Reviewer #1 (Public Review):

The authors report a study, where they have sequenced whole genomes of four individuals of an extinct species of butterfly from western North America (Glaucopsyche xerces), along with seven genomes of a closely related species (Glaucopsyche lygdamus), mainly from museum specimens, several to many decades old. They then compare these fragmented genomes to a high-quality, chromosome-level assembly of a genome of a European species in the same genus (Glaucopsyche alexis). They find that the extinct species shows clear signs of declining population sizes since the last glacial period and an increase in inbreeding, perhaps exacerbating the low viability of the populations and contributing to the extinction of the species.

The study really highlights how museum specimens can be used to understand the genetic variability of populations and species in the past, up to a century or more ago. This is an incredibly valuable tool, and can potentially help us to quickly identify whether current populations of rare and declining species are in danger due to inbreeding, or whether at least their genetic integrity is in good condition and other factors need to be prioritised in their conservation. In the case of extinct species, sequencing museum specimens is really our only window into the dynamics of genomic variability prior to extinction, and such information can help us understand how genetic variation is related to extinction.

I think the authors have achieved their goal admirably, they have used a careful approach to mapping their genomic reads to a related species with a high-quality genome assembly. They might miss out on some interesting genetic information in the unmapped reads, but by and large, they have captured the essential information on genetic variability within their mapped reads. Their conclusions on the lower genetic variability in the extinct species are sound, and they convincingly show that Glaucopyche xerces is a separate species to Glaucopsyche lygdamus (this has been debated in the past).

Reviewer #1 (Public Review):

First, I agree with the authors of this manuscript that conformational changes in the XFEL structures with 2.8 A resolution are not reliable enough for demonstrating the subtle changes in the electron transfer events in this bacterial photosynthesis system. Actually, the data statistics in the paper by Dods et al. showed that the high-resolution range of some of the XFEL datasets may include pretty high noise (low CC1/2 and high Rsplit) so the comparison of the subtle conformational changes of the structures is problematic.

The manuscript by Gai Nishikawa investigated time-dependent changes in the energetics of the electron transfer pathway based on the structures by Dods et al. by calculating redox potential of the active and inactive branches in the structures and found no clear link between the time-dependent structural changes and the electron transfer events in the XFEL structures published by Dods, R.et al. (2021). This study provided validation for the interpretation of the structures of those electron-transferring proteins.

The paper was well prepared.

Comments on latest version:

The revisions the authors have made have improved the manuscript.

Reviewer #2 (Public Review):

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

Comments on latest version:

The authors have satisfied my concerns. I consider that their present manuscript is more attractive and informative for readers.

Reviewer #1 (Public Review):

Summary: This paper performs fine-mapping of the silkworm mutants bd and its fertile allelic version, bdf, narrowing down the causal intervals to a small interval of a handful of genes. In this region, the gene orthologous to mamo is impaired by a large indel, and its function is later confirmed using expression profiling, RNAi, and CRISPR KO. All these experiments are convincingly showing that mamo is necessary for the suppression of melanic pigmentation in the silkworm larval integument.

The authors also use in silico and in vitro assays to probe the potential effector genes that mamo may regulate.

Strengths: The genotype-to-phenotype workflow, combining forward (mapping) and reverse genetics (RNAi and CRISPR loss-of-function assays) linking mamo to pigmentation are extremely convincing.

Weaknesses:

1) The last section of the results, entitled "Downstream target gene analysis" is primarily based on in silico genome-wide binding motif predictions.<br /> While the authors identify a potential binding site using EMSA, it is unclear how much this general approach over-predicted potential targets. While I think this work is interesting, its potential caveats are not mentioned. In fact the Discussion section seems to trust the high number of target genes as a reliable result. Specifically, the authors correctly say: "even if there are some transcription factor-binding sites in a gene, the gene is not necessarily regulated by these factors in a specific tissue and period", but then propose a biological explanation that not all binding sites are relevant to expression control. This makes a radical short-cut that predicted binding sites are actual in vivo binding sites. This may not be true, as I'd expect that only a subset of binding motifs predicted by Positional Weight Matrices (PWM) are real in vivo binding sites with a ChIP-seq or Cut-and-Run signal. This is particularly problematic for PWM that feature only 5-nt signature motifs, as inferred here for mamo-S and mamo-L, simply because we can expect many predicted sites by chance.

2) The last part of the current discussion ("Notably, the industrial melanism event, in a short period of several decades ... a more advanced self-regulation program") is flawed with important logical shortcuts that assign "agency" to the evolutionary process. For instance, this section conveys the idea that phenotypically relevant mutations may not be random. I believe some of this is due to translation issues in English, as I understand that the authors want to express the idea that some parts of the genome are paths of least resistance for evolutionary change (e.g. the regulatory regions of developmental regulators are likely to articulate morphological change). But the language and tone is made worst by the mention that in another system, a mechanism involving photoreception drives adaptive plasticity, making it sound like the authors want to make a Lamarckian argument here (inheritance of acquired characteristics), or a point about orthogenesis (e.g. the idea that the environment may guide non-random mutations).<br /> Because this last part of the current discussion suffers from confused statements on modes and tempo of regulatory evolution and is rather out of topic, I would suggest removing it.

In any case, it is important to highlight here that while this manuscript is an excellent genotype-to-phenotype study, it has very few comparative insights on the evolutionary process. The finding that mamo is a pattern or pigment regulatory factor is interesting and will deserve many more studies to decipher the full evolutionary study behind this Gene Regulatory Network.

Minor Comment :

The gene models presented in Figure 1 are obsolete, as there are more recent annotations of the Bm-mamo gene that feature more complete intron-exon structures, including for the neighboring genes in the bd/bdf intervals. It remains true that the mamo locus encodes two protein isoforms.<br /> An example of the Bm-mamo locus annotation, can be found at : https://www.ncbi.nlm.nih.gov/gene/101738295<br /> RNAseq expression tracks (including from larval epidermis) can be displayed in the embedded genome browser from the link above using the "Configure Tracks" tool.

Based on these more recent annotations, I would say that most of the work on the two isoforms remains valid, but FigS2, and particularly Fig.S2C, need to be revised.

Reviewer #2 (Public Review):

Summary:<br /> The authors tried to identify new genes involved in melanin metabolism and its spatial distribution in the silkworm Bombyx mori. They identified the gene Bm-mamo as playing a role in caterpillar pigmentation. By functional genetic and in silico approaches, they identified putative target genes of the Bm-mamo protein. They showed that numerous cuticular proteins are regulated by Bm-mamo during larval development.

Strengths:<br /> -preliminary data about the role of cuticular proteins to pattern the localization of pigments<br /> - timely question<br /> - challenging question because it requires the development of future genetic and cell biology tools at the nanoscale

Weaknesses:<br /> - statistical sampling limited<br /> - the discussion would gain in being shorter and refocused on a few points, especially the link between cuticular proteins and pigmentation. The article would be better if the last evolutionary-themed section of the discussion is removed.

A recent paper has been published on the same gene in Bombyx mori (https://www.sciencedirect.com/science/article/abs/pii/S0965174823000760) in August 2023. The authors must discuss and refer to this published paper through the present manuscript.

Reviewer #1 (Public Review):

This manuscript presents an important study that contributes to our understanding of the reliability of ancient environmental DNA (aeDNA) extracted from sediment cores. The authors address the potential biases and challenges associated with using aeDNA to infer past ecosystems, specifically focusing on the case of mammoths and woolly rhinoceroses in the Yamal peninsula, West Siberia.

The introduction provides an overview of the significance of sedimentary deposits as archives of past ecosystem changes and illustrates the remarkable insights gained from previous studies using aeDNA, highlighting its potential for reconstructing paleoecology, phylogeography, and understanding extirpation and extinction events of keystone taxa. The authors then report the detection of DNA and near complete mitochondrial genomes of multiple mammoth and woolly rhinoceros individuals in the sampled sediment cores (which are dated to the last few centuries). The authors then employed additional methods to confirm the presence of ancient DNA from mammoths in these sediment cores. Conventional PCR and Sanger sequencing of a mammoth COI fragment confirmed the amplification of mammoth DNA. Mammal metabarcoding and droplet digital PCR (ddPCR) further supported the detection of mammoth DNA in both cores.

The hybridisation enrichment experiment results showed high read counts assigned to Mammuthus, ranging from 2,852 to 72,919 reads per library in core LK-001. Negative controls did not produce any reads assigned to mammals, indicating the absence of contamination. The study also revealed the presence of woolly rhinoceros sequences in the sediment cores, with 12 out of 23 libraries producing more than 100 reads assigned to woolly rhinoceros. The total number of woolly rhinoceros reads was 2,737, and the cumulative mitogenome coverage reached 44%.

The authors carefully addressed the incongruity between the temporal occurrence of these extinct species and the presence of their DNA in recent sediments. They proposed several mechanisms that could explain the recovery of Pleistocene megafaunal DNA in the sediment cores. The minor amount of ancient DNA post mortem damage observed in the mammoth sequences indicates exceptional preservation, consistent with an origin from (recent) permafrost. The dynamics of permafrost thawing and redeposition in the study area provide a plausible explanation for the presence of ancient DNA in the sediments. The authors discuss potential mechanisms for the redistribution of Late Pleistocene material in the sediments, including thermo-denudation processes, methane emissions from degrading permafrost, and the formation of taliks and methane seepage. These processes can disturb the stratigraphy of lake sediments and potentially mix ancient material within the modern sediments. I believe the conclusions are supported by the data and the manuscript is well-written and clear to follow for the reader.

Reviewer #2 (Public Review):

Summary:<br /> The authors report the successful retrieval of mitogenomes from extinct Pleistocene megafauna (woolly Mammoth and woolly rhino) from recent sediment cores from two close Siberian lakes. The cores are too recent to represent real time points of these two extinct species (known to have been extinct for several thousands of years) and therefore, the most plausible interpretation is that permafrost thawing and similar physical processes in the lakes have made surface old ancient DNA, maybe from nearby, deep-buried carcasses.

Strengths:<br /> The pattern of postmortem damage at the end of the Mammoth DNA reads as well as the length distribution (reported in Figure 1) is expected for authentic ancient DNA extracts (besides the phylogenetic evidence). These results pose a question, in my view, on the general reliability of sedimentary DNA in similar contexts, especially in the absence of direct radiocarbon dating of associated remains and in the absence of an understanding of the local geo-physical dynamics. At the same time, the evidence reported here suggests that, at least in Siberian lakes, the sediments can preserve a rich ancient DNA record that it is worth surveying.

Weaknesses:<br /> Although admittedly the work can represent two cases of environments with singular thermal conditions and geodynamics, it opens also the possibility of studying more lake sediments for trying to understand if these findings can be generalized.

Reviewer #3 (Public Review):

Summary:<br /> In this study, the researchers used ancient environmental DNA (aeDNA) retrieved from sediment cores, from two lakes in the Arctic, on the Yamal peninsula, in Siberia. The dating of one of the cores, showed that the sediment layers were very recent (ranging between the years 2019 - 1895). From this core they sequenced 23 libraries which were enriched for mammal mitochondrial genomes. They found a high proportion of two species that have been extinct for thousands of years, the mammoth and the woolly rhinoceros. The highest proportion of mammoth reads were found in very young layer (~81 years old) and as this initial finding does not match the temporal occurrence of the species, they confirmed the identification with several other methods. Additionally, they applied a different dating method on some samples and found that the aging of the samples was not completely congruent. The authors suggest the that the presence of these two Pleistocene megafauna in such recent sediment layers is a consequence of physical processes, specific to the study site, and that the high quality of the aeDNA recovered is a result of permafrost preservation.

Strengths:<br /> The strengths of the study are in the rigorous confirmation of the identification of the taxa with four different PCR and sequencing techniques being used, the initial enrichment panel, and then subsequent metabarcoding PCRs, and taxa specific PCR for COI and cytB. Along with the ancient DNA protocol applied, this is therefore very convincing that the DNA detected in the samples is indeed from the Pleistocene mammals. Additionally, two methods were used to age the sediment cores, and although the depth of the samples tested do not overlap, they give reasonable ages (apart from the anomalous sample) and all together these are robust results.

Weaknesses:<br /> The paper could benefit from clearer aims in the introductions because as it stands the initial aim states that the authors are looking for Arctic mammal abundances through time. However, there are no results relating to general arctic mammal biodiversity presented, which leaves the reader wondering. Perhaps the focus of the study is more on identifying and dating the Pleistocene megafauna. Additionally, it is presented as an analysis on the two taxa, but it feels like the woolly rhinoceros does not receive the same treatment as the mammoth, as there are no additional molecular results, confirmation or figures relating to DNA from this taxa.

Overall the results support that there has been some movement of DNA throughout the sediment core which may impact the dating of the last occurrence of particular extinct taxa. As highlighted, though the geological processes by which this may have arisen are specific to this particular lake and may not be broadly relevant, therefore highlighting that knowledge of each system is important to understanding DNA distribution.

Reviewer #1 (Public Review):

This manuscript by Neininger-Castro and colleagues presents a novel automatic image analysis method for assessing sarcomeres, the basic units of myofibrils and validates this tool in a couple of experimental approaches that interfere with sarcomere assembly in iPSC-cardiomyocytes (iPSC-CM).

Automatic quantification of sarcomeres is definitely something that is useful to the field. I am surprised that there is no reference in the manuscript to SarcTrack, published by Toepfer and colleagues in 2019 (PMID 30700234), which has exactly the same purpose. The advantage of the image analysis software presented in the current manuscript appears to me to be that it can cover both mature sarcomeres and nascent sarcomeres in premyofibrils effectively.

Reviewer #2 (Public Review):

Neininger-Castro et al report on their original study entitled "Independent regulation of Z-lines and M-lines during sarcomere assembly in cardiac myocytes revealed by the automatic image analysis software sarcApp", In this study, the research team developed two software, yoU-Net and sarcApp, that provide new binarization and sarcomere quantification methods. The authors further utilized human induced pluripotent stem cell-derived cardiomyocytes (hiCMs) as their model to verify their software by staining multiple sarcomeric components with and without the treatment of Blebbistatin, a known myosin II activity inhibitor. With the treatment of different Blebbistatin concentrations, the morphology of sarcomeric proteins was disturbed. These disrupted sarcomeric structures were further quantified using sarcApp and the quantification data supported the phenotype. The authors further investigated the roles of muscle myosins in sarcomere assembly by knocking down MYH6, MYH7, or MYOM in hiCMs. The knockdown of these genes did not affect Z-line assembly yet the knockdown of MYOM affected M-line assembly. The authors demonstrated that different muscle myosins participate in sarcomere assembly in different manners.

Reviewer #3 (Public Review):

Neininger-Castro and colleagues developed software tools for the quantification of sarcomeres and sarcomere-precursor features in immunostained human induced pluripotent stem cell-derived cardiac myocytes (hiCMs). In the first part they used a deep-learning- based model called a U-Net to construct and train a network for binarization of immunostained cardiomyocyte images. They also wrote graphical user interface (GUI) software that will assist other labs to use this approach and made it publicly available. They did not compare their approach to existing ones, but example from one image suggests their binarization tool outperforms Otsu thresholding binarization.

In the second part they developed a software tool called sarcApp that classifies sarcomere structures in the binarized image as a Z-Line or Z-Body and assigns each to either a myofibril or to stress fibers. The tools can then automatically count and measure multiple features (33 per cell and 24 per myofibril) and report them on a per-cell, per-myofibril, and per- stress fiber basis.

To test the tools they used Blebbistatin to inhibit sarcomere assembly and showed that the sarcApp tool could capture changes in multiple features such as fewer myofibrils, fewer Z-Lines, decreased myofibril persistence, decreased Z-Line length and altered myofibril orientation in the Blebbistatin treated cells. With some changes the tool was also shown to quantify sarcomeres in titin and myomesin stained cardiomyocytes.

Finally they used sarcApp to quantify the changes in sarcomere assembly after siRNA mediated knockout of MYH7, MYH7, or MYOM. The analysis indicates that neither MYH6 nor MYH7 knockdown perturbed the assembly of Z- or M-lines, and that knockdown of MYOM perturbed the A-band/M-Line but not the Z-Line assembly according to features captured by the sarcApp tool.

Overall the authors developed and made publicly available an excellent software tool that will be very useful for labs that are interested in studying sarcomere assembly. Multiple features that are difficult to measure or count manually can be automatically measured by the software quickly and accurately.

There are however some remaining questions about these tools:<br /> 1. The binarization tool which is tailored to sarcomere image binarization appears promising but was not systematically compared with existing approaches. Example from one cell suggests it outperforms Otsu's binarization approach.<br /> 2. How robust is the tool? The tool was tested on images from one type of cardiomyocytes (hiCMs) taken from one lab using Nikon Spinning Disk confocal microscope equipped with Apo TIRF Oil 100X 1.49 NA objective or instant Structured Illumination Microscopy (iSIM), using deconvolution (Microvolution software) and in a specific magnification. It remains to be seen whether the tool would be equally effective with images taken with other microscopy systems, with other cardiomyocytes (chick or neonatal rat), with different magnifications, live imaging, etc. The authors state that this approach is also useful in other situations, but the data is not included in this manuscript.<br /> 3. The tool was developed for evaluation of sarcomere assembly. The authors show that for this application it can detect the perturbation by Blebbistatin, or knockdown of sarcomeric genes. It remains to be seen if this tool is also useful for assessment of sarcomere structure for other questions beside sarcomere assembly and in other sarcomere pathologies.

Reviewer #1 (Public Review):

The authors use electrophysiological and behavioral measurements to examine how animals could reliably determine odor intensity/concentration across repeated experiences. Because stimulus repetition leads to short-term adaptation evidenced by reduced overall firing rates in the antennal lobe and firing rates are otherwise concentration-dependent, there could be an ambiguity in sensory coding between reduced concentration or more recent experience. This would have a negative impact on the animal's ability to generate adaptive behavioral responses that depend on odor intensities. The authors conclude that changes in concentration alter the constituent neurons contributing to the neural population response, whereas adaptation maintains the 'activated ensemble' but with scaled firing rates. This provides a neural coding account of the ability to distinguish odor concentrations even after extended experience. Additional analyses attempt to distinguish hypothesized circuit mechanisms for adaptation but are inconclusive. A larger point that runs through the manuscript is that overall spiking activity has an inconsistent relationship with behavior and that the structure of population activity may be the more appropriate feature to consider.

To my knowledge, the dissociation of effects of odor concentration and adaptation on olfactory system population codes was not previously demonstrated. This is a significant contribution that improves on any simple model based on overall spiking activity. The primary result is most strikingly supported by visualization of a principal components analysis in Figure 4. However, there are some weaknesses in the data and analyses that limit confidence in the overall conclusions.

1) Behavioral work interpreted to demonstrate discrimination of different odor concentrations yields inconsistent results. Only two of the four odorants follow the pattern that is emphasized in the text (Figure 1F). Though it's a priori unlikely that animals are incapable of distinguishing odor concentrations at any stage in adaptation, the evidence presented is not sufficient to reach this conclusion.<br /> 2) While conclusions center on concepts related to the combination of activated neurons or the "active ensemble", this specific level of description is not directly demonstrated in any part of the results. We see individual neural responses and dimensional reduction analyses, but we are unable to assess to what extent the activated ensemble is maintained across experience.<br /> 3) There is little information about the variance or statistical strength of results described at the population level. While the PCA presents a compelling picture, the central point that concentration changes and adaptation alter population responses across separable dimensions is not demonstrated quantitatively. The correlation analysis that might partially address this question is presented to be visually interpreted with no additional testing.<br /> 4) Results are often presented separately for each odor stimulus or for separate datasets including two odor stimuli. An effort should be made to characterize patterns of results across all odor stimuli and their statistical reliability. This concern arises throughout all data presentations.<br /> 5) The relevance of the inconclusive analysis of inferred adaptation mechanisms in Figure 2d-f and the single experiment including a complex mixture in Figure 7 to the motivating questions for this study are unclear.<br /> 6) Throughout the description of the results, typical standards for statistical reporting (sample size, error bars, etc.) are not followed. This prevents readers from assessing effect sizes and undermines the ability to assign a confidence to any particular conclusion.

Reviewer #2 (Public Review):

Summary:<br /> The authors' main goal was to evaluate how both behavioral responses to odor, and their early sensory representations are modified by repeated exposure to odor, asking whether the process of adaptation is equivalent to reducing the concentration of an odor. They open with behavioral experiments that actually establish that repeated odor presentation increases the likelihood of evoking a behavioral response in their experimental subjects - locusts. They then examine neural activity patterns at the second layer of the olfactory circuit. At the population level, repeated odor exposure reduces total spike counts, but at the level of individual cells there seems to be no consistent guiding principle that describes the adaptation-related changes, and therefore no single mechanism could be identified.

Both population vector analysis and pattern correlation analysis indicate that odor intensity information is preserved through the adaptation process. They make the closely related point that responses to an odor in the adapted state are distinct from responses to lower concentration of the same odor. These analyses are appropriate, but the point could be strengthened by explicitly using some type of classification analysis to quantify the adaptation effects. e.g. a confusion matrix might show if there is a gradual shift in odor representations, or whether there are trials where representations change abruptly.

Strengths:<br /> One strength is that the work has both behavioral read-out of odor perception and electrophysiological characterization of the sensory inputs and how both change over repeated stimulus presentations. It is particularly interesting that behavioral responses increase while neuronal responses generally decrease. Although the behavioral effect could occur fully downstream of the sensory responses the authors measure, at least those sensory responses retain the core features needed to drive behavior despite being highly adapted.

Weaknesses:<br /> Ultimately no clear conceptual framework arises to understand how PN responses change during adaptation. Neither the mechanism (vesicle depletion versus changes in lateral inhibition) nor even a qualitative description of those changes. Perhaps this is because much of the analysis is focused on the entire population response, while perhaps different mechanisms operate on different cells making it difficult to understand things at the single PN level.

From the x-axis scale in Fig 2e,f it appeared to me that they do not observe many strong PN responses to these stimuli, everything being < 10 spikes/sec. So perhaps a clearer effect would be observed if they managed to find the stronger responding PNs than captured in this dataset.

Reviewer #3 (Public Review):

Summary:<br /> How does the brain distinguish stimulus intensity reduction from response reductions due to adaptation? Ling et al study whether and how the locust olfactory system encodes stimulus intensity and repetition differently. They show that these stimulus manipulations have distinguishable effects on population dynamics.

Strengths:<br /> 1. Provides a potential strategy with which the brain can distinguish intensity decrease from adaptation. -- while both conditions reduce overall spike counts, intensity decrease can also changes which neurons are activated and adaptation only changes the response magnitude without changing the active ensemble.<br /> 2. By interleaving a non-repeated odor, they show that these changes are odor-specific and not a non-specific effect.<br /> 3. Describes how proboscis orientation response (POR) changes with stimulus repetition., Unlike the spike counts, POR increases in probability with stimulus. The data portray the variability across subjects in a clear way.

Weaknesses:<br /> 1. Behavior<br /> a. While the "learning curve" of the POR is nicely described, the behavior itself receives very little description. What are the kinematics of the movement, and do these vary with repetition? Is the POR all-or-nothing or does it vary trial to trial?

b. What are the reaction times? This can constrain what time window is relevant in the neural responses. E.g., if the reaction time is 500 ms, then only the first 500 ms of the ensemble response deserves close scrutiny. Later spikes cannot contribute.

c. The behavioral methods are lacking some key information. While references are given to previous work, the reader should not be obligated to look at other papers to answer basic questions: how was the response measured? Video tracking? Hand scored?

d. Can we be sure that this is an odor response? Although airflow out of the olfactometer is ongoing throughout the experiment, opening and closing valves usually creates pressure jumps that are likely to activate mechanosensors in the antennae.

e. What is the baseline rate of PORs in the absence of stimuli?

e.What can you say about the purpose of the POR? I lack an intuition for why a fly would wiggle the maxillary palps. This is a question that is probably impossible to answer definitively, but even a speculative explanation would help the reader better understand.

2. Physiology<br /> a. Does stimulus repetition affect "spontaneous" activity (i.e., firing in the interstimulus interval? To study this question, in Figures 2b and c, it would be valuable to display more of the pre-stimulus period, and a quantification of the stability or lability of the inter-stimulus activity.

b. When does the response change stabilize? While the authors compare repetition 1 to repetition 25, from the rasters it appears that the changes have largely stabilized after the 3rd or 4th repetition. In Figure 5, there is a clear difference between repetition 1-3 or so and the rest. Are successive repetitions more similar than more temporally-separated repetitions (e.g., is rep 13 more similar to 14 than to 17?). I was not able to judge this based on the dendrograms of Figure 5. If the responses do stabilize at it appears, it would be more informative to focus on the dynamics of the first few repetitions.

c. How do temporal dynamics change? Locust PNs have richly varied temporal dynamics, but how these may be affected is not clear. The across-population average is poorly suited to capture this feature of the activity. For example, the PNs often have an early transient response, and these appear to be timed differently across the population. These structures will be obscured in a cross population average. Looking at the rasters, it looks like the initial transient changes its timing (e.g., PN40 responses move earlier; PN33 responses move later.). Quantification of latency to first spike after stimulus may make a useful measure of the dynamics.

d. How legitimate is the link between POR and physiology? While their changes can show a nice correlation, the fact the data were taken from separate animals makes them less compelling than they would be otherwise. How feasible is it to capture POR and physiology in the same prep? This would be most helpful, but I suspect may be too technically challenging to be within scope.

Reviewer #1 (Public Review):

The authors put forth the hypothesis that hepatocyte and/or non-parenchymal liver MCT1 may be responsible for physiologic effects (lower body weight gain and less hepatic steatosis) in MCT1 global heterozygote mice. They generate multiple tools to test this hypothesis, which they combine with mouse diets that induce fatty liver, steatohepatitis and fibrosis. Novel findings include that deletion of hepatocyte MCT1 does not change liver lipid content, but increases liver fibrosis. Deletion of hepatic stellate cell (HSC) MCT1 does not substantially affect any liver parameter, but concomitant HSC MCT1 deletion does reverse fibrosis seen with hepatocyte MCT1 knockout or knockdown. In both models, plasma lactate levels do not change, suggesting that liver MCT1 does not substantially affect systemic lactate. In general, the data match the conclusions of the manuscript, and the studies are well-conducted and well-described. Further work would be necessary to dissect mechanism of fibrosis with hepatocyte MCT1, and whether this is due to changes in local lactate (as speculated by the authors) or another MCT1 substrate. This would be important to understand this novel potential cross-talk between hepatocytes and HSCs.

A parallel and perhaps more important advance is the generation of new methodology to target HSC in mice, using modified siRNA and by transduction of AAV9-Lrat-Cre. Both methods would reduce the need to cross floxed mice with the Lrat-Cre allele, saving time and resources. These tools were validated to an extent by the authors, but not sufficiently to ensure that there is no cross-reactivity with other liver cell types. For example, AAV9-Lrat-Cre-transduced MCT1 floxed mice show compelling HSC but not hepatocyte Mct1 knockdown, but other liver cell types should be assessed to ensure specificity. This is particularly important as overall liver Mct1 decreased by ~30% in AAV9-Lrat-Cre-transduced mice, which may exceed HSC content of these mice, especially when considering a 60-70% knockdown efficiency. This same issue also affects Chol-MCT1-siRNA, which the authors demonstrate to affect hepatocytes and HSC, but likely affects other cell types not tested. As this is a new and potentially valuable tool, it would be important to assess Mct1 expression across more non-parenchymal cells (i.e. endothelial, cholangiocytes, immune cells) to determine penetration and efficacy.

Reviewer #2 (Public Review):

In this study, the authors seek to answer two main questions: 1) Whether interfering with lactate availability in hepatocytes through depletion of hepatocyte specific MCT-1 depletion would reduce steatosis, and 2) Whether MCT-1 in stellate cells promote fibrogenesis. While the first question is based on the observation that haploinsufficiency of MCT-1 makes mice resistant to steatosis, the rationale behind how MCT-1 could impact fibrogenesis in stellate cells is not clear. A more detailed discussion regarding how lactate availability would regulate two different processes in two different cell types would be helpful. The authors employ several mouse models and in vitro systems to show that MCT1 inhibition in hepatic stellate cells reduces the expression of COL-1. The significance of the findings is moderately impacted due to the following considerations:

a) Fibrosis in human NAFLD is a significant problem as a predictor of liver related mortality and is associated with type 1 and type 3 collagen. However, the reduction in COL1 in stellate cells did not amount to a reduction in liver fibrosis even in cell specific KO (in Fig 7E, there is no indication of whether Sirius red staining was different between HSC KO and control mice- the authors mention a downward trend in the text). The authors postulate that type 1 COL may not be the more predominant form of fibrosis in the model. This does not seem likely, since the same ob/ob mouse model was used to determine that fibrosis was enhanced with hepatocyte specific MCT-1 KO and decreased with Chol MCT-1KO. Measurements of different types of collagens in their model and the effect of MCT-1 on different types could be more informative. In particular, although collagens are the structural building blocks for hepatic fibrosis, fibrosis can also be controlled by matrix remodeling factors such as Timp1, Serpine 1, PAI-1 and Lox.

b) The authors use multiple animal models including cell specific KO to conclude that stellate cell MCT-1 inhibition decreases COL-1. However, the mechanisms behind this reduced expression of COL-1 are not discussed or explored, making it descriptive.

c) Different types of diets are used in this study which could impact lactate availability. Choline deficiency diets are reported to cause weight loss, and importantly have none of the metabolic features of human NASH. Therefore, their utility is doubtful, especially for this study which proposes to investigate if metabolic dysregulation and substrate availability could be a tool for therapy.

d) Hepatocyte specific MCT-1 KO mice seem to have increased COL-1 production, despite no noticeable difference in hepatocyte steatosis. The reasons for this are not discussed. Fibrosis in NASH is thought to be from stellate cell activation secondary to signals from hepatocellular damage. There is no evidence that there was a difference in either of these parameters in the mouse models used.

e) The authors report that serum lactate levels did not rise after MCT-1 silencing, but the reasons behind this are unclear. There is insufficient data about lactate production and utilization in this model, which would be useful to interpret data regarding steatosis and fibrosis development. For example, does the MCT-1 KO prevent hepatocyte and stellate cell net import or export of lactate? What is the downstream metabolic consequence in terms of pyruvate, acetylCoA and the NAD/NADH levels. Does the KO have downstream effects on mitochondrial TCA cycling?

f) MCT-1 protein expression is measured only in the in vitro assay. Similar quantitation through western blot is not shown in the animal models.

Reviewer #3 (Public Review):

A major finding of this work is that loss of monocarboxylate transporter 1 (MCT1), specifically in stellate cells, can decrease fibrosis in the liver. However, the underlying mechanism whereby MCT1 influences stellate cells is not addressed. It is unclear if upstream/downstream metabolic flux within different cell types leads to fibrotic outcomes. Ultimately, the paper opens more questions than it answers: why does decreasing MCT1 expression in hepatocytes exacerbate disease, while silencing MCT1 in fibroblasts seems to alleviate collagen deposition? Mechanistic studies in isolated hepatocytes and stellate cells could enhance the work further to show the disparate pathways that mediate these opposing effects. The work highlights the complexity of cellular behavior and metabolism within a disease environment but does little to mechanistically explain it.

The observations presented are compelling and rigorous, but their impact is limited by the nearly complete lack of mechanistic insight presented in the manuscript. As also mentioned elsewhere, it is important to know whether lactate import or export (or the transport of another molecule-like ketone bodies, for example) is the decisive role of MCT1 for this phenotype. Beyond that, it would be interesting, albeit more difficult, to determine how that metabolic change leads to these fibrotic effects.

Kuppfer cells are initially analyzed and targeted. These cells may play a major role in fibrotic response. It will be interesting to determine the effects of lactate metabolism in other cells within the microenvironment, like Kuppfer cells, to gain a complete understanding of how metabolism is altered during fibrotic change.

The timing of MCT1 depletion raises concern, as this is a largely prophylactic experiment, and it remains unclear if altering MCT1 would aid in the regression of established fibrosis. Given the proposal for translation to clinical practice, this will be an important question to answer.

Reviewer #1 (Public Review):

The cerebral cortex, or surface of the brain, is where humans do most of their conscious thinking. In humans, the grooves (sulci) and bumps (convolutions) have a particular pattern in a region of the frontal lobe called Broca's area, which is important for language. Specialists study features imprinted on the internal surfaces of braincases in early hominins by casting their interiors, which produces so-called endocasts. A major question about hominin brain evolution concerns when, where, and in which fossils a humanlike Broca's area first emerged, the answer to which may have implications for the emergence of language. The researchers used advanced imaging technology to study the endocast of a hominin (KNM-ER 3732) that lived about 1.9 million years ago (Ma) in Kenya to test a recently published hypothesis that Broca's remained primitive (apelike) prior to around 1.5 Ma. The results are consistent with the hypothesis and raise new questions about whether endocasts can be used to identify the genus and/or species of fossils.

Reviewer #2 (Public Review):

The authors present new data of endocranial surface details from the early Homo specimen KNM-ER 3732 and discuss the evolution of brain surface features that might be related to the evolution of language in the hominin lineage.

Comments and issues raised by the reviewers have been addressed adequately. I am sure that this contribution will revive discussion about these issues.

Reviewer #3 (Public Review):

The authors provide a detailed analysis of the sulcal and sutural imprints preserved on the natural endocast and associated cranial vault fragments of the KNM-ER3732 early Homo specimen. The analyses indicate a primitive ape-like organization of this specimen's frontal cortex. Given the geological age of around 1.9 million years, this is the earliest well-documented evidence of a primitive brain organization in African Homo.

The various points raised by the reviewers and the responses provided by the authors illustrate that paleoneurology is a research field where little consensus has been reached over the past century. This is due not only to the fragmentary preservation of most fossil endocasts, but also to the limitations of scientific inference in general, and paleoneurological inference in particular. Like any scientific hypothesis, a paleoneurological hypothesis cannot be proven, but at best be falsified, leaving a wide field of possible alternative hypotheses. Furthermore, endocranial morphology does not equate cerebral morphology. A classical example: the endocranial Broca cap is not identical to the cortical Broca area. And last but not least, taxonomy cannot resolve questions of phylogeny.

Reviewer #2 (Public Review):

In this work, the authors investigated the pectoralis work loop and the function of the supracoracoideus muscle in the down stroke during slow flight in doves. The aim of this study was to determine how aerodynamic force is generated, using simultaneous high-speed measurements of the wings' kinematics, aerodynamics, and activation and strain of pectoralis muscles during slow flight. The measurements show a reduction in the angle of attack during mid-downstroke, which induces a peak power factor and facilitates the tensioning of the supracoracoideus tendon with pectoralis power, which then can be released in the up-stroke. By combining the data with a muscle mechanics model, the timely tuning of elastic storage in the supracoracoideus tendon was examined and showed an improvement of the pectoralis work loop shape factor. Finally, other bird species were integrated into the model for a comparative investigation.

The major strength of the methods is the simultaneous application of four high-speed techniques - to quantify kinematics, aerodynamics and muscle activation and strain - as well as the implementation of the time-resolved data into a muscle mechanics model. With a thorough analysis which supports the conclusions convincingly, the authors achieved their goal of reaching an improved understanding of the interplay of the pectoralis and supracoracoideus muscles during slow flight and the resulting energetic benefits.

Reviewer #1 (Public Review):

The authors sought to resolve the coordinated functions of the two muscles that primarily power flight in birds (supracoracoideus and pectoralis), with particular focus on the pectoralis. Technology has limited the ability to resolve some details of pectoralis function, so the authors developed a model that can make accurate predictions about this muscle's function during flight. The authors first measured aerodynamic forces, wing shape changes, and pectoralis muscle activity in flying doves. They used cutting-edge techniques for the aerodynamic and wing shape measurements and they used well-established methods to measure activity and length of the pectoralis muscle. The authors then developed two mathematical models to estimate the instantaneous force vector produced by the pectoralis throughout the wing stroke. Finally, the authors applied their mathematical models to other-sized birds in order to compare muscle physiology across species.

The strength of the methods is that they smoothly incorporate techniques from many complementary fields to generate a comprehensive model of pectoralis muscle function during flight. The high-speed structured-light technique for quantifying surface area during flight is novel and cutting-edge, as is the aerodynamic force platform used. These methods push the boundaries of what has historically been used to quantify their respective aspects of bird flight and their use here is exciting. The methods used for measuring muscle activation and length are standard in the field. Together, these provide both a strong conceptual foundation for the model and highlight its novelty. This model allows for estimations of muscle function that are not feasible to measure in live birds during flight at present. The weakness of this approach is that it relies heavily on a series of assumptions. While the research presented in this paper makes use of powerful methods from multiple fields, those methods each have assumptions inherent to them that simplify the biological system of study. This reduction in the complexity of phenomena allows the specific measurements to be made. In joining the techniques of multiple fields to study the greater complexity of the phenomenon of interest, the assumptions are all incorporated also. Furthermore, assumptions are inherent to mathematical modeling of biological phenomena. That being said, the authors acknowledge and justify their assumptions at each step and their model seems to be quite good at predicting muscle function.

Indeed, the authors achieve their aims. They effectively integrate methods from multiple disciplines to explore the coordination and function of the pectoralis and supracoracoideus muscles during flight. The conclusions that the authors derive from their model address the intended research aim.

The authors demonstrate the value of such interdisciplinary research, especially in studying complex behaviors that are difficult or infeasible to measure in living animals. Additionally, this work provides predictions for muscle function that can be tested empirically. These methods are certainly valuable for understanding flight but also have implications for biologists studying movement and muscle function more generally.

Reviewer #1 (Public Review):

This work describes a structural analysis of the tripartite HipBST toxin-antitoxin (TA) system, which is related to the canonical two-component HipBA system composed of the HipA serine-threonine kinase toxin and the HipB antitoxin. The crystal structure of the kinase-inactive HipBST complex of the Enteropathogenic E. coli O127:H6 was solved and revealed that HipBST forms a hetero-hexameric complex composed of a dimer of HipBST heterotrimers that interact via the HipB subunit. The HipS antitoxin shows a structural resemblance to HipA N-terminal region and the HipT toxin represents to the core kinase domain of HipA, indicating that in HipBST the hipA toxin gene was likely split in two genes, namely hipS and hipT.

The structure also reveals a conserved and essential Trp residue within the HipS antitoxin, which likely prevents the conserved "Gly-rich loop" of HipT from adopting an inward conformation needed for ATP binding. This work also shows that the regulating Gly-rich loop of the HipT toxin contains conserved phosphoserine residues essential for HipT toxicity that are key players within the HipT active site interacting network and which likely control antitoxin binding and/or activity.

Strengths:

The manuscript is well written and the experimental work well executed. It shows that major features of the classical two-component HipAB TA system have somehow been rerouted in the case of the tripartite HipBST. This includes the N-terminal domain of the HipA toxin, which now functions as bona fide antitoxin, and the partly relegated HipB antitoxin, which could only function as a transcription regulator. In addition, this work shows a new mode of inhibition of a kinase toxin and highlights the impact of the phosphorylation state of key toxin residues in controlling the activity of the antitoxin.

Weaknesses:

A major weakness of this work is the lack of data concerning the role of HipB, which likely does not act as an antitoxin. Does it act as a transcriptional regulator of the hipBST operon and to what extent both HipS and HipT contribute to such regulation? These are still open questions.

In addition, there is no in-depth structural comparison between the structure of the HipBST solved in the work and the two recent structures of HipBST from Legionella. This is also a major weakness of this work.

Reviewer #2 (Public Review):

The work by Bærentsen et al., entitled "Structural basis for regulation of a tripartite toxin-antitoxin system by dual phosphorylation" deals with the structural aspects of the control of the hipBST TA operon, the role of auto-phosphorylation in the activation and neutralisation of the enzyme and the direct effects of HipS and HipB in neutralisation. This is a follow-up to the Vang Nielsen et al., and Gerdes et al., papers from the same authors on this very unique TA module, that brings forth a thorough and well written dissection of an unusually complex regulatory system.

This is a much improved manuscript, the paper is more focused and the message is now clear.

Reviewer #3 (Public Review):

Summary:

The authors discovered that the RdnE effector possesses DNase activity, and in competition, P. mirabilis having RdnE outcompetes the null strain. Additionally, they presented evidence that the RdnI immunity protein binds to RdnE, suppressing its toxicity. Interestingly, the authors demonstrated that the RdnI homolog from a different phylum (i.e., Actinomycetota) provides cross-species protection against RdnE injected from P. mirabilis, despite the limited identity between the immunity sequences. Finally, using metagenomic data from human-associated microbiomes, the authors provided bioinformatic evidence that the rdnE/rdnI gene pair is widespread and present in individual microbiomes. Overall, the discovery of broad protection by non-cognate immunity is intriguing, although not necessarily surprising in retrospect, considering the prolonged period during which Earth was a microbial battlefield/paradise.

Strengths:

The authors presented a strong rationale in the manuscript and characterized the molecular mechanism of the RdnE effector both in vitro and in the heterologous expression model. The utilization of the bacterial two-hybrid system, along with the competition assays, to study the protective action of RdnI immunity is informative. Furthermore, the authors conducted bioinformatic analyses throughout the manuscript, examining the primary sequence, predicted structural, and metagenomic levels, which significantly underscore the significance and importance of the EI pair.

Weaknesses:

1. The interaction between RdnI and RdnE appears to be complex and requires further investigation. The manuscript's data does not conclusively explain how RdnI provides a "promiscuous" immunity function, particularly concerning the RdnI mutant/chimera derivatives. The lack of protection observed in these cases might be attributed to other factors, such as a decrease in protein expression levels or misfolding of the proteins. Additionally, the transient nature of the binding interaction could be insufficient to offer effective defenses.

2. The results from the mixed population competition lack quantitative analysis. The swarm competition assays only yield binary outcomes (Yes or No), limiting the ability to obtain more detailed insights from the data.

3. The discovery of cross-species protection is solely evident in the heterologous expression-competition model. It remains uncertain whether this is an isolated occurrence or a common characteristic of RdnI immunity proteins across various scenarios. Further investigations are necessary to determine the generality of this behavior.

Comments from Reviewing Editor:

• In addition to the references provided by Reviewer #2, the first manuscript to show non-cognate binding of immunity proteins was Russell et al 2012 (PMID: 22607806).

• IdrD was shown to form a subfamily of effectors in this manuscript by Hespanhol et al 2022 PMID: 36226828 that analyzed several T6SS effectors belonging to PDDExK, and it should be cited.

Reviewer #2 (Public Review):

Summary:

The manuscript by Knecht et al entitled "Non-cognate immunity proteins provide broader defenses against interbacterial effectors in microbial communities" aims at characterizing a new type VI secretion system (T6SS) effector immunity pair using genetic and biochemical studies primarily focused on Proteus mirabilis and metagenomic analysis of human-derived data focused on Rothia and Prevotella sequences. The authors provide evidence that RdnE and RdnI of Proteus constitute an E-I pair and that the effector likely degrades nucleic acids. Further, they provide evidence that expression of non-cognate immunity derived from diverse species can provide protection against RdnE intoxication. Overall, this general line of investigation is underdeveloped in the T6SS field and conceptually appropriate for a broad audience journal. The paper is well-written and, aside from a few cases, well-cited. As detailed below however, there are several aspects of this paper where the evidence provided is somewhat insufficient to support the claims. Further, there are now at least two examples in the literature of non-cognate immunity providing protection against intoxication, one of which is not cited here (Bosch et al PMID 37345922 - the other being Ting et al 2018). In general therefore I think that the motivating concept here in this paper of overturning the predominant model of interbacterial effector-immunity cognate interactions is oversold and should be dialed back.

Strengths:

One of the major strengths of this paper is the combination of diverse techniques including competition assays, biochemistry, and metagenomics surveys. The metagenomic analysis in particular has great potential for understanding T6SS biology in natural communities. Finally, it is clear that much new biology remains to be discovered in the realm of T6SS effectors and immunity.

Weaknesses:

The authors have not formally shown that RdnE is delivered by the T6SS. Is it the case that there are not available genetics tools for gene deletion for the BB2000 strain? If there are genetic tools available, standard assays to demonstrate T6SS-dependency would be to interrogate function via inactivation of the T6SS (e.g. by deleting tssC).

For swarm cross-phyla competition assays (Figure 4), at what level compared to cognate immunity are the non-cognate immunity proteins being expressed? This is unclear from the methods and Figure 4 legend and should be elaborated upon. Presumably these non-cognate immunity proteins are being overexpressed. Expression level and effector-to-immunity protein stoichiometry likely matters for interpretation of function, both in vitro as well as in relevant settings in nature. It is important to assess if native expression levels of non-cognate cross-phyla immunity (e.g. Rothia and Prevotella) protect similarly as the endogenously produced cognate immunity. This experiment could be performed in several ways, for example by deleting the RdnE-I pair and complementing back the Rothia or Prevotella RdnI at the same chromosomal locus, then performing the swarm assay. Alternatively, if there are inducible expression systems available for Proteus, examination of protection under varying levels of immunity induction could be an alternate way to address this question. Western blot analysis comparing cognate to non-cognate immunity protein levels expressed in Proteus could also be important. If the authors were interested in deriving physical binding constants between E and various cognate and non-cognate I (e.g. through isothermal titration calorimetry) that would be a strong set of data to support the claims made. The co-IP data presented in supplemental Figure 6 are nice but are from E. coli cells overexpressing each protein and do not fully address the question of in vivo (in Proteus) native expression.

Lines 321-324, the authors infer differences between E and I in terms of read recruitment (greater abundance of I) to indicate the presence of orphan immunity genes in metagenomic samples (Figure 5A-D). It seems equally or perhaps more likely that there is substantial sequence divergence in E compared to the reference sequence. In fact, metagenomes analyzed were required only to have "half of the bases on reference E-I sequence receiving coverage". Variation in coverage again could reflect divergent sequence dipping below 90% identity cutoff. I recommend performing metagenomic assemblies on these samples to assess and curate the E-I sequences present in each sample and then recalculating coverage based on the exact inferred sequences from each sample.

A description of gene-level read recruitment in the methods section relating to metagenomic analysis is lacking and should be provided.

Reviewer #1 (Public Review):

In this manuscript, Knecht, Sirias et al describe toxin-immunity pair from Proteus mirabilis. Their observations suggest that the immunity protein could protect against non-cognate effectors from the same family. They analyze these proteins by dissecting them into domains and constructing chimeras which leads them to the conclusion that the immunity can be promiscuous and that the binding of immunity is insufficient for protective activity.

Strengths:

The manuscript is well written and the data are very well presented and could be potentially interesting. The phylogenetic analysis is well done, and provides some general insights.

Weaknesses:

1) Conclusions are mostly supported by harsh deletions and double hybrid assays. The later assays might show binding, but this method is not resolutive enough to report the binding strength. Proteins could still bind, but the binding might be weaker, transient, and out-competed by the target binding.

2) While the authors have modeled the structure of toxin and immunity, the toxin-immunity complex model is missing. Such a model allows alternative, more realistic interpretation of the presented data. Firstly, the immunity protein is predicted to bind contributing to the surface all over the sequence, except the last two alpha helices (very high confidence model, iPTM>0.8). The N terminus described by the authors contributes one of the toxin-binding surfaces, but this is not the sole binding site. Most importantly, other parts of the immunity protein are predicted to interact closer to the active site (D-E-K residues). Thus, based on the AlphaFold model, the predicted mechanism of immunization remains physically blocking the active site. However, removing the N terminal part, which contributes large interaction surface will directly impact the binding strength. Hence, the toxin-immunity co-folding model suggests that proper binding of immunity, contributed by different parts of the protein, is required to stabilize the toxin-immunity complex and to achieve complete neutralization. Alternative mechanisms of neutralization might not be necessary in this case and are difficult to imagine for a DNAse.

3) Dissection of a toxin into two domains is also not justified from a structural point of view, it is probably based on initial sequence analyses. The N terminus (actually previously reported as Pone domain in ref 21) is actually not a separate domain, but an integral part of the protein that is encased from both sides by the C terminal part. These parts might indeed evolve faster since they are located further from the active site and the central core of the protein. I am happy to see that the chimeric toxins are active, but regarding the conservation and neutralization, I am not surprised, that the central core of the protein fold is highly conserved. However, "deletion 2" is quite irrelevant - it deletes the central core of the protein, which is simply too drastic to draw any conclusions from such a construct - it will not fold into anything similar to an original protein, if it will fold properly at all.

4) Regarding the "promiscuity" there is always a limit to how similar proteins are, hence when cross-neutralization is claimed authors should always provide sequence similarities. This similarity could also be further compared in terms of the predicted interaction surface between toxin and immunity.

Overall, it looks more like a regular toxin-immunity couple, where some cross-reactions with homologues will, of course, be possible, depending on how far the sequences have deviated. Nevertheless, taking all of the above into account, these results do not challenge toxin-immunity specificity dogma.

Joint Public Review

Introduction - Well written and placed within the current trends of unprecedented biodiversity loss, with emphasis in freshwater ecosystems. The authors identify three important points as to why biodiversity action plans have failed. Namely, community changes occur over large spatio-temporal scales and monitoring programs capture a fraction of these long-term dynamics (e.g. few decades) which although good at capturing trends in biodiversity change, they often fail at identifying the drivers of these changes. Additionally, most of these rely on manual sorting of samples, overlooking cryptic diversity, or state-of-the-art techniques such as sedimentary DNA (sedaDNA) which allow studying decade-long dynamics, usually focus on specific taxonomic groups unable to represent community-level changes. Secondly, the authors identify that biodiversity is threatened by multiple factors and are rarely studied in tandem. Finally, the authors stress the need for high-throughput approaches to study biodiversity changes since historically, most conservation efforts rely on highly specialized skills for biodiversity monitoring, and even well studied species have relatively short time series data. The authors identify a model freshwater lake (Lake Ring, Denmark) - suitable due to its well documented history over the last 100 years - to present a comprehensive framework using metabarcoding, chemical analysis and climatic records for identifying past and current impacts on this ecosystem arising from multiple abiotic environmental stressors.

Results - They are brief and should expand some more. Particularly, there are no results regarding metabarcoding data (number of reads, filtering etc.). These details are important to know the quality of the data which represents the bulk of the analyses. Even the supplementary material gives little information on the metabarcoding results (e.g. number of ASVs - whether every ASV of each family were pooled etc.). The drivers of biodiversity change section could be restructured and include main text tables showing the families positively or negatively correlated with the different variables (akin to table S2 but simplified).

Discussion<br /> The discussion is well written identifying first, some of the possible caveats of this study, particularly regarding classification of metabarcoding data, its biases and the possible DNA degradation of ancient sediment DNA. The authors discuss how their results fit to general trends showing how agricultural runoff and temperature drive changes in freshwater functional biodiversity primarily due to their synergistic effects on bioavailability, adsorption, etc. The authors highlight the advantage of using a system-level approach rather than focusing on taxa-specific studies due to their indicator status. Similarly, the authors justify the importance of studying community composition as far back as possible since it reveals unexpected patterns of ecosystem resilience. Lake Ring, despite its partially recovered status, has not returned to its semi-pristine levels of biodiversity and community assemblage. Additionally, including enzyme activity allows to assess functional diversity of the studied environment although reference databases of these pathways are still lacking. Finally, the authors discuss the implications of their findings under a conservation and land management framework suggesting that by combining these different approaches, drivers of biodiversity stressors can be derived with high accuracy allowing for better informed mitigation and conservation efforts.

Reviewer #1 (Public Review):

In the best genetically and biochemically understood model of eukaryotic DNA replication, the budding yeast, Saccharomyces cerevisiae, the genomic locations at which DNA replication initiates are determined by a specific sequence motif. These motifs, or ARS elements, are bound by the origin recognition complex (ORC). ORC is required for loading of the initially inactive MCM helicase during origin licensing in G1. In human cells, ORC does not have a specific sequence binding domain and origin specification is not specified by a defined motif. There have thus been great efforts over many years to try to understand the determinants of DNA replication initiation in human cells using a variety of approaches, which have gradually become more refined over time.

In this manuscript Tian et al. combine data from multiple previous studies using a range of techniques for identifying sites of replication initiation to identify conserved features of replication origins and to examine the relationship between origins and sites of ORC binding in the human genome. The authors identify a) conserved features of replication origins e.g. association with GC-rich sequences, open chromatin, promoters and CTCF binding sites. These associations have already been described in multiple earlier studies. They also examine the relationship of their determined origins and ORC binding sites and conclude that there is no relationship between sites of ORC binding and DNA replication initiation. While the conclusions concerning genomic features of origins are not novel, if true, a clear lack of colocalization of ORC and origins would be a striking finding. However, the majority of the datasets used do not report replication origins, but rather broad zones in which replication origins fire. Rather than refining the localisation of origins, the approach of combining diverse methods that monitor different objects related to DNA replication leads to a base dataset that is highly flawed and cannot support the conclusions that are drawn, as explained in more detail below.

Methods to determine sites at which DNA replication is initiated can be divided into two groups based on the genomic resolution at which they operate. Techniques such as bubble-seq, ok-seq can localise zones of replication initiation in the range ~50kb. