Reviewer #1 (Public Review):

Summary: In this manuscript the authors report an RNAi screen to identify proteins that, when depleted, alter nuclear shape and/or nuclear size. They demonstrate that the changes cannot be solely attributed to changes in the expression of nuclear lamins. Many of the hits are factors that impinge on histone modifications and chromatin biology. Comparing hits between fibroblasts and an epithelial cell type (MCF10) demonstrated relatively little overlap. The authors then relate their observations to a potential direct interaction between lamin A and histone H3 that, using histone peptide arrays, may be modulated by the methylation status. Last, the authors find that over-expression of some histone H3 variants/oncohistones alters nuclear appearance.

Overall assessment: The screening effort has revealed a number of interesting and novel suggestions of new modulators of nuclear appearance that are exciting and have the potential to be of value to the field. Unfortunately, the remainder of the manuscript is largely descriptive and rather superficial; perhaps most importantly validation experiments to rigorously confirm the screen "hits" are lacking. There are also concerns about the interpretation of biochemical experiments into lamin A-histone H3 binding although there are also some promising hints into the histone modification-dependence of lamin A binding to H3 that, if more fully investigated, would be an important contribution.

Major Points:

1. The discussion of the screen hits and prior knowledge key to their interpretation is lacking. For example, the authors only report on the purported localization of the hits without an unbiased analysis of their function(s). As a sole example, multiple members of the condensin complex are hits in Fig.1 while multiple members of the cohesin complex are hits in Fig. 2 - but there are many more factors worthy of further discussion. Moreover, the authors need to provide more information on the data used to assign the localization of the hits and how rigorous these assignments may be. For example, multiple CHMP proteins (ESCRTs) are listed - indeed CHMP4B is the highest scoring hit in Fig.1 - but this protein does not reside at the nuclear envelope at steady-state; rather, it is specifically recruited at mitotic exit to drive nuclear envelope sealing. Moreover, there are many hits for which there is prior published evidence of a connection to nuclear shape or size that are ignored: examples include BANF1, CHMP7, Nup155 (and likely far more that I am not aware of). This is a missed opportunity to put the findings into context and to provide a more mechanistic interpretation of the type of effects that lead to the observed changes in nuclear appearance. For example, there is already hints as to whether the effects occur as a mitotic exit defect versus an interphase defect, but conceptually this is not addressed.

2. Validation of the screen is lacking. There appears to be no evidence that the authors validated the initial screen hits by addition siRNA experiments in which the levels of the knock-down could be assessed. As an example: do nucleoporin hits decrease in their abundance at the nuclear envelope in these conditions? This validation is absolutely essential.

3. Differences in cell type - the authors' interpretation that a lack of overlap in the hits across cell types reveals that there are fundamentally cell type-specific mechanisms at play is a stretch. This could also reflect a lack of robustness in the screen, which should be addressed by directly testing the knock-down of the hits from one cell line in the other. Even if this approach reinforces the cell type specificity, the differences in the biology beyond the nucleus itself - an obvious example being the mechanical state of the cell - organization of the cytoskeleton, adhesions, etc that influence forces exerted on the nucleus are different rather than the nuclear response is different. These caveats needs to be explicitly acknowledged.

4. There are major issues with the interpretation of the presented biochemistry. For example, the basis for the supposed effect of monomer/dimer state of lamin is confusing and likely misinterpreted. It is well established that GST imposes dimerization on proteins expressed as GST fusions independent of cysteines. Any effect of DDT would have to manifest through some other mechanism (disulfides between the lamin domains - assumedly what the authors are thinking). Further, GST will impose dimerization of lamin A and lamin C in the co-incubation experiments. It is therefore entirely expected that if lamin A binds H3 and lamin C does not that the mixed dimers will bind H3 with lower affinity. Critically, this does not, however, address how full-length lamin C influences binding of lamin A to H3 in vivo. Last, how an effect of lamin C on lamin A would manifest through a disulfide bond in the nucleus, which has a reducing environment, is entirely unclear.

5. It is important for the authors to address the concept of nuclear size changes versus changes in the nuclear to cell volume ratio - biologically these could be quite different conditions, but obviously these cannot be distinguished by measuring nuclear volume alone. Addressing this experimentally would be best (to provide more depth to the size measurements).

6. There are important caveats to the approach of using the nuclear area as proxy measurement for nuclear size, most prominently that it is highly responsive to changes in nuclear height that can occur for a multitude of reasons (increased height = small radius and decreased height = larger radius), particularly given the different cell types. This needs to be acknowledged directly.

7. What is the evidence that the H3 effects manifest through lamins rather than directly?

8. Context is needed for the "methyl-methyl" histone states described as being the highest binders in the peptide array experiments. Are these states commonly found? Where in the genome? Does this match any DamID data? Again - more depth of investigation is required.

9. That oncohistones induce changes in nuclear shape or size does not mean that this is related to the mechanism in cancer. Also - how over-expression of H3 without its obligate partner H4 could disrupt the cell or an assessment of the extent of the oncohistone incorporation into chromatin achieved in these experiments makes it challenging to interpret.

10. Throughout the manuscript it would be helpful to the reader if the author would provide at minimum a brief statement on the previously identified functions of the hits that are explicitly discussed beyond their localization (membrane versus chromatin). References would also be helpful (for example, again - what is the evidence that SLC27A3 resides at the nuclear envelope?).

Reviewer #1 (Public Review):

The authors have used computational models and protein design to enhance antibody binding, which should have broad applications pending a few additional controls.

The authors' new method could have a broad and immediate impact on a variety of diagnostic procedures that use antibodies as sensitivity is often an issue in these kinds of experiments and the sensitivity enhancement achieved in the two test cases is substantial. Affinity maturation is a viable approach, but it is laborious and expensive. If the catenation method is generalizable, it will open up opportunities for antibody optimization for cases where affinity maturation is either not feasible or otherwise impractical. Less clear is how this method might enhance therapeutic potency. Issues that arise when using therapeutic antibodies are often multifactorial and vary depending on the target and disease state. Many issues that occur with antibody-based therapies will not be rectified with affinity enhancement.

Reviewer #1 (Public Review):

In this paper the authors reconstruct the ancestral states of the body sizes and genomes of Xenarthrans (sloths, armadillos, anteaters) to understand whether duplications of genes that reduce cancer risk are associated with large body size, as has previously been found in Proboscideans (elephants and mammoths). The strong points of the paper are that Xenarthran cells are particularly sensitive to DNA damage, which induces cell death, and that nine-banded armadillos have strikingly little cancer. They also present comparative evidence on the doubling times of cells in culture, but their conclusions are compromised by the small sample size - one individual - for sloths. The data on which their inferences are based do not yet allow them to decide whether large body size evolved before the gene duplications that reduce cancer risk, or vice versa. The main impact of this work is likely to be additional focus on nine-banded armadillos in cancer research, with an emphasis on the discovery of the mechanisms mediating the effects. It should also spur attempts to recover genomes from soft tissues of large-bodied Xenarthran fossils; that may be possible for giant ground sloths.

Reviewer #1 (Public Review):

In this manuscript, Smith et al. evaluate whether phenotypic plasticity and/or species sorting (changes in community composition) occur during a four-week-long incubation of a single soil at a range of temperatures. By using a relatively simple setup and restricting their cultivation to relatively fast-growing taxa well-suited to growth in the lab, the authors were able to measure a commendable number of traits and successfully evaluate the thermal niche of the majority of organisms tested. The authors did a very thorough job of explaining how they came to the conclusion that species sorting is the dominant driver of community-level adaptation to temperature in their experiment, and they do an outstanding job using other literature to support and contextualize these conclusions. I also commend the authors for not overstating the relevance of their results and sticking to the conclusion that this is a possible range of responses rather than concluding that the patterns observed for these taxa are representative of how dominant soil bacteria are responding. Overall this is a very good paper and sets the stage well for future work in, for instance, constraining community turnover vs. acclimation in trait-based carbon cycling models.

Reviewer #1 (Public Review):

This is a well performed study to demonstrate the antiviral function and viral antagonism of the dynein activating adapter NINL. The results are clearly presented to support the conclusions.

This reviewer has only one minor suggestion to improve the manuscript.

Add a discussion (1) why the folds of reduction among VSV, SinV and CVB3 were different in the NINL KO cells and (2) why the folds of reduction of VSV in the NINL KO A549 and U-2 OS cells.

Reviewer #1 (Public Review):

In this study, the authors performed scRNA-seq analysis of iNKT cells from spleen and adipose tissue at steady state and after short-term, long-term, and repetitive ⍺-GalCer stimulation in vivo. They found iNKT cells undergo rapid and extensive transcriptional remodeling during activation. By reanalyzing published scRNA-Seq data of human iNKT cells, the authors found transcriptional signatures of iNKT cell activation are conserved across species. in addition, they showed, adipose NKT10 cells, had blunted response to ⍺-GalCer and expressed markers associated with Tr1 cells. Furthermore, they demonstrated two memory-like iNKT cell populations, expressing immunoregulatory cytokines and maf (cMAF+ iNKT cells) or cytotoxic markers and klrg1 (KLRG1+ iNKT), were constitutively present in adipose tissue, and were induced in the spleen following ⍺-GalCer challenge. Overall, this study provides novel insights into the transcriptional program of activated iNKT cells and the phenotype of regulatory iNKT cells. The bioinformatic aspect of this study is well performed, but the immunology and T cell biology aspects could be strengthened.

Reviewer #1 (Public Review):

Champer et al. evaluate two homing drives that have been developed in the Anopheles mosquito. Variants of one of these (zpg) are possibly being further investigated for an eventual release. Work with the other has seemingly been discontinued because of unintended fitness costs. The authors argue that this second drive may be in fact better if the experimental results are interpreted more favourably. An important point if true, but somewhat separate from the findings in the paper. To a large extent, this point could be made without any of the results in the paper. However, the authors do show through modelling that this difference may in fact be relevant.

This careful justification of the model parameters increases its relevance to the evaluation of those specific gene drives. The zpg drive will likely be extensively investigated and the specific relevance of this work is a valuable contribution. While a range of parameters is tested for each expression pattern, there are no step-by-step investigations of how the drive outcomes are effect by changes to the underlying DNA-repair/deposition/fitness parameters. So while a reader may learn one drive is better than the other, the ability to get a deeper understanding of the underlying relationship is limited. This means this work has a more limited scope and relies on the relevance of the chosen parameters. In that regard, there may be room for improvement. The chosen parameters for zpg and nos may not be completely fair in regards to the target site and I believe this needs to be addressed.

The second aspect of this paper is the comparison between the commonly used panmictic modelling approach and spacial models. This also somewhat relies on the drive parameters being chosen well, as a more comprehensive evaluation of the spacial approach has been done in prior work by this group. However, showing that these particular extremely efficient drives may still struggle when additional spacial factors are considered is useful and relevant. That a second Anopheles-specific spacial model further reduces the drive performance is a relevant finding. This is helped by a specific analysis of the effect of changes to the migration rates and the low-density growth rate. This spacial modelling also has relevant findings for the homing X-shredder design.

Reviewer #1 (Public Review):

The molecular mechanism of articular chondrocyte differentiation has not been fully revealed. In this study, the authors identified NFATc1 as a key regulator of articular chondrocyte differentiation during early mouse development. At E13.5, NFATc1-expressing cells were mainly located in the flanking region of the joint interzone. With cartilage development, NFATc1-expressing cells generated most of articular chondrocytes. Through transcriptome analyses the authors showed a set of genes expressed in NFATc1-enriched articular cartilage progenitor cells. The expression of NFATc1 was diminished during articular chondrocyte differentiation. The authors found that suppression of NFATc1 expression in articular cartilage progenitor cells is sufficient to induce spontaneous chondrogenesis; while overexpressing NFATc1 suppresses chondrogenesis. They further demonstrated that NFATc1 negatively regulated Col2a1 gene transcription. This is an important study since it will help us understand the regulatory mechanism of articular chondrocyte differentiation and pathological mechanisms of joint diseases, such as osteoarthritis.

Reviewer #1 (Public Review):

The authors show that LPS activates Pink1-Parkin-dependent mitophagy in lung endothelial cells, which is mediated by TNFα. Endothelial-specific Pink1-KO improves LPS-induced inflammatory responses in mice and reduces the release of one of the mitochondrial formylated proteins, ND6. These results suggest that PINK1-dependent endothelial mitophagy is pro-inflammatory and increases the release of mitochondrial formyl peptides, one of the mitochondrial DAMPs. The identification of the origin of serum formyl proteins and the elucidation of the release mechanism would be important.

The data are generally clear and convincing. The authors' conclusion would be strengthened if the authors could show that serum ND6 levels during inflammation is indeed regulated by endothelial mitophagy using their endothelial-specific Pink1-KO mouse model.

Reviewer #1 (Public Review):

This study sets out to decipher whether the eDNA that promotes biofilm dispersal in Caulobacter crescentus biofilms is released when a random portion of cells lyse within biofilms, or whether eDNA release is a regulated process. They start by investigating whether any of the C. crescentus TA systems contribute to biofilm-associated cell death, and find that one of the systems, ParDE4 is responsible for cell death and eDNA release. They go on to show that this system is O2-regulated and thus contributes to cell death in particular in the oxygen limited interior regions of biofilms. These findings contribute significantly to our understanding of the biological functions of toxin-antitoxin systems, mechanisms of bacterial programmed cell death, and biofilm growth. The notion that TA systems function in cell death in particular has been controversial, and often based on overexpression of the toxin component, therefore the fact that this study uses a TA system in its native genomic context is notable. The authors also show clearly the somewhat counterintuitive result that the cell death (and presumably, toxin activity) is negatively correlated with transcription of the TA system. This is consistent with what is known about TA biology (but not with many past TA papers, which often correlated TA transcription with toxin activation). The study also provides a logical rationale for how ParDE4 mediated cell death ultimately contributes to bacterial fitness. The paper is well written and figures are clear and easy to follow.

There are two relatively minor shortcomings of the paper, both acknowledged as caveats by the authors in their discussion. First, while the authors do include one experiment that addresses whether the toxin is responsible for the cell death (Fig 3), they do not show direct evidence of the activity of the toxin other than cell death/eDNA release. Second, the authors do not address whether the reduced TA transcription they observe is what causes the release of the toxin and thus the cell death phenotype. This seems likely to be the case based on previous studies of other TA systems (e.g. TA systems involved in plasmid segregation, most clearly shown for CcdAB, or more recently the ToxIN system during phage infection). Connecting this directly would be a very valuable addition to this study.

Reviewer #1 (Public Review):

The findings reported in this paper demonstrate that integration of Wnt and BMP signaling by Axin1 is crucial for lower limb development, and defects in Axin1 and Axin2 signaling could lead to the development of FH disease.

Reviewer #1 (Public Review):

The manuscript by Dolan et al. presents a high-resolution structure of the SARS-CoV-2 M (membrane) protein, determined by cryo-electron microscopy. Despite the protein's small size (50 kDa as a homodimer), the structure is well-determined and of sufficient resolution to build a confident model for the vast majority of the protein chain (missing only a short disordered N-terminal tail). The protein forms a homodimer with each protomer possessing three transmembrane helices and a beta-strand rich C-terminal domain. The overall structure of M is similar to that of ORF3a, a viral-encoded pore protein. The cytosolic surface of M's C-terminal domain is highly positively charged, and the authors propose that this charge mediates interactions with the N protein, S protein, and possibly viral RNA. Finally, the authors perform molecular dynamics simulations that demonstrate that the M dimer is relatively stable, at least over the time-frame of the simulation (1.6 microseconds).

Overall, this is a straightforward work that describes the structure of an important protein in the life cycle of SARS-CoV-2. As such, it is important and timely, and will be of interest to a broad set of readers. The work suggests many directions for future experiments.

Reviewer #1 (Public Review):

This paper follows several innovative articles from the authors exploring the molecular mechanisms of insulin and IGF1 receptors activation by their ligands using cryo-electron microscopy. Here the authors explore the role of an alpha helical C-terminal segment (called the alpha-CT motif) of a disordered disulfide-linked insert domain in the FnIII-2 module of the insulin and IGF1 receptors (at the end of the alpha subunit), in the mechanism of ligand binding, negative cooperativity and receptor activation.

Biochemical data gathered over several decades have suggested that insulin and IGF1 use two separate binding sites, site 1 and site 2, to bind to two distinct domains (sites 1 and 2, and 1'and 2') on each protomer of the homodimeric receptors, disposed in an antiparallel symmetry. This disposition was corroborated by the early x-ray crystallographic studies of the unliganded insulin receptor ectodomain (apo-receptor). A subsequent somewhat surprising finding was that the insulin receptor site 1 is in fact a composite, made of the beta surface of the L1 module of one protomer, and of the alpha-CT motif of the other protomer which binds perpendicularly to the L1 surface (a "tandem binding element"), with insulin binding more to the alpha-CT motif than to L1.

Previous work from the authors showed that the subsaturated insulin receptor has an asymmetric configuration while the receptor saturated with 4 insulins has a symmetric T-shaped configuration. In contrast, the IGF1R shows only one IGF1 bound to an asymmetric configuration, indicating according to the authors a stronger negative cooperativity. This is attributed to a more rigid and elongated conformation of the alpha-CT motives that restricts the structural flexibility of the alternate binding site.

To test this hypothesis, the authors determined the cryo-EM structure of IGF1 bound to IGF1R with a mutated alpha-CT motif elongated by four glycine residues. Strikingly, a portion of these constructs adopt a T-shaped symmetric structure.

Conversely, they show that the cryo-EM structure of insulin bound to an insulin receptor with non-covalently bound alpha-CTs insert domains by mutation of the cysteines to serine adopts asymmetric conformations even at saturated insulin concentrations. They conclude that the alpha-CTs in disulfide-linked insert domains of the insulin receptor play an important role in the structural transition from asymmetric to symmetric during the insulin-induced insulin receptor activation.

All in all, this is a very interesting and well-designed study that represents an advance in the knowledge of the insulin/IGF1 receptor systems, although the details of the structural interpretations deserve some discussion.

Joint Public Review:

As demonstrated in alpha genus human papillomavirus (HPV) 16 positive head and neck squamous cell carcinoma, Hu et al. report that the E6 protein of beta genus HPV8, which is implicated in the development of skin cancer, promotes genomic instability by increasing use of error-prone alternative end-joining repair. Liu et al. (2018) showed that loss of TGFβ signaling compromised HR in HPV+ head and neck squamous cell carcinomas (HNSCC) and shifted repair to alt-EJ. A follow up paper in 2021 showed that cancers with an alt-EJ gene signature have high frequency of microhomology flanked indels, pathognomonic for alt-EJ repair. Leeman et al. (2019) demonstrated that HPV16 E7 promotes error-prone, alt-EJ and suppresses NHEJ. Hence the finding that E6 from beta HVP8 does so as well is not unexpected but it is important to provide convincing experimental evidence as is done in this manuscript. Here the authors confirm and extend earlier studies (Hu et al., 2020; Hu and Wallace, 2022; Wallace et al., 2015) showing that loss of p300, a transcription factor necessary for robust expression of key DNA repair genes, impairs execution of HR and NHEJ, which is a prerequisite for driving up use of alt-EJ as a salvage path. Both pathways are inhibited past the initiation step. During NHEJ 8E6 allows DNA-PKcs assembly and activation at DSBs but attenuates downstream steps, Likewise, during HR 8E6 allows assembly of RAD51 foci but blocks their processing. As 8E6 does not block but rather delays DSB repair, this manuscript provides convincing evidence that alternative end-joining of DSBs is increased in 8E6 expressing cells. The study employs gamma-H2AX foci as a surrogate for DSB levels and employs appropriate reporter assays to monitor HR and alt-EJ. Genomic DNA sequencing of 8E6 expressing human foreskin keratinocytes and control cells documents the typical genome scars of elevated alt-EJ including small deletions flanked by microhomology and small templated insertions. The results contribute to our understanding of DSB repair pathway control and may explain the association of HPV8 with nonmelanoma skin cancer, although this tumor type specificity remains unclear. A key limitation of the study that it is not established which alt-EJ pathway is active in 8E6 expressing cells, in particular whether DNA polymerase theta (POLθ) is involved. The mechanism by which p300 favors NHEJ and HR and its absence favors alt-EJ remains to be determined.

Reviewer #1 (Public Review):

This manuscript investigates the KOW domain of the fold switching, NusG protein family. E. coli RfaH-KOW is known to form an a-helical hairpin when docked onto the NGN domain and generate an auto-inhibited conformation, which blocks access to the RNA polymerase binding site. Upon activation, this helical KOW subdomain can refold into a beta-barrel structure that then is important for making contacts to ribosomes. In this manuscript the authors identify and structurally characterize RfaH protein from Vibrio cholerae, which has only ~36% sequence identity with EcRfaH, yet displays similar fold switching ability. In addition, the authors provide thermodynamic measurements and some structural information on 4 KOW domains from different organisms, and show that it is the instability in their β-barrel structure that enables the conformational plasticity and fold switching ability of these proteins.

Reviewer #1 (Public Review):

This is a well-done analysis using the very robust Swedish national population registry.

The study strengths include large size, prolonged follow-up, and use of two comparison populations.

The main limitations which need to be addressed by the authors are accounting for reverse causality, namely if a psychiatric illness (PI) developed before or about the same time as the CVD. The much steeper risk relationships early after a CVD event are so suggestive. Some further analyses to tease out those with clearly NO PI before CVD would be in order.

Second, for the robust matched cohort design, the authors age and sex matched each patient with 10 individuals from the general population and then also stratified their model by the matching variables. Could adjusting for matched factors in such cohort studies re-introduce bias into these estimates?

Third, the range of PIs associated with CVD is a lot broader than would be expected or unexpected (eg eating disorders!).

Lastly, the authors should try to account for secular changes in smoking and alcohol consumption or BMI over the study period. In particular, while Sweden never had very high smoking rates (due to Snus) alcohol use within specific cohorts might have both affected CVD risk (particularly stroke) and PI risk. Examining trends in for example liver cirrhosis over the study time period might help or use sales/consumption data. The authors do recognize a limitation in being unable to adjust for smoking, alcohol, and adiposity.

Some additional analyses to address these points and some more caution in the discussion are required.

Reviewer #1 (Public Review):

The paper of De Agro et al. proposes a new paradigm to measure wanting (binary choices) and liking (pheromone deposition) in ants in order to test bundling and segregation effects on reward processing.

By using three different treatments: A) rewards (sugar drops) and costs (runway segments) are segregated; B) rewards are segregated and costs bundled; C) rewards and costs are bundled, the authors observed that the main predictor of pheromone release was the segregation of the runaway segments rather than segregation of the reward. Furthermore, no effect of treatment was observed on preferences for the odor associated with the treatment.

The authors interpret their finding as a clear demonstration of segregation effects on liking, but not wanting, which was present only for costs but not rewards.

Strengths: I appreciated the creativity and effort in conducting complex experiments and measurements in insects. Overall, the paper is the first of its kind to propose a method to test reward processing in insects. The design is well thought and the results are straightforward. The analyses seem to be appropriate.

Weaknesses: My main concern relates to the interpretation of the pheromone release as an index of liking. I am not an expert in the field, but I would probably go for a more parsimonious explanation: the effect could be simply due to the quantity of liquid ingested (and therefore corresponding caloric intake). Did you check whether, in the conditions showing the biggest pheromone release, the ants consumed the biggest quantity?

First, this could explain for example the puzzling difference observed in the 3 cohorts and the sequence effects.

Second, a reduced overall caloric intake could also explain why segregated costs seem to drive the results. Digestive processes are possibly kicking in at different times in the segregate all conditions compared to the other two, due to the more time-delayed ingestion of food (i.e. we tend to eat less if we have longer time between meals).

Finally, this account may also explain the reported difference between wanting and liking, as here the release of pheromone is simply the byproduct of how much sugar has been ingested (and possibly nothing to do with reward processes).

If pheromones are released proportionally to sugar intake and if sugar intake was different between conditions, is an important point that should be clarified in the manuscript, in order to guarantee interpretability of the results

Reviewer #1 (Public Review):

This manuscript proposes a spiking network model of the hippocampal circuit, in which spike-time-dependent plasticity leads to the learning of the successor-representation, i.e. a predictive map of the environment. More specifically, the network consists of two layers representing the CA1 and CA3 regions and the connections between the layers are plastic. The main result is that the resulting plasticity process on behavioural timescales can be mapped onto temporal difference learning so that the weights between the two layers learn the successor representation.

Strengths:<br /> - this work presents a model that links two very different levels of description, a biophysical spiking model and reinforcement learning<br /> - analytical results are provided to support the results<br /> - the model provides a framework to implement discounting in continuous time, alleviating the need to discretise time.

Weaknesses:<br /> - the successor representation is learned at the level of synaptic weights between the two layers. It is not clear how it is read out into neural activity and exploited to perform actual computations, as both layers are assumed to be strongly driven by external inputs. This is a major limitation of this work.<br /> - one of the results is that STDP at the timescale of milliseconds can lead to learning over behavioral timescales of seconds. This result seems related to Drew and Abbott PNAS 2006. In that work, the mapping between learning on micro and macro timescales in fact relied on precise tuning of plasticity parameters. It is not clear to which extent similar limitations apply here, and what is the precise relation with Drew & Abbott.<br /> - most of the results are presented at a formal, descriptive level relating plasticity to reinforcement learning algorithms. The provided examples are quite limited and focus on a simplified setting, a linear track. It would be important to see that the results extend to two-dimensional environments, and to show how the successor representation is actually used (see first comment).<br /> - the main text does not explain clearly how replays are implemented.

Reviewer #1 (Public Review):

In this interesting study, which focuses on evolution of jointed jaws, the authors identified a conserved non-coding sequence motif JRS1 downstream of the Nkx3.2 gene, which has an established role in patterning joints. JRS1 is present in most vertebrates with jointed jaws, but apparently absent in jawless hagfish. The authors show that the enhancer has likely binding sites for transcription factors that are known players in skeletal patterning. This section could be improved by validation to demonstrate that one or more of the putative TFs does indeed bind the JRS1.

The authors then take the JRS1 element from various species and use these to drive fluorescent proteins in the zebrafish. Using beautiful imaging, they show that the sequence derived from all species tested leads to expression that is restricted to the joint site. This is very compelling.

The authors also delete JRS1 from the zebrafish genome and show that while nx3.2 expression levels are comparable, the larvae have transient abnormalities in joint patterning, including partial joint fusions. These experiments are compelling, but would be enhanced by characterisation of local changes to chondrocyte maturation.

Reviewer #1 (Public Review):

This work employs high-density electrodes to study functional connections between pairs of neurons within local cortical networks of nonhuman primates. The work aims at providing a proof of principle that using high-density electrodes dramatically increases the number of identified functionally connected neuron pairs, which in turn allows for studying the interactions within local cortical circuits. The work also leverages the large number of identified correlated neuron pairs to study the interactions within and between cortical layers.

Strengths:<br /> Using high-density electrodes (Neuropixels probes) to study interactions within the visual cortex in nonhuman monkeys is elegant because the Neuropixels probes allow recording neuronal activity across the entire depth of the cortical column simultaneously. Moreover, due to the dense sampling, the number of identified single neurons is large (115-221 neurons) and the number of measured interactions between pairs of neurons, via cross-correlation analysis, is impressive (~68000). Thus, high-density electrodes are ideally suited to study interactions within cortical circuits in animals with thick cortices, like the nonhuman primate. This work is a proof of principle that this can be achieved and will likely impact the field.

Weaknesses:<br /> Although the paper does provide rich information on interactions within local cortical circuits, the main weakness of the paper is using the term "functional connection" in an imprecise manner. Cross-correlograms (CCG) of spike trains of pairs of neurons show different shapes depending on the underlying connectivity and not all significant peaks in CCGs reflect functionally connected neuron pairs. For example, CCGs of synaptically connected neuron pairs show a transient peak that is offset from the 0-ms lag due to the synaptic delay. CCGs with this shape thus reflect "functionally connected neuron pairs". In contrast, common inputs to pairs of neurons can induce significant peaks in CCGs, despite the fact that these neurons are only correlated but not functionally connected (e.g. Ostojic et al. 2009). Therefore, taking the shape of significant CCGs into account is important when discussing "functionally connected neuron pairs". While the authors mention this point in the paper, the term "functional connection" is nonetheless used irrespective of the CCG shapes which can be confusing to the reader. Moreover, the authors claim that the method allows identifying "1000s of functionally connected neuronal pairs". This statement is likely not fully supported by the data, evident by the fact that CCGs with the shape of mono-synaptic connections (transient and non-zero lag peak) are not among the distinct classes of CCGs shown in Figure 4.

Reviewer #1 (Public Review):

The authors start the study with an interesting clinical observation, found in a small subset of prostate cancers: FOXP2-CPED1 fusion. They describe how this fusion results in enhanced FOXP2 protein levels, and further describe how FOXP2 increases anchorage-independent growth in vitro, and results in pre-malignant lesions in vivo. Intrinsically, this is an interesting observation. However, the mechanistic insights are relatively limited as it stands, and the main issues are described below.

Main issues:

1. While the study starts off with the FOXP2 fusion, the vast majority of the paper is actually about enhanced FOXP2 expression in tumorigenesis. Wouldn't it be more logical to remove the FOXP2 fusion data? These data seem quite interesting and novel but they are underdeveloped within the current manuscript design, which is a shame for such an exciting novel finding.

Along the same lines, for a study that centres on the prostate lineage, it's not clear why the oncogenic potential of FOXP2 in mouse 3T3 fibroblasts was tested.

2. While the FOXP2 data are compelling and convincing, it is not clear yet whether this effect is specific, or if FOXP2 is e.g. universally relevant for cell viability. Targeting FOXP2 by siRNA/shRNA in a non-transformed cell line would address this issue.

3. Unfortunately, not a single chemical inhibitor is truly 100% specific. Therefore, the Foretinib and MK2206 experiments should be confirmed using shRNAs/KOs targeting MEK and AKT. With the inclusion of such data, the authors would make a very compelling argument that indeed MEK/AKT signalling is driving the phenotype

4. With the FOXP2-CPED1 fusion being more stable as compared to wild-type transcripts, wouldn't one expect the fusion to have a more severe phenotype? This is a very exciting aspect of the start of the study, but it is not explored further in the manuscript. The authors would ideally elaborate on why the effects of the FOXP2-CPED1 fusion seem comparable to the FOXP2 wildtype, in their studies.

5. The authors claim that FOXP2 functions as an oncogene, but the most-severe phenotype that is observed in vivo, is PIN lesions, not tumors. While this is an exciting observation, it is not the full story of an oncogene. Can the authors justifiably claim that FOXP2 is an oncogene, based on these results?

6. The clinical and phenotypic observations are exciting and relevant. The mechanistic insights of the study are quite limited in the current stage. How does FOXP2 give its phenotype, and result in increased MET phosphorylation? The association is there, but it is unclear how this happens.

Reviewer #1 (Public Review):

The authors probe the interaction between the influenza A M2 channel and lipid membrane using a multi-scale computational approach. Using extensive atomistic simulations and different starting structures, the authors are able to probe how various structural features of the M2 channel (e.g., symmetry and AH orientation) impact the properties of nearby lipids, such as bending and lipid tilt. The atomistic protein structures are then used together with a continuum mechanics model for the membrane to estimate the stability of the channel in membranes of different shape (e.g., positive or negative Gaussian curvature). While the energetic consequences were relatively modest, on the scale of a few kT, the results are consistent with experimental observation that M2 channel does not favor convex spherical caps. The symmetry-broken conformations were found to be stabilized by membrane of negative Gaussian curvature, which is important to the fission process. Therefore, the insights gleaned in this work can potentially lead to novel strategies that screen for drug molecules that stabilize fission-incompetent conformations of the M2 channel.

Reviewer #1 (Public Review):

High resolution mechanistic studies would be instrumental in driving the development of Cas7-11 based biotechnology applications. This work is unfortunately overshadowed by a recent Cell publication (PMID: 35643083) describing the same Cas7-11 RNA-protein complex. However, given the tremendous interest in these systems, it is my opinion that this independent study will still be well cited, if presented well. The authors obviously have been trying to establish a unique angle for their story, by probing deeper into the mechanism of crRNA processing and target RNA cleavage. The study is carried out rigorously. The current version of the manuscript appears to have been rushed out. It would benefit from clarification and text polishing.

Reviewer #1 (Public Review):

Voltage-gated sodium channels are fundamental in the generation and transmission of painful signals. For this reason their inhibition has been proposed as a potential way to treat the worst forms of chronic pain. Since the main subtype of sodium channels involved in pain signaling is Nav1.7, its important that potential inhibitors target this subtype with high efficacy and in a selective manner.

In this manuscript, the authors set out to improve on a peptide, ProTxII, which had been previously put forward as a promising blocker of Nav1.7 channels. For this task, they develop a computational workflow that is based on in silico manipulations of the interaction of ProTxII with a Na channel structure determined previously and evaluation of the predicted mutations with electrophysiology. The method employs previously validated algorithms implemented in Rossetta.

The authors succeed in producing two peptides with improved selectivity for Nav1.7 over other subtypes and capable of blocking at low nanomolar concentrations.

The method seems to be robust enough to be implemented for similar tasks in other protein-protein interaction scenarios, although this remains to be proven.

The results and methods presented here should be useful in several ways. First, the developed peptides can be further evaluated in a clinical setting or at least serve as a scaffold to develop further. Second, the methods should be useful to other groups working on biologicals as clinical pharmacological agents and in pure biophysics to probe surfaces of interactions.

Reviewer #1 (Public Review):

The author's stated goal was to determine how many unique populations of neurons there are in PB, whether these populations occupy discrete subnuclei in PB, and whether they project to and receive inputs from specific brain regions. They have succeeded admirably. This work presents the field with a valuable reference tool that will allow us to formulate testable hypotheses about the structure and function of PB, and to design tools to selectively manipulate discrete populations of PB neurons.

Reviewer #1 (Public Review):

Mollentze et al. seek to understand how models to predict species susceptibility to sarbecovirus infection/spillover could be improved and extended. The authors assemble a useful dataset identifying and prioritizing evidence of susceptibility of all animals tested thus far across four classes of experimental study. They appropriately address many questions on data inclusion and bias. Some details of data inclusion and weighting could be more carefully considered, for example the inclusion of native reservoir Rhinolophus bats for which virus:ACE2 arms races drive different dynamics of susceptibility/exclusion than for other species where sarbecovirus spillover is more novel or transient. There is also conflation of ACE2-based metrics like cell culture heterologous susceptibility in the training dataset when true susceptibility is the intended predictive feature may be further confounding model performance. However, as the authors point out in a nicely written Discussion, details of data availability (e.g., ACE2 sequence) are much more limiting in light of observations of widespread animal susceptibility, and that perhaps models of individual species susceptibility (especially based on ACE2 sequence alone) will be better complemented with more careful details of ecological and epidemiological relevance.

Reviewer #1 (Public Review):

The authors developed a structural model for the integral membrane AT3 domain and showed that it adopts a novel fold. The structural model is shown to be stable in molecular dynamics simulations and exhibit structural and dynamic features that are consistent with the function of the AT3 domain. The locations of key residues in the structural model are also consistent with functional studies in the literature. The potential binding site of the acetyl-CoA was also evaluated with a quantum mechanical computation, which supported strong binding interactions. The model will play a major role in guiding future experimental studies for targeted mechanistic analyses for this class of important proteins.

Reviewer #1 (Public Review):

The goal of Han and colleagues is to define the role of myeloid cells in diffuse alveolar hemorrhage (DAH), a murine model of pulmonary vasculitis mimicking that found in lupus and induced by peritoneal administration of pristane to B6 mice. The authors characterize circulating and peritoneal myeloid cells in the DAH model, compared to disease-resistant controls, with the principal findings that: 1) DAH is dependent upon monocyte egress from the bone marrow (BM) as opposed to pulmonary resident myeloid cells, as evidenced by its absence in mice deficient in CCR2, and 2) circulating Ly6Clo cells are comprised of 2 subsets, including a CD138+ one development of which is NR4a1 (Nur77) dependent and which expands in association with, but is not required for development of, DAH, and which is akin to circulating NR4a1-dependent Ly6Clo cells known to be important for maintenance of vascular integrity, and a Ly6Clo NR4a1- independent one, also previously described, function of which is enigmatic. The former subset also expresses TREML4, expression of which is dependent upon NR4a1 and inflammatory signals. The authors propose that pristane-induced pulmonary vasculitis stimulates production of an inflammatory-induced Ly6Clo monocyte subset important for vascular stability, yet ineffectual is controlling pulmonary vasculitis.

The novel findings are that pulmonary vasculitis is dependent upon BM-derived monocytes, and that the Ly6Clo circulating pool can be divided into two populations based upon NR4a1-developmental dependence and CD138 expression, those that are NR4a1-dependent CD138hi and expanded in vascular injury, and those that are NR4a1-independent CD138lo. Additional strengths of the work are the clear phenotypic analysis with genetic support and correlation to clinical outcome.

Yet, the role of NR4a1-dependent CD138hi cells in vascular injury, either contributing to persistence of damage or ineffectually attempting to resolve it, remains uncertain, as does the apparently unique role of CD138 on these cells and their relationship to the Ly6Clo, NR4a1-independent CD138lo subset and function of the latter. Further dissection of these issues would strengthen the work beyond the clear phenotype-clinical correlations that are made.

Reviewer #1 (Public Review):

In this work, the authors were trying to develop an approach for microindentation-based spatial mapping of articular cartilage of mouse femur. Because mouse cartilage in articulating joints is incredibly thin and challenging to indent repeatably and reliably, a need exists to increase resolution of indentation spacing on very small surfaces, improve sensitivity of indentation (e.g., surface detection), and reduce error and improve accuracy of indentation measurements. Using a relatively new multiaxis material test stand with repositioning capabilities and multi axis load cells, the authors developed a spatial indentation test protocol as well as used this array-based approach to measure cartilage thickness via needle probing. They then validated thickness measurements generated using needle probing with high resolution 3D x-ray imaging using contrast enhancement with phosphotungstic acid (PTA). The authors then compared cartilage thickness and indentation mechanical properties between wild type (C57BL6J) and Prg4 mutant mice.

This work is rigorous and includes new techniques that are validated using orthogonal approaches. Some of the techniques used in this work, especially indentation-based mapping of cartilage stiffness in small mouse joints, have been challenging for the field to overcome. This is especially true with the exploding number of small animal studies investigating cartilage health in transgenic mouse strains and injury models. While innovative and important, there remain a few key experiments that would help with validation of the data acquired in these experiments.

Specifically, a general rule of thumb for indentation testing is to test no more than 1/10th the thickness of the indented material. Because the cartilage thickness of the medial condyles (~0.04mm) was only ~2x that of the indentation depth used for automated indentation mapping (0.02mm), it is possible that this thin region of cartilage will lead to substrate effects from the subchondral bone on the indentation data. It is unclear if the indentation measurements are characterizing cartilage or substrate properties. This may not be a major issue for healthy, intact cartilage (including in the mutant strains) but will likely have a major impact on interpretation of results following cartilage degeneration and loss.

It is unclear if damage was caused by the 0.02mm indentations because the XRM scanning occurred after needle probing tests. The "bands" observed in the 3D XRM imaging following both indentation and needle probing (Fig 2A2) suggests that the indentation probes and individual needle probings at each site are not perfectly overlapping. Surface congruency of the cartilage suggest valley formation at indentation sites.

Reviewer #1 (Public Review):

McKey et al. describe mouse ovary morphogenesis in detail using state-of-the-art microscopy and imaging techniques. The authors visualize fetal and perinatal ovary in situ in the context of the whole embryo. They find that three tissues closely associated with the ovary: the ovarian ligaments, the Müllerian duct and the rete ovarii dynamically correlate with ovary morphogenesis. They also find that different combinations of Pax2 and Pax8 deletion alleles affect the oviduct and/or regions of the rete ovarii differentially, and lead to disruptions in ovary morphogenesis.

Strengths:<br /> The detailed analysis and images. The analysis of ovary morphogenesis in the context of surrounding tissues.

Weaknesses:<br /> The molecular analysis of mutant conditions would gain with more detailed cellular observations.

Reviewer #1 (Public Review):

Grande et al report the results of a series of functional connectivity experiments that build upon and extend results reported in Maass et al. (2015). The authors conducted three separate but interrelated analyses with a primary aim of characterising entorhinal-hippocampal processing pathways in the human brain.

The first analysis served to identify subregions within the entorhinal cortex (EC) that preferentially connect with the retrosplenial cortex (RSC), posterior parahippocampal cortex (PHC) and perirhinal areas 35 (A35) and 36 (A36). The results of this analysis revealed that the RSC and PHC preferentially connect with the anterior medial EC and posterior medial EC respectively while A35 and A36 preferentially connect with the anterior lateral EC and posterior lateral EC respectively. In a second analysis, the authors evaluated patterns of functional connectivity between the four entorhinal subregions identified in Analysis 1 and specific subfields of the hippocampus, namely the subiculum and CA1. The authors provide evidence that each EC subregion preferentially connects with specific regions along the transverse (medial-lateral) axis of the subiculum and CA1.

In a third analysis, the authors investigated whether 'object' and 'scene' information is differentially processed within EC subregions and along the transverse axis of the subiculum and CA1. Results revealed that the posterior medial EC and distal (medial) subiculum were preferentially engaged by 'scene' stimuli. In contrast, anterior regions of the EC and the CA1/subiculum border were equally engaged by 'object' and 'scene' stimuli. The authors propose that the posterior medial EC and distal subiculum may represent a unique route for scene/contextual information flow while anterior regions of the EC and the CA1/subiculum border may be involved in integrating both 'scene' and 'object' information.

