do observe transmission of a subset of variants, and those with higher allele frequencies are more likely to be transmitted. They perform a similar analysis in eight previously studied families with 14 offspring and find overall similar results.

An underlying premise of the study is that a priori testing could be performed to prevent transmission of disease-causing variants that usually occur de novo in the affected offspring. A potential weakness is the sample size, as only three cases (sperm + blastocyst) are evaluated. Furthermore, all mosaic variants identified in these cases were deemed likely benign; with the goal of preventing the transmission of deleterious variants, it would be important to expand the cohort in the future and, when possible, evaluate the transmission of potentially deleterious variants.

Reviewer #2 (Public Review):

The manuscript from Hurwitz et al. documents a connection between the integral stress response (ISR) and a centrosome-mediated protein clearance mechanism, using skin carcinoma cells as a model system.

Using ribosomal profiling and molecular approaches, the authors identify that upon stress, the IRS promotes a shift in the translation of centrosomal proteins required for the clearance of unfolded protein-enriched aggregates in the pericentrosomal area. Abrogating the ISR response sensitizes cancer cells, promoting cell death.

The authors generated useful cellular tools for the community and information about the translational changes of specific proteins involved in the IRS response, paving the way for future studies.

There are no major significant weaknesses, and the authors achieve their aim of dissecting the relevance of the ISR in skin carcinoma cells.

Reviewer #2 (Public Review):

The authors of this paper propose a high-throughput software pipeline to stitch and align millions of microscopy images, which is scalable to petabyte-sized datasets and can be executed in distributed computer environments. Although the software was originally designed for electron microscopy (EM) images and research on connectomics, it has been successfully tested in other image modalities. This is an impressive engineering work that opens the door to the analysis of previously unfeasible large-scale datasets by facilitating their assembling at the same pace of acquisition, or even faster. Despite the fact that the resources needed for projects of these dimensions are nowadays only accessible by a few labs and institutions in the world, the proposed software pipeline and tools will have an impact in more modest (but also large-scale) bioimage analysis research. The quality control tools provided within the software are crucial in a framework like this, where errors can get easily propagated and thus human proofreading needs to be facilitated.

The quality of the resulting assembled datasets together with their processing speed proves the suitability of the proposed method. Overall, this is an exciting paper which makes significant contributions to the field of connectomics and large-scale bioimage analysis in general.

Reviewer #2 (Public Review):

This study investigated the lineage-circuit relationships using Drosophila EL neurons born from the NB3-3 lineage in the ventral nerve cord as a model system. This is an important question that is less well-studied. From the already existing studies, it appears that lineage-circuit relationships defer in different contexts. In some cases, neurons from the same lineage preferentially wire together, while in other cases, neurons from different lineages wire together. In this study, the authors tested their hypothesis that Drosophila ventral nerve cord circuits are formed preferentially between different temporal cohorts in different neuroblast lineages. They first demonstrated convincingly that there is a sharp transition in the connectivity pattern at the border of the temporal cohorts. Next they characterized a feed-forward circuit in which early-born EL neurons serve as the output, and showed that this circuit is formed between different temporal cohorts in different neuroblast lineages, and the output neurons are born before the input neurons in this circuit.

This study represents a significant further step in the study of lineage-circuit relationship, and the data are solid and well-controlled to support their conclusion within this context being studied. Major achievements and strengths include: 1) Using a combination of genetic experiments, connectome mining and network science approaches, they precisely mapped the birth-order and the morphology and connectivity of all EL neurons, and provided solid and quantitative evidence to a sharp transition in morphology and connectivity that correlated with the border of temporal cohorts. 2) Further, they characterized extensively the four classes of synaptic inputs to early EL neurons, and showed that early EL neurons are embedded within a feed -forward circuit that encodes vibrational onset. 3) They mapped the origin and birth order of the input neurons, and provided evidence to their hypothesis that Drosophila ventral nerve cord circuits are formed preferentially between different temporal cohorts in different neuroblast lineages. 4) The new permanent labeling construct for ts-MARCM will be a very useful tool for the fly community. 5) They showed that within a feedforward circuit, the output neurons are born before the input neurons. This showed that the strict early to early/ late-to-late hypothesis does not apply to all circuits. One weakness is that it is not known whether the birth order for this particular circuit can be generalized to other feedforward circuits.

Reviewer #2 (Public Review):

In the current manuscript, Khattar et al., have employed a novel analysis using a combinatorial approach composed of the epigenetic and transcriptomic assessment of the developing lung landscape. With this method, they have been able to reduce the noise in data that frequently complicates single assessment of open chromatin or differential gene expression only. In this instance, they were able to ascertain only active transcription factors based on the gene regulatory networks they opened in their analysis. From these data, they discovered a network of PI3 kinase signaling that has been previously implicated in lung development but now confirmed and complemented with their ex vivo and in vivo experiments.

The strengths of this study are the novelty of their epigenetic and transcriptomic combinatorial analysis in the developing lung. The data they have generated will be of significant interest to the lung field, and it has provided a platform for future studies. Their vast bioinformatics analysis supports their conclusions on the first part of this study.

From their bioinformatic analysis, the authors identified a gene regulator network implicating PI3 kinase signaling in branching and proximal-distal axis formation. While much of their data for the remainder of this study supports this pathway's involvement, there remains many unanswered questions to fully support their conclusions.

First and foremost, the authors implicate that there is a gradient of PI3K signaling in the developing lung epithelium based on expression of phospho-AKT. This conclusion would be better supported with confirmation of expression (by qPCR) of several of the previously identified genes in the PI3K regulatory network they identified earlier. In addition, AKT can be modulated by other pathways. The authors should consider examining an additional read out of PI3K signaling. Furthermore, the current imaging has not delineated the proximal-distal axis (Sox2-Sox9), which develops and is sustained from E12.5 to the saccular stage. Additional imaging showing that gradient exists along the proximal-distal axis as well as other time points during development would be critical for their conclusion.

The authors used both ex vivo and in vivo modeling to support a role for PI3K in lung development. Inhibition of PI3K in both systems results in expansion of SOX9+ EPCs. However, the mechanism is quite unclear here, especially in the presence of decreased proliferation of SOX9+ EPCs. Is the expansion of SOX9 EPCs at the expense of proximal SOX2+ epithelial progenitor cells during development. The mechanism would be better supported by assessment of SOX2 EPCs during early development with particular attention to the proximal-distal axis and appropriate branching at early time points. In addition, previous studies demonstrated that the branching defects such as the authors demonstrated result in alveolar specification defects and explain their findings of differentiation defects of both proximal and distal lineages.

Finally, additional controls are need to support their conclusions. In particular, deletion of PI3Kca should be confirmed by its gene expression and pAKT during development. As mentioned earlier, additional confirmation of some of PI3K signaling component and target gene upregulation by RNAseq should be confirmed by qPCR and/or RNAscope/in situ or IHC. These studies would help integrate previous findings in PI3K signaling and lung development and provide a more comprehensive understanding of the mechanism.

Reviewer #2 (Public Review):

First, I want to congratulate the author team on this manuscript, which I read with great pleasure. I think this will be a fine addition to the literature!

The present MS by Clement et al. provides a comprehensive overview of the brain shapes of lungfishes. Besides previously known/described brain endocasts, the work includes models and descriptions of previously undescribed taxa. Notably, all CT data are deposited online following best practices when working with digital anatomy. The specimen sample is impressive, especially as the sampled material is housed in museum all over the world. Although the sample size may seem numerically low (12 taxa), this actually is a comprehensive sample of fossil (and extant) lungfishes in terms of what's preserved in the first place.

The study at hand has several goals: (1) The description of lungfish brains for taxa that were previously undescribed; (2) the quantification of aspects of brain shape using morphometric measurements; (3) the characterization of brain shape evolution of lungfishes using exploratory methods that ordinate morphometric measurements into a morphospace.

The provided 3D data and descriptions will serve as valuable comparisons in future lungfish work. This type of data is imperial for palaeontological studies in general, and the anatomical information will be extremely valuable in the future. For example, anatomical characters related to brain architecture have been shown to be informative about phylogeny in the past, and the presented data may inform future phylogenetic studies.

The quantification of brain shape via (largely linear) measurements is relatively simplistic, and can thus only detect gross trends in brain shape evolution among lungfishes. The authors describe several such trends - such as high variation in the olfactory brain region in comparison to other parts of the brain. The results and interpretations drawn from the authors are supported by their data, and the approach taken is valid, even if more sophisticated shape quantification methods (e.g. 3D landmarking) and analytical methods (e.g. explicit phylogenetic comparative methods) are available, which could provide additional insights in the future. The presented results and interpretations in this regard must be seen as a preliminary assessment of lungfish brain evolution, but it is clearly written and generally well performed.

A potential shortcoming of the paper is the lack of explicit hypothesis testing, which is not problematic per se, but puts limits on the conclusions the authors can draw from their data. For example, the authors state that different anatomical parts of the labyrinth (particularly, the utricle with respect to the semicircular canals or saccule) may show modular dissociation from other labyrinth modules, based on the polarity of eigenvalue signs of the PCA analysis. I think this is fine as a first approximation, but of course there are explicit statistical tools available to test for modularity/integration, such as two-block partial least squares regression analysis (Rohlf & Corti 2000, Syst. Biol.). I don't see the lack of usage of such methods as problematic, because you cannot do everything in one paper, and the authors remain careful in their interpretation. It may be advisable, however, to add the odd sentence or statement about how some findings are preliminary or hypothesized, and that these should receive further treatment and testing using other methods in the future. I think this approach is actually very rewarding, because then you can inspire future work by outlining outstanding research problems that arise from the new data presented herein.

In the following, I comment on a few aspects of the manuscripts. These represent instances where I had additional thoughts or ideas on how to slightly improve various aspects of the manuscript.

1. Presentation of PCA results

The authors provide several PCA analyses (preliminary analyses on partial matrices, BPCA, InDaPCA), and are very explicit about the procedures in general. For instance, I appreciate they explicitely state using correlation matrices for PCA analyses due to the usage of different measurement units among their data.

Visually, the BPCA and InDaPCA are presented in figures 2 and 3, whereas the preliminary partial matrix PCAs are only reported as supplementary figures. While I don't object to any of this, I find the sequence of information given in the results section suboptimal.

The authors start by discussing the partial matrix analyses, although none of these analyses are visually/graphically depicted in the main text figures, and although their results do not seem to be of real importance for the narrative of the discussion. The other two PCA analyses actually are presented afterwards and separately, but they convey some common signals, particularly that the major source of variation seems to be a decreasing olfactory angle with increasing olfactory length, and a scaling relationship between all linear measurements (which all have the same eigenvector signs on the first PC axis). I wonder if an alternative way of presenting the PCA results would be better for this particular MS. For example, the authors could give "first level observations" first ("PCA analyses agree in X,Y,Y"), and then move to second order observations ("Morphospace of BPCA has some interesting taxon distribution with regard to chirodipterids"; "InDaPCA axis projections continuously retrieve clustering of specific variables"). I suspect this would shorten the text somewhat and could serve as a clearer articulation of the take home messages?

2. Selection of PC axes for interpretation

You describe how you use the broken-stick method to decide how many PC axes are retained for the interpretation of results, which I agree is a good procedure. However, I have a few questions regarding this.

First, in line 331 (description of InDaPCA) you state that the first three axes are non-trivial "based on the screeplot" - which got me confused because it sounds a bit like eyeballing off the screeplot. Have you used the broken stick method for all your PCA analyses?

The second question relates to the results of the broken stick method, which I did not find reported. Unless I am mistaken, for the xth axis, the method sums the fractions of 1/i (whereby i = x..n; n = number of axes), and divides this number by n to get a value of expected variation per axis. This number is then compared with the actual value of variance explained by the axis. So for the 1st of 17 axes, the broken-stick expectation is = (1 + 1/2 + .. + 1/17) / 17. If you apply this to your BPCA, the third axis' value (i.e., (1/3 + ... + 1/17)/17) is 0.114, which is smaller than the reported 0.120 that PC3 explains. Thus, following the broken stick method, PC3 does explain more variation that expected (and should thus be retained, contra your comment in line 311 which refers to two non-trivial axes)? Related to this potential issue is the presentation of the BPCA results in Fig. 2: You present loadings of three PC axes, although only the first two are considered in morphospace bi-plots and although the text also mentions only two non-trival axes. If the third axis is indeed non-trivial, then the loading-presentation could be retained in the figure, but then the authors should consider showing a PC1 vs. PC3 plot in addition to the currently presented biplot showing the first and second axis only. If the third axis indeed is trivial, as currently suggested by the text, then showing the loadings is unnecessary.

It would be great if you clarify the usage/application of the broken stick method for all your PCAs. An easy way to report the results may be the add a row to each of your PCA loading tables in the supplements, in which you divide the actual value of variation explained by the value expected under the broken stick method - this way, all axes which explain more variation than expected by the stick method have values larger than 1, and axes which explain less have values lower than 1.

3. Missing commentary on allometry

In basically all PCA analyses, the first PC axis seems to be dominated by allometric size effects, given that all linear measurements have the same eigenvalue signs. The authors do acknowledge this (lines 314-316; 335-336), but offer no further comment on size effects/allometry. For example, it would be interesting to see how the linear measurements scale with overall head size. Similarly, the authors note that the semicircular canal measurements covary strongly, as do the utricle and saccule height/length measurements (paragraph line 346). Basically, it seems that the semicircular canal measurements scale with one another: as one gets bigger, so gets the other. It is interesting that the utricle does not seem to follow the same scaling pattern as the saccule and semicircular canals, and it would be good to hear if the authors think that there is a functional implication for this. Increases in utricular/saccular/semicircular canal sizes are usually explained by increased sensitivity - so is an increased utricular size a compensatory development to decreased semicircular canal+saccule size to retain an overall level of sensitivity, or does it maybe related to a relative change of importance of the specific functions, e.g. increased importance of linear accelerations in the horizontal plane with simultaneous decrease of importance of angular and vertical accelerations?

4. Labyrinth size

With the above mentioned utricular exception, labyrinth size measurements particularly on the semicircular canals seem to imply that there is a relative consistent scaling relationship between the canals. When one canal gets larger, so do the others, perhaps thereby retaining canal symmetry across different absolute labyrinth sizes. Labyrinth size in tetrapods is often interpreted in relation to body size/mass or head size (e.g. Melville Jones & Spells 1963, Proc. R. Soc. Lond. Biol. Sci.; Spoor & Zonneveldt 1998, Yearb. Phys. Anthr.; Spoor et al. 2002, Nature; Spoor et al. 2007, PNAS; Bronzati et al. 2021, Curr. Biol.), as deviations from the expected labyrinth size per head size indicate increased or decreased relative labyrinth sensitivities. Large relative head sizes of birds and (within) mammals have generally been interpreted as indicative of "active" or "agile" behaviour, although doubt has been casted on these relationships recently (e.g., Bronzati et al. 2021). Increased sampling of relative labyrinth size from various vertebrate groups would be important to better understand labyrinth size-function relationships. Melville Jones & Spells (1963) have shown that fishes have large labyrinth sizes compared to most tetrapods, but they don't have lungfish data and the large labyrinth sizes of fishes have often remained uncommented on in tetrapod works. I think this study offers a fantastic opportunity to provide comparative labyrinth size data for lungfishes. In this regard, it would be really interesting to quantify labyrinth size relative to head size, and show a respective (phylogenetic) regression analysis. Ideally, the size of the labyrinth could be quantified along the arc lengths of the semicircular canals, but other ways are also thinkable (for example a box volume of labyrinth size by the existing measurements, contrasted with a box volume of the skull, i.e. height*width*length).

Reviewer #2 (Public Review):

In this manuscript, Villalta, Schmitt, Estrozi and colleagues report their results on genome compaction in one of the most complex known viruses, the Mimivirus. This work will be of interest to a broad readership, and particularly to virologists and structural biologists. The authors describe a novel mechanism used by mimivirus to compact and package its 1.2 Mb dsDNA genome. In particular, the mimivirus genome is shown to be packed into magnificent cylinder-like assemblies composed of GMC-type oxidoreductases, presenting yet another remarkable case of enzyme exaptation. By using cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), the authors determined the structures of such fibers in several relaxation states, which presumably represent different stages of nucleoprotein unpacking upon delivery into host cytoplasm. The authors also suggest (although do not directly visualize) that the lumen of the genomic fibers contains several viral enzymes, most notably, DNA-dependent RNA polymerase, which is necessary for cytoplasmic replication of the mimivirus. Overall, this is an important discovery, which further expands our appreciation of the "inventiveness" of viruses.

I am not an expert on helical reconstructions and cannot evaluate the validity of the models. Thus, my specific comments will focus on aspects of the work with which I am more familiar.

1. In light of the presented results, it is reasonable to assume that GMC-type oxidoreductases of the mimivirus are very important for the formation of functional virions. However, in a previous study (PMID: 21646533), it has been shown that the genes encoding GMC-type oxidoreductases can be deleted from the virus genome (M4 mutant) without the loss of infectivity. The M4 virions were devoid of the external fibers decorating the icosahedral capsid, but the genome was still packaged. How do the authors reconcile these results with those presented in the present manuscript? This should be addressed in the Discussion section.

2. The authors state that mimivirus encodes two GMC-type oxidoreductases (qu_946 and qu_143) and that both could be fitted into the electron densities. However, I could not understand whether the authors think that the fibers are heteroassemblies of both oxidoreductases or different fibers are composed of different proteins, or only one is used for fiber formation. Please clarify. In case you are not able to distinguish between the two homologs (e.g., due to limited resolution), state so explicitly.

3. I am slightly puzzled by the observed "ball of yarn". It is hard for me to imagine that a cylindrical container/fiber containing a continuous dsDNA genome could be bent or fragmented into bundles because this would break the protein-protein interactions holding the fiber together. In Figures 1C and S1, are these parts of the same fiber or multiple fibers coming out of one capsid? Related to this question - is there evidence (e.g., from qPCR) that Mimivirus carries a single copy of genomic dsDNA per capsid?

4. The authors describe the interactions between the monomers in the dimer of qu_946 as well as between qu_946 and DNA. I would also like to see a brief description of protein-protein interactions between subunits within the same helical strand as well as between helical strands, which hold the whole assembly together (i.e., what are the contacts between green subunits as well as between green and yellow subunits shown in Fig 2C). The authors suggest that the shell "would guide the folding of the dsDNA strands into the structure" (L310). To support this statement, the authors could show the lumen of the fiber rendered by electrostatic potential.

5. Please provide some background information on the distribution of GMC-type oxidoreductases in other families of giant viruses, so that it is clearer whether the described packaging mechanism is specific to mimiviruses or is more widespread.

Reviewer #2 (Public Review):

Schor et al. investigated three theories underlying the mechanism of electrical DBS by studying whether therapeutic DBS inhibits STN or SNr activity, antidromically activates the hyperdirect M1 neurons, or disrupts the movement-related neural activity in the STN. Contrary to the former two theories, they found that therapeutic electrical STN DBS excites STN and SNr neurons as shown by their average GCaMP calcium signals, and the activation of M1 hyperdirect neurons is not required for the behavioral rescue in parkinsonian mice as demonstrated by the continued improvements with removal of M1. They show evidence in support of the 3rd theory that the primary effector of STN DBS is the alteration of the pattern and not the rate of activity in the STN. They show that the attenuation of the neural activity in the STN around movement onset is not only correlated with the best behavioral responses, but that mimicking this activity using optical stimulation is sufficient to improve movement, providing a causal link between STN dynamics and DBS-induced therapeutic benefit.

Strengths:<br /> • By using calcium-imaging instead of in vivo electrophysiology, the authors are able to identify the acute effects of DBS on the neural dynamics of adjacent structures without having to worry about electrical artifacts. This method provides a technical advancement to the field of pre-clinical DBS studies.<br /> • Additionally, they provide a rigorous and robust correlation between the STN calcium signals and electrophysiology using both in vivo and ex vivo simultaneous recordings. The correlations in the photometry-based average and single-unit firing activity of basal ganglia nuclei shown for both short and long-time scale interventions like DBS and L-DOPA provide some foundation for the interpretation of the effects of DBS on neural dynamics across experiments.<br /> • The peak-trough distance in Fig. 6 highlighting the effect of therapeutic STN DBS on the fiber photometry signal, a proxy for the movement-related activity in the STN was an effective and impactful result demonstrating the primary therapeutic mechanism of STN DBS.<br /> • The discussion addresses key issues of alternate explanations generated by their data as well as caveats of their methods. Specifically, the acknowledgement that the STN and SNr signals could be a cause, or an effect of the movement changes seems like an important acknowledgement for future studies. Additionally, the clarification of basal-ganglia cell-types and limitations with respect to temporal resolution demonstrates an acknowledgement of the complexity of this circuit.

Minor weaknesses:<br /> The conclusions of this paper are mostly well supported by data, but some more controls to validate the photometry method, as well as establish baseline firing characteristics could be performed:<br /> Calcium-imaging controls:<br /> • The loss of correspondence between spiking and calcium at highest stimulation frequencies produces concern regarding the interpretation of the calcium signals with the "high effect stim" which includes multiple stim protocols with frequency > 100Hz. Added controls with higher frequency stimulation could improve interpretability of the GCaMP signals for DBS at higher frequencies (Fig 1A)<br /> • In addition to establishing baseline firing dynamics in the STN in parkinsonian mice, identification of the movement-related calcium activity in a healthy control mouse would establish whether therapeutic DBS shifts the activity in the direction of healthy STN firing activity (Fig. 1B). This could enhance the relevance of the finding that the movement-related neural dynamics in the STN are abolished with DBS.<br /> Variability in firing between STN and other sites:<br /> • Comparison from WT mice with synapsin-GCaMP in the SNr vs. Cre-dependent GCaMP was unclear<br /> • Validation of correspondence between calcium imaging and in vivo firing activity only performed in the STN. Similar control experiments in the SNr could be valuable since it has a different baseline firing rate.<br /> Evidence against theory suggesting STN inhibition as a mechanism of DBS:<br /> • To further establish that the inhibition of STN activity was not correlated with the behavioral improvement, a correlation between the movement velocity and the change in STN activity could be shown like shown for the M1 analysis (SFig. 5E).<br /> • Interpretation of Fig 7G and K suggesting that the attenuation of movement-related dynamics with the 50 Hz protocol is causal to the velocity increase is confounded by the inhibition of the firing rate (Fig. 7E).<br /> Optical Stimulation Setup:<br /> • The discrepancy between the in vivo and ex vivo firing rate response to 50 Hz optical stimulation could be further explained or experimentally explored in order to make the findings consistent with previously used in vivo validation (Fig 1). Using different frequencies of optical stimulation could identify whether there was frequency-dependence to the effect.

Reviewer #2 (Public Review):

McGregor et al. establish a new reinforcement learning paradigm for songbirds, where instead of auditory feedback (white noise) they use mild cutaneous electrical stimulation as a reinforcer. Their data shows that this somatosensory stimulus can aversively drive pitch changes of a targeted syllable in similar manners as an auditory stimulus does. They further show that the anterior forebrain pathway (AFP) and dopaminergic projections to the AFP are necessary for this non-auditory vocal learning by electrolytically lesioning the output nucleus of the AFP and by depleting dopaminergic input to Area X. Their analysis is rigorous and their data convincingly show shared mechanisms for vocal reinforcement learning using white noise (auditory) or cutaneous electrical stimulation (non-auditory).

However, both the ability of birds to learn from non-auditory stimuli and the involvement of the AFP in this process have been shown previously in Zai et al. 2020, where it is shown that visual stimuli (short periods of light off) can successfully drive changes in pitch both in hearing and in deaf birds; furthermore, in deaf birds, the involvement of the AFP in this process has been shown using a similar lesioning approach. Thus, two out of the three main claims of novelty in the manuscript are not novel in fact. The main novelty beyond the 2020 study is that McGregor et al. are the first to show that somatosensory information (cutaneous electrical stimulation) can induce vocal plasticity and that dopaminergic projections to the AFP are somehow involved in this process.

With the interpretation of the dopamine experiments there is an issue. Authors claim that dopaminergic input is necessary for observing adaptive changes, but their data suggests otherwise, namely that dopamine sets the direction of the change. Strictly speaking, the statement 'dopaminergic inputs are required for non-auditory vocal learning' is incorrect, since the data shows reversal in learning direction, which is a form of learning as well. Therefore, the apparent reversal in learning under lack of dopamine should be discussed.

The authors also claim that there is no systematic difference between learning magnitudes of cutaneous stimulation and of auditory white noise stimulation, suggesting that both training methods result in the same learning efficacy. While their data indeed shows no significant difference between these training methods, there is little ground for this claim. First, learning magnitudes seem to vary a lot across individuals, they may be similar on average but there does not seem to be a correlation between the two. Second, similar learning magnitudes only show that the saliency of the two stimuli were adjusted to be roughly equal, which is not surprising given that they adjusted the magnitude of electric current using a similar criterion as in their initial 2007 paper: In (Tumer and Brainard 2007) they adjusted white noise amplitude until they observed stoppages during the first day of exposure, and in this manuscript they adjusted electric current to interrupt song on the first few instances of cutaneous stimulation.<br /> They further state in their methods that the magnitude of the electric current was "typically" set in the range 100-350 μA, which is large and which most likely influences the saliency of the reinforcing stimulus. Most importantly, the influence of the electric current magnitude is neither discussed nor analyzed in the manuscript. Presumably, a strong electric current is very effective and a weak auditory stimulus is very ineffective.

Statistics: Their statistical tests are in general solid and support the claims of the paper. Authors show using a hierarchical bootstrap approach that cutaneous stimulation can drive adult songbird vocal learning on a population level. However, there are a few instances where more data would help to better evaluate the significance of the results. For example, only one of the three days of baseline song is shown and for only one example bird, and worst of all, the data is reduplicated in this bird on two days, which points to a serious flaw in either the analysis or the illustration. Authors should show more baseline days and include more birds.

The 2-sided KS test to assess the difference between baseline and end of cutaneous stimulation is extremely significant (10^-12) for that one example bird, which is nice, but it would be useful to see whether this is the case for all birds and not just that example bird on that example day. Also, it would be interesting to see how these statistics behave when comparing two or more baseline days. It is unlikely that the washout the KS analysis reveals in this one bird will apply in all birds.

