Reviewer #2 (Public Review):

Mikula et al. have a large experience studying the escape distances of birds as a proxy of behavioral adaptation to urban environments. They profited from the exceptional conditions of social distance and reduced mobility during the covid-19 pandemic to continue sampling urban populations of birds under exceptional circumstances of low human disturbance. Their aim was to compare these new data with data from previous "normal" years and check whether bird behavior shifted or not as a consequence of people's lockdown. Therefore, this study would add to the growing body of literature assessing the effect of the covid-19 shutdown on animals. In this sense, this is not a novel study. However, the authors provide an interesting conclusion: birds have not changed their behavior during the pandemic shutdown. This lack of effects disagrees with most of the previously published studies on the topic. I think that the authors cannot claim that urban birds were unaffected by the covid-19 shutdown. I think that the authors should claim that they did not find evidence of covid-19-shutdown effects. This point of view is based on some concerns about data collection and analyses, as well as on evolutionary and ecological rationale used by the authors both in their hypotheses and results interpretation. I will explain my criticisms point by point:

1) The authors used ambivalent, sometimes contradictory, reasoning in their predictions and results interpretation. Some examples:<br /> 1.1) The authors claimed that urban birds perceive humans as harmless (L224), but birds actually escape from us, when we approach them... Furthermore, they escape usually 5 to 20 m away. This is more distance that would be necessary just to be not trampled.<br /> 1.2) If we are harmless, why birds should spend time monitoring us as a potential threat (L102)? Indeed, I disagree with the second prediction of the authors. I could argue that reduced human activity should increase animal vigilance because real bird predators (e.g., raptors) may increase their occurrence or activity in empty cities. If birds should increase their vigilance because the invisible shield of human fear of their predators is no longer available, then I would expect longer escape distances.<br /> 1.3) To justify the same escape behavior shown by birds in pre- and pandemic conditions from an adaptive point of view, the authors argued a lack of plasticity and a strong genetic determination of such behavior. This contravenes the plasticity proposed in the previous point or the expected effect of the stringency index (L112). In my opinion, some degree of plasticity in the escape behavior would be really favorable for individuals from an adaptive perspective, as they may face quite different fear landscapes during their lives. Looking at the figures, one can see notable differences in the escape distance of the same species between sites in the same city. As I can hardly imagine great genetic differences between birds sampled in a park or a cemetery in Rovaniemi, for instance, I would expect a major role of plasticity to explain the observed variability. Furthermore, if escape behavior would not be plastic, I would not expect date or hour effects. By including them in their models, the authors are accepting implicitly some degree of plasticity.

2) Looking at the figures I do not see the immense stochasticity (L156, Fig. S3, S5) claimed by the authors. Instead, I can see that some species showed an obvious behavioral change during the shutdown. For instance, Motacilla alba, Larus ridibundus, or Passer domesticus clearly reduced their escape distances, while others like the Dendrocopos major, Passer montanus, or Turdus merula tended to increase it. On the other hand, birds in Poland tended to have larger escape distances during the shutdown for most species, while in Rovaniemi there was an apparent reduction of escape distances in most cases. The multispecies and multisite approach is a strength of this study, but it is an Achilles' heel at the same time. The huge heterogeneity in bird responses among species and sites counterbalanced and as a result, there was an apparent lack of shutdown effects overall. Furthermore, as most data comes from a few (European) species (i.e., Columba, Passer, Parus, Pica, Turdus, Motacilla) I would say that the overall results are heavily influenced (or biased) by them. The authors realize that results are often area- or species-specific (L203), therefore, does a whole approach make sense?

3) The previous point is worsened by the heterogeneity of cities and periods sampled. For instance:<br /> 3.1) I can hardly imagine any common feature between a small city in northern Finland (Rovaniemi) and a megacity in Australia (Melbourne). Thus, I would not be surprised to find different results between them.<br /> 3.2) Prague baseline data was for 2014 and 2018, while for the rest of the study sites were for 2018 and 2019. If study sites used a different starting point, you cannot compare differences at the final point.<br /> 3.3) Due to the obvious seasonal differences between the northern and southern hemispheres, data collection in Australia began five months later than in the rest of the sites (Aug vs Mar 2020). There, urban birds faced already too many months of reduced human disturbances, while European birds were sampled just at the beginning of the lockdown.<br /> 3.4) Some cities were sampled by a single observer, while others by many of them. Even if all of them are skilled birders, they represent different observers from a statistical point of view and consequently, observer identity was an extra source of noise in your data that you did not account for.

4) Although I liked the stringency index as a variable, I am not sure if it captured effectively the actual human activity every day. Even if restrictive measures were similar between countries, their actual accomplishment greatly depended on people's commitment and authorities' control and sanctions. I would suggest using a more realistic measure of human activity, such as google mobility reports.

5) The authors used escape trials from birds on the ground and perched birds. I think that they are not comparable, as birds on the ground probably perceive a greater risk than those placed some meters above the ground, i.e. I would expect shorter escape distances for perched birds. As this can be strongly dependent on the species preferences or sampling site (i.e, more or less available perches), I wonder how this mixture of observations from birds on the ground and perched birds could be affecting the results.

6) The authors did not sample the same location in the same breeding season to avoid repeated sampling of the same individuals (L331). This precaution may help, but it does not guarantee a lack of pseudoreplication. Birds are highly mobile organisms and the same individuals may be found in different places in the same city. This pseudoreplication seems particularly plausible for Rovaniemi, where sampling points must be necessarily close due to the modest size of this city.

7) An intriguing result was that the authors collected data for 135 species during the shutdown, while they collected data only for 68 species before the pandemic. Such a two-fold increase in bird richness would not be expected with a 36% increase in sampling effort during 2020-21. I wonder if this could be reflecting an actual increase in bird richness in urban areas as a positive result of the shutdown and reduced human presence.

8) The authors dismissed the multicollinearity problem of explanatory variables unjustifiably (L383). However, looking at fig. S1, I can see strong correlations between some of them. For instance, period and stringency index were virtually identical (r=0.95), while temperature and date were also strongly correlated.

9) The random structure of the models is a key element of the statistical analyses but those random factors are poorly explained and justified. I needed to look up the supplementary tables to fully understand the complex architecture of the random part of the models. To the best of my knowledge, random variables aim to account for undesirable correlations in the covariance matrix, which is expected in hierarchical designs, such as the present one. However, the theoretical violation of data independence may happen or not. As the random structure is usually of little interest, you should keep it as simple as necessary, otherwise random factors may be catching part of data variability that you would like to explain by fixed variables. I think that this is what is happening (at least, in part) here, as the authors included a too-complex random structure. For instance, if you include the year as a random factor, I think that you are leaving little room for the period effect. The authors simplified the random structure of the models (L387), but they did not explain how. Nevertheless, this model selection was not important at all, as the authors showed the results for several models. I assume, consequently, that the authors are considering all these models equally valid. This approach seems quite contradictory.

Reviewer #2 (Public Review):

Fuks et al. provide extensive paleobotanical data from several sites in the Negev desert to address hypotheses regarding the relative importance of the Roman Agricultural Diffusion (RAD) and the Islamic Green Revolution (IGR) in the dispersal of crops across Eurasia.

While the overall claims from the authors are convincing, I found the presentation of the data somewhat difficult to follow.<br /> Graphical visualization of the data with respect to the proposed hypotheses would go a long way towards making the argument clearer for a non-specialist audience.

The authors apply appropriate caveats in the discussion about their ability to assess IGR given their timeline only incorporates the first few hundred years and some IGR plants may not leave macrobotanical remains. Yet I think more could be done to explain how the data they do find provides positive evidence for RAD. Many of their findings are inferred to be RAD introductions not because of the timing in their sites, but because of previous evidence of introductions at other sites. It would thus be helpful to be more explicit about what additional evidence these findings provide beyond previously published data of introductions of many of these crops into the Levant.

Reviewer #2 (Public Review):

Antiretroviral therapy (ART) can control HIV replication and improve the quality of life for people living with HIV (PLWH); however, it does not cure infection, nor does it revert T cell exhaustion. Inhibitory receptor expression is a characteristic of CD8+ T cell exhaustion and a better understanding of the differences in receptor expression dynamics between healthy donors and PLWH on ART is of interest. In this comparative study, Blanch-Lombarte et al. use single-cell analysis of flow cytometric PBMC profiling to examine inhibitory receptor expression (IR) and functional markers in CD8+ T cells derived from PLWH on ART and healthy donors.

The authors first perform a mix of cross-sectional and longitudinal characterization of IR expression and memory differentiation markers in donors who are healthy controls, are in the early stages of HIV infection, PLWH on ART for ~ 2 years, and PLWH on ART for ~10 years. They conduct both supervised and unsupervised analyses of the phenotypic results. The authors use three experimental conditions (unstimulated, SEB stimulation, HIV Gag peptide pool stimulation) to perform cluster analyses. The longitudinal paired samples allow determination of the persistence of the alterations observed early after initiation of ART. The analyses show inverse correlations between frequencies of TIGIT+ and TIGIT+ TIM+ CD8 subsets and CD4 counts. However, findings for HIV-specific CD8 were different, with a selective reduction of TIGIT+ clusters whose functionality in terms of CD107 expression was recovered by anti-TIGIT blockade.

The authors conclude that TIGIT could be a therapeutic target to revive exhausted T cells (Tex) at all ART stages.

Strengths:<br /> - The study addressed relevant questions for the field.<br /> - The is a logical sequence of experiments and analyses.<br /> - The authors investigate interesting samples - longitudinal time points on ART several years apart are a significant asset.<br /> - Assessment of CD8 T cell populations as bulk unstimulated cells, broad stimulation with a superantigen (SEB), and HIV-specific responses (Gag peptide pool stimulation).<br /> - Complementary use of supervised and detailed unsupervised analyses of flow cytometry data.<br /> - The analyses are overall detailed and carefully presented, except for minor issues in color coding and font size.<br /> - Functional assays to assess the functional impact of TIGIT upregulation on CD8 T cell function.<br /> -<br /> Weaknesses:<br /> - While the paper reads overall well, the hypotheses and concepts should be clarified in several instances. For example, the authors speak of T cell exhaustion, which in principle is understood as antigen-specific T dysfunction associated with antigen persistence. However, a good part of the paper is focused on total CD8 T cells, and the links between findings in the different populations of CD8 examined (total, SEB-stimulated, Gag-stimulated) are hard to understand.<br /> - Upregulation of IRs can be associated with the state of T cell differentiation and also modulated by chronic inflammation independently of TCR signaling (eg, common gamma-chain cytokines upregulate PD-1), so defining these cells as univocally Tex is not correct.<br /> - The study mostly focuses on descriptive phenotypic analyses of CD8 T cells rather than dynamics studies which would imply more in-depth investigations of T cell evolution and fate.<br /> - HIV-specific CD8 T cells can be both quantitatively and quantitatively impaired, but the quantitative aspects are not considered, nor shifts in phenotype. For example, HIV-specific TIGIT+ CD8 responding to blockade proportionally over time - It is unclear if this is compensated by other subsets.<br /> - The functional assays with TIGIT blockade are limited and do not include other markers of cytotoxic cells (perforin, granzyme B expression...). It is not clear how do these subsets compare to the other clusters in terms of CD107 expression.<br /> - The statistical analyses do apparently not include correction for multiple comparisons.

Reviewer #2 (Public Review):

Summary:<br /> In the paper from Hartman, Vandenberg, and Hill entitled "assessing drug safety, by identifying the access of arrhythmia and cardio, myocytes, electro physiology", the authors, define a new metric, the axis of arrhythmia" that essentially describes the parameter space of ion channel conductance combinations, where early after depolarization can be observed.

Strengths:<br /> There is an elegance to the way the authors have communicated the scoring system. The method is potentially useful because of its simplicity, accessibility, and ease of use. I do think it adds to the field for this reason - a number of existing methods are overly complex and unwieldy and not necessarily better than the simple parameter regime scan presented here.

Weaknesses:<br /> The method described in the manuscript suffers from a number of weaknesses that plague current screening methods. Included in these are the data quality and selection used to inform the drug-blocking profile. It's well known that drug measurements vary widely, depending on the measurement conditions.

There doesn't seem to be any consideration of pacing frequency, which is an important consideration for arrhythmia triggers, resulting from repolarization abnormalities, but also depolarization abnormalities. Extremely high doses of drugs are used to assess the population risk. But does the method yield important information when realistic drug concentrations are used? In the discussion, the comparison to conventional approaches suggests that the presented method isn't necessarily better than conventional methods.

In conclusion, I have struggled to grasp the exceptional novelty of the new metric as presented, especially when considering that the badly needed future state must include a component of precision medicine.

Reviewer #2 (Public Review):

Anderson et al profiled chromatin features, including active chromatin marks, RNA polymerase II distribution, and histone modifications in the sex chromosomes of spermatogenic cells in Drosophila. The results are new and the experiments and analyses look well done, including with appropriate numbers of replicates. Results were parsed by comparing them among two arrest mutants and wildtype, as well as in FACS-sorted spermatocytes. The authors also profiled larval wing discs to serve as reference-somatic cells, which allowed them to focus only on features in their testis data that were associated with germ cells. Their results were further refined by categorizing the genes of interest based on available single nucleus RNA seq expression profiles. The authors document interesting phenomena, such as differences in the distribution of RNAPIIS2p on some genes in germ cells vs somatic cells, the presence of a uH2A body beginning in early spermatocytes, and high levels of uH2A on the Y chromosome and little or none on the X. The former is intriguing because this modification is usually associated with silencing, yet the Y chromosome is active in spermatogenic cells. The authors interpret some of their data as implying a lack of dosage compensation of the X chromosome in spermatocytes.

The data are believable and new, but it is not fully clear how to interpret them. The paper's interpretations rely on subtractive logic to parse results from mixtures of cells down to cell type, extracting spermatogonia, spermatocyte, etc. features by comparing bam mutants (only spermatogonia) to aly mutants (spermatogonia and early spermatocytes but no later stages) to wildtype (all spermatogenic stages), and extracting testis germline data by comparison to wing disc soma; their FACS sorted spermatocytes also have heterogeneity. I recognize that the present paper was a lot of work and am not suggesting that the authors redo their study using methods that give more purity and precision of stage (https://doi.org/10.1126/science.aal3096, https://doi.org/10.1101/gad.335331.119), but they should be aware of them and of their results.

The conclusions about dosage compensation are indirect, but are consistent with the current model documented in the studies cited by the authors, as well as earlier studies (doi: 10.1186/jbiol30).

Reviewer #2 (Public Review):

In this manuscript, the authors generate an annotated brain atlas for the prairie vole, which is a widely studied organism. This species has a suite of social behaviors that are difficult or impossible to study in conventional rodents, and has attracted a large community of researchers. The atlas is impressive and will be a fantastic resource. The authors use this atlas to examine brain-wide c-fos expression in prairie voles that were paired with same-sex or opposite-sex voles across multiple time points. In some sense, the design resembles PET studies done in primates that take whole brain scans after an important behavioral experience. The authors observed increased c-fos expression across a network of brain regions that largely corresponds with the previous literature. The study design captured several novel observations including that c-fos expression in some regions correlates strongly between males and females during pair bond formation and mating, suggesting synchrony in neural activity. An important caveat to this study not mentioned by the authors is that c-fos provides a snapshot of neural activity and that important populations of neurons could be active and not express c-fos. Thus observed correlations are likely to be robust, but the absence of differences (in say accumbens) may just reflect the limits of c-fos estimation of neural activity. Similarly, highly coordinated neural activity between males and females might still be driven by different mechanisms if different cell types were activated within a specific region. Nonetheless, the creation of this resource and its use in a well-designed study is an important accomplishment.

Reviewer #2 (Public Review):

The manuscript by Maio et al attempts to examine the bioenergetic mechanisms involved in the delayed migration of DC's during Mtb infection. The authors performed a series of in vitro infection experiments including bioenergetic experiments using the Agilent Seahorse XF, and glucose uptake and lactate production experiments. This is a well-written manuscript and addresses an important question in the TB field. A major weakness is the use of dead Mtb in virtually all the experiments. Unfortunately, the authors did not attempt to address this critical confounding factor. As a result, data was interpreted, and conclusions were made as if live Mtb was used. Also, previous studies (PMID: 30444490 and PMID: 31914380) have shown that live Mtb suppresses glycolysis, which contradicts findings in this study, perhaps because dead Mtb was used here. For these reasons, obtaining any pertinent conclusions from the study is not possible, which diminishes the significance of the work.

Reviewer #2 (Public Review):

In this work, the authors address the problem of missing data imputation in the life sciences domain and propose several new algorithms which improve on the current state-of-the-art. In particular (i) they modify two existing Random Forest-based imputation methods -- MissForest and miceRanger -- to use either determinantal sampling or deterministic determinantal sampling, and show slightly improved classification performance on two datasets (one synthetic, one real); in addition, (ii) the authors present a quantum circuit for performing the determinantal sampling which scales asymptotically better than the best-known classical methods, and perform small scale experiments using both a (noiseless) quantum simulator as well as a 10 qubit IBM quantum computer to validate that the approach works in principle.

The problem of data imputation is important in practice, and results that improve on existing methods should be of interest to those in the field. The use of determinantal sampling for applications beyond data imputation should also be of broader interest, and the connection to quantum computing warrants further investigation and analysis.

The use of classification accuracy (as measured by AUC) as a measure of success is well-motivated, and the authors use both real and synthetic datasets to evaluate their methods, which consistently (if only marginally) outperform the existing state-of-the-art. The results obtained here motivate the further study of this approach to a wider class of datasets, and to areas beyond life sciences.

As it stands, in my opinion, two points need addressing.

1. Additional clarity is required on what is novel:

While the application of determinantal and deterministic determinantal sampling to the specific case of data imputation appears to be novel, the authors should make it more clear that both of these methods themselves are not new, and have been directly lifted from the literature. As it stands, the current wording in the main body of the paper gives the impression that the deterministic determinantal algorithm is novel, e.g. "this motivated us to develop a deterministic version of determinantal sampling" (p.2), and it is only in the methods section that a reference is made to the paper of Schreurs et al. which proposed the algorithm.

Similarly, in the abstract and main body of the text, the wording gives the impression that the quantum circuits presented here are new (e.g., "We also develop quantum circuits for implementing determinantal point processes") whereas they have been previously proposed (although one of the authors of the current paper was also an author of the original paper proposing the quantum circuits for determinantal sampling).

2. Additional analysis is needed to support the claims of potential for quantum advantage:

The authors claim that the quantum algorithm for implementing determinantal point processes provides a computational advantage over classical ones, in that the quantum circuits scale linearly in the number of features compared with cubic scaling classically. While this may be true asymptotically, in my opinion, more discussion is required about the utility and feasibility of this method in practice, as well as the realistic prospects of this being a potential area of application for quantum computing.

For example, the authors mention that a quantum computer of 150 qubits capable of running circuits of depth 400 is needed to perform the determinantal sampling for the MIMIC-III dataset considered, and say "while [such hardware is] not available right now, it seems quite possible that they will be available in the not so far future". The authors also state "This suggests that with the advent of next-generation quantum computers... one could expect a computational speedup in performing determinantal sampling" and "it is expected that next-generation quantum computers will provide a speedup in practice". These are strong assertions (even if 'next generation' is not clearly defined), and in my opinion, are not sufficiently backed by evidence to date. Given that datasets of the size of MIMIC-III (and presumably much larger) can be handled efficiently classically, the authors should clarify whether one expects a quantum advantage by this approach in the "NISQ" (pre-error-corrected) era of quantum computing. This seems unlikely, and any argument that this is the case should include an analysis accounting for the absolute operation speeds and absolute times required to perform such computations, including any time required for inputting data, resetting quantum circuits etc. On the other hand, if by 'next generation' the authors mean quantum computers beyond the NISQ era (i.e., assuming fault-tolerant quantum computers and logical qubits), then the overhead costs of quantum error correction (both in terms of physical qubit numbers as well as computational time) should be analyzed, and the crossover regime (i.e., data size where a quantum computation takes less absolute time than classical) estimated in order to assess the prospects of a practical quantum advantage, especially in light of recent analyses e.g., [1,2] below.

[1] Hoefler, Haner, Troyer. Communicatios of the ACM, 66.5 (2023):82-87<br /> [2] Babbush et al., PRX Quantum 2.1 (2021):010103

Other comments and suggestions:<br /> The authors measure "running time [as] the depth of the necessary quantum circuits." While circuit depth may indeed correspond to wall-clock time, quantum circuit size (i.e. number of gates) is the fairer complexity metric for comparison with classical running time. If depth is used, then a fair comparison to classical methods should be to compare with classical parallel processing time using N processors. However, if circuit size is used, then the quantum complexity is Nd, which contrasts with the classical value of Nd^2 (pre-processing) + d^3 (per sample). This yields a subquadratic quantum speedup over classical, as opposed to a qubic speedup.

The results (e.g Table 1) show that the new algorithms consistently outperform the original miceRanger and MissForest methods, although the degree of improvement is small, typically of order 1% or less. Some discussion is therefore warranted on the practical benefits of this method, and any tradeoff in terms of efficiency. In particular, while Table 1 compares the classification accuracy (as measured by AUC) of the newly proposed methods vs the existing state-of-the-art, a discussion on the scalability and efficiency would be welcome. The determinantal sampling takes time Nd^2, how does this compare with the original methods? For what dataset and feature sizes are the determinantal methods feasible (which will determine the scale at which other approaches, e.g. those based on quantum computing may be required).

A discussion (or at least mention) of the algorithmic complexity of the classical deterministic determinantal sampling (which seems to also be Nd^2) in the main body of the text would be welcome.

The final paragraph of the Methods section discusses sampling many times from the quantum circuits to estimate the most probable outcome, and hence perform the deterministic determinantal sampling. A more careful analysis of the number of samples needed (for bounded variance/error) and the impact on the running time (and whether one still expects an advantage over classical (although one must define some bounded error version of the deterministic algorithm to do so) or performance of the algorithm would be welcome.

A discussion on the absolute running time required for the quantum experiments performed (and how they compare to classical) would be interesting.

A mention of which quantum simulator was used would be welcome.

In the introduction, three kinds of data missingness (MCAR, MAR, MNAR) are mentioned, although experiments are only performed for MCAR and MNAR. Can some explanation for excluding MAR be given?

Reference 24 (Shadbar et al., the study that demonstrated the effectiveness of miceRanger and MissForest) used 4 datasets: MIMIC-III, Simulated, Breast Cancer, and NHSX COVID-19. Of these, MIMIC-III is used in the current paper, and Simulated appears similar (although with 1000 instead of 2000 rows) to the synthetic dataset of the current paper. An analysis of the determinantal sampling methods applied to the Breast Cancer and NHSX COVID-19 datasets (which have naturally occurring missingness), and a comparison to the results of Shadbar et al. would be interesting.

Reviewer #2 (Public Review):

Summary<br /> In this research advance, the authors purport to show that the unified neutral theory of biodiversity (UNTB) is not a suitable null model for exploring the relationship between macroecological quantities, and additionally that the stochastic logistic growth model (SLM) is a viable replacement. They do this by citing other studies where UNTB was unable to capture individual macroecological quantities and then demonstrating SLM's strength at modeling macroecological diversity metrics. They extend this analysis to show SLM's modeling capability at multiple scales of coarse-graining. Finally, the authors conduct a similar analysis to Madi et al. (2020) by investigating the relationship between diversity measures within a group and across coarse-grained groups (e.g. genera diversity in one family compared to diversity of families). The authors show that choosing SLM as a null model reveals some previously reported relationships to be no longer "novel", in the sense that the patterns can be adequately captured by the null model.

Strengths<br /> 1. The authors make a strong argument that UNTB is not a good null model of macroecological observables and especially relationships between them. The authors convincingly argue that a SLM is a better null since the gamma distribution it predicts is a better description of the empirical Abundance Fluctuation Distributions (AFD).<br /> 2. The authors show that the gamma distribution predicted by SLM is a good fit for the AFD's at many different scales of coarse-graining, not just the OTU level as was previously demonstrated.<br /> 3. The authors convincingly demonstrate how SLM can be used to test the relevance of interactions to macroecological relationships.

Weaknesses<br /> 1. Use of the word "predict" with the SLM in this advance is confusing, and to this reviewer seems to make a stronger claim than shown by the authors. For example, in their abstract, the authors state "We found that measures of biodiversity at a given scale can be consistently predicted using predictions (sic) derived from a minimal model of ecology." This appears to imply that a minimal model predicted the behavior of a system when in reality it accurately described the data it was trained on. This potential for confusion extends throughout the text and obscures what was actually achieved.<br /> 2. More generally, to my mind the presentation in the manuscript could benefit from a clearer delineation between the question of "what patterns are explainable by a noninteracting model vs require interactions" (which could be assessed with no reference to SLM, but by a simple randomization test), and whether specifically, SLM is a good null model / better than UNTB.

Overall Impact<br /> The authors achieve their aims, even though the text is at times dense. The use of SLM as a non-interacting null model for macroecological quantities and relationships is well supported by the text, and SLM should be used as a null model for these types of phenomena going forward.

Reviewer #2 (Public Review):

The study focuses on a mechanism of pest/pathogen resistance identified in Solanum commersonii, which appears to offer dominant resistance to Alternaria solani (potato early blight) through the activity of specific glycosyltransferases which facilitate the production of tetraose glycoalkaloids in leaf tissue. The authors demonstrated that these glycoalkaloids are suppressive to the growth of multiple pathogenic ascomycetes and furthermore, that transgenic plants expressing these glycosyltransferases in susceptible S. commersonii clones demonstrate improved resistance to specific strains of A. solani and a genotype of Colorado Potato Beetle. The study design is straightforward, yet thorough, and does a good job demonstrating the importance of these genes in resistance. This work is significant because it demonstrates the mechanism behind resistance to a necrotrophic pathogen. Resistance to this group of pathogens has historically relied on mechanisms that do not include the use of typical dominant resistance gene products (nucleotide-binding, leucine-rich repeat proteins). The identification of these glycosyltransferases and their role in resistance will give potato breeders options for the development of markers associated with resistance to this group of pathogens. However, this may demonstrate an important battle to balance between production traits (like disease resistance) and quality traits (like glycoalkaloid content), as the two may be mutually exclusive in the development of new varieties.

Reviewer #2 (Public Review):

This is an interesting follow-up study that uses long-read sequencing to examine previously constructed mutation accumulation lines between wild populations of S. cerevisiae and S. paradoxus. They also complement this work with reporter assays in hybrid backgrounds. The authors are attempting to test the hypothesis that hybridization leads to genome shock and unrestrained transposition. The paper largely confirms previous results (suggesting hybridization does not increase transposition) that are well cited and discussed in the paper, both from this group and from the Smukowski Heil/Dunham group but extends them to a new set of species/hybrids and with some additional resolution via the long read sequencing. The paper is well written and clear and I have no serious complaints.

In the abstract, the authors make three primary claims:

Structural variation plays a strong role in TE load.<br /> Transposition plays only a minor role in shaping the TE landscape in MA lines.<br /> Transposition rates are not increased by hybridization but are affected by genotype-specific factors.

I found all three claims supported, albeit with some minor questions below:

Structural variation plays a strong role in TE load.<br /> Convinced of this result. However:<br /> Line 185-187/Figure 3C: I'm curious given that the changes in Ty count are so often linked to changes in gross DNA sequence whether the count per total DNA sequence is actually changing on average in these genomes. Ie., does hybridization tend to increase TE count via CNV or does hybridization tend to increase DNA content in the MA lines and TEs come along for the ride?

One question about ploidy (lines 175-177):

Both aneuploidy and triploidy seem easy to call from this data. A 3:1 tetraploidy as well. However, in Figure 2B there are tetraploids that are around the 1:1 line. How are the authors calling ploidy for these strains? This was not clear to me from the text.