Overall, the study was well-motivated, well-designed and appropriately analysed to address the research questions. The conclusions of the paper are well supported by the data.

The primary novelty of these results relate to the characterisation of how the RSC, PHC, A35 and A36 functionally connect with different portions of the EC and how, in turn, these EC subregions preferentially connect along the medial-lateral axis of the subiculum and CA1. These new and detailed insights will have an impact on and advance current theoretical models of entorhinal-hippocampal functional organisation in the human brain with implications for our understanding of human memory processing and its dysfunction.

The study also provides new evidence regarding the functional organisation of EC-hippocampal circuitry as it relates to 'object' and 'scene' processing. Results of this component of the analysis support accumulating evidence that medial portions of the hippocampus and EC are preferentially engaged during scene-based cognition.

Taken together, the results of this study inform and extend current theoretical models of entorhinal-hippocampal information processing pathways in the human brain.

A major strength of the study is the detailed approach used to investigate each cortical region of interest (ROI), to characterise their functional connectivity with subregions of the EC and, in turn, how these EC subregions functionally relate to hippocampal subfields. The authors take advantage of the rich dataset acquired at 7T to gain new insights into entorhinal-hippocampal functional interactions.

While the detailed approach noted above is a major strength of the study, it is also the source of some weaknesses. For example, when manually segmenting small ROIs (such as hippocampal subfields), quality assurance measures are important to give the reader confidence that the ROI masks are, as accurately as possible, measuring what we think they are measuring. A weakness of this study in its current form is that no quality assurance measures have been presented for the ROIs. The authors provide no metrics relating to intra- or inter-rater reliability (e.g., DICE metrics) for the manually segmented ROIs. Also, it can be difficult to warp small ROIs such as hippocampal subfields to EPI images with sufficient accuracy. No data is presented to assure readers that the ROIs (manually segmented on structural images and then warped to EPI space) were well aligned with the EPI images.

It is also important to note that the subiculum mask used in this study appears to encompass the entire 'subicular complex' inclusive of the subiculum, presubiculum and parasubiculum. Importantly, the pre- and parasubiculum are located on the medial most aspect of the 'subicular complex' but this region is referred to throughout the current study as the 'distal subiculum'. Therefore, results attributed to the distal subiculum likely also reflect functional activation of the pre- and parasubiculum. Indeed, this makes sense considering accumulating evidence that the pre- and parasubiculum are preferentially engaged during scene-based cognition. Interpretation of results relating to the 'distal subiculum' should, therefore, be interpreted with this in mind.

Reviewer #1 (Public Review):

This well-written paper combines a novel method for assaying ubiquitin-proteasome system (UPS) activity with a yeast genetic cross to study genetic variation in this system. Many loci are mapped, and a few genes and causal polymorphism are identified. A connection between UPS variation and protein abundance is made for one gene, demonstrating that variation in this system may affect phenotypic variation.

The major strength of the study is the power of yeast genetics which makes it possible to dissect quantitative traits down to the nucleotide level. The weakness is that is not clear whether the observed UBS variation matters on any level, however, the claims are suitable to moderate, and generally supported.

The paper provides a nice example of how it is possible to genetically dissect an "endo-phenotype", and learn some new biology. It also represents a welcome attempt to put the function of a mechanism that is heavily studied in molecular cell biology in a broader context.

Reviewer #1 (Public Review):

Overall this is a decently controlled clinical study with an investigation into both the humoral and cellular immune responses generated by a whole virus vaccine. The conclusions note that T cell immunity can likely be achieved quickly with a short-span dosing schedule but that an optimal humoral response may need longer exposure durations and likely boosters to increase breadth and neutralization capabilities. There are no overt weaknesses in the manuscript however, its applicability to the broader COVID field is limited as no comparison to mRNA-based vaccines was made.

Reviewer #1 (Public Review):

The combination of near-completion of the Drosophila brain connectome and the simultaneous development of neurogenetic tools for manipulating neurons with high temporal and spatial specificity provides a new opportunity to understand the functional relevance and underlying molecular biology of circuits within the Drosophila brain with unprecedented coverage and resolution. A major challenge to this is matching neurons in connectomic datasets to those in known driver lines. NeuronBridge is a useful online search tool that builds on previous tools developed by the community (such as Neuron Basic Local Alignment Tool (NBLAST) and Color Depth Maximum Intensity Projection (CDM)) to link images from ~74000 fly brains to themselves so it's possible to find multiple lines that express in the same neuron, and to neurons in the FlyEM hemibrain connectomics data. This is an important resource for the Drosophila neuroscience community as it provides the ability to generate tools for manipulating neurons with unparalleled resolution and link high resolution anatomy and connectivity to function. Meissner et al is a very accessible manuscript which is written to provide detail and clarity for the expert reader, and includes enough information, resources and references for amateur and novice readers to follow. The authors did an excellent job of outlining their questions and problems, how these challenges were addressed, and the performance of the NeuronBridge software.

Overall the claims in the manuscript are clearly communicated and justified by the data. However, one of the features on NeuronBridge that was mentioned in the manuscript did not work intuitively and could use more description in the manuscript. This was the feature to upload a confocal stack to search for other Gal4 lines or the appropriate neurons in the EM hemibrain. When a known Gal4 was in the database, it was easy and intuitive to go from a driver line to an EM neuron or, alternatively if an EM neuron was known it was easy to go from that neuron to find a driver line. It was, however, difficult to upload a stack and find the neuron names or a driver line. The example on Neuronbridge was somewhat helpful but an accompanying brief 'How-to' for this process in the manuscript would be very welcome. If it's a possibility, I recommend adding this in as a 'box' or Figure in the revised paper. Further, the authors may want to provide a troubleshooting guide on the website for uploading a confocal stack onto Neuronbridge.

As a relatively minor point, could the authors also provide more clarifications on the known number of neurons in the adult Drosophila brain? On line 182, the authors cite that the adult central brain has ~30,000 neurons. The approximations I'm most familiar with for the adult brain with range between 100,000-200,000 cells with ~50-67% of cells being in the optic lobes and maybe 10-15% being glia. That being said, some of those numbers don't appear to have rigorous cell counts to back up the data although Raji et al (2021) recently found the whole adult brain has ~200,000 neurons with ~100,000 in the central brain and ~100,000 in the optic lobes. The authors should rewrite that statement in the introduction to provide clarity and accuracy on their numbers of neurons in the adult brain.

Reviewer #1 (Public Review):

This study aimed to test the hypothesis that resident immune cells are strategically positioned along the epididymal duct to provide different immunological environments to prevent pathogens from ascending the urogenital tract. By using an epididymitis mouse model, the differential responses at different segments along the epididymis were examined at both histological and gene expression levels, and the data appeared to support their hypothesis. Furthermore, single-cell RNA-seq analyses identified the composition of resident immune cell types along the epididymal duct, and the parabiosis model further corroborated the major findings. Overall, the study was well conducted and the major conclusion seems well supported. The only caveat is the lack of elucidation on the direct or indirect impact of the resident immune cells on sperm maturation.

Reviewer #1 (Public Review):

In their paper, Noel, Angelaki and colleagues investigate neural coding in an innovative closed-loop sensorimotor task, where monkeys navigate to a "firefly" target with a joystick in a virtual reality set-up. They collect an impressive data set of hundreds of single neurons from areas MST, 7a and dlPFC. They analyse the data set by fitting spike trains to a Poisson Generalized Additive Model (P-GAM) to discern the different influences (e.g. task variables, hidden variables) have on firing rates.

The strengths of the manuscript lie in the innovative task that relies closed-loop perception-action integration, the large data-set of single cells across sensory, parietal and frontal cortices and the novel analysis approach to this complex data set.

Weaknesses lie in the complexity of the data set and analyses that make it difficult for the reader to relate the results back to the literature of single units intensively characterised with optimised stimuli and more traditional tasks. This would allow the reader to potentially distinguish neural coding that is central to the particular task performance from unrelated signals and fully assess the novelty of the results. Further information on strength of unit tuning, responsiveness, task lateralisation, visual stimulus patterns and other methodological information would be helpful.

This work is of potentially considerable impact on the field as it is trying to capture the dynamic of neural coding across many single neurons in a closed-loop sensori-motor task.

Reviewer #1 (Public Review):

Using a mouse model of menstruation the authors have investigated the contribution of stromal mesenchyme cell populations to the restotation of the luminal epithelium. This work has been performed by combining the strengths of trajectory analysis in single cell RNAseq data with lineage tracking of cells using reporter constructs. This approach is an excellent example of integrating bioinformatic analysis with in vivo modelling to achieve a synergy between the two different types of data. The findings are clear and well presented with careful consideration of confounding issues. The understanding developed of the restoration of the luminal epithelium using this model system helps to define the mechanisms involved in the rapid nature of this event. This understanding is of obvious relevance to a number of related human pathologies. As yet the comparison between the mouse model data and human systems is preliminary.

Reviewer #1 (Public Review):

An osteocyte cell line exposed to oxidant stress shows enhanced translocation of connexin43 to mitochondria where it forms hemichannels that favor the ATP synthesis. Moreover, connexin43 hemichannels mediate the K+, H+, and ATP transfer across the mitochondrial inner membrane. This article provides valuable information that explains relevant steps of preconditioning. The authors used ad hoc modern cell biology techniques to unravel the interaction of Cx43 with other critical molecular elements and to demonstrate the functional role of connexin hemichannels.

In general, the manuscript is well organized and clearly written. The discussion provides the required information to easily understand the relevance of each finding.

Reviewer #1 (Public Review):

Tang et al. in this report investigate the effects of deleting Surf4 in mouse liver by generating three different mouse models. Previously this group has shown that Surf4 functions as a cargo receptor that facilitates the secretion of PCSK9 in cultured cells. Here they have deleted the gene in hepatocytes and find that there is a significant reduction in plasma PCSK9 levels with a resulting increase in LDLR protein and lowering of plasma cholesterol levels. Surf deletion in hepatocytes using albumin-Cre had no deleterious effects in liver. What was found was a 60% reduction in plasma PCSK9 with no change in PCSK9 mRNA levels. These results were confirmed using Cas9 mice in which Surf4 was acutely deleted. Consistent with the known function of PCSK9, the reduction in plasma PCSK9 was associated with a significant increased in liver LDLR protein levels. In addition to dramatically lower plasma cholesterol levels in all lipoprotein fractions, they also find reduced plasma TG levels they show was due to a marked reduction in apoB and TG secretion. Interestingly, there was no defect in intestinal lipid absorption. Combined the studies are well done and convincing show the role of Surf4 in facilitating PCSK9 and apoB secretion from liver. Interesting remaining questions would be to address whether Sruf4 plays a similar role in intestine and whether it is required for fat absorption from the gut.

Reviewer #1 (Public Review):

This work employs a new method, namely connectivity gradient, for measuring the brain-cognition relationship. Such a method has been proposed and widely studied in large-scale connectivity. It reveals that cortical function and intrinsic connectivity change systematically along a 'principal gradient', which has primary sensory and motor cortex at one end, and transmodal regions implicated in abstract and memory-based functions at the other. Recently it has become possible to detect such gradient associations in humans using task-based fMRI. This paper provides a modelling and inference framework for detecting such gradient-related links to human semantic cognition. Specifically, the authors manipulated the degree to which ongoing semantic cognition was aligned with long-term semantic knowledge and quantified the similarity of the multivariate response to each trial along the principal gradient. Such elegant design should therefore be expected to indicate that the dimensionality of neural representations in a semantic task to decrease from unimodal to transmodal areas along the principal gradient, reflecting increasingly abstract and culturally shared representations towards the apex of the gradient. This work could be a promising flag-use for task-based fMRI brain-cognition association studies using the gradient method.

Reviewer #1 (Public Review):

The manuscript describes Mendelian Randomization (MR) analyses aimed at determining what, if any, causal effect body mass index (BMI) has on childhood emotional problems: depression, anxiety, and attention-deficit and hyperactivity disorder (ADHD) at age 8. To do this, the study leverages genetic association results on BMI to construct a genetic 'instrument', called a polygenic score, that predicts BMI. They use this score to see if the genetic predictor of BMI also predicts childhood emotional problems. What distinguishes this study from typical MR studies is that they use a large sample of 26,370 children with genotype data available for the child and both parents. This enables them to use within-family MR: within-family MR uses the parental genotypes as controls to remove confounding factors. Because offspring genotype is randomly assigned given parental genotype, controlling for parental genotype removes bias due to gene-environment correlation and assortative mating.

The authors find that 'classic MR' (i.e. without controls for parental genotypes) gives evidence that higher BMI increases depressive symptoms and ADHD symptoms in children. However, when controlling for parental genotype (within-family MR), the estimates become smaller and are no longer statistically significant. While this is consistent with 'classic MR' being confounded due to gene-environment correlation and/or assortative mating, the within family MR analysis is less powerful (i.e,. considerable uncertainty about the effect remains) so it is hard to draw any strong conclusions about whether there is or is not an effect of BMI on childhood emotional problems.

This study provides further evidence that MR analyses that do not control for parental genotypes can be biased and conclusions drawn from these analyses should not be taken at face value. However, the fact that there is still a high degree of uncertainty in the within-family MR estimates despite having a large sample of children with genotyped parents implies that, for many hypotheses, much larger samples with genotyped parents will be needed to conduct well-powered within-family MR analyses. Further studies could also interrogate what aspects of the environment explain the observed correlation between parental genotype and offspring emotional problems.

Reviewer #1 (Public Review):

The authors have examined different pathways of B cell differentiation in patients with SARS-CoV-2 infection who did or did not have HIV-1 infection. They conclude that B cell responses to SARS-CoV-2 infection occur via an extra-follicular (EF) pathway to a greater extent in people with HIV-1 infection compared with people who do not have HIV-1 infection.

The data are important and generally robust but there are deficiencies related to presentation and interpretation of data, as indicated below:

1. There are concerns about nomenclature of cell populations defined by tSNE plots (figure 2A). For example, the population defined as "CSM/marginal zone" does not express IgD or IgM, as would be expected for class-switched memory B cells but not marginal zone B cells. In addition, while tissue homing and GC homing CSM B cells express expected amounts of CXCR4 and CXCR5, both express high amounts of CXCR3, which would be unexpected for GC homing cells. Finally, in line 144, the authors should clarify what is meant by "class switched, IgMhi B cells (highlighted in blue)". The population highlighted in blue in figure 2A, referred to as "IgM++ GC homing B cells", has the immunophenotype IgDlow, IgMhigh, CD27-. Aren't these cells at one end of a naïve B cell spectrum ranging from IgD+/IgM- to IgD+/IgM+ to IgDlow /IgMhigh? There are also other populations that have unconventional names and/or appear to be intermediary populations.

2. IgM switched memory B cells (lines 201-207) are referred to as IgM-only memory B cells by some investigators (for example, see - Bautista D et al. Front Immunol. 2020; 11:736). It would help the reader if this were indicated.

3. The authors have defined DN2 B cells based on expression of the activation marker CD95 (Fas) (see Figure 4) but the original definition of DN2 B cells in patients with SLE was based on expression of CD11c and lack of expression of CXCR5 (see - Jenks SA et al. Immunity. 2020; 52:203). These cells also express T-bet and therefore, have many characteristics in common with CD11c+/T-bet+ memory B cells (also known as age-associated B cells or atypical memory B cells). It would be informative if data on CXCR5- DN B cells were in analysed in addition to, or instead of, CD95+ DN B cells.

4. It might also be informative to discuss the extra-follicular (EF) response pathway in more detail. Recently published data from studies undertaken in mice indicate that CD11c+/T-bet+ MBCs interact with T follicular helper cells in lymphoid follicles but not in germinal centres (Song W et al. Immunity 2022; 55:290-307.e5), so it could be argued that the differentiation pathway is extra-GC rather than extra-follicular, at least in some situations. Also, in people with HIV-1 infection, HIV-1 gp140-specific B cells expressing T-bet are produced outside of GCs (Austin JW et al. Sci Transl Med. 2019; 11:eaax0904. Is the EF response pathway different to the extra-GC differentiation pathway? Where does it occur?

5. Similarly, in lines 288-290, the authors should re-consider the statement that "Both DN2 and activated naïve B cells mature via an EF pathway, independent of T cell help and in response to pro-inflammatory cytokines IFNγ, TNFa, and IL-21; and TLR 7 and 9 stimulation". There are data indicating that differentiation of DN2 B cells is T-cell-dependent (Keller B et al. Sci. Immunol. 2021; 6:eabh0891).

6. In lines 254-60 and figure 6, the investigators should consider the possibility that the CXCR3+ and DN2 SARS-CoV-2-specific MBCs that are increased in people with HIV infection are the same population of cells. CD11c+/T-bet+ MBCs (ie. DN2 B cells, age-associated B cells or atypical memory B cells) usually express high levels of CXCR3.

Reviewer #1 (Public Review):

The manuscript shows that bone is resorbed during the early steps of limb regeneration in urodeles, and osteoclasts are required for this process. In case of impaired resorption, integration of newly-formed tissue with the original bone shaft is compromised. The manuscript further shows that wound epithelium is required for bone resorption and suggests that it induces osteoclastogenesis or migration of osteoclasts. Furthermore, the authors showed that the formation of novel skeletal elements is initiated while the resorption of the old one is still actively ongoing.

The study is well designed, conclusions are relatively well supported, and data are presented in a clear way. Two new models of transgenic axolotls have been created. The strongest and most important finding is that partial bone resorption is required for tissue reintegration. My main concern is the novelty of this study, which is quite limited in my opinion. Specifically, resorption of bone stump during limb regeneration has been shown before in various model organisms. The role of osteoclasts in this process has not been well characterized in urodeles but has been shown during the regeneration of a mouse digit. It is reasonable to anticipate that similarly, osteoclasts are resorbing bone in salamanders, especially since this is the only cell type known for bone resorption. Thus, this observation, despite being nicely and thoroughly done, is of limited interest. The role of wound epithelium in bone histolysis is well demonstrated via skin flap experiments in this manuscript. However, upon skin flap surgery no limb regeneration occurs, implying wound epithelium is a key tissue triggering all the processes of limb regeneration. Accordingly, the absence of bone histolysis in such conditions can be secondary to the absence of any other part of the regenerative process, e.g., blastema formation, macrophage M1 to M2 transition, reinnervation, etc. The proposed link between wound epithelium and osteoclastogenesis (i.e., Sphk1, Ccl4, Mdka) is very superficial and very suggestive. No functional evidence was provided to confirm these connections. Finally, the authors showed that new bone formation occurs while resorption of the bone stump is still ongoing. This is a nice observation, but again, rather indirect as it is based on the dynamics of bone resorption and bone formation in different animals. Due to high variability among animals, direct evidence, like double staining for osteoclasts and blastema markers would address this point more precisely.

Reviewer #1 (Public Review):

The authors are trying to show that transitions between ring-like structures and clusters are driven by the balance between 2 main forces: filament treadmilling and motor protein-driven contractility. The results obtained in computer simulations are always compared with properly set experiments, making the story very convincing. In addition, the possible microscopic picture of the mechanisms is provided, although at a more phenomenological level. But given the complexity of the system, I find it very appropriate.

One of the most important achievements of this work is that the authors clearly identified and proved the factors that lead to a very non-trivial behavior. This should stimulate more work on understanding what biological regulation mechanisms might be involved in these phenomena.

I believe that this work will have a strong impact in the field. I am especially impressed by the successful combination of advanced computational and experimental methods.

Reviewer #1 (Public Review):

The aim of the present study was to develop and validate a novel mouse model that allows to determine the proteome of defined sub-cellular compartments, and to use this model in order to elucidate the molecular processes that govern the establishment of synaptic contacts between cortical and striatal neurons in the brain. Given that knowledge of the protein composition of defined sub-cellular compartments is of key importance for the characterisation of protein machines that mediate defined cellular functionalities, the establishment of corresponding mouse models to study such issues is of major general interest. The same is true for the development and function of cortico-striatal connectivity in the brain, which plays key roles in multiple major brain processes and is perturbed in many neuropsychiatric disorders.

The major strength of the present paper is that it presents a novel mouse line that promises to serve as a very helpful tool in this context. The authors generated a KI mouse line that expresses APEX2 under the control of a Cre-activatable promoter from the ROSA26 locus, and they show convincingly that this new mouse line, upon crossing with corresponding Cre-expressing driver lines, allows the identification of cell-sub-compartment specific proteomes and phosphoproteomes - via APEX2-mediated proximity biotinylation, tissue dissection, protein affinity purification, and mass spectrometric analysis.

The biological context of the present study is less convincingly established. Focussing on neuronal connections between the cerebral cortex and the striatum, bioinformatic analyses of corresponding datasets pinpoint a selection of axon guidance systems and protein kinase cascades to play roles in the development of cortico-striatal connectivity. The corresponding data partially align with the published record, but potentially new biological insights deduced from bioinformatic analyses of proteomic data were not followed up by experimental validation.