Then, for the analysis only data between 10 am and 12 pm are used (to account for potential circadian effects) but then this window is extended if birds sing less than 30 renditions of the target syllable during this time window. It is unclear from their description how often this is the case and how it influences their analysis. Furthermore, they exclude birds that dropped their singing rate below 10 songs per day for more than a day, again not stating how many birds were excluded based on this criterion.

Reviewer #2 (Public Review):

This paper describes the analysis of a large data set collected from growth experiments on one strain of E. coli. The experimenters varied the growth media and used machine learning to try to deconstruct what was going on biologically. I have two major concerns with the methodology.

1. The results of growth experiments are often severely affected by whether or not the strain has had time to adapt to the growth conditions tested. There is no time allowed for the different cultures to become adapted to these different growth media.

2. All of these results are based on the concentration of chemical substances at t=0. As a culture grows it uses chemicals and releases other chemicals. That means the concentration of the different chemicals is changing as well as the ratio of different chemicals.

Because of this, I have serious doubts about the specific biological claims.

The concept of making ML methods less opaque and using them to tease apart specific biological processes is intriguing. This is also a very interesting and large data set that would be useful to others for developing algorithms. Readers who are interested in ML applications in biology would be interested in this paper.

Reviewer #2 (Public Review): 

Insights into the neurochemical mechanisms underlying the trade-off between model-based and model-free behavior may lead to a deeper understanding of the decision-making deficits in several clinical disorders. The current findings show that pharmacologically blocking dopaminergic neurotransmission strengthens model-based over model-free behavior, whereas reduced opioidergic activity showed no significant effects. The current investigation has several strengths: It uses an established task and a sophisticated computational model to quantify the balance between the model-based and the model-free system. The main weakness is that the interpretation of the data is hampered by the fact that the administered dose of amisulpride can lead to both presynaptic and postsynaptic effects.

Reviewer #2 (Public Review):

In this work the authors sought to explore the relationship between changes in regional cerebral blood flow (rCBF) and functional connectivity (FC) in human infants across the first 24 months after birth. Understanding this is important, as it is increasingly appreciated that the brain's lifelong framework of functional connections is established across this period, with alterations seemingly associated with the development of conditions such as autism later in life. They show a relationship between developmental increases in rCBF with maturational changes in FC specific to the default mode network (DMN), a functional network which is known to rapidly mature during this period. Interestingly, this relationship was not significant when studying the primary visual and sensorimotor networks which are thought to be already mature at birth.

The combination of measuring both rCBF and FC with pCASL and BOLD fMRI in this population is relatively novel, and would certainly have been challenging data to acquire which is a clear strength. That they validate the assumed (but largely not proven) link between rCBF and FC during development will be of use to the field, although this result is perhaps not surprising and given the cross sectional nature of the data, unfortunately, does not really provide further mechanistic insight into the relationship. The authors' suggestion that the results for example can tell us about brain metabolism is rather speculative and is not supported by the data (as they have no additional measure of oxygen extraction or glucose metabolism).

Due to the difficulties with infant cooperation (and movement), it is extremely rare to be able to measure rCBF in this population, so the results will be of interest in this context, particularly as they demonstrate that regional differences, with the strongest correlation with age appearing to be frontally and across the midline. Providing the CBF data and trajectories will be of great use to the field where it can be compared to other maturational brain changes identified in large studies such as the HBCD cohort. However, there is some caution about these results, as these were all infants who had imaging performed for clinical reasons (albeit with normal neurology) who received sedation for the scan. Furthermore, given the rapid development across this period (which is, of course, the major focus of the work), a further potential drawback is that the same acquisition sequence was used across all of the infants. This likely has implications, particularly for the rCBF estimation - as key factors such as partial voluming effects, the T1 of arterial blood, and arterial transit time are all rapidly developing across this time.

The FC analysis methods are largely appropriate and are in line with the broader literature which shows established connectivity in primary networks, but the apparent establishment of long distance organisation within the DMN (which is neatly shown in figure 3). The authors show that in a number of different ways, the identified relationships between rCBF and FC are network specific, which strengthens their conclusions that the two are linked in the developing brain. However, interpretation is somewhat limited by their approach of only considering three networks which have been empirically derived from the older infants.

Reviewer #2 (Public Review):

In this manuscript, Martin and colleagues use the zebrafish embryo model to evaluate how the transcription factor Nr2f1a regulates early heart development. Previous work by the authors' lab and others has shown that NR2F homologues in mice and zebrafish play important roles in maintaining an atrial cardiomyocyte identity and repressing ventricular fate. Mutation of NR2F2 in humans is associated with congenital heart disease, further underscoring the importance of this family of genes in heart development. Here the authors show via further analysis of a zebrafish nr2f1a mutant that two events are occurring in the atria: 1) and expansion of ventricular cardiomyocyte gene expression in the region of the atrioventricular canal; and 2) and expansion in cells with a pacemaker cardiomyocyte character at the venous pole of the heart. This second point is in particular a novel observation and the focus of this manuscript.

Following transcriptome analysis that shows changes in gene expression associated with atrial, ventricular, and pacemaker cardiomyocytes in mutant nrf21a atria, detailed counts of cardiomyocytes coupled with analysis of markers of cardiomyocyte fates are used to show that changes in atrial cardiomyocyte cell state occur over 48 to 96 hours post-fertilization in nr2f1a mutants. Electrophysiological analysis of mutant hearts supports a model where pacemaker cardiomyocyte fate is expanded at the venous pole of mutant hearts, whereas cells at the atrioventricular canal behave more like ventricular cardiomyocytes. Mechanistically, it is shown that Nr2f1a may act to maintain the expression of nkx2.5 in atrial cardiomyocytes bordering pacemaker cells at the venous pole, consistent with the known role of Nkx2.5 in repressing pacemaker identity. This is supported by experiments showing that transgenic overexpression of nkx2.5 can rescue some aspects of atrial/pacemaker cell identity defects in nr2f1a mutants.

Quite a bit is known with respect to NR2F1/2 in mammalian heart development, including the promotion and maintenance of atrial at the expense of ventricular cell identity. Dr. Waxman's group has also previously shown in zebrafish that Nr2f1a similarly promotes atrial identity. What is new here is a role for Nr2f1a in preventing an atrial to pacemaker fate switch at the venous pole of the heart via maintaining nkx2.5 expression. The question of how different regions (AVC vs venous pole) of the heart may respond differently to the same transcription factor (Nr2f1a in this case) is a truly interesting one, and the regionalized regulation of nkx2.5 by Nr2f1a shown in this work certainly provides another piece for this puzzle.

Strengths:<br /> This work includes a comprehensive quantification of cell numbers along with multiple markers to describe the dynamics in changes of cell state in the developing atrium of nr2f1a mutants. This is coupled with detailed electrophysiological analyses that support the overall conclusion that an atrial to pacemaker CM cell state change is occurring in nr2f1a mutants. The analysis of a putative Nr2f1a-regulated nkx2.5 enhancer and the demonstration of the rescue of some aspects of pacemaker expansion in nr2f1a mutants by restoration of nkx2.5 expression present a compelling potential mechanism for Nr2f1a activity.

Weaknesses:<br /> In some cases, there is a reliance on a few markers (the fgf13a:GFP transgene, in particular) to ascribe cell lineage/state. An examination of if nkx2.5 expression can rescue cardiac function and electrophysiology is not shown but would have been a great addition to this work.

Reviewer #2 (Public Review):

The study of Hu et al. aims to decipher early immune signatures of severe forms of COVID-19. Using data collected early in the infection in outpatients, the authors identify a set of plasma proteins that can predict a number of outcomes, including disease progression, control of viral shedding and onset of antibodies.<br /> The study is interesting but I have a number of questions on the methodology and the implications of this work. I would really encourage the authors to clarify the methods so that other groups can build on it. As such a number of details need to be clarified to ensure full reproducibility.

1. The authors take for granted that the administration of Peg-IFN lambda does not modify the course of the disease and therefore that treated and untreated individuals can be analyzed together. This is at odds with other randomized studies, that have shown antiviral and clinical effect of IFN-based therapy. In particular Peg-lambda accelerated viral decline in outpatients and prevented clinical deterioration in a study performed in a similar setting using the same dose than here (Feld et al., Lancet Resp Med 2021). Other positive results in early patients were found with IFN-beta (Monk et al, Lancet Resp Med 2020).<br /> 2. Even if the administration of IFN in this study had no clinical or virological benefits, it could nonetheless alter the kinetics of ISG. The authors claim it is not the case, but it is difficult to assess it based on the figures shown, using PCA.<br /> 3. I really doubt that any strong claim can be made on disease progression since only 8 patients were hospitalized in this study. In addition, it should be clarified when these patients progressed. Page 10, it is said that the median time to progression is 2 days, so in fact the data collected at day 0 and 5 are very close, or even perhaps posterior to hospitalization in some cases, making it difficult to claim that it can be used for prediction. More generally data used are up to 14 days post symptom onset, while the median time to hospitalization in these populations is roughly ~8 days. This makes it here as well difficult to really argue that the model has a "predictive" value to anticipate disease progression.<br /> 4. If data used in the study are close to hospitalization, then this really diminishes the novelty of the findings, as many studies have already reported an association between these markers and disease severity (see also Young et al, Viral Dynamics and Immune Correlates of Coronavirus Disease 2019 (COVID-19) Severity, CID 2021).<br /> 5. The definition of disease progression seems to differ from the original study "Overall, 17 participants had evidence of disease progression, defined as hospitalization, presentation to the emergency department, or worsening cough or shortness of breath defined as an increase in severity of two points or more on a five-point scale"? Please clarify what is your endpoint and why, if relevant, it differs from the original study.<br /> 6. Can you clarify how viral shedding was analyzed? I am puzzled by the fact that viral load is analyzed with a different metrics than other proteins when looking at predictors of disease progression? I am also not convinced by Fig S5 which relies on AUC of viral load calculated in patients with high heterogeneity in their symptom onset. Please use the same approach for viral load than what was used for IP-10 in order to demonstrate that IP-10 is a better predictor of disease progression than viral load.<br /> 7. Regarding prediction, it is really unclear how the model using demographics was built. It is obvious than many other factors than age and sex are highly predictive of disease progression.<br /> 8. If you want these results to be useful for the clinical community then the model used in figure 7 should be explicitly given so that any one can use these results to build score on its own population.

Reviewer #2 (Public Review):

This work reports several interesting and novel results that tie RyR2 dispersion during prolonged β-Adrenergic stimulation with isoproterenol to receptor phosphorylation by CaMKII and PKA. The potential clinical relevance is highlighted with the comparison and correlation to the RyR2 dispersion that occurs during HF, building and substantially expanding upon previous work by this group. Indeed, this group has recognized strengths in nanoscale analyses of RyR2 and here uses their own impressive 3D correlative reconstruction approach to provide a striking visual demonstration of the distribution of RyR2 in relation to the nearby t-tubule membrane. The group implements a broad array of techniques to investigate the functional implications of the RyR2 dispersion that they elegantly demonstrate with super-resolution microscopy, including in-depth analyses of Ca2+ spark and transient dimensions, and kinetics. The imaging techniques are well-executed and beautifully presented and support the novel conclusion that prolonged ISO stimulation leads to RyR2 dispersion. It also raises interesting discussion points that will stimulate future studies including evoking Vatner and Lederer's idea that non-uniform SR Ca2+ depletion may create "fire-breaks" that prevent Ca2+ wave propagation. Altogether, this is an exciting and timely study and will have an impact in the field that is currently only beginning to understand and explore the functional implications of nanoscale changes in RyR2 and other EC-coupling proteins.

The conclusions are mostly well supported by data, but a few aspects of image acquisition and data analysis need to be clarified and extended.

- A critical control is missing to demonstrate the effects of 2 hrs ISO treatment on RyR2 arrangements. This will strengthen the conclusions from the CaMKII and PKA inhibitor RYR2 dispersion reversal experiments which utilize a protocol that includes a 1 hr ISO stimulation followed by a 1Hr ISO + inhibitor treatment.

- The mathematical modeling results would also benefit from more explanation of how they complement, align, and expand on the experimental studies.

Reviewer #2 (Public Review):

In this MEG work employing two types of bistable perception test and unique regression analyses, the authors identified different neural frequencies to different components of visual perception: its content and stability.

Strengths:

This study has a nice set of three different experiments to clarify neural differences between content, memory and stability of visual perception.

The state space analysis appears to be powerful to identify such different neural signatures for different cognitive components as well.

Weaknesses:

Despite such strengths, this work may have the somewhat critical weakness specified in the recommendations for the authors.

First, in the analysis to identify content-specific neural frequency, the authors concluded that the SCP is more relevant to the visual perceptual content compared to the neural activity in the alpha and beta-band frequencies. In my impression, to claim this, it would be necessary to show statistically significant differences in the prediction accuracy between the SCP and the other frequencies. Given the not-so-high prediction accuracy seen in the SCP-based analysis, such statistical supports appear essential.