Reviewer #2 (Public Review):

This was an interesting study, and I enjoyed seeing different experimental approaches used to compare the properties of the different native proteins, the ancestral reconstructions, and the other mutants. I think it provides convincing mechanistic evidence as to how these small heat shock proteins have evolved. Thus, I think it represents a valuable contribution to the field. However, to a certain extent, I think the authors have at times over-interpeted their results, and over-simplified their explanations, as the differences between the ancestral proteins, and the changes induced by the two mutations, only partially explain the differences between IbpA proteins from the two different species. Furthermore, in some places, I found this difficult to follow and figures were not properly explained or labelled. If these issues were addressed, I think the paper would be considerably more accessible to readers.

Reviewer #2 (Public Review):

In this manuscript, the authors introduced an explicit ion model using the coarse-grained modelling approach to model the interactions between nucleosomes and evaluate their effects on chromatin organization. The strength of this method lies in the explicit representation of counterions, especially divalent ions, which are notoriously difficult to model. To achieve their aims and validate the accuracy of the model, the authors conducted coarse-grained molecular dynamics simulations and compared predicted values to the experimental values of the binding energies of protein-DNA complexes and the free energy profile of nucleosomal DNA unwinding and inter-nucleosome binding. Additionally, the authors employed umbrella sampling simulations to further validate their model, reproducing experimentally measured sedimentation coefficients of chromatin under varying salt concentrations of monovalent and divalent ions.

The significance of this study lies in the authors' coarse-grained model which can efficiently capture the conformational sampling of molecules while maintaining a low computational cost. The model reproduces the scale and, in some cases, the shape of the experimental free energy profile for specific molecule interactions, particularly inter-nucleosome interactions. Additionally, the authors' method resolves certain experimental discrepancies related to determining the strength of inter-nucleosomal interactions. Furthermore, the results from this study support the crucial role of intrinsic physicochemical interactions in governing chromatin organization within the nucleus.

The method is simple but can be useful, given the authors can provide more details on their ion parameterization. The paper says that parameters in their "potentials were tuned to reproduce the radial distribution functions and the potential of mean force between ion pairs determined from all-atom simulations." However, no details on their all-atom simulations were provided; at some point, the authors refer to Reference 67 which uses all-atom simulations but does not employ the divalent ions. Also, no explanation is given for their modelling of protein-DNA complexes.

Overall, the paper is well-written, concise and easy to follow but some statements are rather blunt. For example, the linker histone contribution (Figure 5D) is not clear and could be potentially removed. The result on inter-nucleosomal interactions and comparison to experimental values from Ref#44 is the most compelling. It would be nice to see if the detailed shape of the profile for restrained inter-nucleosomal interactions in Figure 4B corresponds to the experimental profile. Including the dependence of free energy on a vertex angle would also be beneficial.

Another limitation of this study is that the authors' model sacrifices certain atomic details and thermodynamic properties of the modelled systems. The potential parameters of the counter ions were derived solely by reproducing the radial distribution functions (RDFs) and potential of mean force (PMF) based on all-atom simulations (see Methods), without considering other biophysical and thermodynamic properties from experiments. Lastly, the authors did not provide any examples or tutorials for other researchers to utilize their model, thus limiting its application.

Reviewer #2 (Public Review):

Summary:<br /> The major purpose of this manuscript is to examine whether leucine treatment would be a potential strategy to treat cytokine storm syndrome (CSS). CSS is a common symptom in multiple infectious diseases in clinic, which gradually leads to multiple organ failure and high mortality. Strategies to treat CSS including pulse steroid therapy normally lead to severe side effects. Therefore, it is still required to develop a safe strategy with high efficacy to treat CSS. In clinic, sepsis is well characterized to exhibit CSS and therefore multiple studies utilized a LPS-induced sepsis model to evaluate CSS symptoms. In this study, the authors examined whether leucine, an essential amino acid that has been absorbed daily in our body, could ameliorate CSS symptoms in the LPS-induced sepsis mouse model. They found a potential protective effect of leucine in terms of the survival rate and inflammatory responses.

Strengths:<br /> The study is overall well designed and the results are well analyzed with only minor issues. The methods utilized are appropriate.

Weaknesses:<br /> The mechanistic insights are not sufficient and could not fully explain the phenotype they found. Considering the importance of this study is to identify the potential protective role of leucine in CSS, the authors could also consider investigator-initiated clinical trials to further expand the significance of this study.

Reviewer #2 (Public Review):

In this paper, Boi et al. thoroughly classified the electrophysiological and morphological characteristics of serotonergic and dopaminergic neurons in the DRN and examined the alterations of these neurons in the 6-OHDA-induced mouse PD model. Using whole-cell patch clamp recording, they found that 5-HT and dopamine (DA) neurons in the DRN are electrophysiologically well-distinguished from each other. In addition, they characterized distinct morphological features of 5-HT and DA neurons in the DRN. Notably, these specific features of 5-HT and DA neurons in the DRN exhibited different changes in the 6-OHDA-induced PD model. Then the authors utilized desipramine (DMI) to separate the effects of nigrostriatal DA depletion and noradrenalin (NA) depletion which are induced by 6-OHDA. Interestingly, protection from NA depletion by DMI pretreatment reversed the changes in 5-HT neurons, while having a minor impact on the changes in DA neurons in the DRN. These data indicate that the role of NA lesion in the altered properties of DRN 5-HT neurons by 6-OHDA is more critical than the one of DA lesion.

Overall, this study provides foundational data on the 5-HT and DA neurons in the DRN and their potential involvement in PD symptoms. Given the defects of the DRN in PD, this paper may offer insights into the cellular mechanisms that may underlie non-motor symptoms associated with PD. Despite the importance of the primary claim proposed by the authors, however, several weaknesses undermine the significance of the data.

Reviewer #2 (Public Review):

This manuscript describes experiments that further investigate the actions of the transcription factor Bcl11b in regulating mossy fiber (MF) synapses in the hippocampus. Prior work from the same group had demonstrated that loss of Bcl11b results in loss of MF synapses as well as a decrease in LTP. Here the authors focus on a target of Bcl11b a secreted synaptic organizer C1ql2 which is almost completely lost in Bcl11b KO. Viral reintroduction of C1ql2 rescues the synaptic phenotypes, whereas direct KD of C1ql2 recapitulates the Bcl1 phenotype. C1ql2 itself interacts directly with Nrxn3 and replacement with a binding deficient mutant C1q was not able to rescue the Bcl11b KO phenotype. Overall there are some interesting observations in the study, however there are also some concerns about the measures and interpretation of data.

The authors state that they used a differential transcriptomic analysis to screen for candidate targets of Bcl11b, yet they do not present any details of this screen. This should be included and at the very least a table of all DE genes included. It is likely that many other genes are also regulated by Bcl11b so it would be important to the reader to see the rationale for focusing attention on C1ql2 in this study.

All viral-mediated expression uses AAVs which are known to ablate neurogenesis in the DG (Johnston DOI: 10.7554/eLife.59291) through the ITR regions and leads to hyperexcitability of the dentate. While it is not clear how this would impact the measurements the authors make in MF-CA3 synapses, this should be acknowledged as a potential caveat in this study.

The authors claim that the viral re-introduction "restored C1ql2 protein expression to control levels. This is misleading given that the mean of the data is 2.5x the control (Figure 1d and also see Figure 6c). The low n and large variance are a problem for these data. Moreover, they are marked ns but the authors should report p values for these. At the least, this likely large overexpression and variability should be acknowledged. In addition, the use of clipped bands on Western blots should be avoided. Please show the complete protein gel in primary figures of supplemental information.

Measurement of EM micrographs: As prior work suggested that MF synapse structure is disrupted the authors should report active zone length as this may itself affect "synapse score" defined by the number of vesicles docked. More concerning is that the example KO micrographs seem to have lost all the densely clustered synaptic vesicles that are away from the AZ in normal MF synapses e.g. compare control and KO terminals in Fig 2a or 6f or 7f. These terminals look aberrant and suggest that the important measure is not what is docked but what is present in the terminal cytoplasm that normally makes up the reserve pool. This needs to be addressed with further analysis and modifications to the manuscript.

The study also presents correlated changes in MF LTP in Bcl11b KO which are rescued by C1ql2 expression. It is not clear whether the structural and functional deficits are causally linked and this should be made clearer in the manuscript. It is also not apparent why this functional measure was chosen as it is unlikely that C1ql2 plays a direct role in presynaptic plasticity mechanisms that are through a cAMP/ PKA pathway and likely disrupted LTP is due to dysfunctional synapses rather than a specific LTP effect. The authors should consider measures that might support the role of Bcl11b targets in SV recruitment during the depletion of synapses or measurements of the readily releasable pool size that would complement their findings in structural studies.<br /> Bcl11b KO reduces the number of synapses, yet the I-O curve reported in Supp Fig 2 is not changed. How is that possible? This should be explained.

Matsuda et al DOI: 10.1016/j.neuron.2016.04.001 previously reported that C1ql2 organizes MF synapses by aligning postsynaptic kainate receptors with presynaptic elements. As this may have consequences for the functional properties of MF synapses including their plasticity, the authors should report whether they see deficient postsynaptic glutamate receptor signaling in the Bcl11b KO and rescue in the C1ql2 re-expression.

Reviewer #2 (Public Review):

Schommartz et al. present a manuscript characterizing neural signatures of reinstatement during cued retrieval of middle-aged children compared to adults. The authors utilize a paradigm where participants learn the spatial location of semantically related item-scene memoranda which they retrieve after short or long delays. The paradigm is especially strong as the authors include novel memoranda at each delayed time point to make comparisons across new and old learning. In brief, the authors find that children show more forgetting than adults, and adults show greater engagement of cortical networks after longer delays as well as stronger item-specific reinstatement. Interestingly, children show more category-based reinstatement, however, evidence supports that this marker may be maladaptive for retrieving episodic details. The question is extremely timely both given the boom in neurocognitive research on the neural development of memory, and the dearth of research on consolidation in this age group. Also, the results provide novel insights into why consolidation processes may be disrupted in children. Despite these strengths, there are quite a few important design and analytical choices that derail my enthusiasm for the paper. If the authors could address these concerns, this manuscript would provide a solid foundation to better understand memory consolidation in children.

Reviewer #2 (Public Review):

The paper 'Complexes of vertebrate TMC1/2 and CIB2/3 proteins 1 form hair-cell mechanotransduction cation channels' by Giese and coworkers is quite an intense reading. The manuscript is packed with data pertaining to very different aspects of MET apparatus function, scales, and events. I have to praise the team that combined molecular genetics, biochemistry, NMR, microscopy, functional physiology, in-vivo tests for vestibulo-ocular reflexes, and other tests for vestibular dysfunction with molecular modeling and simulations. The authors nicely show the way CIBs are associated with TMCs to form functional MET channels. The authors clarify the specificity of associations and elucidate the functional effects of the absence of specific CIBs and their partial redundancy.

Reviewer #2 (Public Review):

Zheng et al., investigated the molecular and functional mechanisms of two homeodomain missense mutations causing human retinal photoreceptor degeneration diseases in photoreceptor development regulated by the CRX transcription factor. They analyzed the E80A mutation associated with dominant cone-rod dystrophy (CRD) and the K88N mutation associated with dominant Leber Congenital Amaurosis (LCA). The authors found that E80A CRX binds to the same target DNA sites as WT CRX, but the binding specificity of K88N CRX is altered from that of WT in an in vitro assay. They generated Crx(E80A) and Crx(K88N) KI mice and performed ChIP assay and observed that K88N CRX binds to novel genomic regions from the WT-binding sites, while E80A binds to the WT sites. In addition, using the KI mice, they found that E80A and K88N differently affect the expression of Crx target genes. This study is well executed with proper and solid methodologies, and the manuscript is clearly written. This study gives us the insights into how single missense CRX mutations lead to different types of human retinal photoreceptor degeneration diseases.

Overall, the authors have significantly improved the manuscript, but there is still an unclarified point. In response to the inquiry in the initial review on how extent E80A KI mice function as a pathological model of dominant CoRD, the authors add data (Figures S7) and described the sixth section in the discussion. However, the authors mentioned that it is technically too challenging because of a small number of cones. The point is not clear to me, but it is possible to analyze cone differentiation and degeneration by immunostaining at multiple stages even though cone number is small. Cone arrestin and S- and M-opsins become positive at early postnatal stages in the mouse retina. Cone arrestin seems earlier than cone opsins. Cones seem born by detecting RXRg at P0, but are cone arrestin and/or cone opsins expressed in early postnatal E80A/+ retina? If positive, how about an apoptosis marker? If negative, it seems to be a cone development phenotype rather than cone degeneration phenotype. If so, authors should modify the expression to say that the E80A retina underlies CoRD-like phenotype. It seems an overstatement.

Reviewer #2 (Public Review):

Zheng et al., investigated the molecular and functional mechanisms of two homeodomain missense mutations causing human retinal photoreceptor degeneration diseases in photoreceptor development regulated by the CRX transcription factor. They analyzed the E80A mutation associated with dominant cone-rod dystrophy (CRD) and the K88N mutation associated with dominant Leber Congenital Amaurosis (LCA). The authors found that E80A CRX binds to the same target DNA sites as WT CRX, but the binding specificity of K88N CRX is altered from that of WT in an in vitro assay. They generated Crx(E80A) and Crx(K88N) KI mice and performed ChIP assay and observed that K88N CRX binds to novel genomic regions from the WT-binding sites, while E80A binds to the WT sites. In addition, using the KI mice, they found that E80A and K88N differently affect the expression of Crx target genes. The authors may want to provide explicit clarification on whether CRX E80A mice exhibit cone development and/or degeneration defects.

This study is well executed with proper and solid methodologies, and the manuscript is clearly written. This study gives us the insights into how single missense CRX mutations lead to different types of human retinal photoreceptor degeneration diseases.

Reviewer #2 (Public Review):

Kraus, Aurora et al. investigated the potential immune response of the olfactory bulb after exposure of the infectious hematopoietic necrosis virus (IHNV), via the olfactory epithelia. Specifically, they show that a) viral-specific neuronal activation of "OSNs" (Crypt cells), b) changes in behaviour of both adult and larval zebrafish after viral exposure, c) Pituitary adenylate-cyclase-activating polypeptide (PACAP), was enriched when assayed by single cell transcriptomic profiling of cells in the OB after OSNs are exposed to IHNV

Although the paper does have strengths in principle, the weaknesses of the manuscript are that these strengths are not directly demonstrated and the referencing of the manuscript omits many references important for the understanding of the questions and the results of the study. Furthermore, the data presented are not sufficient to fully support the key claims in the manuscript. In particular:

a) Viral-specific neuronal activation of OSNs:<br /> What type of neurons? The authors are a bit elusive and do not clearly state that the neurons are crypt cells (Sepahi et al.: rainbow trout) which have a very specific axonal projection to the brain and whose response characteristics are not well characterized (see work of Korsching lab). Crypt cells are not present in the olfactory epithelia of mammals. Furthermore, in their previous work the crypt cells die; so how do they think the (inflammatory) virus response is transmitted to the olfactory bulbs in order to protect the brain?<br /> The authors state from previous work that they never detected virus in the brain, but why would they? Does INHV move trans-synaptically?<br /> The neuronal activity was monitored using a pan-neuronal marker thus these data are of limited use when trying to understand the role of neuronal activity (crypt cells) in the IHNV-triggered activity: the authors may be looking at a generalized inflammation response, and the image presented is not particularly informative it is difficult to decipher the results. The authors assume IHNV is an odorant without carefully ruling out the possibility of a generalized inflammation response.<br /> b) Changes in behaviour of both adult and larval zebrafish after viral exposure:<br /> What is the motivating question for looking at behaviour of the virus infected animals? Do we know the effects of crypt cell loss on the behaviour in any fish species? Authors need to build a better conceptual framework for the behaviour experiments.

c) Pituitary adenylate-cyclase-activating polypeptide (PACAP) was enriched when assayed by single cell transcriptomic profiling of cells in the OB after OSNs are exposed to IHNV. Authors draw many generous conclusions from limited data. Authors seem to have forgotten to cite papers previously published showing that PACAP-38 has anti-viral activities in fish (VHSV: trout) such as: Velasquez et al 2020, First in vivo evidence of pituitary adenylate cyclase-activating polypeptide antiviral activity in teleost.<br /> The histology for PACAP presented in the manuscript is not convincing. The antibody is against the human form of PACAP thus any labelling should be treated with caution (and called PACAP-38-like).

Summary: The authors need to better develop their model (perhaps a diagram would be helpful) explaining exactly which neurons are transmitting the information. Because of the elusive nature of some referencing and the skirting of important issues such as clearly stating which neurons are affected (crypt cells), what the point of the behaviour is (relate to neuronal type infected by virus), and, the lack of an antibody specific to the zebrafish protein, the model appears to be built on an unstable base.

DOI: 10.1101/2023.08.09.552694

Resource: (ZFIN Cat# ZDB-ALT-060919-2,RRID:ZFIN_ZDB-ALT-060919-2)

Curator: @olekpark

SciCrunch record: RRID:ZFIN_ZDB-ALT-060919-2

What is this?

Reviewer #2 (Public Review):

Summary:<br /> In their preprint, Fang et al present data on extending a spatial transcriptomics method, MERFISH, to 3D using a spinning disc confocal. MERFISH is a well-established method, first published by Zhaung's lab in 2015 with multiple follow-up papers. In the last few years, MERFISH has been used by multiple groups working on spatial transcriptomics, including approximately 12 million cell maps measured in the mouse brain atlas project. Variants of MERFISH were used to map epigenetic information complementary to gene expression and RNA abundance. However, MERFISH was always limited to thin ~10um sections to this date. The key contribution of this work by Fang et al. was to perform the optimization required to get MERFISH working in thick (100-200um) tissue sections.

Major strengths and weaknesses:<br /> Overall the paper presents a technical milestone, the ability to perform highly multiplexed RNA measurements in 3D using MERFISH protocol. This is not the first spatial transcriptomics done in thick sections. Wang et al. 2018 - StarMAP used thick sections (150 um), and recently, Wang 2021 (EASI-FISH, not cited) performed serial HCR FISH on 300um sections. Data so far suggest that MERFISH has better sensitivity than in situ sequencing approaches (StarMAP) and has built-in multiplexing that EASI-FISH lacks. Therefore, while there is an innovation in the current work, i.e., it is a technically challenging task, the novelty, and overall contribution are modest compared to recently published work.

The authors could improve the writing and the manuscript text that places their work in the right context of other spatial transcriptomics work. Out of the 25 citations, 12 are for previous MERFISH work by Zhaung's lab, and only one manuscript used a spatial transcriptomics approach that is not MERFISH. Furthermore, even this paper (Wang et al, 2018) is only discussed in the context of neuroanatomy findings. The fact that Wang et al. were the first to measure thick sections is not mentioned in the manuscript. The work by Wang et al. 2021 (EASI-FISH) is not cited at all, as well as the many other multiplexed FISH papers published in recent years that are very relevant. For example, a key difference between seqFISH+ and MERFISH was the fact that only seqFISH+ used a confocal microscope, and MERFISH has always been relying on epi. As this is the first MERFISH publication to use confocal, I expect citations to previous work in seqFISH and better discussions about differences.

To get MERFISH working in 3D, the authors solved a few technical problems. To address reduced signal-to-noise due to thick samples, Fang et al. used non-linear filtering (i.e., deep learning) to enhance the spots before detection. To improve registrations, the authors identified an issue specific to their Z-Piezo that could be improved and replaced with a better model. Finally, the author used water immersion objectives to mitigate optical aberrations. All these optimization steps are reasonable and make sense. In some cases, I can see the general appeal (another demonstration of deep learning to reduce exposure time). Still, in other cases, the issue is not necessarily general enough (i.e., a different model of Piezo Z stage) to be of interest to a broad readership. There were a few additional optimization steps, i.e., testing four concentrations of readout and encoder probes. So while the preprint describes a technical milestone, achieving this milestone was done with overall modest innovation.

Data and code sharing - the only link in the preprint related to data sharing sends readers to a deleted Dropbox folder. Similarly, the GitHub link is a 404 error. Both are unacceptable. The author should do a better job sharing their raw and processed data. Furthermore, the software shared should not be just the MERlin package used to analyze but the specific code used in that package.

Reviewer #2 (Public Review):

In this study, the authors measured extracellular electrical features of colliding APs travelling in different directions down an isolated earthworm axon. They then used these features to build a model of the potential ephaptic effects of AP annihilation, i.e. the electrical signals produced by colliding/annihilating APs that may influence neighbouring tissue. The model was then applied to some different hypothetical scenarios involving synaptic connections. The conclusion was that an annihilating AP at a presynaptic terminal can ephaptically influence the voltage of a postsynaptic cell (this is, presumably, the 'electrical coupling between neurons' of the title), and that the nature of this influence depends on the physical configuration of the synapse.

As an experimental neuroscientist who has never used computational approaches, I am unable to comment on the rigour of the analytical approaches that form the bulk of this paper. The experimental approaches appear very well carried out, and here I just have one query - an important assumption made is that the conduction velocity of anti- and orthodromically propagating APs is identical in every preparation, but this is never empirically/statistically demonstrated.

My major concern is with the conclusions drawn from the synaptic modelling, which, disappointingly, is never benchmarked against any synaptic data. The authors state in their Introduction that a 'quantitative physical description' of ephaptic coupling is 'missing', however, they do not provide such a description in this manuscript. Instead, modelled predictions are presented of possible ephaptic interactions at different types of synapses, and these are then partially and qualitatively compared to previous published results in the Discussion. To support the authors' assertion that AP annihilation induces electrical coupling between neurons, I think they need to show that their model of ephaptic effects can quantitatively explain key features of experimental data pertaining to synaptic function. Without this, the paper contains some useful high-precision quantitative measurements of axonal AP collisions, some (I assume) high-quality modelling of these collisions, and some interesting theoretical predictions pertaining to synaptic interactions, but it does not support the highly significant implications suggested for synaptic function.

Reviewer #2 (Public Review):

The authors have provided evidence for a rostral-caudal organisation of locus coeruleus connectivity, which they show i) differs across the lifespan, ii) is associated with relevant cognitive and mood measures. They have taken a data-driven, gradient-based approach, which was applied in the CamCan dataset and then replicated in the HCP dataset. This is a useful contribution to the field as it comprehensively shows a rostral-caudal pattern of connectivity in vivo, which has mostly been supported by tracer studies to date.

The strengths of the study are the large sample sizes and replication across two cohorts. The connectomic mapping approach they have applied is very well suited to the question at hand, as it allows a continuous gradient of organisation to be identified.

Reviewer #2:

The authors have significantly improved the manuscript, where assumptions and analytical and numerical results are now presented more clearly.

I still have some comments, more of less specific, that I list below, starting with the conceptual ones.

1. Citation of previous work on dynamical quorum sensing (lines 51 & 52) I think misses two important points: first these works (and others following them) deal with the appearance of collective oscillations at high density (therefore, the same general problem addressed here); second, Taylor et al. studied also a transition where the oscillators involved did not oscillate at low density, whereas above a density threshold, they display coherent collective oscillations whose period decreases with density - similar to what observed here. I do not think this takes anything away from the originality of this work, which refers to a different system, and models it with different equations, but the parallelism between integrate-and-fire dynamics with quenched noise and excitable dynamics in the presence of noise should in my opinion not be overlooked.<br /> 2. As the authors stress in lines 105 and 132, the analytical model shows that all that really matters in this phenomenon is the fastest frequency of the system. This could be used as an argument to say that the actual frequency distribution of individual fireflies is not all that important, as long as their fastest frequency is comparable. The assumption that they are identical would then sound less radical. Ideally, one could use the numerical simulations to check this, as well as the fact that the phenomenon does not break down when the shortest individual interburst interval Tb_min is narrowly distributed (which could also explain why having a few individuals who can flash at a higher frequency does not affect the outcome).<br /> 3. I still feel that the agreement between the model and observations is a bit overstated (line 120). At least, I think the authors may stress that whereas the model predicts that the frequency of the 7-14 minutes oscillations should increase a lot with N, this is not observed in the data. Maybe this mismatch would be reduced if inter-individual variability was added.<br /> 4. In paragraph 4.2, I found it unclear why the authors find it unsurprising that different experiments would correspond to different betas. I think that this point should be discussed, as beta and N appear in combination in determining the interaction strength. Otherwise, they could try to fit all distributions with the same beta, which would be more natural for me. I guess that the fits would be anyway good to the eye, though quantitatively suboptimal (which could be quantified with the distance introduced).

Minor stylistic comments:<br /> 1. Lines 98-100. Are all three 'Thus' needed?<br /> 2. 114: 'sufficiently identical' sounds like an oxymoron: what about just 'identical', or 'sufficiently close, so that they can be approximately considered identical'?<br /> 3. It would be more in line with the text (line 122) if panel F was the first panel of Figure 3. Also, the two orange lines are very hardly visible in print. They could be thickened. The inset, which I guess represents a zoom into the low Tbs, should be explained in the figure caption.<br /> 4. The caption of figure 5 relative to panels A-E does not say what is depicted. On line 3, row -> rows<br /> 5. Line 195 provide -> provides

Reviewer #2 (Public Review):

In this paper, Wang and colleagues build on previous technical and analytical achievements in establishing tetraploid human-chimpanzee hybrid iPSCs to investigate the cell type-specificity of allele-specific expression and allele-specific chromatin accessibility across six differentiated cell types (here, "allele-specific" indicates species differences with a cis-regulatory basis). The combined body of work is remarkable in its creativity and ambition and has real potential for overcoming major challenges in understanding the evolutionary genetics of between-species differences. The present paper contributes to these efforts by showing how differentiated cells can be used to test a long-standing hypothesis in evolutionary genetics: that cis-regulatory changes may be particularly important in divergence because of their potential for modularity.

In my view, the paper succeeds in making this case: allele (species)-specific expression (ASE) and allele-specific chromatin accessibility (ASCA) are enriched in genes asymmetrically expressed in one cell type, and many cases of ASE/ASCA are cell type-specific. The authors do an excellent job showing that these results are robust across a set of possible analysis decisions. It is somewhat less clear whether these enrichments are primarily a product of relaxed constraint on cell type-specific genes or primarily result from positive selection in the human or chimp lineage. While the authors attempt to control for constraint using several variables (variance in ASE in humans and the sequence-based probability of haploinsufficiency score, pHI), these are imperfect proxies for constraint. For the pHI scores, enrichments for ASE also appear to be strongest in the least constrained genes. Overall, the relative role of relaxation of constraint versus positive selection is unresolved, although the manuscript's language leans in favor of an important role for selection.

The remainder of the manuscript draws on the cell type-specific ASE/ASCA data to nominate candidate genes and pathways that may have been important in differentiating humans and chimpanzees. Several approaches are used here, including comparing human-chimp ASE to the distribution of ASE observed in humans and investigating biases in the direction of ASE for genes in the same pathway. The authors also identify interesting candidate genes based on their role in development or their proximity to human accelerated regions (where many changes have arisen on the human lineage in otherwise deeply conserved sequence) and use a deep neural network to identify sequence changes that might be causally responsible for ASE/ASCA. These analyses have value and highlight potential strategies for using ASE/ASCA and hybrid cell line data as a hypothesis-generating tool. Of course, the functional follow-up that experimentally tested these hypotheses or linked sequence/expression changes in the candidate pathways to organismal phenotype would have strengthened the paper further- but this is a lot to ask in an already technically and analytically challenging piece of work.

