Reviewer #1 (Public Review):

Utilizing mouse models as well as in-vitro studies, the authors demonstrate that cardiac cell mapping provides novel insights into intercellular communication drivers underlying pathological extracellular matrix remodeling during diabetic myocardial fibrosis.The work provides new perspectives to help understanding the cellular and molecular mechanisms of diabetes-induced cardiac pathology.

Reviewer #1 (Public Review):

Han et al use sophisticated genetic approaches to investigate leptin-responsive neural circuits. Overall, this is an impressive series of studies that provide fairly convincing evidence for a key inhibitory pathway downstream of AGRP neurons. A few data sets require additional validation or explanation.

Reviewer #1 (Public Review):

Demographic inference is a notoriously difficult problem in population genetics, especially for non-model systems in which key population genetic parameters are often unknown and where the reality is always a lot more complex than the model. In this study, Rose et al. provided an elegant solution to these challenges in their analysis of the evolutionary history of human specialization in Ae. aegypti mosquitoes. They first applied state-of-the-art statistical phasing methods to obtain haplotype information in previously published mosquito sequences. Using this phased data, they conducted cross-coalescent and isolation-with-migration analyses, and they innovatively took advantage of a known historical event, i.e., the spread of Ae. aegypti to South America, to infer the key model parameters of generation time and mutation rate. With these parameters, they were able to confirm a previous hypothesis, which suggests that human specialists evolved at the end of the African Humid Period around 5,000 years ago when Ae. aegypti mosquitoes in the Sahel region had to adapt to human-derived water storage as their breeding sites during intense dry seasons. The authors further carried out an ancestry tract length analysis, showing that human specialists have recently introgressed into Ae. aegypti population in West African cities in the past 20-40 years, likely driven by rapid urbanization in these cities.

Given all the complexities and uncertainties in the system, the authors have done outstanding jobs coming up with well-informed research questions and hypotheses, carrying out analyses that are most appropriate to their questions, and presenting their findings in a clear and compelling fashion. Their results reveal the deep connections between mosquito evolution and past climate change as well as human history and demonstrate that future mosquito control strategies should take these important interactions into account, especially in the face of ongoing climate change and urbanization. Methodologically, the analytical approach presented in this paper will be of broad interest to population geneticists working on demographic inference in a diversity of non-model organisms.

In my opinion, the only major aspect that this paper can still benefit from is more explicit and in-depth communication and discussion about the assumptions made in the analyses and the uncertainties of the results. There is currently one short paragraph on this in the discussion section, but I think several other assumptions and sources of uncertainties could be included, and a few of them may benefit from some quantitative sensitivity analyses. To be clear, I don't think that most of these will have a huge impact on the main results, but some explicit clarification from the authors would be useful. Below are some examples:

1. Phasing accuracy: statistical phasing is a relatively new tool for non-model species, and it is unclear from the manuscript how accurate it is given the sample size, sequencing depth, population structure, genetic diversity, and levels of linkage disequilibrium in the study system. If authors would like to inspire broader adoption of this workflow, it would be very helpful if they could also briefly discuss the key characteristics of a study system that could make phasing successful/difficult, and how sensitive cross-coalescent analyses are to phasing accuracy.

2. Estimation of mutation rate and generation time: the estimation of these important parameters is made based on the assumption that they should maximize the overlap between the distribution of estimated migration rate and the number of enslaved people crossing the Atlantic, but how reasonable is this assumption, and how much would the violation of this assumption affect the main result? Particularly, in the MSMC-IM paper (Wang et al. 2020, Fig 2A), even with a simulated clean split scenario, the estimated migration rate would have a wide distribution with a lot of uncertainty on both sides, so I believe that the exact meaning and limitations of such estimated migration rate over time should be clarified. This discussion would also be very helpful to readers who are thinking about using similar methods in their studies. Furthermore, the authors have taken 15 generations per year as their chosen generation time and based their mutation rate estimates on this assumption, but how much will the violation of this assumption affect the result?

3. The effect of selection: all analyses in this paper assume that no selection is at play, and the authors have excluded loci previously found to be under selection from these analyses, but how effective is this? In the ancestry tract length analysis, in particular, the authors have found that the human-specialist ancestry tends to concentrate in key genomic regions and suggested that selection could explain this, but doesn't this mean that excluding known loci under selection was insufficient? If the selection has indeed played an important role at a genome-wide level, how would it affect the main results (qualitatively)?

Reviewer #1 (Public Review):

In this manuscript Sugatha et al. present a comprehensive study on sorting nexin 32 (SNX32) with a wide-spectrum of methodologies and model systems. Authors investigate binding to other sorting nexins involved in the same pathways (SNX1 and SNX4) as well as to its cargo in biochemical and cell-based experiments. They show the importance and explore mechanisms of SNX32 in Transferrin Receptor and Cation Independent Mannose-6-Phosphate Receptor trafficking. Moreover, this work also demonstrates the role of SNX32 in concert with Basigin in neuron differentiation.

Authors with the help of structure modelling and subsequent biochemical experiments find specific residues within the BAR domain of SNX32 that are crucial for heterodimer formation with its interaction partners on endosomal membranes: SNX1 and SNX4. Moreover, this study, by using various microscopy techniques, also demonstrates localization of SNX32 to early endosomes as well as its co-trafficking with Rab11 and Golgi marker. Furthermore, authors with knock-down and rescue experiments investigate the role of SNX32 in Transferrin Receptor and Cation Independent Mannose-6-Phosphate Receptor trafficking. With co-immunoprecipitation they show that the cargo interaction occurs via the conserved stretch in the PX domain and that single amino acid substitution can disrupt this binding. This feature is utilized in a subsequent neuroblastoma cell-based SILAC screen for SNX32 interactome that identifies Basigin (a transmembrane receptor belonging to the superfamily of immunoglobulins) as one of the most prominent interactors in these cells. Finally, authors identify SNX32 and Basigin as crucial factors involved in neurite outgrowth and network formation. Experiments demonstrate that SNX32, but not its homolog SNX6, assists in the surface localization of Basigin where this protein could potentially interact with monocarboxylate transporters crucial for neuro-glial coordination.

Reviewer #1 (Public Review):

This is a carefully written manuscript describing the structure of a low-light inducible PSI complex from Ostreococcus tauri. The work expands our knowledge of how photosynthetic systems react to changes in light conditions and shows how this ecologically important green alga utilizes its unique antenna, Lhcp.

In general, I find that the work described in the manuscript is of high quality. The cryoEM maps obtained by the authors clearly show the addition of lhcp trimers to PSI under low light conditions and the distinction between lhcp1 and lhcp2 appears sound together with the identification of the phosphorylation site and its binding in the PSI complex.

Reviewer #1 (Public Review):

In this article, Sanz Perl and colleagues set out to use a computational whole-brain model to simulate the patterns of functional connectivity (as observed from functional MRI) that characterise different forms of dementia, namely Alzheimer's Disease (AD) and behavioural variant frontotemporal dementia (bvFTD). To overall goal is to develop a paradigm to model a specific disorder, and then develop an in silico assessment of the effects of different interventions. They show that superior fitting of the simulated data to the empirical data of both pathologies can be achieved when a Hopf model of brain activity is informed by patterns of combined AD and bvFTD atrophy, or by the intrinsic organisation of brain regions into canonical resting-state networks. They also show that regional differences in the fitted parameters pertain to AD and bvFTD, both in terms of location, and in terms of dynamical regime. They then use a machine learning algorithm, the variational auto-encoder (VAE), to compress functional connectivity patterns into a 2-dimensional space (given by the relative activation of the VAE's two hidden neurons). This space reveals that AD and bvFTD perturb brain connectivity along two distinct dimensions, further stratifying sub-categories of AD. Finally, through visualisation in this latent space, the authors can assess the effects of different simulated interventions on the models previously fitted to AD and bvFTD: namely, stimulation of different regions and with different dynamical regimes, to evaluate whether the resulting model is moved closer to the region occupied by healthy controls.

A strength of this work is its creative combination of different modelling approaches, combining the more biologically-informed Hopf model, which incorporates atrophy maps and connectivity, with the VAE for the purpose of dimensionality reduction and visualisation. Another strength is the use of different controls, such as an atrophy map from a different disorder (Parkinson's) or the use of randomised heterogeneities, showing that the improved fit is not just due to increased degrees of freedom: an important concern for high-dimensional models, which the authors lay to rest.

Admittedly, the stimulation paradigm shows limited success at bringing the disorder-fitted models back to the region occupied by controls - except for the AD- sub-category, which is the least affected and shows the most promise in the authors' in-silico trial. The limited success of this approach in this specific context does not invalidate the framework's promise. This may also be attributed to the fact that the authors do not use disease-specific atrophy maps to model AD and bvFTD: rather, they use a single atrophy map obtained by combining the two and use this joint atrophy map both to model AD, and to model bvFTD. Likewise, the connectivity of the model is the same for all conditions.

A weakness of this work is that, as the authors themselves acknowledge, the brain regions whose stimulation pushes the model to be least far from controls in the latent space did not match with those presenting different bifurcation parameters. In fact, it is not clear whether this is because stimulation fails to reverse the regional alterations of the dynamical regime, or whether it does succeed, but introduces new alterations - although it should be possible to extract this information from the model, to provide additional insight. This raises the intriguing question of the biological meaning of the latent space. Although the authors do show what kinds of FC correspond to the different values of the VAE hidden neurons' activation, the latent space effectively acts as a 2-dimensional goodness-of-fit - raising the question of how much of the stimulation results could be captured by simply evaluating the stimulated model's GOF against controls (while acknowledging that this would conflate the two distinct dimensions along which AD and bvFTD differ from controls).

Since stimulation is intended to mimic the effects of different real-life interventions such as tACS and tDCS, it would be helpful to see whether the regions that are suggested as most promising for stimulation, do in fact match the regions that have shown the most success in actual clinical trials that have already been carried out. This would be a powerful validation from model to real applicability.

In its essence, the work makes progress towards the authors' goal of modelling different pathologies by incorporating biologically-derived information, highlighting their differences, and enabling the evaluation of different stimulation strategies. This computational framework is widely applicable to a variety of pathological (and even non-pathological) conditions, combining evaluation and intervention in a single workflow.

Reviewer #1 (Public Review):

In this manuscript the authors use single nucleus sequencing together with in situ to profile neurons from the paraventricular nucleus of the thalamus. The PVT has been implicated in diverse functions and here the authors use snRNAseq to try to assign those functions to distinct cell types within the structure. They first use punches of PVT and iterative clustering and filtering to find neuronal clusters with known PVT markers. Other cell types and neurons from surrounding brain regions were also present in the dataset. These data both support the previous division of PVT neurons into Drd2+/- cells and suggest these two groups can be further subdivided into 5 distinct clusters. In a nice in situ experiment the authors assessed top marker gene expression for each cluster across the anterior-posterior axis of the PVT. This showed that the five types were largely in distinct spatial locations. Follow-up in situ with an additional set of marker genes supported the same conclusion but also showed that expression of single genes even within a cell "type" can vary. The authors discuss how the transcriptomes of the cell types could map onto known function of anterior and posterior PVT neurons. Finally, the authors integrate their sequencing data with a dataset of thalamic neurons with specific known projection patterns. Of the cells that co-cluster between the datasets, they identify specific transcriptomic populations of cells that best overlap different cortical projection patterns. The authors identify Col12a1 as a marker of one particular population of PFC-projecting cells.

The idea of spatial gradients of transcription in brain regions rather than discrete cell "types" has been shown in a number of recent studies that combine transcriptomics and in situ hybridization. Application of this idea to other important functional areas of the brain like the PVT generally enhances understanding of the parcellation of neuronal function. Combining these data with mapping of projection patterns by a lab interested in the function of this region, will be of interest to other researchers who study PVT and its role in brain circuits. The data appear to be of high quality and the discussion is scholarly.

Reviewer #1 (Public Review):

Marjaneh et al. studied the atrial septal variation through QTL mapping of inbred mouse strains which show extremes of septal phenotypes. The analysis discovered many interesting septal QTLs. Furthermore, the authors identified high-confidence candidate deleterious variants through whole genome sequencing of parental strains and analyzed variant architecture across gene features.

Overall, this is a comprehensive study that will provide a useful reference for the field. It will be a useful tool for hypothesis generation, which could lead to research on therapies that target atrial septal or common congenital heart disease.

Reviewer #1 (Public Review):

In this study, single neurons were recorded, using tetrodes, from the parahippocampal cortex of 5 rats navigating a double-Y maze (in which each arm of a Y-maze forks again). The goal was located at any one of the 4 branch terminations, and rats were given partial information in the form of a light cue that indicated whether the reward was on the right or left side of the maze. The second decision point was uncued and the rat had no way of knowing which of the two branches was correct, so this phase of the task was more akin to foraging. Following the outbound journey, with or without reward, the rat had to return (inbound journey) to the maze and start to begin again.

Neuronal activity was assessed for correlations with multiple navigation-relevant variables including location, head direction, speed, reward side, and goal location. The main finding is that a high proportion of neurons showed an increase in firing rate when the animal made a wrong turn at the first branch point (the one in which the correct decision was signalled). This increase, which the authors call rate remapping, persisted throughout the inbound journey as well. It was also found that head direction neurons (assessed by recording in an open field arena) in the same location in the room were more likely to show the rate change. The overall conclusion is that "during goal-directed navigation, parahippocampal neurons encode error information reflective of an animal's behavioral performance" or are "nodes in the transmission of behaviorally relevant variables during goal-directed navigation."

Overall I think this is a well-conducted study investigating an important class of neural representation: namely, the substrate for spatial orientation and navigation. The analyses are very sophisticated - possibly a little too much so, as the basic findings are relatively straightforward and the analyses take quite a bit of work to understand. A difficulty with the study is that it was exploratory (observational) rather than hypothesis-driven. Thus, the findings reveal correlations in the data but do not allow us to infer causal relationships. That said, the observation of increased firing in a subset of neurons following an erroneous choice is potentially interesting. However, the effect seems small. What were the actual firing rate values in Hz, and what was the effect size?

I also feel we are lacking information about the underlying behavior that accompanies these firing rate effects. The authors say "one possibility is that the head-direction signal in the parahippocampal region reflects a behavioral state related to the navigational choice or the lack of commitment to a particular navigational route" which is a good thought and raises the possibility that on error trials, rats are more uncertain and turn their heads more (vicarious trial and error) and thus sample the preferred firing direction more thoroughly. Another possibility is that they run more slowly, which is associated with a higher firing rate in these cells. I think we, therefore, need a better understanding of how behavior differed between error trials in terms of running speed, directional sampling, etc. A few good, convincing raw-data plots showing a remapping neuron on an error trial and a correct trial on the same arm would also be helpful (the spike plots were too tiny to get a good sense of this: fewer, larger ones would be more helpful). It would be useful to know at what point the elevated response returned to baseline, how - was it when the next trial began, and was the drop gradual (suggesting perhaps a more neurohumoral response) or sudden.

Reviewer #1 (Public Review):

In this paper, the authors present evidence from studies of biopsies from human subject and muscles from young and older mice that the enzyme glutathione peroxidase 4 (GPx4) is expressed at reduced levels in older organisms associated with elevated levels of lipid peroxides. A series of studies in mice established that genetic reduction of GPx4 and hindlimb unloading each elevated lipid peroxide levels and reduced muscle contractility in young animals. Overexpression of GPx4 or N-acetylcarnosine blocked atrophy and loss of force generating capacity resulting from hindlimb unloading in young mice. Cell culture experiments in C2C12 myotubes were used to develop evidence linking elevated lipid peroxide levels to atrophy using genetic and pharmacologic approaches. Links between autophagy and atrophy were suggested.

Experiments on GPx4 expression levels, lipid peroxide levels, muscle mass and muscle force generating capacity were internally consistent and convincing. I thought the experiments supporting the view that autophagy contributed to atrophy were convincing. The hypothesis that altered lipidation of autophagy factors contributed was tested or supported in my view. Evidence for muscle atrophy in response to genetic or pharmacologic manipulations is a bit inconsistent throughout the paper, possibly because the small N of some experiments does not provide sufficient power to detect observed numeric differences in the means. The pattern of muscle fiber atrophy by fiber type is consistent throughout the paper but there is variability in which comparisons reached the threshold for significance, again, possibly because of the small N of the experiments. I agree with the authors that altered activity of enzymes in the contractile apparatus provides one explanation for the observed weakness but respectfully wish to point out there are others such as impaired excitation-contraction coupling which is well known to occur in aging.

Reviewer #1 (Public Review):

In this study, the authors characterize the impact of histone deacetylation on spatial regulation of gene expression in the early gastrula embryo. They utilize Xenopus tropicalis as a vertebrate model embryo and focus on maternal HDAC1 and HDAC2 deacetylases to characterize the regulatory role of histone acetylation on zygotic transcription. In particular, they are interested in whether this epigenetic mark positively or negatively regulates gene expression for the presumptive germ layer and contributes spatially to cell lineage integrity in gastrulation.

Using gene expression analysis, they find that HDAC1 and HDAC2 are present maternally in the egg and throughout blastula and gastrula stages. By performing HDAC1 ChIP-Seq, they find that the deacetylase is already bound as early as the Stage 8 blastula - time of genome activation - and that HDAC1 peaks located within promoter regions generally increase over time from blastula to early gastrula, Stage 10.5. Interestingly, the binding of HDAC1 is not dependent on the zygotic transcript, as HDAC1 ChIP-seq peaks show little difference upon alpha-amanitin treatment. Many of the HDAC1 peaks correlate with peaks of both FoxH1 and Sox3, suggesting their role in its deacetylase recruitment to the genome. Examination of epigenetic signatures of HDAC1 bound regions using previously published datasets identifies distinct chromatin binding categories: authors find a strong correlation with H3K27-Ac and pan-H3Kac, and that HDAC1 generally binds to regions free of repressive marks such as H3K9-me3. The authors find that a majority of HDAC1 peaks contain H3K27Ac but not H3K37me3 peaks and approximately ten percent of HDAC1 loci have both activating and repressive marks.

The authors investigate a functional role for histone deacetylation by inhibiting it, using the broad inhibitor TSA, and HDAC1 specific inhibitor VPA. Importantly, they spatially characterize pan-H3K acetylation and gene expression changes in animal cag (AC) and vegetal mass (VG) regions on the embryo. These are very useful datasets that provide new insights into how histone acetylation is tied to the maintenance of lineage integrity. At a global level, they find that TSA inhibition leads to gastrulation arrest and leads to widespread upregulation of H3K acetylation (pan-H3Kac); suggesting that proper regulation of histone acetylation is required for development. Further, they find that previously repressed regions, marked by H3K27me3 show the most upregulation of pan-H3Kac upon TSA treatment. Regionally, they find a number of interesting results upon inhibition of histone acetylation. First, TSA treatment causes dysregulation - upregulation - of the animal cap (AC) pan-H3Kac peaks in vegetal mass (VG), and upregulation of VG peaks in the animal cap. This suggests that lineage specifically is likely maintained in part by HDAC-mediated de-acetylation of germ layer genes. Gene expression characterization in AC and VG explants +/- TSA treatment supports this conclusion as inappropriate upregulation of VG gene expression is found in AC and inappropriate upregulation of AC genes is found in VG. Somewhat surprisingly, HDACs also appears to play a positive regulatory role in germ layer expression. Focusing on genes near HDAC1 peaks containing H3K27Ac, the authors show that genes downregulated upon TSA treatment tend to be spatially restricted; downregulated genes in AC tended to be AC genes and downregulated genes in VG tended to be VG genes. This suggests that HDACs play both positive and negative roles in regulating germ layer expression in the gastrula.

Strengths of the work include the demonstration that histone deacetylase HDAC1 binds to the genome by the onset of genome activation, accumulates in promoters as the embryo develops through early gastrula, and that inhibition of histone deacetylation disrupts germ layer lineage integrity. New datasets include ChIP-seq of HDAC1 from blastula to gastrula, panH3Kac ChIP-seq within animal and vegetal regions of the embryo, and regional RNA-seq of embryos with and without TSA inhibition of histone acetylation. This study helps demonstrate and clarify that HDAC enzymes play both a positive and negative role in gene expression regulation, and that histone acetylation is required to maintain spatial specificity of germ layer expression in gastrula. Some of the weaknesses of the work include the correlative nature of the experiments and missing analysis. Overall, the research is interesting and impactful, contributing to a growing body of work about the role of histone acetylation in the spatial regulation of earliest cell fate decisions in the embryo.

Reviewer #1 (Public Review):

In this work, the authors investigated the mechanism by which ions are selected in ATP-gated P2X receptor channels using patch-clamp electrophysiology. P2X receptors are known to be cation-selective channels, but one of them (the P2X5) also displays anion permeability through a molecular mechanism that is unclear. Here, the authors identify in P2X2 a glutamate residue (E17) which plays a critical role in determining ion selectivity. This residue is localized in the intracellular side of the permeating pathway and is part of three large intracellular lateral fenestrations that are thought to be potential exit/entry pathways for ions. The authors elegantly show that when the side chain of E17 was substituted for cysteine, it became accessible to water-soluble, thiol-reactive methanethiosulfonate (MTS) derivatives that were applied from both sides of the membrane. By mutating E17 into lysine, which reverts the charge, they show that mutated channels displayed increased anion permeability, although channels still remained largely cation selective. However, reverting the charge in the mouse P2X5 (K17E and K17D), they provide evidence for a complete ion selectivity switch (that is mutated P2X5 became cation selective). Therefore, although the mechanism by which P2X2 selects cation versus anion still remains incompletely understood, it seems that K17 is a key determinant for P2X5 anion permeability.

The conclusions of this paper are well supported by data. The work should advance our understanding of ion selectivity in P2X receptors and will likely provide the foundation for further studies.

Reviewer #1 (Public Review):

Authors aimed to decode signatures linked to tremor, slowness and effective motor control using different types of signals acquired from a group of Parkinson's disease patients during deep brain stimulation surgery. They were able to identify distinct frequency bands which corresponded to different symptoms and conclude that multi frequency band and cortical decoding surpass single frequency band and subthalamic nucleus-based decoding.

The main strength of the study is the recording types used to decode symptoms emerging during the same experimental task: authors leveraged micro and macro level recordings from the subthalamic nucleus and ECoG recordings from the motor cortex, enabling them to provide decoding performance across distinct recording scales and from two critical structures linked to Parkinson's pathophysiology. This allowed the authors to contrast rhythm-based signatures and timescales of Parkinson's disease motor symptoms.

The primary weakness is the level of description used to describe key methods which makes it difficult to unpack the results: authors should pay particular attention to validating and justifying metrics used for assessing behaviour (e.g., tremor, slowness, and effective motor control). Also, the relationship between behavioural measures and UPDRS scores should be further justified. For instance, (1) what is the definition of tremor amplitude probability density in the absence of tremor and what is its relationship to relevant subcategories of clinical tremor severity?; (2) why did the authors link tremor while performing a task to UPDRS rest tremor scores? ; (3) why did the authors opt for normalised cursor speed as a metric for slowness?; (4) Are there any implications of this normalisation when exploring slowness across participants? Authors consider cortical and subthalamic recordings separately: if these recordings were acquired simultaneously, analysing the relationship between the two signals (i.e., envelope, phase, phase-amplitude) would significantly improve the paper.

Authors aimed to decode signatures linked to different symptoms of Parkinson's disease. Results support their primary conclusions that cortical decoding performs better than subthalamic decoding and that using a multi-dimensional feature space improves the performance of the decoder. The paper and data generated will contribute to movement control, movement disorders, and brain stimulation fields.

Reviewer #1 (Public Review):

Temporal patterning allows a neural stem cell to generate different neural identities through the course of development. While this relationship has been demonstrated in many instances of stem cells and/or neurons, it is unclear how birth order translates to target specification. In this manuscript, the authors use live imaging and new tools generated from single-cell RNA sequencing data to address this issue.

They find that neurons born from a given time window (at the resolution of early>middle>late) innervate together - and distinctly from - those born at different temporal windows, though the specifics of the innervations differ between neural stem cell lineages. They also find that neurons achieve this by extending their dendrites in exploratory directions and selectively stabilising the ones in the appropriate direction. This process likely occurs at the sub-second timescales. Finally, they also demonstrate that embryonic-born (larval-specific) neurons that remodel to integrate into adulty-specific circuitry simultaneously perform pruning and dendrite extension to integrate into the circuitry at the appropriate time.

This is a valuable description of how developmental programmes imparted to neurons at the time of their birth might translate to their targetting and connectivity. It lays down a framework for understanding the defects in these processes.

Reviewer #1 (Public Review):

Previous studies from this group reported that PEG10 is increased in the spinal cord from Ubiquilin 2-/- mice as well as PEG10 being elevated in models of Ubiquilin 2-mediated ALS. In this study, the authors provide evidence supporting the concept that the proteasome factor Ubiquilin 2 regulates the activity of the Gag-pol retrotransposon gene (PEG10). Mutations in Ubiquilin 2 underlie a portion of the familial forms of ALS. It is found that in spinal cord tissue from sporadic ALS patients PEG10-pol levels are elevated, leading to the conclusion that altered regulation of PEG10 levels by Ubiquilin 2 and a subsequent alteration in genes regulating axon remodeling may contribute to all forms of ALS pathogenesis. Strengths of this work include the extensive analyses and direct data on the mechanism by which Ubiquilin 2 regulates PEG10 levels in human cells resulting in less PEG10. They further show that peptides generated by the self-cleavage of PEG10 alter the expression of genes involved in axon function. The major weakness of this study is the complete absence of data that directly show that an alteration of PEG10 by Ubiquilin 2 is critical for ALS pathogenesis. As noted by the authors, multiple pathways have been broadly implicated in genetics and sporadic forms of ALS. Thus while the study provides interesting data on the regulation of PEG10 by Ubiquilin 2, the extent to which this pathway underlies ALS pathogenesis and/or progression is speculative.

Reviewer #1 (Public Review):

In this study, Jigo et al. measured the entire contrast sensitivity function and manipulated eccentricity and stimulus size to assess changes in contrast sensitivity and acuity for different eccentricities and polar angles. They found that CSFs decreased with eccentricity, but to a lesser extent after M scaling while compensating for striate-cortical magnification around the polar angle of the visual field did not equate to contrast sensitivity.

In this article, the authors used classic psychophysical tests and a simple experimental design to answer the question of whether cortical magnification underlies polar angle asymmetries of contrast sensitivity. Contrast sensitivity is considered to be the most fundamental spatial vision and is important for both normal individuals and clinical patients in ophthalmology. The parametric contrast sensitivity model and the extraction of key CSF attributes help to compare the comparison of the effect of M scaling at different angles. This work can provide a new reference for the study of normal and abnormal space vision.

The conclusions of this paper are mostly well supported by data, but some aspects of data collection and analysis need to be clarified and extended. 1) In addition to the key CSF attributes used in this paper, the area under the CSF curve is a common, global parameter to figure out how contrast sensitivity changes under different conditions. An analysis of the area under the CSF curve is recommended. 2) In Figure 2, CRFs are given for several SFs, but were the CRFs at the cutof-sf well-fitted? The authors should have provided the CRF results and corresponding fits to make their results more solid. 3) The authors suggested that the apparent decrease in HVA extent at high SF may be due to the lower cutoff-SF of the perifoveal VM. Analysis of the correlation between the change in HVA and cutoff SF after M scaling may help to draw more comprehensive conclusions. 4) In Figure 6, it would be desirable to add panels of exact values of HVA and VMA effects for key CSF attributes at different eccentricities, as shown in Figures 4B, D, and F, to make the results more intuitive.

More discussions are needed to interpret the results. 1) Due to the different testing distances in VM and HM, their retinae will be in a different adaptation state, making any comparison between VM and HM tricky. The author should have added a discussion on this issue. 2) In Figure 4, the HVA extent appears to change after M-scaling, although the analysis shows that M-scaling only affects the HVA extent at high SF. In contrast, the range of VMA was almost unchanged. The authors could have discussed more how the HVA and VMA effects behave differently after M-scaling. 3) The results in Figure 4 also show that at 11.3 cpd, the measurement may be inaccurate. This might lead to an inaccurate estimate of the M scaling effect at 11.3 cpd. The authors should discuss this issue more. 4) The different neural image-processing capabilities among locations, which is referred to as the "Qualitative hypothesis", is the main hypothesis explaining the differences around the polar angle of the visual field. To help the reader better understand this concept, the author should provide further discussions.

The authors should also provide more details about their measures. For example, high grayscale is crucial in contrast sensitivity measurements, and the authors should clarify whether the monitor was calibrated with high grayscale or only with 8-bit. Since the main experiment was measuring CS at different locations, it should also be clarified whether the global uniformity of the display was calibrated. In addition, their method of data analysis relies on parametric contrast sensitivity model fitting. One of the concerns is whether there are enough trials for each SF to measure the threshold. The authors should have included in their method the number of trials corresponding to each SF in each CSF curve.

Reviewer #1 (Public Review):

Pasquereau and Turner investigated the encoding of reward and delay information in subthalamic (STN) neurons in behaving macaques. They record during a forced-choice task with three levels of reward and two levels of delay, using rejection rates to model subjective value. Task-dependent neurons, those which encoded reward and/or delay, were identified with a sliding-window regression model. They then investigated the time course of reward and delay information using a principal component analysis approach. They find that the strength of the first and four principal components varies systematically along the anteroposterior axis of the STN, suggesting a spatial distribution of value coding. These data, recorded in a controlled task, add to the understanding of STN function.

The data, collected from a well-defined brain area and with appropriate motor and oculomotor controls included during a straight-forward task, are a good foundation for investigating STN function. However, the statistical procedures used are not completely described and may not be appropriate, particularly in the sliding window analysis. Given this analysis underlies some of the further analyses, it must be clarified or corrected for the conclusions to stand. Further, the analysis only explores the encoding of delay at the time of a cue and does not consider how the value of delay may change over time.

The sliding window analysis, a common approach in investigating time-course data, necessitates multiple comparisons (188 time-bins here) and so requires a controlling procedure to keep the family-wise error-rate low. The authors describe, not completely, how the pre-instruction period was used to establish the boundaries for significance for each coefficient. The pre-instruction period, by the authors' own account, is a period of lower variance and so it would be expected that the boundaries for significance would be lower and the number of task-dependent neurons is therefore an overestimate. The shuffling process the authors use when they determine significance in their principal components analysis is a more appropriate method.

The task design and analysis provide a limited test of delay encoding. As only two levels of delay were tested, it is not possible to directly test whether the subjective discounting function is hyperbolic or exponential and hence whether the delay is encoded subjectively or objectively. Further, the task has several variable interval lengths (hold in: 1.2-2.8 s, short delay: 1.8-2.3 s, long delay: 3.5-4s) that frustrate interpretation. The distribution of these delays is not described, for example as it reads it seems possible that some long delay rewards are delivered with shorter latency between cue and reward than some short delay rewards (1.2 + 3.5 = 4.7s vs. 2.8+2.3 = 5.1 s). The authors have not considered that if the delay value is encoding, then the value, both objectively and subjectively, may be changing as the delay elapses. The variation of these task intervals may have an effect on the value of delay.

The principal components analysis is an interesting way to explore patterns of encoding and the spatial distribution of these patterns. In particular, the finding that Discounting- neurons, those whose firing rate increases with increasing reward cues and decreases with increasing delay cues, are preferentially found in the posterior STN, which the authors demonstrate with both the principal component analysis and the sliding-window classification analysis, challenges previous ideas of STN organization.

Reviewer #1 (Public Review):

In this work, Pan et al. investigate the properties of the underexplored snake venom phosphodiesterase (svPDE) from a genomic, transcriptomic, and structural perspective. These analyses are complemented by comparisons with similar ENPP proteins to better understand the elements that may underline the specific role of svPDE in envenomation. The data support a role for svPDE that may be related to its interactions with partner proteins or due to its phosphodiesterase activity to enhance the cytotoxic effects of other venoms present in the environment.

Overall, the authors have done a good job of investigating the origins and function of svPDE. The evolutionary analyses are adequate and informative, which are expanded by further experiments to determine the structure and interactions of svPDE. The protein-protein interaction experiments and the svPDE activity experiments with different substrate types shed light on the possible role of the protein in the context of its cellular environment and point to the potential role of glycosylation as part of the mode of action of svPDE. These results will pose a good prelude for further research into the mechanism and interactions of svPDE from other species. Further, the mechanistic insights from this work may also help the development of antivenom compounds that target svPDE.

Reviewer #1 (Public Review):

ARL15 forms a complex with the TRPM7 channel and CNNM transporters and is involved in the regulation of the TRPM7 function. To understand the regulatory mechanism, the authors performed biochemical and structural characterizations. In this work, they determined the crystal structure of ARL15 in complex with CNNM2 CBS domain, performed the mutational analysis based on the structure, and successfully revealed the binding mechanism between ARL15 and CNNM.

However, the detailed mechanism of TRPM7 inhibition by ARL15 remains unclear because the structure of TRPM7 in complex with ARL15 is still unknown. Furthermore, despite the structure determination of ARL15 in complex with CNNM, the effect of ARL15 on CNNM function is still unclear.

Nevertheless, the structural information on the ARL15-CNNM complex provided by the authors is valuable for the related research field, and the structure-based CNNM mutants specifically targeting disruption of binding to either ARL15 or PRL would also be useful.

Reviewer #1 (Public Review):

These authors use a mouse model of gestational intermittent hypoxia (GIH), a component of sleep apnea during pregnancy, to test the hypothesis that GIH induces inflammation in the central nervous system that impairs respiratory functions, in a sex-dependent manner. The major finding of this work is that spinal cord inflammation, mainly driven by activated microglia cells, impairs inactivity-induced inspiratory motor facilitation (iMF). The authors successfully test this hypothesis and their results support their conclusion.

Major strengths of this work include a robust study design, a well-defined translational model (GIH that sets on later in pregnancy), complementary biochemical and experimental methods such that correlated findings are followed up by interventional studies, and sufficient power to evaluate sex differences. In particular, the authors note the upregulation of several NF-kB regulates genes and increased concentration expression of inflammatory markers in the spinal cords of male mice. These mice also have deficits in the iMF response. By depleting microglia and blocking Ik-kinases, the authors convincingly demonstrate that the increased spinal inflammation is causative in the disruption of respiratory plasticity.

The major limitation as the manuscript is currently written is a clear rationale for evaluating the iMF response as a primary endpoint. One of the corresponding authors is an expert in iMF, but there is no rationale for why it is expected that this aspect of plasticity might be disrupted. The authors discuss breathing and respiratory function in the introduction, but these have not been measured here. It is not known whether GIH impacts respiratory response or baseline breathing in a spontaneous breathing model, including baseline frequency and tidal volume and the ventilatory responses to hypoxia and hypercapnia. Shortening the introduction to offer a clear rationale would be beneficial, given the wide audience of this journal. The limitations of this model, including vagotomy, mechanical ventilation, hyperoxic ventilation, and recording from the phrenic nerve in lieu of respiratory measures, should also be discussed in the discussion for readers not familiar with this model outside of the respiratory control field.

Reviewer #1 (Public Review):

The paper starts with a general explanation of the method behind temporal response functions (TRFs), an analysis technique for M/EEG data that has led to many new findings in the last few years. The authors touch upon convolution and show how a linear model can be used to model non-linear responses. The methods section provides a practical introduction to the TRF, in which advice on general analysis steps - such as EEG preprocessing and centering the predictor variables - is intertwined with explanations of the use of the toolbox Eelbrain. The results section outlines how to use the outcome of a TRF model to answer (cognitive) neuroscientific questions and provides a comparison between ERPs and TRFs. The discussion section touches upon a couple of considerations, the most important one being a discussion of the Sparsity prior/Boosting algorithm.

A first great merit of this paper is that it manages to clearly explain both the analysis and the important decisions a researcher needs to make in just a few pages. When following the steps outlined in (in particular) the methods section, the researcher will know how to implement a TRF model using Eelbrain, as well as have a general idea about the decisions that one needs to make in the process. Furthermore, the explicit comparison between ERPs and TRFs will help many understand what TRFs are, and in which ways they allow for more fine-grained analysis of the data than ERPs. For these reasons, this work is a suitable starting point for anyone who wants to get started with TRFs, and a good addition to the existing set of papers on this topic, such as Crosse, Di Liberto, Bednar, and Lalor (2016) and Sassenhagen (2019).

An important contribution of this work is the implementation of the Boosting algorithm. Although it is yet to be determined whether this algorithm creates better models of the neural data than previous implementations of the TRF, the authors provide good arguments for the suitability of this algorithm for the analysis of neural time-series data.

On the practical side, the tutorial analyses are well-designed for the target audience, with interpretable questions and contrast relevant to the field of cognitive neuroscience. The corresponding scripts are clear and well-commented. Finally, the implementation of this method in Python will be greatly appreciated - especially by those who do not have access to a MATLAB license.

All in all, this is a highly didactic paper that will help many researchers get started with temporal response functions both theoretically (to understand the method) and practically (to work with the toolbox). As such, this work has the potential to be of great importance in the field of cognitive neuroscience.

Reviewer #1 (Public Review):

The authors propose that the ER-resident large GTPase Sey1, a homolog of mammalian atlastin, localizes to LDs and promotes their association with the Legionella-containing vacuole (LCV); They also propose that the effector LegG1 contributes to this process by activating the host GTPase RanA on the LCV surface. Once LDs associate with the LCV, the authors favor a model where LDs are taken up into the LCV lumen where they are consumed by L. pneumophila as a carbon source. They propose that the fatty acid transporter FadL, Lpg1810, is involved in the transport of palmitate across the bacterial membrane.

Strong points of this study are the use of Dictyostelium as a genetically tractable model system, the finding that FadL and the addition of exogenous palmitate positively affect intracellular bacterial growth, and the fact that LDs can be detected within LCVs which, if confirmed, would be of significant biological importance.

The main concern is that the molecular mechanism underlying LCV-LD dynamics and LD uptake have only been superficially described. It needs to be determined how exactly proteins like Sey1 or LegG1 promote LD recruitment to LCVs. Does this process really depend on Ran GTPases and if so, do constitutively inactive Ran mutants phenocopy the defects? And by what mechanism are LDs delivered across the LCV membrane into their lumen? The authors themselves raise that question in the discussion, but provide no explanation or supporting data. How commonly can LD uptake into LCVs be observed across a population of cells? And are the phenotypes observed upon deletion of Sey1 direct effects, or are global changes in the ER/host cell protein or lipid landscape indirectly causing those phenotypes? These are some of the questions that, once addressed, would improve the impact of this study.

Reviewer #1 (Public Review):

In this manuscript, the authors were trying to achieve the generation of continuous cell lines after lineage-restricted mis-expression of RasV12 in vivo followed by primary cell culture. They used glia-, epithelia-, and muscle-specific Gal4s, to get glial, epithelial, and muscle cell lines, as well as the RU-inducible Gene Switch Gal4, to get neuronal and blood cell lines. They performed RNA-seq analysis of the cell lines and showed that they are most similar to each by principal component analysis. They compared their RNA-seq to the Fly Cell Atlas and showed that the cell lines were quite similar to their in vivo counterparts. They treated cell lines with the steroid hormone ecdysone and found that many of the cell lines differentiate. These cell lines also contain an attP site, allowing for CRISPR-based screens. These cell lines could be passaged for many generations, but robust effects were found in the early passages. These cell lines have been deposited at a public resource center (The Drosophila Genomics Resource Center, DGRC).

The major strengths of the paper include rigorous analysis of characteristics, gene expression, and differentiation potential of the cell lines. There were only a few minor weaknesses related to editorial changes in the manuscript.

The authors provide convincing results that support their conclusions and as such the authors achieved their aims.

This work is likely to have a positive impact on the Drosophila community. These cell lines will serve as a solid foundation for both low- and high-throughput screens.

Reviewer #1 (Public Review):

This study aimed to estimate contact parameters associated with the transmission of SARS-CoV-2 in unvaccinated South African households over one year. The authors found no correlation between the frequency or duration of contacts and infection risk. Similar parameters (e.g., sharing a room with the index patient) also failed to yield an association. Reassuringly, a robust association was found with the Ct of the index case; female sex and individuals aged 13-17 years were also associated with increased risk. In a more general analysis, obesity, age >5 and <60 y, and non-smoking status were associated with increased risk.

Strengths of the study are its relatively large size (131 households involving 497 people) with detailed proximity data; frequent testing to enable high ascertainment of infections; and ability to exclude individuals seropositive at baseline. Additionally, several outcomes were evaluated in the models, partly to accommodate uncertainty in the index case. Different model structures were evaluated to gauge robustness.

Limitations of the study include the fact that many index cases were likely enrolled after their infectious period, and it is possible that apparent secondary cases in the household arose from a shared exposure with the index case but had a longer latent period. Each of these factors could weaken the perceived effect of close contacts. Statistically, there is the vexing question of what age (gender, smoking, etc.) really represents mechanistically, and whether the models may be conditioning on a collider. Another statistical consideration is that many household contacts were excluded from the study because they were seropositive at baseline. In effect, their households may already have been "challenged" with the virus, and there may be heterogeneities in household susceptibility that are not fully considered by the simple exclusion of individuals with evidence of prior infection. Separating these household types in the analysis might have yielded different results.

All that said, it is telling that in these households, infection is not clearly linked to typically defined close contacts. This is an important result that complements other strong evidence that aerosols are the dominant route of transmission for SARS-CoV-2. This information is critical for the design of effective intervention strategies. Additionally, the authors outline how future studies can be designed to improve on this work.

Reviewer #1 (Public Review):

FLC is a gene involved in cold-dependent induction of flowering, as prolonged cold exposure leads to a progressive decrease in the level of this floral repressor as a result of a digital switch from an ON to an OFF state occurring asynchronously in cell populations. In this work, the authors analyze the contribution of analog and digital regulation to FLC expression in the absence of cold exposure. To do so, they use a genetic trick to be able to perform this analysis in the wild-type Ler ecotype where the molecular tools are available to do such an analysis. In Ler, an activator of FLC is missing due to a natural mutation and FLC expression is repressed during vegetative development by a pathway called the autonomous repressive pathway, allowing for a rapid transition to flowering. The authors used two mutant allele in one component of the autonomous pathway, the FCA gene. In the strongest allele, FLC is highly expressed and the plant are late flowering while in the weaker allele FLC shows a weaker expression and the plant requires an intermediate time between Ler and the strong fca allele to flower.

The authors demonstrate that the expression levels of the FLC gene vary quantitatively in the three genetic background they use (Ler and two fca alleles), and that mutating FCA leads to an analog increase in FLC expression. The quantifications performed by the authors indicate that increased level of FLC correlate with a decrease in the proportion of cells that can switch OFF FLC, with the strong fca allele showing a negligible amount of cells that can switch OFF FLC. The authors further measure the half-life of FLC mRNA and FLC protein, and show that FLC expression switch from ON to OFF is a one-way-switching. They used these data to build a computational model of the regulation of FLC expression and show that the model can reproduce the dynamics of FLC protein level at the cell population level in a time-course with measurement at 7, 15 and 21 days after sowing. Taken together their work suggest that, at least in the weak fca mutant, a combination of analog and digital regulation of transcription explains the population-wide dynamics of FLC expression. The authors propose that this regulation could be explained by high level of transcription of FLC preventing the digital switch, as a result of the short half-lives of FLC mRNA and FLC protein.