In sum, the new APEX2 reporter mouse line reported in the present paper will likely be of substantial interest to researchers in many fields of mammalian biology, but the extent of 'new biology' provided in the present study is very limited.

Reviewer #1 (Public Review):

The study by Tu and Zhang is very strong, from its technical implementation, the interesting question being addressed, and a clear presentation of the results. Indeed, the visual guides in the figures allow for easy navigation of the results and help the readers make his/her own inferences seamlessly. The quality of the MRI combined with electrophysiological recordings is excellent, as far as I can tell without looking at the data made available by the authors. The experiments and analysis follow a logical progression that makes sense. If any weakness is to be found, perhaps the authors overstep their inferences of respiration -> neuronal signal causality in the discussion.

Reviewer #1 (Public Review):

The paper by Campell et al., describes the isolation and characterization of Designed Ankyrin Repeat Proteins (DARP) that recognize distinct forms of gephryin. Gephyrin is a key determinant for postsynaptic accumulation of both glycine and GABAAR at synapses and thereby determines the efficacy of fast synaptic inhibition. In addition to this gephyrin regulates the synthesis of molybedum-cofactor, an essential co-factor for a number of metabolic enzymes.

The authors create DARPs that recognize specific splice forms of gephyrin and versions that discriminate between phosphorylated and dephosphorylated forms of gephyrin. These new tools reveal the differential recruitment of gephyrin isoforms to axo-axonic and somatodendritic synapses. In addition to these new tools allow the efficient one-step purification of differing gephyrin isoforms and their respective binding partners.

Reviewer #1 (Public Review):

The authors have previously reported the identification of a series of cell-cell junctional proteins as pTyr protein targets for the receptor-like PTPRK tyrosine phosphatase (PTP), including Afadin, a junctional plaque protein that links cell surface adhesion proteins to the cytoskeleton. They identified Afadin pY1230 as a target for PTPRK-mediated dephosphorylation, in keeping with the known role of tyrosine phosphorylation in regulating Afadin function in adherens junctions. They also showed that Afadin/PTPRK interaction did not require its tyrosine phosphorylation, and that the whole PTPRK cytoplasmic domain (ICD) was needed for in vitro dephosphorylation of pY1230 Afadin in vitro.

Here, they used two approaches to define a predicted 63-residue coiled-coil (CC) region (residues 1393-1455) in Afadin as being sufficient to bind the PTPRK intracellular domain (ICD). However, this region behaved as a monomer suggesting it is not a typical CC region. The CC bound the PTPRK ICD with low μM affinity and interacted selectively with the PTPRK D2 pseudophosphatase domain in vitro. Based on a predicted AlfaFold2/Multimer Afadin CC/D2 domain structure, they biochemically defined the key D2/CC interactions showing that a conserved core charged region, residues 1408-1448, in Afadin was essential, which then allowed them to refine the AlfaFold2 model. Their new model places the Afadin CC core region folded as an α-helix bound across the backside (?) of the D2 domain. They had shown previously that the ICD of the related PTPRU also bound Afadin whereas that of the PTPRM did not, and using the structural model showed that the key contact sites in PTPRK with the Afadin CC helix were conserved in PTPRU but not in PTPRM. When the residues in the G1273/L1335 "acidic" pocket of the D2 domain involved in Afadin helix binding were simultaneously mutated to His and Arg respectively, the basic residues found in PTPRM D2, both the double G1273H/L1335R mutant (DM) D2 alone and the entire PTPRK DM ICD failed to bind Afadin or to dephosphorylate (how much less that WT?) pY1230 in Afadin in lysates of pervanadate-treated cells, as assayed using a pY1230 specific antiserum they generated, even though both the WT and DM PTPRK ICD could dephosphorylate pTyr p120-catenin, another PTPRK substrate. On this basis the authors suggest that the D2 pseudophosphatase domain of PTPRK can act as a substrate recruitment domain that allows the active D1 domain to dephosphorylate a distant pTyr residue, in this case pY1230 ~150 residues away.

In this interesting study, the authors present evidence for the novel concept that the D2 pseudophosphatase domain of PTPRK can serve as a recruitment platform for a subset of PTPRK substrates, such as Afadin. Their evidence for this conclusion is strong, and by extension, their findings suggest that the D2 pseudophosphatase domains of other RPTPs may have a similar general function in substrate recruitment and selectivity.

1. While the AF2-Multimer prediction is quite compelling and supported by the properties of the RPTPK D2 DM mutant, this story would have been even more convincing if they had generated a co-crystal structure (perhaps using a PTPRK D2-Afadin aa 1393-1455 fusion with a long linker). In the absence of a true structure, some additional mutational validation of the proposed Afadin-D2 interaction would strengthen their conclusions.

2. The DM mutant data in Figure 4 show that the D2 domain interaction is important for Afadin pTyr dephosphorylation in vitro, but one would also like evidence that the DM PTPRK mutant lacks Afadin pY1230 dephosphorylating activity in cells. The authors have the PTPRK KO MCF10A cells they generated in their first paper that could be used to re-express the WT and DM PTPRK and then monitor Afadin dephosphorylation with their new anti-pY1230 antibodies.

3. If key residues in PTPRM are mutated into the equivalent PTPRK D2 residues, does this now confer on PTPRM the ability to dephosphorylate pY1230 in Afadin, i.e. a gain of function experiment?

4. It would be helpful to know whether any of the other PTPRK substrates that the authors identified previously have a similar motif that might allow them to bind to the D2 domain and be recruited for dephosphorylation.

Reviewer #1 (Public Review):

In this paper, the authors ask a key question in the field of adult plasticity, and in particular, amblyopia treatment: whether transient dark exposure followed by light re-introduction disrupts neural representation for basic stimulus attributes in a manner that could negatively impact vision. Prior work by Rose and colleagues using calcium imaging showed that closing one eye in adult mice leaves the responsiveness of V1 neurons unchanged but alters their orientation preference and pairwise correlations; such representational drift may require downstream areas to adjust how they readout V1 signals. The question posed here is whether binocular visual deprivation in adult mice does the same. The authors use 2-photon calcium imaging in 6 awake, head-fixed [transgenic - GCaMP6f driven by the EMX1 promoter] mice before and after transient dark exposure to record ensemble responses of layer 2/3 excitatory V1 neurons to oriented gratings of varying spatial frequencies. Data were acquired twice at baseline (allowing for an assessment of representational drift during exposure to the natural [cage] environment), once immediately after 8 days of dark exposure and once about 8 days after animals were once again exposed to their natural [cage] environment.

The study appears to be generally well designed with multiple analytical approaches trained on the same questions. Major strengths include the ability to analyze a large number of neuronal responses simultaneously in the awake-behaving state using calcium imaging in transgenic mice, and the ability to record activity in the same neurons across several weeks and following different behavioral manipulations. A relative weakness was the implication of only being able to elicit relevant visual responses from a small fraction of V1 neurons for comparison purposes. This begs the question of what may have happened to the neurons that were not tracked, and whether this in fact may have been significant. For the ~30% of V1 neurons which were tracked, the findings appear to be that dark exposure of adult mice for 8 days did not significantly corrupt their orientation or SF tuning. Instead, there were increase pairwise correlations between them, interpreted as increased stability of stimulus representation. However, when the entire neuronal pool was analyzed, a decrease in decoding accuracy was noted, attributed to decreased response reliability. Nonetheless, a recovery back to baseline was noted after mice were re-exposed to light and their natural cage environments for 8 days. The study thus provides a binocular deprivation alternative to the earlier monocular deprivation findings of Rose et al. In addition, it provides some new insights, suggesting that the early visual system (i.e. V1) of adult animals normally exhibits a flexible stimulus representation for simplistic, artificial visual stimuli such as oriented gratings, and that temporary dark exposure decreases this flexibility. Importantly for therapeutic approaches however, this can be reversed upon re-introduction of the natural, complex visual environment.

Reviewer #1 (Public Review):

This study demonstrates the role of the circadian clock in spatiotemporal regulation of floral development. The authors nicely illustrated floral development patterns in domesticated sunflower. In particular, during anthesis, discrete developmental zones, namely pseudowhorls, are established, and hundreds of florets simultaneously undergo maturation in each psudowhorl in a circadian-dependent manner. Consistently, the flower development follows key features of the circadian clock, such as temperature compensation and gating of plant response to environmental stimuli. Evolutionary advantages of this regulation will add more merit to this study.

Reviewer #1 (Public Review):

In addition to canonical bacterial signaling methods, two-component systems, and serine/threonine kinases, one of the most ubiquitous signal transduction modalities in M. tuberculosis is via adenylate cyclases. This study seeks to identify new adenylate cyclases of M. tuberculosis used to sense antibiotic treatment and resist its effects. To this end, authors employed cutting-edged techniques including genetic knock-out strategy, CRISPRi knock-down strategy, LC-MS-based target metabolite quantification, and various biochemical/microbiological methods. This study provides a conceptually novel strategy to kill M. tuberculosis with conventional tuberculosis chemotherapy.

• ffff*

Why mordern tv series like to describe middle age as a "Dark Age"?

Reviewer #1 (Public Review):

The authors have modified protocols for Phage Immunoprecipitation sequencing or PhIP-seq to allow much larger throughput and have examined value of this platform for auto-antigen discovery. Overall the manuscript is technically sound. The finding of shared auto-antigens in Kawasaki Disease and MIS-C was of interest.

Reviewer #1 (Public Review):

The paper has determined a considerable number of different structures and conformations by Cryo-EM, that describes the full conformational spectrum of the KdpFABC catalytic cycle. They also show by EPR that the non-phosphorylatable variant KdpBS162A variant was indeed arrested in the state observed by Cryo-EM.

Although they have been able to validate that the Cryo-EM structure of the off-cycle state is consistent with the conformational state probed by pulsed EPR, it is unclear what protein phosphorylates and then inactivates KdpFABC at higher K+ concentrations. As such, at present, it is not possible to fully comprehend the exact physiological conditions when the arrested state is formed.

Reviewer #1 (Public Review):

A novel approach is introduced for targeting Protein-RNA interactions. The approach (presented in Figure 1) integrates computational techniques with cellular assays, and is applicable, in principle, whenever the protein-RNA complex has a druggable binding pocket. It is demonstrated with the discovery of inhibitors of YB-1's interaction with its mRNA target. Of 22 putative hits, discovered based on virtual screen, 11 come out as very strong hits. Far beyond the 5-10 percent success rate that one often sees in drug discovery.

The main strength here is the proof of concept that protein-RNA interactions are targetable.

Reviewer #1 (Public Review):

The submitted manuscript describes an optimized tissue clearing protocol with some modest advantages including better preservation of tissue volume, compatibility with traditional histology methods, and simple processing steps. By combining known advantages of organic solvent-based and aqueous-based procedures the authors were able to generate a very simple, efficient, and fast tissue clearing protocol that can preserve endogenous and synthetic fluorescent signals. The manuscript is mostly written well and the fluorescent images are very striking. However, the lack of quantification throughout the manuscript makes it is difficult to assess how robust the results are across many samples and key experimental applications are missing.

1. Immunofluorescent labeling/staining is a very common procedure in whole, cleared tissues. Given that immunofluorescent labeling works well in tissue sections from EZ Cleared brains, it appears that it should work in the whole tissues after clearing. An extended version of the EZ Clear protocol with immunofluorescent labeling procedures in whole mouse brain tissue should be included along with quantification of fluorescent intensity as a function of depth. If EZ Clear provides more uniform immunofluorescent labeling relative to other protocols, this is a significant advantage.

2. The differences in tissue volume and sample processing steps between EZ Clear and Fast 3D are important, but relatively modest. Additional quantitative comparisons between EZ Clear and Fast 3D/3Disco would considerably strengthen the manuscript. The qualitative differences shown in Figure 1G-J are striking, but it is difficult to determine how robust this effect is across multiple samples without a quantitative comparison. Similar quantitative comparisons should be made for endogenous fluorescent intensity and immunofluorescent labeling as a function of tissue depth between the various protocols.

3. It would be helpful to see how the intensity and contrast of the fluorescent labeling changes as a function of depth (e.g. Lectin-649 labeling in Figures 2E and H). There is a clear improvement with EZ View relative to RIMS, but there are still noticeable changes in the signal as a function of depth. Quantification would help determine the extent of these changes, as well as reproducibility across multiple samples.

4. LSFM imaging should be performed in some of the other mouse tissues to demonstrate sufficient clearing for quantification purposes.

Reviewer #1 (Public Review):

The authors use a model system to investigate how three classes of kinesins (1, 2 and 3) interact with the dynein-dynactin-truncated BicD2 complex when coupled via a DNA scaffold. Complexes with kinesin 1 have been shown to have a plus-end bias, but unexpectedly the authors show that this is also true for kinesins 2 and 3 despite these motors having a higher load sensitivity. The authors reconcile this finding by showing via simulations that faster reattachment kinetics compensate for faster detachment rates under load. They conclude that motor kinetics is another important feature in understanding both the velocity and directionality that cargo is transported.

This is the first study directly comparing three classes of constitutively active kinesin motors versus DDB in a controlled fashion, which is a strength of this study. The caveat is that these results may require modification when dynein and kinesin are coupled via an activating adaptor rather than DNA. However, the studies in the current manuscript are a required prerequisite, as different activating adaptors would be needed for the different classes of kinesin, thus introducing another variable into how the two classes of motors interact. Moreover, results from these studies can be used as a platform for further investigation of the effect of MAPs, regulatory proteins, and PTMs of the MT on model bidirectional complexes.

Reviewer #1 (Public Review):

GCaMP indicators have become common, almost ubiquitous tools used by many neuroscientists. As calcium buffers, calcium indicators have the potential to perturb calcium dynamics and thereby alter neuronal physiology. With so many labs using GCaMPs across a variety of applications and brain regions, it's remarkable how few have documented GCaMP-related perturbations of physiology, but there are two main contexts in which perturbations have been observed: after prolonged expression of a high GCaMP concentration (common several weeks after infection with a virus using a strong promoter); and when cytoplasmic GCaMP is present during neuronal development. As a result, GCaMP studies are often designed to avoid these two conditions.

Here, Xiaodong Liu and colleagues ask whether GCaMP-X series indicators are less toxic that GCaMPs. GCaMP-X indicators are modified GCaMPs with an additional N-terminal calmodulin binding domain that reduces interactions of the calmodulin moiety of GCaMP with other cellular proteins. Xiaodong Liu and colleagues document effects of GCaMP expression on neuronal morphology in vitro, calcium oscillations in vitro, and sensory responses in vivo, in each case showing that GCaMP-X indicators are less toxic. Their results are compelling.

Unfortunately, the paper suffers two main weaknesses. Firstly, the results demonstrate that GCaMP is toxic during development, after prolonged expression via viruses in vivo, and in cell culture where maturation of the culture likely recapitulates key steps in development. GCaMPs are known to be toxic in these circumstances, such toxicity is readily circumvented by driving expression in the adult, and there are countless examples of studies in which adequate GCaMP expression was achieved without toxicity. These new results are of little relevance to the majority of GCaMP experiments. That GCaMP-X indicators are less toxic during development is a new result and may be of interest to those who wish to deploy calcium indicators during development, but this is a relatively small number of neuroscientists.

Secondly, the authors extend their claims to conclude that GCaMP indicators are toxic under other circumstances, claims supported by neither their results nor the literature. To provide one example, at the end of the introduction is the statement, 'chronic GCaMP-X imaging has been successfully implemented in vitro and in vivo, featured with long-term overexpression (free of CaM-interference), high spatiotemporal contents (multiple weeks and intact neuronal network) and subcellular resolution (cytosolic versus nuclear), all of which are nearly infeasible if using conventional GCaMP.' The statement's inaccurate: there are many chronic imaging studies in vitro and in vivo using GCaMP indicators without nuclear accumulation of GCaMP or perturbed sensory responses. There are more examples throughout the paper where the conclusions overreach the results and are inaccurate. The results are simply insufficient to support many of the strong statements in the paper.

Reviewer #1 (Public Review):

This study attempts to understand the source of problems in allocentric navigation in older adults and children compared to young adults. Using a simple and elegant Y-maze design with extensive behavioral analyses, the authors convincingly show that older adults and children are impaired with respect to the ability to use landmark cues, but not geometric cues, in order to orient in the environment. Their testing further shows that this results from a problem of remembering spatial relations between landmarks and using those to navigate, and not an issue of encoding the landmarks themselves or attending to them. The findings are important in two respects: 1) understanding the navigational problems of older adults, 2) understanding the cognitive systems underlying allocentric navigation. With regard to the first point, the authors' results from the map drawing task demonstrate that the problem is specifically with remembering the relative configuration of the landmarks with respect to one another and to the start and goal location. With regard to the second point, the paper is exciting in that it demonstrates a dissociation between two systems of allocentric navigation - landmark-based and geometry-based. As the authors point out, most papers refer to "allocentric navigation" as a process where subjects use either the geometry or landmarks interchangeably as reference points in their mental map, but these findings suggest that those systems might be dissociable. Overall, I think that the study is well-designed, the analyses are adequate, and the research questions are addressed appropriately. The authors took care to exclude other sources of difference between groups by having both physical and virtual reality mazes, using a walking VR paradigm to eliminate computer use proficiency differences, and testing visual attention and gaze as well as an array of other variables.

Reviewer #1 (Public Review):

Redox signaling is a dynamic and concerted orchestra of inter-connected cellular pathways. There is always a debate whether ROS (reactive oxygen species) could be a friend or foe. Continued research is needed to dissect out how ROS generation and progression could diverge in physiological versus pathophysiological states. Similarly, there are several paradoxical studies (both animal and human) wherein exercise health benefits were reported to be accompanied by increases in ROS generation. It is in this context, that the present manuscript deserves attention.

Utilizing the in-vitro studies as well as mice model work, this manuscript illustrates the different regulatory mechanisms of exercise and antioxidant intervention on redox balance and blood glucose level in diabetes. The manuscript does have some limitations and might need additional experiments and explanation.

The authors should consider addressing the following comments with additional experiments.

1. Although hepatic AMPK activation appears to be a central signaling element for the benefits of moderate exercise and glucose control, additional signals (on hepatic tissue) related to hepatic gluconeogenesis such as Forkhead box O1 (FoxO1), phosphoenolpyruvate carboxykinase (PEPCK), and GLUT2 needs to be profiled to present a holistic approach. Authors should consider this and revise the manuscript.<br /> 2. Very recently sestrin2 signaling is assumed significant attention in relation to exercise and antioxidant responses. Therefore, authors should profile the sestrin2 levels as it is linked to several targets such as mTOR, AMPK and Sirt1. Additionally, the levels of Nrf2 should be reported as this is the central regulator of the threshold mechanisms of oxidative stress and ROS generation.<br /> 3. Authors should discuss the exercise-associated hormesis curve. They should discuss whether moderate exercise could decrease the sensitivity to oxidative stress by altering the bell-shaped dose-response curve.<br /> 4. It would not be ideal to single-out AMPK as a sole biomarker in this manuscript. Instead, authors should consider AMPK activation and associated signaling in relation to redox balance. This should also be presented in Fig 7.

Reviewer #1 (Public Review):

Klein and colleagues have developed a new setup to artificially activate genetically targeted neurons in temporal precise correlation with specific behaviors in larva of Drosophila melanogaster. The work explores how the activation of specific sets of reward and punishment coding neurons during the execution of side-specific bending alters the occurrence of this behavior. Indeed, activating serotonergic neurons during specific bending in a training phase, biases bending direction in the test. Since altering behavior as a consequence of its rewarding or punishing outcome is considered operant learning the authors conclude that the targeted neurons mediate operant conditioning. Below I will point out the strength and my criticisms concerning the presented work.

The newly developed closed-loop set-up is impressive and will pave the way for many exciting studies on learned behavior and beyond. To validate the set up the authors induce rolling behavior by thermo- or optogenetically activating two sets of previously described neurons in individual larva. Both approaches show convincing induction of the behavior per se. However, it is worth pointing out that there seems to be an interaction of the different tools used (thermo and opto-genetic) and the targeted neurons: the authors observe different dynamics of the behavior across the three stimulation cycles depending on stimulation method and labeled neurons. These findings make it difficult to understand why the authors choose only the optogenetic activation to investigate operant conditioning. The strength of the setup is that individual animals can be targeted. Though the presented data show that behavior can be reliably induced in stimulated animals, it lacks the information about the behavior of non-targeted larva during the stimulation. Thus, it would strengthen the work if the authors could show the behavior of the non-targeted larva during the time when targeted larva receive light or heat.

The authors use their setup to investigate operant conditioning. In operant conditioning an animal learns to associate its action with the consequences. Their new setup allows the authors to artificially induce consequences, the activation of reward or punishment coding neurons, upon side-specific bending behavior. The experiments show that side specific bending in the test is slightly biased towards the side previously paired with the neuronal stimulation. Interestingly, the data suggest that this effect requires the activity of serotonergic neurons outside of the brain (in the VNC) and that it is not mediated by dopamine signaling in the brain. Though, the effects seem to be reproducible with Ddc- and the Tph-GAL4 the reported differences are small, and the origin of the relative difference between left and right bending in the paired group is not entirely clear. Thus, it will be important to strengthen the work by additional experiments and extend the analysis of the presented data. Given the novelty of the method and the differences between the tools in the proof of principle experiments the authors should repeat the key experiments (Figure 3 b and e) with the thermogenetic stimulation. Further it would strengthen the investigation on operant conditioning if the authors would explore the temporal relationship between the CS and US, especially since the effect might be a reduction of the unreinforced behavior (see below). Concerning the analysis, the authors should consider that given the small effect they observe, they want to be sure that it originates from training. Though they show the pretraining results for one of the experiments (Figure 3b, the trained group), the pretraining bending is very relevant for each of the operant learning experiments. In fact, training induced effects should not only be measured by looking at the left vs right bending in the final test but as a change between pre versus post or between a trained and a mock control group. This is done for one group (Ddc-GAL4) in Figure 3b but will be mandatory for all operant learning experiments. It would improve the accessibility of the learning induced change of behavior if the authors could show the pre vs post training results for each run (10-12 larva in a plate). Further, they should plot the numbers of reinforced behaviors in each of the training protocols and relate it to the test performance. The presented data clearly suggests a decrease of the unstimulated bending rather than a change in the reinforced behavior. Though the authors mention it, they do not explain or discuss it. It will be very important for the logic of the manuscript that the authors explain this phenomenon and how it relates to operant conditioning.

Lastly, though the manuscript discusses most of the data carefully, in my view the authors miss an important issue: it remains to be shown if fly larva are capable of operant learning using external reward or punishment. The presented evidence is based on artificial activation of neurons, which arguably is a hint but not a prove that operant conditioning is withing the repertoire of a fly larva, an issue the authors should mention and discuss.

Reviewer #1 (Public Review):

The goal of the current study is to determine the impact of sleep on resilience to social stress. The research team accomplished their goals using male mice that underwent social defeat stress by a larger conspecific. The team found that sleep is necessary and sufficient for promoting stress resilience to social defeat stress. They also identified the prefrontal cortex as a major player in the link between sleep and stress resilience.

Overall, this is a well-written manuscript that is strengthened by the translational relevance and significance, the well-executed study design, and the robustness of the data.

Reviewer #1 (Public Review):

In this manuscript, the authors leverage novel computational tools to detect, classify and extract information underlying sharp-wave ripples, and synchronous events related to memory. They validate the applicability of their method to several datasets and compare it with a filtering method. In summary, they found that their convolutional neural network detection captures more events than the commonly used filter method. This particular capability of capturing additional events which traditional methods don't detect is very powerful and could open important new avenues worth further investigation. The manuscript in general will be very useful for the community as it will increase the attention towards new tools that can be used to solve ongoing questions in hippocampal physiology.

Additional minor points that could improve the interpretation of this work are listed below:

- Spectral methods could also be used to capture the variability of events if used properly or run several times through a dataset. I think adjusting the statements where the authors compare CNN with traditional filter detections could be useful as it can be misleading to state otherwise.

- The authors show that their novel method is able to detect "physiological relevant processes" but no further analysis is provided to show that this is indeed the case. I suggest adjusting the statement to "the method is able to detect new processes (or events)".

- In Fig.1 the authors show how they tune the parameters that work best for their CNN method and from there they compare it with a filter method. In order to offer a more fair comparison analogous tuning of the filter parameters should be tested alongside to show that filters can also be tuned to improve the detection of "ground truth" data.

- Showing a manual score of the performance of their CNN method detection with false positive and false negative flags (and plots) would be clarifying in order to get an idea of the type of events that the method is able to detect and fails to detect.

- In fig 2E the authors show the differences between CNN with different precision and the filter method, while the performance is better the trends are extremely similar and the numbers are very close for all comparisons (except for the recall where the filter clearly performs worse than CNN).

- The authors acknowledge that various forms of SWRs not consistent with their common definition could be captured by their method. But theoretically, it could also be the case that, due to the spectral continuum of the LFP signals, noisy features of the LFP could also be passed as "relevant events"? Discussing this point in the manuscript could help with the context of where the method might be applied in the future.

- In fig. 5 the authors claim that there are striking differences in firing rate and timings of pyramidal cells when comparing events detected in different layers (compare to SP layer). This is not very clear from the figure as the plots 5G and 5H show that the main differences are when compare with SO and SLM.

- Could the above differences be related to the fact that the performance of the CNN could have different percentages of false-positive when applied to different layers? Alternatively, could the variability be related to the occurrence (and detection) of similar events in neighboring spectral bands (i.e., gamma events)? Discussion of this point in the manuscript would be helpful for the readers.

Overall, I think the method is interesting and could be very useful to detect more nuance within hippocampal LFPs and offer new insights into the underlying mechanisms of hippocampal firing and how they organize in various forms of network events related to memory.

Reviewer #1 (Public Review):

The manuscript by Arnason et al. reports a careful in-depth analysis of genomic patterns of diversity of the Atlantic codfishes, sampled twice near the Icelandic coast. The manuscript is scientifically sound and provides thorough details of the statistical analysis and of the underlying models. In essence, the analysis demonstrates that recurrent selective sweeps are the most compatible scenario to explain the data. The analysis is extremely detailed, well constructed, and very convincing. It also advertises the family of Multiple-Merger Coalescents (MMCs) as good models for standard population genetics analyses. Overall, I found this article very interesting and extremely well-documented.

Reviewer #1 (Public Review):

The experiments presented in this extensive study by Ronzano et al. are a tour-de-force investigating the spatial organization of premotor interneurons in the mouse spinal cord to re-examine the fundamental question of whether there is spatial segregation of interneurons with monosynaptic connections to motoneurons innervating functionally antagonistic (flexor and extensor) pairs of limb muscles. Such segregation has been proposed from earlier studies utilizing strategies for retrograde trans-synaptic tracing of spinal premotoneurons with rabies virus (RabV) following muscle injection. This spatial organization has been suggested to provide an anatomical substrate for labeled line inputs from proprioceptive afferents to motor neurons with possibly organization advantages for motor control. The present premotor circuit mapping experiments, involving four different collaborating laboratories applying an extensive set of complementary RabV-based trans-synaptic circuit tracing techniques, convincingly demonstrate complete spatial overlap among flexor and extensor premotor interneurons, contradicting the previous mapping results that suggest spatial segregation. The present results revise our understanding of the spatial organization of spinal premotor circuits and provide an alternative view of the role of interneuron positioning in sensory input connectivity without specific spatial patterning of output connectivity to motoneurons, with fundamental implications for understanding motor circuit function.

Strengths of these studies include:

1. The investigators systematically tested and directly compared most of the available premotor circuit tracing strategies utilizing genetically modified mouse strains and viruses, as well as the previous approaches, with all tests replicating the spatial overlap of flexor and extensor premotor interneurons.

2. The authors utilized a mouse genetic strategy combining a Cre conditional allele expressing RabV glycoprotein G from the rosa locus with either the ChAT::Cre or Olig2::Cre mouse lines, which in contrast to previous RabV-based approaches, enables selective and potentially high levels of G expression in all motoneurons at the time of RabV muscle injection and likely robust transsynaptic transfer for premotor neuron labeling.

3. The authors present a very useful instructive exposition of the currently available techniques for labeling premotor interneurons outlining experimental strategies and indicating advantages and disadvantages for interpretation of results by illustrating RabV trans-synaptic transfer pathways that could confound experimental results.

4. The authors also used transgenic strategies in combination with their other approaches to differentiate inhibitory or putative excitatory premotor interneurons controlling the activity of flexor and extensor muscles and demonstrated from technically elegant spatial analyses that flexor and extensor premotor neurons were always spatially intermingled regardless of their neurotransmitter identity.

5. The authors further confirmed the lack of spatial segregation by pooling together all the results obtained with the different circuit tracing methods.

6. The authors thoroughly discuss the limitations of their mouse genetic strategy for circuit tracing including off-target G complementation in cells other than the targeted cholinergic motoneurons with the possibility of labeling disynaptic pathways via cholinergic spinal interneurons. Also considered is the problem in identifying the number of motoneurons with G complementation, which is a main determinant of reproducibility in RabV tracing experiments and a key parameter for comparing results from different circuit tracing approaches.

7. Overall the experiments are rigorously performed with a design that reduces biases associated with the various RabV-based circuit tracing methods, and the data although very extensive with numerous data source files and supplemental illustrations, are clearly presented.

Reviewer #1 (Public Review):

This project by Li et al. describes a colony morphology of P. aeruginosa that arises on agar plates and is especially pronounced in mutants lacking flagella, which were used for the majority of experiments in the paper. The paper documents the formation of large channels in the projections of swarming colonies, and within these channels, the rapid transport of fluid, cells, and extracellular vesicles. This transport is measured with great care and supported with additional support modeling.

- By and large, the project looks to have been executed with strong methodology and attention to detail in describing the channel formation effect found among colonies of P. aeruginosa flgK mutants. The authors have done very well in pushing known imaging methods to document transport within the colony channels and to make a case for how this transport is being driven physically. I think the aims of the detailed description of the physical phenomenon of colony growth in this environmental condition have been accomplished.

- A limitation here is that this colony morphology only seems to manifest strongly in mutants lacking flagella, which I don't think is common among wild P. aeruginosa isolates. To the extent that groups of P. aeruginosa cells have been imaged in situ, e.g. in the sputum of CF patients, this kind of channel formation does not occur in more realistic conditions. See DePas et al. (2015) https://journals.asm.org/doi/epub/10.1128/mBio.00796-16. I think it's more likely that this colony morphology is idiosyncratic to the agar growth substrate on which the cells are growing in this case, so the more interesting thing here is the physics of the system rather than its applications to clinical or ecological settings.

- The authors have established that flgK-null P. aeruginosa forms colonies with channels in this agar growth and incubation environment, and made a strong case for the physics underlying the spontaneous formation of this morphology. The idea that this morphology reflects a multicellular developmental program for P. aeruginosa is not strong, though, as this morphology is not found in the wild. In general, the idea that groups of microbes on agar are analogous to multicellular organisms with circulatory systems has little support from in-situ imaging experiments, or from fundamental evolutionary theory. So, I would advise shifting the introduction and discussion away from the multicellular organism focus toward a greater focus on the physics of the system and its potential for synthetic systems. See for example Yan et al. (2019) https://elifesciences.org/articles/43920

Reviewer #1 (Public Review):

The study presented by AL Seufert et al. follows the trajectory of trained immunity research in the context of sterile inflammatory diseases such as gout, cardiovascular disease and obesity. Previous studies in mice have shown that a 4 week Western-type diet is sufficient to induce systemic trained immunity, with gross reorganization of the bone marrow to support a potentiated inflammatory response [PMID: 29328911]. The current study demonstrates that mice on a Western-type diet (WD) and the more extreme Ketogenic diet (KD; where carbohydrates are essentially eliminated from the diet) for 2 weeks results in a state of increased monocyte-driven immune responsiveness when compared to standard chow diets (SC). This increased immune responsiveness after high-fat diet resulted in a deadly hyper-inflammatory in the mice in response to endotoxin (LPS) challenge in vivo. These initial findings as displayed in Figure 1 are made difficult to interpret because the authors use a mix of male and female mice coupled with very small sample sizes ( n = 5 - 9). Male and female mice are shown to have dimorphic responses to LPS exposure in vivo, with males having elevated cytokine levels (TNF, IL-6, IL-1β, and also interesting IL-10) increased rates severe outcomes to LPS challenge [PMID: 27631979]. As a reader it is impossible to discern from their methodological description what the proportion of the sexes were in each group, and therefore cannot determine if their data are skewed or biased due to sexual dimorphic responses to LPS rather than diet. Additionally due to the very small sample sizes, the authors can't perform a stratified analysis based on sex to determine whether the diets are having the greatest effects in accordance with LPS induce inflammation.

When comparing SC to the KD, the authors identify large changes in fatty acid distribution circulating in the blood. The majority of the fatty acids were shown to relate to saturated fatty acids (SFA). Although Lauric, Myristic, and Myristovaccenic acid where the most altered after KD, the authors focus their research on the more thoroughly studied palmitic acid (PA). PA was shown to increase the expression of inflammatory cytokines gene expression and protein production of TNF, IL-6 and IL-1β in bone marrow derived macrophages (BMDMs). The authors tie these effects to ceramide synthesis through a pharmacological blockade as well as the use of oleic acid, which allegedly sequesters ceramide synthesis. The author's claim that oleic acid supplementation reverses the inflammatory signaling induced by PA is invalid, as oleic acid was shown to induce a high level of cytokines in their model. When PA was added along with oleic acid, the cytokine levels returned to the levels produced by BMDM's stimulated with PA alone (see Figure 4 panels D- F).

Finally the authors test whether injection of PA into mice can recapitulate the systemic inflammatory response seen by WD and KD feeding followed by LPS exposure. They were able to demonstrate that injecting 1 mM of PA, waiting for 12h, and then exposing the mice to LPS for 24h could similarly result in a hyper-inflammatory state resulting in greater mortality. The reviewer is skeptical that 1 mM of PA truly represents post-prandial PA levels as one would expect to see after a single fatty meal, and whether this injection is generally well tolerated by mice. Looking into the paper cited by Eguchi et al. to inform their methods, it's shown that the earlier study continuously infused an emulsified ethyl palmitate solution (which contained 600 mM) at a rate of 0.2 uL/min. As far as I can read by Eguchi, they only managed to reach a serum PA concentration of 0.5 mM. This is hardly the same thing as a single i.p. injection of 1 mM PA. and reflects a single bolus injection of double the serum concentration of PA achieved by Eguchi et al.

PA is known to induce inflammation in monocytes and macrophages, therefore the findings certainly make sense in the context of previously published literature. However the authors have made some poor methodological decisions in their mouse studies, namely haphazardly switching between groups of young and old mice (4-6 weeks, 8-9 weeks, and 14-23 weeks), using different LPS injection protocols (6, 10, and 50 mg/ml of LPS), and including multiple sexes of mice. All of which are drastically alter the interpretation of the data, and preventing solid conclusions from being drawn.

Reviewer #1 (Public Review):

In this manuscript, the authors generated a zbtb14 mutant zebrafish strain via CRISPR-Cas9. In the mutant fish, they found an abnormal expansion of primitive macrophages during early development and adult macrophages in the kidney marrow. The abnormal expansion of macrophages in the mutants was confirmed to be caused by the loss of zbtb14 function, as over-expressing either zebrafish zbtb14 or human ZBTB14 could rescue the phenotype. To explore the underlying molecular mechanism, the authors performed RNA-seq analysis and found that the expression of pu.1 was up-regulation in the mutant macrophages. They further showed that the injection of mpeg1.1:pu.1-DBD construct into the mutant embryos to suppress the Pu.1 activity was able to rescue the mutant phenotype. The authors then went on to show that the SUMOylation of Zbtb14 plays an essential role in the transcriptional repression activity of the proteins. Finally, the authors documented that over-expressing the S8F mutant form of human ZBTB14, an AML associated mutation, failed to rescue the macrophage phenotype in zbtb14 mutants, suggesting that the loss of ZBTB14 function may be associated with the development of AML. Overall, the findings are interesting in developmental biology and gene regulation, especially in normal and malignant myelopoiesis.

Reviewer #1 (Public Review):

The authors have used many cleverly chosen mouse models (periodontitis models; various models that lead to an on-switch of genes) and methods (immune localizations of high quality; single cell RNA sequencing) for the quest of elucidating a role for telocytes. They describe that more telocytes are present around teeth in mice that had periodontitis. These cells proliferated, and they expressed a pattern of genes that allowed macrophages to differentiate into a different direction. In particular, they showed that telocytes in periodontitis express HGF, a molecule that steers macrophage differentiation towards a less inflammatory cell type, paving the way for recovery. As a weakness, one could state that an attempt to extrapolate to human cells is missing.

Reviewer #1 (Public Review):

It was previously shown that HGF and Met controls development of the diaphragm muscle. In particular, the signal induces delamination and migration of muscle progenitor cells that colonize the diaphragm. The present manuscript by Sefton and coworkers confirms and extends these observations using (i) conditional mouse lines in which the HGF gene was targeted by Cre/loxP recombination in the pleuroperitoneal folds (Prx1-cre) and at other sites PdgfraCreERT2, and of (ii) Met inhibitors. Overall, the technical quality of the data on diaphragm muscle development is excellent; the conceptual advance over previous work is not exceptional; the evidence for Met/HGF-dependent development of the phrenic nerve is marginal and needs to be strengthened.

The data show that fibroblasts provide HGF signals received by Met in muscle progenitor cells that is essential for diaphragm development. The PdgfraCreERT2 line was used to demonstrate that HGF produced by fibroblasts but not by muscle progenitors is essential for diaphragm development. Moreover, development of dorsal and ventral regions of diaphragm muscle requires continuous MET signaling. Thus, HGF is not only required for the delamination of progenitors, but also for proliferation and survival of those muscle progenitors that reached the anlage of the diaphragm.

My major concern is the limited data on the HGF-dependent development of the phrenic nerve (defasciculation). While it is well documented that HGF acts as a trophic factor for motor neurons in culture, its role in development of motor neurons was highly debated due to the fact that some changes observed in Met or HGF mutant mice in vivo are also present in other mutants that lack the muscle groups derived from migrating muscle progenitors. Moreover, careful genetic analyses previously demonstrated indirect mechanisms of Met during motor neuron development, i.e. a non-cell-autonomous function of Met during the recruitment of motor neurons to PEA3-positive motor pools (Helmbacher et al., Neuron 2003).

Sefton et al. provide an analysis of a single time point, one histological picture (3G, magnified in 3H) that indicate that in Met+/- animals defasciculation of the phrenic nerve does not occur correctly. This is accompanied by a quantification that barely reaches significance (Fig. 3K). Data shown in Fig. 7 using Met inhibitors show a major change in phrenic nerve branching, which is presumably due to the major change in diaphragm development, as conceded by the authors.

Despite this weakness on the experimental side, the role of HGF/Met in phrenic nerve development is strongly emphasized in abstract /intro/discussion (e.g. line 414: However, PPF-derived HGF is crucial for the defasciculation and primary branching of the nerve, independent of muscle). The data need to be strengthened in order to conclude that HGF coordinates both, diaphragm muscle and phrenic development.

סיימתי!

DOI: 10.1016/j.isci.2022.105028

Resource: (ZFIN Cat# ZDB-ALT-130506-1,RRID:ZFIN_ZDB-ALT-130506-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-130506-1

What is this?

Reviewer #1 (Public Review):

This Methods paper explores methods of assaying the balance between muscle cell quiescence and activation. If successful, it offers a miniaturized assay that will permit systematic investigations of long-standing queries in key areas of muscle function such as regulation of adult stem cell pool size and functional heterogeneity. It could also be used to discover regulators of quiescence.

Reviewer #1 (Public Review):

This paper represents the first spatio-temporal functional parcellation derived from infant multimodal imaging data. The parcellations are generated from the longitudinally collected baby connectome project, and clearly benefit from incorporating repeat samples from individuals. Analyses demonstrate that parcellations estimated for different age groups (3, 6, 9, 12, 18 and 24 months) are fairly consistent and that repeat generation of the parcellations, using shuffled 'generating' and 'repeating' groups is robust.

In general, I think the paper does an extremely good job of robustly testing its claims and therefore I have relatively few suggestions for improvement. However, I do have some concerns that the differences in network clustering reported in Fig 6 may be due to noise and I think the comparisons against the HCP parcellation could be more robust.

Specifically, with regard to the network clustering in Fig 6. The authors use a clustering algorithm (which is not explained) to cluster the parcels into different functional networks. They achieve this by estimating the mean time series for each parcel in each individual, which they then correlate between the n regions, to generate an nxn connectivity matrix. This they then binarise, before averaging across individuals within an age group. It strikes me that binarising before averaging will artificially reduce connections for which only a subset of individuals are set to zero. Therefore averaging should really occur before binarising. Then I think the stability of these clusters should be explored by creating random repeat and generation groups (as done for the original parcells) or just by bootstrapping the process. I would be interested to see whether after all this the observation that the posterior frontoparietal expands to include the parahippocampal gryus from 3-6 months and then disappears at 9 months - remains.

Then with regard to the comparison against the HCP parcellation, this is only qualitative. The authors should see whether the comparison is quantitatively better relative to the null clusterings that they produce.

While it's clear from the results that the template achieves some good degree of spatio-temporal coherence, from the considerable benefit of the longitudinal imaging, not all individuals appear (from Fig 8) to be acquired exactly at the desired timepoints, so maybe the authors might comment on why they decided not to apply any kernel weighted or smoothing to their averaging? Pg. 8 'and parcel numbers show slight changes that follow a multi-peak fluctuation, with inflection ages of 9 and 18 months' explain - the parcels per age group vary - with age with peaks at 9 and 18 - could this be due to differences in the subject numbers, or the subjects that were scanned at that point?

I also have some residual concerns over the number of parcels reported, specifically as to whether all of this represents fine grained functional organisation, or whether some of it represents noise. The number of parcels reported is very high. While Glasser et al 2016 reports 360 as a lower bound, it seems unlikely that the number of parcels estimated by that method would greatly exceed 400. This would align with the previous work of Van Essen et al (which the authors cite as 53) which suggests a high bound of 400 regions. While accepting Eickhoff's argument that a more modular view of parcellation might be appropriate, these are infants with underdeveloped brain function. Further comparisons across different subjects based on small parcels increases the chances of downstream analyses incorporating image registration noise, since as Glasser et al 2016 noted, there are many examples of topographic variation, which diffeomorphic registration cannot match. Therefore averaging across individuals would likely lose this granularity. I'm not sure how to test this beyond showing that the networks work well for downstream analyses but I think these issues should be discussed.

Finally, I feel the methods lack clarity in some areas and that many key references are missing. In general I don't think that key methods should be described only through references to other papers. And there are many references, particular to FSL papers, that are missing.

Reviewer #1 (Public Review):

In this paper, Abadchi et al. investigate neocortical activity patterns surrounding sharp-wave ripples in awake head-fixed mice. To do so, the authors combine multiple approaches, including wide-field voltage and glutamate imaging, 2-photon single-cell calcium imaging, and electrophysiology, used to monitor the hippocampal LFP and MUA. The authors' previous findings in anaesthetized and head-fixed sleeping mice indicated that the majority of cortical areas were strongly activated by ripples. In contrast, they now show that ripple-related neocortical patterns in the awake brain show predominantly suppression of activity. Interestingly, this deactivation seems to be most pronounced and to occur earliest in the agranular retrosplenial cortex (aRSC). To gain a better understanding of the internal dynamics underlying ripple modulation in the RSC the authors perform 2-photon calcium imaging and find that similar proportions of superficial excitatory cells are activated and suppressed during ripples.

Ripple oscillations have been implicated in multiple cognitive processes including memory consolidation, memory retrieval, and planning, and there is causal evidence suggesting that awake and sleep ripples are differentially involved in those functions. Consequently, understanding the physiological mechanisms underlying hippocampal-neocortical communication during both brain states is of pivotal importance. Many studies investigated the modulation of various cortical areas by ripples during sleep and wakefulness, but the majority of those studies focused on one or few areas. The author's previous study (Abadchi et al., 2020) was an exception in this regard, as it provided a rich characterization of activity surrounding sleep ripples in multiple neocortical areas, including latency to response and direction of propagation. The present study purports to be complementary to those published results, although it lacks many of the analyses used for the sleep paper, which is a missed opportunity. The stark sleep/wake differences in cortical peri-ripple activity reported by the authors are surprising, interesting, and potentially of substantial importance for understanding the functions of ripples in the awake vs. sleep state. However, many of the results presented in the paper are insufficiently analyzed and their statistical significance is unclear, demanding further quantification and clarifications. Moreover, while the paper's major strength lies in the combination of multiple large-scale approaches, it could do better in combining those observations into a coherent conclusion.

Major points:

1) There is affluent evidence that the cortical activity in the waking brain, even in head restrained mice, is not uniform but represents a spectrum of states ranging from complete desynchronization to strong synchronization, reminiscent of the up and down states observed during sleep (Luczak et al., 2013; McGinley et al., 2015; Petersen et al., 2003). Moreover, awake synchronization can be local, affecting selective cortical areas but not others (Vyazovskiy et al., 2011). State fluctuations can be estimated using multiple criteria (e.g., pupil diameter). The authors consider reduced glutamatergic drive or long-range inhibition as potential sources of the voltage decrease but do not attempt to address this cortical state continuum, which is also likely to play a role. For example: does the voltage inactivation following ripples reflect a local downstate? The authors could start by detecting peaks and troughs in the voltage signal and investigate how ripple power is modulated around those events.

2) Ripples are known to be heterogeneous in multiple parameters (e.g., power, duration, isolated events/ ripple bursts, etc.), and this heterogeneity was shown to have functional significance on multiple occasions (e.g. Fernandez-Ruiz et al., 2019 for long-duration ripples; Nitzan et al., 2022 for ripple magnitude; Ramirez-Villegas et al., 2015 for different ripple sharp-wave alignments). It is possible that the small effect size shown here (e.g. 0.3 SD in Fig. 2a) is because ripples with different properties and downstream effects are averaged together? The authors should attempt to investigate whether ripples of different properties differ in their effects on the cortical signals.

3) The differences between the voltage and glutamate signals are puzzling, especially in light of the fact that in the sleep state they went hand in hand (Abadchi et al., 2020, Fig. 2). It is also somewhat puzzling that the aRSC is the first area to show voltage inactivation but the last area to display an increase in glutamate signal, despite its anatomical proximity to hippocampal output (two synapses away). The SVD analysis hints that the glutamate signal is potentially multiplexed (although this analysis also requires more attention, see below), but does not provide a physiologically meaningful explanation. The authors speculate that feed-forward inhibition via the gRSC could be involved, but I note that the aRSC is among the two major targets of the gRSC pyramidal cells (the other being homotypical projections) (Van Groen and Wyss, 2003), i.e., glutamatergic signals are also at play. To meaningfully interpret the results in this paper, it would be instrumental to solve this discrepancy, e.g., by adding experiments monitoring the activity of inhibitory cells.

4) I am puzzled by the ensemble-wise correlation analysis of the voltage imaging data: the authors point to a period of enhanced positive correlation between cortex and hippocampus 0-100 ms after the ripple center but here the correlation is across ripple events, not in time. This analysis hints that there is a positive relationship between CA1 MUA (an indicator for ripple power) and the respective cortical voltage (again an incentive to separate ripples by power), i.e. the stronger the ripple the less negative the cortical voltage is, but this conclusion is contradictory to the statements made by the authors about inhibition.<br /> 5) Following my previous point, it is difficult to interpret the ensemble-wise correlation analysis in the absence of rigorous significance testing. The increased correlation between the HPC and RSC following ripples is equal in magnitude to the correlation between pre-ripple HPC MUA and post-ripple cortical activity. How should those results be interpreted? The authors could, for example, use cluster-based analysis (Pernet et al., 2015) with temporal shuffling to obtain significant regions in those plots. In addition, the authors should mark the diagonal of those plots, or even better compute the asymmetry in correlation (see Steinmetz et al., 2019 Extended Fig. 8 as an example), to make it easier for the reader to discern lead/lag relationships.

6) For the single cell 2-photon responses presented in Fig. 3, how should the reader interpret a modulation that is at most 1/20 of a standard deviation? Was there any attempt to test for the significance of modulation (e.g., by comparing to shuffle)? If yes, what is the proportion of non-modulated units? In addition, it is not clear from the averages whether those cells represent bona fide distinct groups or whether, for instance, some cells can be upmodulated by some ripples but downmodulated by others. Again, separation of ripples based on objective criteria would be useful to answer this question.

7) Fig. 3: The decomposition-based analysis of glutamate imaging using SVD needs to be improved. First, it is not clear how much of the variance is captured by each component, and it seems like no attempt has been made to determine the number of significant components or to use a cross-validated approach. Second, the authors imply that reconstructing the glutamate imaging data using the 2nd-100th components 'matches' the voltage signal but this statement holds true only in the case of the aRSC and not for other regions, without providing an explanation, raising questions as to whether this similarity is genuine or merely incidental.

8) The estimation of deep pyramidal cells' glutamate activity by subtracting the Ras group (Fig. 4d) is not very convincing. First, the efficiency of transgene expression can vary substantially across different mouse lines. Second, it is not clear to what extent the wide field signal reflects deep cells' somatic vs. dendritic activity due to non-linear scattering (Ma et al., 2016), and it is questionable whether a simple linear subtraction is appropriate. The quality of the manuscript would improve substantially if the authors probe this question directly, either by using deep layer specific line/ 2-P imaging of deep cells or employing available public datasets.

Cited literature<br /> Abadchi, J.K., Nazari-Ahangarkolaee, M., Gattas, S., Bermudez-Contreras, E., Luczak, A., McNaughton, B.L., and Mohajerani, M.H. (2020). Spatiotemporal patterns of neocortical activity around hippocampal sharp-wave ripples. Elife 9, 1-26.<br /> Fernandez-Ruiz, A., Oliva, A., Oliveira, E.F. De, Rocha-Almeida, F., Tingley, D., and Buzsáki, G. (2019). Long-duration hippocampal sharp wave ripples improve memory. Science (80-. ). 364, 1082-1086.<br /> Van Groen, T., and Wyss, J.M. (2003). Connections of the Retrosplenial Granular b Cortex in the Rat. J. Comp. Neurol. 463, 249-263.<br /> Luczak, A., Bartho, P., and Harris, K.D. (2013). Gating of Sensory Input by Spontaneous Cortical Activity. J. Neurosci. 33, 1684-1695.<br /> Ma, Y., Shaik, M.A., Kim, S.H., Kozberg, M.G., Thibodeaux, D.N., Zhao, H.T., Yu, H., and Hillman, E.M.C. (2016). Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches. Philos. Trans. R. Soc. B Biol. Sci. 371.<br /> McGinley, M.J., David, S. V., and McCormick, D.A. (2015). Cortical Membrane Potential Signature of Optimal States for Sensory Signal Detection. Neuron 87, 179-192.<br /> Nitzan, N., Swanson, R., Schmitz, D., and Buzsáki, G. (2022). Brain-wide interactions during hippocampal sharp wave ripples. Proc. Natl. Acad. Sci. 119.<br /> Pernet, C.R., Latinus, M., Nichols, T.E., and Rousselet, G.A. (2015). Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields: A simulation study. J. Neurosci. Methods 250, 85-93.<br /> Petersen, C.C.H., Hahn, T.T.G., Sakmann, B., Grinvald, A., and Mehta, M. (2003). Interaction of sensory responses with spontaneous depolarization in layer 2/3 barrel cortex. Proc. Natl. Acad. Sci. 100, 13638-13643.<br /> Ramirez-Villegas, J.F., Logothetis, N.K., and Besserve, M. (2015). Diversity of sharp-wave-ripple LFP signatures reveals differentiated brain-wide dynamical events. Proc. Natl. Acad. Sci. 112, E6379-E6387.<br /> Steinmetz, N.A., Zatka-Haas, P., Carandini, M., and Harris, K.D. (2019). Distributed coding of choice, action and engagement across the mouse brain. Nature 1-8.<br /> Vyazovskiy, V. V, Olcese, U., Hanlon, E.C., Nir, Y., Cirelli, C., and Tononi, G. (2011). Local sleep in awake rats. Nature 472, 443-447.

Reviewer #1 (Public Review):

The Cretaceous dinosaur Spinosaurus has recently drawn significant attention as it was hypothesized as the first aquatic dinosaur. The authors provide additional lines of evidence including the CT-based skeletal restoration of Spinosaurus and biomechanical tests to challenge the 'aquatic hypothesis'. The key claims of the manuscript are supported by the new data and the new analyses are important for the further clarification of the Spinosaurus lifestyle.

Reviewer #1 (Public Review):

Bosada et al present a study on how regulatory elements found in two atrial fibrillation-associated regions at the TBX5 locus correlate to Tbx5 expression levels and arrhythmia susceptibility. In transgenic mouse models, the investigators deleted the orthologues of these regulatory elements at the human Tbx5 locus. Tbx5 expression levels were increased in both models, and the downstream impact on epigenetic and gene expression levels was assessed. The RE(int)-/- mice had higher expression levels of Tbx5 compared to RE(down)-/- mice and this was correlated with increased atrial arrhythmia inducibility and higher numbers of transcripts impacted in the atrial gene regulatory network analysis. Multiple pathways are affected, and the authors present data on the interaction between Tbx5 and Prrx1, which encodes a cardiac transcription factor and the human ortholog harbors an atrial fibrillation-associated variant. The presented work links with the prior observation that increase in Tbx5 expression is associated with human atrial fibrillation and provides a plausible mechanistic link.

Reviewer #1 (Public Review):

The authors aim at establishing a biologically plausible learning rule for the Successor Representation (SR) to be computed by neural circuits.

The study is well designed with a strong logical flow moving from a simple example (random process on a circle) to comparison with real neural data. The manuscript is well written in all its components and figures are clear. All the results provided in the main paper are backed up by a thorough theoretical analysis outlined in the supplementary material. As it is common the theoretical analysis does not have much space in the manuscript. I would suggest summarizing with more specific statements the theoretical results that are achieved whenever there is a pointer to a supplementary note.

While the authors perform an extensive and careful review of the literature, a lot of it is confined to the Discussion. As the results of the paper strongly rely on the normalizing term in Eq.4. I would suggest potentially moving upfront part of the discussion of this term. I would suggest enlarging the paragraph that discusses the biological plausibility of this specific term. Clearly laying out, for the non-expert reader, why it is biologically plausible compared to other learning rules. And I would also consider moving the required material to establish the novelty of such term: a targeted review of the relevant literature (current lines 358-366 and 413-433). This would allow the reader to understand immediately the significance and relative novelty of such term. For example, I personally wondered while reading the paper how different was such term from the basic idea of Fiete et al. Neuron 2010 (DOI 10.1016/j.neuron.2010.02.003).

I would also suggest writing a "limitations" paragraph in the discussion clearly outlining what this learning rule couldn't achieve. For example, Stachenfeld et al Nat.Neuro. have many examples where the SR is deployed. I wonder if the learning rule suggested by the authors would always work across the board, or if there are limitations that could be highlighted where the framework suggested would not work well. I am not suggesting performing more experiments/simulations but simply sharing insight regarding the results and the capability of the proposed learning rule.

Reviewer #1 (Public Review):

This is an elegant and fascinating paper on individuality of structural covariance networks in the mouse. The core precepts are based on a series of landmark papers by the same authors that have found that individuality exists in inbred mice, and becomes entrenched when richer environments are available. Here they used structural MRI to provide whole brain analyses of differences in brain structure. They first replicated brain (mostly hippocampal) effects of enrichment. Next, they used their roaming entropy measurements to show that, after dividing their mice into two groups based on their roaming entropy, that there were no differences in brain structure between the two groups yet significant differences in brain networks as measured by structural covariance. Overall I enjoyed this paper, though am confused (and possibly concerned) about how they arrived at their two groups and have some less important methods questions.

The division of mice into two groups (down and flat) is confusing. The methods appear to suggest that k-means clustering combined with the silhouette method was used (line 380). The actual analyses used involves 2 groups of 15 mice each. The body of the manuscript suggests that 10 intermediate mice were excluded (line 100), but the methods (line 390) suggest that 8 mice were excluded, 2 for having intermediate results and 6 for having high RE slope values.

This leads to a series of questions:<br /> - How many mice were excluded and for what reasons, given the discrepancy between body and methods?<br /> - Was the k-means clustering actually used? It appears that the main division of mice was based on visual assessments.<br /> - If the clustering was used, did it result in 2 or 3 groups?<br /> - The intermediate group bothers me (if it was indeed 10 intermediate mice as indicated by the body rather than 2 as indicated in the methods): if these are indeed intermediate shouldn't they be analyzed and shown to be intermediate on the graph or other measures?<br /> - Please explain the reasoning for excluding mice for having too high of a slope (if there were indeed mice excluded for having too high of a slope).

I'd also appreciate more discussion about the structural covariance differences between flat and down mice. It is not clear what the direction of effects are - it appears that flats show mostly increases in covariance?

Reviewer #1 (Public Review):

This is a very timely and substantial advance in connectomics research that allows the fast reconstruction of selected neuronal circuits at synaptic resolution using tissue expansion and light sheet imaging. The authors describe this methodology in detail as applied to Drosophila brain, with multiple examples across different neuronal types and labeling strategies. The study is very rigorously done, methods are presented with important details, and the discussion is engaging and balanced. The paper is excellently written and very informative.

The authors begin by introducing a workflow to detect and quantify presynaptic structures of specific neuronal types. This approach takes advantage of the T-bar protein Brp ubiquitously expressed at presynapses and the widely used nc82 antibody against it, as well as the fact that presynapses are larger neurites that are readily resolvable with light microscopy. Using three distinct neuronal types, the authors show that the number of presynapses obtained with the presented light microscopy method, matches well the synapse number quantified by the gold standard, electron microscopy.

Next, the authors present two approaches to tackle a more difficult task - the quantification of the synaptic connectivity between 2 specific neuronal types. Compared to mammals, the identification of the postsynaptic site is more difficult in the Drosophila, because each presynapse contacts several different postsynaptic neurites that are right next to each other and are much smaller in size. No ubiquitous postsynaptic marker is currently available for the fly brain either. However when there is a postsynaptic marker available for specific connection, this makes the synaptic connection identification much more reliable, as shown with the example of the synaptic connections between the cholinergic SAG neurons and their postsynaptic target, the pC1 neurons, using the postsynaptic marker Drep2. Using this strategy the authors demonstrate that mated female flies have significantly less synaptic connections between SAG neurons and pC1 neurons, compared to virgin flies.

In addition to chemical synapses, this study also shows a proof of principle that electrical synapses, gap junctions, can similarly be mapped using the same approach. This is very important, because these synapses are much more difficult to identify with electron microscopy and are not currently included in the available Drosphila connectomes. Definitive mapping of gap junctions however will require further work, outside the scope of this study, because there are different gap junction proteins and individual gap junctions may be heterotypic, composed of two different proteins.

Finally, the authors extend this approach to address the important question of whether variations in behavior can be explained by differences in underlying synaptic connectivity. Using the neuronal circuit known to be responsible for the male fly courtship song, the authors show that the synaptic connectivity between pC2l and pIP10 neurons is correlated with a specific component of the optogenetically-elicited fly song.

The developed imaging and analysis pipeline includes software for visualization of multi-terabyte images, automated neuronal segmentation, detection and quantification of pre- and postsynaptic sites. As the authors point out, these tools could be useful for circuit analysis in other species as well. The different imaging and analysis pipelines are presented very well, with multiple examples that cover different scenarios, and are well validated. While with this method it is not possible to directly correlate the fluorescence signal with the underlying ultrastructure as seen with EM, and thus it cannot be confirmed that the detected synaptic connections correspond to ultrastructurally defined synapses, the authors have convincingly demonstrated that the proposed approach is precise enough to detect a similar number of synapses as EM studies of the same neurons, and that it is sensitive enough to detect changes in synapse numbers in different experimental conditions.

Reviewer #1 (Public Review):

Current generative models of protein sequences such as Potts models, Variational autoencoders, or autoregressive models must be trained on MSA data from scratch. Therefore, they cannot learn common substitution or coevolution patterns shared between families, and require a substantial number of sequences, making them less suitable for small protein families (e.g., conserved only for eukaryotes or viruses). MSA transformers are promising alternatives as they can generalize across protein families, but there is no established method to generate samples from them. Here, Sgarbossa et al. propose a simple recursive sampling procedure based on iterative masking to generate novel sequences from an input MSA. The sampling method has three hyperparameters (masking frequency, sampling temperature, and the number of iterations) which are set by rigorous benchmarking. The authors compare their approach to bmDCA, and evaluate i) single sample quality metrics ii) sample diversity and similarity to native sequences iii) similarity between original and generated sequence distribution, and iv) phylogeny/topology in sequence space of the generated distribution.

Strengths:

- The proposed sampling approach is simple.<br /> - The computational benchmarking is thorough.<br /> - The code is well organized and looks easy to use.

Weaknesses:

- There is no experimental data to back up the methodology.<br /> - It is not clear whether the sampling hyperparameter used is optimal for all protein sizes.<br /> - I am unsure that the bmDCA baseline method was trained appropriately and that the sampling method was adequate for protein design purposes (regular sampling).<br /> - Quality assessment of predicted structures is incomplete.<br /> - The proposed metrics for evaluating the diversity of generated sequences are fairly technical.

Impact assessment: The claim that MSA Transformer could be useful for protein design is supported by the computational benchmark. This work will be useful for researchers interested in applying MSA-Transformer models for protein design

Reviewer #1 (Public Review):

Our understanding of the early stages of myelination within the CNS is relatively rudimentary. In this manuscript the authors use selective cell labeling to visualize the initial interactions between individual oligodendrocytes and their target axons in the developing zebra fish with the goal of understanding the regulation of myelin sheath formation.

There are considerable strengths to the manuscript. The work extends earlier studies through the use of high spatial and temporal resolution analysis. This approach reveals a highly dynamic interaction between oligodendrocyte processes and local axons that had not previously been appreciated. The data on the initial interactions between an individual oligodendrocyte and its target axons is closely analyzed, which reveals a number of interesting traits. For example, while dorsal cells have a higher number of initial axonal interactions and ultimately myelinate more axons than ventral cells, the proportion of initial interactions that lead to a myelin sheath is similar between the two populations. To begin to examine the molecular regulation of the initial oligodendrocyte and axon interactions and subsequent formation of myelin sheaths the authors perturb selective components of the endocytic pathway and provide evidence that disruption of Rab5 selectively affects the long-term stabilization of myelin sheaths.

While there are some new advances in the current manuscript, the significance of many of the observations is unclear. For example, while the data documents extensive interactions between oligodendrocytes and axons, the nature of those interactions is not well defined. The authors describe the loss of olig/axon interactions as "ensheathment destabilization" however, it is not clear from the data that they don't represent simple oligodendrocyte process retraction.

The different interactions of dorsal and ventral cells with their target axons is interesting and may reflect different oligodendrocyte populations or environments.

Reviewer #1 (Public Review):

In this manuscript, the authors investigate the genes involved in the retention of eggs in Aedes aegypti females. They do so by identifying two candidate genes that are differentially expressed across the different reproductive phases and also show that the transcripts of those two genes are present in ovaries and in the proteome. Overall, I think this is interesting and impressive work that characterizes the function of those two specific protein-coding genes thoroughly. I also really enjoyed the figures. Although they were a bit packed, the visuals made it easy to follow the authors' arguments. I have a few concerns and suggested changes, listed below.

1. These two genes/loci are definitely rapidly evolving. However, that does not automatically imply that positive selection has occurred in these genes. Clearly, you have demonstrated that these gene sequences might be important for fitness in Aedes aegypti. However, if these happen to be disordered proteins, then they would evolve rapidly, i.e., under fewer sequence constraints. In such a scenario, dN/dS values are likely to be high. Another possibility is that as these are expressed only in one tissue and most likely not expressed constitutively, they could be under relaxed constraints relative to all other genes in the genome. For instance, we know that average expression levels of protein-coding genes are highly correlated with their rate of molecular evolution (Drummond et al., 2005). Moreover, there have clearly been genome rearrangements and/or insertion/deletions in the studied gene sequences between closely-related species (as you have nicely shown), thus again dN/dS values will naturally be high. Thus, high values of dN/dS are neither surprising nor do they directly imply positive selection in this case. If the authors really want to investigate this further, they can use the McDonald Kreitman test (McDonald and Kreitman 1991) to ask if non-synonymous divergence is higher than expected. However, this test would require population-level data. Alternatively, the authors can simply discuss adaptation as a possibility along with the others suggested above. A discussion of alternative hypotheses is extremely important and must be clearly laid out.

2. The authors show that the two genes under study are important for the retention of viable eggs. However, as these genes are close to two other conserved genes (scratch and peritrophin-like gene), it is unclear to me how it is possible to rule out the contribution of the conserved genes to the same phenotype. Is it possible that the CRISPR deletion leads to the disruption of expression of one of the other important genes nearby (i.e., in a scratch or peritrophin-like gene) as the deleted region could have included a promoter region for instance, which is causing the phenotype you observe? Since all of these genes are so close to each other, it is possible that they are co-regulated and that tweedledee and tweedledum and expressed and translated along with the scratch and peritrophin-like gene. Do we know whether their expression patterns diverge and that scratch and peritrophin-like genes do not play a role in the retention of viable eggs?

References:<br /> Drummond DA, Bloom JD, Adami C, Wilke CO, Arnold FH. 2005. Why do highly expressed proteins evolve slowly? Proc Natl Acad Sci U S A. 102:14338-14343.

McDonald JH, Kreitman M. 1991. Adaptive protein evolution at the Adh locus in Drosophila. Nature. 351:652-654. doi: 10.1038/351652a0.

Reviewer #1 (Public Review):

The rice sensor NLR protein Pik-1 carries a HMA domain to sense fungal AVR proteins. Past studies have shown that it is possible to modify the HMA domain to change new recognition specificity. However, whether this approach can generate broad-spectrum NLRs that function in rice plants remains to be shown. Prior work from the authors have shown that each of the existing Pik-1 alleles only recognizes some, but not all AVR-Pik alleles. Interestingly, they found that a natural rice target protein HIPP19 is capable of binding to all known AVR-Pik proteins. In the current study, the authors tested the idea that AVR-Pik-binding sequence in HIPP19 could be utilized to engineer Pik-1 protein with broader recognition specificity. Strikingly, the engineered Pikp-1OsHIPP19-mbl7 is capable of recognizing AVR-PikD, C, and F, whereas the original Pikp-1 is only capable of recognizing Avr-PikD. This is supported by both HR-elicitation and protein-protein interactions in N. benthamiana plants. The authors further used a structure-guided approach to identify specific amino acids responsible for expanded recognition of AVR proteins. To this end, they show that the Pikp-1SNK-EKE variant is capable of recognizing all three of the aforementioned AVR-Pik proteins. The proper interactions of the newly introduced amino acids with the Avr-Pik proteins were nicely demonstrated with structural work. Most excitingly, the Pikp-1OsHIPP19-mbl7 and Pikp-1SNK-EKE constructs were introduced in to rice plants lacking Pik-1 as stable transgenes. These lines displayed disease resistance to rice blast strains carrying any of the three AVR-Pik proteins. Overall, the study is well executed and shows how knowledge of structural and evolutionary studies can help engineering disease resistance in a major crop plant. The weakness is with the use of a strong promoter to drive the expression of the engineered Pikp-1 variants in rice and a lack of assessment of potential effects on traits.

Reviewer #1 (Public Review):

This is an awesome comprehensive manuscript. Authors start by sorting putative stromal cell-containing BM non-hematopoietic (CD235a-/CD45-) plus additional CD271+/CD235a-/CD45- populations to identify nine individual stromal identities by scRNA-seq. The dual sorting strategy is a clever trick as it enriches for rare stromal (progenitor) cell signals but may suffer a certain bias towards CD271+ stromal progenitors. The lack of readable signatures already among CD45-/CD45- sorts might argue against this fear. This reviewer would appreciate a brief discussion on number & phenotype of putative additional MSSC phenotypes in light of the fact that the majority of 'blood lineage(s)'-negative scRNA-seq signatures identified blood cell progenitor identities (glycophorin A-negative & leukocyte common antigen-negative). The nine stromal cell entities share the CXCL12, VCAN, LEPR main signature. Perhaps the authors could speculate if future studies using VCAN or LEPR-based sort strategies could identify additional stromal progenitor identities?

The authors furthermore localized CD271+, CD81+ and NCAM/CD56+ cells in BM sections in situ. Finally, referring to the strong background of the group in HSC research, in silico prediction by CellPhoneDB identified a wide range of interactions between stromal cells and hematopoietic cells. Evidence for functional interdependence of FCU-F forming cells is completing the novel and more clear bone marrow stromal cell picture.<br /> An illustrative abstract naming the top9 stromal identities in their top4 clusters by their "top10 markers" + functions would be highly appreciated.

Reviewer #1 (Public Review):

The present study used an innovative meta-analytic approach to elucidate the functional organization of the lateral prefrontal cortex (LPFC). Co-activation profiles based upon over 14,000 fMRI studies revealed a principle rostral-caudal gradient in the LPFC, as well as a secondary dorsal-ventral gradient. Rostral-ventral zones in this gradient tended to contain areas in cognitive control (Control B) and salience networks and were associated with terms involving memory and affect. Caudal-dorsal zones in the gradient tended to contain areas in cognitive control (Control A) and spatial attention networks and were associated with terms involving perception and action. Areas in-between overlapped prominently with a variety of networks including Control A and were associated with various cognitive terms associated with language, working memory, and cognitive control. Moreover, the authors found hemispheric asymmetries with the left hemisphere associated with language-related topics and the right hemisphere with response inhibition and error processing. Hemispheric differences did not show an obvious rostral-caudal topography. Collectively, the data provide quantification of the general organization of the LPFC along rostral-caudal, dorsal-ventral, and hemispheric axes. From the associations of networks and terms, the authors conclude that the rostral-caudal axis reflects an internal/external axis, with areas in the middle supporting integrative processing.

Detailing the functional organization of the LPFC has remained a challenge given the diversity of its functions and widespread involvement across various tasks. Due to the limitations of single studies in terms of what can be measured (i.e. number of tasks used), construct validity of what is measured (e.g. purity of contrasts), and the reliability and reproducibility with which things can be measured, a meta-analysis of this scale can provide a welcome synthesis.

A major challenge with meta-analyses of fMRI data is obtaining appropriate specificity. Most meta-analytic methods that have been applied to fMRI data are both spatially and functionally coarse, which hinders efforts to properly synthesize the literature. Here, the authors employ innovative techniques to maximize specificity insofar as possible. As a result, the present data can be considered our best summary to date of the functional organization of the LPFC as detailed by fMRI.

Even as the study has innovated over previous attempts, limitations of meta-analyses must still be considered. Meta-analysis will never have the spatial resolution of well-performed individual studies. Indeed, the techniques used here may cause spatial blurring given the impression of spatially ordered consistency which may not actually be present. For example, there are data to suggest that there may be multiple rostral-caudal axes along the LPFC, which can potentially be blurred together into a single axis here. So, the spatial organization detailed here may offer a gross overall picture of how the LPFC is organized, but we will naturally get more fine-grained details from carefully conducted individual studies.

Nevertheless, the approach used here is helpful not only for detailing the functional organization of the LPFC, but as a proof-of-concept that can be applied to future investigations. These techniques may be helpful for detailing the organization of other heteromodal zones of the brain such as the medial frontal wall, and parietal cortices, offering a means of distilling the thousands of fMRI studies that have been conducted into a comprehensive whole.

Reviewer #1 (Public Review):

Oppong and colleagues present a study on the association of mitochondrial DNA abundance in blood and personality traits, both of which have been linked to morbidity and mortality in aging populations. They found that mtDNAcn is negatively associated with traits related to neuroticism as well as positively with a higher personality-mortality index (PMI). The association of the PMI with mortality was attenuated by including mtDNAcn in the model, indicating that the association is mediated by mitochondrial abundance in blood.

General comments:<br /> • Previous studies have shown that mtDNAcn are potentially mediated by hormonal levels and thus menopause. Given the mean age of 57 in the SardiNIA cohort, the authors should investigate in more detail the potential confounding effects of menopause in women.<br /> • The only personality trait (out of the big five) available in the UK Biobank is neuroticism. Since the authors found that most of their associations are significant for this complex, I would strongly suggest they try to replicate their findings in patients from the UK Biobank which have both, genome-wide sequencing data as well the summary score of neuroticism (Data-Field 20127)<br /> • The amount of mtDNA varies across populations and across different haplogroups. The authors should therefore compute the major haplogroups present in Europeans and adjust/account for those variables in the correlation and mortality analyses.

Reviewer #1 (Public Review):

Liu et. al. applied an existing method to study the subtypes of CRC from a network perspective. In the proposed framework, the authors calculated the perturbation of expression-rank differences of predefined network edges in both tumor and normal samples. By clustering the derived perturbation scores in CRC tumors using publicly available gene expression datasets, they reported six subtypes (referred to as GINS 1-6) and then focused on the association of each subtype with clinical features and known molecular mechanisms and cell phenotypes. My recommendation is major revision.

Major concerns:

(1) While this study originates from the network-perspective, it is unclear to me if the new subtypes provide key novel insights into the gene regulatory mechanisms for the development of CRC. For example, the "Biological peculiarities of six subtypes" section is descriptive and lacks a punch point.

(2) To further demonstrate the novelty of the identified subtypes, the authors need to show the additional benefit of the GINS1-6 to patient stratification derived from existing methods, such as integrative clustering based on multiple genomic evidence (copy number alterations, gene expression and somatic mutations).

Reviewer #1 (Public Review):

The hippo signaling pathway has emerged as a key signaling pathway in cancer and many other diseases, but there is a lack of high-quality chemical tools that would enable functional studies. The developed chemical probe targeting TEAD is therefore a much-needed chemical tool enabling more functional studies on this pathway in diverse diseases. The chemical MYF-03-69 is comprehensively characterized and it, therefore, represents a high-quality probe for future studies.

Reviewer #1 (Public Review):

The manuscript "BRCA2 BRC missense variants disrupt RAD51-dependent DNA repair" by Jimenez-Sainz et al focuses on the characterization of three BRCA2 mutants that were previously classified as Variants of Uncertain Significance (VUS) with unknown functional consequences. Mutations in the BRCA2 tumor suppressor gene predispose to breast, ovarian, pancreatic, prostate, and other cancers and are responsible for nearly half of all hereditary breast cancers and ovarian cancers. Identification of truly pathogenic BRCA2 missense mutations is a challenging but very important task for early cancer diagnostics. In this study, the authors developed a methodology for the identification of pathogenic BRCA2 mutations. They performed comprehensive analyses of three BRCA2 mutations including S1221P and T1980I, which map to conserved residues in the BRC2 and BRC7 repeats, and T1346I, located within the spacer region between BRC2 and BRC3 repeats. Using an impressive array of cellular and biochemical approaches they demonstrated that the first two BRCA2 mutants have a detrimental effect on RAD52-dependent DNA repair, and therefore likely to be pathogenic. In contrast, T1980I seems to have no effect on DNA repair in various tested assays and is likely to be a passenger mutation.

Overall, I found the presented study of high quality. The developed methodology can be applied for analyses of other potentially pathogenic mutations in BRCA1, BRCA2, or other genes involved in DNA double-strand break repair. The work may have a broad impact on the biomedical field. The presentation quality is good as well.

Reviewer #1 (Public Review):

In this manuscript the authors found a direct synaptic connection between inhibitory neurons in the central nucleus of the amygdala and inhibitory and other neurons in the zona incerta. They conducted a rigorous and detailed anatomical study of both the anterograde and retrograde connections between PKCdelta CeA neurons and the zona incerta. Furthermore they conducted rigorous chemogenetic investigation of the zona incerta inhibitory neurons across pain modalities. This led to the overall conclusion that PKCdelta neurons inhibit zona incerta inhibitory neurons leading to enhanced pain processing. While the results mainly support the conclusions, there is a lack of direct support for the CeA-PKCdelta-->vGAT-ZI hypothesis.

Reviewer #1 (Public Review):

The authors use both genome-wide correlations between genetic effects on metabolite pairs ('genetic correlation') and the pleiotropic effects of individual genetic variants to build an understanding of how biochemical pathways relate to global ('genetic correlation') and local (individual variant or pathway) pleiotropy. The authors look at metabolites, which are themselves interesting and predictive of metabolic health, but also serve as a useful 'model system' for understanding genetic correlation.

The authors demonstrate that genetic variants that have 'discordant' effects on a pair of metabolites, i.e. effects whose product of signs is opposite to the sign of the genome-wide genetic correlation, tend to be variants (likely) affecting pathway-relevant enzyme or transporter genes and/or affect biochemical pathways 'between' the two metabolites.

The authors attempt to extend this further to a variant associated with coronary artery disease (CAD), which they hypothesize to act by decreasing the activity of the gene PCCB. While an interesting hypothesis, establishing such a mechanism in the etiology of CAD would require further validation.

This paper represents an advance in linking statistical genetics constructs such as 'genetic correlation' to a biochemical mechanism for an important case: metabolites. While I expect their approach to be influential in showing how to dissect genetic correlation in a way that can point to the biological mechanism, extending their method to more complex phenotypes with less well-characterized biochemical pathways may be challenging.

Reviewer #1 (Public Review):

In this study, the authors aim to analyze the functions of the motor subunit klc4 in nervous system development and function. This is an important question to address, as not much is known about the cellular functions of klc4 even though mutations in this gene cause early onset hereditary spastic paraplegia in human. The authors used CRISPR/Cas9 to generate a klc4 mutant in zebrafish and analyzed the development of sensory neurons in embryos as well as behavior in adults. The strengths of this study include the generation of a novel klc4 mutant in zebrafish, the use of high and super-resolution live microscopy over time coupled to a rigorous analysis to reveal unsuspected developmental defects in klc4 mutants, including the formation of aberrant projections by sensory neurons and an abnormal development of peripheral sensory axons that appear less branched and fail to repel each other. The behavioral assays conducted by the authors also yielded robust results supporting a role for klc4 in adult neural circuits regulating stress response. The data are very well quantified and support the key findings of the study. Although the study does not delineate the molecular mechanisms causing an abnormal development of sensory neurons, its findings have a high impact, as they suggest specific functions of Klcs in neuronal patterning and compartimentalization and identify klc4 as a novel gene associated with anxiety behavior.

Reviewer #1 (Public Review):

In the manuscript "Airway Basal Cells Show Regionally Distinct Potential to Undergo Metaplastic Differentiation" by Yizhou, Yang et al., the authors take an unbiased approach to interrogate basal cell heterogeneity in the trachea. Their single-cell RNA-seq data suggests that several sub-populations of basal cells exist. Follow-up studies support the conclusion that two major basal cell populations exist corresponding to the dorsal and ventral trachea. Strikingly, their functional data also supports that the microenvironment of the dorsal or ventral trachea, being surrounded by smooth muscle or cartilage respectively, and that loss of cartilage leads to aberrant patterning of BC1 and BC2. Overall, this is an interesting study with reasonable conclusions that are supported by the data, and, the data is clear and of high quality. One point that requires further discussion pertains to the KRT13 expression following injury, and whether calling KRT13 activation "aberrant" is appropriate if it is simply a part of the natural repair process.

Reviewer #1 (Public Review):

The present manuscript offers valuable transcriptomic data sets of manually picked adult zebrafish photoreceptors from dissociated retinas of different transgenic lines, in which rods and cones (UV, S, L, M) were marked by the fluorescent reporter proteins. This is a very valuable approach because allows for selecting "healthy cells". Whether the approach is comparable to single-cell RNA-seq as the authors do (see page 3 and discussion) is however questionable as each of their samples is composed of 20 cells.

The authors further focused on transcription factors that are differentially expressed in the five photoreceptors cell types that they analyze, identifying a large number of them with still unidentified functions. This is very valuable information. However, the idea that this analysis will help to identify new TF involved in the specification of the photoreceptors (as stressed in the title) is at odds with the experimental setup. The authors have analyzed adult photoreceptors and thus by definition cells that had been already specified. Many of the TF involved in the specification may no longer be expressed. The analysis rather offers a list of TFs that are involved in photoreceptor homeostasis, some of which had been also involved in their specification. Proof of this is the fact that none of the four TFs of yet uncharacterized function (Skor1a, Sall1a, Lrrfip1a, and Xbp1) turned out to be involved in photoreceptor specification. The F0 screen only confirmed factors that were already known to be involved in cell specification and that in adult photoreceptors likely play a different role.

The authors further investigate the activity of the two tbx2 zebrafish paralogues in photoreceptors' specification, showing a novel role for tbx2 in the repression of different opsin in specific photoreceptor cell types. This is an interesting finding, however, it is overinterpreted by the authors. Indeed, tbx2 cannot be considered as a "master regulator of photoreceptor fate" (page 7) but, at best, a TF is required to control an appropriate proportion of the different photoreceptors' subtypes.

Overall this is an interesting and well-performed study with valuable information. The conceptual framework of the study should however be re-elaborated, further avoiding overinterpretations.

Reviewer #1 (Public Review):

Kim and coauthors have performed multiple simultaneous whole cell recordings in living slices of human neocortex obtained from neurosurgical resection in order to study the properties of synaptic connections from excitatory pyramidal neurons onto various types of inhibitory interneurons. Strengths of the study include the unique ability to study biophysical properties of human synapses, and the sophisticated in situ hybridization and other approaches used to identify the class of the postsynaptic interneurons. The main finding of the study is that a key principle identified in rodent neocortex: that fast-spiking parvalbumin-positive neurons receive initially depressing synapses, whereas other categories of interneurons receive more initially facilitating synapses, is conserved in the human. The authors also make important technical contributions to our ability to study synapses in human tissue including a slice culture technique that prolongs the use of these valuable samples, and a multi-pronged approach to characterizing interneuron identity. The main weaknesses of the current version of the manuscript relate to incomplete analyses and a somewhat confusing presentation that leave in question the relative importance of interneuron identity vs. other factors in determining the degree of synaptic facilitation and depression.

Reviewer #1 (Public Review):

Ugrankar et al provide an interesting article exploring the impact of the actin network in adipocyte cell size and nutrient uptake. The manuscript is well written and presents gaps in current knowledge well. The authors use Drosophila to address their research questions, describing a specific isoform of actin, Actin 5C, as the critical mediator of lipid metabolism in the larval fat body. In support, they show that loss of a mediator of actin dynamics, twinfilin, can have similar impacts as actin 5C loss. The authors further probe for impacts of additional cytoskeletal proteins, spectrins, in this process, concluding that spectrin activity differs from Actin 5C. Last, the authors attempt to explore how actin network in the fat body impacts nutrient uptake in multiple ways. Overall, this is an interesting study that sheds light on adipocyte cytoskeletal dynamics. However, there are a number of concerns, including: a need to validate the many RNAi used, the need to add data to rule out a potential contribution from other actin isoforms, further characterization of the assays used to address nutrient uptake, and further validation of the data used to argue that actin 5C is not essential during embryogenesis.

Reviewer #1 (Public Review):

This study has some neat technological features that go a long way to reconcile contradictory data regarding functions of disease associated PTPN22 variants. These include:<br /> • Crispr/Cas9 gene editing of exon 14 of PTPN22 in primary human T cells to generate HDR for WT, and gene editing for risk and KO sequences<br /> • Use of cord blood T cells, mitigating against any variability in T cell responses that could be influenced by activation or differentiation state<br /> • Lentiviral infection of these T cells with high and low avidity TCRs that recognise the same peptide from the islet cell autoantigen IGRP, presented by HLA-DRB1*0401; the TCRs are chimeric, allowing detection of LV transgene and detection of TCRs that have not cross-paired with endogenous TCR chains<br /> • Cis-linked GFP to detect those T cells expressing TCR transgenes. Infection is undertaken using titres of virus likely to avoid high copy number TCRs and therefore variable TCR expression<br /> • Repeat experiments using multiple donors<br /> • TCR stimulations using a range of different readouts

The main findings and things to look out for are:<br /> • The HDR editing process leads to reduced expression of PTPN22 when compared to unedited/mock edited wild type T cells; thresholds of signalling are therefore different. But this is ok because expression of phosphatase in edited wild type and risk variants is equivalent, albeit at lower levels (Fig 1).<br /> • The technology inevitably leads to hemizygosity with biallelic editing events, and this needs to be born in mind when considering the homogeneity of T cell populations<br /> • The impact of the PTPN22 risk variant or phosphatase deficiency is uncovered under conditions of lower avidity/low signal strength, where loss of negative regulation leads to increased proliferation and cytokine production (IFN or IL-2)<br /> • Consistent with this PTPN22 regulates responses of T cells expressing low avidity L-TCR, but not high avidity H-TCR<br /> • Thus, the risk variant mimics the knockout, to a large extent

Additional things/experiments that might strengthen the study:<br /> • The claims of the authors might be further substantiated if they extended the range of T cell stimulatory readouts eg different cell surface markers such PD-1, OX-40, 41BB, ICOS, GPR56, whose expression is linked to TCR signalling thresholds<br /> • Additional signalling experiments such as phospho-flow using phospho-Erk specific antibodies would be a bonus; I worry a bit about only showing pS6 data<br /> • Repeat the experiments comparing wild type and ko T cells and study cytokine expression eg IFNg in non-risk edited and risk edited T cells. As it stands the only data we see comparing these genotypes is proliferation.

Reviewer #1 (Public Review):

The authors aimed at explaining the origin of the persistent activity observed in neural populations recorded from larval zebrafish, its dependence on the temperature of the water the fish was immersed in, and the effects of visual stimulation. They deploy a popular data-driven model to capture the statistical structure of large neural populations, fitting a maximum entropy model (Ising model) to the average activity and pairwise correlation of recorded neurons. Using mean field methods, they reduce this high-dimensional model to two dimensions, describing the average activities of populations in the left and right hemispheres. Both the high and low dimensional models are capable of generating the long timescale of persistent activity, even though they were only trained to learn the static mean and pairwise correlation structure. The crucial theoretical insight is that this long timescale emerges from the energy landscape of the reduced model in terms of stochastic transitions between metastable attractors following the well known Arrhenius law. The height of the barriers separating the attractors is modulated by water temperature, explaining the change in transition times and persistent activity. The model can also explain the dependence of persistent activity on the water temperature.

The major strength of the present work is that, by using a simple and well motivated statistical model (maximum entropy model) based on minimal assumptions, the authors are able to quantitatively reproduce complex spatiotemporal effects of fish behavior. The authors explain why this is the case due to the emergence of metastable dynamics based on stochastic transitions between local minima of the free energy. This classic model is very easily interpretable and of wide appeal for the neuroscience and larger life science community.

In my opinion, the current manuscript has three main weaknesses. The first one is that the model fit and its comparison to the data is not cross-validated and thus likely affected by overfitting. I strongly recommend recasting all results in terms of comparison of cross-validated observables. The second weakness is the fact that it is not explained how the water temperature appears in the model, which is the central quantity whose dependence they aim to model. There is a significant confusion on issues of water temperature vs. temperature in the model Gibbs measure. The author should make sure this point gets clarified. The third weakness is that, although the authors claim that the sign of the difference between the mean population activities of left and right hemispheres is the observables that determines whether the fish is going to change swimming directions, they don't actually provide direct evidence for this, but only compare the statistical distribution of this observable with the behavioral distribution. I recommend the authors explicitly test the predictive nature of the neural observable by showing that changes in swim directions are temporally aligned to the onset of a sign change.

If the results still stand after applying cross-validation, which I believe is a quite likely outcome, I believe this manuscript will have a strong impact in the field since they demonstrated the power of a principled and well-known approach in capturing complex spatiotemporal activity of large neural populations. This work has the potential to be widely adopted and generalized to many different directions in systems neuroscience and beyond.

Reviewer #1 (Public Review):

Carlos Serpa et al., build on prior work from their laboratory showing that the rat ventrolateral orbitofrontal cortex (OFC) is not involved in goal-directed action control per se, but is involved in the updating of such actions. Here they demonstrated that noradrenergic but not dopaminergic inputs within the OFC (and not the medial PFC) are necessary for action-updating in this manner. The conclusions are well supported by the data. Overall this is an excellent manuscript with many strengths and few weaknesses.

Strengths are as follows:<br /> 1. The manuscript is written beautifully<br /> 2. The rationale for the study is clear.<br /> 3. The data are mostly very solid. All the claims are statistically supported, not only by pairwise comparison statistics but also interactions. This is very important in ensuring robustness and replicability of effects.

Weaknesses<br /> 1. There are no major weaknesses. As a minor point, a clearer demonstration of precise anatomical placements would be helpful as the function of the OFC (and the medial PFC) can differ significantly with even small alterations in placement.

I think these data will be of interest to neuroscientists and possibly psychopharmacologists. It may also be of interest to researchers in other fields, such as clinicians, although it doesn't have extremely clear health implications, so clinician interest could be limited.

Reviewer #1 (Public Review):

The manuscript describes changes in single cell RNA sequencing signatures of dorsal root ganglion neurons over the development of neuropathic pain in the murine chronic constriction injury (CCI) model. Bioinformatic algorithms were employed to cluster neurons into sub-classes described previously, based on transcriptomic signatures. The authors report emergence of 4 new clusters, resulting from loss of cellular identity of neurons in known clusters and induction of inflammatory and hyperexcitability-associated genes. Moreover, they segregated neurons between injured and uninjured subclasses and observed induction of genes in both categories as well as differences between these categories. Some injured neurons maintained cellular identity. conversely, non-injured neurons were also found to show significant transcriptional plasticity in clusters with a prominent role in pain sensitivity. Sexual dimorphism was noted, particularly with respect to the c-LTMR class of sensory neurons.

The results of the current study are interesting, and the study is very well-performed. The fact that fluorescently labelled DRG neurons were employed here is an advantage since it led to lower representation of non-neuronal genes and better representation of neuronal genes expressed at low levels. However, it is largely descriptive and the level of advance beyond recent single cell transcriptomics studies on DRG neurons as well as older studies on bulk sequencing in models of neuropathic pain is debatable.

Reviewer #1 (Public Review):

This study analyzes the R-ISS-related plasma cell (PC) heterogeneity by 10X Genomics ScRNA sequencing and identified the two subsets of PCs(GZMA+ cytotoxic PCs and proliferating PCs). Three R-ISS-dependent gene modules in cytotoxic CD8+ T and NKT cells were also functionally analyzed. Potential immuno cell-cell communication such as SIRPA-CD47 and TIGIT-NECTIN3 were explored for the potential immunotargets which is an important direction for treating R/R MM. The work holds a promising way to study the drug resistance of R/R myeloma. However, the cost and complexity of the experimental method make it difficult to be widely used.

Reviewer #1 (Public Review):

SRSF6 is an understudied SR family member, best characterized for its role in controlling alternative splicing. Through comparative RNA-Seq analysis, the authors find that knockdown of SRSF6 results in a markedly different gene expression program than other SR proteins tested in that SRSF6 depletion leads to a dramatic increase in expression of interferon responsive genes (ISGs) and a downregulation of mitochondrial related genes. Given this correlation the authors explore the possibility that loss of SRSF6 leads to mitochondrial damage, which releases dsDNA to trigger the innate immune response through the DNA-sensor cGAS. They further propose that mitochondrial damage is due to a change in splicing of the gene BAX. The data shown in the manuscript are consistent with these conclusions, however do not rule out additional mechanisms. In particular, the mitochondrial and BAX phenotypes are much less dramatic than the interferon response. Moreover, the authors do not show that the change in BAX splicing induced by loss of SRSF6 is sufficient to lead to a change in ISG expression.

Reviewer #1 (Public Review):

This is an interesting study, addressing a timely question of the crosstalk between cancer, immune, and stromal cell populations in the tumor microenvironment, and the effect of therapy on the tumor microenvironment. The authors were aiming to show that the ratio between neutrophils and lymphocytes could predict treatment responses in pancreatic cancer. They indeed show that there is an association between the Neutrophil to lymphocyte ratio (NLR) and treatment outcome, suggesting that this could be a predictive marker. They go on to use a mouse model to perturb the NLR and combine this with treatment similar to that used in the clinic and find that targeting neutrophils affects tumor growth, suggesting a costive and not the only correlative role. Finally, they show that this could be mediated through the stromal compartment since this treatment affects the ratio of inflammatory to myofibroblastic CAFs.

The main strength of the paper is in tying together neutrophils, lymphocytes, and CAFs and showing how these populations affect each other. The correlations in human patients are promising and the regulation of CAF transitions is interesting.

While the correlation between NLR and survival is convincing and strong, the relevance of CAF transitions to this effect in human patients is weak, and shown only in mice and not in humans. Also in the mouse, the evidence for CAF transitions should be strengthened to support the authors' full conclusions.

Reviewer #1 (Public Review):

The manuscript by Lian et al. presents a population graph deep learning model constructed using Transformer-generated imaging features and non-imaging clinical characteristics that were proven to be effective at predicting the survival of patients with early-stage NSCLC. This study demonstrates GNN-based model significantly outperforms the TNM model and ResNet-Graph model in predicting survival in all datasets. The paper is well-written, clear for a general audience, takes nice innovations in computer vision into the medical field, and presents a usable tool for survival analysis. The strengths and limitations of the approach are brought forth in the discussion.

Reviewer #1 (Public Review):

This publication shows a strong understanding and implementation of large-scale multiprotein MD simulations. It is the first application of MD simulations to full-length membrane-bound TSHR. The authors showed that the LR is intrinsically disordered, contrasting a previously published homology model. Some simulation results are supported by cryo-EM structures. Finally, it is significant that the inclusion of TSH in the binding site altered the dynamics of the LR region, supporting a hypothesis that the LR is involved in a signaling mechanism, though the authors acknowledge this result as preliminary.

Weaknesses:<br /> The methods section lacks sufficient detail, and arbitrary choices made in the simulation setup may have biased the results. The author's finding that the LR is disordered does not provide obvious mechanistic insights, and the simulations with the bound ligand are too preliminary to make solid conclusions. Although this manuscript is technically strong, the significance of the results is often unclear.

Reviewer #1 (Public Review):

Wang et al., developed a CRISPR/Cas 9 based protocol with the aim to accurately and quickly detect bacteria in ICU patients with severe pneumonia.

The development of such a tool is important as quick and reliable identification of pathogens is extremely important. This study is innovative and aims to address an important clinical problem. The authors de novo designed an algorithm to screen species-specific . Then they used the species specific DNA tags to identify 10 pathogens.

1) It is not very clear on which epidemiological data these pathogens were selected on. Moreover, the selected pathogens are only bacteria.

2) Page 9. It is not very clear on how the primers' specificity was evaluated.

3) Page 9. Were patients on antibiotics before getting into the trial?

4) Page 10 At which timepoint the patients received different treatment based on the results of the culture or SSBD? Was this consistent?

5) Page 11. The second sentence of 3.1 section in results is not clear.

6) How were patients allocated to groups? Randomised?

7) The table describing the patient cohort is in supplementary. This shall be in the main manuscript. It seems that the control and experimental groups were not balanced.

8. The exact protocol of the study needs to be in the supplementary.

9. Were any samples poly-microbial?

10. Which was the threshold level of fluorescence (Figure 3) which was considered important?

Reviewer #1 (Public Review):

In this paper, Gao et al report that Kiaa1024L/Minar2 causes hearing loss in mice and in zebrafish. The animal studies are well executed. Mechanistically, the authors claim that Kiaa1024L/Minar2 is responsible for the enrichment of an accessible pool of cholesterol in the hair bundle membrane. Increasing cholesterol levels rescues hair cell defects whereas decreasing cholesterol aggravates the problem.

Unfortunately, the mechanistic arm of this study doesn't go beyond this correlation. The characterization of cholesterol levels and pools is not rigorous and it is unclear why cholesterol matters for hearing.

Reviewer #1 (Public Review):

The authors examined the impact of pre-gravid obesity in human mothers on the monocytes of newborns by collecting umbilical cord blood. Additionally, the authors also used a non-human primate (NHP) model of diet-induced obesity to isolate fetal macrophage and assess the impact of maternal obesity on fetal macrophage function.

The comprehensive analysis of the human umbilical cord blood monocytes by studying cytokine release, bulk RNA-seq and bulk ATAC-seq, single cell RNA-seq and single cell ATAC-seq, responses to pathogen stimulation as well as metabolic studies such as glucose uptake are major strength of the work. They present convincing evidence that the monocytes of offspring with obese mothers have epigenetic and transcriptomic profiles consistent with impaired immune responses, both during baseline conditions and upon stimulation.

However, it is not clear from the data how the epigenetic data and the transcriptomic data are related to each other. The implication that the epigenetic changes drive the downstream transcriptional differences is not clearly demonstrated. Furthermore, it is not clear which of the observed attenuations of monocyte transcriptional responses overlap with chromatin accessibility differences. Such an overlap would make a stronger case for the mechanistic link.

The increased phagocytosis of E.coli in umbilical cord monocytes of newborns with obese mothers appear counter-intuitive because it implies greater host defense capacity.

One of the most remarkable aspects of the manuscript is the analysis of the fetal macrophages in a non-human primate (NHP) model of diet induced obesity because of the challenge of studying fetal macrophages in humans. The cytokine assays nicely show that the fetal macrophages in the obesity model show impaired cytokine production, consistent with what was seen in the umbilical cord blood monocytes of human newborns. This is especially important because circulating monocytes or monocyte progenitors seed the fetal tissues and give rise to fetal macrophages, thus elegantly linking the human work on circulating umbilical cord blood monocytes to the tissue macrophages in the NHP model.

However, the NHP studies do not show any additional macrophage characterization beyond the cytokine assays. Flow cytometry analysis of the macrophage phenotype and functional assays would strengthen the conclusions regarding macrophage dysregulation.

Reviewer #1 (Public Review):

The authors endeavored to determine molecular pathways that could enhance the viability and function of MSCs. The authors identified the master anti-oxidant regulator NRF2 as a direct regulator of DKK1, a Wnt pathway inhibitor. Moreover, the authors demonstrate over expression of NRF2 and DKK1 ameliorates liver regeneration in a model of acute on chronic liver failure. The strengths of this study are their multi-tier approach utilizing molecular biology, genetic interventions and in vitro and vivo models. These findings have uncovered a novel signaling loop with the potential for enhancing MSC function in vivo.

Reviewer #1 (Public Review):

Bacterial carboxysomes are compartments that enable the efficient fixation of carbon dioxide in certain types of bacteria. A focus of the current work is on two protein components that provide spatial regulation over carboxysomes. The McdA system is an ATPase that drives the positioning of carboxysomes. The McdB system is essential for maintaining carboxysome homeostasis, although how this role is achieved is unclear. Previous studies, by the lead author's lab, showed that the McdB system is a driver of phase separation in vitro and in cells. They proposed a putative connection between McdB phase separation and carboxysome homeostasis. The central premise of the current work is as follows: In order to understand if and how phase separation of McdB impacts carboxysome homeostasis, it is important to know how the driving forces for phase separation are encoded in the sequence and architecture of McdB. This is the central focus of the current work. The picture that emerges is of a protein that forms hexamers, which appears to be a trimer of dimers. The domains that drive that the dimerziation and trimerization appear to be essential for driving phase separation under the conditions interrogated by the authors. The N-terminal disordered region regulates the driving forces for phase separation - referred to as the solubility of McdB by the authors. To converge upon the molecular dissections, the authors use a combination of computational and biophysical methods. The work highlights the connection between oligomerization via specific interactions and emergent phase behavior that presumably derives from the concentration (and solution condition) dependent networking transitions of oligomerized McdB molecules.

Having failed to obtain specific structural resolution for the full-length McdB as a monomer or oligomer, the authors leverage a combination of computational tools, the primary one being iTASSER. This, in conjunction with disorder predictors, is used to identify / predict the domain structure of McdB. The domain structure predictions are tested using a limited proteolysis approach and, for the most part, the predictions stand up to scrutiny affirming the PONDR predictions. SEC-MALS data are used to pin down the oligomerization states of McdB and the consensus that emerges, through the investigations that are targeted toward a series of deletion constructs, is the picture summarized above.

Is the characterization of the oligomerization landscape complete and likely perfect? Quite possibly, the answer is no. Deletion constructs pose numerous challenges because they delete interactions and inevitably impose a modularity to the interpretation of the totality of the data. Accordingly, we are led to believe that the N-terminal IDR plays no role whatsoever in the oligomerization. Close scrutiny, driven by the puzzling choice of nomenclature and the Lys to Gln titrations in the N-terminal IDR raise certain unresolved issues. First, the central dimerization domain is referred to as being Q-rich. This does not square with the compositional biases of this region. If anything is Q/L or just L-rich. This in fact makes more sense because the region does have the architecture of canonical Leu-zippers, which do often feature Gln residues. However, there is nothing about the sequence features that mandates the designation of being Q-rich nor are there any meaningful connections to proteins with Q-rich or polyQ tracts. This aspect of the analysis and discussion is a serious and erroneous distraction. Back to the middle region that drives dimerization, the missing piece of the puzzle is the orientation of the dimers. One presumes these are canonical, antiparallel dimers. However, this issue is not addressed even though it is directly relevant to the topic of how the trimer of dimers is assembled. If the trimer is such that all binding sites are fully satisfied (with the binding sites presumably being on the C-terminal pseudo-IDR), then the hexamer should be a network terminating structure, which it does not seem to be based on the data. Instead, we find that only the full-length protein can undergo phase separation (albeit at rather high concentrations) in the absence of crowder. We also find that the driving forces for phase separation are pH dependent, with pH values above 8.5 being sufficient to dissolve condensates. Substitution of Lys to Gln in the N-terminal IDR leads to a graded weakening of the driving forces for phase separation. The totality of these data suggest a more complex interplay of the regions than is being advocated by the authors. Almost certainly, there are complementary electrostatic interactions among the N-terminal IDR and C-terminal pseudo IDR that are important and responsible for the networking transition that drives phase separation, even if these interactions do not contribute to hexamer formation. The net charge per residue of the 18-residue N-terminal IDR is +0.22 and the NCPR of the remainder is ≈ -0.1. To understand how the N-terminal IDR is essential, in the context of the full-length protein, to enable phase separation (in the absence of crowder), it is imperative that a model be constructed for the topology of the hexamer. It is also likely that the oligomer does not have a fixed stoichiometry.

Therefore, the central weakness of the current work is that it is too preliminary. A set of interesting findings are emerging but by fixating on Lys to Gln titrations within the N-terminal IDR and referring to these titrations as impacting solubility, a premature modular and confused picture emerges from the narrative that leaves too many questions unanswered.

The work itself is very important given the growing interest in bacterial condensates. However, given that the focus is on understanding the molecular interactions that govern McdB phase behavior - a necessary pre-requisite in the authors minds for understanding if and how phase separation impacts carboxysome homeostasis - it becomes imperative that the model that emerges be reasonably robust and complete. At this juncture, the model raises far too many questions. The MoRF analysis is distraction away from the central focus.

The problem, as I see it, is that the authors have gone down the wrong road in terms of how they have interpreted the preliminary set of results. Further, the methods used do not have the resolution to answer all the questions that need to be answered. Another issue is that a lot of standard tropes are erected and they become a distraction. For example, it is simply not true that in a protein featuring folded domains and IDRs it almost always is the case that the IDR is the driver of phase transitions. This depends on the context, the sequence details of the IDRs, and whether the interactions that contribute to the driving forces for phase separation are localized within the IDR or distributed throughout the sequence. In McdB it appears to be the latter, and much of the nuance is lost through the use of specific types of deletion constructs.

Overall, the work represents a good beginning but the data do not permit a clear denouement that allows one to connect the molecular and mesoscales to fully describe McdB phase behavior. Significantly more work needs to be done for such a picture to emerge.