Second, two behavioural metrics in the neural state space analysis-i.e., Switch and Direction-may be too arbitrary. As suggested by the power-law distribution of the percept duration, the neural dynamics during seemingly stable percept may not be able to be described in linear functions. Instead, the brain may go back and forth between several neural states even when we are thinking we're experiencing stable visual consciousness. If so, the current definition of the Switch metric and Direction index, which seems to be based on the behaviour of the Switch index, may be arbitrary. In other words, I feel the authors may have to elaborate the rationale for the definitions of such metrics.

Reviewer #2 (Public Review):

In this manuscript titled "Here's the twist: How the brain updates the representations of naturalistic events as our understanding of the past changes", the authors reported a study that examined how new information (manipulated as a twist at the end of a movie) changes the neural representations in the default mode network (DMN) during the recall of prior knowledge. Three groups of participants were compared - one group experienced the twist at the end, one group never experienced the twist, and one group received a spoiler at the beginning. At retrieval, participants received snippets of 18 scenes of the movie as cues and were asked to freely describe the events of each scene and to provide the most accurate interpretation of the scene, given the information they gathered throughout watching.

All three groups were highly accurate in the recall of content. The groups that experienced the twist at the end as well as at the beginning as a spoiler showed a higher twist score (the extent to which twist information was incorporated into the recall), while seemingly also keeping the interpretation without the twist ("Doctor representation") intact. Neurally, several regions in the DMN showed significant interaction effects in their neural similarity patterns (based on intersubject pattern correlation), indicating a change in interpretation between encoding and recall in the twist group uniquely, presumably reflecting memory updating.

Several points that I think should be addressed to strengthen the manuscript:

1) The results from encoding-retrieval similarity analysis (particularly the one depicted in Figure 3B) don't match the results from encoding/retrieval interaction (particularly those shown in Figure 2C). While they were certainly based on different comparisons, I would think that both analyses were set up to test for memory updating. Can the authors comment on this divergence in results?

2) The recall task was self-paced. Can reaction time information be provided on how long participants needed to recall? Did this differ across groups? Presumably in the twist group and spoiled group participants might have needed a longer time to incorporate both the original and twist interpretation. How was the length difference across events taken into consideration in the beta estimates? Also, is there an order effect, such that one type of interpretation tended to be recalled first?

3) The correlation analysis between neural pattern change and behavioral twist score is based on a small sample size and does not seem to be well suited to test the postulation of the authors, namely that some participants may hold both interpretations in their memory. Interestingly, the twist score of the spoiled group was similar to the twist group, indicating participants in this group might have held both interpretations as well. Could this observation be leveraged, for example by combining both groups (hence better powered with larger sample size), in order to relate individual differences in neural similarity patterns and behavioral tendency to hold both interpretations?

4) Several regions within the DMN were significant across the analysis steps, specifically the angular gyrus, middle temporal cortex, and medial PFC. Can the authors provide more insights on how these widely distributed regions may act together to enable memory updating? The discussion on the main findings is largely at a rather superficial level about DMN, or focuses specifically on vmPFC, but neglects the distributed regions that presumably function interactively.

Reviewer #2 (Public Review):

This manuscript addresses the link between the developmental change (increase) of excitatory-inhibitory (E/I) balance and the observed decorrelation of neural activity, measured by the decrease in spiking correlations between pairs of neurons). The authors perform in vivo electrophysiological recordings in the prefrontal cortex of mice and combine them with modeling, optogenetic experiments that target a specific neuronal population of interneurons to justify their claims and even consider a mouse disease model and human data from babies to ensure that their results go beyond the development of mice.

Strengths:<br /> What is remarkable about this study is that it generates and explores data from multiple developmental ages providing a continuous glance into the developmental trajectory of the prefrontal cortex. The authors consider the ages of P2-12 and investigate the properties of spontaneous activity of over 100 mice, including the evolution of activity from being discrete and very infrequent to completely continuous, as in adulthood. The model is a great addition to the paper and is used very well in testing new hypothesis that are then explored back in the data. The authors also nicely use a measure for correlations, the spike time tiling coefficient, that was explicitly proposed for developmental data that has wildly varying firing rates. With this measure, they demonstrate that correlations decrease as a function of age, suggesting activity decorrelation. With the use of optogenetics they can increase the activity of interneurons and demonstrate one of the long-standing questions in the field about whether GABA is excitatory or inhibitory early in development. Similarly, optogenetic inactivation of interneurons increased overall levels of activity in the network. These optogenetic manipulations are then nicely linked to the change in spiking pairwise correlations. The authors also provide an interesting connection to a disease mouse model (GE) which have an altered E/I ratio and consequently different activity decorrelation compared to wildtype.

Weaknesses:<br /> While the paper explores large data sets from many points of view, it can do a better job of connecting the observed activity patterns to existing literature on spontaneous activity (work of M. Colonese, C. Lohmann, R. Khazipov, N. Rochefort & A. Konnerth). There are some references in the introduction but they should be expanded to put the paper in a broader context.<br /> Though the model is very useful, it is not clear what assumptions went into it and why. For example, why lognormal synaptic connection strengths, what happens if this assumption is relaxed?<br /> The effects on the firing rates in the population are not very clear upon optogenetic manipulation. The authors hint at the "paradoxical effect" in their Discussion, but a more extensive discussion of this would be good, also possibly in the results, to properly be able to interpret the observed results.<br /> The authors present the decorrelation of neural activity as the ultimate goal of the cortical network, but why it's not clear why that is so. In the abstract it is mentioned "for the efficient retrieval and processing of information" but this is very loose and imprecise. How does this link (does it?) to the emergence of sensory processing and the transition to sensory driven activity?

Reviewer #2 (Public Review):

Jangir and Yang, et al.'s manuscript presents highly interesting datasets aiming to shed light on the role of standing genetic diversity in the evolution of antibiotic resistance via epistatic interactions between chromosomal and plasmid genes. It combines a set of elegant evolution and downstream experiments with genomics and epidemiological genomic data with datasets from China and the UK. The authors focus on colistin resistance mediated by the MCR-1 colistin resistance gene, and its ability to increase E. coli's capacity to evolve higher levels of colistin resistance by adding mutations in lpxC.

The data presented is interesting and well presented. It also adds to the question of how beneficial foreign material interacts with the bacterial chromosome and how it can be sustained. The results presented here are interesting and important to expand our understanding of antibiotic resistance evolution, but I do have some concerns about the data and the way it is presented.

Reviewer #2 (Public Review):

Influenza A viruses evolve rapidly in US swine, generating novel reassortants that also occasionally infect humans (e.g., H3N2v). The virus is not well controlled in US swine herds, because of the difficulty of designing vaccines that protect against the full diversity of strains. This group and others have done prior work examining different prime-boost strategies to improve the effectiveness of swine influenza vaccines. Here, the authors extend that work by examining the potential for vaccination to blunt the evolution of the virus. Seeder pigs experimentally infected with H1N1 or H3N2 influenza A viruses were co-housed with vaccinated and unvaccinated pigs. The study finds that H1N1 and H3N2 viruses readily coinfect pigs, generating a large number of reassortants over a relatively short time period, and possibly fewer reassortants in animals administered the prime-boost regimen.

Reviewer #2 (Public Review):

This systematic review and meta-analysis titled 'The effect of calcium supplementation in people under 35 years old: A systematic review and meta-analysis of randomized controlled trials' provide good evidence for the importance of calcium supplementation at the age around the plateau of PBM. The statistical analyses were good overall and the manuscript was generally well written.

One concern in this study is that RCTs included were substantially heterogenous in subjects, calcium types, duration, vitamin D supplements, etc. According to the inclusion criteria, RCTs with calcium or calcium plus vitamin D supplements with a placebo or no treatment were included in this study. However, no information about vitamin D supplementation was provided. Therefore, it seems unclear whether the effect of improving BMD or BMC is due to calcium alone or calcium plus vitamin D.

Reviewer #2 (Public Review):

The authors present a novel dotplot-based approach to identify Low-complexity regions (LCRs) and dimensionality reduction techniques coupled with image processing methods to define the presence and organization of LCR regions. The dot-plot based method is unique in that it not only identifies different LCRs in a protein but could also define the relatedness between the different LCRs. Using UMAPs, they present a unified view of LCR sequence space in humans and predict the LCR space for different higher order assemblies. Using experimental studies they show how valency of LCRs could influence phase-separation behavior of such proteins. An expanded LCR sequence space map is used to capture the conservation and divergence of higher order assemblies LCR sequences across species. Finally, the authors showcase the efficacy of the approach by identifying a thus far unannotated T/H rich LCR cluster in Teleosts.

The method is robust. However, clarity is required regarding the FDR thresholding for identifying LCRs and assigning preponderant amino acids in the unified LCR sequence space. The findings regarding the sequence space across different higher order assemblies is commendable.

The approach and insights presented here could help all researchers working towards establishing protein sequence-function relationships and how variation in LCRs could affect fitness.

Reviewer #2 (Public Review):

Jia et al. present a CNN based tool named "Selfee" for unsupervised quantification of animal behavior that could be used for objectively analyzing animal behavior recorded in relatively simple setups commonly used by various neurobiology/ethology laboratories. This work is very relevant but has some serious unresolved issues for establishing credibility of the method.

Overall Strengths: Jia et al have leveraged a recent development "Simple Siamese CNNs" to work for behavioral segmentation. This is a terrific effort and theoretically very attractive.

Overall Weakness: Unfortunately, the data supporting the method is not as promising. It is also riddled with incomplete information and lack of rationale behind the experiments.

Specific points of concern:

1) No formal comparison with pre-existing methods like JAABA which would work on similar videos as Selfee.<br /> 2) For all Drosophila behavior experiments, I'm concerned about the control and test genetic background. Several studies have reported that social behaviors like courtship and aggression are highly visual and sensitive to genetic background and presence of "white" gene. The authors use Canton S (CS) flies as control data. Whereas it is unclear if any or all of the test genotypes have been crossed into this background. It would be helpful if authors provide genotype information for test flies.<br /> 3) Utility of "anomaly score" rests on Fig 3 data. Authors write they screened "neurotransmitter-related mutants or neuron silenced lines" (lines 251-252). Yet Figure 3B lacks some of the most commonly occurring neurotransmitter mutants/neuron labeling lines (e.g. Acetelcholine, GABA, Dopamaine, instead there are some neurotransmitter receptor lines, but then again prominent ones are missing). This reduces the credibility of this data.<br /> 4) The utility of AR-HMM following "Selfee" analysis rests on the IR76b mutant experiment (Fig4). This is the most perplexing experiment! There are so many receptors implicated in courtship and IR76b is definitely not among the most well-known. None of the citations for IR76b in this manuscript have anything to do with detection of female pheromones. IR76b is implicated in salt and amino acid sensation. The authors still call this "an extensively studies (co)receptor that is known to detect female pheromones" (lines310-311). Unsurprisingly the AR-HMM analysis doesn't find any difference in modules related to courtship. Unless I'm mistaken the premise for this experiment is wrong and hence not much weight should be given to its results.

Concluding remarks: The method has some promise but the authors have not presented a proper rationale for the parameters they have chosen and the experiments they performed for testing this tool. Furthermore, not all information is easily accessible (e.g. lack of genotype info) and hence there is little reason why a new user would turn to this method over existing alternatives.

Reviewer #2 (Public Review):

The manuscript reports results of a combined experimental and numerical investigation of magnetotactic bacteria in strong spatial confinement and under the influence of an external magnetic field. Single cells are trapped in micrometer-sized microfluidic chambers and their motion is analyzed. A variety of different trajectories are found, which depend on the chamber size and the strength of the magnetic field. Simulations of a model of active Brownian spheres helps to explain the variety of trajectories by the interplay between the wall interactions and the magnetic torque. A pronounced cell-to-cell heterogeneity is observed.

The swimming behavior without magnetic field is found to be very similar to the previously observed swimming of algae in a circular environment, i.e. with the microswimmers moving along the wall, see Ref.[31]. In the current study, a magnetic field can be used as an additional external control parameter, which leads to U-turns inside the trap to reorient bacteria in the field direction.

Reviewer #2 (Public Review):

The goal of the paper is to test the idea that colloidal osmotic pressure controls nuclear growth as suggested by Tim Mitchison in a recent review.

In fleshing out the idea, Lemiere and colleagues develop a simple mathematical model that focuses on the forces generated by the movement of macromolecules across the nuclear-cytoplasmic boundary, ignoring any contribution of ions or small molecules which they assume equilibrate across the nuclear envelope. In testing this model, they focus their quantitative analysis on the response of cells that lack a wall (protoplasts) to osmotic shocks and to perturbations of nuclear export, protein synthesis and symmetric cell division.<br /> They also analyse the motion of small 40nm particles to test how diffusion is affected by these perturbations in both compartments.

Their analysis leads them to make some important observations that suggest that the system is even simpler than they might have hoped, since under the conditions tested nuclei (which lack lamins) behave as ideal osmometers. That is, the nuclei and cytoplasm grow and shrink in concert following sudden osmotic shocks. This suggests that the tension in the nuclear envelope, which gives nuclei their spherical shape, plays no role in constraining nuclear size.

While most of the paper's claims are well supported by their data under the assumptions of the model, there are a few claims that are less convincing.

For example, while their data are consistent with the idea that cells regulate their nuclear/cytoplasmic size ration using an adder type mechanism, in which a fix ratio of nuclear and cytoplasmic proteins are synthesised per unit time as cells grow, this has not been rigorously put to the test. In addition, while the diffusion analysis is very interesting, it does not fully support the authors' simple model linking diffusion, molecular crowding and colloidal osmotic pressure, something that could be more thoroughly discussed in the manuscript.

Overall, the paper is well written in a manner that will make clear to any reader the aims and relevant background. In addition, the paper controls an impressive amount of data and includes clever controls (e.g. labelled ribosomal proteins of different sizes). The inconsistencies in the use of graph axes in Figures are likely to confuse readers though.

Reviewer #2 (Public Review):

This manuscript by Kosillo and colleagues presents a series of carefully carried out experiments evaluating the impact of perturbing the mTORC1 and mTORC2 protein complexes selectively in mouse dopamine neurons. The work presents a substantial set of data and represents a significant advance in our understanding of the respective roles of these two protein complexes in dopamine neuron structure and function.

Conceptually, it is not particularly surprising to see that in dopamine neurons, like in most other neuronal types, inhibition of these pathways and in particular of mTORC1 induces reduced morphological development and reduced neurotransmitter release.

The value of the work is more in detailing the origin of this effect on dopamine release by showing that it is likely to be due to reduced dopamine synthesis and reduced axonal density. The work also adds to the literature by clarifying the respective contributions of the mTORC1 and mTORC2 pathways to the integrity and functions of SNc and VTA dopamine neurons.

The authors conclude that there is no change in the number of dopamine neurons in the two lines of conditional KO mice. However, this is based on quantification of cell number in a very small subset of mice and using a technique this is not state of the art.

Reviewer #2 (Public Review):

Condensins promote the condensation of chromosomes during mitosis and meiosis. In many eukaryotes, including humans, there are two condensin complexes, condensin I and II, that are thought to alter chromosome morphology in different yet poorly understood ways. Key studies from the Hirano lab have previously parsed the roles of the condensin I subunits in condensation, but much less was known about condensin II at the mechanistic level. Thus, the authors examined the different contributions of each of the subunits of the five-member condensin II complex to mitotic chromosome condensation in Xenopus egg extracts, a powerful system that recapitulates the hallmarks of condensation and allows manipulations of condensin makeup that would be difficult or impossible in other systems. This important study provides an excellent foundation for our understanding of vertebrate condensin II function.

Key findings of this work are the surprising roles of the condensin II G2 and D3 subunits in the regulation of condensin II ATPase activity, condensin interaction with chromatin, and chromosome morphology, many of which are different than the previously elucidated roles of condensin I subunits using a similar experimental setup. Specifically, the authors establish a positive, ATP-hydrolysis dependent role for CAP-D3 in condensin II chromosomal accumulation and chromosome axis formation while demonstrating a negative role for CAP-G2 in those processes, as well as in condensin II ATP-hydrolysis. These results demonstrate that condensin II is acting in a distinct manner from condensin I, which is a big advance over our previously limited understanding of the differences between these complexes. The results here, especially the demonstration that removal of the C-terminal tail of the D3 subunit can promote a condensin I-like shaping activity, suggests regulatory events that are unique to condensin II. As condensin II is also involved in other processes, including the shaping of genome architecture, and centromere identity, these findings will undoubtedly be of broad interest. The experiments are generally well-conducted and clearly and logically presented. However, there are some potential weaknesses of the current work, which include the use of mouse sperm nuclei, instead of frog sperm nuclei, as the chromatin source, and the incomplete depletion of some condensin II subunits.

Reviewer #2 (Public Review):

Spinal motoneurons were the first neurons in the mammalian CNS to be studied via intracellular recording and in the seventy years that have elapsed since then a number of studies have examined the potential relationship between motoneuron morphology, intrinsic properties and excitability. Elwood Henneman (Henneman, Science 1957) proposed that motoneurons are activated in order of increasing size and much of the experimental work that followed has been directed toward understanding the mechanism of the "size principle". Caillet and colleagues have done the field a valuable service by collating and normalizing data from 18 experimental studies in cats in which at least two morphometric or electrophysiological parameters were measured to determine the best power-relation fits between estimates of size (based on cell soma diameter) and all other measures of cell properties such as axonal conduction velocity, input resistance and rheobase. They then invert these size-related relationships to predict relationships between all other parameter pairs. Finally, they show that with some exceptions, these relationships can be applied to intrinsic properties measured in other species (rats and mice).

The authors discuss the potential inaccuracies of estimates of cell size at great length, but do not consider other sources of error in any detail. For example, measurement of membrane time constant can be difficult due to the contribution of hyperpolarization-activated conductances to the measured voltage decay (cf. Fleshman et al., J Neurophysiol., 1988). Estimates of specific membrane properties are even more problematic - specific membrane resistivity (Rm) can be estimated from the membrane time constant assuming that specific capacitance is constant (e.g., Gustafsson and Pinter, J Physiol,1984) or it can be estimated from an equivalent cable model of the motoneuron, given input resistance, estimated electrotonic length and cell surface area (e.g., Ulfhake and Kellerth, Brain Res, 1984). Finally, adding further complexity, estimates of Rm based on completely reconstructed motoneurons suggest that it may vary over the surface of the motoneuron (Fleshman et al., J Neurophyiol, 1988; Clements and Redman, J Physiol, 1989). This is important because it has been argued that variations in Rm are as important as variations in cell size in determining motoneuron excitability (Gustafsson and Pinter, Trends in Neurosci., 1985).

The authors could focus more on the range of variation of different variables and its implications for mechanisms. The ranges of variation (ratio of the minimum to maximum values) of size-related variables (soma diameter, cell surface area) are around 3, whereas input resistance and rheobase show much larger ranges of variation. This suggests that size alone can not explain the observed variation in relative excitability. In cases where size, input resistance, specific membrane resistivity and rheobase have all been measured it might be possible to use some combination of the other variables to predict rheobase.

Reviewer #2 (Public Review):

This work evaluates the role of cystathione beta-synthase (CBS) as a regulatory tumor suppressor in AKT-activated tumors. The authors previously conducted a genome-wide siRNA screen for genes whose removal promotes escape from AKT-induced senescence (AIS), in which CBS was identified as top hit. Here, they validate the role of CBS in AIS escape in a number of cell lines, probe the mechanism of escape through metabolomic and transcriptomic analysis, and examine CBS levels in human gastric tumor samples. Overall, the presence of CBS loss in human samples is well-validated, and its impact on tumorigenesis is presented in a xenograft model. However, the authors' conclusions regarding the biological mechanism are not well-supported by the presented data and techniques.

Strengths:<br /> The authors validate the role of CBS loss in escape from AIS, using appropriate knockdown cell lines and rescue experiments. Interestingly, CBS's function is specific to AIS, and not other forms of senescence, in particular RAS-induced senescence. These results validate their identification of CBS in their previously published genome-wide screen.

The authors provide strong data (Fig. 5) that CBS loss is frequent in gastric cancer tumor samples and gastric cancer cell lines; due to mutations, and promoter hypermethylation.

The authors provide strong data (Fig. 6) that CBS loss is sufficient to promote oncogenic transformation and tumorigenesis, making use of a gastric epithelial cell line (GES-1), and AGS cancer cells (which harbor AKT activation and CBS loss). These results correlate well with the frequent loss of CBS observed in human gastric tumors (Fig. 5), and support a role for CBS as a tumor suppressor in AKT-activated gastric cancer.

Weaknesses:<br /> The primary weakness of the manuscript lies within the author's exploration of mechanism: i.e., how CBS loss promotes cancer.

First: Upon removal of CBS, the authors do not observed expected changes in levels of transsulfuration and glutathione-related metabolites: for instance, cystathionine, cysteine and glutathione, and H2S are not depleted. The manuscript does not probe or explain the underlying compensatory mechanisms for these metabolite abundances in the setting of CBS loss.

Second: Based on the above, the authors propose a mitochondrial role for CBS in regulating CBS senescence. However, their experiments do not convincingly demonstrate the existence of mitochondrially-localized CBS: their fluorescence-based imaging is not sufficiently conclusive, and no alternative methods are used to validate mitochondrial localization of CBS.

Third: Critically, the authors do not demonstrate that the mitochondrial form of CBS is required or sufficient for the observed effects on oxidative phosphorylation and ROS generation, as well as the escape from AIS. Without this demonstration, the proposed mechanism is not well supported.

Reviewer #2 (Public Review):

Summary: This substantial collaborative effort utilized virus-based retrograde tracing from cervical, thoracic and lumbar spinal cord injection sites, tissue clearing and cutting-edge imaging to develop a supraspinal connectome or map of neurons in the brain that project to the spinal cord. The need for such a connectome-atlas resource is nicely described, and the combination of the actual data with the means to probe that data is truly outstanding.

They then compared the connectome from intact mice to those of mice with mild, moderate and severe spinal cord injuries to reveal the neuronal populations that retain axons and synapses below the level of injury. Finally, they look for correlations between the remaining neuronal populations and functional recovery to reveal which are likely contributing to recovery and its variability after injury. Overall, they successfully achieve their primary goals with the following caveats: The injury model chosen is not the most widely employed in the field, and the anatomical assessment of the injuries is incomplete/not ideal.

Concerns/issues:

1. I would like to see additional discussion/rationale for the chosen injury model and how it compares to other more commonly employed animal models and clinical injuries. Please relate how what is being observed with the supraspinal connectome might be different for these other models and for clinical injuries.

2. The assessment of the thoracic injuries employed is not ideal because it provides no anatomical description of spared white matter (or numbers of spared axons) at the injury epicenter.

3. Related to this, but an issue that requires separate attention is the highly variable appearance of the injury and tracer/virus injection sites, the variability in the spatial relationship with labeled neurons (lumbar) and how these differences could influence labeling, sprouting of axons of passage and interpretation of the data. In particular this is referring to the data shown in Figure 6 (and related data).

Reviewer #2 (Public Review):

This study provides a new approach to image alignment between electron microscopy (EM) and time-lapse fluorescence microscopy (FM). It uses previously developed methods of EM sampling (FIB-SEM and array-tomography), imaging and software approaches of nuclei lineaging. It combines these together with a new landmark-based co-optimization algorithm, suggested to contribute to high accuracy, for cross-modality image alignment. The study seeks to combine the spatial resolution by EM and the temporal resolution of FM to characterize cell morphologies in C. elegans embryos, specifically its central nervous system neuropil, the major sensory organ, and excretory canal. The work presents the timing of axon growth of specific neurons of the neuropil and specific appositions of neurons and glia in the analyzed sensory organ. The authors present a way towards cross-modality analysis in C. elegans and suggest their combined approach can be modified for future use in alignment and annotation of other complex images.

Reviewer #2 (Public Review):

Babies cry immediately after birth, but how the ability to produce sounds develops before birth remains a mystery. Marmoset monkeys have attracted much attention as a useful model for studying vocal communication, especially in the early vocal development. Infant marmosets experience a remarkable process of vocal development during the first 2 months after birth. To be sure, the vocal ability also develops during the prenatal period, but it is difficult to observe. The authors try to address this issue in marmoset monkeys by investigating their fetal orofacial movements in a densely-sampled, longitudinal ultrasound imaging study. They analyze fetal head and orofacial movements in marmoset monkeys by a highly quantitative approach and find that orofacial movements necessary for producing rhythmical vocalizations may differentiate from a larger movement pattern that includes the entire head. More importantly, they find that signature features of marmoset infant contact calls emerge prenatally as a distinct pattern of orofacial movements. Thus, the marmoset monkey is a non-human primate model mimicking not only the vocal maturation after birth but also the sensorimotor development necessary for vocalizing occurs prenatally.

This work is interesting and meaningful. The evidence of prenatal development of orofacial movements required for vocal production is clear. The non-invasive longitudinal ultrasound imaging method is reasonable and the data analyses are highly quantitative and rigorous. The conclusions of this paper are mostly well supported by data, but some aspects of data interpretation need further discussion.

1) In this study, the authors want to emphasize the difference between orofacial movements necessary for vocalizations and more global bodily movements. In fact, the development of orofacial movements is a part of the overall development of bodily movements. It is difficult to specifically correlate orofacial movements to vocal production. For example, orofacial movements may be also important for sucking or breathing. They are not in conflict.

2) In the study, a distinct pattern of orofacial movements is related to the production of infant contact calls. In previous studies, marmoset monkeys have been shown to produce contact calls around every 10 s (~0.1 Hz), which is correlated with heart rate and "Mayer wave", an oscillation of the autonomic nervous system. Thus, the link between orofacial movements and the production of contact calls could be explained by the autonomic nervous system, such as breathing.

3) Contact phee calls and twitter calls are mature calls in marmoset monkeys. Infant marmosets have a specific "cry" call which is similar to that of human babies. It will be of particular interest whether there is any developmental clue for the production of "cry" calls during the prenatal stage.

Reviewer #2 (Public Review):

The study by Surrett et al. uncovers a novel regulatory axis in Vibrio fischeri that controls the expression of the qrr1 small RNA, which post-transcriptionally controls various quorum-dependent outputs. This study is timely and addresses a major question about the physiology of this important model symbiosis and potentially other Vibrio species. The results should be of broad interest within the field of microbiology.

While it was previously believed that qrr1 expression is under the strict control of the LuxO-dependent quorum sensing cascade, the authors demonstrate that qrr1 expression can be induced by another bEBP, SypG, in a manner that is quorum-independent. It was previously shown that qrr1 is important for colonization, and the authors recapitulate and extend this finding here. However, bacteria are likely at high cell density prior to entry into the crypts, which would repress qrr1 expression. Thus, despite the importance of qrr1 expression for crypt colonization, it would counterintuitively be repressed. The discovery of the SypG quorum-independent induction of qrr1 in this study may help resolve this conundrum. The authors take a largely genetic approach to characterize this novel regulatory pathway in combination with a squid colonization model. The experiments performed are generally well controlled and the data are clearly presented. The authors, however, fail to provide experimental evidence to support the physiological relevance of SypG-dependent control of qrr1 expression during host colonization.

Fig. 2 - It is unclear why there is a disconnect between qrr1 expression and qrr1-dependent effects. Data in 2B, indicate that qrr1 is induced in the ∆binK mutant according to the Pqrr1-gfp reporter but this expressed qrr1 does not have any effect on phenotypes like bioluminescence according to the data presented in 2C. While the authors reveal an effect of the binK deletion when rscS is overexpressed, it is unclear why this is necessary since simple deletion of bink without rscS* is sufficient to induce qrr1 in 2B. Could this discrepancy be due to the fact that experiments in 2B are done on solid media while the experiments in 2C are performed in liquid media? Do cells in liquid not express qrr1? Or conversely, perhaps testing the bioluminescence of cells scraped off of plates could reveal a phenotype for the binK mutant similar to those seen in the rscS* background in liquid. Or alternatively, if cells in a liquid culture still express qrr1, perhaps there is a posttranscriptional mechanism that prevents qrr1 from exerting an effect on bioluminescence? The latter possibility would alter the proposed model.

The authors propose a model in which sypG dependent activation of qrr1 is required for appropriate temporal regulation of this small RNA and contributes to optimal fitness of V. fischeri during colonization, however, this was not directly tested, and experimental evidence to support a physiological role for spyG-dependent regulation of qrr1 remains lacking. Data in Fig. S3 and Fig. 4G-H suggest that the Gs at -131 and -97 in Pqrr1 are largely dispensable for LuxO-dependent activation, but are important for SypG-dependent activation of Pqrr1. Also, the Pqrr1 mutations at C -130 and -96 completely prevent sypG-dependent activation while only partially reducing LuxO-dependent activation. If SypG-dependent activation of qrr1 is critical for the fitness of V. fischeri, a strain harboring these Pqrr1 promoter mutations should be attenuated in a manner that resembles the qrr1 deletion mutant as shown in Fig. 3C.

Fig. S4 - these data suggest that LuxO cannot enhance transcription of PsypA and PsypP at native expression levels. But sypG-dependent induction of qrr1 was largely tested with Ptrc-dependent overexpression of SypG. Would overexpression of LuxO induce PsypA and PsypP? The authors should at least acknowledge this possibility in the text.

The authors adopt three distinct strategies to induce sypG-dependent activation of qrr1 in distinct figures throughout the manuscript: deletion of binK, overexpression of rscS (rscS*), and direct overexpression of sypG. It is not entirely clear why distinct approaches are used in different figures. This is particularly true for Fig. 5 since the authors already demonstrated that the direct overexpression of sypG can be used, which is a more direct way of addressing this question. Similarly, sypG overexpression should inhibit bioluminescence in Fig. 2 based on the proposed model, which would have tested the claims made more directly. Additional text to clarify this would be helpful.

The Fig. 5D legend indicates that the strains harbor a Ptrc-GFP reporter. However, the text would suggest that these strains should harbor a Pqrr1-GFP reporter to test the question posed.

The conclusion that SypG and LuxO share UASs in the qrr1 promoter is based on fairly limited genetic evidence where point mutations were introduced into 3 bp of the predicted LuxO UASs within the qrr1 promoter. This conclusion needs to be qualified in the text or additional experimental evidence is needed to support this claim. For example, in vivo ChIP-exo could be used to map the SypG and LuxO binding sites. Or SypG and LuxO could be purified to assess binding to the qrr promoter in vitro (to map binding sites or test competitive interactions of these proteins to the qrr promoter).

On a related note, SypG binding to the qrr1 promoter is speculated based on indirect genetic evidence. But the authors do not directly demonstrate this. This should be acknowledged in the text or additional experimental evidence should be provided to support this claim.

Reviewer #2 (Public Review):

The investigators looked at mφs in lumbar DRG after a spared nerve injury in which two of the three branches of the sciatic nerve are transected and the third left intact. This is a classical preparation for studying neuropathic pain. This paper demonstrates that the increase of mφs is an increase in the number of CX3CR1+ (resident) mφs and not CCR2+ (infiltrating mφs) by using CX3CR1 and CCR2 individual reporter mice. Using a CX3CR1 conditional knockout (KO) mouse, they found that this receptor must be present on the mφs for the increase in number to occur. Next, they did a parabiosis experiment with GFP+ mice and found that neither of these mφ subtypes infiltrated into the DRG. To examine proliferation, they injected animals with Ki67 and found this label, which is an indication of proliferation, was present in the CX3CR1+ mφs (but not the CCR2+ mφs). Finally, they identified the CX3CR1 mφs to be the cells that express TNFα and IL-1b but not IL-6.

An experiment that would be useful would be to determine if there is an increase or a decrease in the availability to mφs of the ligand CXC3L1 after the spared nerve injury. The authors state from the work of others that membrane-bound CX3CL1 is constitutively expressed and that it is decreased after nerve injury. They hypothesize that this indicates a release of the chemokine, but such a decrease could also indicate a decrease in expression. A few sentences on what is known in other systems on the importance and mode of action of membrane-bound and non-membrane-bound CX3CL1 would be useful.

The main weakness of the manuscript is that many highly relevant previous findings, in some cases reporting nearly identical experiments sometimes with the same and sometimes with somewhat different results, are not mentioned. Kalinski et al. (which is cited but not in this context) reported a very similar parabiosis experiment. While they did not identify subtypes of mφs, they found an increase in infiltration of mφs, which was small (though statistically significant) compared to the larger increase that occurred in the distal nerve. In 2013 and 2018, Niemi et al. and Lindborg et al (J Neurosci and J Neuroinflammation respectively) reported that mφs in the DRG are somewhat decreased in a CCR2 KO mouse, suggesting again that there is some infiltration of mφs into the DRG after axotomy. They also showed that the mφ chemokine CCL2 increases in the DRG after sciatic nerve injury. With regard to proliferation, Yu et al. in 2020 (which again is cited but not in this context) also used a spared nerve paradigm stained DRGs for CX3CR1+ mφs and found an increase. They then stained DRG sections for Ki67 and demonstrated proliferation in this population. An earlier reference by Krishnan et al in 2018 published in J Neuropathol Exp Neurol is entitled "An Intimate Role for Adult Dorsal Root Ganglia Resident Cycling Cells in the Generation of Local Macrophages and Satellite Glial Cells". With regard to cytokine expression, in 1995, Murphy et al published a paper in J Neurosci demonstrating induction of interleukin-6 in axotomized sensory neurons.

Reviewer #2 (Public Review):

The manuscript reports a cholesterol-sensing mechanism in the plasma membrane (PM) of mammalian cells. The cholesterol sensor Aster-A diffuses into the tubular ER and monitors the molar ratio of cholesterol in the inner leaflet of the PM (IPM) via transient ER-PM contact sites. When the cholesterol ratio in the IPM exceeds a threshold level, the lifetime of Aster-A at the PM-ER contact sites is increased to mediate the transfer of cholesterol to the ER membrane. The SREB-Scap system detects the increase in ER cholesterol and cholesterol uptake and synthesis. The colocalization of GFP-labeled Aster-A with PM-ER contact sites was studied by confocal laser-scanning microscopy. By using a cholesterol-binding domain of pore-forming cytolysin, the authors monitored the cholesterol level in the extracellular leaflet of the PM. The experimental data suggest that the cholesterol amount in the PM cytosolic leaflet, which is decreased by ABCCA1 or ABCG1, controls the Aster-A recruitment to PM/ER contact sites. The authors provide an interesting working model of how the ER senses cholesterol levels in the IPM.

Reviewer #2 (Public Review):

I am enthusiastic about the comprehensive approach, the thorough analysis, and the intriguing findings. This work makes a timely contribution to the field and warrants a wider discussion in the community about how computational methods are deployed and interpreted. The paper is also a great and rare example of how much can be learned from going beyond a meta-analytic approach to systematically collect data that assess commonly held assumptions in the field, in this case in a large data-driven study across multiple tasks. My only criticism is that at times, the paper misses opportunities to be more constructive in pinning down exactly why authors observe inconsistencies in parameter fits and interpretation. And the somewhat pessimistic outlook relies on some results that are, in my view at least, somewhat expected based on what we know about human RL. Below I summarize the major ways in which the paper's conclusions could be strengthened.

One key point the authors make concerns the generalizability of absolute vs. relative parameter values. It seems that at least in the parameter space defined by +LRs and exploration/noise (which are known to be mathematically coupled), subjects clustered similarly for tasks A and C. In other words, as the authors state, "both learning rate and inverse temperature generalized in terms of the relationships they captured between participants". This struck me as a more positive and important result than it was made out to be in the paper, for several reasons:

- As authors point out in the discussion, a large literature on variable LRs has shown that people adapt their learning rates trial-by-trial to the reward function of the environment; given this, and given that all models tested in this work have fixed learning rates, while the three tasks vary on the reward function, the comparison of absolute values seems a bit like a red-herring.

- Regarding the relative inferred values, it's unclear how high we really expect correlations between the same parameter across tasks to be. E.g., if we take Task A and make a second, hypothetical, Task B by varying one feature at a time (say, stochasticity in reward function), how correlated are the fitted LRs going to be? Given the different sources of noise in the generative model of each task and in participant behavior, it is hard to know whether a correlation coefficient of 0.2 is "good enough" generalizability.

- The +LR/inverse temp relationship seems to generalize best between tasks A/C, but not B/C, a common theme in the paper. This does not seem surprising given that in A and C there is a key additional task feature over the bandit task in B -- which is the need to retain state-action associations. Whether captured via F (forgetting) or K (WM capacity), the cognitive processes involved in this learning might interact with LR/exploration in a different way than in a task where this may not be necessary.

- More generally, isn't relative generalizability the best we would expect given systematic variation in task context? I agree with the authors' point that the language used in the literature sometimes implies an assumption of absolute generalizability (e.g. same LR across *any* task). But parameter fits, interactions, and group differences are usually interpreted in light of a single task+model paradigm, *precisely b/c* tasks vary widely across critical features that will dictate whether different algorithms are optimal or not and whether cognitive functions such as WM or attention may compensate for ways in which humans are not optimal. Maybe a more constructive approach would be to decompose *tasks* along theoretically meaningful features of the underlying Markov Decision Process (which gives a generative model), and be precise about (1) which features we expect will engage additional cognitive mechanisms, and (2) how these mechanisms are reflected in model parameters.

Another point that merits more attention is that the paper pretty clearly commits to each model as being the best possible model *for its respective task*. This is a necessary premise, as otherwise, it wouldn't be possible to say with certainty that individual parameters are well estimated. I would find the paper more convincing if the authors include additional information and analysis showing that this is actually the case. I am particularly interested to see whether some of the discrepancies in parameter fits can be explained by the fact that the model for Task A did not account for explicit WM processes, even though (1) Task A is similar to Task C (Task A can be seen as a single condition of Task C with 4 states and 2 possible visible actions, and stochastic rather than deterministic feedback) and (2) prior work has suggested a role for explicit memory of single episodes even in stateless bandit tasks such as Task B.

It is interesting that one of the parameters that generalizes least is LR-. The authors make a compelling case that this is related to a "lose-stay" behavior that benefits participants in Task B but not in Task C, which makes sense given the probabilistic vs deterministic reward function. I wondered if we can rule out the alternative explanation that in Task C, LR- could reflect a different interpretation of instructions vis. a vis. what rewards indicate - do authors have an instruction check measure in either task that can be correlated with this "lose-stay" behavior and with LR-? And what does the "lose-stay" distribution look like, for Task C at least? I basically wonder if some of these inconsistencies can be explained by participants having diverging interpretations of the deterministic nature of the reward feedback in Task C. The order of tasks might matter here as well -- was task order the same across participants? It could be that due to the within-subject design, some participants may have persisted in global strategies that are optimal in Task B, but sub-optimal in Task C.

The PCA analysis adds an interesting angle and a novel, useful lens through which we can understand divergence in what parameters capture across different tasks. One observation is that loadings for PC2 and PC3 are strikingly consistent for Task C, so it looks more like these PCs encode a pairwise contrast (PC2 is C with B and PC2 is C with A), primarily reflecting variability in performance - e.g. participants who did poorly on Task C but well on Task B (PC2) *or* Task A (PC3). Is it possible to disentangle this interpretation from the one in the paper? It also is striking that in addition to performance, the PCs recover the difference in terms of LR- on Task B, which again supports the possibility that LR- divergence might be due to how participants handle probabilistic vs. deterministic feedback.

Reviewer #2 (Public Review):

Precise control of neuronal diversity is an important issue in developmental neurobiology. The lamina in the Drosophila visual system is an essential model system to deal with this issue. The inductive action of Hedgehog and EGF signals from the retina triggers the differentiation of L1-L5 lamina neurons that are precisely arranged to form the lamina column (or cartridge) structure. The authors previously revealed that the wrapping glia secretes insulin ligands in response to EGF and induces the differentiation of L1-L4 lamina neurons. However, the mechanism that induces L5 differentiation was not known.

In this study, the authors focus on the role of the outer chiasm giant glia (xgO) to induce L5 differentiation. They argue that xgO produces multiple ligands in response to the EGF signal to induce MAPK-dependent L5 differentiation. They also show that the differentiating L5 produces Argos, a secreted EGF antagonist, to repress extra L5 differentiation. Those extra L5 cells may be removed by apoptosis. As a result, each lamina column contains one L5 neuron.

The study is based on the authors' previous study and is significantly extended by integrating the roles of xgO glia to induce L5 differentiation. The authors identified multiple candidate ligands such as Spi and Col4a1 that may induce L5 differentiation.

The results solely depend on the ectopic expression of Spi and Col4a1. Although the authors performed rescue experiments, they depend on EGFR[DN] and non-physiological levels of ligand expression under the control of the Gal4/UAS system. To meet the standard of Drosophila genetics, the authors have to demonstrate the loss of function experiments for Spi and Col4a1 in xgO.

Major points:

1. The authors argue that xgO secretes Spi and Col4a1 to induce MAPK-dependent L5 differentiation. However, no loss-of-function condition for these putative ligands was tested. Since they speculated that expression of Spi and Col4a1 alone may not lead to a sufficient level of MAPK activity, the results of their loss of function conditions have to be included in the paper.

2. The authors found ectopic L5 neurons when apoptosis was repressed (Fig. 1). It is likely that cells that fail to differentiate to L5 are removed by apoptosis, but this link was not clearly demonstrated in the paper. As a result, there is a gap between the data in Fig. 1 (section 1 in the text) and the other part of the paper. The relationship between Fig. 1 and the other data should be carefully discussed. In my opinion, the first section of Results should be moved after the last section so that the results of Fig. 1 are explained as a potential mechanism to remove cells that failed to differentiate to L5.

Reviewer #2 (Public Review):

Bailon-Zambrano et al study the possible mechanisms that contribute to the oft-observed phenomenon that an individual mutation may be associated with variable expression of a phenotype. They focus on loss-of-function of the mef2ca gene of zebrafish, which is needed for the normal development of several craniofacial structures. They demonstrate that recessive putative loss-of-function mutant alleles of the mef2ca gene of zebrafish are associated with a range of expressivity. By focusing on one aspect of the mutant phenotype, the length of the symplectic cartilages that support the jaw, they find a correlation between the average strength of the phenotype of an allele (measured as reduction in length) and the extent of variability between mutant individuals that carry the allele. I am concerned about this conclusion and generalizations that may be drawn from focus on a single quantifiable character, the symplectic cartilage. Perhaps there is always a fixed variation in the length of this cartilage. As stronger alleles produce shorter cartilage pieces, variations in size may appear to be of greater significance when affecting shorter average length.

The authors hypothesize that one factor that contributes to the varied phenotypic expression of an allele (expressivity) is the co-expression of paralogs that may provide wildtype function and thus partially or wholly rescue the mutant phenotype. They test this hypothesis by "fixing" conditions where a single mutation may be expressed with low or high penetrance. By selective breeding based on phenotype, they create two sets of strains that carry an identical mef2ca mutation: one strain has high penetrance of the mutant phenotype and the other low penetrance. They then investigate the factors that are likely responsible for the high vs low penetrance. Historically we would call these factors "genetic modifiers". There is extensive literature on the nature of genetic modifiers and there are many current screens in both mice and Drosophila to identify genetic modifiers and uncover their nature, but there is little reference to these studies in the current manuscript. Further, there is previously published work that hypothesizes that one important function of paralogs in multicellular organisms is to provide a buffer to stabilize levels of gene expression needed for developmental decisions.

The authors find that paralogs of the mef2ca gene are expressed in cells that normally express mef2ca, and that these paralogs are expressed at higher levels in the mutant strain with low penetrance than in the mutant strain with high penetrance. They say that selection for high penetrance of the mef2ca mutant phenotype "leads to down-regulation" of paralog expression. As the authors only show that paralog expression is at lower levels in high penetrance vs low penetrance strains, it is not clear what they mean by "down-regulation". Perhaps their breeding scheme has only "captured" what is natural variation and there is no active mechanism of "down-regulation". The authors need to clarify what they mean.

The authors also find that individuals from the high penetrance strains that don't carry the mef2ca mutation (they are wildtype for this gene) sometimes exhibit mef2ca mutant characters. They suggest the reduced paralog expression is responsible for the occasional emergence of the mef2ca mutant characters. In contrast with this suggestion, the authors later claim the paralogs "have no function" in craniofacial development. The authors need to clarify their thoughts about what is paralog function in craniofacial development and why reduced paralog function might contribute to the expression of mef2ca mutant characters. This topic is worthy of discussion.

The authors claim is there is both up-regulation of paralogs in low penetrance strains and down-regulation of paralogs in high penetrance strains. As they only compare steady state levels of expression in each strain, they can only reasonably conclude that there are differences - they seem to imply a mechanism and they need to be clear about what they are thinking.

They hypothesize that paralog expression in the low penetrance strain masks the effects of loss of mef2ca. They test this by creating CRISPR-engineered mutations of two paralogs and examining the effects of the paralog mutations in wildtype fish or in fish carrying the mef2ca mutation. They find the putative loss-of-function mutations in the paralogs have no effect in wildtype backgrounds and conclude these paralog genes have no function in craniofacial development. However, the paralog mutations enhance the mutant phenotype in fish that carry the mef2ca mutation. This provides strong evidence consistent with the model that the elevated expression of the paralogs functions to reduce the severity of the phenotype associated with the mef2ca mutation.

Reviewer #2 (Public Review):

Rhodes et al., use an elegant biochemical capture approach to identify the SERK-dependent LRR receptor kinase HSL3 as the only receptor for the newly identified CTNIP peptides in Arabidopsis, and in other species. This idea is based on their finding that synthetic CTNIP peptides trigger cytoplasmic calcium influx and ROS production in wild-type but not bak1-5 mutant Arabidopsis plants. Using the BAK1 co-receptor and the synthetic peptide they identify HSL3 as a major BAK1 signaling complex component and then elegantly demonstrate in vivo and in vitro that CTNIPs are direct ligands targeting the HSL3 extracellular domain. HSL3, despite its name, is thus no receptor for IDA/IDL peptides but for a new family of peptides with possible roles in stress responses and in root development. While most experiments are performed to a high technical standard and are well documented, the bioinformatic characterization of the CTNIP peptide family could be described in more detail. In addition it remains unclear if the peptide fragment used in this study corresponds to the mature signaling peptide processed in vivo. It also remains to be clarified if the two invariant cysteine residues in CTNIPs are involved in intra- or intermolecular disulfide bonds, and if the peptides could be post-translationally modified.

Reviewer #2 (Public Review):

The authors explored if and how Piezo1 regulated mechanical stiffness and inflammatory signals, thereby directing the differentiation of TH1 and Treg cells in cancer. They showed the genetic deletion of Piezo1, a mechanosensory ion channel, in dendritic cells, promoted tumor growth in a mouse model. Piezo1ΔDC mice showed an increase in Tregs and a decrease in IFNg+ Th1 cells in the MC38 tumor tissue. They showed TGFbR2-pSmad3 and IL-12Rb2-pStat4 signaling axis were involved in this process. Moreover, they suggested cooperation between Piezo1-SIRT1-HIF1a-glycolysis metabolism pathway and calcium-Piezo1-calcineurin-NFAT signaling pathway in DCs.

The authors have never directly tested the relationship between Piezo1 and DC stiffness. The authors claimed that "Piezo1 integrates innate inflammatory signals and mechanical stiffness signals". But what they showed were independent experiments of inflammatory stimulus (LPS) or stiffness stimulus (50kPa hydrogel). Do these two stimuli work together to induce Piezo1 signaling and contribute to Piezo-mediated differentiation of Th1 and Treg cells?

Reviewer #2 (Public Review):

This study uses a well-established reaching task to assess the effect of learning on cortical structures as assessed by MRI in mice. The results show a decrease in grey matter (GM) and an increase in white matter (WM) volumes that appear to peak at experimental day 8, falling slightly thereafter.

This is an interesting addition to the literature around myelination changes associated with learning/activity (adaptive myelination). However, it requires significant additional analysis. The correlation between imaging and histology is critical, but the only measure used here is MBP immunoreactivity. This is insufficient, as MBP can be expressed by newly-formed oligodendrocyte cell bodies, by their processes, and by the myelin sheath they form; but only the latter is relevant to function. So, a much more detailed analysis of oligodendrocyte morphology and myelin sheath number/size is required. This analysis needs to distinguish different layers of the cortex. This is easy for the superficial layers where myelination is sparse but much more difficult in the more heavily myelinated deeper layers. Here, counting nodes of Ranvier by Caspr immunostaining provides a good proxy. Ideally, both sheath number and sheath length would be analysed, but I accept that most studies point to number rather than changes in length as being the key changes in adaptive myelination. Then, the critical precise correlation of imaging changes with myelin sheath number can be made and the conclusion that the MRI changes represent physiologically significant changes in myelination becomes more solid.

Reviewer #2 (Public Review):

Kamal and colleagues study the mechanism of chitinous cuticle formation in ecdysozoa using the C. elegans pharyngeal cuticle as a model. They make extensive use of published material including spatio-temporal transcriptomics, electron micrographs, protein-protein interaction databases, and others. They combine this meta-analysis with a few focused yet highly informative experiments to provide a synthesized version of the knowledge. They use this synthesis to identify new families of secreted proteins that are predicted to be intrinsically disordered proteins (IDPs) and show that one such IDP can undergo phase separation in vitro.

The paper is well-written, the analysis is rigorous, and the discussion is insightful. I anticipate this will be a widely cited paper, as it leads to several interesting hypotheses to pursue.

I could identify no major concerns in their data and claims.

Reviewer #2 (Public Review):

In this work, Kuey et al develop a synthetic system to test if clathrin, on its own, can bend and cut membranes inside living cells. The authors expand a previously-developed "hotwire" system to recruit a clathrin-binding hook (Beta2 hinge/appendage domain) to the cytoplasmic face of the mitochondrial outer membrane through an FKBP/rapamycin/FRB dimerization system. After the addition of the ligand, clathrin was observed to form puncta on mitochondria and create double-membrane clathrin-coated vesicles. This process was independent of many classic endocytic proteins including dynamin. The authors propose that clathrin itself is the only protein needed to generate the forces required to drive vesicle formation and scission inside cells. This work supports the idea that the dozens of accessory proteins important for CME at the plasma membrane play roles specific to the forces, lipids, or cargo encountered at the plasma membrane.

This is an excellent and well-done study. The questions are important and the experiments creative. It leads to a much clearer view of how the clathrin lattice functions in endocytosis. It is a controlled dissection of the endocytic machinery. It is particularly useful because many of the proteins involved in endocytosis have overlapping and complex roles.

Reviewer #2 (Public Review):

Huan-Huan et al. investigated the structure of phosphoribosyl pyrophosphate (PRPP) synthase (PRPPS) from Escherichia coli, a highly conserved enzyme from bacteria to mammals that catalyzes the synthesis of a key common compound for several metabolic pathways. Although the structure of this enzyme was known, the mechanism of regulation by ADP and AMP remained uncharacterized. Previously, the group of JE. Wilhelm found that PRPP synthetase from different eukaryotes assembles into long filamentous structures (named cytophidia). The present study shows that PRPP synthetase filaments also form in bacteria, both in vitro and in vivo. Then, they determined the structure of two different forms of PRPPS filaments at atomic detail using cryo-electron microscopy. Combining structural data with mutagenesis and activity assays, they demonstrate that the enzyme is regulated differently by allosteric effectors when assembled into one filament form or the other.

The strength of the manuscript is the high-quality cryo-EM data, which allows the reconstruction of two different filament forms bound to different ligands, the identification of a new regulatory site, and the description of the movements of the regulatory loop at the active site, which either blocks the active site (in filament type B) or hampers the binding and inhibition of ADP to the allosteric site (in filament type A).

Based on the structural information, the authors designed point mutants that favor the formation of one filament type or the other. Using these mutants, the authors dissect the different responses of the two filament forms to the nucleotides that bind and regulate the reaction rate.

The authors conclude that filament formation is not needed for PRPPS activity, but that the formation of these filaments is an additional layer to fine-tune its activity.

Overall, the data are of high quality and the conclusions are of interest to understanding the significance of the organization of proteins into supramolecular membrane-less compartments.

A similar filamentous organization is expected for this enzyme in other higher eukaryotes, including humans. Defects in the human enzyme are the cause of rare congenital diseases. Based on the current data, the authors speculate that the mechanistic effect for certain pathogenic variants could be affecting the formation of the filaments.

This manuscript reveals that this enzyme is more complicated than initially expected. The newly proposed regulatory mechanism is not easy to understand, since ADP can inhibit or enhance the reaction depending on whether it binds to one regulatory site or to the other, but also by competing with ATP in the catalytic site. Some parts of the text and figures are not sufficiently clear and difficult to follow. The authors could make an effort to improve clarity and correct grammatical issues.

Reviewer #2 (Public Review):

In this work, a new software package for hippocampus segmentation, unfolding, and subfield labeling is presented. The method is packaged into a BIDS app, in order to use it with standard 3T MRI, but can also accommodate more advanced 7T imaging, and the different steps can be performed independently, for instance when processing post-mortem histology data or incorporating manual delineations.

The unfolding procedure defines a flat map of the hippocampus, which may be particularly useful for visualization, similarly to the flat maps or partially inflated maps previously built for the cerebral and cerebellar cortices.

The method is evaluated on high resolution data from the HCP (3T) as well as ultra-high resolution 7T data often acquired for hippocampus morphometry. Comparisons are made with the two other leading software packages for hippocampus segmentation and subfield labeling, showing that the proposed method is more complete, including both head and tail, and arguing that it preserves better the topology of unfolded subfields.

The software package is distributed in open source, including detailed documentation but unfortunately no actual test data. Multiple outputs options make the software tool very flexible and potentially useful in a large number of data sets.

Overall, the methods employed are sound and appear both robust and elegant. However, there are a few potential limitations and confusions with regard to the method that needs to be addressed.

First, the different methods used in the toolbox are not fully described, sending the reader to collate information from multiple sources in order to understand what algorithms are run in the processing pipeline. This article would be the opportunity to summarize the different methods used in sufficient detail, especially as modifications and adjustments have been made from the original works.

Second, there is a general confusion about topology and topology preservation throughout the paper. The voxel domain and its relatively coarse resolution with regard to the hippocampal formation and its subfields can hardly allow to preserve (digital) topology, and the proposed method in fact does not guarantee it, like the other ones. What it does preserve is the relative arrangement of the subfields in the unfolded plane, which is fixed to match the map obtained from labeling a single post-mortem data set, BigBrain. Comparing the capabilities of other methods to preserve this arrangement is somewhat unfair, and not really relevant. The important topological feature that is actually preserved (or better, estimated) is the hippocampal folding structure, which is conserved independently of the variation in digitation. Separating the two questions (of mapping a folded surface representation and of correctly placing subfields label on it) is important, and somewhat confused in the paper.

Third, there is an implicit assumption made that unfolded hippocampi should match, which is not tested in experiments, and is arguable: in the same way that cortical maps unfolded into perfect spheres still need to be aligned for establishing proper correspondences (see e.g. the Spherical Demons algorithm in FreeSurfer), hippocampal maps require non-linear alignment in the unfolded plane, unless the unfolding procedure takes into account additional features such as the location of subfields, stable morphometric landmarks, and/or MRI contrasts. While this problem is likely less pronounced here because of the generally less variable shape of the hippocampus, it should be fully acknowledged.

Fourth, the key segmentation step to obtain the unfolded representation is performed by a U-Net. While such artificial neural networks have generally excellent performance with the type of data they have been trained with, they are often challenged to generalize across different contrasts. The authors provide some results showing a limited yet systematic decrease in performance (Fig.5B), but a discussion of the limitations and important preprocessing steps recommended would be useful for the general user.

Reviewer #2 (Public Review):

Stolz and colleagues show that murine or human Treg cells deficient in NCOR1 display increased expression of MYC that drives the effector Treg cell differentiation. This effect is restricted mainly to mature Treg cells as it is not associated with thymic changes in Treg development. The impact of NCOR1 in Treg development was also confirmed because NCOR1 repressed the acquisition of an eTreg gene signature by naïve Treg cells. In addition, the authors found that the liver X receptor beta (LXRbeta, a cholesterol sensor involved in the cholesterol biosynthesis) could interact with NCOR1. Agonists of LXRbeta disrupted LXRbeta-NCOR1 interactions, leading to MYC upregulation that phenocopied the outcome of NCOR1-deficiency. Finally, the authors showed that NCOR1-deficiency in Treg cells, although supporting the differentiation of eTreg cells, failed to prevent colitis upon adoptive cell transfer into lymphopenic mice transferred with CD4+ T cells. This observation was interpreted as evidence that NCOR1, besides having an impact on eTreg cell differentiation, can also be essential to maintaining the suppressive function of Treg cells.

Reviewer #2 (Public Review):

The manuscript makes large steps forward in our understanding of the life cycle of C. depauperatus, and includes the development of a transformation method for this species. The experimental work has been carried out to a very high standard and the Figures are very clear. The Introduction is also comprehensive and clear. I congratulate the authors on this excellent work.

Reviewer #2 (Public Review):

The manuscript by Bai et al. explores the single-cell motility dynamics within a chemotactic soliton wave in E. coli. They tracked individual cells and measured their trajectory speed and orientation distributions behind and ahead of the wave. They showed cells behind the wave were moving in a more directed fashion towards the center of the wave compared to cells ahead of the wave. This behavior explains the stability of group migration, as confirmed by numerical simulations.

Saragosti et al (2011) already provided exactly what the authors claim to do here : "How individuals with phenotypic and behavioral variations manage to maintain the consistent group performance and determine their relative positions in the group is still a mystery." (Line 75-77) (See the last sentences from Saragosti et al : "This modulation of the reorientations significantly improves the efficiency of the collective migration. Moreover, these two quantities are spatially modulated along the concentration profile. We recover quantitatively these microscopic and macroscopic observations with a dedicated kinetic model.")<br /> What is novel here is the titration of the behavior with chemo-receptor abundance.

What is novel here is the titration of the behavior with chemo-receptor abundance, but I believe the scope is not wide enough for publication in eLife. I suggest the authors to submit in a more specialized journal.

Reviewer #2 (Public Review):

While the idea of H2S acting as a regulator of HIV-1 latency is interesting, there is a long list of inconsistencies that hamper the enthusiasm for this manuscript.

Much of the cited literature that is used to make the case for their hypothesis is very old and actually refers to active HIV infection and patient studies prior to ART. Also, the literature they cite regarding the role of H2S as an antimicrobial agent seem to be limited to tuberculosis infection.

The choice of the latently infected model cell lines is rather unfortunate. There are much better defined models out there these days than J1.1 or U1 cells, such as the J-LAT cells from the Verdin lab or the various reporter cell lines generated by Levy and co-workers. In particularly, U1 cells should not be considered as latently infected, as the virus has a defect in the Tat/TAR axis and is mostly just transcriptionally attenuated. It is unclear why the authors only use J-LAT cells for one of the last experiments.

It is further unclear why the authors perform most of the experiments using U1 cells, which are considered promonocytic, but in the end seek to demonstrate the influence of H2S on latent HIV-1 infection in CD4 T cells. Performing all experiments in J1.1 or better J-LAT cells would have seemed more intuitive.

The authors suggest that H2S production would control latent HIV-1 infection and reactivation. Regarding the idea that CBS, CTH or possibly MPST would control latent infection as a function of their ability to produce H2S from different sources, there are several questions. First, if H2S is the primary factor, why would the presence of e.g. MPST no compensate for the reduction of CTH? Second, why would J1.1 and U1 cells both host latent HIV-1 infection events, however, their CDB/CTH/MPST composition is completely different? Third, natural variations in CTH expression caused by culture over time are larger than variations caused by PMA activation.

Also, the statement that H2S production as exerted per loss of CTH would control reactivation is not supported by the kinetic data. In latently HIV-1 infected T cell lines or monocytic cell lines, PMA-mediated HIV-1 reactivation at the protein level is usually almost complete after 24 hours, but at this time point the difference between e.g. CTH levels only begins to appear in U1 cells.<br /> The data for J1.1. are even less convincing.

Figure 2F. PMA is known to induce an oxidative stress response, however, in the experiments the data suggest that PMA results in a downregulated oxidative stress response. Maybe the authors could explain this discrepancy with the literature. In fact, both shRNA transductions, scr and CTH-specific seem to result in a lower PMA response.

Given that the others in subsequent experiments use GYY4137, which is supposed to mimic the increased release of H2S, the authors should have definitely included experiments in which they would overexpress CTH, e.g. by retroviral transduction. Specifically in U1 cells, which seemingly do not express CBS, overexpression of CBS should also result in a suppressed phenotype.

Figure 4F: The authors need to explain how they can measure a 4-fold gag RNA expression change in untreated cells. Also, according to Figure 4A, 300 µM GYY produces much less H2S than 5mM, yet the suppressive effect of 300 µM GYY is much higher?

Initially, the authors argue "that the depletion of CTH could contribute to redox imbalance and mitochondrial dysfunction to promote HIV-1 reactivation"(p. 9). Less CTH would suggest less produced H2S. However, later on in the manuscript they demonstrate that addition of a H2S source (GYY4137) results in the suppression of HIV-1 replication and supposedly HIV-1 reactivation. This is somewhat confusing.

CTH, or for that matter CBS or MPST do not only produce H2S, however, they also are part of other metabolic pathways. It would have been interesting and important to study how these metabolic pathways were affected by the genetic manipulations and also how the increased presence of H2S (GYY4137) would affect the metabolic activity of these enzymes or their expression.

H2S has been reported to cause NFkB inhibition by sulfhydration of p65; as such, the findings here are not particularly novel or surprising. Also, H2S induced sulfhydration is rather not targeted to a specific protein, let alone a HIV protein, making this approach a very unlikely alternative to current ART forms.

The description of the primary T cell model used to generate the data in Figure 6 is slightly misleading. Also, the idea of this model was originally to demonstrate that "block and lock" by didehydro-cortistatin is possible. In this application, the authors did not investigate whether GYY4137 would actually induce a HIV "block and lock" over an extended period of time.

The authors claim that the major conclusion of their study is that HIV-1 reactivation is coupled to depletion of endogenous H2S, which is associated with dysfunctional mitochondrial bioenergetics, in particular suppressed OXPHOS, GSH/GSSG imbalance, and elevated mitoROS. However, the authors never provide evidence that endogenous H2S is altered in latently HIV-1 infected cells (which may actually be an impossible task). By the end of the manuscript, the authors have not provided clear evidence that the effects of e.g. CTH deletion would be mediated by the production of H2S, and not by another function of the enzyme. Similarly, the inability of stimuli to trigger efficient HIV-1 reactivation following the provision of unnaturally high levels of H2S is not surprising given reports on the effect of GYY4137 as anti-inflammatory agent and suppressor NF-kB activation. Unless the authors were to demonstrate a true "block and lock" effect by GYY4137 the data will likely have limited impact on the HIV cure field.

Reviewer #2 (Public Review):

In this work, Van Winkle et al. examine contributions of interferons and microbiota to innate responses in the intestine, and which cell types are involved. Previous work by this team and others demonstrated that microbiota influence interferon responses in the intestine, which can affect infection with several enteric viruses, either increasing infection or decreasing infection depending on the viral system. Here, the team profiles expression of ISGs, examines which cells produce IFNs and express ISGs, whether these responses are microbiota dependent, and examines the effect on infection with murine rotavirus.

Strengths:

The most interesting aspect of this study is the observation that ISG expression in the intestine is extremely patchy and limited to a few mature enterocytes. Fig. 6 is stunning, and these data are supported by beautiful controls (robust/broad ISG expression everywhere in the intestine of mice treated IP with IFNlambda in Fig. S4, but loss of expression in mice treated with ABX, and confirmation in public single cell RNA-seq data sets). This is the most unique and significant contribution of the study.

Other aspects of the study are also well done with appropriate controls (multiple panels with ISG levels throughout, etc.). The team uses a variety of mouse strains, treatments, etc. to support their claims.

Weaknesses:

The primary weakness lies in significance, partially based on past work. The observation about patchy ISG expression in mature enterocytes is very cool, but it remains unknown why/how this happens and whether there are any functional consequences. This reviewer understands that this is a very tough problem and may take time to figure out. Additionally, much work has already been done with microbiota and IFNlambda effects on enteric virus infection, making many of the findings here overlapping or redundant with prior work: IFNlambda effects on IECs and viral infection (Sommereyns Plos Path 2008, Baldridge JVI 2017), leukocytes as the source of IFNlambda (Mahlakoiv Plos Path 2015), and microbiota-mediated innate immune modulation and effects of IFNlambda (e.g., Baldridge Science 2015, Nice Science 2015).

Reviewer #2 (Public Review):

In the manuscript "Coarse-grained model of mitochondrial metabolism enables subcellular flux inference from fluorescence lifetime imaging of NADH", the authors use fluorescence imaging to estimate NADH/NAD turnover flux and electron transfer rate in the mitochondria of mouse oocytes. Because of high spatial resolution of microscopy, the authors could also observe significant subcellular spatial gradient of oxidative flux in oocytes.