The finding of this work are potentially of wide interest to understanding transcriptional regulation by providing a functional link between the digital and analog mode of regulation of gene expression. However, the evidence of a link between expression levels resulting from analog regulation and the digital regulation are only partly supported by correlations from cell population-wide analysis of FLC expression. The authors did not provide experiments to more directly test that higher level of transcription could indeed prevent the OFF switch of FLC. It is likely but not shown that the ON to OFF switch of FLC is regulated similarly in the absence of cold exposure (this study) and upon cold exposure. Also, in their model, the authors used the assumption that FLC switches off at division but they do not test this important assumption. Finally it is unclear whether this combination of analog and digital regulation is relevant to FLC regulation in wild-type plants or is only relevant to the laboratory-induced mutants studied in this work.

Reviewer #1 (Public Review):

The authors present a nice collection of analyses identifying the likely causal locus and pigmentation basis underlying color polymorphism in a model aposematic moth system. In general, the writing and presentation are very clear. There are several areas of the text, however, that could benefit from more clarity and attention to detail. Those changes should be very simple for the authors to make.

My primary concern however is the interpretation of their findings, in light of the lack of analysis of recombination, as well as the flanking region of their identified gene duplication. Specifically, while the authors do an OK job characterizing the genomic region 3' of their identified novel insertion/duplication associated with white coloration, I could not find an analysis of the 5' region, in which there could be other functional elements that could give rise to their "complex polymorphism". Additionally, the authors discuss their findings and the potential of their duplicated region to "provide a region of reduced recombination" (lines 249-251). However, they need to be much more clear with the reader that this is a hypothesis that they have not measured (even though they have WGS data from a sufficient number of individuals estimating LD, which I find strange).

Reviewer #1 (Public Review):

In this manuscript the authors proposed a novel system by which they can suppress the expression of any gene of interest precisely and efficiently with a pre-validated, highly specific and efficient synthetic short-hairpin RNA. The idea of identifying potent artificial RNAi (ARTi) triggers is intriguing, and the authors successfully identify six ARTi with robust knockdown efficiency and limited to no off-target effects. As a proof-of-concept, the authors examined three oncology targets for validation, including EGFRdel19 (which already has a clinically approved drug for validation), KRASG12R (for which there are no in vivo compatible inhibitors yet) and STAG1 (which has a synthetic lethal interaction with recurrent loss-of-function mutations of STAG2). The authors demonstrated significant suppression of colony formation and in vivo tumor growth for all three oncology targets.

This novel system could serve as a powerful tool for loss-of-function experiments that are often used to validate a drug target. Not only this tool can be applied in exogenous systems (like EGFRdel19 and KRASG12R in this paper), the authors successfully demonstrated that ARTi can also be used in endogenous systems by CRISPR knocking in the ARTi target sites to the 3'UTR of the gene of interest (like STAG2 in this paper).

ARTi enables specific, efficient, and inducible suppression of these genes of interest, and can potentially improve therapeutic target validations. However, the system cannot be easily generalized as there are some limitations in this system:

• The authors claimed in the introduction sections that CRISPR/Cas9-based methods are associated with off-target effects, however, the author's system requires the use CRISPR/Cas9 to knock out a given endogenous genes or to knock-in ARTi target sites to the 3' UTR of the gene of interest. Though the authors used a transient CRISPR/Cas9 system to minimize the potential off-target effects, the advantages of ARTi over CRISPR are likely less than claimed.

• Instead of generating gene-specific loss-of-function triggers for every new candidate gene, the authors identified a universal and potent ARTi to ensure standardized and controllable knockdown efficiency. It seems this would save time and effort in validating each lost-of-function siRNAs/sgRNAs for each gene. However, users will still have to design and validate the best sgRNA to knock out endogenous genes or to knock in ARTi target sites by CRISPR/Cas9. The latter is by no-means trivial. Users will need to design and clone an expression construct for their cDNA replacement construct of interest, which will still be challenging for big proteins.

• The approach of knocking-out an endogenous gene followed by replacement of a regulatable gene can also be achieved using regulated degrons, and by tet-regulated promoters included in the gene replacement cassette. The authors should include a discussion of the merits of these approaches compared with ARTi.

Often instructive quotations aren't appropriate for the current situation because they have been stripped of their original context which doesn't apply to the new situation in which it is being used.

Reviewer #1 (Public Review):

Van Dongen et al. investigated the methylation signature of smoking found in the blood among monozygotic twins ascertained from the Netherlands Twin Register. With their unique study design (which by design controls for the influence of age and sex), the authors shed light on DNA methylation levels that vary with smoking status, as well as with smoking cessation. The authors novel study design examined of twin pairs concordant or discordant for smoking status (current, former, never). The authors performed an epigenome-wide association study (EWAS) and identified 13 genome-wide significant CpGs that were differentially methylated between the discordant twin current-never smoking pairs. Another EWAS conducted by the authors found 5 additional genome-wide significant CpGs among current-former smoking discordant pairs. Each of the 13 identified CpG sites between current-former twins have been previously identified as associated with smoking. The authors found that 3 of these 13 CpGs are located within 1Mb of a single nucleotide polymorphism (SNP) previously associated with smoking initiation, suggesting a role for the SNP in both genetic susceptibility of smoking as well as methylation. The authors tested for enrichment of the 13 CpGs within traits and pathways and found enrichment among smoking related traits, as well as the dopaminergic synapse pathway. Interestingly, the authors found that twin pairs discordant for former smoking (former smoking-never pair) had methylation levels that nearly returned to baseline (never smoking) after smoking cessation. These data broaden our understanding of methylation signatures in the blood using a concordant/discordant smoking and twin study design. The authors evaluated within-twin pair methylation differences for the 13 significant CpGs and found twins concordant for smoking status had very little difference between their methylation levels, yet those discordant for smoking status had larger differences with the current-never smoking twins having the largest differences. Importantly, using a dataset with both methylation and RNA sequencing data, the authors found higher methylation at three CpGs was associated with lower gene expression providing functional context for their findings. The authors correctly acknowledge the limitations of only having blood to evaluate methylation signatures and using a methylation array rather than bisulfite sequencing.

There are a couple of aspects that would be useful to help with interpretation of their findings, such as whether presentation of a formal test for trend shows a linear relationship between overall DNA methylation and smoking pack-years and smoking quit time. It would help the reader if the authors could put their findings into context with what has been previously identified in studies such as the Framingham Heart Study or the prior twin study with concordant/discordant twins. While the findings are interesting, the moderate sample size and use of a methylation array rather than sequencing may ultimately lead this work to have only moderate impact on the field.

Reviewer #1 (Public Review):

The manuscript by Warren et al., presents evidence suggesting that aberrant Yap signaling plays a role in epithelial progenitor cell dysregulation in lung fibrosis. This work builds on a body of work in the literature that Hippo signaling is aberrantly regulated in idiopathic pulmonary fibrosis. They use a combination of single nuclear and spatial transcriptomics, together with in vivo conditional genetic perturbations of Hippo signaling in mice, to investigate roles for Yap/Taz signaling in alveolar epithelial homeostasis and remodeling associated with exposure to a fibrosing agent, bleomycin. They show that Taz and Tead1/4 are most abundantly expressed by alveolar type 1 (AT1) cells, but Nf2 immunoreactivity (upstream activator of Hippo) is observed predominantly within airway and AT2 cells. Bleomycin exposure was associated with reduced p-Mst in regenerating alveolar epithelium, that inactivation of Yap/Taz arrested AT2>AT1 differentiation, and inactivation of either Nf2 or Mst1/2 promoted AT1 differentiation after bleomycin exposure and reduced matrix deposition/fibrosis. They go on to show that compromised alveolar regeneration resulting from inactivation of Yap/Taz results in enhanced bronchiolization of injured alveoli. Experiments are well designed and include quantitative endpoints where appropriate, data of high quality, and results are generally supportive of conclusions. These studies provide valuable new data relating to roles for the Hippo pathway in regulation of alveolar homeostasis and epithelial regeneration/remodeling in injury/repair and fibrosis.

Reviewer #1 (Public Review):

The authors of the current study investigated the effect of the suspension of the Australian breast, bowel and cervical cancer screening program for 3, 6, 9, or 12 months on cancer outcomes and cancer services.

The major strengths of the current study are the usage of the validated Policy1 modelling platform to estimate the effects of delays in the screening program on cancer outcomes. Furthermore, they described a wide range of different scenarios and looked at all three national screening programs together. A clear and detailed description of the screening programs was given. The results are well-described and detailed.

The authors reached their aim. They showed how a disruption of the breast cancer screening program of 12 months led to less screen-detected and interval invasive cancers, and to an increase in the percentage of tumours with a tumour size of more than 15mm or with nodal involvement. In addition, suspension of the bowel screening program for 12 months led to upstaging for 891 tumors. Suspension of the cervix screening program for 12 months let to 27 upstaged tumors, and to 69 extra tumors. On the contrary, suspension of the breast screening for 3 months did not lead to a higher percentage of tumours with a tumor size of more than 15 mm or to a higher percentage of tumors with nodal involvement. Suspension of the bowel screening program for 3 months led to upstaging of 261 tumors, and suspension of the cervical screening program for 6 months led to 21 extra tumors and to 9 upstaged tumors. The conclusion of the authors that 'maintaining screening participation is critical to reducing the burden of cancer at a population level' is therefore not completely correct, as suspension for 3 months might be needed in situations with limited resources and will not have a very large impact on the cancer burden.

This paper predicts upstaging due to the disruptions in the screening program. This information can be used by hospitals so they know what they can expect, and can be used in the future if decisions need to made about suspending the screening program.

Reviewer #1 (Public Review):

Overall, the paper by Dang and colleagues is an interesting addition to the field. This study investigates the relationship between socioeconomic status and lifetime obesity using group-based trajectory modeling. The authors identified three trajectories overall, the most prevalent being stable normal BMI. Overall, higher SES was associated with a greater risk of obesity, which is contradictory to studies that examine the relationship among developed countries. Their findings and conclusions are supported by their analysis/data, however, some consideration and additional details are needed to help understand and be more confident in the final results.

Strengths of this study include:

- The use of novel techniques to investigate the relationship between SES and lifetime obesity, which is important for understanding the life course of disease and for designing future public health interventions and strategies.<br /> - A large sample size.<br /> - The use of a population-based sampling strategy to recruit participants, which helps the generalizability of findings and limits volunteer bias.<br /> - The availability of data on SES and height/weight over a 20-year follow-up, including objectively measured weight and height.<br /> - The availability of important confounders (e.g., physical activity, energy intake).

While overall it is an interesting study, there are some considerations and unclarities that should be addressed.

Weaknesses of this study include:

- Lack of clarity on how the authors conceptualize and define socioeconomic status in some sections of the paper. A limitation is the definition of SES only encompasses educational attainment and occupation, and not other aspects (e.g. income, social class). However, most studies published to date also focus mostly on education and occupation.<br /> - A large majority (~90%) of participants were excluded from the analysis due to missing data on exposures and outcomes. This is a substantial proportion, and it is quite possible that this may have resulted in selection bias for those included vs. those not included, and may limit the generalizability of the findings.<br /> - As with all studies that use self-reported data, there is some potential for information bias. However, the authors do acknowledge this as a limitation in their study.<br /> - There is a lack of clarity with some of the methods (e.g. how multinomial logistic regression was used, latent classes, and how confounders were chosen). The paper would benefit from the inclusion of these details.

a 6. sor első mondata fejezi ki a vers alap helyzetét: Itthon vagyok : ezt a gondolatot fejti ki a költő a következő pár sorban, apró életképekkel: mit jelent számára a haza? ismerős bokrokat, házakat, embereket és ismerős fájdalmakat is, melyeket a háború okozott: a költőt a nyári alkony színei a fehér ház falán a lefolyó vérre emlékeztetik - valószínűleg abban a házban is siratnak valakit, akit a háború szakított el családjától

Reviewer #1 (Public Review)

There has been a lot of work showing that multi-peaked tuning curves contain more information than single peaked ones. If that's the case, why are single-peaked tuning curves ubiquitous in early sensory areas? The answer, as shown clearly in this paper, is that multi-peaked tuning curves are more likely to produce catastrophic errors.

This is an extremely important point, and one that should definitely be communicated to the broader community. And this paper does an OK job doing that. However, it suffers from two (relatively easily fixable) problems:

I. Unless one is an expert, it's very hard to extract why multi-peaked tuning curves lead to catastrophic errors.

II. It's difficult to figure out under what circumstances multi-peaked tuning curves are bad. This is important, because there are a lot of neurons in sensory cortex, and one would like to know whether multi-peaked tuning curves are really a bad idea there.

And here are the fixes:

I. Fig. 1c is a missed opportunity to explain what's really going on, which is that on any particular trial the positions of the peaks of the log likelihood can shift in both phase and amplitude (with phase being more important). However Fig. 1c shows the average log likelihood, which makes it hard to understands what goes wrong. It would really help if Fig. 1c were expanded into its own large figure, with sample log likelihoods showing catastrophic errors for multi-peaked tuning curves but not for single peaked ones. You could also indicate why, when multi-peaked tuning curves do give the right answer, the error tends to be small.

II. What the reader really wants to know is: would sensory processing in real brains be more efficient if multi-peaked tuning curves were used? That's certainly hard to answer in all generality, but you could make a comparison between a code with single peaked tuning curves and a _good_ code with multi-peaked tuning curves. My guess is that a good code would have lambda_1=1 and c around 0.5 (you could use the module ratio the grid cell people came up with -- I think 1/sqrt(2) -- although I doubt if it matters much). My guess is that it's the total number of spikes, rather than the number of neurons, that matters. Some metric of performance (see point 1 below) versus the contrast of the stimulus and the number of spikes would be invaluable.

Reviewer #1 (Public Review):

Buglak et al. describe a role for the nuclear envelope protein Sun1 in endothelial mechanotransduction and vascular development. The study provides a full mechanistic investigation of how Sun1 is achieving its function, which supports the concept that nuclear anchoring is important for proper mechanosensing and junctional organization. The experiments have been well designed and were quantified based on independent experiments. The experiments are convincing and of high quality and include Sun1 depletion in endothelial cell cultures, zebrafish, and in endothelial-specific inducible knockouts in mice.

Reviewer #1 (Public Review):

In mammals, a small subset of genes undergoes canonical genomic imprinting, with highly biased expression in function of parent of origin allele. Recent studies, using polymorphic mouse embryos and tissues, have reevaluating the number of allele-specific expressed genes (ASE) to 3 times more than previously thought, however with most of these novel genes showing a very low ASE (50%-60% bias toward one parental allele). Here, the authors undergo a comparison of 4 datasets and complete bioinformatic reanalysis of 3 recent allele specific RNAseq to study potential novel imprinted genes, using recently released iSoLDE pipeline. Very few genes have been confirmed with true ASE in the different studies and/or validated by pyrosequencing analysis, However, the authors show that most of the newly discovered ASE genes are lying in close proximity of already known imprinted loci and could be co-regulated by these imprinted clusters. This is important to understand how and to which extent imprinted control regions control gene expression.

This manuscript highlights the number of potential false discovered imprinted genes in previous datasets that could result to either lack of replicates, weak allelic ratio or low gene expression and lack of read depth. But the lack of overlap in the ASE called genes (at the exception to the known imprinted genes) between the different datasets is worrying and important to discuss, as the authors did. I would have appreciated more details into the differences between the different datasets that could explain the lack of reproducibility : library preparation protocol, sequencer technology, SNP calling, number of reads per SNP, bioinformatics pipeline.

Studying allele specific expression of lowly expressed genes is difficult by technology based on PCR amplification (library preparation, pyrosequencing) and could result on a bias expression only due to the random amplification of a small pool of molecules. Could the author compare the level of expression of their different classes of genes? The more robust ASE genes in their study could be the more highly expressed? Several genes were identified only in one or two of the previous studies, were they expressed in the other studies when not define as ASE? This would also allow defining a threshold of expression to study allelic bias in the future. To conclude, this study is an important resource for the epigenetic field and better understand genomic imprinting.

Reviewer #1 (Public Review):

In humans, mutations in specific ribosomal protein genes and ribosome assembly factors cause a group of diseases collectively known as ribosomopathies. Patients with these diseases typically display a number of remarkably similar tissue specific phenotypes including anemia and craniofacial abnormalities. The causes of the tissue specificity of these disorders have long remained an outstanding question in the field, and more recent evidence points to the induction of nucleolar stress which triggers a p53-dependent response and cell death. In previous work, the authors have shown that loss and gain of Drosophila Rps12 causes a number of unexpected phenotypes. This current paper seeks to investigate the function of Rps12 in mice.

The authors generate a conditional knockout allele within the mouse Rps12 locus and show that homozygous loss of Rps12 results in early embryonic lethality, while heterozygous mutants display a number of cell specific defects in the hematopoietic system. The authors provide evidence that haploinsufficiency of Rps12 results in erythropoiesis defects that worsen with age, a decrease in the number of hematopoietic progenitor cells, and disruption of hematopoietic stem cell (HSC) quiescence correlated with a failure of mutant HSCs to reconstitute peripheral blood. Strikingly, loss of Rps12 results in increased translation in HSCs and early progenitors, marked by activation of MEK/ERK and ARK/TOR signaling pathways.

Strengths<br /> The paper provides new evidence that loss of Rps12 results in a number of specific defects in the hematopoietic system. The phenotypic characterization is rigorous and clearly described in the text. The observations Rps12 heterozygotes exhibit increases in protein synthesis and loss of HSC quiescence are interesting and warrant further investigation. This paper will have broad appeal to those interested in development, stem cell maintenance, ribosome biology, and ribosomopathies.

Weaknesses<br /> The Rps12 gene has two embedded snoRNAs, the disruption of which could contribute to all of the described phenotypes. Additional work is needed to confirm that the mutant phenotypes are caused specifically by loss of Rps12

Reviewer #1 (Public Review):

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

Strengths:

The technical advances in the measurement of animal interactions with food will help advance the understanding of feeding behavior and motivational states.

The correlation of specific types of food interactions across satiation state, sex, and circadian time will help drive forward the understanding of the scope of an animal's goals with feeding, and likely their relation between species and eating disorders.

The assessment of mushroom body circuitry in a type of food interaction is helpful for understanding the coding of feeding control in the brain.

Limitations:

All feeding data presented in the manuscript are from the interactions of individual flies with a source of liquid food, where interaction is defined as 'physical contact of a specific duration.' It would be helpful to approach the measurement of feeding from multiple angles to form the notion of hedonic feeding since the debate around hedonic feeding in Drosophila has been ongoing for some time and remains controversial. One possibility would be to measure food intake volumetrically in addition to food interaction patterns and durations (e.g. via the modified CAFE assay used by Ja).

Some of the statistical analyses were presented in a way that may make understanding the data unnecessarily difficult for readers. Examples include:

1) In Table I the authors present food interaction classifications based on direct observation. These are helpful. However, the classification system is updated or incompletely used as the manuscript progresses, most importantly changing from four categories with seven total subcategories to three categories and no subcategories. In subsequent data analyses, only one or two of these categories are assessed. It would be helpful, especially when moving from direct observation to automated categorization, to quantify the exact correspondences between all of the prior and new classifications, as well as elaborate on the types of data that are being excluded.

2) The authors switch between a variety of biological and physiological conditions with varying assays, which makes following the train of reasoning nearly impossible to follow. For example, the authors introduce us to circadian aspects of feeding behavior to introduce the concept of 'meal' and 'non-meal' periods of the day. It is then not clear in which of the subsequent experiments this paradigm is used to measure food interactions. Is it the majority of the subsequent figure panels? However, the authors also use starved flies for some assays, which would be incompatible with circadian-locked meals. The somewhat random and incompletely reported use of males and females, which the authors show behave differently, also makes the results more difficult to parse. Finally, the authors are comparing within-fly for the 'control environment' and between flies for their 'hedonic environment' (Figure 3A and subsequent panels), which I believe is not a good thing to do.

3) Statistical analyses are not always used consistently. For example, in Figures 3B and C, post hoc test results are shown for sucrose vs. yeast interactions, but no such statistics are given for 3E and 3F, preventing readers from assessing if the assay design is measuring what the authors tell us it is measuring.

Reviewer #1 (Public Review):

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

EDPB rightly smacks the IE SA around a bit for generally cocking this all up.

Now we're moving on to #legitimate_interests and Article 6(1)(f)

Reviewer #1 (Public Review):

This work provides a comprehensive assessment of volumetric-MRI-based brain age estimates in relation to AD-related biomarkers and AD risk factors. Brain age modeling has been studied extensively in recent years. Brain age estimates are suggested surrogate markers for aging-associated changes in the brain. This paper provides findings on how brain age estimates are associated with AD-related amyloid and tau accumulation, cerebrovascular white matter disease, and unspecific neurodegeneration detected by plasma NfL and to some extent CSF NfL as well. The authors also provide important results on sex-specific differences in these associations.

Strengths:

Modeling and analyses were performed on different observational cohorts. Analysis was repeated for the cognitively unimpaired, and individuals with MCI separately.

Weaknesses:

Although the authors concluded that brain age prediction is a biomarker of AlD pathology, only associations were assessed in this study. Further analyses are required to truly assess the biomarker value of brain age prediction for AD pathology.

Reviewer #1 (Public Review):

This study uses a rigorous methodological approach to chart thalamocortical tracts originating from distinct thalamic nuclei, coupled with a model to characterize relative tissue and fluid components along these tracts. This allows a precise description of changes specific to tracts between thalamic nuclei and distinct cortical projection areas. In conjunction with analyses of the microstructure at various distances along the tracts between the thalamus and cortex, these results demonstrate a remarkably consistent organization of thalamic projections as early as 23w, while also highlighting specific gestational-age (GA) dependent processes specific to each tract. This provides a strong step forward in characterizing the development of fetal white matter tracts from non-invasive diffusion MRI data.

Performing detailed neuroimaging analyses of fetal brain development incurs myriad technical challenges, and significant effort has been applied to overcome these. Nevertheless, several aspects of the approaches employed would benefit from better justification. For example, while acquisition parameters necessarily differ from those used in studies in post-natal developmental, or even adult, diffusion MRI studies, this raises several questions regarding the applicability of the modeling analyses employed (in particular, MSMT-CSD with low b-value dMRI data). Additionally, the normalization approach for assessing location-specific differences along each tract is complicated by the gross changes in brain size occurring during this period. Distinguishing the contribution of location-specific changes in microstructure from topographical change (e.g., terminal zones may constitute a smaller relative portion of the tract at later GAs), would enhance the inferences drawn from these results.