As a minor critique, the present paper is very closely integrated with other manuscripts that have used the hybrid human-chimp cell lines for biological insight or methods development. Although its contributions make it a strong stand-alone contribution, some aspects of the methods are not described in sufficient detail for readers to understand (even on a general conceptual level) without referencing that work, which may somewhat limit reader understanding.

Reviewer #2 (Public Review):

In this paper, the authors presented a compelling rationale for investigating the role of UBCs in prolonging and diversifying signals. Based on the two types of UBCs known as ON and OFF UBC subtypes, they have highlighted the existing gaps in understanding UBCs connectivity and the need to investigate whether UBCs target UBCs of the same subtype, different subtypes, or both. The importance of this knowledge is for understanding how sensory signals are extended and diversified in the granule cell layer.

The authors designed very interesting approaches to study UBCs connectivity by utilizing transgenic mice expressing GFP and RFP in UBCs, Brainbow approach, immunohistochemical and electrophysiological analysis, and computational models to understand how the feed-forward circuits of interconnected UBCs transform their inputs.

This study provided evidence for the existence of distinct ON and OFF UBC subtypes based on their electrophysiological properties, anatomical characteristics, and expression patterns of mGluR1 and calretinin in the cerebellum. The findings support the classification of GRP UBCs as ON UBCs and P079 UBCs as OFF UBCs and suggest the presence of synaptic connections between the ON and OFF UBC subtypes. In addition, they found that GRP and P079 UBCs form parallel and convergent pathways and have different membrane capacitance and excitability. Furthermore, they showed that UBCs of the same subtype provide input to one another and modify the input to granule cells, which could provide a circuit mechanism to diversify and extend the pattern of spiking produced by mossy fiber input. Accordingly, they suggested that these transformations could provide a circuit mechanism for maintaining a sensory representation of movement for seconds.

Overall, the article is well written in a sound detailed format, very interesting with excellent discovery and suggested model, however, I have some comments/suggestions that may help to improve this manuscript:

• The discovery of UBCs innervating each other and their own subtypes, suggesting the presence of feed-forward networks in the cerebellum, is an incredibly fascinating and exciting finding followed by an intriguing model by authors. However, it is worth considering an alternative model as well. I acknowledge that visualizing such interactions using current tools and methods can be challenging ("The approaches used here were not able to determine the existence of networks of more than 2 UBCs connected one after the other. If present, 3 or more UBCs in series could extend and transform the input in even more dramatic ways. The temporal diversity that UBC circuits generate may underlie the flexibility of the cerebellum to coordinate movements over a broad range of behaviors."). Therefore, if this is the case in which more than 2 UBCs connected one after the other, then an alternative model PERHAPS resembles the basal nuclei, with its direct and indirect circuits, can be considered (maybe a type of circular model). The basal nuclei circuits are also regulated by modulators such as D1 dopamine receptors in the direct pathway, causing depolarization, and D2 dopamine receptors in the indirect pathway, resulting in hyperpolarization upon dopamine activation. This approach could involve using computational models to gain insight into potential alternatives within this pathway (may be a future direction).

• GRP UBCs are more densely distributed in lobes VI-IX, while P079 UBCs are more densely distributed in the dorsal leaflet of lobe X in sagittal sections. While the cerebellum is well known for its characteristic stripy pattern, are UBC distributions the same in coronal/transverse section?

• The extension of the axons from both subtypes of UBCs show they are long enough to pass several UBCs and even projections are directed toward the white matter (e.g. Fig 9A), suggesting targeting the UBCs or granule cells in other lobules. Is it suggesting UBCs connectivity between different lobules (perhaps longitudinal connectivity)? Is there any observation or information in coronal/transverse section to visualize mediolateral connectivity?

• The limitation in identifying networks involving more than two sequentially connected UBCs was briefly noted. I suggest including a paragraph describing limitations and discussing the implications of the findings would enhance the overall impact of the research and broaden our understanding of cerebellar function.

• It is a pity that there is no clear conclusion to the discussion of this very interesting study. I suggest providing the key points as a conclusion.

• Please make the correction in Figure 2A by relabeling it as IXa, IXb, and IXc to correct the typographical error.

• I recommend rotating Figure 7A to align its orientation with the other figures for consistency.

Reviewer #2 (Public Review):

The authors developed an algorithm that allows for deconvoluting of plasmid sequences from a mixture of plasmids that have been sequenced by nanopore long read technology. As library preparations and barcoding of individual samples increase sequencing costs, the algorithm bypasses this need and thus decreases time on sample prep and sequencing costs. In the first step, the tool assesses which of the plasmid constructions can be mixed in a single library preparation by calculating a distance matrix between the reference plasmid and the constructions producing sequence clusters. The user is given groups of plasmids, from different clusters, to be pooled together for sequencing. After sequencing, the algorithm deconvolutes the reads by classifying them based on alignments to the reference sequence. A Bayesian analysis approach is used to obtain a consensus sequence and quality scores.

Strengths<br /> The authors exploit one of the main advantages of long-read sequencing which is to accurately resolve regions of high complexity, as regularly found in plasmids, and developed a tool that can validate plasmid constructions by reducing sequencing costs. Multiple plasmids (up to six) can be analyzed simultaneously in a single library without the need for sample barcoding, also reducing sample preparation time. Although inserts must be different, just 2 bases difference would be enough for a correct assignation. It maximizes cost-efficiency for projects that require large amounts of plasmid constructions and high-throughput validation.

Weaknesses<br /> The method proposed by the authors requires prior knowledge of plasmid sequences (i.e., blueprints or plasmid reference) and is not suitable for small experiments. The plasmid inserts or backbones must be different e.g., multiple colonies from the same plasmid construction effort cannot be submitted together.

Reviewer #2 (Public Review):

Using standard and widely used tools, the authors revealed the factors (cultural, phenotypic, phylogenetic, etc.) shaping societal and scientific interest in natural species around the globe. The strength of this manuscript (and the authors') lies in its command of the available literature, database and variable management and analysis, and its solid discussion. The authors thus achieved a manuscript that was pleasant to read.

While I agree that doing a global study requires losing details of local patterns, maybe this is exactly the biggest shortcoming of the manuscript, oblivious to how different cultures (compare USA to PNG, for example) are reflected in these global patterns.

Related to this previous point, my only other comment is about using English as a reference of societal interest (i.e., the presence of a common name in English). While English may be widespread in Academia, it is still not that common in other societal circles, especially those not using Wikipedia for lack of internet access.

Reviewer #2 (Public Review):

In this study, the authors tried to gauge the effect of human activity on three species, (1) the Hooded grow, an urban exploiter, (2) the Rose ring parakeet, an invasive, alien species that has adapted to exploit human resources, and (3) the Graceful Prinia, an urban adapter, which is relatively shy of humans. A goal of the study was to increase awareness of the importance of urban parks.

Strengths:<br /> Strengths of the study include the fact that it was conducted at 17 different sites, including parks, roads and residential areas, and included three species with different habitat preferences. Each species produced relatively loud and repeatable vocalizations. To avoid the effect of seasonal changes, sounds were sampled within a 10 day period of the lockdown as well as post-lockdown. The analysis included a comparison of the number of sound files, binary values indicating emission of a common syllable, and also the total number of syllables emitted as a measurement of bird activity. Ambient temperatures and sound levels of human activity were also recorded. All of these factors speak to the comprehensive approach and analysis adopted in this study. The results are based on a rigorous statistical analysis, ruling out effects of various extraneous parameters.

Weaknesses:<br /> The explanation of methods can be improved. For example, it is not clear if data were low-pass filtered before resampling to avoid aliasing.<br /> It is quite possible that birds move into the trees and further from the recorders with human activity. Since sound level decreases by the square of the distance of the source from the recorders, this could significantly affect the data. As indicated in the Discussion, this is a significant parameter that could not be controlled.<br /> In interpreting the data, the authors mention the effect of human activity on bird vocalizations in the context of inter-species predator-prey interactions; however, the presence of humans could also modify intraspecies interactions by acting as triggers for communication of warning and alarm, and/or food calls (as may sometimes be the case) to conspecifics. Along the same lines, it is important to have a better understanding of the behavioral significance of the syllables used to monitor animal activity in the present study.<br /> Another potential effect that may influence the results but is difficult to study, relates to the examination of vocalizations near to the ambient noise level. This is the bandwidth of sound levels where most significant changes may occur, for example, due to the Lombard effect demonstrated in bird and bat species. However, as indicated, these are also more difficult to track and quantify. Moreover, human generated noise, other than speech, may be a more relevant factor in influencing acoustic activity of different bird species. Speech, per se, similar to the vocalizations of many other species, may simply enrich the acoustic environment so that the effects observed in the present study may be transient without significant long-term consequences.

In general, the authors achieved their aim of illustrating the complexity of the effect of human activity on animal behavior. At the same time, their study also made it clear that estimating such effects is not simple given the dynamics of animal behavior. For example, seasonality, temperature changes, animal migration and movement, as well as interspecies interactions, such as related to predator-prey behavior, and inter/intra-species competition in other respects can all play into site-specific changes in the vocal activity of a particular species.

Reviewer #2 (Public Review):

Iske et al. provide experimental data that NAD+ lessens disease severity in bacterial sepsis without impacting on the host pathogen load. They show that in macrophages, NAD+ prevents Il1b secretion potentially mediated by Caspase11.

While the in vivo and in vitro data is interesting and hints towards a crucial role of NAD+ to promote metabolic adaptation in sepsis, the manuscript has shortcomings and would profit from several changes and additional experiments that support the claims.

Conceptually, the definition of sepsis is outdated. Sepsis is not SIRS, as in sepsis-2. Sepsis-3 defines sepsis as infection-associated organ dysfunction. This concept needs to be taken into account for the introduction and when describing the potential effects of NAD+ in sepsis. Also, LPS application cannot be considered a sepsis model, since it only recapitulates the consequence of TLR-4 activation. It is a model of endotoxemia. Also, the LPS data does not allow to draw conclusions about bacterial clearance (L135).

The authors state that protective effects by NAD were independent of the host pathogen load. This clearly indicates that NAD confers protection via enhancing a disease tolerance mechanism, potentially via reducing immunopathology. This aspect is not considered by the authors. The authors should incorporate the concept of disease tolerance in their work, cite the relevant literature on the topic and discuss it their findings in light of the published evidence for metabolic alteration sand adaptations in sepsis.

For the in vitro data, the manuscript would benefit from additional experiments using in vitro infection models.

In the merge manuscript, the authors provide two different versions of the figures. In one, bar plots are shown without individual data and in the other with scatter blots. All bar plots need to be provided as scatter plots showing individual values.

The authors should show further serology data for kidney and liver failure etc. as well as further cytokine data such as IL-6 and TNF to better characterize their models.

Careful revision of the entire manuscript, the figure legends and figures is required. The figure legend should not repeat the methods and materials section. The nomenclature for mouse protein and genes needs to be thoroughly revised.

L350. The authors write that they dissect the capacity of NAD+ to dampen auto- and alloimmunity. In this work, no data that supports this statement is shown and experiments with autoantigens or alloantigens are not performed.

L163 The authors describe pyroptosis but in the figure legend call it apoptosis. Specific markers for each cell death should be measured and determined which cell death mechanisms is involved.

Animal data comes from an infection model and LPS application. The RNAseq data is obtained from cells primed with Pam3CSK4 and subsequently subjected to LPS. It is unclear how the cell culture model reflects the animal model. As such the link between IFN signaling and the bacterial infection/LPS model are not convincing and need to be further elaborated.

Figure 5: It is unclear how many independent survival experiments were done, how many mice per group were used and whether the difference between groups was statistical significant. This information should be added.

Further experiments with primary cells from Il10 k.o. and Caspase11 k.o. animals should be provided that support the findings in macrophages.

Reviewer #2 (Public Review):

This manuscript describes the functional and structural characterization of an anaerobic (Class III) ribonucleotide reductase (RNR) with an ATP cone domain from Prevotella copri (PcNrdD). Most significantly, the cryo-EM structural characterization revealed the presence of a flap domain that connects the ATP cone domain and the active site and provides structural insights about how nucleotides and deoxynucleotides bind to this enzyme. The authors also demonstrated the catalytic functions and the oligomeric states. However, many of the biochemical characterizations are incomplete, and it is difficult to make mechanistic conclusions from the reported structures. The reported nucleotide-binding constants may not be accurate because of the design of the assays, which complicates the interpretation of the effects of ATP and dATP on PcNrdD oligomeric states. Importantly, statistical information was missing in most of the biochemical data. Also, while the authors concluded that the dATP binding makes the GRD flexible based on the absence of cryo-EM density for GRD in the dATP-bound PcNrdD, no other supports were provided. There was also a concern about the relevance of the proposed GRD flexibility and the stability of Gly radical. Overall, the manuscript provides structural insights about Class III RNR with ATP cone domain and how it binds ATP and dATP allosteric effectors. However, ambiguity remains about the molecular mechanism by which the dATP binding to the ATP cone domain inhibits the Class III RNR activity.

Strengths:<br /> 1. The manuscript reports the first near-atomic resolution of the structures of Class III RNR with ATP domain in complex with ATP and dATP. These structures revealed the NxN flap domain proposed to form an interaction network between the substrate, the linker to the ATP cone domain, the GRD, and loop 2 important for substrate specificity. The structures also provided insights into how ATP and dATP bind to the ATP cone domain of Class III RNR. Also, the structures suggested that the ATP cone domain is directly involved in the tetramer formation by forming an interaction with the core domain in the presence of dATP. These observations serve as an important basis for future study on the mechanism of Allosteric regulation of Class III RNR.

2. The authors used a wide range of methodologies including activity assays, nucleotide binding assays, oligomeric state determination, and cryo-EM structural characterization, which were impressive and necessary to understand the complex allosteric regulation of RNR.

3. The activity assays demonstrated the catalytic function of PcNrdD and its ability to be activated by ATP and low-concentration dATP and inhibited by high-concentration dATP.

4. ITC and MST were used to show the ability of PcNrdD to bind NTP and dATP.

5. GEMMA was used successfully to determine the oligomeric state of PcNrdD, which suggested that PcNrdD exists in dimeric and tetrameric forms, whose ratio is affected by ATP and/or dATP.

Weaknesses:<br /> 1. Activity assays.<br /> The activity assays were performed under conditions that may not represent the nucleotide reduction activity. The authors initiated the Gly radical formation and nucleotide reduction simultaneously. The authors also showed that the amount of Gly radical formation was different in the presence of ATP vs dATP. Therefore, it is possible that the observed Vmax is affected by the amount of Gly radical. In fact, some of the data fit poorly into the kinetic model. Also, the number of biological and technical replicates was not described, and no statistical information was provided for the curve fitting.

2. Binding assays.<br /> The interpretation of the binding assays is complicated by the fact that dATP binds both a- and s-sites and ATP binds a- and active sites. dATP may also bind the active site as the product. It is unknown if ATP binds s-site in PcNrdD. Despite this complexity, the binding assays were performed under the condition that all the binding sites were available. Therefore, it is not clear which event these assays are reporting.

3. Oligomeric states.<br /> Due to the ambiguity in the kinetic parameters and the binding constants determined above, the effects of ATP and dATP on the oligomeric states are difficult to interpret. The concentrations of ATP used in these experiments (50 and 100 uM) were significantly lower than KL determined by the activity assays (780 uM), while it is close to the Kd values determined by ITC or MST (~25 uM). Since it is unclear what binding events ITC and MST are reporting, the data in Figure 3 does not provide support for the claimed effects of ATP binding. For the effects of dATP, the authors did not observe a significant difference in oligomeric states between 50 or 100 uM dATP alone vs 50 uM dATP and 100 uM CTP. The former condition has dATP ~ 2x higher than the Kd and KL (Figure 1b) and therefore could be considered as "inhibited". On the other hand, NrdD should be fully active under the latter condition. Therefore, these observations show no correlation between the oligomeric state and the catalytic activity.

4. Effects of dATP binding on GRD structure<br /> One of the key conclusions of this manuscript is that dATP binding induces the dissociation of GRD from the active site. However, the structures did not provide an explanation for how the dATP binding affects the conformation of GRD or whether the dissociation of GRD is a direct consequence of dATP binding or it is due to the absence of nucleotide substrate. Also, Gly radical is unlikely to be stable when it is not protected from the bulk solvent. Therefore, it is unlikely that the GRD dissociates from the active site unless the inhibition by dATP is irreversible. Further evidence is needed to support the proposed mechanism of inhibition by dATP.

5. Functional support for the observed structures.<br /> Evidence for connecting structural observations and mechanistic conclusions is largely missing. For example, the authors proposed that the interactions between the ATP cone domain and the core domain are responsible for tetramer formation. However, no biochemical evidence was provided to support this proposal. Similarly, the functional significance of the interaction through the NxN flap domain was not proved by mutagenesis experiments.

Reviewer #2 (Public Review):

In this work, Xin et al. describe cryo-EM structures of the native and carotenoid-depleted forms of RC-LH from R. castenholzii, attempting to reveal how differences in the carotenoid composition may result in the structural and functional differences in the RC-LH complex. Previously, the authors obtained the nRC-LH structure at 4.1 angstrom resolution. The current work extends the earlier moderate-resolution to a higher resolution (2.8 angstrom), which allowed them to identify 14 additional carotenoid molecules located at the external positions between adjacent LHs. These external carotenoids, together with bacteriochlorophylls, result in an impenetrable LH ring surrounding the RC, leaving only the LH opening shaped by subunit X and c-TM as the pathway for quinone exchange. They further solve the dRC-LH structure at 3.1 angstrom resolution, and find that while nRC-LH binds 15 internal and 14 external carotenoids, dRC-LH contains only five internal carotenoids, as well as a highly mobile c-TM, but no subunit X. Comparing the two types of complexes at both structural and biochemical levels, they show that these structural changes may result in the accelerated quinone exchange in dRC-LH than that in nRC-LH.<br /> The structural data in this work are solid. The cryo-EM structures are well discussed and presented by the authors to highlight the structural features that may arise from carotenoid depletion. The authors also measured the oxidation rate of the auracyanin to characterize the quinone exchange rate. The work carried out by the authors is useful in the understanding of the regulatory role of carotenoids in complex assembly and quinone exchange.

Reviewer #2 (Public Review):

This is a modeled analysis of the impact of disruptions in school-based HPV vaccination due to the COVID-19 pandemic. Different catch-up scenarios were considered, ranging from a rapid catch-up period to no catch-up vaccination, and the impact of these on future HPV-related malignancies was approximated. The approach in this study could shed light on strategies for catch-up vaccination due to disruptions caused by the COVID-19 pandemic.

Strengths:<br /> - Using the context of Australia, which has led the world in vaccination, allows us to consider a best-case scenario for the impact of disruptions in a well-running HPV vaccination program with good population coverage.<br /> - The model accounts for multiple factors, including HPV transmission dynamics, mitigation of disease development by screening

Suggested clarifications:<br /> - It could benefit from fleshing out concepts instead of using parentheses, particularly in the abstract.<br /> - There is space to expand on the results presented in Table 1, including an explanation of Affected cohorts 2008 vs Affected cohorts 2008-2009. It may also be useful to explain this analysis in the methods section.<br /> - Given that Australia is a best-case scenario and other countries have not had the same success in HPV vaccination coverage, in the discussion would it be possible to give a comparison of how these three scenarios would look different in a population with school-based vaccination but lower coverage volume, such that readers could understand how much of the success / failures of each of the three catch-up scenarios? It would be particularly helpful for readers who are not familiar with the modeling tool used in this analysis.

Reviewer #2 (Public Review):

The purpose of this study is unclear from the introduction. Additionally, the methods are incomplete and did not describe how data was collected and analyzed. The results do not describe the sample. Once these are described more clearly, further comments can be made about what the authors were trying to achieve and the impact of the work on the field.

Reviewer #2 (Public Review):

In studying the neural control of action generation there is a presumption that different nodes within a connected neural control circuit contribute differentially to the production of a given gesture. In many cases, these circuits also receive inputs that can bias ongoing motor commands to alter output and therefore the motor gesture itself. Showing the specific role that each of the different areas play in motor control and how inputs might bias motor output is challenging. Taking advantage of a precisely controlled error-correction learning task of adult birdsong, Tian et al. perform simultaneous neural recording in both the primary forebrain song motor output nucleus (RA) as well as in an input structure (LMAN) known to be necessary for biasing motor output during such learning tasks. By comparing the activity pattern and timing between recorded activity in both structures, they show that LMAN activity leads RA activity for each of the song syllables but that there is a preferential gain in activity level in LMAN after learning only during the precise time window (10 - 50 msec) associated with the specific syllable that is targeted during the error-correction paradigm. They then follow these recordings with short focal electrical stimulation in LMAN targeted to the precise time window that shows increased gain in the dual recording paradigm. This stimulation is intended to scramble the bias signal and they show that such manipulation, in a temporally specific manner, does indeed eliminate the acoustic bias imposed by LMAN.

The precise combination of dual recording and targeted stimulation, in my opinion, convincingly shows that LMAN provides a temporally precise command that can bias motor output in RA. It is assumed that LMAN inputs onto RA are mapped with some level of functional topography, especially given that RA is thought to have some degree of motor mapping. The more dorsal areas, for example, likely contribute more to respiratory control while the more ventral portion contributes to acoustic control with a possible acoustic motor map within that region. Unfortunately, the spatial precision of the recording electrodes in both RA as well as LMAN is rather coarse and a careful functional spatial mapping of spike timing correlation is not possible. Hopefully in future studies, more precise spatial mapping will provide correlations within these two structures that might be able to target subareas that encode the signal bias for subcomponents of the specific acoustic features that are being targeted in this error-correction learning paradigm.

Reviewer #2 (Public Review):

This study by Pentz et al. aims to understand how cellular attachments and/or development affect the fitness of the transition to undifferentiated multicellularity. This work has the potential to better understand why some types of multicellular development (e.g. clonal development) versus others (e.g. aggregative development) are more or less commonly observed in nature.

Presently, much of our understanding of these processes comes from observation and theoretical work. This work aims to bridge this gap by rewiring the evolutionary clock and testing if different selected undifferentiated multicellular developmental strategies are better or worse.

The authors compare the fitness of Snowflake and Floc yeast under settling-based selection. They find that Snowflake is fitter under these conditions than Floc. They augment these findings with a simplified mathematical model that supports these findings.

On their face, the findings seem interesting but have limitations in that the authors did not consider alternate selective conditions and may come to different conclusions, potentially supporting the null hypothesis. In addition, doing experiments in related multicellular model systems that the authors have previously worked in would substantially improve generalizability.

Reviewer #2 (Public Review):

This work attempts to connect the diet of a mother to the physiology and feeding behaviors of multiple generations of her offspring. Using genetic and molecular biology approaches in the fruit fly model, the authors argue that this Lamarckian inheritance is mediated by germline-inherited chromatin and is regulated by the general activity of a histone methylase. However, many of the measured effects are small and variable, the statistical tests to prove their significance are missing or poorly described, and some experiments are inadequately described and lack important controls.

1) The authors claim that the diet of a mother can influence the physiology of her progeny for several generations. However, the observed effects of maternal diet on later generations were small and variable for most assays (see Fig1C, S1.1A, B, D). Additionally, the effect size between F0 HSD to ND was often larger than the effect size between the progeny of F0 parents and ND. To put it another way, if the authors were to compare the F1, F2, etc. to the F0 HSD flies, they would conclude that the majority of the response to diet is not maternally transmitted, and is directly controlled by the diet of the individual being measured.<br /> 2) The authors chose to study PER, which had the largest average effect sizes between conditions. However, PER was highly variable in the averaged data, with some individuals showing large effects and others having no effects. A better characterization of transgenerational PER may increase the robustness of this assay and confidence in its results. For example, the authors could measure PER in lineages derived from individual flies to determine when transgenerational effects on PER decline or disappear. This form of data collection could help to explain the high variation in the averaged data presented in the paper.<br /> 3) What do the error bars represent on any figure? There are many examples where the data is highly variable and lies completely outside of the error bars. What is the statistical test for significance that is carried out in each figure? The brief comment about statistics in the methods section is inadequate. The authors should also supply the raw data used to generate the figures so that readers can perform their own statistical tests.<br /> 4) The model that global H3K27me3 is regulated by ancestral diet is unconvincing without further experimental validation and explanation. Points 4-10 address specific issues. The authors performed ChIP on cycle 11 embryos. This stage is extremely short (11 min) and contains roughly 10 times less chromatin than embryos only 30 minutes older. These features make it very difficult to collect large numbers of precisely staged embryos without significant contamination. It is also debatable whether early cell cycles (including and preceding cycle 11) are slow enough to deposit and propagate histone marks in the presence of new histone incorporation. See the opposing arguments in Zenk et al 2017 and Li et al 2014. The authors could perform ChIP on older embryos to avoid this controversy. Surely any maternally inherited information will also be present in cycle 14 or 15 embryos if it is to influence the development or physiology of the brain. The observed differences in global H3K27me3 levels in F1 vs ND flies could be explained by slightly different aged embryo collections or technical variations in the ChIP protocol. The authors could strengthen their conclusion by performing more ChIP replicates. Alternatively, the authors could use orthogonal approaches like antibody staining or western blots to measure global H3K27me3 levels in precisely staged embryos.<br /> 5) The authors measure PRC2 subunit mRNA levels in adult fly heads to attempt to explain the observed differences in inherited H3K27me3 levels in fly embryos. The authors should examine PRC2 components in germ cells and early embryos to understand how germ cells and early embryos generate H3K27me3 patterns.<br /> 6) The RNAi experiment targeting PRC2 components in embryos is uninterpretable without appropriate controls and an explanation of the genotypes used in the experimental paradigm. Are the authors crossing nosNGT mothers to UAS-RNAi fathers and assaying the progeny? What is the genotype of the F1 flies and how does it compare to the genotype of the ND flies? The authors should also note that the Gal4 drivers they use are not necessarily restricted to the ovary, and could directly affect other tissues controlling PER like neurons and muscle. Additionally, the authors should supply the appropriate controls to verify that their experimental paradigm has the intended effect. PRC2 proteins are presumably loaded into embryos and would be immune to zygotic-expressed RNAi. The authors could validate when PRC2 RNAi is effective by staining embryos for H3K27me3.<br /> 7) Although the authors do not note this, nosNGT>RNAi affects the PER of ND flies (compare Gal4>RNAi to just RNAi or just Gal4 in ND columns in Fig3A-D). This could be due to RNAi expression in neurons or muscles or some other indirect effect. Regardless of the mechanism, this result makes it difficult to interpret how RNAi treatments affect the transgenerational inheritance of PER if there is an equivalently strong non-transgenerational effect.<br /> 8) The matalpha gal4 experiment is inadequately explained in the text or methods. Are the authors expressing RNAi in the ovaries of the F0 flies that are fed an HSD? Does the ovary influence their PER somehow? Similar to point 8, there appears to be a non-transgenerational component to the RNAi phenotype that clouds the interpretation of the transgenerational effect (compare F0 in S3.1A-C).<br /> 9) For the EED inhibitor experiments (both PER and calcium imaging), it is unclear whether the authors fed the mothers or their adult progeny the EED inhibitor. If adult progeny were fed, what tissues were affected? The authors should stain various tissues with an H3K27me3 antibody to verify the effectiveness of their inhibitor. Finally, the effect of the EED inhibitor on calcium imaging was not convincing because the variation was so large.<br /> 10) In all of the PRC2 RNAi and inhibitor experiments, are there any other phenotypes that would suggest that the treatments are working? There are many published PRC2 loss-of-function phenotypes (molecular and developmental) in different tissues. The authors could assure the reader that their treatments are working as expected by doing these controls.<br /> 11) The authors propose that a transgenerationally inherited state of the caudal gene is responsible for the transgenerationally inherited PER. However, the experiments investigating the methylation state and expression level of caudal are unconvincing. Cad mRNA abundance varied immensely in the ND RNAseq samples. When the authors compared cad levels across generations, the effect size was small. A single outlier in the ND sample in both the RNAseq and the RTPCR experiments appears to drive up its mean and effect size. The H3K27me3 ChIP on cad is very similar in the F1 and ND samples and the acetylation peak on its promoter appears unchanged. The authors could vastly improve the caudal experiments in this paper by simply using cad antibodies to stain the relevant tissues that contribute to PER. For example, the authors could stain GR5a neurons for cad expression in different generations that inherit (or don't inherit) maternal PER to more accurately determine if cad levels are indeed transgenerationally regulated. The authors could also perform more ChIP experiments at a less variable stage to convincingly correlate epigenetic marks on cad with its expression level.

Reviewer #2 (Public Review):

This work describes the development of a new structure-based learning approach to predict transcription binding specificity and its application in the modeling of regulatory complexes in cis-regulatory modules. The development of accurate computer tools to model protein-DNA complexes and to predict DNA binding specificity is a very relevant research topic with significant impact in many areas.

This article highlights the importance of transcriptional regulatory elements in gene expression regulation and the challenges in understanding their mechanisms. Traditional definitions of activating regulatory elements, such as promoters and enhancers, are becoming unclear, suggesting an updated model based on DNA accessibility and enhancer/promoter potential. Experimental techniques can assess the sequence preferences of transcription factors (TFs) for binding sites. Recent models propose a cooperative model in which regulatory elements work together to increase the local concentrations of TFs, RNA polymerase II, and other co-factors. Co-operative binding can be mediated through protein-protein or DNA interactions. The authors developed a structure-based learning approach to predict TF binding features and model the regulatory complex(es) in cis-regulatory modules, integrating experimental knowledge of structures of TF-DNA complexes and high-throughput TF-DNA interactions. They developed a server to characterize and model the binding specificity of a TF sequence or its structure, which was applied to the examples of interferon-β enhanceosome and the complex of factors SOX11/SOX2 and OCT4 with the nucleosome. The models highlight the co-operativity of TFs and suggest a potential role for nucleosome opening.

The results presented by the authors have a large variability in performance upon the different TF families tested. Therefore, it would be ideal if the performance/accuracy of the method is tested in some simple predictions and validated with prospective experimental data before applying it to model difficult scenarios such as those described here: SOX11/SOX2/OCT4 and nucleosome or interferon beta and enhanceosome. This will give more support to the models generated and thus the validity of the conclusions and hypothesis derived from them.

Reviewer #2 (Public Review):

Toker et al. use a frequency-resolved analysis of cortico-thalamic and thalamo-cortical information transfer to determine at which combinations of frequencies a frequency-specific transfer of information exists, and how this transfer is modulated by anesthesia, spike-and-wave seizures, and psychedelic states. They find that anesthesia and seizures lower the transfer of information at a specific combination of frequencies (sending: 1.5-13Hz, receiving 50-100Hz), whereas psychedelic states induced by 5-MeO-DMT increase. The reductions were observed for both directions whereas significant increases were only observed from cortex to thalamus.

Neural mean-field modeling shows that these empirical observations may be linked to a deviation of neural dynamics from the critical point between ordered and chaotic dynamics.

The manuscript tackles an important question using innovative methods. Yet, the analysis of spectrally resolved information transfer at present suffers from an unfortunate choice of analysis parameters (especially a history length of 1, and a low number of surrogate data), that need to be changed to fully install trust in the presented results. The statistical analysis seems to suffer from so-called 'double-dipping', but there are several possible ways to fix this issue.

Reviewer #2 (Public Review):

Davies et al combine TurboID with conditional mutagenesis to reveal how a perturbing event alters the accessibility of a sub-cellular proteome to proximity biotinylation. The approach builds on established techniques for antibody-mediated enrichment of biotinylated peptides (rather than purification of whole biotinylated proteins by avidin) to enable mapping of the specific lysines that are biotinylated by TurboID and how access to these sites changes between conditions. The insights gained have a range of potential implications touching on protein trafficking/localization, complex dynamics and membrane topology. The authors apply this strategy to study trafficking of the key P. falciparum adhesin PfEMP1 to the infected erythrocyte surface. This group has previously shown that the exported parasite kinase FIKK4.1 is important for this process but the specific mechanism is unknown. In the first part of the present study, the authors develop PerTurboID and analyze the altered biotinylation patterns upon FIKK4.1 deletion in parasite lines bearing TurboID tags on PTP4 or KAHRP, two proteins required for this pathway and likely direct substrates of FIKK4.1. Numerous changes in site-specific biotinylation are quantitatively assessed on hundreds of proteins and possible implications for these changes are discussed, including topology of parasite integral membrane proteins exported into the RBC compartment as well as how the conformation of the RhopH complex might be altered upon RBC membrane integration. In a final set of experiments, the authors show that among 18 exported FIKK kinases, FIKK4.1 is uniquely important to PfEMP1 surface display but not to the distinct RIFIN class of parasite proteins that are also trafficked to the RBC surface. On the whole, the data are compelling and provide an important new approach that advances the proximity labeling toolkit.

While the resolution of PerTurboID captures the site-specific changes in biotinylation abundance and position that occur upon loss of FIKK4.1, a limitation of the study is that these observations do not necessarily clarify the model for how FIKK4.1 is controlling the PfEMP1 trafficking pathway. The authors convincingly show that FIKK4.1 uniquely supports PfEMP1 surface presentation and cytoadhesion. However, this is not connected to the PerTurboID data in a way that provides a mechanism for how this is achieved by FIKK4.1 activity and in my opinion doesn't deliver on the title claim to "reveal the impact of kinase deletion on cytoadhesion". Certainly the changes in biotinylation suggest a range of interesting possibilities related to the accessibility and topology of proteins within and beyond the PfEMP1 trafficking pathway; however, it is hard to interpret the relationship of these changes to the process in view. For instance, deletion of FIKK4.1 increases biotinylation of several Maurer's clefts proteins in both the PTP4- and KAHRP-TurboID experiments but why this is or whether it is significant for PfEMP1 transport is unclear.

Reviewer #2 (Public Review):

This study follows up on a previous study by the group (Sibille et al Nature Communications 2022) in which high density Neuropixel probes were inserted tangentially through the superficial layers of the superior colliculus (SC) to record the activity of retinocollicular axons and postsynaptic collicular neurons in anesthetized mice. By correlating spike patterns, connected pairs could be identified which allowed the authors to demonstrate that functionally similar retinal axon-SC neuron pairs were strongly connected.

In the current study, the authors use similar techniques in vGAT-ChR2 mice and add a fiber optic to identify light-activated GABAergic and non-light-activated nonGABAergic neurons. Using their previously verified techniques to identify connected pairs, within regions of optogenetic activation they identified 214 connected pairs of retinal axons and nonGABAergic neurons and 91 pairs of connected retinal axons and GABAergic neurons. The main conclusion is that retinal activity contributed more to the activity of postsynaptic nonGABAergic SC neurons than to the activity of postsynaptic GABAergic SC neurons.

The study is very well done. The figures are well laid out and clearly establish the conclusions. My main comments are related to the comparison to other circuits and further questions that might be addressed in the SC.

It is stated several times that the superior colliculus and the visual cortex are the two major brain areas for visual processing and these areas are compared throughout the manuscript. However, since both the dorsal lateral geniculate nucleus (dLGN) and SC include similar synaptic motifs, including triadic arrangements of retinal boutons with GABAergic and nonGABAergic neurons, it might be more relevant to compare and contrast retinal convergence and other features in these structures.

The GABAergic and nonGABAergic neurons showed a wide range of firing rates. It might be interesting to sort the cells by firing rates to see if they exhibit different properties. For example, since the SC contains both GABAergic interneurons and projection neurons it would be interesting to examine whether GABAergic neurons with higher firing rates exhibit narrower spikes, similar to cortical fast spiking interneurons. Similarly, it might be of interest to sort the neurons by their receptive field sizes since this is associated with different SC neuron types.

The recording techniques allowed for the identification of the distance between connected retinocollicular fibers and postsynaptic neurons. It might also be interesting to compare the properties of connected pairs recorded at dorsal versus ventral locations since neurons with different genetic identities and response properties are located in different dorsal/ventral locations (e.g. Liu et al. Neuron 2023). Also, regarding the strength of connections, previous electron microscopy studies have shown that the retinocollicular terminals differ in density and size in the dorsal/ventral dimension (e.g Carter et al JCN 1991).

Was optogenetic activation of GABAergic neurons ever paired with visual activation? It would be interesting to examine the receptive fields of the nonGABAergic neurons before and after activation of the GABAergic neurons (as in Gale and Murphy J Neurosci 2016).

Reviewer #2 (Public Review):

The authors compare their single-cell data of the self-forming brain-eye centroids with the published single-cell data from human fetal retinas and brain/optic organoids. This analysis further supports the similarity of their centroids with the human fetal retinal cell clusters, including the detection of the VSX2+/PAX2+ cells. The new findings further support the presented centroids' applicability for future studies on human RGC development and axon guidance mechanisms.

Reviewer #2 (Public Review):

The authors wanted to address the differential processing of GSDME by caspase 3 and 7, finding that while in humans GSDME is only processed by CASP3, Takifugu GSDME, and other mammalian can be processed by CASP3 and 7. This is due to a change in a residue in the human CAPS7 active site that abrogates GSDME cleavage. This phenomenon is present in humans and other primates, but not in other mammals such as cats or rodents. This study sheds light on the evolutionary changes inside CASP7, using sequences from different species. Although the study is somehow interesting and elegantly provides strong evidence of this observation, it lacks the physiological relevance of this finding, i.e. on human side, mouse side, and fish what are the consequences of CASP3/7 vs CASP3 cleavage of GSDME.

Fish also present a duplication of GSDME gene and Takifugu present GSDMEa and GSDMEb. It is not clear in the whole study if when referring to TrGSDME is the a or b. This should be stated in the text and discussed in the differential function of both GSDME in fish physiology (i.e. PMIDs: 34252476, 32111733 or 36685536).

Reviewer #2 (Public Review):

In this study, Abele et al. present evidence to suggest that two different forms of regulated cell death, pyroptosis and apoptosis, are not equivalent in their ability to clear infection with recombinant Salmonella strains engineered to express the pro-pyroptotic NLRC4 agonist, FliC ("FliC-ON"), or the pro-apoptotic protein, BID ("BID-ON"). In general, individual experiments are well-controlled, and most conclusions are justified. However, the cohesion between different types of experiments could be strengthened and the overall impact and significance of the study could be articulated better.

Reviewer #2 (Public Review):

This work started with transcriptomic profiling of ductal cells to identify the upregulation of calcineurin in the zebrafish after beta-cell ablation. By suppressing calcineurin with its chemical inhibitor cyclosporin A and expressing a constitutively active form of calcineurin ubiquitously or specifically in ductal cells, the authors found that inhibited calcineurin activity promoted beta-cell regeneration transiently while ectopic calcineurin activity hindered beta-cell regeneration in the pancreatic tail. They also showed similar effects in the basal state but only when it was within a particular permissive window of Notch activity. To further investigate the roles of calcineurin in the ductal cells, the authors demonstrated that calcineurin inhibition additionally induced the proliferation of the ductal cells in the regenerative context or under a limited level of Notch activity. Interestingly, the enhanced proliferation was followed by a depletion of ductal cells, suggesting that calcineurin inhibition would exhaust the ductal cells. Based on the data, the authors proposed a very attractive and intriguing model of the role of calcineurin in maintaining the balance of the progenitor proliferation and the endocrine differentiation. However, the conclusions of this paper are only partially supported by the data as some evidence from the data remains suggestive.

1. In the transcriptomic profiling, genes differentially regulated in the ablated adults could be solely due to the chemical effects of metronidazole instead of the beta-cell ablation. A control group without ins:NTR-mCherry but treated with metronidazole is necessary to exclude the side effects of metronidazole.

2. Although it has been shown that the pancreatic duct is a major source of the secondary islets in the pancreatic tail in previous studies, there is no direct evidence showing the cyclosporin A-induced cells share the source in this manuscript. Without any proper lineage tracing work, the origin of those cyclosporin A-induced cells cannot be concluded.

3. It is interesting to see an increase of beta cells in the primary islet after cyclosporin A treatment (Supplemental Fig 2B). However, it remains unclear if their formation shares the same mechanism with the newly formed beta cells in the pancreatic tail.

4. The conclusion of the effect of cyclosporin A on the endocrine progenitors (Line 175) is not convincing because the data cannot distinguish the endocrine progenitors from the insulin-expressing cells. Indeed, Figure 2E shows that neurod1+ cells are fewer than ins+ cells (Figure 2D) in the pancreatic tail at 10 dpt, suggesting that all or at least the majority of neurod1+ cells are already ins+.

5. Figure 5D shows a significant loss of nkx6.1+ cells in the combined treatment group but there is no direct evidence showing this was a result of differentiation as the authors suggested. This cell loss also outnumbered the increase in ins+ cells (Figure 4D). The cell fates of these lost cells are still undetermined, and the authors did not demonstrate if apoptosis could be a reason of the cell loss.

Reviewer #2 (Public Review):

Novelty: The concept that capillary stalls occur in the ischemic penumbra is not new. However, there are several interesting findings in the current study.<br /> 1- Flow reversal, 2- the effect of flow disturbances on oxygenation, and 3- capillary pericytes do not affect the hemodynamics in the penumbra.<br /> However, more in-depth analysis is needed and the underlying mechanism of flow reversal and the link between flow reversal and pericytes is unclear.

Strengths:<br /> 1. The study employs a combination of techniques including Laser speckle imaging, two photon microscopy and biophysical modelling to specifically examine hemodynamic and metabolic changes in the penumbra following experimental stroke.<br /> 2. The importance of following microvascular flow changes during hours after stroke.<br /> 3. The authors used a rat model of stroke and confirmed previous work that has been performed in mice about capillary stalls and flow disturbance in the ischemic penumbra.

Weaknesses:<br /> 1- The reliance on laser speckle to define the ischemic core and penumbra is not convincing.<br /> 2- The mechanisms behind microvascular flow disturbance are poorly defined.<br /> 3- The inability to measure capillary flow simultaneously in the regions of interest: e.g, Bessel beam imaging or volumetric imaging.<br /> 4- Lack of baseline measurements.

Reviewer #2 (Public Review):

In the manuscript by Salmani et al., the authors explore the transcriptomic characterization of dopamine neurons in order to explore which neurons are particularly vulnerable to 6-OHDA-induced toxicity. To do this they perform single nucleus RNA sequencing of a large number of cells in the mouse midbrain in control animals and those exposed to 6-OHDA. This manuscript provides a detailed atlas of the transcriptome of various types of ventral midbrain cells - though the focus here is on dopaminergic cells, the data can be mined by other groups interested in other cell types as well. The results in terms of cell type classification are largely consistent with previous studies, though a more nuanced picture of cellular subtypes is portrayed here, a unique advantage of the large dataset obtained. The major advance here is exploring the transcriptional profile in the ventral midbrain of animals treated with 6-OHDA, highlighting potential candidate genes that may influence vulnerability. This approach could be generalizable to investigate how various experiences and insults alter unique cell subtypes in the midbrain, providing valuable information about how these stimuli impact DA cell biology and which cells may be the most strongly affected.

Overall, the manuscript is relatively heavy on characterization and comparatively light on functional interpretation of findings. This limits the impact of the proposed work. It also isn't clear what the vulnerability factors may be in the neurons that die. Beyond the characterization of which neurons die - what is the reason that these neurons are susceptible to lesion? Also, the interpretation of these findings is going to be limited by the fact that 6-OHDA is an injectable, and the effects depend on the accuracy of injection targeting and the equal access of the toxin to access all cell populations. Though the site of injection (MFB) should hit most/all of the forebrain-projecting DA cells, the injection sites for each animal were not characterized (and since the cells from animals were pooled, the effects of injection targeting on the group data would be hard to determine in any case).

I am also not clear why the authors don't explore more about what the genes/pathways are that differentiate these conditions and why some cells are particularly vulnerable or resilient. For example, one could run GO analyses, weighted gene co-expression network analysis, or any one of a number of analysis packages to highlight which genes/pathways may give rise to vulnerability or resilience. Since the manuscript is focused on identifying cells and gene expression profiles that define vulnerability and resilience, there is much more that could have been done with this based on the data that the authors collected.

Another limitation of this study as presented is the missed opportunity to integrate it with the rich literature on midbrain dopamine (and non-dopamine) neuron subtypes. Many subtypes have been explored, with divergent functions, and can usually be distinguished by either their projection site, neurotransmitter identity, or both. Unfortunately, the projection site does not seem to track particularly well with transcriptomic identities, aside from a few genes such as DAT or the DRD2 receptor. However, this could have been more thoroughly explored in this manuscript, either by introducing AAVretro barcodes through injection into downstream brain sites, or through existing evidence within their sequencing dataset. There are likely clear interpretations from some of that literature, some of which may be more exciting than others. For example, the authors note that vGluT2-expressing cells were part of the resilient territory. This might be because this is expressed in medially-located DA cells and not laterally-located ones, which tends to track which cells die and which don't.

It is not immediately clear why the authors used a relaxed gate for mCherry fluorescence in Figure 1. This makes it difficult to definitively isolate dopaminergic neurons - or at least, neurons with a DAT-Cre expression history. While the expression of TH/DAT should be able to give a fairly reliable identification of these cells, the reason for this decision is not made clear in the text.

Reviewer #2 (Public Review):

In their study, Zaman et al. demonstrate that deletion of either the receptor tyrosine kinase Kit from cerebellar interneurons or the kit ligand (KL) from Purkinje cells reduces the inhibition of Purkinje cells. They delete Kit or KL at different developmental time points, illustrating that Kit-KL interactions are not only required for developmental synapse formation but also for synapse maintenance in adult animals. The study is interesting as it highlights a molecular mechanism for the formation of inhibitory synapses in Purkinje cells.

The tools generated, such as the floxed Kit mouse line and the virus for Kit overexpression, may have broader applications in neuroscience and beyond.

However, to enhance the publication's impact and strengthen its hypotheses, conclusions, and scientific rigor, it would be beneficial to include additional experimental details, data analyses (particularly regarding the quantification of electrophysiology data), as well as methodological and textual clarifications.

One general weakness is that Kit expression is not limited to molecular layer interneurons but also extends to the Purkinje layer and Golgi interneurons. Although this expression may not conflict with the reported results, as Purkinje layer interneurons form few or no synapses onto Purkinje cells, it should be highlighted in the text (introduction and/or discussion).

In summary, the data support the hypothesis that the interaction between Kit and KL between cerebellar Molecular Layer Interneurons and Purkinje Cells plays a crucial role in promoting the formation and maintenance of inhibitory synapses onto PCs. This study provides valuable insights that could inform future investigations on how this mechanism contributes to the dynamic regulation of Purkinje cell inhibition across development and its impact on mouse behavior.

Reviewer #2 (Public Review):

This paper takes a novel look at the protein economy of primary human and mouse T-cells - in both resting and activated state. Their findings in primary human T-cells are that:

1. A large fraction of ribosomes are stalled in resting cultured primary human lymphocytes, and these stalled ribosomes are likely to be monosomes.<br /> 2. Elongation occurs at similar rates for HeLa cells and lymphocytes, with the active ribosomes in resting lymphocytes translating at a similar rate as fully activated lymphocytes.

They then turn their attention to mouse OT-1 lymphocytes, looking at translation rates both in vitro and in vivo. Day 1 resting T-cells also show stalling - which curiously wasn't seen on freshly purified cells - I didn't understand these differences.

In vivo, they show that it is possible to monitor accurate translation and measure rates. Perhaps most interestingly they note a paradoxically high ratio of cellular protein to ribosomes insufficient to support their rapid in vivo division, suggesting that the activated lymphocyte proteome in vivo may be generated in an unusual manner.

This was an interesting and provocative paper. Lots of interesting techniques and throwing down challenges to the community - it manages to address a number of important issues without necessarily providing answers.

Reviewer #2 (Public Review):

The authors introduce the notions of "variant vulnerability" and "drug applicability" as metrics quantifying the sensitivity of a given target variant across a panel of drugs and the effectiveness of a drug across variants, respectively. Given a data set comprising a measure of drug effect (such as growth rate suppression) for pairs of variants and drugs, the vulnerability of a variant is obtained by averaging this measure across drugs, whereas the applicability of a drug is obtained by averaging the measure across variants.

The authors apply the methodology to a data set that was published by Mira et al. in 2015. The data consist of growth rate measurements for a combinatorially complete set of 16 genetic variants of the antibiotic resistance enzyme beta-lactamase across 10 drugs and drug combinations at 3 different drug concentrations, comprising a total of 30 different environmental conditions. For reasons that did not become clear to me, the present authors select only 7 out of 30 environments for their analysis. In particular, for each chosen drug or drug combination, they choose the data set corresponding to the highest drug concentration. As a consequence, they cannot assess to what extent their metrics depend on drug concentration. This is a major concern since Mira et al. concluded in their study that the differences between growth rate landscapes measured at different concentrations were comparable to the differences between drugs. If the new metrics display a significant dependence on drug concentration, this would considerably limit their usefulness.

As a consequence of the small number of variant-drug combinations that are used, the conclusions that the authors draw from their analysis are mostly tentative with weak statistical support. For example, the authors argue that drug combinations tend to have higher drug applicability than single drugs, because a drug combination ranks highest in their panel of 7. However, the effect profile of the single drug cefprozil is almost indistinguishable from that of the top-ranking combination, and the second drug combination in the data set ranks only 5th out of 7.

To assess the environment-dependent epistasis among the genetic mutations comprising the variants under study, the authors decompose the data of Mira et al. into epistatic interactions of different orders. This part of the analysis is incomplete in two ways. First, in their study, Mira et al. pointed out that a fairly large fraction of the fitness differences between variants that they measured were not statistically significant, which means that the resulting fitness landscapes have large statistical uncertainties. These uncertainties should be reflected in the results of the interaction analysis in Figure 4 of the present manuscript. Second, the interpretation of the coefficients obtained from the epistatic decomposition depends strongly on the formalism that is being used (in the jargon of the field, either a Fourier or a Taylor analysis can be applied to fitness landscape data). The authors need to specify which formalism they have employed and phrase their interpretations accordingly.

Reviewer #2 (Public Review):

Multiple sclerosis is an inflammatory and demyelinating disease of the central nervous system where immune cells play an important role in disease pathobiology. Increased incidence of disease in individuals carrying certain HLA class-II genes plus studies in animal models suggests that HLA-DRB1*15 restricted CD4 T cells might be responsible for disease initiation, and other immune cells such as B cells, CD8 T cells, monocytes/macrophages, and dendritic cells (DC) also contribute to disease pathology. However, a direct role of human immune cells in disease is lacking to a lag between immune activation and the first sign of clinical disease. Therefore, there is an emphasis on understanding whether immune cells from HLA-DR15+ MS patients differ from HLA-DR15+ healthy controls in their phenotype and pro-inflammatory capacity. To overcome this, authors have used severely immunodeficient B2m-NOG mice that lack B, T cells, and NK cells and have defective innate immune responses and engrafted PBMCs from 3 human donors (HLA-DR15+ MS and HI donors, HLA-DR13+ MS donor) in these B2m-NOG mice to determine whether they can induce CNS inflammation and demyelination like MS.<br /> The study's strength is the use of PBMCs from HLADRB1-typed MS subjects and healthy control, the use of NOG mice, the characterization of immune subsets (revealing some interesting observations), CNS pathology etc. The major weaknesses are i) lack of sufficient sample size (n=1 in each group) to make any conclusion, ii) lack of phenotype in mice, iii) no disease phenotype even in humanized mice immunized for disease using standard disease induction protocol employed in an animal model of MS, and iv) mechanistic data on why CD8 T cells are more enriched than CD4+ T cells. The last point is very important as postmortem human MS patients' brain tissue had been shown to have more CD8+ T cells than CD4+ T cells.

Thus, this work is an important step in the right direction as previous humanized studies have not used HLA-DRB1 typed PBMCs however the weaknesses as highlighted above make the findings incremental to the field.

Reviewer #2 (Public Review):

Place cells fire sequentially during hippocampal theta oscillations, forming a spatial representation of behavioral experiences in a temporally-compressed manner. The firing sequences during theta cycles are widely considered as essential assemblies for learning, memory, and planning. Many theoretical studies have investigated the mechanism of hippocampal theta firing sequences; however, they are either entirely extrinsic or intrinsic. In other words, they attribute the theta sequences to external sensorimotor drives or focus exclusively on the inherent firing patterns facilitated by the recurrent network architectures. Both types of theories are inadequate for explaining the complexity of the phenomena, particularly considering the observations in a previous paper by the authors: theta sequences independent of animal movement trajectories may occur simultaneously with sensorimotor inputs (Yiu et al., 2022).

In this manuscript, the authors concentrate on the CA3 area of the hippocampus and develop a model that accounts for both mechanisms. Specifically, the model generates extrinsic sequences through the short-term facilitation of CA3 cell activities, and intrinsic sequences via recurrent projections from the dentate gyrus. The model demonstrates how the phase precession of place cells in theta sequences is modulated by running direction and the recurrent DG-CA3 network architecture. To evaluate the extent to which firing sequences are induced by sensorimotor inputs and recurrent network architecture, the authors use the Pearson correlation coefficient to measure the "intrinsicity" and "extrinsicity" of spike pairs in their simulations.

I find this research topic to be both important and interesting, and I appreciate the clarity of the paper. The idea of combining intrinsic and extrinsic mechanisms for theta sequences is novel, and the model effectively incorporates two crucial phenomena: phase precession and directionality of theta sequences. I particularly commend the authors' efforts to integrate previous theories into their model and conduct a systematic comparison. This is exactly what our community needs: not only the development of new models, but also understanding the critical relationships between different models.

Reviewer #2 (Public Review):

The manuscript by Elfstrom et al describes the impact of implementing self-sampling as the primary screening test in Sweden to address decreases in coverage following the COVID pandemic. The authors have a very rich dataset including all records of invitations to screen and screening results in the Stockholm area. A limitation is that there is no individual record linkage to allow investigation of the profile of the individuals who chose to screen using the self-sample.

The conclusions are generally well supported by the authors with the following exceptions:

1) There was not enough evidence presented in the manuscript to conclude that "The most likely explanation for the large increase in population coverage seen is that the sending of self-sampling kits resulted in improved attendance in particular among previously non-attending women."

2) The authors state there is no evidence that delays in screening have impacted cervical cancer rates however they present no data to this effect in the manuscript.

Reviewer #2 (Public Review):

In this article, Moses and Harel present genetic knock-out and partial rescue of the phenotypes of neuropeptides gh1 and fshb, and tshb in a short-lived vertebrate African turquoise killifish Nothobranchius furzeri. Neuropeptides are among the key regulators of growth, reproduction, and metabolism. Understanding their mechanisms of action has important implications for vertebrate physiology.

The authors first characterize the loss of function phenotypes of gh1, fshb, and tshb in killifish, followed by attempts to rescue the loss of function phenotypes through ectopic expression of two of the neuropeptides. The primary strength and innovation of this work are partially rescuing the phenotypes by muscular injection of plasmids followed by electroporation, including a doxycycline-inducible system for tunable expression control. The techniques for tunable expression control and rescue of knock-out phenotypes have not been established for killifish and will be useful to expand the technical repertoire of this emerging model organism. Once established, these techniques can be extended to other categories of genes to rapidly evaluate their function and the impact of their loss or gain of function on killifish and other fish models.

However, the phenotypes discussed need further characterization, many technical details are unclear, and it seems that appropriate controls are missing for some of the experiments. The rescued phenotypes also need more validation.

Reviewer #2 (Public Review):

This article focuses on drug resistance acquired by Plasmodium falciparum malaria parasites that have been pressured with different inhibitors of the essential enzyme DHODH (dihydroorotate dehydrogenase). The study focuses on collateral sensitivity between DSM265, which has been evaluated in a human clinical trial and found to select for resistance via the point mutation C276Y (C276F and G181S were also implicated; PMID 29909069), and the GSK compound TMCDC-125334, against which a panel of DHODH mutant parasites (including C276Y) were found to have increased sensitivity. The authors herein explore this case of "collateral sensitivity" by examining whether these two inhibitors, when used simultaneously, might preclude the selection of resistant parasites. The answer, in this case, is no; collateral sensitivity did not prevent parasites from acquiring a novel mutation (V532A) that mediated resistance to both. Culture competition assays provide evidence that this mutant retains normal fitness. The authors conclude that for this target the idea of combining these inhibitors is not a viable therapeutic strategy. The authors also illustrate how TMCDC-125334 can select for resistance via a separate mutation (I263S) or amplification of a chromosomal segment containing dhodh. They also present modeling data to examine binding poses and how mutations could impact drug binding, which is allosteric to the enzyme's substrates (orotate and FMN). The data are thorough and provide convincing evidence that in this case collateral sensitization by distinct chemotypes does not translate into a viable strategy to inhibit DHODH in a way that can preclude mutations that confer cross-resistance.

Reviewer #2 (Public Review):

In their recent manuscript, Broca-Brisson et al. deliver a multidisciplinary approach to investigate creatine transporter deficiency (CTD) using human-derived brain organoids. The authors have provided a compelling CTD human brain organoid model using induced pluripotent stem cells (iPSCs) derived from individuals with CTD. This model shows distinct differences in creatine uptake between organoids originating from CTD patients and their healthy counterparts. Furthermore, the researchers effectively restored creatine uptake by reintroducing the wild-type CRT in the iPSCs.

The team used advanced molecular biology techniques and sophisticated mass spectrometry to identify changes in protein regulation within these CTD brain organoids. They propose an intriguing theory linking reduced creatine uptake to abnormalities in the GSK3β kinase pathway and mitochondrial function, which might underlie intellectual disability seen in CTD patients.<br /> This study is well-structured and easy to follow, with clear and concise explanations of the experiments. The authors present an important idea: a dysfunction in just one protein transporter (CRT) can cause significant biochemical changes in the brain. Their findings are well-presented and backed by high-quality figures and comprehensive data analysis.

There are only minor suggestions for improvement in this manuscript. The authors strongly link creatine uptake, the GSK3β pathway, and intellectual disability. Enhancing this claim with data on phosphorylation differences between organoids derived from healthy individuals and those from CTD patients could solidify this foundation and facilitate a more holistic understanding of the disease. In addition, the in vitro model based on organoids might be closer than other experimental setups; however, proving that those differences are also present in vivo would greatly benefit the story.

There is also some uncertainty around the rescue experiment using the exogenous SLC6A8 gene. Could the difference in creatine uptake between the rescue iPSCs and the healthy control be due to CRT overexpression? Higher levels of the transporter may explain the elevated levels of intracellular creatine. Thus, a comparison using Western blotting experiments could be a valuable addition to evaluating the expression levels of this protein.

Overall, this study provides valuable insights into CTD and potential therapeutic targets. It enriches our understanding of CTD and opens up new avenues for future research in this field.

Reviewer #2 (Public Review):

The authors used cutting-edge bio-telemetry technology to decipher the roles of wind speed and wave height on the take-off of albatrosses from the water surface. They revealed that each of these factors contributes to take-off in a unique way with interesting interactions of the two factors. The authors achieved their objectives and their results support their conclusions. This work will set new standards in integrating information about bird movement and environmental conditions experienced by the bird in a comprehensive, integrative and hypothesis-driven framework. The approach of the authors is highly advanced, providing heuristic insights for many additional systems where organisms are influenced by, and respond to small-scale environmental conditions.

Reviewer #2 (Public Review):

The manuscript by Seah and Saranathan investigates the cell-based growth mechanism of so called honeycomb-structures in the upper lamina of papilionid wing scales by investigating a number of different species. The authors chose Parides eurimedes as a focus species with the developmental pathway of five other papilionid as a comparative backup. Through state-of-the-art microscopy images of different developmental steps, the author find that the intricate f-actin filaments reorganise, support cuticular discs that template the air holes that form the honeycomb lattice. The manuscript is well written and easy to follow, yet based on a somewhat limited sample size for their focus species, limiting attempts to suppress expression and alter structure shape.

The fact that the authors find a novel reorganisation mechanism is exciting and warrants further research, e.g. into the formation of other microscale features or smaller scale structures (e.g. the mentioned gyroid networks).<br /> The authors place their results in the discussion in the light of current literature (although the references could be expanded further to include the breadth of the field). However, the mechanistic explanation completely ignores the mechanical properties of the membranes as an origin of some of the observed phenomena (see McDougal's work for example) and places the occurence of some features into Turing patterns and Ostwald ripening, which I find somewhat unlikely and I suggest that the authors discover this aspects further in the discussion.

I have little concerns regarding the experimental approach beyond the somewhat limited sample size. One thing the authors should more clearly mention are the pupation periods for all investigated species as only the periods for two species are named.

Reviewer #2 (Public Review):

In this study, Sekulovski and colleagues report refinements to an in vitro model of human amnion formation. Working with 3D cultures and BMP4 to induce differentiation, the authors chart the time course of amnion induction in human pluripotent stem cells in their system using immunofluorescence and RNA-seq. They carry out validation through comparison of their data to existing embryo datasets, and through immunostaining of post-implantation marmoset embryos. Functional experiments show that the transcription factor TFAP2C drives the amnion differentiation program once it has been initiated.

There is currently great interest in the development of in vitro models of human embryonic development. While it is known that the amnion plays an important structural supporting role for the embryo, its other functions, such as morphogen production and differentiation potential, are not fully understood. Since a number of aspects of amnion development are specific to primates, models of amniogenesis will be valuable for the study of human development. Advantages of this model include its efficiency and the purity of the cell populations produced, a significant degree of synchrony in the differentiation process, benchmarking with single-cell data and immunocytochemistry from primate embryos, and identification of key markers of specific phases of differentiation. Weaknesses are the absence of other embryonic tissues in the model, and overinterpretation of certain findings, in particular relating bulk RNA-seq results to scRNA-seq data from published analyses of primate embryos and results from limited (though high quality) embryo immunostainings.

Reviewer #2 (Public Review):

The authors of the manuscript have developed and used cloning-free method. It is not entirely novel (rather it is based on previously described ISA method) but it is clearly efficient and useful complementation to the already existing methods. One of strong points of the approach use by authors is that it is very versatile, i.e. can be used in combination with already existing methods and tools. I find it important as many laboratories have already established their favorite methods to manipulate SARS-CoV-2 genome and are probably unwilling to change their approach entirely. Though authors highlight the benefits of their method these are probably not absolute - other methods may be as efficient or as fast. Still, I find myself thinking that for certain purposes I would like to complement my current approach with elements from authors CLEVER method.

The work does not contain much novel biological data - which is expected for a paper dedicated to development of new method (or for improving the existing one). It may be kind of shortcoming as it is commonly expected that authors who have developed new methods apply it for discovery of something novel. The work stops on step of rescue the viruses and confirming their biological properties. This part is done very well and represents a strength of the study. The properties of rescued viruses were also studied using NSG methods that revealed high accuracy of the used method, which is very important as the method relies on use of PCR that is known to generate random mistakes and therefore not always method of choice.

What I found missing is a real head-to-head comparison of the developed system with an existing alternatives, preferably some PCR-free standard methods such as use of BAC clones. There are a lot of comparisons but they are not direct, just data from different studies has been compared. Authors could also be more opened to discuss limitations of the method. One of these seems to be rather low rescue efficiency - 1 rescue event per 11,000 transfected cells. This is much lower compared to infectious plasmid (about 1 event per 100 cells or so) and infectious RNAs (often 1 event per 10 cells, for smaller genomes most of transfected cells become infected). This makes the CLEVER method poorly suitable for generation of large infectious virus libraries and excludes its usage for studies of mutant viruses that harbor strongly attenuating mutations. Many of such mutations may reduce virus genome infectivity by 3-4 orders of magnitude; with current efficiencies the use of CLEVER approach may result in false conclusions (mutant viruses will be classified as non-viable while in reality they are just strongly attenuated).

Reviewer #2 (Public Review):

In this work, the authors describe engineering of sgRNAs that render Cas9 DNA binding controllable by a second RNA trigger. The authors introduce several iterations of their engineered sgRNAs, as well as a computational pipeline to identify designs for user-specified RNA triggers which offers a helpful alternative to purely rational design. Also included is an investigation of the fate of the engineered sgRNAs when introduced into cells, and the use of this information to inform installation of modified nucleotides to improve engineered sgRNA stability. Engineered sgRNAs are demonstrated to be activated by trigger RNAs in both cultured mammalian cells and zebrafish.

The conclusions made by the authors in this work are predominantly supported by the data provided. However, some claims are not consistent with the data shown and some of the figures would benefit from revision or further clarification.

Strengths:<br /> - The sgRNA engineering in this paper is performed and presented in a systematic and logical fashion. Inclusion of a computational method to predict iSBH-sgRNAs adds to the strength of the engineering.<br /> - Investigation into the cellular fate of the engineered sgRNAs and the use of this information to guide inclusion of chemically modified nucleotides is also a strength.<br /> - Demonstration of activity in both cultured mammalian cells and in zebrafish embryos increases the impact and utility of the technology reported in this work.

Weaknesses:<br /> - While the methods here represent an important step forward in advancing the technology, they still fall short of the dynamic range and selectivity likely required for robust activation by endogenous RNA.<br /> - While the iSBH-sgRNAs where the RNA trigger overlaps with the spacer appear to function robustly, the modular iSBH-sgRNAs seem to perform quite a bit less well. The authors state that modular iSBH-sgRNAs show better activity without increasing background when the SAM system is added, but this is not supported by the data shown in Figure 3D, where in 3 out of 4 cases CRISPR activation in the absence of the RNA trigger is substantially increased.<br /> - There is very little discussion of how the performance of the technology reported in this work compares to previous iterations of RNA-triggered CRISPR systems, of which there are many examples.

Reviewer #2 (Public Review):

The manuscript by Berrocal et al. asks if shared bursting kinetics, as observed for various developmental genes in animals, hint towards a shared molecular mechanism or result from natural selection favoring such a strategy. Transcription happens in bursts. While transcriptional output can be modulated by altering various properties of bursting, certain strategies are observed more widely.  As the authors noted, recent experimental studies have found that even-skipped enhancers control transcriptional output by changing burst frequency and amplitude while burst duration remains largely constant. The authors compared the kinetics of transcriptional bursting between endogenous and ectopic gene expression patterns. It is argued that since enhancers act under different regulatory inputs in ectopically expressed genes, adaptation would lead to diverse bursting strategies as compared to endogenous gene expression patterns. To achieve this goal, the authors generated ectopic even-skipped transcription patterns in fruit fly embryos. The key finding is that bursting strategies are similar in endogenous and ectopic even-skipped expression. According to the authors, the findings favor the presence of a unified molecular mechanism shaping even-skipped bursting strategies.  This is an important piece of work. Everything has been carried out in a systematic fashion. However, the key argument of the paper is not entirely convincing.

Reviewer #2 (Public Review):

Strengths include:

1) Given the variability in responses from ChatGPT, the author pooled two scores for each review and demonstrated significant correlation between these two iterations. He confirmed also reasonable scoring by manipulating reviews. Finally, he compared a small subset (7 papers) to human scorers and again demonstrated correlation with sentiment and politeness.

2) The figures are consistently well presented and informative. Figure 2C nicely plots the scores with example reviews. The supplementary data are also thoughtful and include combination of first/last author genders. It is interesting that first author female last author male has the lowest score.

3) A series of detailed analysis including breaking down reviews by subfield (interesting to see the wide range of reviewer sentiment/politeness scores in computational papers), institution, and author's name and inferred gender using Genderize. The author suggests that peer review to blind the reviewers to authors' gender may be helpful to mitigating the impoliteness seen.

Weaknesses include:

1) This study does not utilize any of the wide range of Natural Language Processing (NLP) sentiment analysis tools. While the author did have a small subset reviewed by human scorers, the paper would be strengthened by examining all the reviews systematically using some of the freely available tools (for example, many resources are available through Hugging Face [https://huggingface.co/blog/sentiment-analysis-python ]). These methods have been used in previous examinations of review text analysis (Luo et al. 2022. Quantitative Science Studies 2:1271-1295). Why use ChatGPT rather than these older validated methods? How does ChatGPT compare to these established methods? See also: colab.research.google.com/drive/1ZzEe1lqsZIwhiSv1IkMZdOtjPTSTlKwB?usp=sharing

2) The author's claim in the last paragraph that his study is proof of concept for NLP to analyze peer review fails to take into account the array of literature already done in this domain. The statement in the introduction that past reports (only three citations) have been limited to small dataset sizes is untrue (Ghosal et al. 2022. PLoS One 17:e0259238 contains over 1000 peer review documents, including sentiment analysis) and reflects a lack of review on the topic before examining this question.

3) The author acknowledges the limitation that only papers under neuroscience were evaluated. Why not scale this method up to other fields within Nature Communications? Cross-field analysis of the features of interest would examine if these biases are present in other domains.

Reviewer #2 (Public Review):

In this article, Bracey et al. provide insights into the factors contributing to the distinct arrangement observed in sub-membrane microtubules (MTs) within mouse β-cells of the pancreas. Specifically, they propose that in clonal mouse pancreatic β-cells (MIN6), the motor protein KIF5B plays a role in sliding existing MTs towards the cell periphery and aligning them with each other along the plasma membrane. Furthermore, similar to other physiological features of β-cells, this process of MTs sliding is enhanced by a high glucose stimulus. Because a precise alignment of MTs beneath the cell membrane in β-cells is crucial for the regulated secretion of pancreatic enzymes and hormones, KIF5B assumes a significant role in pancreatic activity, both in healthy conditions and during diseases.

The authors provide evidence in support of their model by demonstrating that the levels of KIF5B mRNA in MIN6 cells are higher compared to other known KIFs. They further show that when KIF5B is genetically silenced using two different shRNAs, the MT sliding becomes less efficient. Additionally, silencing of KIF5A in the same cells leads to a general reorganization of MTs throughout the cell. Specifically, while control cells exhibit a convoluted and non-radial arrangement of MTs near the cell membrane, KIF5B-depleted cells display a sparse and less dense sub-membrane array of MTs. Based on these findings, the Authors conclude that the loss of KIF5B strongly affects the localization of MTs to the periphery of the cell. Using a dominant-negative approach, the authors also demonstrate that KIF5B facilitates the sliding of MTs by binding to cargo MTs through the kinesin-1 tail binding domain. Additionally, they present evidence suggesting that KIF5B-mediated MT sliding is dependent on glucose, similar to the activity levels of kinesin-1, which increase in the presence of glucose. Notably, when the glucose concentrations in the culturing media of MIN6 cells are reduced from 20 mM to 5 mM, a significant decrease in MT sliding is observed.

Strengths: This study unveils a previously unexplained mechanism that regulates the specific rearrangement of MTs beneath the cell membrane in pancreatic β-cells. The findings of this research have implications and are of significant interest because the precise regulation of the MT array at the secretion zone plays a critical role in controlling pancreatic function in both healthy and diseased states. In general, the author's conclusions are substantiated by the provided data, and the study demonstrates the utilization of state-of-the-art methodologies including quantification techniques, and elegant dominant-negative experiments.

Weaknesses: A few relatively minor issues are present and related to data interpretation and the conclusions drawn in the study. Namely, some inconsistencies between what appears to be the overall and sub-membrane MT array in scramble vs. KIF5B-depleted cells, the lack of details about the sub-cellular localization of KIF5B in these cells and the physiological significance of the effect of glucose levels in beta-cells of the pancreas.

Reviewer #2 (Public Review):

In this manuscript, Yao et al. present a series of experiments aiming at generating a cellular atlas of the human hippocampus across aging, and how it may be affected by injury, in particular, stroke. Although the aim of the study is interesting and relevant for a larger audience, due to the ongoing controversy around the existence of adult hippocampal neurogenesis in humans, a number or technical weaknesses result in poor support for many of the conclusions made from the results of these experiments.

In particular, a recent meta-analysis of five previous studies applying similar techniques to human samples has identified different aspects of sample size as main determinants of the statistical power needed to make significant conclusions. Some of these aspects are the number of nuclei sequenced and subject stratification. These two aspects are of concern in Yao's study. First, the number of sequenced nuclei is lower than the calculated number of nuclei required for detecting rare cell types. However, Yao et al. report succeeding in detecting rare populations, including several types of neural stem cells in different proliferation states, which have been demonstrated to be extremely scarce by previous studies. It would be very interesting to read how the authors interpret these differences. Secondly, the number of donors included in some of the groups is extremely low (n=1) and the miscellaneous information provided about the donors is practically inexistent. As individual factors such as chronic conditions, medication, lifestyle parameters, etc... are considered determinant for the variability of adult hippocampal neurogenesis levels across individuals, this represents a series limitation of the current study. Overall, several technical weaknesses severely limit the relevance of this study and the ability of the authors to achieve their experimental aims.

Reviewer #2 (Public Review):

This proof-of-principle study lays important groundwork for future studies. Murphy et al. expressed ChrimsonR and GCaMP6s in retinal ganglion cells of a living macaque. They recorded calcium responses and stimulated individual cells, optically. Neurons targeted for stimulation were activated strongly whereas neighboring neurons were not.

The ability to record from neuronal populations while simultaneously stimulating a subset in a controlled way is a high priority for systems neuroscience, and this has been particularly challenging in primates. This study marks an important milestone in the journey towards this goal.

The ability to detect stimulation of single RGCs was presumably due to the smallness of the light spot and the sparsity of transduction. Can the authors comment on the importance of the latter factor for their results? Is it possible that the stimulation protocol activated neurons nearby the targeted neuron that did not express GCaMP? Is it possible that off-target neurons near the targeted neuron expressed GCaMP, and were activated, but too weakly to produce a detectable GCaMP signal? In general, simply knowing that off-target signals were undetectable is not enough; knowing something about the threshold for the detection of off-target signals under the conditions of this experiment is critical.

Minor comments:<br /> Did the lights used to stimulate and record from the retina excite RGCs via the normal light-sensing pathway? Were any such responses recorded? What was their magnitude?

The data presented attest to a lack of crosstalk between targeted and neighboring cells. It is therefore surprising that lines 69-72 are dedicated to methods for "reducing the crosstalk problem". More information should be provided regarding the magnitude of this problem under the current protocol/instrumentation and the techniques that were used to circumvent it to obtain the data presented.

Optical crosstalk could be spatial or spectral. Laying out this distinction plainly could help the reader understand the issues quickly. The Methods indicate that cells were chosen on the basis that they were > 20 µm from their nearest (well-labeled) neighbor to mitigate optical crosstalk, but the following sentence is about spectral overlap.

Figure 2 legend: "...even the nearby cell somas do not show significantly elevated response (p >> 0.05, unpaired t-test) than other cells at more distant locations." This sentence does not indicate how some cells were classified as "nearby" whereas others were classified as being "at more distant locations". Perhaps a linear regression would be more appropriate than an unpaired t-test here.

Line 56: "These recordings were... acquired earlier in the session where no stimulus was present." More information should be provided regarding the conditions under which this baseline was obtained. I assume that the ChrimsonR-activating light was off and the 488 nm-GCaMP excitation light was on, but this was not stated explicitly. Were any other lights on (e.g. room lights or cone-imaging lights)? If there was no spatial component to the baseline measurement, "where" should be "when".

Please add a scalebar to Figure 1a to facilitate comparison with Figure 2.

Lines 165-173: Was the 488 nm light static or 10 Hz-modulated? The text indicates that GCaMP was excited with a 488 nm light and data were acquired using a scanning light ophthalmoscope, but line 198 says that "the 488 nm imaging light provides a static stimulus".

A potential application of this technology is for the study of visually guided behavior in awake macaques. This is an exciting prospect. With that in mind, a useful contribution of this report would be a frank discussion of the hurdles that remain for such application (in addition to eye movements, which are already discussed).

Reviewer #2 (Public Review):

This study investigates how genes in the Gr28 family of gustatory receptors function in the taste system of Drosophila larvae. Gr28 genes are intriguing because they have been implicated in taste as well as other functions, such as sensing temperature and ultraviolet light. This study makes several new findings. First, the authors show that four Gr28 genes are expressed in putative taste neurons, and these neurons can be largely divided into subsets that express Gr28a versus Gr28bc. The authors then demonstrate that these two neuronal subsets drive opposing behaviors (attraction versus avoidance) when activated. The avoidance-promoting neurons respond to bitter compounds and are required for bitter avoidance, and Gr28bc and Gr28ba were specifically implicated in bitter detection in these cells. Together, these findings provide insight into the complexity of taste receptor expression and function in Drosophila, even within a single receptor subfamily.

The conclusions are well-supported by the experimental data. Strengths of the paper include the use of precise genetic tools, thorough analyses of expression patterns, carefully validated behavioral assays, and well-controlled functional imaging experiments. The role of Gr28bc neurons is more thoroughly explored than that of Gr28a neurons. However, a previous study from the same lab (Mishra et al., 2018) showed that Gr28a neurons detect RNA and ribose, which are attractive to larvae. Presumably, this is the attractive response that is being recapitulated upon artificial activation of Gr28a neurons.

I only have one technical concern: In Figure 2B, the authors do not show confirmation that using Gr66a-lexA driving lexAop-Gal80 eliminates Gal4-driven gene expression in the desired cells (cells co-expressing Gr66a and Gr28a). This is important for interpreting the behavioral experiment in order to demonstrate that the Gr28a cells mediating attraction are distinct from Gr66a/Gr28bc cells.

Reviewer #2 (Public Review):

Leeds et al. investigated the role of mechanical coupling in coordinating the growth kinetics of microtubules in kinetochore-fibers (k-fibers). The authors developed a dual optical-trap system to explore how constant load redistributed between a pair of microtubules depending on their growth state coordinates their growth.

• The main finding of the paper is that the duration and frequency of pausing events during individual microtubule growth are decreased when tension is applied at their tips via kinetochore particles coupled to optically trapped beads. However, the study does not offer any insight into the possible mechanism behind this dependency. For example, it is not clear whether this is a specific property of the kinetochore particles that were used in this experiment, whether it could be attributed to specific proteins in these particles, or if this could potentially be an inherent property of the microtubules themselves.

• The authors simulate the coordination between two microtubules and show that by using the parameters of pausing and variability in growth rates both measured experimentally they can explain coordination between two microtubules measured in their experiments. This is a convincing result, but k-fibers typically have many more microtubules, and it seems important to understand how the ability to coordinate growth by this mechanism scales with the number of microtubules. It is not obvious whether this mechanism could explain the coordination of more than two microtubules.

• The range of stiffnesses chosen to simulate the microtubule coupling allows linkers to stretch hundreds of nanometers linearly. However, most proteins including those at kinetochore must have finite size and therefore should behave more like worm-like chains rather than linear springs. This means they may appear soft for small elongations, but the force would increase rapidly once the length gets close to the contour length. How this more realistic description of mechanics might affect the conclusions of the work is not clear.

• The novel dual-bead assay is interesting. However, it only provides virtual coupling between two otherwise independently growing microtubules. Since the growth of one affects the growth of the other only via software, it is unclear whether the same insight can be gained from the single-bead setup, for example, by moving the bead at a constant speed and monitoring how microtubule growth adjusts to the fixed speed. The advantages of the double-bead setup could have been demonstrated better.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the goal of the authors is to understand the process of mature sprout formation from mini-sprouts to develop new blood vessels during angiogenesis. For this, they use their earlier experimental setup of engineered blood vessels in combination with a modified spatio-temporal model for Notch signalling. The authors first study the role of VEGF on Tip (Delta-rich) and Stalk (Notch-rich) patterning. The Tip cells are further examined for their space-time dynamics as Mini-sprouts and mature Sprouts. The Notch signalling model is later supplemented with a phenomenological _random uniform model_ for Sprout selection as a plausible mechanism for Sprout formation from Mini-Sprouts. Finally, the authors look into the role of fibronectin in the Sprout formation process. Overall, the authors propose that VEGF interacts with Notch signalling in blood vessels to generate spatially disordered and co-localized Tip cells. VEGF and fibronectin then provide external cues to dynamically modulate mature Sprout formation from Mini-Sprouts that could control the location and density of developing blood vessels with a process that is consistent with a Turing-like mechanism.

Strengths and Weaknesses:<br /> In this manuscript, work motivation, problem definition, experimental procedures, analysis techniques, mathematical methods (including the parameters), and findings are all presented quite clearly. Moreover, the authors carefully indicate whenever they make any assumptions and do not mix unproven hypothesis with deduced or known facts. The experimental techniques and most of the mathematical methods used in this paper are borrowed from the earlier works of the corresponding authors and thus are not completely novel. However, the use of these ideas to provide a simple elucidation of the role of VEGF and fibronectin in Sprout formation, in an otherwise complex system, is very interesting and useful. Some of the data analysis methods presented in the paper - (i) quantification of Tip spatial patterns (Fig. 3) and (ii) Sprout temporal dynamics using Sankey diagram (Fig. 4) - seem quite novel to me in the context of Notch signalling literature. Similarly, the authors also provide a new mechanism (VEGF) to obtain disordered Delta-Notch patterning without explicitly including _noise_ in the system (Fig. 2 and Fig. S1). The authors also systematically quantify the statistics of spacing between the Sprouts and show that the Sprouts have a tendency to be away from each other, something that they could also partially recapitulate by additionally including a novel _random uniform model_ for Sprout selection (Fig. 5). Although the association between fibronectin and angiogenesis is known in the literature, in this manuscript, the authors could clearly demonstrate that fibronectin is present in high and low levels, respectively, around Sprouts and Mini-sprouts (Fig. 6). A combination of these findings could then motivate the authors to hypothesize, as mentioned above, a Turing-like mechanism for Sprout formation, something that I find interesting.

Although I find the relative simplicity of the experimental system and theoretical model and the clear findings they generate appealing, some aspects raise a few questions. The authors experimentally find 20 +- 0.08 percent of Tip cells in the model blood-vessels that is consistent with the salt-and-pepper pattern seen in Notch signalling model (~25 %). However, it is not clear to me if the reverse is true, i.e., 25% of Tip cells automatically imply a salt-and-pepper pattern - the authors do not seem to provide direct experimental evidence. Furthermore, the authors use their Notch signalling model on a regular hexagonal lattice, but there is a large variability in the cell sizes (Fig. 3) in the experimental system. Since it is observed in the literature that signalling depends on the contact area between the neighbouring cells, it is not clear how that would affect the findings presented in this paper. Similarly, since some of the cells are quite small compared to the others, I worry about how appropriate it is to express the distance between the Tip cells in terms of _cell numbers_ (Fig. 3). Regarding Sprout classification, as per Table 1, a bridge of two cells is formed as per early-stage-I mechanism for Sprout. On the other hand, the entire data interpretation of experiments seems to be based on early Stage II and matured stage in that same table (also Figs. 3 and 4) in which only one Tip cell seems to be counted per mature Sprout. However, if some Sprouts are formed via early stage-I mechanism, a projection in 2D for analysis would give a count of __two__ adjacent Tip cells, but corresponding to a __single__ Sprout. It could be possible that the presence of such two-cell Sprouts affects the statistics of inter-Sprout distances (Fig. 5). Finally, I find the proposed mechanism of Sprout formation dynamics to be somewhat unsatisfactory. Other than the experimental evidence regarding the spacing of Sprouts and the fibronectin levels around Sprouts and Mini-sprouts (Figs. 4 and 5), there is very little evidence to support the hypothesis about a Turing-like mechanism for Sprouting. Moreover, it seems to me that Turing patterns can appear in a wide variety of settings and could be applied to the current problem in an abstract manner without making any meaningful connections with the system variables. Also, from a modeling point of view, cell migration and mechanics, are expected to take a major part in Sprout formation, while cell division and inclusion would most likely influence Tip-Stalk cell formation. However, it seems that in the present work, these effects are coarse-grained into Notch signalling parameters and the Sprout selection model, thus making any experimental connection quite vague.

Overall Assessment

I feel that the authors, on the whole, do achieve their main goals. Although I have a few concerns that I have raised above, overall, I find the work presented in this manuscript to be a solid addition to the broad field of collective cell dynamics. The authors use well established experimental and mathematical methods while adding a few novel analysis techniques and modeling ideas to provide a compelling, albeit incomplete, picture of Sprout formation during angiogenesis. While the direct application of this work in the context of angiogenesis is obvious, the broad set of ideas and techniques (discussed above) in this work would also be useful to researchers who work on Notch signalling in morphogenesis, collective cell migration, and epithelial-mesenchymal-transition.

Reviewer #2 (Public Review):

It is well known that human and simian immunodeficiency viruses (HIV and SIV, respectively) evolved numerous mechanisms to compromise effective immune responses but the underlying mechanisms remain incompletely understood. Here, Yamamoto and Matano examined the humoral immune response in a large number of rhesus macaques infected with the difficult-to-neutralize SIVmac239 strain. They identified a subgroup of animals that showed significant neutralizing Ab responses. Sequence analyses revealed that in most of these animals (7/9) but only a minority in the control group (2/19) SIVmac variants containing a CD8+ T-cell escape mutation of G63E/R in the viral Nef gene emerged. They further show that this change attenuates the ability of Nef to stimulate PI3K/Akt/mTORC2 signaling. The authors propose that this induction of SIVmac239 nAb induction is reciprocal to antibody dysregulation caused by a previously identified human PI3K gain-of-function (Ref). Altogether, the results suggest that PI3K signaling plays a key role in B-cell maturation and generation of effective nAb responses.

Strengths of the study are that the authors analyzed a large number of SIVmac-infected macaques to unravel the biological significance of the known effect of the interaction of Nef with PI3K/Akt/mTORC2 signaling. This is interesting and may provide a novel means to improve humoral immune responses to HIV. Weaknesses are that only G63E and not G63R that also emerged in most animals was examined in most functional assays. Some effects of the G63E mutation seem modest and comparison to a grossly nef-defective SIVmac construct would be desirable to better assess to impact of the mutation of Nef-mediated stimulation of PI3K. While the impact of this Nef mutations on PI3K and the association with improved nAb responses is largely convincing, the results on the potential impact of soluble Nef on neighboring B cells is much less clear. SIVmac239 infects and manipulates helper CD4 T cells and these are essential for the activation and differentiation of B cells into antibody-producing plasma cells and effective humoral immune responses. Without additional functional evidence that Nef indeed specifically targets and manipulated B cells these results and conclusions should be made with much greater caution. Finally, the presentation of the results and conclusions is partly very convoluted and difficult to comprehend. Editing to improve clarity is highly recommended.

Reviewer #2 (Public Review):

Summary<br /> The authors seek to characterize the role of splicing factor SRSF1 during spermatogenesis. Using a conditional deletion of Srsf1 in germ cells, they find that SRSF1 is required for male fertility. Via immunostaining and RNA-seq analysis of the Srsf1 conditional knockout (cKO) testes, combined with SRSF1 CLIP-seq and IP-MS data from the testis, they ultimately conclude that Srsf1 is required for spermatogonial stem cell (SSC) homing and self-renewal due to alternative splicing of Tial1.

Strengths<br /> The overall methods and results are robust. The histological analysis of the Srsf1 cKO traces the origins of the fertility defect to the postnatal testis, and the authors have generated interesting datasets characterizing SRSF1's RNA targets and interacting proteins specifically in the testis.

Ultimately, the authors have shown that SRSF1's effects on alternative splicing are required to establish spermatogenesis. In the absence of Srsf1, the postnatal gonocytes/nascent spermatogonia do not properly relocate from the seminiferous tubules' lumen to basement membrane, and consequently, never initiate spermatogenesis. I believe this relocation event is what the authors are referring to as "SSC homing".

Weaknesses<br /> I do not think there is enough evidence to support two major conclusions. First, the authors conclude that SRSF1 is required for "SSC self-renewal." Given the defect in nascent spermatogonial development, it is not evident to me that SSCs actually form in the Srsf1 cKO. Second, the authors conclude that SRSF1 controls alternative splicing of Tial1 to "implement SSC homing and self-renewal." I'm unsure as to the basis for TIAL1's role in "SSC homing and self-renewal," particularly as the only reference provided about Tial1's effects on the germ line shows that germ cells are completely lost during embryonic gestation. As a result, it's ultimately unclear to me how SRSF1 mechanistically regulates the relocation of gonocytes/nascent spermatogonia to the basement membrane.

Alternative splicing is quite pronounced in the testis relative to other tissues. The authors have presented interesting work that shows that alternative splicing is required in the testicular germ line for the establishment of spermatogenesis.

Reviewer #2 (Public Review):

Relative simplicity and genetic accessibility of the fly brain make it a premier model system for studying the function of genes linked to various diseases in humans. Here, Pan et al. show that human UBA5, whose mutations cause developmental and epileptic encephalopathy, can functionally replace the fly homolog Uba5. The authors then systematically express in flies the different versions of the gene carrying clinically relevant SNPs and perform extensive phenotypic characterization such as survival rate, developmental timing, lifespan, locomotor and seizure activity, as well as in vitro biochemical characterization (stability, ATP binding, UFM-1 activation) of the corresponding recombinant proteins. The biochemical effects are well predicted by (or at least consistent with) the location of affected amino acids in the previously described Uba5 protein structure. Most strikingly, the severity of biochemical defects appears to closely track the severity of phenotypic defects observed in vivo in flies. While the paper does not provide many novel insights into the function of Uba5, it convincingly establishes the fly nervous system as a powerful model for future mechanistic studies.

One potential limitation is the design of the expression system in this work. Even though the authors state that "human cDNA is expressed under the control of the endogenous Uba5 enhancer and promoter", it is in fact the Gal4 gene that is expressed from the endogenous locus, meaning that the cDNA expression level would inevitably be amplified in comparison. The fact that different effects were observed when some experiments were performed at different temperatures (18 vs. 25) is also consistent with this. While I do not think this caveat weakens the conclusions of this paper, it may impact the interpretation of future experiments that use these tools, and thus should be clearly discussed in the paper. Especially considering the authors argue that most disease variants of UBA5 are partial loss-of-functions, the amplification effect could potentially mask the phenotypes of milder hypomorphic alleles. If the authors could also show that the T2A-Gal4 expression pattern in the brain matches well with that of endogenous RNA or protein (e.g. using HCR-FISH or antibody), it would help to alleviate this concern.

Reviewer #2 (Public Review):

This study provides an unbiased characterization of the cardiac proteome in the setting of intermittent fasting. The findings constitute a resource of quantitative proteomic data that sheds light on changes in cardiac function due to diet and that may be used in the future by other investigators. There are a number of key missing details that limit interpretation or present opportunities to strengthen the study. For example, the authors find that apolipoproteins are altered with fasting but it is not clear whether this is a contribution of myocardial tissue changes or systemic effects spilling into blood in cardiac tissues. Some statements in the text like "Approximately one-third of the differentially expressed proteins in IF groups compared to AL were enzymes with catalytic activity involved in energy homeostasis pathways" do not appear to be supported by data. It is not clear how the list of Kinases were generated for Figure 1B. Changes in chromatin or gene expression are not measured so the conclusion that EOD led to 'epigenetic changes' relative to IF16 is not well supported. There are also a number of areas where the text is vague. For example, it is not clear what is meant by 'trend shift' when discussing EOD results and Figure 3 generally could use additional information to better understands the figures. An interesting finding is that the IF16 groups showed cardiac hypertrophy (SFig 11b). This is potentially a novel finding and the text should elaborate more on this phenomenon.

Reviewer #2 (Public Review):

In their manuscript entitled "Transcriptional immune suppression and upregulation of double stranded DNA damage and repair repertoires in ecDNA-containing tumors" Lin et al. describe an important study on the transcriptional programs associated with the presence of extrachromosomal DNA in a cohort of 870 cancers of different origin. The authors find that compared to cancers lacking such amplifications, ecDNA+ cancers express higher levels of DNA damage repair-associated genes, but lower levels of immune-related gene programs.

This work is very timely and its findings have the potential to be very impactful, as the transcriptional context differences between ecDNA+ and ecDNA- cancers are currently largely unknown. The observation that immune programs are downregulated in ecDNA+ cancers may initiate new preclinical and translational studies that impact the way ecDNA+ cancers are treated in the future. Thus, this study has important theoretical implications that have the potential to substantially advance our understanding of ecDNA+ cancers.

Strengths<br /> The authors provide compelling evidence for their conclusions based on large patient datasets. The methods they used and analyses are rigorous.

Weaknesses<br /> The biological interpretation of the data remains observational. The direct implication of these genes in ecDNA(+) tumors is not tested experimentally.

Reviewer #2 (Public Review):

Here, Chitraju et al have studied the phenotype of mice with an adipocyte-specific deletion of the diglycerol acyltransferases DGAT1 and DGAT2, the two enzymes catalyzing the last step in triglyceride biosynthesis. These mice display reduced WAT TG stores but contrary to their expectations, the TG loss in WAT is not complete and the mice are resistant to a high-fat diet intervention and display a metabolically healthier profile compared to control littermates. The mechanisms underlying this are not entirely clear, but the double knockout (DKO) animals have increased EE and a lower RQ suggesting that enhanced FA oxidation and WAT "browning" may be involved. Moreover, both adiponectin and leptin are expressed in WAT and are detectable in circulation. The authors propose that "the capacity to store energy in adipocytes is somehow sensed and triggers thermogenesis in adipose tissue. This phenotype likely requires an intact adipocyte endocrine system...." Overall, I find this to be an interesting notion.

Reviewer #2 (Public Review):

Acknowledging practical difficulties in teasing out the principles behind animal locomotion from the body's functions and survival needs, the authors embark on a computational experiment to replay the "tape of life." Specifically, the chief objective of the study was to explore the necessity of symmetry and modularity for better-directed locomotion on the ground.

Towards this important goal, the authors put forward a comprehensive computational study using physics-based simulations of 3D voxel-based robots. Such a simulation environment allows one to capture salient dynamics behind locomotion, including interactions with the environment. The authors undertake simulations for three different gravitational environments, water, Earth, and Mars. The work has several methodological strengths, with respect to the ingenuity of the approach and the elegance of the analysis; I was particularly intrigued by the use of graph theory in the context of modularity. Results point to a complex, rich role of modularity and symmetry in locomotion, modulated by the gravitational environment.

The association between "locomotion ability" and average speed is, in my view, tenuous, whereby locomotion is a complex phenomenon that should be assessed across a range of intertwined dynamic metrics that include, for example, stability with respect to external perturbations and energy efficiency. I also am not fully convinced of i) the adequacy of the spatial resolution, whereby I failed to see a compelling argument regarding the completeness of 64 voxels; ii) the realism of the oscillatory patterns, whereby all the voxels are set to oscillate at the same, constant, frequency of 2Hz; and iii) the accuracy of simulations in water where added mass effects seem to be neglected. Overall, dynamics and control aspects could be improved in both the methods and the interpretation of the results. Finally, I believe that a stronger connection between the hypotheses of the study and the literature (in animal or robot locomotion) would help frame the narrative better. I would be particularly curious to see some tie with human bipedal locomotion.

The work bears important implications in the study of locomotion, shedding light on the role of modularity and symmetry, beyond what one could gather from mere observations. Not only do I expect these new insights to stimulate further research in the area of locomotion, but also I envision other communities embracing a similar computational approach to address related questions in life sciences and robotics.

Reviewer #2 (Public Review):

In this study, Tomasi et al identify a series of tRNA modifying enzymes from Mtb, show their function in the relevant tRNA modifications and by using at least one deleted strain for MnmA, they show the relevance of tRNA modification in intra-host survival and postulate their potential role in pathogenesis.

Conceptually it is a wonderful study, given that tRNA modifications are so fundamental to all life forms, showing their role in Mtb growth in the host is significant. However, the authors have not thoroughly analyzed the phenotype. The growth defect aspect or impact on pathogenesis needs to be adequately addressed.

- The authors show that ΔmnmA grows equally well in the in vitro cultures as the WT. However, they show attenuated growth in the macrophages. Is it because Glu1_TTC and Gln1-TTG tRNAs are not the preferred tRNAs for incorporation of Glu and Gln, respectively? And for some reason, they get preferred over the alternate tRNAs during infection? What dictates this selectivity?

- As such the growth defect shown in macrophages would be more convincing if the authors also show the phenotype of complementation with WT mnmA.

An important consideration here is the universal nature of these modifications across the life forms. Any strategy to utilize these enzymes as the potential therapeutic candidate would have to factor in this important aspect.

Reviewer #2 (Public Review):

Summary:<br /> Mouse models are widely used to determine key molecular mechanisms of atherosclerosis, the underlying pathology that leads to coronary artery disease. The authors use various systems biology approaches, namely co-expression and Bayesian Network analysis, as well as key driver analysis, to identify co-regulated genes and pathways involved in human and mouse atherosclerosis in artery and liver tissues. They identify species-specific and tissue-specific pathways enriched for the genetic association signals obtained in genome-wide association studies of human and mouse cohorts.

Strengths:<br /> The manuscript is well executed with appropriate analysis methods. It also provides a compelling series of results regarding mouse and human atherosclerosis.

Weaknesses:<br /> The manuscript has several weaknesses that should be acknowledged in the discussion. First, there are numerous models of mouse atherosclerosis; however, the HMDP atherosclerosis study uses only one model of mouse atherosclerosis, namely hyperlipidemic mice, due to the transgenic expression of human apolipoprotein E-Leiden (APOE-Leiden) and human cholesteryl ester transfer protein (CETP). Therefore, when drawing general conclusions about mouse pathways not being identified in humans, caution is warranted. Other models of mouse atherosclerosis may be able to capture different aspects of human atherosclerosis. Second, the mouse aorta tissue is atherosclerotic, whereas the atherosclerosis status of the GTEX aorta tissues is not known. Therefore, it is possible that some of the human or mouse-specific gene modules/pathways may be due to the difference in the disease status of the tissues from which the gene expression is obtained. Third, it is unclear how the sex of the mice (all female in the HMDP atherosclerosis study and all male in the baseline HMDP study) and the sex of the human donors affected the results. Did the authors regress out the influence of sex on gene expression in the human data before performing the co-expression and preservation studies? If not, this should be acknowledged. Fourth, some of the results are unexpected, and these should be discussed. For example, the authors identify that the leukocyte transendothelial migration pathway and PDGF signaling pathway are human-specific in their vascular tissue analysis. These pathways have been extensively described in mouse studies. Why do the authors think they identified these pathways as human-specific? Similarly, the authors identified gluconeogenesis and branched-chain amino acid catabolism as human and mouse-shared modules in the vascular tissue. Is there evidence of the involvement of these pathways in atherosclerosis in vascular cells?

Overall, acknowledging these drawbacks and adding points to the discussion will strengthen the manuscript.

Reviewer #2 (Public Review):

The manuscript by Nishikawa et al. addresses time-dependent changes in the electron transfer energetics in the photosynthetic reaction center from Blastochloris viridis, whose time-dependent structural changes upon light illumination were recently demonstrated by time-resolved serial femtosecond crystallography (SFX) using X-ray free-electron laser (XFEL) (Dods et al., Nature, 2021). Based on the redox potential Em values of bacteriopheophytin in the electron transfer active branch (BL) by solving the linear Poisson-Boltzmann equation, the authors found that Em(HL) values in the charge-separated 5-ps structure obtained by XFEL are not clearly changed, suggesting that the P+HL- state is not stabilized owing to protein reorganization. Furthermore, chlorin ring deformation upon HL- formation, which was expected from their QM/MM calculation, is not recognized in the 5-ps XFEL structure. Then the authors concluded that the structural changes in the XFEL structures are not related to the actual time course of charge separation. They argued that their calculated changes in Em and chlorin ring deformations using the XEFL structures may reflect the experimental errors rather than the real structural changes; they mentioned this problem is due to the fact that the XFEL structures were obtained at not high resolutions (mostly at 2.8 Å). I consider that their systematic calculations may suggest a useful theoretical interpretation of the XFEL study. However, the present manuscript insists as a whole negatively that the experimental errors may hamper to provide the actual structural changes relevant to the electron transfer events.

Reviewer #2 (Public Review):

This manuscript explores the interplay between Legionella Dot/Icm effectors that modulate ubiquitination of the host GTPase Rab10. Rab10 undergoes phosphoribosyl-ubiquitination (PR-Ub) by the SidE family of effectors which is required for its recruitment to the Legionella containing vacuole (LCV). Through a series of elegant experiments using effector gene knockouts, co-transfection studies and careful biochemistry, Kubori et al further demonstrate that:

1. The SidC family member SdcB contributes to the polyubiquitination (poly-Ub) of Rab10 and its retention at the LCV membrane.<br /> 2. The transglutaminase effector, MavC acts as an inhibitor of SdcB by crosslinking ubiquitin at Gln41 to lysine residues in SdcB.

Some further comments and questions are provided below.

1. From the data in Figure 1, it appears that the PR-Ub of Rab10 precedes and in fact is a prerequisite for poly-Ub of Rab10. The authors imply this but there's no explicit statement but isn't this the case?<br /> 2. The complex interplay of Legionella effectors and their meta-effectors targeting a single host protein (as shown previously for Rab1) suggests the timing and duration of Rab10 activity on the LCV is tightly regulated. How does the association of Rab10 with the LCV early during infection and then its loss from the LCV at later time points impact LCV biogenesis or stability? This could be clearer in the manuscript and the summary figure does not illustrate this aspect.<br /> 3. How do the activities of the SidE and SidC effectors influence the amount of active Rab10 on the LCV (not just its localisation and ubiquitination)<br /> 4. What is the fate of PR-Ub and then poly-Ub Rab10? How does poly-Ub of Rab10 result in its persistence at the LCV membrane rather than its degradation by the proteosome?<br /> 5. Mutation of Lys518, the amino acid in SdcB identified by mass spec as modified by MavC, did not abrogate SdcB Ub-crosslinking, which leaves open the question of how MavC does inhibit SdcB. Is there any evidence of MavC mediated modification to the active site of SdcB?<br /> 6. I found it difficult to understand the role of the ubiquitin glycine residues and the transglutaminase activity of MavC on the inhibition of SdcB function. Is structural modelling using Alphafold for example helpful to explain this?<br /> 7. Are the lys mutants of SdbB still active in poly-Ub of Rab10?

Reviewer #2 (Public Review):

Cho and Hetzer provide evidence that nuclear pore complexes (NPCs) are "trimmed" by caspases as a key element of muscle (and other) differentiation programs. Overall, the data are of high quality and are well presented. There is an interesting mechanism demonstrated whereby nuclear and cytosolically-oriented nups are specifically degraded from the NPC (fragments are sometimes associated with the NPCs), which leads to a specific inhibition of nuclear export. A highlight is a quantitative proteomic analysis of nuclear fractions that nicely demonstrates the change in the nuclear proteome upon NPC trimming, which includes elevated levels of many NES-containing factors. An important control is that these nuclear proteome changes don't occur when caspases are inhibited. These data are valuable although they fall short in demonstrating that NPC trimming is actually required for the execution of the differentiation program. It is recognized, however, that editing several nup genes at several sites to prevent caspase recognition would be extremely challenging and unfeasible, thus ultimately this does not detract from the significance of the findings. Indeed, there is a new broadly impactful concept being introduced - that caspases need not be destructive but they can be productively utilized to contribute to cell fate decisions.

Reviewer #2 (Public Review):

While the question of 'are AlphaFold-predicted structures useful for drug design' has largely seen comparisons of AF versus experimental protein structures, this paper takes a less explored (but perhaps more practically important) angle of 'are AlphaFold-predicted structures any better than the previous generation of homology modeling tools' to the protein-ligand (rigid) docking problem. The conclusions of this work will be of largest interest to the audience less familiar with the precision required for successful rigid docking, while the expert crowd might find them obvious, yet a good summary of results previously shown in the literature. Further work, understanding the structural objectives/metrics that should be placed on future AlphaFold-like models for better pose prediction performance, would greatly expand the practicality of the observations made here.

The main conclusion of the paper, that structural accuracy (expressed as RMSD) of the protein model is not a good predictor of the accuracy the model will show in rigid docking protein-ligand pose prediction, is a good reminder of the well-appreciated need for high-quality side chain placements in docking. The expected phenomenon of AlphaFold predicting 'more apo-like structures' is often discussed in the field, and readers should be cautious about drawing conclusions from the rigid (rather than flexible, as in some previous works) docking done here.

The authors have very clearly communicated that the use of AlphaFold-generated structures in traditional docking might not be a good idea, and motivated that the time of a molecular designer might be better spent preparing a high-quality homology model. The visual presentation of the conclusions is very clear but might leave the reader wanting a more in-depth discussion of which structural elements of the AF models lead to bad docking outcomes. For example, Fig. 3 presents an example of a very accurate AlphaFold prediction leading to the ligand being docked completely outside of the binding pocket. Close inspection of the Figure suggests a clash of the ligand with the slightly displaced tryptophan residue in the AF model that might be to blame, as can be confirmed by comparison of the model and PDB structure by the reader themselves but has not been discussed by the authors. Only a few examples of the systems used are shown even visually, leaving the reader unable to study more interesting cases in depth without re-doing the work themselves.

The authors acknowledged that several recent studies exist in this space. They point out two advancements made in their work, worthy of further review. Similarly, it's important to evaluate the novelty of this work's claims vs previously available results, and the diversity of information made available to the reader.

"First, we use structural models generated without any use of known structures of the target protein. For machine learning methods, this requires ensuring that no structure of the target protein was used to train the method." This is done by limiting the scope of the work to GPCRs whose structures became available only after the training date of AlphaFold (April 30, 2018), as well as not using templates available after that date during prediction. The use of a time limit seems less preferable than the approach taken in Ref. 1 of discarding templates above a sequence identity cutoff. On the other hand, the 'ablation test' performed in Ref. 2 showed no loss in accuracy when no templates were used at all. Authors should discuss in more detail whether these modeling choices could change anything in their conclusions and why they made their choices compared to those in previous work.

"Second, we perform a systematic comparison that takes into account the variation between experimentally determined structures of the same protein when bound to different ligands." Cross-docking is indeed a more appropriate comparison than self-docking (as done in previous works), and the observation that the accuracy of AF models is similar to that between different holo structures of the same protein is interesting. Previous literature on cross-docking should however be discussed, and the well-known conclusions from it that small variations in side-chain positions, in otherwise highly similar structures, can lead to large changes in docked poses. It is important to realize that AlphaFold models are 'just another structure' - if previous literature is sufficient to show the sensitivity of rigid docking, doing it again on AF structures does not add to our understanding. Further, Ref. 3 might have already addressed the question of correlation between binding site RMSD and docking pose prediction accuracy - see e.g. Supplementary Figure 3 there (also Figure S15 in Ref. 2).

Further, the authors should discuss the commonly brought up problem of AlphaFold generating 'more apo-like structures' - are the models used here actually 'holo-like' because of the low RMSDs? (what RMSD differences are to be expected between apo and holo structures of these systems?) How are the volumes of the pockets affected? The position on this problem taken by previous works is worth mentioning - "much higher rmsd values are found when using the AF2 models (...), which reflect the difficulties in performing docking into apo-like structures" in Ref. 1 and "computational model structures were predicted without consideration of binding ligands and resulted in apo structures" in Ref. 2.

Because of this 'apo problem', Ref. 2 assumed that rigid docking (as done here) would not succeed and used flexible docking where "two sidechains at the binding site were set to be flexible". In fact, the reader of this new paper will be left to wonder if it is not simply presenting a subset of the results already seen in Ref. 2, where "the success ratios dropped significantly for them because misoriented sidechains prevented a ligand from docking (Figure S14)". While this conclusion is not made as clear in Ref. 2 as it is here, a comparison of Figures 4 and S14 there will lead the reader to the same conclusion, and more -- that flexible docking meaningfully improves the performance of AF models, and more so than homology models.

Finally, certain data analyses present in previous works but not here should be necessary to make this work more informative to the readers:<br /> a) Consideration of multiple top poses, e.g., in Ref. 2, Figures 4 and S14 mentioned before, comparison of success rates in top 1 and top 3 docked poses add much context.<br /> b) Notes on the structural features preventing successful docking, see e.g., in Ref. 1, Table 2 or in Ref. 4, Tables 2 and 4.

This work has the potential to become an important piece of the puzzle, if deeper insights into the reasons for AF model failures are drawn by the authors. These could include a discussion of the problematic structural elements (clashes of side chain with ligands, missing interactions/waters, etc.), potential solutions with some preliminary data (flexible docking, softening interactions, etc.), or proposals for metrics better than RMSD to score the soundness of pockets generated by AF for docking.

References:<br /> 1. Díaz-Rovira, A. M., Martín, H., Beuming, T., Díaz, L., Guallar, V., & Ray, S. S. (2023). Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures. Journal of Chemical Information and Modeling, 63(6), 1668-1674. https://doi.org/10.1021/acs.jcim.2c01270<br /> 2. Heo, L., & Feig, M. (2022). Multi-state modeling of G-protein coupled receptors at experimental accuracy. Proteins: Structure, Function, and Bioinformatics, 90(11), 1873-1885. https://doi.org/10.1002/prot.26382<br /> 3. Beuming, T., & Sherman, W. (2012). Current assessment of docking into GPCR crystal structures and homology models: Successes, challenges, and guidelines. Journal of Chemical Information and Modeling, 52(12), 3263-3277. https://doi.org/10.1021/ci300411b<br /> 4. Scardino, V., Di Filippo, J. I., & Cavasotto, C. (2022). How good are AlphaFold models for docking-based virtual screening? [Preprint]. Chemistry. https://doi.org/10.26434/chemrxiv-2022-sgj8c

Reviewer #2 (Public Review):

In this manuscript, the authors attempt to examine how the temporal expression of the lin-4 microRNA is transcriptionally regulated. However, the experimental support for some claims is incomplete. The authors repeatedly use the ju1121(G247R) mutation of myrf-1, but more information is required to evaluate their claim that this mutation "abolishes its DNA binding capability but also negatively interferes with its close paralogue MYRF-2". Additionally, in the lin-4 scarlet endogenous transcriptional reporter, the lin-4 sequence is removed. Since lin-4 has been reported to autoregulate, it seems possible that the removal of lin-4 coding sequence could influence reporter expression. Further, concrete evidence for direct lin-4 regulation by MYRF-1 is lacking, as the approaches used are indirect and not standard in the field. Overall, while the aims of the work are mostly achieved, data regarding the direct regulation of lin-4 by MYRF-1 and placing the work into the context of previous related reports is lacking. Because of its very specific focus, this paper reports useful findings on how a single transcription factor family might control the expression of a microRNA.

Reviewer #2 (Public Review):

Summary of major findings:<br /> The manuscript "The Plasmodium falciparum artemisinin resistance-associated protein Kelch 13 is required for formation of normal cytostomes" authored by Tutor et al. provides evidence that Kelch13 is necessary for the formation and maintenance of cytostomes. The group provides compelling evidence using multiple state-of-the-art microscopy imaging techniques to demonstrate that when Kelch13 is mislocalized to the nucleus, cytostomes are decreased, cytostome morphology is aberrant, and there are decreased levels of heme within the parasite.

Impact of the study:<br /> Mutations in Kelch13 have been associated with artemisinin resistance. The biological function of Kelch13 has been a question of great interest. Kelch13 was shown to associate with proteins in the endocytic machinery although not with clathrin. It was previously shown that Kelch13 mutants have decreased levels of hemoglobin digestion-derived peptides, decreased Kelch13 protein (although levels are not decreased at all asexual stages), and decreased heme. Here, the authors show that when Kelch13 is mislocalized, there are decreased numbers of properly-formed cytostomes that lead to decreased heme within parasites. Although not formally demonstrated, it is thus possible that there is decreased subsequent heme-mediated activation of artemisinin, which would explain the connection between Kelch13 and artemisinin resistance.

Reviewer #2 (Public Review):

The authors attempt to address a long-standing controversy in the study of the neural correlates of visual awareness, namely whether neurons in prefrontal cortex are necessarily involved in conscious perception. Several leading theories of consciousness propose a necessary role for (at least some sub-regions of) PFC in basic perceptual awareness (e.g., global neuronal workspace theory, higher order theories), while several other leading theories posit that much of the previously reported PFC contributions to perceptual awareness may have been confounded by task-based cognition that co-varied between the aware and unaware reports (e.g., recurrent processing theory, integrated information theory). By employing intracranial EEG in human patients and a threshold detection task on low-contrast visual stimuli, the authors assessed the timing and location of neural populations in PFC that are differentially activated by stimuli that are consciously perceived vs. not perceived. Overall, the reported results support the view that certain regions of PFC do contribute to visual awareness, but at time-points earlier than traditionally predicted by GNWT and HOTs.

Major strengths of this paper include the straightforward visual threshold detection task including the careful calibration of the stimuli and the separate set of healthy control subjects used for validation of the behavioral and eye tracking results, the high quality of the neural data in six epilepsy patients, the clear patterns of differential high gamma activity and temporal generalization of decoding for seen versus unseen stimuli, and the authors' interpretation of these results within the larger research literature on this topic. This study appears to have been carefully conducted, the data were analyzed appropriately, and the overall conclusions seem warranted given the main patterns of results.

Weaknesses include the saccadic reaction time results and the potential flaws in the design of the reporting task. This is not a "no report" paradigm, rather, it's a paradigm aimed at balancing the post-perceptual cognitive and motor requirements between the seen and unseen trials. On each trial, subjects/patients either perceived the stimulus or not, and had to briefly maintain this "yes/no" judgment until a fixation cross changed color, and the color change indicated how to respond (saccade to the left or right). Differences in saccadic RTs (measured from the time of the fixation color change to moving the eyes to the left or right response square) were evident between the seen and unseen trials (faster for seen). If the authors' design achieved what they claim on page 3, "the report behaviors were matched between the two awareness states ", then shouldn't we expect no differences in saccadic RTs between the aware and unaware conditions? The fact that there were such differences may indicate differences in post-perceptual cognition during the time between the stimulus and the response cue. Alternatively, the RT difference could reflect task-strategies used by subjects/patients to remember the response mapping rules between the perception and the color cue (e.g., if the YES+GREEN=RIGHT and YES+RED=LEFT rules were held in memory, while the NO mappings were inferred secondarily rather than being actively held in memory). This saccadic RT result should be better explained in the context of the goals of this particular reporting-task.

Nevertheless, the current results do help advance our understanding of the contribution of PFC to visual awareness. These results, when situated within the larger context of the rapidly developing literature on this topic (using "no report" paradigms), e.g., the recent studies by Vishne et al. (2023) Cell Reports and the Cogitate consortium (2023) bioRxiv, provide converging evidence that some sub-regions of PFC contribute to visual awareness, but at latencies earlier than originally predicted by proponents of, especially, global neuronal workspace theory.

Reviewer #2 (Public Review):

The manuscript by Ramesh et al builds upon prior studies from the Sigrist group to examine synergistic interactions between the Spinophilin (Spn) and Syd-1 synaptic proteins and their role in regulating presynaptic homeostatic plasticity at Drosophila larval NMJs and adult olfactory memory in the Mushroom Body (MB). The authors show synergistic interactions between the two proteins in these processes, where late PHP and long-term memory are abolished in Spn mutants, but restored upon reduction of Syd-1 function in the mutants. The authors go on to show that Spn appears to act in PHP by regulating a late stage in AZ remodeling and longer-term increases in the readily releasable SV pool by controlling actin polymerization/dynamics through the Mical protein. Although key aspects of the overall bigger picture have been published before (Mical's role in PHP, antagonism between Spn and Syd-1 in AZ development, AZ remodeling in MB-dependent memory), the current paper ties together many of these observations into a bigger picture of how PHP plasticity at the NMJ is established and provides support for a role for PHP-required proteins in promoting long-term memory in the adult MB through effects on AZ structure and AZ protein content/amount. The study also provides new links to the role of Spn in regulating local synaptic actin dynamics and how this alters the readily releasable pool and SV release. Some points of note are provided below.

1. I'm a bit confused about the time course experiments the authors describe that seem to be contradictory in Figures 1 and 2. The authors indicate control animals transiently increase BRP AZ levels during PHP at 10 mins, but by 30 minutes this increase is gone, even though PHP remains. As such, the data in these early figures suggests increases in BRP AZ levels may support an early aspect of the PHP effect (though I note this appears controversial, as other data indicate blocking the rapid AZ remodeling by several manipulations such as Arl8 transport disruption, permits early PHP, but disrupts late PHP). In contrast, the authors show that Spn mutants do not display AZ BRP increase at 10 mins, and still show early PHP, but lack late PHP. I assume the early PHP does not require AZ remodeling or an increase in the RRP at this early time point?

2. In relation to point 1 above, the time course seems different in MB neurons, where the AZ remodeling (noted by increases in AZ BRP) seems to take 2-3 hours. Do the authors have any ideas into why the time course of PHP AZ remodeling at larval NMJs can occur in 10 minutes, but MB neuron remodeling seems to take hours?

3. Could the lack of rapid BRP accumulation during early PHP in Spn mutants be secondary to the larger # of AZs in those mutants and a known rate-limiting amount of BRP available that might not be enough to go to the extra AZs?

4. There isn't any validation of the Spn co-IP results shown in Figure 3 through other assays, and a lot of proteins are being pulled down. I can't see some of these being real (mitochondrial translation proteins? - how could Spn gain access to the inside of the mitochondria since it's a cytosolic protein?). As such, I don't know how to value that huge group of pull-down interactions without further validation, making it difficult to sort out how relevant these really are. The genetic validation of similar phenotypes in the Mical mutant, together with rescues, supports that interaction. Not sure about the rest of that list.

5. Are the authors worried about the fact that the Actin-GFP line they use to look at synaptic actin dynamics is driven by a GAL4, and the 2nd top hit of their Spn IP pull downs are translation regulators? Could the changes in actin-GFP they see between control and Spn mutants have anything to do with a different translation of the exogenous UAS-actin-GFP? Would have been helpful to do an endogenous stain for actin levels with an anti-actin antibody so no transcription/translation issues of a transgene would be at play. This would be easy to do for the quantification of total actin levels at the synapse.

6. Are Mical levels normalized in the Spn, Syd1 double mutants, given PHP is recovered?

Reviewer #2 (Public Review):

In this manuscript, Dumeaux et al. assess the heterogeneous cellular response of the fungal pathogen Candida albicans to antifungal agents, using single-cell RNA sequencing. The researchers develop and optimized single-cell transcriptomics platform for C. albicans, and exploit this technique to monitor the cellular response to treatment with three distinct antifungal agents. Through this analysis, they identify two distinct subpopulations of cells that undergo differential transcriptomic responses to antifungal treatment: one involving upregulation of translation and respiration, and the other involving stress responses. This work monitors how different and prolonged antifungal exposure alters and shifts fungal cell populations between these responses. This is an innovative study that exploits novel single-cell transcriptomic techniques to address a very interesting question regarding the heterogeneous nature of the fungal response to antifungal drug treatment. This work optimizes a protocol for single-cell RNA sequencing, which is a significant contribution to the fungal research community and will bolster future research efforts in this area. The identification of two distinct subpopulations of fungal cells with differential responses to antifungal treatment is an exciting and novel finding. While there are aspects of this manuscript that are of significant interest, there are also limitations to this work. The research is framed as a method to study antifungal drug tolerance, but it is not clear how it does so, based on the methods. This work also compares very different populations of cells (rapidly growing untreated cells compared with cells grown in antifungal for several days), making it difficult to assess the role of antifungal treatment specifically in this analysis. This manuscript is also written with a great deal of highly technical language that makes it difficult to dissect the major findings and outcomes from the study.

Reviewer #2 (Public Review):

This study highlights a connection between the power spectra of fMRI signals and the temporal dynamics of the hemodynamic response function (HRF). Using visual stimulation experiments and resting-state scans, the spectral features of resting-state fMRI signals in V1 and LGN are found to have a significant relationship to the relative timing of HRF responses during the task.

Overall, I found this to be an interesting and clearly written study, with high-quality data. The connection between BOLD signal spectra and vascular responses is not discussed in much of the resting-state fMRI literature, and represents an important message and consideration. While the connection between the amplitude of resting-state BOLD fluctuations and the amplitude of task HRFs has been investigated in the past, I am not aware of prior work that had considered the timing aspect. The present comparison between resting-state spectra and breath-holding task responses also provides useful data about the hemodynamic information carried by these two conditions.

The present experiments were conducted at 7T with high temporal resolution and focused on a visual experiment. The generalization of the findings to other task conditions, brain regions, and acquisition parameters would be a valuable future step. Understanding the translation to other datasets would be a practical consideration for researchers who are considering applying this method. Regarding the evaluation of the classification models, it currently appears possible that the train/test sets might contain closely spaced and thus correlated voxels. Accounting for this effect could help to better support the conclusions of this analysis. More discussion about the neural or vascular basis of the slow- versus fast-HRF voxels could also bring further insights to the work (for instance, the location of the fast and slow V1 voxels with respect to functional boundaries and vascular anatomy).

Reviewer #2 (Public Review):

This study shows that rab12 has a role in the phosphorylation of rab10 by LRRK2. Many publications have previously focused on the phosphorylation targets of LRRK2 and the significance of many remains unclear, but the study of LRRK2 activation has mostly focused on the role of disease-associated mutations (in LRRK2 and VPS35) and rab29. The work is performed entirely in an alveolar lung cell line, limiting relevance for the nervous system. Nonetheless, the authors take advantage of this simplified system to explore the mechanism by which rab12 activates LRRK2. In general, the work is performed very carefully with appropriate controls, excluding trivial explanations for the results, but there are several serious problems with the experiments and in particular the interpretation.

First, the authors note that rab29 appears to have a smaller or no effect when knocked down in these cells. However, the quantitation (Fig1-S1A) shows a much less significant knockdown of rab29 than rab12, so it would be important to repeat this with better knockdown or preferably a KO (by CRISPR) before making this conclusion. And the relationship to rab29 is important, so if a better KD or KO shows an effect, it would be important to assess by knocking down rab12 in the rab29 KO background.

Secondly, the knockdown of rab12 generally has a strong effect on the phosphorylation of the LRRK2 substrate rab10 but I could not find an experiment that shows whether rab12 has any effect on the residual phosphorylation of rab10 in the LRRK2 KO. There is not much phosphorylation left in the absence of LRRK2 but maybe this depends on rab12 just as much as in cells with LRRK2 and rab12 is operating independently of LRRK2, either through a different kinase or simply by making rab10 more available for phosphorylation. The epistasis experiment is crucial to address this possibility. To establish the connection to LRRK2, it would also help to compare the effect of rab12 KD on the phosphorylation of selected rabs that do or do not depend on LRRK2.

A strength of the work is the demonstration of p-rab10 recruitment to lysosomes by biochemistry and imaging. The demonstration that LRRK2 is required for this by biochemistry (Fig 4A) is very important but it would also be good to determine whether the requirement for LRRK2 extends to imaging. In support of a causal relationship, the authors also state that lysosomal accumulation of rab12 precedes LRRK2 but the data do not show this. Imaging with and without LRRK2 would provide more compelling evidence for a causative role.

The authors also touch base with PD mutations, showing that loss of rab12 reduces the phosphorylation of rab10. However, it is interesting that loss of rab12 has the same effect with R1441G LRRK2 and D620N VPS35 as it does in controls. This suggests that the effect of rab12 does not depend on the extent of LRRK2 activation. It is also surprising that R1441G LRRK2 does not increase p-rab10 phosphorylation (Fig 2G) as suggested in the literature and stated in the text.

Most important, the final figure suggests that PD-associated mutations in LRRK2 and VPS35 occlude the effect of lysosomal disruption on lysosomal recruitment of LRRK2 (Fig 4D) but do not impair the phosphorylation of rab10 also triggered by lysosomal disruption (4A-C). Phosphorylation of this target thus appears to be regulated independently of LRRK2 recruitment to the lysosome, suggesting another level of control (perhaps of kinase activity rather than localization) that has not been considered.

Reviewer #2 (Public Review):

The present manuscript by the Claire Wyart group analyses the behaviour of Reissner's fibre (RF) when it is cut, as well as the behaviour of cells touching RF when contact is interrupted. They show that RF is under tension that is higher in the rostral than in the caudal spinal cord. One of the proposed mechanisms is a caudally oriented movement of the cilia of ependymal radial glials cells (ERG) that is inherent rather than caused by the contact with RF. Kolmer Agduhr neurons that are also CSF contacting (CSF-cN), alter their activity when contact is lost through laser ablation of RF.

This is an interesting paper - RF has long been proposed to be a source of signalling molecules in the development and physiological function of neural cells in the spinal cord. Cilia are the main centre of signalling activity in ciliated cells (e.g. for sonic hedgehog signalling) and the fact that ERG cilia are in direct contact with RF is intriguing. Presumably, signalling molecules could be directly transferred from RF to ERG at the contact points.

Functionally, CSF-cN are augmenting spinal cord intrinsic sensory feedback on body curvature. This had been shown in vitro/ex vivo, but not clearly evaluated in the living animal. The data shown here demonstrate a possible mechanism for how the feedback can be mediated through contact with RF. This is of fundamental interest to understand the functioning of a locomotor network that is under evolutionary pressure to function early, since fish hatch at 3 days post fertilisation.

Interestingly, the authors propose (and discuss against the relevant literature) that the presence of RF in the central canal can influence the flow of the CSF, which should be investigated in further work.

Overall, the results are clearly presented, and methods are thoroughly given, including some indication on the reduction of bias (by blinding movies before analysis). The authors also clearly state the limitations of their work, mostly derived from optical limitation (size of the RF in the larval fish, and speed of the recording in the laser-equipped microscope). This doesn't affect the fundamental statements.

Reviewer #2 (Public Review):

This well-written manuscript provides a technical tour-de-force to provide a novel mechanism for sustaining CaMKII autophosphorylation through an interholoenzyme reaction mechanism the authors term inter-holoenzyme phosphorylation (IHP). The authors use molecular engineering to create designer molecules that permit detailed testing of the proposed interholoenzyme reaction mechanism. By catalytically inactivating one population of enzymes, they show using standard assays that the inactive enzyme can be phosphorylated by active holoenzymes. They go on to show that in cells, the inactive enzyme is phosphorylated only in the presence of co-expressed active CaMKII and that this does not appear to be due to active and inactive subunits mixing within the same holoenzyme. The authors suggest reasons for why previous experiments failed to expose IHP and in some experiments provide evidence that reproduces and then extends earlier studies. Some noted differences from earlier experiments are the reaction temperature, the time course of the reactions, and that significantly higher concentrations of the inactive (substrate) kinase in the present study amplify the IHP. These are plausible reasons for earlier studies not finding significant evidence for IHP and the presented data is well-controlled and of high quality.

The authors then take on the idea of subunit exchange employing multiple strategies. Using genetic expansion, they engineer an unnatural amino acid into the hub domain of the kinase (residue 384). In the presence of the photoactivatable crosslinker BZF and UV illumination, a ladder of subunits was generated indicating intraholoenzyme crosslinks were established. Using this cross-linked enzyme, presumably incapable of subunit exchange, the authors show significant phosphorylation of the kinase-dead mutant. This further supports that IHP is the cause of phosphorylation and not subunit exchange. Extending these experiments, they could not find evidence when CaMKIIF394BZF was mixed with the kinase-dead mutant and exposed to UV light, that there was evidence of the kinase-dead subunits exchanged into CaMKIIF394 (active) enzymes.

With an entirely different approach, the authors use isotopic labeling of different pools of wt CaMKII (N14 or N15) followed by bifunctional cross-linking and mass spec to assess potential intra- and inter-holoenzyme contacts. Several interesting findings came of these studies detailed in Figure 4, mapped in detail in Figure 5, and extensively documented in supplementary tables. Critically, numerous cross-links were found between different domains of the enzyme (catalytic, regulatory, hub) that are themselves a nice database of proximity measurements, but critical to the hypothesis, no heterotypic cross-links were found in the hub domains at any activated state or time point of incubation. This data supports two findings, that catalytic domains come into close proximity between holoenzymes when activated, supporting the potential for IHP, but that no subunit exchange occurs.

The authors then pursue the approach used originally to provide evidence of subunit mixing, single molecule-based fluorescence imaging. Using pools of CaMKII labeled with spectrally separable dyes, the authors reproduce the earlier findings (Stratton et al, 2016) showing that under activating conditions, but not basal conditions, colocalized spots were detected. Numerous controls were done that confirm the need for full activation (Ca2+/CaM + Mg2+/ATP) to visualize co-localized CaMKII holoenzymes. Extending these studies, the authors mix holoenzymes, fully activate them, and after sufficient time for subunit exchange (if it occurs), the reactions were quenched, and then samples were analyzed. The result was that no evidence of dual-colored holoenzymes was present; if subunits had mixed between holoenzymes, dual-colored spots should have been evident after quenching the reactions. This was not the case. Further, experiments repeated with pools of differentially labeled kinase dead enzymes produced no colocalization, as predicted, if activation of the catalytic domains is necessary to establish IHP.

Finally, the authors employ mass photometry to investigate the potential for interholoenzyme interactions. At basal conditions, only a mass peak consistent with CaMKII dodecamers was evident. Upon activation, a small fraction of dimeric complexes was evident (with Ca2+/CaM bound) but the majority of the peak was a dodecamer with 12 associated CaM molecules, and importantly, a significant fraction of a mass population was found consistent with a pair of holoenzymes with associated CaM. As an aside, the holoenzyme population appeared to be modestly destabilized as evidence of a minor fraction of dimers appeared as the authors diluted the enzyme, but the pools of holoenzyme and pairs of holoenzymes (with CaM) remained the dominant species when activated under all three enzyme concentrations assessed. Supporting the importance of activation for interactions between holoenzymes, the catalytically dead kinase even under activating conditions, shows no evidence of dimers of holoenzymes.

Each of the approaches is well-controlled, the data is of uniformly high quality, and the authors' interpretations are generally well-supported.

Reviewer #2 (Public Review):

The article by Joechner et al is a reanalysis of a large cohort data-set on sleep oscillation development. By combining an analysis with fixed frequencies derived from adults with adaptive frequency ranges, they highlight that initially spindle oscillations are slower and it takes until mid adolescence for spindles to be more adult like. Further, those spindles that already have adult-like frequency ranges also show the other properties known from adults. These results are intriguing and the analysis is well-done and thorough. I only have minor comments on how the article could be improved.

Some additional analysis that would complement the current findings: in Fig 1 it would be good to include the adult-like slow frontal spindles for comparison (similar as the inclusion for the centro parietal ones). Further, providing distributions could let the readers have some valuable insight into the events. Could the authors combine all events and show 3D scatter plots with frequency X amplitude X duration of each spindle event? And then either color code the events from different age groups or have them in separate plots. Additionally, the frequency cut-off for adult-events could be added to the plot. This would likely show nicely how the events shift in their properties over age and thus slowly reach adult-like characteristics.

On page 2. Line 17 the authors state that spindles align ripples. While this is the case, the interaction between these oscillations are more complex. Ripples will also occur before the spindle and the ripples before spindles have been shown to be causally related to memory consolidation. Please cite Maingret et al Nat Neurosci 2016. Further, the authors should also discuss other rodent work for example Garcia et al Frontiers 2022, which also investigates the development of spindles.

Reviewer #2 (Public Review):

This study investigates the associations and causal relationship between second primary cancers and the initial diagnosis of a primary cancer, utilizing a large-scale database. The study's unique contribution lies in its combination of pan-cancer analysis and the incorporation of Mendelian randomization, which adds novelty and enhances the value of the research.

Furthermore, the findings of this study have the potential to provide valuable insights into important clinical considerations, such as patients' prognosis, treatment decisions, and survivorship care.

Reviewer #2 (Public Review):

In this Manuscript, Huang et al generated engineered MSC (eMSC) to produce mutant b-GALH363A, and when stimulated with a pro-drug (MGP) they can release NO. These cells were tested in vivo in a mouse model of AKI. When MGP is systemically administrated in AKI mice, it can induce eMSC to release NO in a precise and spatiotemporal manner, possibly enhancing the therapeutic efficacy of these stem cells.

The authors have conducted a very interesting study. The results are likely of interest to the renal scientific community, especially in the context of acute kidney injury.

Weaknesses are present. Methods (animals, groups, time points, cell lines, bulk RNA-seq, etc.) are not clearly described and details are missing. Legends are not clear, and some Figures do not clearly represent the results discussed.

Reviewer #2 (Public Review):

In this study, Pinatel et al. address the role of interneuron myelination in the hippocampus using a 4.1B protein mouse knockout model. They show that deficiency in 4.1B significantly reduces myelin in CA1 stratum radiatum, specifically myelin along axons of parvalbumin and somatostatin hippocampal interneurons. In addition, there are striking defects in the distribution of ion channels along myelinated axons, with misplacement of Na channel clusters along the nodes of Ranvier and the heminodes, and a pronounced decrease in potassium channels (Kv1) at juxtaparanodes. The axon initial segments of SST are also shorter. Because the majority of myelinated axons in the stratum radiatum of the hippocampus belong to PV and SST interneurons such profound changes in myelination are expected to affect interneuronal function. Interestingly, the authors show that PV basket cells' properties appear largely unaffected, while there are substantial changes in stratum oriens O-LM cells. Inhibitory inputs to pyramidal neurons are also changed. Behaviorally, the 4.1B KO mice exhibit deficits in spatial working memory, supporting the role of interneuronal myelination in hippocampal function. This study provides important insights into the role of myelination for the function of inhibitory interneurons, as well as in the mechanisms of axonal node development and ion channel clustering, and thus will be of interest to a broad audience of circuit and cellular neuroscientists. However, the claims of the specificity of the reported changes in myelination need to be better supported by evidence.

Strengths:<br /> The authors combine a wide array of genetic, immunolabeling, optical, electrophysiological, and behavioral tools to address a still unresolved complex problem of the role of myelination of locally projecting inhibitory interneurons in the hippocampus. They convincingly show that changing myelination and ion channel distribution along nodes and heminodes significantly impairs the function of at least some interneuron types in the hippocampus and that this is accompanied by behavioral deficits in spatial memory.

Regarding the organization of myelinated axons, the lack of 4.1B causes striking changes at the nodes of Ranvier that are convincingly and beautifully presented in the Figures. While the reduction in Kv1 in 4.1B KO mice has been previously reported, the mislocalization of sodium channels at the nodes and heminodes had only been observed in developing but not adult spinal cords. This difference in the dependence of the sodium channel distribution on 4.1B in adult hippocampus vs spinal cord may hold important clues for the varying role of myelin along axons of different neuronal types.

The manuscript is very well written, the discussion is comprehensive, and provides detailed background and analysis of the current findings and their implications.

Weaknesses:<br /> Because of the wide diversity of interneuron types in the hippocampus, and also the presence of myelinated axons from other neuron types as well, including pyramidal neurons, it is very difficult to disentangle the effects of the observed changes in the 4.1 B KO mouse model. While the authors have been careful to explore different possibilities, some of the claims of the specificity of the reported changes in myelination are not completely founded. For example, there is no compelling evidence that the myelination of axons other than the local interneurons is unchanged. The evidence strongly supports the claims of changes in interneuronal myelination, but it leaves open the question of whether 4.1B lack affects the myelination of hippocampal pyramidal neurons or of long-range projections.

To be able to better interpret the changes in the 4.1B KO mice, knowledge of the distribution of 4.1B in the hippocampus of control mice will be very helpful. The authors state that 4.1B is observed in PV neurons but not in pyramidal neurons, however, the evidence is not convincing. Thus, the lack of immunolabeling at the pyramidal neuron cell bodies does not indicate that 4.1B is missing at the axonal level. The analysis also leaves out the question of whether 4.1 B is seen in the axons of somatostatin neurons.

Reviewer #2 (Public Review):

In this manuscript, the authors characterize activity-dependent transcriptional and epigenetic changes at two different time points (1h and 4hrs) after neuronal activation using rat striatal primary cultures. They show that while at 1h post-stimulation mostly a selective set of IEGs are up-regulated, at 4hrs a wider set of genes, identified as late-response genes (LRGs), are upregulated, with distinct functional signatures. By using ATAC-seq, the authors show how chromatin accessibility is mostly spared at 1h post-stimulation, while a prominent set of differentially accessible regions (DARs) could be identified at 4hrs post-stimulation, enriched in motifs for TFs upregulated at their initial time-point. These chromatin changes appear to be dependent on the earlier translation of proteins, as they are avoided when neuronal cultures are pre-treated with the protein synthesis inhibitor Anisomycin. Afterwards, the authors characterized a set of regulatory regions of a particular LRG, Pdyn, associated with neuropsychiatric disorders, by using CRISRPR to activate or inactivate an enhancer that increases its accessibility at 4hrs post-stimulation, showing that the expression of Pdyn is highly dependent on this regulatory region both, at basal level and for its proper activity-dependent stimulation and that it is enriched in motifs for IEGs upregulated at 1h post-stimulation. Using publicly available data from human GABAergic and glutamatergic neurons similarly stimulated with KCl, the authors show that this enhancer is conserved in humans and that it is mostly modified in GABAergic neurons in response to neuronal stimulation, but not in glutamatergic neurons. Finally, the authors suggest that the regulatory role of the Pdyn enhancer they focus on it might be cell-type specific, as single-nuclei ATAC-seq data generated in rat Nucleus Accumbens (NAc) shows that its coaccessibility score together with Pdyn promoter is more prominent in Drd1- and Grm8-MSNs.

Among the major strengths of the article, there is the generation of neuronal RNA-seq and ATAC-seq data in a model system, rat striatal neuronal cells, that hasn't been so broadly characterized as other more common ones such as mouse hippocampal neuronal cells and the functional characterization of an enhancer of the Pdyn gene that might be of interest for translational applications in which alterations of this gene might be occurring in neurological disorders.

On the other hand, the manuscript presents several weaknesses to consider. First of all, at a conceptual level, most of the findings related to the induction of particular transcriptional programs upon neuronal activation the changes in chromatin state, and the need for protein translation for proper induction of LRGs have been broadly characterized previously in the literature (Tyssowski et al., Neuron, 2018; Ibarra et al., Mol. Syst. Biol., 2022; and also reviewed by Yap and Greenberg, Neuron, 2018). In addition, it is not so obvious why to focus on Pdyn gene regulatory regions among the thousands of genes upregulated and with modified chromatin landscape after neuronal activation. The authors highlight three particular traits of this gene as the reason to choose it, but those traits are probably shared by most of the genes that are part of the LRGs set.

At the methodological level, some attention should be put into the timings chosen for generating the data. The authors claim that these time points (1h and 4hrs) identify the first (i.e IEGs) and second (i.e LRGs) waves of transcription. However, at 4hrs the highest over-expressed genes are still IEGs, as shown in the volcano plots of Figure 1B and 1C, showing a high overlap with up-regulated genes found at 1h (Figure 1D). This might suggest that the 4hrs time point is somewhere in between the first and second wave of transcription, probably missing some of the still-to-be-induced LRGs of the latest one.

Finally, while only prosed as a suggestion, the assumption that from the data generated in this article, we can envision a mechanism by which AP-1 family of transcription factors interacts with the SWI/SNF chromatin remodeling complex is going too far, as no evidence is provided implicated SWI/SNF in the data presented in the manuscript.

Reviewer #2 (Public Review):

The authors phototag DA and GABA neurons in the VTA in mice performing a t-maze task, and report choice-specific responses in the delay period of a memory-guided task, more so than in a variant task w/o a memory component. Overall, I found the results convincing. While showing responses that are choice selective in DA neurons is not entirely novel (e.g. Morris et al NN 2006, Parker et al NN 2016), the fact that this feature is stronger when there is a memory requirement is an interesting and novel observation.

I found the plots in 3B misleading because it looks like the main result is the sequential firing of DA neurons during the Tmaze. However, many of the neurons aren't significant by their permutation test. Often people either only plot the neurons that are significant, or plot with cross-validation (ie sort by half of the trials, and plot the other half).

Relatedly, the cross-task comparisons of sequences (Fig, 4,5) are hampered by the fact that they sort in one task, then plot in the other, which will make the sequences look less robust even if they were equally strong. What happens if they swap which task's sequences they use to order the neurons? I do realize they also show statistical comparisons of modulated units across tasks, which is helpful.

Overall, the introduction was scholarly and did a good job covering a vast literature. But the explanation of t-maze data towards the end of the introduction was confusing. In Line 87, I would not say "in the same task" but "in a similar task" because there are many differences between the tasks in question. And not clear what is meant by "by averaging neuronal population activities, none of these computational schemes would have been revealed. " There was trial averaging, at least in Harvey et al. I thought the main result of that paper related to coding schemes was that neural activity was sequential, not persistent. I think it would help the paper to say that clearly. Also, I'm not aware it was shown that choice selectivity diminishes when the memory demand of the task is removed - please clarify if that is true in both referenced papers. If so, an interpretation of this present data could be found in Lee et al biorxiv 2022, which presents a computational model that implies that the heterogeneity in the VTA DA system is a reflection of the heterogeneity found in upstream regions (the state representation), based on the idea that different subsets of DA neurons calculate prediction errors with respect to different subsets of the state representation.

I am surprised only 28% of DA neurons responded to reward - the reward is not completely certain in this task. This seems lower than other papers in mice (even Pavlovian conditioning, when the reward is entirely certain). It would be helpful if the authors comment on how this number compares to other papers.

Reviewer #2 (Public Review):

This work presents a new, automated, deep learning-based segmentation pipeline for fetal cerebral MRI based on the anatomical definitions of the new fetal atlas of the Developing Human Connectome Project. The authors' new software pipeline demonstrated robust performance across different acquisition protocols and gestational age ranges, reducing the need for manual refinement. To provide ground truth data for training their deep learning network, the authors employed a semi-supervised approach, in which atlas labels were propagated to the datasets, and they were corrected manually.

This work stands out for its extensive training on a large number of datasets, it achieves precise anatomical definition through a refined brain tissue parcellation protocol, and it evaluates the segmentation results against growth curves, allowing for a comprehensive assessment of fetal brain development. Due to the fact that abnormal anatomy was largely unobserved by the segmentation network, it is highly likely, however, that the BOUNTI pipeline would lead to some incorrect segmentations in subjects with moderate to large ventriculomegaly, as well as in cases of malformations of the corpus callosum, brainstem or neural tube defects. Further work is required for BOUNTI to generalize its application to pathological brains, as the vast majority of fetal cerebral MRI cases in clinical practice involve such abnormalities rather than normal brain development. This step is crucial for facilitating the clinical translation of BOUNTI. The algorithm is publicly available and works without limitations on datasets acquired in other centers.

Reviewer #2 (Public Review):

Sequences of neural activity underlie most of our behavior. And as experience suggests we are (in most cases) able to flexibly change the speed for our learned behavior which essentially means that brains are able to change the speed at which the sequence is retrieved from the memory. The authors here propose a mechanism by which networks in the brain can learn a sequence of spike patterns and retrieve them at variable speed. At a conceptual level I think the authors have a very nice idea: use of symmetric and asymmetric learning rules to learn the sequences and then use different inputs to neurons with symmetric or asymmetric plasticity to control the retrieval speed. The authors have demonstrated the feasibility of the idea in a rather idealized network model. I think it is important that the idea is demonstrated in more biologically plausible settings (e.g. spiking neurons, a network with exc. and inh. neurons with ongoing activity).

Summary

In this manuscript authors have addressed the problem of learning and retrieval sequential activity in neuronal networks. In particular, they have focussed on the problem of how sequence retrieval speed can be controlled?<br /> They have considered a model with excitatory rate-based neurons. Authors show that when sequences are learned with both temporally symmetric and asymmetric Hebbian plasticity, by modulating the external inputs to the network the sequence retrieval speed can be modulated. With the two types of Hebbian plasticity in the network, sequence learning essentially means that the network has both feedforward and recurrent connections related to the sequence. By giving different amounts of input to the feed-forward and recurrent components of the sequence, authors are able to adjust the speed.

Strengths<br /> - Authors solve the problem of sequence retrieval speed control by learning the sequence in both feedforward and recurrent connectivity within a network. It is a very interesting idea for two main reasons: 1. It does not rely on delays or short-term dynamics in neurons/synapses 2. It does not require that the animal is presented with the same sequences multiple times at different speeds. Different inputs to the feedforward and recurrent populations are sufficient to alter the speed. However, the work leaves several issues unaddressed as explained below.

Weaknesses<br /> - The main weakness of the paper is that it is mostly driven by a motivation to find a computational solution to the problem of sequence retrieval speed. In most cases they have not provided any arguments about the biological plausibility of the solution they have proposed e.g.:

-- Is there any experimental evidence that some neurons in the network have symmetric Hebbian plasticity and some temporally asymmetric? In the references authors have cited some references to support this. But usually the switch between temporally symmetric and asymmetric rules is dependent on spike patterns used for pairing (e.g. bursts vs single spikes). In the context of this manuscript, it would mean that in the same pattern, some neurons burst and some don't and this is the same for all the patterns in the sequence. As far as I see here authors have assumed a binary pattern of activity which is the same for all neurons that participate in the pattern.

-- How would external inputs know that they are impinging on a symmetric or asymmetric neuron? Authors have proposed a mechanism to learn these inputs. But that makes the sequence learning problem a two stage problem -- first an animal has to learn the sequence and then it has to learn to modulate the speed of retrieval. It should be possible to find experimental evidence to support this?

-- Authors have only considered homogeneous DC input for sequence retrieval. This kind of input is highly unnatural. It would be more plausible if the authors considered fluctuating input which is different from each neuron.

-- All the work is demonstrated using a firing rate based model of only excitatory neurons. I think it is important that some of the key results are demonstrated in a network of both excitatory and inhibitory spiking neurons. As the authors very well know it is not always trivial to extend rate-based models to spiking neurons.

I think at a conceptual level authors have a very nice idea but it needs to be demonstrated in a more biologically plausible setting (and by that I do not mean biophysical neurons etc.).

Reviewer #1 (Public Review):

The manuscript by Kulkarni et al proposes a new cellular origin of ENS, which is increased with age and therefore may be associated with the gradual decline of gut function. The study is based on an initial observation that many enteric neurons do not seem to retain tdTomato expression in Wnt1Cre-R26-Tom mice, suggesting a loss of neurons that are replaced by a non-neural crest source. Further detection of reporter expression within the ENS of Tek and Mesp Cre-lines indicated a mesodermal origin of the new enteric neurons. Mesodermally derived neurons (MENS) were associated with Met, while neural crest derived neurons (NENS) expressed Ret. GDNF could decrease occurrence of MENS (defined as tdTomato-negative cells), while HGF had the opposite effect. Age-associated decline in gut transit was alleviated with GDNF treatment, while Ret heterozygote mutants had an increase of MENS. Overall, the study suggests that neural crest derived neurons are replaced by mesodermal-derived neurons that lead to an overall reduction in GI-physiology and that manipulation of the balance between the two types of neurons could have beneficial effects of age-associated gut malfunction. Generation of neurons from non-ectodermal sources would be a paradigm shift not only in the ENS, but in the Neuroscience field as a whole. The presence of mesenchymal marker genes in subsets of cells of the ENS in native gut tissue is convincing and the lack of retained fluorescent reporter expression in ENS from the many neural and Cre drivers used is indeed clear.

The current state of the manuscript is though not conceivable as it has unsound interpretation of data at many places, most importantly there is no firm connection between the MENs identified in tissue and the scRNA cluster annotated as MENs. "scRNA-seq-MENs" show very little expression of the bona fide neuron markers used to detect "tissue-MENs" including Elavl4 and the overall proportions of "scRNA-seq-MENs" in the tissue is very far from that of "tissue-MENs". Hence, the claims that "tissue-MENs" equals "scRNA-seq MENs" could be excluded or their interpretation discussed in an unbiased manner. Marker expression of "scRNA-seq MENs" are suggestive of mesothelial cell identities, not ENS cells. Even the annotation of scRNA-seq profiles denoted as neural-crest derived enteric neurons (NENs) is highly questionable as 25% of the cells display bona fide lympathic epithelial cell markers and no neuronal markers.

Reviewer #2 (Public Review):

The question the authors pose is very simple and yet very important. Does the fact that many genes compete for Pol II to be transcribed explain why so many trans-eQTL contribute to the heritability of complex traits? That is, if a gene uses up a proportion of Pol II, does that in turn affect the transcriptional output of other genes relevant or even irrelevant for the trait in a way that their effect will be captured in a genome-wide association study? If yes, then the large number of genetic effects associated with variation in complex traits can be explained but such trans-propagating has effects on the transcriptional output of many genes.

This is a very timely question given that we still don't understand how, mechanistically, so many genes can be involved in complex traits variation. Their approach to this question is very simple and it is framed in classic enzyme-substrate equations. The authors show that the trans-propagating effect is too small to explain the ~70% of heritability of complex traits that are associated with trans-effects. Their conclusion relies on the comparison of the order of magnitude of a) the quantifiable transcriptional effects due to Pol II competition, and b) the observed percentage of variance explained by trans effects (data coming from Liu et al 2019, from the same lab).

The results shown in this manuscript rule out that competition for limited resources in the cell (not restricted to Pol II, but applicable to any other cellular resource like ribosomes, etc) could explain the heritability of complex traits.

Reviewer #2 (Public Review):

The manuscript investigates the connections between the ubiquitin ligase protein deltex and the wingless pathway. Two different connections are proposed, one is the function of deltex to modulate the gradient of wingless diffusion and hence modulate the spatial pattern of wingless pathway targets, which regulate at different thresholds of wingless concentration. The second is a direct interaction between deltex and armadillo, a downstream component of the wingless pathway. Deltex is proposed to cause the degradation of armadillo resulting in suppression of wingless pathway activity. The results and conclusions of the manuscript are interesting and for the most part, novel, although previously published work linking Notch and deltex to wingless signal regulation, and endocytosis to wingless gradient formation could be more extensively discussed. However neither of the two parts of the manuscript seem in themselves sufficiently complete, and combining both parts together therefore seems to lack focus.

The main issue with the manuscript is that many of the conclusions are inferred from genetic interactions in vivo between loss of function mutants and overexpression. While providing useful in vivo physiological context, this type of approach struggles to be able to make definitive conclusions on whether an interaction is due to a direct or indirect mechanism, as the authors themselves conclude at the end of section 2.3. The problem is confounded by the fact that there is already documented much cross-talk between the Notch signaling pathway and wingless at the transcriptional level, and deltex is already a Notch modulator that can alter wingless mRNA expression (See Hori et al 2004). Deltex in addition to promoting a ligand-independent Notch signal can also induce expression of Notch ligand, allowing further non-autonomous Notch activation and subsequent cell autonomous cis-inhibition of the initial deltex-induced signal. The dynamics and outcomes of the Notch signal response to deltex in vivo are therefore already very complicated to interpret before even considering unraveling indirect (via Notch) and direct interactions with wingless, although the two possibilities are not mutually exclusive.

Reviewer #2 (Public Review):

Wang, He et al. shed insight into the molecular mechanisms of deep-sea chemosymbiosis at the single-cell level. They do so by producing a comprehensive cell atlas of the gill of Gigantidas platifrons, a chemosymbiotic mussel that dominates the deep-sea ecosystem. They uncover novel cell types and find that the gene expression of bacteriocytes, the symbiont-hosting cells, supports two hypotheses of host-symbiont interactions: the "farming" pathway, where symbionts are directly digested, and the "milking" pathway, where nutrients released by the symbionts are used by the host. They perform an in situ transplantation experiment in the deep sea and reveal transitional changes in gene expression that support a model where starvation stress induces bacteriocytes to "farm" their symbionts, while recovery leads to the restoration of the "farming" and "milking" pathways.

A major strength of this study includes the successful application of advanced single-nucleus techniques to a non-model, deep-sea organism that remains challenging to sample. I also applaud the authors for performing an in situ transplantation experiment in a deep-sea environment. From gene expression profiles, the authors deftly provide a rich functional description of G. platifrons cell types that is well-contextualized within the unique biology of chemosymbiosis. These findings offer significant insight into the molecular mechanisms of deep-sea host-symbiont ecology, and will serve as a valuable resource for future studies into the striking biology of G. platifrons.

The authors' conclusions are generally well-supported by their results. However, I recognize that the difficulty of obtaining deep-sea specimens may have impacted experimental design. In this area, I would appreciate more in-depth discussion of these impacts when interpreting the data.

Because cells from multiple individuals were combined before sequencing, the in situ transplantation experiment lacks clear biological replicates. This may potentially result in technical variation (ie. batch effects) confounding biological variation, directly impacting the interpretation of observed changes between the Fanmao, Reconstitution, and Starvation conditions. It is notable that Fanmao cells were much more sparsely sampled. It appears that fewer cells were sequenced, resulting in the Starvation and Reconstitution conditions having 2-3x more cells after doublet filtering. It is not clear whether this is due to a technical factor impacting sequencing or whether these numbers are the result of the unique biology of Fanmao cells. Furthermore, from Table S19 it appears that while 98% of Fanmao cells survived doublet filtering, only ~40% and ~70% survived for the Starvation and Reconstitution conditions respectively, suggesting some kind of distinction in quality or approach.

There is a pronounced divergence in the relative proportions of cells per cell type cluster in Fanmao compared to Reconstitution and Starvation (Fig. S11). This is potentially a very interesting finding, but it is difficult to know if these differences are the expected biological outcome of the experiment or the fact that Fanmao cells are much more sparsely sampled. The study also finds notable differences in gene expression between Fanmao and the other two conditions- a key finding is that bacteriocytes had the largest Fanmao-vs-starvation distance (Fig. 6B). But it is also notable that for every cell type, one or both comparisons against Fanmao produced greater distances than comparisons between Starvation and Reconstitution (Fig. 6B). Again, it is difficult to interpret whether Fanmao's distinctiveness from the other two conditions is underlain by fascinating biology or technical batch effects. Without biological replicates, it remains challenging to disentangle the two.

Reviewer #2 (Public Review):

This is an interesting paper from a reputable group in the field of islet physiology. The authors have provided the results from extensive studies, which will contribute to the knowledge of islet dysfunction and diabetes pathophysiology. The authors studied "the human orthologues of the correlated mouse proteins that are proximal to the glycemia-associated SNPs in human GWAS". This implies two assumptions - (1) human and mouse proteins do not differ in terms of islet physiology and calcium signaling; (2) the proteins proximal to the SNPs are the causal factors for functional differences, though the SNPs could affect protein/gene function distant from the SNPs.

Reviewer #2 (Public Review):

The authors aimed to investigate whether digital insoles are an appropriate alternative to laboratory assessment with force plates when attempting to identify the knee injury status. The methods are rigorous and appropriate in the context of this research area. The results are impressive, and the figures are exceptional. The findings of this study can have a great impact on the field, showing that digital insoles can be accurately used for clinical purposes. The authors successfully achieved their aims.

Reviewer #2 (Public Review):

The manuscript by Hayashi et al provides the characterization of a new mouse line that targets V2 neurons and demonstrates the locomotor consequences of manipulating the large V2 population. Prior work has examined the effects of silencing and/or ablation of the excitatory V2a and inhibitory V2b neuronal populations independently. Since the two populations are derived from the same V2 lineage but have opposite transmitter phenotypes, one may expect some common synaptic targets and/or similar or complementary functional roles that require excitatory/inhibitory balance. Overall, the value and importance of the study is that comparison of prior manipulations of the V2a and V2b populations (individually in prior studies) with the more global V2 manipulation (here) provides additional insights into spinal locomotor circuitry.

The authors successfully generate a new Hes2cre mouse line that targets the V2 population with high accuracy. The characterizations as far as the specificity and efficiency of the line are compelling. This line is then used to examine the locomotor effects of, first, synaptically silencing all Hes2 neurons throughout the neuroaxis beginning in early development and, then, ablating spinal Hes2 neurons in the adult. The phenotypes of both groups of mice are quite similar, with some small exceptions. The most obvious disturbance in both is the shortened steps, faster step cycle, and more steps required to travel the same distance. As the authors point out, much of the phenotype may be due to a disruption in balance. Interestingly, the hyperextension that is characteristic of V2b neuronal ablation is lost when the function of V2a neurons is compromised as well, suggesting antagonistic functions of these populations in intralimb coordination.

The experiments are rigorous and the data are clearly presented. The findings are interesting to consider in context with prior work. Some comparisons are difficult since gait is not considered and one of the major roles of spinal V2a neurons has been demonstrated to be speed/gait-dependent. The ipsilateral deficits are a major conclusion but some of the supporting data are not clearly derived (or there was an error in the figure?). The use of spinal restricted manipulation removes many of the potential confounds of the full Hes2 silencing. It is still, however, not possible to disentangle the local spinal circuit effects from altered proprioceptive input pathways or ascending information from the lumbar cord to the cervical regions or the brainstem. Although of value to inform future experiments, this impacts the strength of the conclusions that can be drawn.

Reviewer #2 (Public Review):

The chemoreceptor proteins expressed by olfactory sensory neurons differ in their selectivity such that glomeruli vary in the breadth of volatile chemicals to which they respond. Prior work assessing the relationship between tuning breadth and the demographics of principal neuron types that innervate a glomerulus demonstrated that narrowly tuned glomeruli are innervated more projection neurons (output neurons) and fewer local interneurons relative to more broadly tuned glomeruli. The present study used high-resolution electron microscopy to determine which synaptic relationships between principal cell types also vary with glomerulus tuning breadth using a narrowly tuned glomerulus (DA2) and a broadly tuned glomerulus (DL5). The strength of this study lies in the comprehensive, synapse-level resolution of the approach. Furthermore, the authors implement a very elegant approach of using a 2-photon microscope to score the upper and lower bounds of each glomerulus, thus defining the bounds of their restricted regions of interest. There were several interesting differences including greater axo-axonic afferent synapses and dendrodentric output neuron synapses in the narrowly tuned glomerulus, and greater synapses upon sensory afferents from multiglomerular neurons and output neuron autapses in the broadly tuned glomerulus.

The study is limited by a few factors. There was a technical need to group all local interneurons, centrifugal neurons, and multiglomerular projection neurons into one category ("multiglomerular neurons") which complicates any interpretations as even multiglomerular projection neurons are very diverse. Additionally, there were as many differences between the two narrowly tuned glomeruli as there were comparing the narrowly and broadly tuned glomeruli. Architecture differences may therefore not reflect differences in tuning breadth, but rather the ecological significance of the odors detected by cognate sensory afferents. Finally, some synaptic relationships are described as differing and others as being the same between glomeruli, but with only one sample from each glomerulus, it is difficult to determine when measures differ when there is no measure of inter-animal variability. If these caveats are kept in mind, this work reveals some very interesting potential differences in circuit architecture associated with glomerular tuning breadth.

This work establishes specific hypotheses about network function within the olfactory system that can be pursued using targeted physiological approaches. It also identifies key traits that can be explored using other high-resolution EM datasets and other glomeruli that vary in their tuning selectivity. Finally, the laser "branding" technique used in this study establishes a reduced-cost procedure for obtaining smaller EM datasets from targeted volumes of interest by leveraging the ability to transgenically label brain regions in Drosophila.

Reviewer #2 (Public Review):

Working memory is not error free. Behavioral reports of items held in working memory display several types of bias, including contraction bias and serial dependence. Recent work from Akrami and colleagues demonstrates that inactivating rodent PPC reduces both forms of bias, raising the possibility of a common cause.

In the present study, Boboeva, Pezzotta, Clopath, and Akrami introduce circuit and descriptive variants of a model in which the contents of working memory can be replaced by previously remembered items. This volatility manifests as contraction bias and serial dependence in simulated behavior, parsimoniously explaining both sources of bias. The authors validate their model by showing that it can recapitulate previously published and novel behavioral results in rodents and neurotypical and atypical humans.

Both the modeling and the experimental work is rigorous, providing compelling evidence that a model of working memory in which reports sometimes sample past experience can produce both contraction bias and serial dependence, and that this model is consistent with behavioral observations across rodents and humans in the parametric working memory (PWM) task.

Evidence for the model advanced by the authors, however, remains incomplete. The model makes several bold predictions about behavior and neural activity, untested here, that either conflict with previous findings or have yet to be reported but are necessary to appropriately constrain the model.

First, in the most general (descriptive) formulation of the Boboeva et al. model, on a fraction of trials items in working memory are replaced by items observed on previous trials. In delayed estimation paradigms, which allow a more direct behavioral readout of memory items on a trial-by-trial basis than the PWM task considered here, reports should therefore be locked to previous items on a fraction of trials rather than display a small but consistent bias towards previous items. However, the latter has been reported (e.g., in primate spatial working memory, Papadimitriou et al., J Neurophysiol 2014). The ready availability of delayed estimation datasets online (e.g., from Rademaker and colleagues, https://osf.io/jmkc9/) will facilitate in-depth investigation and reconciliation of this issue.

Second, the bulk of the modeling efforts presented here are devoted to a circuit-level description of how putative posterior parietal cortex (PPC) and working-memory (WM) related networks may interact to produce such volatility and biases in memory. This effort is extremely useful because it allows the model to be constrained by neural observations and manipulations in addition to behavior, and the authors begin this line of inquiry here (by showing that the circuit model can account for effects of optogenetic inactivation of rodent PPC). Further experiments, particularly electrophysiology in PPC and WM-related areas, will allow further validation of the circuit model. For example, the model makes the strong prediction that WM-related activity should display 'jumps' to states reflecting previously presented items on some trials. This hypothesis is readily testable using modern high-density recording techniques and single-trial analyses.

Finally, while there has been a refreshing movement away from an overreliance on p-values in recent years (e.g., Amrhein et al., PeerJ 2017), hypothesis testing, when used appropriately, provides the reader with useful information about the amount of variability in experimental datasets. While the excellent visualizations and apparently strong effect sizes in the paper mitigate the need for p-values to an extent, the paucity of statistical analysis does impede interpretation of a number of panels in the paper (e.g., the results for the negatively skewed distribution in 5D, the reliability of the attractive effects in 6a/b for 2- and 3- trials back).

Reviewer #2 (Public Review):

This work describes transcriptome profiling of dissected skin of zebrafish at post-embryonic stages, at a time when adult structures and patterns are forming. The authors have used the state-of-the-art combinatorial indexing RNA-seq approach to generate single cell (nucleus) resolution. The data appears robust and is coherent across the four different genotypes used by the authors.

The authors present the data in a logical and accessible manner, with appropriate reference to the anatomy. They include helpful images of the biology and schematics to illustrate their interpretations.

The datasets are then interrogated to define cell and signalling relationships between skin compartments in six diverse contexts. The hypotheses generated from the datasets are then tested experimentally. Overall, the experiments are appropriate and rigorously performed. They ask very interesting questions of interactions in the skin and identify novel and specific mechanisms. They validate these well.

The authors use their datasets to define lineage relationships in the dermal scales and also in the epidermis. They show that circumferential pre-scale forming cells are precursors of focal scale forming cells while there appeared a more discontinuous relationship between lineages in the epidermis.

The authors present transcriptome evidence for enamel deposition function in epidermal subdomains. This is convincingly confirmed with an ameloblastin in situ. They further demonstrate distinct expression of SCPP and collagen genes in the SFC regions.

The authors then demonstrate that Eda and TH signalling to the basal epidermal cells generates FGF and PDGF ligands to signal to surrounding mesenchyme, regulating SFC differentiation and dermal stratification respectively.

Finally, they exploit RNA-seq data performed in parallel in the bnc2 mutants to identify the hypodermal cells as critical regulators of pigment patterning and define the signalling systems used.

Whilst these six interactions in the skin are disparate, the stories are unified by use of the sci-RNA-seq data to define interactions. Overall, it's an assembly of work which identifies novel and interesting cell interactions and cross-talk mechanisms.

The paper provides robust evidence of cell interrelationships in the skin undergoing morphogenesis and will be a welcome dataset for the field.

Reviewer #2 (Public Review):

Raymond Laboy et.al explored how transcriptional Mondo/Max-like complex (MML-1/MXL-2) is regulated by glucose metabolic signals using germ-line removal longevity model. They believed that MML-1/MXL-2 integrated multiple longevity pathways through nutrient sensing and therefore screened the glucose metabolic enzymes that regulated MML-1 nuclear localization. Hexokinase 1 and 2 were identified as the most vigorous regulators, which function through mitochondrial beta-oxidation and the pentose phosphate pathway (PPP), respectively. MML-1 localized to mitochondria associated with lipid droplets (LD), and MML-1 nuclear localization was correlated with LD size and metabolism. Their findings are interesting and may help us to further explore the mechanisms in multiple longevity models, however, the study is not complete and the working model remains obscure. For example, the exact metabolites that account for the direct regulation of MML-1 were not identified, and more detailed studies of the related cellular processes are needed.

The identification of responsible metabolites is necessary since multiple pieces of evidence from the study suggests that lipid other than glucose metabolites may be more likely to be the direct regulator of MML-1 and HXK regulate MML-1 indirectly by affecting the lipid metabolism: 1) inhibiting the PPP is sufficient to rescue MML-1 function independent of G6P levels; 2) HXK-1 regulates MML-1 by increasing fatty acid beta-oxidation; 3) LD size correlates with MML-1 nuclear localization and LD metabolism can directly regulate MML-1. The identification of metabolites will be helpful for understanding the mechanism.

Beta-oxidation and the PPP are involved in the regulation of MML-1 by HXK-1 and HXK-2, respectively. But how these two pathways participate in the regulation is not clear. Is it the beta-oxidation rate or the intermediate metabolites that matters? As for the PPP, it provides substrates for nucleotide synthesis and also its product NADPH is essential for redox balance. Is one of the metabolites or the NADPH levels involved in MML-1 regulation? More studies are needed to provide answers to these concerns.