It's unclear from the methods how mothers were recruited to get the range of GAs represented, and whether this incurred any demographic correlations to GA. Some more description of recruitment, and a demographic comparison to GA, to clarify that there was not likely to be bias in who was scanned at different times (e.g., 2nd vs 3rd trimester) would strengthen the generalizability of these results.

The statistical basis for comparison among GA groups in the analysis of location-dependent changes in microstructure is not clear. E.g., the characterization of the depths at which GA-dependent differences in tissue fraction occur should be more clearly laid out, such that these observations can be demonstrated quantitatively, rather than reported descriptively.

Reviewer #1 (Public Review):

In this manuscript, Harada et al. build upon prior studies in honeybees and mammalian cells that high levels of mannose impair proliferation, glucose entry into glycolysis. Here, they find that an inability to adequately metabolize mannose results in dNTP depletion and impaired DNA synthesis at replication forks, which sensitizes to chemotherapy. They provide solid evidence that dNTP depletion is sufficient to impair proliferation and increase chemosensitivity, although causality in the context of an inability to metabolize mannose is not established.

Strengths:<br /> This is a very rigorous, well-designed study and the findings are valuable and broadly interesting for the metabolism and cancer communities. The methods are comprehensive and the experimental details in the legends are complete.

Weaknesses:<br /> When giving context to their work, the authors focus heavily on what is known about mannose metabolism in honeybees and do not discuss thoroughly what is known in cancer cells, including prior work that performed very in-depth metabolic phenotyping of mannose phosphate isomerase low and high cells. The claim that the activity of the pentose phosphate pathway is not affected by mannose is not completely justified by the data presented, as pathway flux is not examined. Moreover, the mechanistic connection between mannose and dNTP depletion is not established. Finally, causality for dNTP depletion in cell cycle perturbation and chemosensitivity is not established.

Reviewer #1 (Public Review):

It is now widely accepted that the age of the brain can differ from the person's chronological age and neuroimaging methods are ideally suited to analyze the brain age and associated biomarkers. Preclinical studies of rodent models with appropriate neuroimaging do attest that lifestyle-related prevention approaches may help to slow down brain aging and the potential of BrainAGE as a predictor of age-related health outcomes. However, there is a paucity of data on this in humans. It is in this context the present manuscript receives its due attention.

Comments:

1) Lifestyle intervention benefits need to be analyzed using robust biomarkers which should be profiled non-invasively in a clinical setting. There is increasing evidence of the role of telomere length in brain aging. Gampawar et al (2020) have proposed a hypothesis on the effect of telomeres on brain structure and function over the life span and named it as the "Telomere Brain Axis". In this context, if the authors could measure telomere length before and after lifestyle intervention, this will give a strong biomarker utility and value addition for the lifestyle modification benefits.

2) Authors should also consider measuring BDNF levels before and after lifestyle intervention.

Reviewer #1 (Public Review):

In the paper, the authors illustrated a novel method for Electrolytic Lesioning through a microelectronics array. This novel lesioning technique is able to perform long-term micro-scale local lesions with a fine spatial resolution (mm). In addition, it allows a direct comparison of population neural activity patterns before and after the lesions using electrophysiology. This new technique addresses a recent challenge in the field and provides a precious opportunity to study the natural reorganization/recovery at the neuronal population level after long-term lesions. It will help discover new causal insights investigating the neural circuits controlling behavior.

Several minor concerns are summarized below:

It was not always clear what the lesion size was. This information is important for future applications, for example, in the visual cortex, where neurons are organized in retinotopy patterns.

It would be helpful if the author could add some discussion about whether and how this method could be used in other types of array/multi-contact electrodes, such as passive neuropixels, S-probes, and so on. In addition, though an op-amp was used in the design, it would still be helpful if the author could provide a recommended range for the impedance of the electrodes.

Reviewer #1 (Public Review):

This paper presents a highly compelling and novel hypothesis for how the brain could generate signals to guide navigation towards remembered goals. Under this hypothesis, which the authors call "Endotaxis", the brain co-opts its ancient ability to navigate up odor gradients (chemotaxis) by generating a "virtual odor" that grows stronger the closer the animal is to a goal location. This idea is compelling from an evolutionary perspective and a mechanistic perspective. The paper is well-written and delightful to read.

The authors develop a detailed model of how the brain may perform "Endotaxis", using a variety of interconnected cell types (point, map, and goal cells) to inform the chemotaxis system. They tested the ability of this model to navigate in several state spaces, representing both physical mazes and abstract cognitive tasks. The Endotaxis model performed reasonably well across different environments and different types of goals.

The authors further tested the model using parameter sweeps and discovered a critical level of network gain, beyond which task performance drops. This critical level approximately matched analytical derivations.

My main concern with this paper is that the analysis of the critical gain value (gamma_c) is incomplete, making the implications of these analyses unclear. There are several different reasonable ways in which the Endotaxis map cell representations might be normalized, which I suspect may lead to different results. Specifically, the recurrent connections between map cells may either be an adjacency matrix, or a normalized transition matrix. In the current submission, the recurrent connections are an un-normalized adjacency matrix. In a previous preprint version of the Endotaxis manuscript, the recurrent connections between the map cells were learned using Oja's rule, which results in a normalized state-transition matrix (see "Appendix 5: Endotaxis model and the successor representation" in "Neural learning rules for generating flexible predictions and computing the successor representation", your reference 17). The authors state "In summary, this sensitivity analysis shows that the optimal parameter set for endotaxis does depend on the environment". Is this statement, and the other conclusions of the sensitivity analysis, still true if the learned recurrent connections are a properly normalized state-transition matrix?

Overall, this paper provides a very compelling model for how neural circuits may have evolved the ability to navigate towards remembered goals, using ancient chemotaxis circuits.

This framework will likely be very important for understanding how the hippocampus (and other memory/navigation-related circuits) interfaces with other processes in the brain, giving rise to memory-guided behavior.

Reviewer #1 (Public Review):

stdpopsim is an existing, community-driven resource to support population genetics simulations across multiple species. This paper describes improvements and extensions to this resource and discusses various considerations of relevance to chromosome-scale evolutionary simulations. As such, the paper does not analyse data or present new results but rather serves as a general and useful guide for anyone interested in using the stdpopsim resource or in population genetics simulations in general.

Two new features in stdpopsim are described, which expand the types of evolutionary processes that can be simulated. First, the authors describe the addition of the ability to simulate non-crossover recombination events, i.e. gene conversion, in addition to standard crossover recombination. This will allow for simulations that come closer to the actual recombination processes occurring in many species. Second, the authors mention how genome annotations can now be incorporated into the simulations, to allow different processes to apply to different parts of the genome - however, the authors note that this addition will be further detailed in a separate, future publication. These additions to stdpopsim will certainly be useful to many users and represent a step forward in the degree of ambition for realistic population genetics simulations.

The paper also describes the expansion of the community-curated catalog of pre-defined, ready-to-use simulation set-ups for various species, from the previous 6 to 21 species (though not all new species have demographic models implemented, some have just population genetic parameters such as mutation rates and generation times). For each species, an attempt was made to implement parameters and simulations that are as realistic as possible with respect to what's known about the evolutionary history of that species, using only information that can be traced to the published literature. This process by which this was done appears quite rigorous and includes a quality-control process involving two people. Two examples are given, for Anopheles gambiae and Bos taurus. The detailed discussion of how various population genetic and demographic parameters were extracted from the literature for these two species usefully highlights the numerous non-trivial steps involved and showcases the great deal of care that underlies the stdpopsim resource.

The paper is clearly written and well-referenced, and I have no technical or conceptual concerns. The paper will be useful to anyone interested in population genetics simulations, and will hopefully serve as an inspiration for the broader effort of making simulations increasingly more realistic and flexible, while at the same time trying to make them accessible not just to a small number of experts.

Reviewer #1 (Public Review):

Sun and colleagues outline structural and mechanistic studies of the bacterial adhesin PrgB, an atypical microbial cell surface-anchored polypeptide that binds DNA. The manuscript includes a crystal structure of the Ig-like domains of PrgB, cryo-EM structures of the majority of the intact polypeptide in DNA-bound and free forms, and an assessment of the phenotypes of E. faecalis strains expressing various PrgB mutants.

Generally, the study has been conducted with a good level of rigor, and there is consistency in the findings. However, I do have some specific technical concerns relating to the study. Although the PX work has been expertly undertaken, the Cryo-EM structures reported are both at ~10-angstrom resolution. Visual inspection indicates that the positioning of the PrgB domains into the EM envelopes is somewhat questionable and this needs to be addressed. The narrative of the manuscript very much hinges on this being correct. In addition, wrt the PrgB mutant studies, it could be that the loss of function observed in specific mutants is simply a consequence of mutation-induced misfolding of those polypeptides. Experimental evidence supporting the direct interaction between the PAD and the stalk domains in PrgB is also lacking.

Reviewer #1 (Public Review):

In this study, Dominici et. al. show that small molecule inhibition of Type I PRMTs in muscle stem cells (MSCs) can result in the expansion of this cell type in vitro, solving a major limitation in the field. Importantly, once the inhibitor is removed these stem cell differentiate "normally". This advance will likely facilitate CRISPR-based screening approaches and stem cell engraftment therapy. Furthermore, they show that when a mouse model of Duchenne muscular dystrophy is treated with these same inhibitors these mice rather rapidly gain grip strength, demonstrating the therapeutic value of these findings.

Strengths:

- Previous studies from the same group have shown that the conditional ablation of PRMT1 in MSCs results in the expansion of this cell type, but this expanded PRMT1-null MSC pool cannot terminate the myogenic differentiation program. This raises the question of whether PRMT1 small molecule inhibition of MSCs will also facilitate the expansion of these cells, and if the removal of the inhibitor after expansion will result in a large functional pool of MSCs, which could then be used for both in vitro and in vivo studies.

- Using a combination of muscle fiber culture, myoblast culture and single cell RNA-seq, this is indeed what they show.

- They also perform two types of in vivo experiments to validate their cell culture findings; 1) MSCs expanded under the treatment of MS023 were washed clean of the inhibitor and engrafted into the tibialis anterior muscle. These cells were marked with GFP to allow efficient tracking. Mice receiving the MS023-treated MSCs produced more than double the mature GFP+ muscle fibers than cells treated with DMSO. 2) A mouse model of Duchenne muscular dystrophy displayed grip strength improvement after just one treatment of MS023.

- MS023 is a Type I PRMT inhibitor and thus can also target CARM1. CARM1 has been implicated in MSC function by the Rudnicki group. Importantly, they exclude a role for CARM1 in the expansion of MSC cell number by treatment with a very specific CARM1 inhibitor, TP064. Thus, indicating that PRMT1 inhibition is likely the main driver of this expansion phenotype.

Weaknesses:

- Very few weaknesses.

- The in vivo efficacy of MS023 does not seem to be very great. The mice treated with MS023 display a very small reduction in ADMA levels and a small increase in SDMA levels (Fig S6A).

Reviewer #1 (Public Review):

Using health insurance claims data (from 8M subjects), a retrospective propensity score matched cohort study was performed (450K in both groups) to quantify associations between biphosphonate (BP) use and COVID-19 related outcomes (COVID-19 diagnosis, testing and COVID-19 hospitalization. The observation periods were 1-1-2019 till 2-29-2020 for BP use and from 3-1-2020 and 6-30-2020 for the COVID endpoints. In primary and sensitivity analyses BP use was consistenyl associated with lower odds for COVID-19, testing and COVID-19 hospitalization.

The major strength of this study is the size of the study population, allowing a propensity-based matched-cohort study with 450K in both groups, with a sizeable number of COVID-19 related endpoints. Health insurance claims data were used with the intrinsic risk of some misclassification for exposure. In addition there probably is misclassification of endpoints as testing for COVID-19 was lmimited during the study period. Furthermore, the retrospective nature of the study includes the risk of residual confounding, which has been addressed - to some extent - by sensitivity analyses.

In all analyses there is a consistent finding that BP exposure is associated with reduced odds for COVID-19 related outcomes. The effect size is large, with high precision.

The authors extensively discuss the (many) potential limitations inherent to the study design and conclude that these findings warrant confirmation, preferably in intervention studies. If confirmed BP use could be a powerful adjunt in the prevention of infection and hospitalization due to COVID-19.

DOI: 10.1093/humrep/dead031

Resource: ZFIN_ZDB-ALT-070406-1

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-070406-1

What is this?

Reviewer #1 (Public Review):

This is a welcome contribution investigating proteomics in different physiological muscle types in a particular murine (DHT) Ryr1 abnormality. This recapitulates a particular human clinical condition. It emerges with a comparative analysis of the expression not only of RyR1 protein but also of other functional proteins. The work emerges with insights into pathological mechanism of congenital myopathies linked to mutations in a range of other genes related to excitation contraction coupling.

Reviewer #1 (Public Review):

The authors present normative modeling results using both structural data and functional connectivity data to demonstrate the strength of normative modeling in investigations of group effects, classification tasks, and brain-behavioral modeling. The models are built across 3 large data sets and tested in a rigorous manner. The strengths of this work are in the clarity or presentation, the demonstration of the value of normative modeling, the availability of the models and code, and the statistical rigor supporting the results. The work will have a significant impact on the field in that such models (built in large data sets) can be applied to smaller studies of specific populations of interest, therefore, facilitating research on many populations in a statistically rigorous manner.

Reviewer #1 (Public Review):

This manuscript describes a relatively novel approach to discovering combinations of herbal medications that may help modulate immune responses, and in turn help treat diseases such as cancer. The authors use breast plasma call mastitis as a disease in which they present results from a non-blinded clinical trial with modest results.

The main shortcomings are a lack of rigor around standardizing the control group given steroids versus the treatment group given the combinations of herbal medications. There needs to be a detailed statistical analysis of the comparison in tumor size, stage, invasiveness, etc. as well as consideration of confounding disease states (autoimmune disease, prior cancers, diabetes, etc.). While the results are interesting in that the use of herbal medications is often overlooked in Western medicine, the manuscript needs great detail in the clinical comparison in order to provide convincing evidence for an effect.

Reviewer #1 (Public Review):

In this work, the authors set out to use contact tracing and whole-genome sequencing to track the elimination of dog-mediated rabies in Pemba island, Tanzania. A major strength is the use of multiple data types in the analysis. A major limitation is the rudimentary health economics approach to make claims about the cost-effectiveness of different approaches. The work will likely have an impact on influencing the practical policies that can be implemented to target the elimination of dog-mediated rabies in other regions/contexts.

Reviewer #1 (Public Review):

The authors developed a new concept: Skeletal age, which is chronological age + years lost due to suffering a low-energy fracture.<br /> There seem to be conceptual problems with this concept: It is not known if the years lost are lost due to the fracture or co-morbidities. In addition, with the possible exception of zoledronate after hip fracture, we have no evidence that this increased risk of mortality can be changed with interventions. Furthermore, it is not clear why the authors think that patients and doctors will better understand the implications of older "skeletal age", on future fracture risk and the need for prevention, for example, the 10-year risk of MOF? Knowing that my bones are older than me, could make a patient feel even more fragile and afraid of being physically active. The treatment will reduce the risk of future fractures, but this study provides no information about the effect on mortality of preventing the subsequent fracture or the risk of mortality associated with recurrent fractures.

Introduction:<br /> The statement that treatment reduces the risk of dying, needs modification as the majority of clinical trials have not demonstrated reduced mortality with treatment.<br /> It is not clear how the skeletal age captures the risk of a future fracture. The other difference between the idea of "skeletal age" and for example "heart age" is that there are treatments available for heart disease that reduce the risk of mortality, as mentioned above this has not been shown consistently in clinical trials in osteoporosis.

Discussion:<br /> The prevalent comorbidities; cardiovascular diseases, cancer, and diabetes, suggest that fracture patients die from their comorbidities and not their fractures.<br /> The discussion should be more balanced as there is a number of clinical trials demonstrating reductions in vertebral and non-vertebral fractures without effect on mortality. There may be specific effects of zoledronate on mortality, but that has not been shown for the vast majority of treatments.<br /> It is not correct that FRAX does not take mortality into account? It does not tell you specifically how high the risk of dying and how high the risk of a fracture is but integrates the two. "Skeletal age" does not provide either information, it just tells you that your skeleton is older than your chronological age - most patients and doctors will not associate that with an increased risk of dying - only of frailty.<br /> The statement that zoledronate reduces the "skeletal age" by 3 years, has not been demonstrated and it is not clear how this can be demonstrated by the analysis reported here. As the reduced mortality has only been shown for the Horizon RFT, this cannot be inferred for other treatments and other fracture types.<br /> The information provided by the "skeletal age" is only that the fracture you already had took x years of your remaining lifetime. With the exception of perhaps zoledronate after hip fracture, we have no indication from clinical trials that the treatment of osteoporosis will change this.

Reviewer #1 (Public Review):

The authors demonstrate that modest oscillatory changes in the E-I ratio occur throughout the day and are linked to changes in both synaptic excitation and inhibition. These conclusions were based on adequately sampled electrophysiological data of stimulation-driven and non-evoked excitatory and inhibitory currents. For these studies, a fixed stimulation was not used across slice recordings but was limited to intensities where the E-I ratio was stable. Two points may need further clarification in the text. Firstly, authors might comment on whether current magnitudes plateau at these stimulation intensities. Secondly, make clear why the cause of E-I balance changes was not elucidated from convergent, evoked measurements in the same cell, but instead relied on non-evoked measures of spontaneous miniature excitatory postsynaptic currents and miniature inhibitory postsynaptic currents (mEPSCs and mIPSCs) that were recorded separately in different cell populations. mEPSCs and mIPSCs data analysis relied on statistical scrutiny within genotype and could gain additional rigor and benefits to study reproducibility by applying tests ( e.g. two- way repeated measures (RM) ANOVA) that consider the influence of both genotype and time of day. With this approach, the authors could determine in figures 3 and 4 whether control (B6) mice exhibit the predicted increase in mEPSCs and reduction in mIPSCs at ZT0 when compared to its ASD mouse model. In a noteworthy experiment, the authors connect abnormalities in inhibitory oscillations to altered endocannabinoid signaling using measurements of spontaneous (s) IPSCs, where changes in sIPSC charge were noted. The measurements used to make the paper's conclusion lacked consistency and the authors can bridge these differences by testing whether WIN agonist treatment can restore normal daily E/I oscillation in FMR1 KO and BTBR mice using the stimulation-evoked measurements from figure 1. The study used male and female BTBR mice and only male Fmr1 KO mice. Sex- effects in the study were not disclosed, so it is unclear whether daily E/I oscillation changes were similar in male and female BTBR mice or occur at all in female Fmr1 KO mice. Lastly, numerous studies have noted significant changes in the magnitude of the E-I ratio in an autism mouse model and causally linked these changes to alterations in disorder-related behavior or homeostatic regulation of circuit activity. However, in this current study, neither the loss nor reversal of daily E/I ratio oscillation were causally linked to alterations in sleep timing and architecture or any change in behavioral phenotype. On a promising note, the authors did find a slight decrease in NREM delta power in the Fmr1 KO and a larger decrease in the BTBR mice. Future mechanistic studies on this topic may aim to buttress support for E/I oscillations rather than alterations to the overall E/I level in causing autism-related phenotypes by providing supporting examples of biological significance.

Reviewer #1 (Public Review):

Pathological conformation and aggregation of tau protein are involved in several neurodegenerative diseases such as tauopathies and Alzheimer's disease. Identifying drug-candidates capable of interfering with pathological transformation of tau remains a challenge for which sensitive and specific assays are needed. This article describes the development and characterization of tau biosensors based on NanoBit technology (nanoluciferase complementation). It is a well-designed and precise study providing very interesting new tools.

Strengths<br /> 1/ The authors have developed a variety of tau biosensors: some that can be used for basic research to monitor pathological tau transformation and others with properties suitable for drug screening. All biosensors make it possible to evaluate the action of different agents (chemical products, purified proteins, cell or tissue extracts) in a living cell.

2/ The intermolecular biosensors developed from a shortened version of tau (K18), or the full-length tau, and carrying the P301L mutation possess sensibility and specificity allowing their further development to identify drug-candidates interfering with tau self-interaction.

3/ The characterization of the tau probes confirmed the physiological and pathological knowledge concerning the tau protein: - proximity of full-length tau when bound to microtubules, - conformational changes of tau during its phosphorylation and - tau-self interaction induced by pathological seeds.

Weaknesses<br /> 1/ The suitability of tau biosensors for high-throughput screening needs to be further developed as experiments were only performed in 96-well plates. No scaling up in 384- or 1536-well plates was attempted. Moreover, the transfection of the biosensors could be tedious.

2/ The models used are basic (HEK-293T cells associated with tau aggregates, Aβ oligomers or mouse brain lysates). The number of drugs tested is also quite low.

Collectively, the conclusions drawn by the authors are supported by the results. These new biosensors will be easily usable by the scientific community in fundamental research and could also be of interest to pharmaceutical laboratories wishing to carry out screenings of molecules capable of impacting the pathological transformation of tau.

Reviewer #1 (Public Review):

The authors use a newly developed object-space memory task comprising of a "Stable" version and "Overlapping" version where two objects are presented in two locations per trial in a square open field. Each version consists of 5 training trials of 5-min presentations of an object-space configuration, with both object locations staying constant across training trials in the Stable condition, and only one object location staying fixed in the Overlapping condition. Memory is tested in a test trial 24 hours later where the opposite configuration is presented - overlapping configuration presented for the Stable condition and stable configuration presented for the Overlapping condition - with the thesis that memory in this test trial for the Overlapping condition will depend on the accumulated memory of spatial patterns over the training trials, whereas memory for the test trial in the Stable condition can be due to episodic memory of last trial or accumulated memory. Memory is quantified using a Discrimination Index (DI), comparing the amount of time animals spend exploring the two object locations.

Here, animals in other groups are also presented with an interference trial equivalent to the test trial, to test if the memory of the Overlapping condition can be disrupted. The behavioral data show that for RGS14 over-expressing animals, memory in the Overlapping condition is diminished compared to controls with no interference or controls where over-expression is inhibited, whereas memory in the Stable condition is enhanced. This is interpreted as interference in semantic-like memory formation, whereas one-shot episodic memory is improved. The authors speculate that increased cortical plasticity should lead to increased and larger delta waves according to the sleep homeostasis hypothesis, and observe that instead increased cortical plasticity leads to less non-REM sleep and smaller delta waves, with more prefrontal neurons with slower firing rates (presumably more plastic neurons). They further report increased hippocampal-cortical theta coherence during task and REM sleep, increased NonREM oscillatory coupling, and changes in hippocampal ripples in RGS14 over-expressing animals.

While these results are interesting, there are several issues that need to be addressed, and the link between physiology and behavioral results is unclear.

1) The behavioral results rely on the interpretation that the Overlapping condition corresponds to semantic-like memory and the Stable condition corresponds to episodic-like memory. While the dissociation in memory performance due to interference seen in these two conditions is intriguing, the Stable condition can correspond not just to the memory of the previous trial but also accumulated memory of a stable spatial pattern over the 5 testing trials, similar to accumulated memory of a changing spatial pattern in the Overlapping pattern.

Here, it is puzzling that in the behavioral control with no interference (Figure 1D), memory in the Stable and Overlapping condition is unchanged in the test trial, with the DI statistically at 0 in the test trial. In the original description of the Object Space task by the authors in the referenced paper, the measure of memory was a Discrimination Index significantly higher than 0 in both the Stable and Overlapping conditions. This discrepancy needs to be reconciled. Is the DI for the interference trial shown in Fig. S1 significantly different than 0? No statistics or description is provided in the figure legend here.

2) The physiology experiments compare Home cage (HC) conditions to the Object Space task (OS) throughout the manuscript. While some differences are seen in the control and RGS14 over-expressing animals, there is no comparison of the Stable vs. Overlapping condition in the physiology experiments. This precludes making explicit links between physiological observations and behavioral effects.

3) The authors speculate that learning will result in larger and more delta waves as per the synaptic homeostasis hypothesis. It should be noted here that an alternative hypothesis is that there should also be a selective increase in synaptic plasticity for learning and consolidation. The authors do observe that control animals show more frequent and higher-amplitude delta waves, but rather than enhancing this process, RGS14 animals with increased plasticity show the opposite effect. How can this be reconciled and linked with the behavioral data in the Stable and Overlapping condition? Similarly, there is an increase in slower-firing neurons in RGS14 over-expressing animals. Slower-firing neurons have been proposed to be more plastic in the hippocampus based on their participation in learned hippocampal sequences, but appropriate references or data are needed to support the assertion that slower-firing neurons in the prefrontal cortex are more plastic.

4) It is noted that changing cortical plasticity influences hippocampal-cortical coupling and hippocampal ripples, suggesting a cortical influence on hippocampal physiological patterns. It has been previously shown that disrupting prefrontal cortical activity does alter hippocampal ripples and hippocampal theta sequences (Schmidt et al., 2019; Schmidt and Redish, 2021). The current results should be discussed in this context.

Reviewer #1 (Public Review):

The authors push a fresh perspective with a sufficiently sophisticated and novel methodology. I have some remaining reservations that concern the actual make-up of the data basis and consistency of results between the two (N=16) samples, the statistical analysis, as well as the "travelling" part.

I previously commented on the fact that findings from both datasets were difficult to discern and more effort should be made to highlight these. Also, a major conclusion "the directionality effect [effect of attention on forward waves] only occurs for visual stimulation" only rested on a qualitative comparison between studies. The authors have improved on this here, e.g., by toning down this conclusion. One thing that is still missing is a graphical representation of the data from Foster et al. (the second dataset analysed here) that would support the statistical results and allow the reader a visual comparison between the sets of findings.

Also, for any naive reader, the concept of travelling waves may be hard to grasp in the way data are currently presented - only based on the results of the 2D-FFT. Can forward and backward-travelling waves be illustrated in a representative example to make this more intuitive?

Finally, the way Bayes Factors from the Bayesian ANOVA are presented, especially with those close to the 'meaningful boundaries' ⅓ and 3, as defined in the 'Statistical analysis' section, requires some unification/revision. For example, here: "We found a positive correlation between contra- and ipsi- lateral backward waves, and occipital (all Pearson's r~=0.4, all BFs 10 ~=3) and -to a smaller extent- frontal areas (all Pearson's r~=0.3, all BFs 10 ~=2).", where the second part should strictly be labelled as inconclusive evidence. In the same vein, there is occasional mention of "negative effects", where it should say that evidence favours the absence of an effect.

Reviewer #1 (Public Review):

The manuscript by Silva et al. "Evaluation of the highly conserved S2 hairpin hinge as a pan-coronavirus target" seeks to evaluate a new epitope target on the S2 domain of SARS-CoV2 Spike protein and evaluate its potential as a pan-coronavirus target. This is an impressive combination of extensive structural, HDXMS-based dynamics and antibody engineering approaches. What is missing is a detailed correlation of HDXMS with Spike dynamics. The authors have not examined the allosteric effects of 3A3 binding to the Spike trimer, specifically cooperativity in antibody binding. Does binding of one Fab positively or negatively impact the subsequent binding of antibody? In this regard, readers would benefit from HDXMS spectral envelopes in figures, at least for the epitope locus peptides. Further, what is the effect of the intrinsic ensemble behavior of the Spike protein on 3A3 interactions? In a broader sense antibody binding is assisted by intrinsic trimer ensemble behavior, as observed by the lowered binding to the omicron variant- but are there induced binding effects? It would help to better integrate HDXMS with cryo-EM and antibody engineering. It is a novel, less explored epitope target on the S2 domain. Overall, a more definitive mechanistic conclusion for how targeting the S2 hinge can advance future pan-coronavirus strategies is missing.

Major Comments:

1) Given that the authors have demonstrated ensemble switching behavior from 4 ℃ to 37 ℃ (Costello et al. (2021)) why is this not factored in how the HDXMS is carried out? The samples were stored, frozen at -80 ℃, thawed, and equilibrated for 20 min at 20 ℃ with or without antibody present and analyzed by HDXMS. However, the reported t1/2 for trimer tightening at 37 ℃ is t1/2 = 2.5 h (Supplementary Fig. 7). The samples should ideally be analyzed under standardized conditions with the stable conformer. Sample heterogeneity from HDXMS is likely due to any of the following contributing factors:<br /> i) Intrinsic ensemble heterogeneity (Costello et al. (2021)), Kinetics of RBD- up and down conformational switching<br /> ii) Cooperativity of Fab binding.<br /> iii) Partial occupancy of trimer epitopes with bivalent IgG.<br /> iv) Combination of cooperativity effects and partial binding effects

I would predict for any of the above reasons, it is intriguing why are there no bimodal kinetics of deuterium exchange reported. Partial occupancy should be evident from HDXMS paratope analysis.

2) Pan-coronavirus neutralization potential is clearly evident. It is intriguing that the antibodies were isolated after immunization with an authentic MERS S2 domain but showed better selectivity to full-length 6P-engineered Spike. How is cooperativity built into antibody binding, given that the epitope site is occluded to various extents by the S1 domain and access is contingent upon RBD up-down kinetics?

3) I am surprised that there is no allostery described for 3A3 (Supplementary figures 5, 6).

Reviewer #1 (Public Review):

Nephronophthisis (Nphp) is a multigenic, recessive disorder of the kidney presenting in childhood that is characterized by cysts predominantly at the cortico-medullary junction and progressive fibrosis. An infantile form of the disease presents earlier with more diffuse cystic change. The condition is considered a ciliopathy because most of the genes linked to the condition encode proteins involved in ciliary biogenesis or function. Germline mutations in NPHP2 are associated with a particularly severe, infantile form of the disease. Given that interstitial fibrosis is a more prominent feature of Nphp compared to many other forms of polycystic kidney disease, the authors sought to determine the mutant cell types responsible for the phenotype.

In the current study, the authors generated and characterized mouse lines with Nphp2 selectively inactivated in either renal epithelial cell or stromal cell lineages and found that inactivation in renal epithelial cells was both necessary and sufficient to cause disease. They further showed that markers of interstitial fibrosis and proliferation increase in mutants prior to the onset of histologically evident cystic disease, suggesting that aberrant epithelial-stromal cell signaling is an early and primary feature of the condition (Figures 1-4). The study design was straightforward and appropriate to address the question, and the results support their conclusions.

They next tested whether the cilia-dependent cyst-activating pathway (CDCA) that is "unmasked" by loss of other PKD-related genes is similarly active in Nphp2 mutants by generating Nphp2/Ift88 double mutants. Their studies found that the severity of cystic disease and markers of proliferation and fibrosis was attenuated in double-mutants (Fig 5, 6). These studies were also appropriate for testing the hypothesis and the results were similarly consistent with their interpretation.

In the last set of studies, they tested whether valproic acid (VPA), a drug that has multiple modes of action including acting as a broad inhibitor of HDACs and previously used by the investigators in other forms of polycystic kidney disease, would have similar effects in Nphp2 mutants. The authors tested daily injection from days P10 through P28 in both control and Nphp2 mutant mice with VPA or an appropriate vehicle control and found that VPA was beneficial (Fig 7). The study design was acceptable and the results generally support their conclusions. The one perplexing result is shown in Fig 7B. The Nphp2 mutants, regardless of treatment status, have body weights (BW) that are significantly lower than the controls, with treated mutants even trending lower than their untreated mutant counterparts. This is unexplained and should be addressed. In the mutants with more widespread epithelial cell knock-out of Nphp2 (Ksp-Cre, Fig 1), total body weight decreased as mice became more severely cystic with renal impairment. In the milder form of disease produced with the Pkhd1-Cre (Fig 7), total body weight is inexplicably approx. 2g lower on average despite having much more modestly elevated KBWs and BUNs. Moreover, one might have expected that mutants treated with VPA would have had BWs intermediate between untreated mutants and controls since the severity of the disease was moderately attenuated. These differences raise the question as to whether body weight differences are due to factors independent of disease status, the most likely of which would be that the controls were not littermates. This prompted a careful review of the text for descriptions of the control mice. Throughout the study, the investigators describe selecting animals from the same "cohort", but this term is imprecise. There is little information provided about background strains, whether any of the lines were congenic, or whether any of the studies were done using littermate controls. This must be addressed. It would help if the investigators identified the litter status in their plots. This would clearly show relationships between animals and the number of litters that had animals with these properties. If littermates were not used for each study, the authors must explain both why they didn't do so and how they then selected which animals to use. This information is especially important for interpreting the results of their genetic interaction and drug treatment studies.

Several other considerations. The authors state that the effects of VPA are mediated through the drug's inhibition of HDACs and suggest that future studies could be directed at refining the specific HDAC. While this is certainly possible, the authors should acknowledge that VPAs have been reported to have numerous pharmacologic effects and targets and which of these is mediating the effects in their model is unknown. They would need mechanistic studies to show this, though it doesn't discount their possible efficacy as a therapy for PKD. The authors also state in their abstract that their double knock-out studies "support a significant role of cilia in Nphp2 function in vivo." It is not clear to me how their studies show this nor how they can exclude that ciliary activity is operating in an Nphp2-independent, parallel fashion that modulates some common downstream pathways.

Reviewer #1 (Public Review):

The paper reports important work in which the Fub-1 boundary of the Drosophila bithorax complex is characterized in detail. Fub-1 separates the bxd/pbx regulatory domain, which is active in PS6/A1, from the abx/bx regulatory domain, which is active in PS5/T3. The work presented provides compelling evidence that Fub-1 consists of two key elements: an insulating boundary region called HS1, which is regulated by an adjacent region called HS2. HS2 contains a promoter that is activated in PS6/A1 by enhancers in the bxd/pbx region. Read-through of HS1 by transcripts from the HS2 promoter blocks the insulating activity of HS1, allowing the bxd/pbx regulatory regions to activate Ubx transcription in PS6/A1. It has long been appreciated that boundary elements within the BX-C are regulated in a segment-specific fashion. The work presented in the Ibragimov manuscript provides a very nice example of how this segment-specific regulation can take place. For the most part, the work is very thorough and the conclusions are well-supported. However, there are a few important issues that should be addressed.

First, throughout the manuscript, it is stated that the read-through transcription of HS1 eliminates its blocking activity. Missing, however, is a test of whether the direction of transcription of HS1 is important. That is, no construct is tested in which HS1 is inverted so that RNAs from the HS2 promoter are transcribed from the opposite strand of HS1. If read-through transcription of HS1 is all that is required to abrogate its blocking activity, such a construct should behave identically to constructs in which HS1 is not inverted. However, if the structure of the F1HS2 RNA is critical to preventing the blocking activity of HS1, inversion of HS1 relative to HS2 may render it immune to inactivation by transcripts initiated at HS2.

Second, the terminology used to designate the constructs tested is very hard to follow and needs simplification. Since the orientation of HS1 in isolation is unimportant, perhaps just HS1 HS2, HS1 Inv(HS2), HS2 HS1, and Inv(HS2) HS1 could be used.

Third, in many places in the manuscript genotypes are shown in which the HS1 insulator is placed into F7attP50. For these genotypes, H1 is said to block the interaction between iab-6 and iab-7, but not to support bypass activity. Readers need some help here, as they will not understand why A5 and A6 tergites are black in these genotypes, as this implies that iab-5 is able to act over the HS1 element to activate Abd-B. One explanation may be that iab-5 can promote pigmentation by acting on abd-A.

Fourth, a more complete description of the HS1248 HS2505R genotype is needed. In this genotype, the H1 insulator is constitutively active, as H2 is inverted. Do animals of this genotype show a bxd phenotype in the larval cuticle? Do adults show a transformation of the halteres like that shown by classical bxd mutations? Answers to these questions would shed light on when H1 is active as an insulator, and whether it is active throughout PS6/A1.

Reviewer #1 (Public Review):

Maksim Kleverov et al. developed the tool called Phantasus, a web application for matrix visualization and analysis of gene expression data generated by either microarray or RNA-seq technologies. By Phantasus, the users can load, normalize, and plot their own data or those available in public databases and investigate the samples to remove outliers before the differential expression analysis.

Phantasus can be accessed on-line or can be installed locally from Bioconductor.<br /> One of the advantages of the web application is that it combines an interactive graphical user interface with access to various R-based analysis methods. For the methods that rely on functions that are already available in the existing R packages, for such practices, only wrapper R functions are implemented. The tool was developed focusing on being helpful to both expert and non-expert users in bioinformatic gene expression analysis.

Reviewer #1 (Public Review):

In this work, the authors propose a "transfer learning" approach for modeling the properties of sequences that are selected from larger sequence pools on the basis of biophysical or functional properties, where the source populations may themselves be biased in composition. Examples include the set of immunogenic peptides, considered as a subset of all HLA-presented peptides, or the set of TCRs that are specific for a given peptide epitope, as selected from within the much larger pool of all peripheral TCRs. The motivation for transfer learning is that there may only be small numbers of selected sequences available for training and many more examples of the background sequences. Rather than directly fitting a single model on the selected sequences, the idea is to first fit a background model that captures the properties of the source/background population of sequences, using the many examples available for training, and then train a "differential" model that specifically seeks to capture the differences between the selected and background populations. This differential model is trained using the subset of selected sequences, by optimizing their likelihood under a composite model that combines the background model (whose parameters are frozen) and the differential model. The specific architecture used here is the "restricted Boltzmann machine" (RBM), which can be thought of as a generalization of the position-weight matrix approach that can capture pairwise and higher-order interactions between positions. The applications are the two mentioned above, prediction of immunogenic peptides and prediction of TCRs specific for a given peptide-MHC epitope. This work builds on previous work by the authors applying the RBM architecture to peptide-MHC binding [Bravi et al., 2021b] and T-cell responses [Bravi et al., 2021a]. The advance here is in formalizing the "differential" framework and testing immunogenicity prediction and epitope specificity. Considering the field and the current state of the art, the main contributions of the manuscript appear to be theoretical/conceptual, in introducing the "diffRBM" method and providing a range of evaluations of its performance, for example, the use of contact prediction to assess the model. For TCR-epitope prediction, it does not look like the method improves over methods like TCRex or TCRdist, though an advantage is that the parameters may be more interpretable than some black box machine learning approaches. Also for epitope prediction, as noted by the authors, the model may be learning features that differentiate TCRs expressed by CD8+ T cells from the background of all TCRs (which is probably weighted toward CD4+ T cells). This would explain the poorer performance discriminating TCRs specific for one MHC class I epitope from those specified for a different class I epitope. For immunogenicity prediction, evaluations are so dependent on the specifics of the datasets, and the feature itself is so murky, that it's hard to say whether there is a performance advance here.

One nice feature of the diffRBM model is that scores ("single-site factors") can be assigned to individual amino acids in a peptide (or TCR) sequence that captures the contribution of that amino acid at that position to the overall score of the sequence, taking into account the sequence context. The authors show that these single-site factors, for the diffRBM model trained on immunogenic peptides, highlight positions that tend to be involved in TCR contacts as well as specific amino acids, such as "W at position 5", that have been found in previous studies to enhance TCR recognition. The single-site factors for a diffRBM model trained on epitope-specific TCRs appear to do a reasonable job of predicting CDR3 positions that contact the peptide.

Overall, the conclusions of the study are well-supported and the descriptions of the method's performance are balanced. The manuscript is well-written, and the supporting information nicely addresses minor questions that come up in reading the main text. One minor quibble I have is with the description of the method as "unsupervised", especially in the TCR-epitope prediction setting, since the sequences provided to the diffRBM for training, and which the model is tasked with learning differences between, is exactly the positive and negative sequences for the AUROC calculations (up to train/test sampling). It is also confusing to me that the overall selection factors for TCR-epitope binding are so very modest (0.19 for Flu M158, for example; Figure S20D, this is the "effective fraction of sequences retained in selected data compared to background ones"). This doesn't seem like it can be correct, given how focused some of these epitope-specific repertoires are. Overall, though, the study and associated software tools are likely to be useful contributions to the field.

Reviewer #1 (Public Review):

CD73 is a promising biomarker in cancer and has been characterized as having an immunosuppressive role in the tumor microenvironment. However, many cancer cell-intrinsic roles of CD73 are still under investigation. In this work, the authors explore the immune-independent roles of CD73 in cancer and demonstrate a function in maintaining metabolic fitness in cancer cells. The authors utilize genetic and pharmacological inhibition of CD73 to characterize metabolic changes in a panel of cancer cell lines and assess tumor growth in vivo. Furthermore, the authors demonstrate that the impaired metabolic fitness due to CD73 inhibition rendered cancer cells more susceptible to DNA-damaging agents. Overall, this work demonstrates the new roles of CD73 in cancer and provides a rationale for combination therapies including CD73 inhibition.

Reviewer #1 (Public Review):

This important study by Bonnet et al addresses the question of how AMPA receptor numbers at the synapse are regulated during basal conditions and during chemically induced Long Term Potentiation (cLTP). Specifically, the study aims to determine which molecular mechanisms contribute to export from Golgi/the ER, intracellular trafficking of AMPA receptors, and insertion into the synaptic plasma membrane, respectively. The authors had previously established an approach to separately measure these distinct events: to enable a high-fidelity measurement of the Golgi/ER release and subsequent speed of GluA1-containing vesicles, the release of vesicles is synchronized. Finally, the insertion into the plasma membrane is measured by immunolabelling.<br /> The authors set out to specifically understand the contributions of two auxiliary proteins in AMPA receptor expression: 4.1N and SAP97. Namely, the authors find that under basal conditions, binding of SAP97 to GluA1 is necessary for the GluA1 release from the Golgi/ER and intracellular trafficking. In turn, binding of 4.1N to GluA1 is necessary for the exocytosis of the receptor at the plasma membrane at basal conditions. Following induction of cLTP, the authors find that the role of SAP97 remains similar to that observed under basal conditions but, interestingly, 4.1N significantly grows in influence and is required for all stages of GluA1 expression - from release from the Golgi/ER to exocytosis and insertion into the plasma membrane.

In summary, using convincing methodology, the authors are able to dissect the distinct roles of two proteins that bind to the C-terminal domain of the AMPA receptor subunit GluA1: 4.1N and SAP97.<br /> The scientific rigor is high in this work. For example, the question of whether the expression of GluA1 depends on physical interaction with 4.1N and/or SAP97 is nicely addressed by several, well-considered experiments. Overall, the authors' claims are well justified by the data presented.

I did not find any major scientific weaknesses in this manuscript. The approach developed by the group appears to be a good tool for studying the molecular choreography at the synapse under different conditions and the results will be of interest to a wide range of neuroscientists.

DOI: 10.1016/j.cub.2023.01.039

Resource: ZFIN_ZDB-ALT-160830-1

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-160830-1

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DOI: 10.1016/j.cub.2023.01.039

Resource: (ZFIN Cat# ZDB-ALT-160120-1,RRID:ZFIN_ZDB-ALT-160120-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-160120-1

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DOI: 10.1016/j.cub.2023.01.039

Resource: (ZFIN Cat# ZDB-ALT-150324-1,RRID:ZFIN_ZDB-ALT-150324-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-150324-1

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Reviewer #1 (Public Review):

The authors used viral replication assays to select for and define the resistance pathways against ten developmental Protease Inhibitors (PIs) and their parent drug, Darunavir (DRV), which is one of the leading antiretrovirals used to treat people living with HIV/AIDS. There are two specific regions of the small molecule inhibitors that are actively being modified to increase potency against drug-resistant mutants, the P1' region, and the P2' region, which protrude into pockets of PR occupied by I84 / I50, and a neighboring region containing D29-D30, respectively. Selections using drugs containing small modifications of the P1' region led to primary mutations at PR position I184V, but not I150V. In contrast, selections using drugs containing larger modifications at the P1' region led to primary mutations at PR position I150V, a pathway that is less fit. Furthermore, having modifications at the P2' position added additional potency to the inhibitors, most evident within the I184V pathway. The authors rationalize their findings using previously published structural biology data. These results provide the first evidence for de novo pathway selection using state-of-the-art drugs based on the DRV scaffold and provide an atomic basis for designing compounds that are highly active against DRMs. The comprehensive nature of the analysis of drug resistance to the latest generation PIs, and the insights gained that can be rationalized based on atomic structure, are the major strengths of the paper. The weakness is the lack of commentary on the accessory mutations, which frequently arise in the selections but are not well-explained. It would also be useful to provide some concrete suggestions for minimizing drug resistance using 5th generation PIs, as part of a discussion.

Reviewer #1 (Public Review):

Thakkar et al describe the immune effects of 3rd and 4th doses of COVID-19 monovalent vaccines in a diverse cohort of immunocompromised cancer patients. They describe augmentation of anti-Spike antibodies after dose 3, especially seroconversion in 57% of patients, followed by a durable response over six months. The fourth dose was associated with increased anti-Spike antibodies in 67% of patients. T-cell responses were seen in 74% and 94% of patients after the third and fourth doses respectively. Strikingly, neutralization of Omicron was absent in all patients after the third dose but increased to 33% after the fourth dose.

Strengths:<br /> Diverse cohort (34% Caucasian, 31% AA, 25% Hispanic 8% Asian) including 106 cancer patients after dose 3, of which 47 patients were longitudinally assessed for six months, as well as eighteen patients assessed after the fourth dose.<br /> Seronegative as well as seropositive patients benefit from a third dose of vaccination.<br /> Assessment of cellular (T cell) immune responses and viral neutralization against wild-type as well as Omicron variant is commendable.

Weaknesses:<br /> The efficacy of the bivalent vaccine (Omicron specific) is not studied here, since the fourth dose of vaccine was a monovalent vaccine. This should be clarified in the discussion.<br /> The authors describe an increase in anti-S titers after monoclonal antibodies. Were any of the patients receiving IVIG, and what was the effect, if any on Anti-S antibodies?<br /> Characteristics of breakthrough infections, particularly if they had prolonged duration, would be important to include.

Reviewer #1 (Public Review):

In this work, Diekmann and Cheng have proposed a new computational model for hippocampal replay. The new model is based on the linear RL work by Piray and Daw 2021, and addresses a fundamental problem in the seminal replay model of Mattar and Daw 2018 (M&D). The new model is based on the default representation, which is a realistic account for state closeness in model-based RL.

This study addresses an important problem in neuroscience at the computational level. The proposed theory is a significant normative computational model that captures important aspects of experimental data in the replay literature. The paper is very well-written (a difficult task for a pure computational work) and figures illustrate the main concepts very well. I have only one question/suggestion:

I believe that there is important data in the literature that cannot be explained by the current model, especially regarding representation of the goal. That is fine; no model is complete, but it is important that authors discuss those caveats in the discussion.

Reviewer #1 (Public Review):

The manuscript by Zhang et al. titled "Retinal microvascular and neuronal pathologies probed in vivo by adaptive optical two-photon fluorescence microscopy" reports a custom-designed two-photon fluorescence microscope coupled with adaptive optics (AO-2PFM) that allows in vivo imaging of mouse retinal structures at a lateral resolution of ~0.8 μm and axial resolution of ~6.7 μm. The authors provided two examples of applications for in vivo imaging of mouse retinal structure and function. In the first example, AO-2PFM has been used to visualize capillary lesions in a mouse model of retinal angiomatous proliferation (RAP), a form of age-related macular degeneration characterized by capillary proliferation and focal vascular leakage. Using AO-2PFM, the authors observed capillary disruption, with which dye leakage was associated. In the second example, the authors performed in vivo functional imaging of Ca2+ signals in RGCs of the rd1 mouse - a model of retinal degeneration with a mutation in the Pde6B gene. They interpreted the elevated Ca2+ signals in RGCs of rd1 mouse as an indication of RGC hyperactivity that has been reported in ex vivo electrophysiological recordings. They further observed dampened Ca2+ signals in RGCs of rd1 mouse upon retro-orbital injection of lidocaine.

The authors carefully documented the technical features of this state-of-the-art in vivo mouse retina imaging system. The manuscript is very well written and, needless to say, the images presented are of superb quality. There is no doubt that the system will be of great value to many retinal researchers studying the normal structure and function of the retina as well as tracking the pathophysiology of retinal disease models longitudinally.

Reviewer #1 (Public Review):

This manuscript investigates the question of how polylysogeny impacts competition with a sensitive non-lysogen, and how this is shaped by phage resistance. This is an important and timely question, as lysogeny can be a strategy to invade new niches, and prophages are important vehicles for the acquisition of a range of virulence factors by pathogens including Klebsiella. The authors use a polylysogenic Klebsiella clone in competition with a non-lysogen that is sensitive to at least some of the prophages produced by the polylysogen. They compete these strains over a 30-day period and measure host population dynamics and evolution of phage resistance and lysogenic conversion in the (initially) sensitive competitor. Overall, the experiment shows that lysogen formation is relatively rare and short-lived. Instead, phage resistance through complete loss of the capsule is the primary mechanism evolving, but other resistant capsule mutants, with more subtle mutations affecting capsule expression, emerge as well. The authors have collected a very impressive amount of data and made some very interesting observations.

My main problem with this paper is that the manuscript lacks a clear narrative, making it very hard to extract the key message this paper wants to convey. Related to this, (some of) the conclusions that the authors make do not appear to be well supported by the data. For example, the authors conclude that selection favours more subtle capsule mutations because they are less costly than capsule-loss mutants (lines 497-500). However, there are no data to support this conclusion, as fitness costs of the various resistance phenotypes analysed were not measured. Apart from the genotypes, the data that are presented in this show that these subtle mutants have more subtle decreases in capsule production compared to the mutants that show a complete loss of capsule. But this does not tell us their relative cost. It also doesn't tell us how the emergence of these different mutants relates to phage pressure, because whilst bacterial population dynamics data are monitored meticulously, phage dynamics data are missing (I have not found them in the supplemental information either). This makes it impossible to directly relate the emergence of the various resistance mechanisms to phage infection pressure during the coevolution experiment, even though this appears to be a hypothesis the authors wish to test.

Overall I think the overarching question of the manuscript is important and the model system is a very relevant one to study this question, but in my view, the current data don't support the conclusions of the paper. Apart from these criticisms, the manuscript is very well written and the figures are overall easy to interpret.

Reviewer #1 (Public Review):

Rab27 is a major regulator of insulin granule exocytosis from beta cells, and it acts via (at least) three distinct effector proteins; Granuphilin, Melanophilin and Exophilin-8. Although the role of each of these three Rab-effectors in the regulation of insulin secretion is fairly well-established from studies of KO mice, the functional hierarchy between the effectors remains largely unknown. This study by Zhao et al addresses this question by investigating how simultaneous loss of two these effectors influence insulin granule exocytosis and also provide an explanation for their differential regulation of this process. They propose that Exophilin-8 acts upstream of Melanophilin, which in turn is involved in crash-fusion of granules with the plasma membrane, and that the interaction between these two effectors require the exocyst complex. This mode of exocytosis is relatively rare and only accounts for around 20% of all fusion events. The majority of fusion events instead involves exocytosis of granules stably docked at the plasma membrane. The authors propose that this mode of exocytosis also depends on Exophilin-8, now acting by removal of a Granuphilin-mediated exocytic clamp.

Technically, this is a superb study where the authors use primary mouse islets isolated from both single and double KO mice and perform both bulk secretion assays and single-cell granule imaging to elucidate the role of Rab27 effectors in glucose-stimulated insulin secretion. Unfortunately, while visualization of granule dynamics is performed in living cells, visualization of the Rab27 effectors and the ecoxyst components is restricted to static immunofluorescence imaging. It is therefore difficult to reconcile granule dynamics with effector action. While the results are clearly presented and largely consistent with previous work, I feel that many of the conclusions are based on over-interpretation of data and that important control experiments are missing. The authors are able to confirm their and others' previous observations that each of the three Rab27 effectors have distinct functions during insulin secretion. A connection between insulin granule exocytosis and the Exocyst complex has also been established in previous studies. The most intriguing finding in this study is that the Exocyst complex function in cooperation with Rab27 and its effectors, thus connecting these two pathways, and that there appears to be a functional hierarchy amongst the Rab27 effectors where Exophilin-8 act upstream of the other two. What remains unclear to me is how this entire process is regulated and how it relates to prevailing models of insulin granule pools and modes of exocytosis.

Understanding the mechanism that regulate insulin secretion is imperative for understanding how this process fails in certain types of diabetes. This study reinforces the concept that the secretion of insulin granules is a very heterogenous process that involves multiple pools of granules and modes of exocytosis and provides important new information on how cross-talk between these pathways help to shape the secretory response and give it robustness.

Reviewer #1 (Public Review):

Decidualization, denoting the transformation of endometrial stromal cells into specialized decidual cells, is a prerequisite for normal embryo implantation and successful pregnancy in humans. Abnormal cytokine-associated inflammation during decidualization can alter the endometrium's receptivity to healthy embryo implantation. Jiang and colleagues present an important analysis of the role and function of the Gaq axis on the inflammatory response during decidualization essential for early pregnancy, and present preliminary data on its clinical relevance.

The data narrative provides solid evidence of the mechanisms suggested by Jiang and colleagues. The study is highlighted both by the in vitro analysis and also by the study of human samples and subjects impacted by Recurrent Pregnancy Loss (RPL). Overall, the data seems to justify the conclusions taken, although some of the methodology and data interpretation require further clarification and justification.

Reviewer #1 (Public Review):

The expression and localization of Foxc2 strongly suggest that its role is mainly confined to As undifferentiated spermatogonia (uSPGs). Lineage tracing demonstrated that all germ cells were derived from the FOXC2+ uSPGs. Specific ablation of the FOXC2+ uSPGs led to the depletion of all uSPG populations. Full spermatogenesis can be achieved through the transplantation of Foxc2+ uSPGs. Male germ cell-specific ablation of Foxc2 caused Sertoli-only testes in mice. CUT&Tag sequencing revealed that FOXC2 regulates the factors that inhibit the mitotic cell cycle, consistent with its potential role in maintaining a quiescent state in As spermatogonia. These data made the authors conclude that the FOXC2+ uSPG may be the true SSCs, essential for maintaining spermatogenesis. The conclusion is largely supported by the data presented, but two concerns should be addressed: 1) terminology used is confusing: primitive SSCs, primitive uSPGs, transit amplifying SSCs... 2) the GFP+ cells used for germ cell transplantation should be better controlled using THY1+ cells.

Reviewer #1 (Public Review):

The fields of ancient and environmental DNA have many similarities. Practitioners are constantly tinkering with methods to extract as much information from biological samples as possible. Both fields of research also have to deal with the fact that only a tiny fraction of the DNA is 'on target' and that the background DNA (largely bacterial) is often immense.

In this research Urban et al tackle the question of individual identification of a flightless New Zealand parrot (the kakapo) using shotgun eDNA (from soil) within a study system where reference genomes exist for most of the animals within a population. Most eDNA studies stay in the relative safety of metabarcoding (typically on mitochondrial DNA) thus Urban et al are breaking new ground.

In this small-scale (and highly controlled) study, Urban et al. use shotgun eDNA from a gram of soil and then match kakapo reads to reference genomes. Using some innovative Bayesian inference the researchers are able to identify individuals within the populations.

There are a number of innovations in this study that have relevance to the conservation sector. The idea that we can identify individuals in a population in a non-invasive manner is an exciting prospect. It immediately conjures up the possibility of genetic mark-recapture applications. In the case of highly endangered populations, the work shows the value of building reference genomes for the whole population.

At its core, this is a proof-of-principal study that arguably leaves the reader with more questions than answers. I was left wondering (i) why didn't nanopore's adaptive sampling function enrich targets? (ii) how would short-read platforms compare (iii) could genomic signatures of other taxa (e.g. bats) identified by metabarcoding be detected in shotgun data? And (iv) is sediment the best substrate for this work?

Sedimentary DNA methods have been around for ~20 years and it is exciting to see the field continue to innovate. The speed and portability of nanopore devices may, with time, see real-time genotyping become a reality in conservation biology. I welcome these innovations as, on the global stage, we need all the tools we can get to battle the biodiversity crisis.

Reviewer #1 (Public Review):

Medwig-Kinney et al perform the latest in a series of studies unraveling the genetic and physical mechanisms involved in the formation of C. elegans gonad. They have paid particular attention to how two different cell fates are specified, the ventral uterine (VU) or anchor cell (AC), and the behaviors of these two cell types. This cell fate choice is interesting because the anchor cell performs an invasive migration through a basement membrane. A process that is required for correct C. elegans gonad formation and that can act as a model for other invasive processes, such as malignant cancer progression. The authors have identified a range of genes that are involved in the AC/VC fate choice, and that imparts the AC cell with its ability to arrest the cell cycle and perform an invasive migration. Taking advantage of a range of genetic tools, the authors show that the transcription factor NHR-63 is strongly expressed in the AC cell. The authors also present evidence that NHR-63 is could function as a transcriptional repressor through interactions with a Groucho and also a TCF homolog, and they also suggest that these proteins are forming repressive condensates through phase separation.

The authors have produced an extensive dataset to support their two primary claims: that NHR-67 expression levels determine whether a cell is invasive or proliferative, and also that NHR-67 forms a repressive complex through interactions with other proteins. The authors should be commended for clearly and honestly conveying what is already known in this area of study with exhaustive references. But absent data unambiguously linking the formation and dissolution of NHR-67 condensates with the activation of downstream genes that NHR-67 is actively repressing, the novelty of these findings is limited.

Reviewer #1 (Public Review):

Vaparanta et al propose a new bioinformatic algorithm for pathway discovery from multi-omics data sources at one time point, and validate some of their algorithm's predictions using functional experiments. The authors should be commended for their detailed experimental work and comprehensive data collection around TYRO3 signaling in melanoma, which will likely be of value to that field. They also provide a mature software package that is well documented for implementing their bioinformatic methods. The reviewer's experience with the software was that it is computationally efficient/fast with well written code. The biological data (both multiomics and functional validation studies) will be of interest to melanoma research as well as scientists interested in TYRO3 signaling.

At this time, however, the bioinformatics algorithm proposed is of unclear utility to the broader multiomics community for the following reasons:

First, the algorithm itself has numerous hyperparameters, which can make it challenging to use and potentially highly sensitive to these user inputs. Just the regulatory complex inference step has 10 hyperparameters/settings required to be selected.

Second, the algorithm is presented in an ad hoc manner without mathematical/statistical justifications of the many design decisions and steps in the analysis. For example, the authors write "The inference of regulatory complexes from the combined score follows the nearest neighbor principle, assuming that while a single high combined score can be random chance, the combination of combined scores between 3 cell signaling molecules would be predictive". It is mathematically unclear that this is true, and thus this reviewer attempted to test the algorithm using simulated uncorrelated Gaussian noise (see code/outputs at end of the review) in 10K genes and 10 samples using a best attempt at hyperparameter selection per the code comments and documentation. It appears that nearly 1/3 of all genes (i.e., 3205 of 10K) were erroneously grouped into complexes (assuming no mistakes in reviewer's usage of the code). In general, "unbiased" pathway analysis in multiomics that is not relying on prior knowledge will require solving the extraordinarily challenging task of estimating a very large covariance matrix from statistically small sample sizes. This puts the method at high risk of producing spurious results.

Third, pathway analysis has long been a bioinformatic goal in the literature, with the authors citing a landmark paper for the WGCNA method from 2008. As such, there are numerous and long-standing discussions in the literature regarding challenges of pathway analysis (i.e., omics data often has dimensionality D far larger than sample size N, and correlation matrix estimation requires D^2 >> N parameters to be estimated) and its potential for spurious correlations. Some authors use sophisticated statistical tools (e.g., "Biological network inference using low order partial correlation" 2014, "Learning Large‐Scale Graphical Gaussian Models from Genomic Data" 2005, "Incorporating prior knowledge into Gene Network Study" 2013) to attempt to deal with this issue. Furthermore, the authors indicate that their approach is the first to attempt pathway analysis in multi-omics setting, stating "Integrative approaches combining more than one robust molecular association measure, however, have not been explored", but one can find attempts such as "An Integrative Transcriptomic and Metabolomic Study of Lung Function in Children With Asthma" to build on WGCNA for work in multiomics datasets. The 2020 review paper "Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources" seems to identify multiple published methods dealing with pathway estimation in multiomics datasets. As the paper stands, this reviewer cannot adequately assess the impact of the proposed bioinformatic algorithm and its results against the existing body of literature for pathway inference.

Reviewer #1 (Public Review):

Siegfried et al. study a very interesting and timely topic in cell biology: the connection between ER-PM membrane contact sites (MCS) and cell migration. In brief, the authors use the polarized epithelial model cell line (CACO-2) to study this process. They routinely compare parental cells (Control) with a clonal CACO-2 cell line knocked out (KO) for the ER tether protein VAP-A. They convincingly show that KO cells move faster but in a less directional manner, leading to slower monolayer migration. Interestingly, they showed that KO cells have larger focal adhesions (FAs), a phenotype that was reverted upon expression of the wild-type VAP-A but not of a VAP-A mutant (VAP-A-KDMD, mutation in the MSP domain) defective in binding to FFAT-containing partner proteins. Some observations regarding the role of VAP-A's MSP domain on the regulation of the actin cytoskeleton, although the evidence for this was incomplete. Furthermore, VAP-A depletion was shown to have an impact on PI(4,5)P2 levels at the PM (but not on PI(4)P levels at the Golgi membranes), to stabilize the dynamics of ER-PM MCS, and to increase FA lifetime by decreasing FA disassembly rate. Finally, they showed that there is a correlation between the appearance of ER-PM MCS at FAs with FA disassembly, however, how VAP-A plays a role in this effect is unclear. The authors put their findings in the context of the literature in the field to propose a working hypothesis by which VAP-A at ER-PM MCS could impact FA dynamics and cell motility.

Reviewer #1 (Public Review):

The authors' conclusions presented herein are supported by a well-established mouse genetic conditional approach and an extensive array of phenotypic analyses.

Strengths:

1. The authors utilized well-described genetic tools, AdipoQCre, to target preadipocyte-like progenitor cell populations in bone marrow, as well as Csf1 floxed alleles. They further sifted through the cell population by showing that mature lipid-laden adipocytes express Csf1 at a much lower level, and determined that AdipoQCre-marked progenitor cell population presents a major cellular source of M-CSF,

2. The reanalysis of published scRNAseq datasets in Figure 1, as well as the following phenotypic analyses of the mutant mice are well-conducted. The analyses include a broad range of experiments both in vivo (3DmicroCT, histology, flow cytometry) and ex vivo (osteoclastogenesis assay in bone marrow cell culture). The confidence of the reported findings is high.

3. The data presented in this manuscript are of very high quality.

Weaknesses:

1. The role of AdipoQ-lineage progenitors as a source of M-CSF is overstated. The authors claim in many instances that "mature bone adipocytes do not express M-CSF", "These cells however do not produce Csf1", "...these peripheral AdipoQ+ cells nearly do not produce M-CSF". However, the authors' qPCR experiments only show four times differences in Csf1 expression. Therefore, the claim that AdipoQ-lineage progenitors are an exclusive source of M-CSF is not well substantiated. In line with this, some of the recent literature reporting conditional deletion of M-CSF in other bone cells (JBMR Plus. 4:e10080., Nature. 590:457-462) are not included.

2. Some of the phenotypic analyses are still incomplete. The authors did not report whether CHet (AdipoQCre Csf1(flox/+)) showed any bone phenotype. Further, the authors did not show that Csf1 mRNA or M-CSF protein is expressed in AdipoQ-lineage progenitors using histological methods. Current evidence is only based on scRNAseq and qPCR of isolated cells. Whether there was any change in circulating bone resorption markers in CKO mice was not shown. Cortical bone parameters were not included in the 3D-microCT analyses. These missing pieces of information would be important to correctly interpret the phenotypes.

3. Which bone marrow cell population(s) are marked by AdipoQCre remain largely unclear. It is possible that AdipoQCre also marks at least part of MSPC-osteo cluster in addition to MSPC-adipo. Adipo-lineage progenitors may not stay entirely as adipoprogenitors and drift toward osteoblasts or their precursor cells.

4. The OVX data in Figure 5 are not very well explained. The data do not seem to support the authors' conclusion that M-CSF deficiency in AdipoQ-lineage progenitors alleviates estrogen-deficiency induced osteoporosis. The CKO mice lose bone mass almost to the same extent as WT mice upon OVX.

Reviewer #1 (Public Review):

Although COVID-19 primarily causes an inflammatory response in the lungs, there is growing evidence that other organs are also affected by SARS-Cov-2, and that some patients continue to receive long-term effects of the disease sequelae even after treatment. We are not clear at this time about the effects of COVID-19 in organs other than the lungs. In this study, the authors presented the COVID Tissue Atlas (CTA) that comprises scRNA-seq data across six human organs of severe COVID-19. This study provides a valuable data resource to study the systemic effects of severe COVID-19, especially the common and specific transcriptional response to COVID-19 in multiple organs. Specifically, the authors identified dysregulated insulin and HIF signaling and prominent macrophage-endothelial interactions. This study will obviously help us to understand the pathogenesis of long-COVID.

Reviewer #1 (Public Review):

In this study, Tanentzapf and colleagues have developed a new live-imaging technique for the lymph gland hematopoiesis over 12 hours, which is enough to visualize changes in the cell state or cell division by tracking the same cell. With the new method, the authors successfully cultured the lymph gland for a long period without modifying cell viability or stress responses and detected a continuous cell cycle and division. Moreover, the authors showed that lymph gland progenitors divide when they reach a certain size and regrow upon division, supporting previous findings and providing a new concept in lymph gland biology. The authors moved on to resolve the spatial distribution of progenitor mitosis in 3D and found that progenitors divide in a polarized manner which contributes to the typical shape of lymph glands. In addition to developing lymph glands, the authors observed the lymph gland following oral infection and found that progenitors divide less upon infection but significantly increase the number of differentiations at the MZ-CZ boundary. Furthermore, the authors found two different modes of differentiation in the lymph gland: sigmoid and linear, which are altered during infection.

Studies in the lymph gland hematopoiesis have heavily relied on snapshots of the lymph gland phenotypes although stem-progenitor differentiation is a continuous process. In this regard, the method developed in this study is extremely valuable to the fly community and will help improve the ex vivo culture and analysis techniques of fly organs as well as the lymph gland. The authors rigorously took advantage of numerous measures to validate the new method, including cell death, oxidative stress response, cell viability, and cell cycle, and observed biologically significant phenomena of the correlation between cell size and cell division, cell division polarity, and changes in the mode of differentiation during development or infection. This study provides a useful system for Drosophila immunologists and developmental biologists and will help explore the real-time mechanisms underlying blood development and immune reactions.

Reviewer #1 (Public Review):

Single-cell sequencing technologies such as 10x, in conjunction with DNA barcoded multimeric peptide MHCs (pMHCs) has enabled high throughput paring of T cell receptor transcript with antigen specificity. However, the data generated through this method often suffers from the relatively high background due to ambient DNA barcodes and TCR transcripts leaking into "productive" GEMs that contain a 10X bead and a T cell decorated with antigen-specific barcoded proteins. Such contaminations can affect data analysis and interpretation and have the potential to lead to spurious results such as an incorrect assessment of antigen-TCR pairs or TCR cross-reactivity. To address this problem, Povelsen and colleagues have described a data-driven algorithm called "Accurate T cell Receptor Antigen Pairing through data-driven filtering of sequencing information from single-cells" (ATRAP) that supplies a set of filtering approaches that significantly reduces background and allows for accurate pairing of T cell clonotypes with cognate pMHC antigens.

This paper is rigorously conducted and will be useful for the field - there are some areas where further clarifications and comparisons will benefit the reader.

Strengths:<br /> 1. Povelsen and colleagues have systematically evaluated the extent to which parameters in the experimental metadata can be used to assess the likelihood of a GEM to correctly identify the antigen specificity of the associated T cell clonotype.<br /> 2. Povelsen and colleagues have provided elegant data-driven scoring metrics in the form of concordance score, specificity score, and an optimal ratio of pMHC UMI counts between different pMHCs on a GEM, which allows for easy identification of poor quality data points.<br /> 3. Based on the experimental goals, ATRAP allows for customizable filters that could achieve appropriate data quality while maximizing data retention.

Weakness:<br /> 1. The authors mention that 100% of the 6,073 "productive" GEMs contained more than one sample hashing barcode, and 65% contained pMHC multiplets. While the rest of the paper elaborates on the steps taken to deal with pMHC multiplets issue, not much is said about the extent of multiplet hashing issue and how was it dealt with when assigning cells to individual donors. How is this accounted for? Even a brief explanation would be beneficial.

2. It would be helpful for the authors to describe how experimental factors such as the quality of the input MHC protein may affect the outputted data (where different proteins may have different degrees of non-specific binding), and to what degree the ATRAP approach is robust to these changes. As an example, the authors mention that RVR/ A03 was present at high UMI counts across all GEMs and RPH/ B07 was consistently detected at low levels. Are these observations the property of the pMHCs or the barcoded dextran reagent? Furthermore, are there differences in the frequency of each of these multimers in the starting staining library which manifests in consistent high vs low read counts for the pMHC barcodes?

3. It would be helpful for the authors to further explain how ATRAP handles TCRs that may be present in only one (or a small number) of GEMs, as seen in Figure 7b, and potentially for the large number of relatively small clonotypes observed for the RVR/A03 peptide in Figure 6 (it is difficult to know if the long tail of clonotypes for RVR is in the range of 1 or 10 GEMs based on the scale bar). Beyond that, is there any effect on expected (or observed) clonal expansion on these data analyses, for example, if samples are previously expanded with a peptide antigen ex vivo or not?

4. The authors mention a second method, ICON, for conducting these types of analyses, and that the approach leads to significantly more data loss. However, given there could be differences in dataset quality themselves, and given the dataset, ICON is publicly available, it would be helpful for a more explicit cross-comparison to be conducted and presented as a figure in the paper.

Reviewer #1 (Public Review):

George and Levine present in their manuscript a mathematical framework describing the evolution of tumor cells under immune surveillance. The adaptive immune system recognizes tumor associate antigens (TAAs) to eliminate the cancer cells, while the tumor evades it through an evolutionary process of clonal selection. Their framework describes how the TAAs are gained and lost from the tumor, as a discreet time-stochastic process. The authors construct and parametrize their model to fit different known regimes of tumor and its microenvironment and explore the consequences of different tumor behaviors. Specifically, they suggest that tumor cells might sense the action of the immune system and adapt their escape probability.

The mathematical analysis is clear and is an impressive attempt to find governing principles behind a complicated and messy process. While the model cannot give specific predictions at this point, it facilitates understanding real-world observations, like high and low mutation tumors. As such it can motivate further modeling of more realistic situations. In its current form, however, the manuscript is difficult to follow, with the many mathematical details and regimes confounding the message. Also, since the model simplifies the clonal nature of the evolution processes considerably, in its current form it has limited capability to make predictions or be more than supporting evidence to empirically known observations.

Reviewer #1 (Public Review):

N1-methyladenosine (m1A) is a rather intriguing RNA modification that can affect gene expression and RNA stability etc. The manuscript presented the exploration of RNAs m1A modification in normal and OGD/R-treated neurons and the effects of m1A on diverse RNAs. The authors showed that m1 modification can mediate circRNA/LncRNA-miRNA-mRNA mechanism and 3'UTR methylation of mRNAs can disturb miRNA-mRNA binding.

The manuscript provides evidence for the following,<br /> 1. The OGD/R can have impacts on various functions of m1A mRNAs and neuron fates.<br /> 2. The m1A methylation of mRNA 3'UTRs disturbs the miRNA-mRNA binding.<br /> 3. The authors identified three possible patterns of m1A modification regulation in neurons.

The main merit of the manuscript is that the authors identified some critical features and patterns of m1A modification and in neurons and OGD/R-treated neurons. Moreover, the authors identified m1A modifications on different RNAs and explored the possible effects of m1A modification on the functions of different RNAs and the overall posttranscriptional regulation mechanism via an integrated approach of omics and bioinformatics. The major weakness of the manuscript is that technique details for many results are missing. Moreover, language inconsistences can be found throughout the manuscript. My general feeling about the manuscript is that some conclusions are rather superficial and therefore require validation and discussion.

Reviewer #1 (Public Review):

Here, the authors generated a CSAS-LexA driver line to investigate the expression pattern of CSAS and showed that CSAS expression is confined to glia and does not overlap with DSiaT expression. DSiaT expression is presumed to be in neurons, but this was not evaluated with specific markers in this study.

The authors showed that restoring CSAS expression specifically in glia but not neurons could rescue the mutant phenotype of temperature sensitive paralysis and confirmed that glial (and not neuronal) CSAS expression could rescue excitatory junction potentials at neuromuscular junctions in CSAS mutants. In addition to rescue experiments, the authors also performed RNAi knockdowns in glia vs. neurons to show that CSAS function is required in glia and DSiaT in neurons for the same paralysis phenotype.

Next, the authors performed mass spec to analyse sialylated proteins in larval brains and found that sialylated proteins could not be detected in DSiaT and CSAS mutants. However, sialylated proteins were only barely detectable in wildtypes.

Of note, the authors show that CSAS functions normally in glia and cannot function in neurons due to low endogenous NANS activity (sialic acid synthase).

Finally, the authors explore the hypothesis that the temperature-sensitive paralysis CSAS phenotype is due to oxidative stress with a paraquat exposure paradigm. This could be strengthened by examining ROS levels in vivo in CSAS or DSiaT mutants. The specific genetic background of these experiments seemed to be a major factor in the results obtained and more stringent controls or backcrossing to isogenize the genetic background would be required to be fully confident in the conclusions drawn from these experiments.

The authors also demonstrate a link between sialylation and Para (protein) expression. Although intriguing, there is very little data provided on this aspect of the story, though it does not detract from the broader message of the manuscript.

Reviewer #1 (Public Review):

High-throughput genetic screening is a powerful approach to elucidate genes and gene networks involved in a variety of biological events. Such screens are well established in single-celled organisms (i.e. CRISPR-based K/O in tissue culture or unicellular organisms; screens of natural variants in response to drugs). It is desirable to extend such methodology, for example to Arabidopsis where more than 1000 ecotypes from around the Northern hemisphere are available for study. These ecotypes may be locally adapted and are fully sequenced, so the system is set up for powerful exploration of GxE. But to do so, establishing consistent "in vitro" conditions that mimic ecologically relevant conditions like drought is essential.

The authors note that previous attempts to mimic drought response have shortcomings, many of which are revealed by 'omics type analysis. For example, three treatments thought to induce osmotic stress; the addition of PEG, mannitol, or NaCl, fail to elicit a transcriptional response that is comparable to that of bonafide drought. As an alternative, the authors suggest using a low water-agar assay, which in the things they measure, does a better job of mimicking osmotic stress responses. The major issues with this assay are, however, that it introduces another set of issues, for example, changing agar concentration can lead to mechanical effects, as illustrated nicely in the work of Olivier Hamant's group (e.g., https://elifesciences.org/articles/34460).

Reviewer #1 (Public Review):

In this study, the authors found that the chromatin remodeling complex mutant isw1Δ of the fungal pathogen Cryptococcus neoformans is resistant to multiple different antifungal drugs. The mutant, however, is fully virulent in a mouse model. By comparing transcript changes of the wild type and the mutant when treated with antifungal fluconazole, they found that many transporter genes are differentially expressed in the isw1Δ mutant. Consistently, they showed reduced expression of genes involved metabolism of another antifungal 5-FC and a lower level of cellular accumulation of 5-FC in the isw1Δ mutant, which likely contributes to its 5-FC resistance. They found that the Isw1 protein is degraded mostly through ubiquitination and identified K97 deacetylation as being critical for drug resistance/protein degradation. Then they mutated nine E3 ubiquitination ligase genes and identified Cdc4 to be responsible for Isw1 degradation. Lastly, they showed that Isw1 is low in some clinical isolates that are modestly resistant to antifungals. The evidence of the interplay between acetylation status and ubiquitination of Isw1 is strong. The finding that reduced Isw1 increases drug resistance also fits the growing interest in studying epigenetic regulation of drug resistance in fungal pathogens. One area that needs to be strengthened is the potential clinical relevance of Isw1 reduction in drug resistance.

Reviewer #1 (Public Review):

In this manuscript the authors overproduce two M. smegmatis DNA polymerases, DinB2 and DinB3, as a way to determine whether they may contribute to DNA damage tolerance and/or mutagenesis; the roles of these DNA polymerases in DNA damage tolerance and mutagenesis is currently unknown. The authors show that overproduced levels of DinB2, but not DinB3, impeded growth, and this inhibition was relieved by the disruption of DinB2 catalytic activity using the DinB-D109A mutation. They further demonstrate that the overproduction of DinB2 contributed to frameshift mutagenesis, while DinB3 did not. The contribution of overproduced levels of DinB2 to frameshift mutagenesis was studied in a careful and systematic way, convincingly showing that frameshifts correlated with DinB2 slipping while replicating homopolymeric nucleotide runs during dNTP and not rNTP incorporation. The authors also show that the metal cofactor (Mn vs Mg) contributes to the mutagenic behavior of DinB2. While this work is mostly compelling, the major concern is it fails to address the contribution of DinB2 and DinB3 to DNA damage tolerance and mutagenesis when they are expressed at normal levels from their respective chromosomal loci.

Reviewer #1 (Public Review):

Damon-Soubeyrand and colleagues use 3DISCO tissue clearing and light-sheet microscopy to provide a detailed atlas of the blood and lymphatic circulating networks of the mouse epididymis. While this manuscript does not address the function of these networks during the development or homeostasis of the epididymis, it is an outstanding example of a descriptive study that paves the way towards functional investigations of the role of epididymal vasculature in the post-testicular maturation of spermatozoa.

Strengths: The authors used a wide range of markers to carefully assess the differential patterns of epididymal blood and lymphatic vasculature, and elegantly describe each image in great detail. Where possible, the authors used appropriate quantitative methods to support their descriptive data, which are useful metrics for readers seeking to characterize vascular and lymphatic networks in disease models.

Weaknesses: In its current form, it is unclear which of the elements presented in the manuscript are novel discoveries about the blood and lymphatic networks of the epididymis, as the text lacks concise and precise statements about the major findings of the study. In addition, the authors frame this study of the vasculature as a way to understand the immune context of spermatozoa in the epididymis but do not integrate their data on blood and lymphatic networks with the immune system.

Reviewer #1 (Public Review):

This study aims at investigating temporal variation in patterns of germline mutation during the evolution of human populations. For this purpose, the authors analyzed polymorphism data from the 1000 Genomes project. They inferred the age of each derived variant using Relate, a newly developed method that reconstructs local genealogies based on phased haplotype sequences and estimates allele ages (Speidel et al. 2019).

Speidel et al. (2019) already had used their method to explore temporal variation in mutation patterns. Their analysis had confirmed the transient elevation in non-CpG C>T mutations in Europeans compared to African and Est Asians previously described by Harris (2015). However, Speidel et al. did not push their study very far, notably because of the difficulty of distinguishing the effects of changes in mutation patterns from those of GC-biased gene conversion (gBGC).

Here Gao et al. carefully accounted for gBGC to further explore variation in mutation patterns. As expected, they confirmed the previously described European-specific mutational shift. In addition, they identified two novel interpopulation differences in the mutation spectrum. This suggests that shifts in mutation spectra occur frequently, over a few thousands of generations. The reasons (environmental or genetic) for these recurrent shifts are not known, but the authors convincingly show that they cannot be explained by changes in the age of reproduction over time.

I found this manuscript very well written and very interesting. There is however an important point in their results that seems very puzzling. Indeed, the authors report that among mutations that are estimated to be old (>28800 generations), the ratio of T>C over T>G differs significantly in African samples compared to non-African samples (Fig. 2A). This difference is unexpected given that these old mutations largely predate the out-of-Africa migration (<3000 generations), and hence are a priori expected to be largely shared across populations. Curiously, this pattern is driven by variants for which the derived allele is observed in both Neanderthals and Denisovans (ND11 variants) (while ND01 and ND10 variants do not contribute to this pattern; Fig. 2D, SupFig 2.8). The authors hypothesize that the T>C/T>G ratio was higher in one or more populations in the remote past and those ancient groups contribute variable amounts of ancestry to contemporary populations. However, I do not understand how this model can account for the fact that ND10 and ND01 variants behave differently from ND11 variants (ND10 and ND01 variants are also expected to be emerged prior to the split of modern humans and archaic hominins).

It is possible that I misunderstood something, but in any case, there are several points in the methodology that have to be clarified. Notably, it is not clear to me if the reported pattern is driven by variants that are specific to the African samples, or if it is also observed among variants that are shared across populations. Furthermore, I suspect that polarization errors (notably at CpG sites) might be responsible for this pattern.

In summary, this manuscript reports very interesting observations, but several additional tests have to be done to check whether they are real or if they might result from methodological artefacts.

Reviewer #1 (Public Review):

Inter-cellular mitochondria transfer has been observed in many systems but the role or relevance of transferred mitochondria in recipient cells is poorly defined in contexts where recipient cells have intact functional networks. This manuscript directly addresses this important question and present a model in which transferred mitochondria act as signaling organelles to increase cancer cell proliferation.

The authors present compelling evidence that macrophages transfer mitochondria to cancer cells. Activated macrophages transfer mitochondria more effectively than non-activated macrophages, and this increased transfer is at least in part due to enhanced mitochondrial fragmentation in activated macrophages. Probing the significance of mitochondrial transfer, the authors find that transferred mitochondria remain distinct from endogenous mitochondrial networks and do not exhibit the polarization that traditionally characterizes functional mitochondria. The transferred mitochondria have features consistent with elevated oxidative stress and/or ROS production. A series of elegant imaging experiments demonstrate that mitochondrial transfer is associated with increased growth in daughter cells that inherit transferred mitochondria. Mechanistically, the authors propose that ROS produced by transferred mitochondria stimulate ERK signaling to induce a proliferation advantage.

Overall the work addresses an important question regarding the functional role of mitochondria transferred to cancer cells. The data largely support the model that transferred mitochondria are defective and induce proliferation in recipient cells. Some clarification on the effect timescales and the role role of ROS and ERK signaling in cell proliferation in cells that do not receive mitochondria is warranted. Overall this work provides an important new view for how mitochondrial transfer affects cell biology and provides a suite of tools and protocols for quantifying the impact of mitochondrial transfer on recipient cells.

Reviewer #1 (Public Review):

The present study investigates the anatomical connectivity between Mu opioid receptor (MOR) expressing neurons of the pontine respiratory group with down-stream targets of the respiratory network in the medulla oblongata. The study employs a variety of viral tracing approaches, optogenetic stimulation of pre-synapses of descending pontine projection neurons, and patch clamp electrophysiology. Overall the study is well conducted and the authors show that MOR expressing excitatory glutamatergic pontine neurons project to the medullary respiratory rhythm generator and adjacent ventral respiratory group. The study implies that opioids act on MOR-located somata and dendrites of the pontine and medullary respiratory groups. Importantly MOR are expressed on the pre-synapses of the descending pontine projections neurons. The authors, therefore, propose that opioids mediate respiratory depression via distinct pre- and post- synaptic mechanisms across inter-connected ponto-medullary respiratory neurons. The study advances our knowledge of network mechanisms that mediate opioid respiratory depression and may provide interesting frameworks for the development of therapies to counteract or prevent opioid respiratory depression. The study is of broad interest to the respiratory control research community, as well as medically relevant.

Reviewer #1 (Public Review):

Many previous studies have examined the regulation of hyphal growth in vitro, and have identified about 1,000 genes capable of influencing this process. However, a weakness is that most of these genes have weak effects and are not important in vivo. Therefore, it is very significant that this is the first large-scale study to examine the regulation of hyphal growth in vivo by analyzing a set of 156 transcription factor mutants in mice. A strength of these innovative studies is that mutant strains were injected into a mouse ear, which permitted the use of high-resolution microscopy to quantify the fraction of cells forming hyphae and the rate of hyphal elongation. Furthermore, wild-type cells were co-injected to serve as an internal control, which enhanced the rigor of these studies.

One major conclusion is that three core transcription factors were identified as being important in vivo (Rob1, Brg1, and Efg1) and two negative regulators (Tup1 and Efg1). Previously, many transcription factors were found to be important in vitro, so this is important for focusing future studies on the key regulators. Nanostring gene expression studies verified that these core factors regulate overlapping but distinct sets of genes in vitro and in vivo, which reinforces the importance of carrying out studies in vivo. Additional mutants were discovered to have minor defects in filamentous growth and were considered to be ancillary factors that act in concert with the core regulators.

Another innovative aspect of the manuscript is that they examined the rate of hyphal elongation in vivo. This is an understudied area both in vitro and in vivo. Transcription factors UME6, LYS14, and HMS1 were shown to regulate the elongation rate, which opens up new opportunities to study the mechanisms. Consistent with this, these transcription factors were shown to regulate a set of genes that is distinct from those regulated by transcription factors that control the initiation of hyphal growth.

Genetic approaches (complex haploinsufficiency) were used to examine the relationship between the core factors and the ancillary factor TEC1. Interestingly, these results revealed genetic interactions between TEC1 and the core factors EFG1 and BRG1, including their ability to regulate other transcription factors. This shows how these complex networks are functioning in vivo.

Another major advance was that the in vivo analysis of the two negative regulators of hyphal growth (Nrg1 and Tup1) revealed a new model for how they interact with the master transcriptional regulator Efg1. The results indicate that the major function of Efg1 in vivo is to mediate relief of Nrg1 repression. It was not needed to regulate the expression of hypha-induced genes.

Reviewer #1 (Public Review):

Taking advantage of a publicly available dataset, neuronal responses in both the visual and hippocampal areas to passive presentation of a movie are analyzed in this manuscript. Since the visual responses have been described in a number of previous studies (e.g., see Refs. 11-13), the value of this manuscript lies mostly on the hippocampal responses, especially in the context of how hippocampal neurons encode episodic memories. Previous human studies show that hippocampal neurons display selective responses to short (5 s) video clips (e.g. see Gelbard-Sagiv et al, Science 322: 96-101, 2008). The hippocampal responses in head-fixed mice to a longer (30 s) movie as studied in this manuscript could potentially offer important evidence that the rodent hippocampus encodes visual episodes.

The analysis strategy is mostly well designed and executed. A number of factors and controls, including baseline firing, locomotion, frame-to-frame visual content variation, are carefully considered. The inclusion of neuronal responses to scrambled movie frames in the analysis is a powerful method to reveal the modulation of a key element in episodic events, temporal continuity, on the hippocampal activity. The properties of movie fields are comprehensively characterized in the manuscript.

Although the hippocampal movie fields appear to be weaker than the visual ones (Fig. 2g, Ext. Fig. 6b), the existence of consistent hippocampal responses to movie frames is supported by the data shown. Interestingly, in my opinion, a strong piece of evidence for this is a "negative" result presented in Ext. Fig. 13c, which shows higher than chance-level correlations in hippocampal responses to same scrambled frames between even and odd trials (and higher than correlations with neighboring scrambled frames). The conclusion that hippocampal movie fields depend on continuous movie frames, rather than a pure visual response to visual contents in individual frames, is supported to some degree by their changed properties after the frame scrambling (Fig. 4). However, there are two potential issues that could complicate this main conclusion.

One issue is related to the effect of behavioral variation or brain state. First, although the authors show that the movie fields are still present during low-speed stationary periods, there is a large drop in the movie tuning score (Z), especially in the hippocampal areas, as shown in Ext. Fig. 3b (compared to Ext. Fig. 2d). This result suggests a potentially significant enhancement by active behavior.

Second, a general, hard-to-tackle concern is that neuronal responses could be greatly affected by changes in arousal or brain state (including drowsy or occasional brief slow-wave sleep state) in head-fixed animals without a task. Without the analysis of pupil size or local field potentials (LFPs), the arousal states during the experiment are difficult to know. Many example movie fields in the presented raw data (e.g., Fig. 1c, Ext. Fig. 4) are broad with low-quality tuning, which could be due to broad changes in brain states. This concern is especially important for hippocampal responses, since the hippocampus can enter an offline mode indicated by the occurrence of LFP sharp-wave ripples (SWRs) while animals simply stay immobile. It is believed that the ripple-associated hippocampal activity is driven mainly by internal processing, not a direct response to external input (e.g., Foster and Wilson, Nature 440: 680, 2006). The "actual" hippocampal movie fields during a true active hippocampal network state, after the removal of SWR time periods, could have different quantifications that impact the main conclusion in the manuscript.

Another issue is related to the relative contribution of direct visual response versus the response to temporal continuity in movie fields. First, the data in Ext. Fig. 8 show that rapid frame-to-frame changes in visual contents contribute largely to hippocampal movie fields (similarly to visual movie fields). Interestingly, the data show that movie-field responses are correlated across all brain areas including the hippocampal ones. This could be due to heightened behavioral arousal caused by the changing frames as mentioned above, or due to enhanced neuronal responses to visual transients, which supports a component of direct visual response in hippocampal movie fields. Second, the data in Ext. Fig. 13c show a significant correlation in hippocampal responses to same scrambled frames between even and odd trials, which also suggests a significant component of direct visual response.

Is there a significant component purely due to the temporal continuity of movie frames in hippocampal movie fields? To support that this is indeed the case, the authors have presented data that hippocampal movie fields largely disappear after movie frames are scrambled. However, this could be caused by the movie-field detection method (it is unclear whether single-frame field could be detected). Another concern in the analysis is that movie-fields are not analyzed on re-arranged neural responses to scrambled movie frames. The raw data in Fig. 4e seem quite convincing. Unfortunately, the quantifications of movie fields in this case are not compared to those with the original movie.

Cultural geography = human science, approach to the lives of people. Investigates relevance of culture to the global society today. * Contrast between mental and natural space * Space can be produced by society, but society creates itself within a cultural space

Consensus Public Review:

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

Overall, these conclusions are interesting and mostly well supported by the data, although there are some doubts about their definition of value coding. One limitation is the lack of focus on population-level dynamics from the perspective of decoding, with the analysis focusing primarily on encoding analyses within individual neurons.

Some specific comments:

The authors use reduced-rank kernel regression to characterize the 5332 recorded neurons on a cell-by-cell basis in terms of their responses to cues, licks, and reward, with a cell characterized as encoding one of these parameters if it accounts for at least 2% of the observed variance. At least 50% of cells met this inclusion criterion in each recorded area. 2% feels like a lenient cutoff, and it is unclear how sensitive the results are to this cutoff, though the authors argue that this cutoff should still only allow a false positive rate of 0.02% (determined by randomly shuffling the onset time of each trial).

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

In subsequent sections, the authors expand their model of anticipatory-licking-as-value by incorporating trial and stimulus history terms into the model, allowing them to predict the anticipatory lick rate on individual trials within a session. They also use 2-photon imaging in PFC to demonstrate that neural coding of cue and lick are stable across three days of imaging, supported by two lines of evidence. First, they show that the correlation between cell responses on all periods except for the start of day 1 is more correlated with day 3 responses than expected by chance (although the correlation is still quite low, for example, 0.2 on day 2). Second, they show that cue identity is able to capture the highest unique fraction of variance (around 8%) in day 3 cue cells across three days of imaging, and similarly for lick behavior in lick cells and cue+lick in cue+lick cells. Nonetheless, their sample rasters for all imaged cells also indicate that representations are not perfectly stable, and it will be interesting to see what *does* change across the three days of imaging.

Importantly, the authors do not present evidence that value itself is stably encoded across days, despite the paper's title. The more conservative in its claims in the Discussion seems more appropriate: "these results demonstrate a lack of regional specialization in value coding and the stability of cue and lick [(not value)] codes in PFC."

Reviewer #1 (Public Review):

The authors use a model of neonatal E.coli pneumonia to study differences between early neonates ad juvenile animals. They observe increased monocyte derived macrophage recruitment in juveniles compared to neonates as well as an increase in IFNG related genes. The data are of potential interest but in its current form it is unclear how well the experiments were controlled for confounders, such as sex and CFU.

1. This paper conducted research to identify the window of susceptibility to pneumonia due to E. coli, a bacteria that most often causes pneumonia in the neonatal period. This is an understudied area and thus the research is significant.

2. The paper provides evidence of differences in immune response in neonatal mice vs juvenile mice. However, it is unclear if the data are controlled adequately for the bacterial burden in the lung, which would be a crucial control to control for epi-phenomena. Additionally, it is unclear if the molecules that regulate macrophage recruitment are defective in neonatal mice or if it is an issue of macrophage progenitor cells.

Reviewer #1 (Public Review):

Synapses are modulated by neural activity on a variety of timescales. Typical neural network models primarily consider long-lasting changes to synaptic strengths, applied while the network is learning, with synaptic strengths then being fixed after learning. However, shorter-term plasticity mechanisms are ubiquitous in the brain and have been shown to have significant computational and information-storage capabilities. Here the authors study these mechanisms in the context of the integration of information tasks. Their two primary contributions are to analyze these short-term mechanisms separately from recurrent connections to isolate the specific ways these might be useful and to apply ideas from population data analysis to dissect how their networks solve the tasks.

I thought this was a clear, well-written, and well-organized paper, tackling an important problem. I also found that the conclusions were adequately supported by the simulations and analyses shown. I particularly appreciated the careful analysis of how the different networks solved the task and found the distinction between hidden neurons reflecting accumulated evidence (attractor architecture) vs. reflecting inputs (MPN architecture) very interesting and potentially very useful for thinking about experimental observations. My comments are primarily about the connection to biology/biological interpretability as well as how this study relates to prior work.

1) I was confused about the nature of the short-term plasticity mechanism being modeled. In the Introduction, the contrast drawn is between synaptic rewiring and various plasticity mechanisms at existing synapses, including long-term potentiation/depression, and shorter-term facilitation and depression. And the synaptic modulation mechanism introduced is modeled on STDP (which is a natural fit for an associative/Hebbian rule, especially given that short-term plasticity mechanisms are more often non-Hebbian). On the other hand, in the network models the weights being altered by backpropagation are changes in strength (since the network layers are all-to-all), corresponding more closely to LTP/LTD. And in general, standard supervised artificial neural network training more closely resembles LTP/LTD than changing which neurons are connected to which (and even if there is rewiring, these networks primarily rely on persistent weight changes at existing synapses). Moreover, given the timescales of typical systems neuroscience tasks with input coming in on the 100s of ms timescale, the need for multiple repetitions to induce long-term plasticity, and the transient nature/short decay times of the synaptic modulations in the SM matrix, the SM matrix seems to be changing on a timescale faster than LTP/LTD and closer to STP mechanisms like facilitation/depression. So it was not clear to me what mechanism this was supposed to correspond to.

2) A number of studies have explored using short-term plasticity mechanisms to store information over time and have found that these mechanisms are useful for general information integration over time. While many of these are briefly cited, I think they need to be further discussed and the current work situated in the context of these prior studies. In particular, it was not clear to me when and how the authors' assumptions differed from those in previous studies, which specific conclusions were novel to this study, and which conclusions are true for this specific mechanism as opposed to being generally true when using STP mechanisms for integration tasks.

Reviewer #1 (Public Review):

This paper identifies an intracellular O-GlcNAc glycosylation of specific proteins in the control of bone formation and bone marrow adiposity. Compelling evidence is provided for the role of OGT-mediated O-GlcNAc glycosylation of RUNX2 in osteogenic differentiation versus OGT-mediated O-GlcNAc glycosylation of C/EBPβ in bone marrow adipogenesis.

Overall, the experiments have been done with great rigor, and sufficient details are provided for reproducibility. The authors developed a novel concept in the control of bone formation and bone marrow adiposity.

Reviewer #1 (Public Review):

The authors made some biologically reasonable approximations of the Pump and Leak model. e.g., assuming the alpha_0 parameter to be zero. These approximations significantly simplify the model and make the results much more intuitive, e.g., Eq. 4 in the main text. The authors proposed an interesting and simple model of amino acid production, which is argued to be the primary determinant of cell volume. Combined with the gene expression model proposed recently by Lin and Amir, their model can nicely explain the homeostasis of protein density. Furthermore, by considering the saturation of DNA and mRNA by RNA polymerase and ribosome, the authors extended Lin and Amir's model by introducing protein degradation, which I think is the key to explaining cytoplasm dilution. The authors also discussed other applications of their model, including mitotic swelling and nuclear scaling. Below are my major comments:

1. Eq. 2 is valid for stationary states where the cell volume is constant with time. However, many cells grow and divide, including yeast cells. I think the authors have implicitly neglected the effects of cell growth. The authors may want to mention this explicitly to avoid confusion.

2. It's unclear how the authors go from Eq. S.21 to Eq. 2, although the authors mentioned it is straightforward. I think the dilute solution assumption is used without explicit mention, at least in section A of the SI.

3. A slight deviation from equilibrium is implicitly assumed in Eq. S.22 I think since the flow is linearly proportional to the chemical potential difference. The authors may want to mention this explicitly since the linear assumption is not necessarily true for biological systems.

4. A more general gene expression model is recently proposed by some of the authors of Ref. 30, in which the saturation of DNA by RNAPs is due to a high free RNAP concentration near the promoter (Wang and Lin, Nature Communications, 2021). I think the exact saturation mechanism is not very important to the conclusions. Still, I think it's good to let readers be aware that there are biologically more realistic saturation mechanisms.

5. The success of the fitting in Figure 2E is intriguing but may not be a smoking gun evidence of the model's validity. All one needs is a protein number proportional to cell volume for tt**, as far as I understand. Alternative models incorporating the above features will be able to reproduce the fitting of Figure 2E as well, I think. For example, instead of adding protein degradation, one can alternatively assume that protein translation becomes much slower for t>t**, but amino acids are still produced at a constant rate. The time-dependences of amino acids and cell volume may not be important if one just wants to fit the data in Figure 2E since the cell volume dynamics are extracted from Figure 2B. The authors may want to discuss this point.

6. On line 752, the estimation of the average charge of proteins is unclear to me. How did the authors obtain z_p = 0.8?

Reviewer #1 (Public Review):

This work applies duplex sequencing to study point mutations in mice across tissues in young (4.5 months) and old mice (26 months). In this study, they identified 89,000 independent somatic mtDNA mutations representing the largest collection of somatic 'point' mtDNA mutation (not considering mtDNA deletions). They find that mtDNA mutations accumulate linearly with age in a clock-like manner but are not uniformly represented in all tissues. This indicates a likely constant 'clock-like' accumulation analogous to what is seen in the nuclear genome. This part of the paper is a comprehensive extension of work done by Arbeithuber et al., 2020. They also find variability between tissues of the ROS-linked (transversions) mutations. Similar to prior work by Kennedy and Loeb (2013 Plos Genetics) they conclude that ROS-linked mutations do not accumulate significantly with age. Lastly, the authors apply this knowledge and technique to interrogate whether mtDNA mutations are affected by two known treatments, elimipretide and nicotinamide mononucleotide, that have been shown to improve mitochondrial function and reverse apparent aging phenotypes. Here they demonstrate that these treatments reduced the low level of ROS accumulated mtDNA mutations seen in untreated tissues.

Comments:<br /> The paper states that they observed a combined total of 77,017 single-nucleotide variants (SNVs) and 12,031 insertion/deletions (In/Dels) across all tissue, age, and intervention groups. Collectively, these data represent the largest collection of somatic mtDNA mutations obtained in a single study to date. However, A study with more somatic mtDNA mutations by the LostArc method (PMID 32943091) revealed 35 million deletions (~ 470,000 unique spans) in skeletal muscle from 22 individuals with and 19 individuals without pathogenic variants in POLG. Thus, the authors should reword this part to say that this study represents the largest collections of mouse mtDNA point mutations detected, but not the largest amount of mutations (deletions exceed this number).

What is the theoretical limit of pt mutations in the mitochondrial genome, assuming only one pt mutation per genome? Doesn't 77000 detected independent pt mutations approach that limit? Can the authors estimate how many molecules contained two or more pt mutations? Did the analysis reveal any un-mutated regions implying an essential function? For example, on p.9 can the authors provide an explanation of why OriL and other G/C-rich regions were not uniformly covered as compared to the rest of the genome?

Given that mitochondrial disease usually doesn't present until >60% of the genomes are affected, the very low level of detected pt mutations observed in the mouse (and presumably similar to human) would mean that they are well below a physiological level. Thus, these low-level pt mutations are well tolerated. Can the authors estimate a theoretical age of the mouse (well beyond their life span) where over 50% of the genomes carry at least one pt mutation?

Also, the problem with this low level of pt mutations is that they are not physiological, the effect of the drug treatment causing a reduction in ROS-mediated transversions would not be expected to have a detectable effect on mitochondria. The improvement on mitochondrial seen by others is most likely independent of the mutations in the genome. There needs to be a cause and effect here and I don't see one.

There's no mention in this paper and methodology about how point mutations in nuclear-encoded mtDNA (NUMTs) are excluded from the reads and I'm worried that these errors are being read as rare errors in the mtDNA genome. While NUMTs have been documented for decades, a recent report in Science (PMID: 36198798) documents how frequently and fluidly NUMTs occur. Can the authors provide a clear explanation of how mutations in NUMTs are excluded?

Reviewer #1 (Public Review):

The manuscript by Hekselman et al presents analyses linking cell-types to monogenic disorders using over-expression of monogenic disease genes as the signal. The manuscript analyses data from 6 tissues (bone marrow, lung, muscle, spleen, tongue and trachea) together with ~1,000 rare diseases from OMIM (with ~2,000 associated genes) to identify cell-type of interest for specific disease of choice. The signal used by the approach is the relative expression of OMIM-genes in a particular cell type relative to the expression of the gene in the tissue of interest identifying cell-type-disease pairs that are then investigated through literature review and recapitulated using mouse expression. A potentially interesting finding is that disease genes manifesting in multiple tissues seem to hit same cell-types. Overall this important study combines multiple data analyses to quantify the connection between cell types and human disorders. However whereas some of the analyses are compelling, the statistical analyses are incomplete as they don't provide full treatment of type I error.

Reviewer #1 (Public Review):

This is a carefully performed and well-documented study to indicate that the FUS protein interacts with the GGGGCC repeat sequence in Drosophila fly models, and the mechanism appears to include modulating the repeat structure and mitigating RAN translation. They suggest FUS, as well as a number of other G-quadruplex binding RNA proteins, are RNA chaperones, meaning they can alter the structure of the expanded repeat sequence to modulate its biological activities.

Overall this is a nicely done study with nice quantitation. It remains somewhat unclear from the data and discussions in exactly what way the authors mean that FUS is an RNA chaperone: is FUS changing the structure of the repeat or does FUS binding prevent it from folding into alternative in vivo structure?

Reviewer #1 (Public Review):

This manuscript by Mahlandt, et al. presents a significant advance in the manipulation of endothelial barriers with spatiotemporal precision, and in the use of optogenetics to manipulate cell signaling in vascular biology more generally. The authors establish the role of Rho-family GTPases in controlling the cytoskeletal-plasma membrane interface as it relates to endothelial barrier integrity and function and adequately motivate the need for optogenetic tools for global and local signaling manipulation to study endothelial barriers.

Throughout the work, the optogenetic assays are conceptualized, described, and executed with exceptional attention to detail, particularly as it relates to potential confounding factors in data analysis and interpretation. Comparison across experimental setups in optogenetics is notoriously fraught, and the authors' control experiments and measurements to ensure equal light delivery and pathway activation levels across applications are very thorough. In demonstrating how these new opto-GEFs can be used to alter vascular barrier strength, the authors cleverly use fluorescent-labeled dextran polymers of different sizes and ECIS experiments to demonstrate the physiological relevance of BOEC monolayers to in vivo blood vessels. Of particular note, the resiliency of the system to multiple stimulation cycles and longer time course experiments is promising for use in vascular leakage studies.

Given that dozens of Rho GTPase-activating GEFs exist, an expanded rationale for the selection of p63, ITSN1, and TIAM1 in the form of discussion and literature citations would be helpful to motivate their selection as protein effectors in the engineered tools. Extensive tool engineering studies demonstrate the superiority of iLID over optogenetic eMags or rapamycin-based chemogenetic tools for these purposes. However, as the utility of iLID and eMags has been demonstrated for the manipulation of a variety of signaling pathways, the iSH-Akt demonstration does not seem necessary for these systems.

The demonstration of orthogonality in GTPase- and VE-cadherin-blocking antibody-mediated barrier function decreases and is compelling, even without full elucidation of the role of cell size or overlap in barrier strength. The discussion section presents a mature and thoughtful description of the limitations, remaining questions, and potential opportunities for the tools and technology developed in this work. Importantly, this manuscript demonstrates a commitment to scientific transparency in the ways in which the data are visualized, the methods descriptions, and the reagent and code sharing it presents, allowing others to utilize these tools to their full potential.

Reviewer #1 (Public Review):

This is a well-conceived and well-executed investigation of how activation loop autophosphorylation and IN-box autophosphorylation synergistically activate AURKB/INCENP. An elegant chemical ligation strategy allowed construction of the intermediate phospho-forms so that the contributions of each phosphorylation event to structure, dynamics, and activity could be dissected. Autophosphorylation at both sites serves to rigidify both AURKB and the IN-box, and to coordinate opening, twisting, and activation loop movements. Consistent with previous findings, both sites are necessary for enzymatic activity; further, this work finds that activation loop autophosphorylation occurs slowly in cis while IN-box autophosphorylation occurs quickly in trans.

Due to abundant previous work in the field, many of the conclusions of this paper were expected. However, that does not diminish the quality of the work, and the addition of how kinase dynamics contribute to activation is important for AURKB and many other kinases. The experimental results are clear and interpreted appropriately, with good controls. The computational work is also clearly explained and directly tied to the function of the enzyme, making it highly complementary to the experimental findings and to previously published structures.

Some minor limitations of the study:

1. Of note when interpreting the HDX data, there is no coverage of the peptide containing the activation loop autophosphorylation site T248 (Fig S2A), and as mentioned in the Discussion, the time scale of HDX is not able to capture differences in exchange in very flexible regions like the activation loop.

2. Some data lack robust statistical analysis, which would make the findings more compelling.

3. One point that might be clarified is how the occupancy of T248 was confirmed to be either fully phosphorylated in the [AURKB/IN-box]IN-deltaC or fully dephosphorylated in the IN-box K846N/R827Q mutant. Especially because T248 autophosphorylation is found to occur in cis, it is unclear how incubating the [AURKB/IN-box]IN-deltaC with traces of wild-type [AURKB/IN-box]all-P would ensure that T248 is phosphorylated.

Reviewer #1 (Public Review):

This paper by Melo et al. is a technically elegant study investigating the important emerging hypothesis that the brainstem preBötzinger complex (preBötC) region - a critical nuclear structure where the rhythm of breathing in mammals originates - has segregated subgroups of output neurons that modulate specific behaviors coordinated with breathing, in this study the orofacial muscle activity. The preBötC has been under intense investigation for several decades but the subregional neuronal subtype composition and organization are not fully understood. Understanding this organization and how breathing modulates specific behaviors has many implications for normal brain function and pathophysiology.

Strengths of the paper include:<br /> 1) The authors use an effective combinatorial dual viral transgenic approach for Cre-dependent expression of the chloride channel (GtACR2) and labeling of neurons projecting to the facial motor nucleus controlling orofacial muscle activity, for optogenetic photoinhibition of these preBötC neurons in vivo.<br /> 2) The experimental results presented convincingly support the authors' conclusion that a subgroup of preBötC neurons provides inspiratory modulation of facial motoneurons that appear to be distinct from other output neurons that drive inspiratory activity to bulbospinal neurons and neurons projecting to autonomic nervous system circuits.<br /> 3) These results advance our understanding of preBötC circuit organization that coordinates and integrates breathing with different motor and physiological behaviors.

Weaknesses:<br /> There are a few technical issues related to the photoinhibition paradigm used and the patterns of neuronal transduction with the dual viral transgenic approach used that the authors need to clarify.

Reviewer #1 (Public Review):

This research tackles an important question in evolutionary biology that has long stood on theory, with little experimental evidence to support this big idea. This paper provides a large natural dataset on several morphometric factors that allow a robust testing of the "handicap principle". The strength in this dataset comes from extensive field observations not only on morphology, but also fecundity and pairing behavior. The manuscript could use a little tightening up in prose, but the statistics and results are well explained. As the discussion mostly focuses on shrimp, generalizable principles are somewhat unclear. Overall, the research is an important finding that could one day be incorporated into undergraduate textbooks.

DOI: 10.7554/eLife.85800

Resource: (ZFIN Cat# ZDB-ALT-090324-1,RRID:ZFIN_ZDB-ALT-090324-1)

Curator: @evieth

SciCrunch record: RRID:ZFIN_ZDB-ALT-090324-1

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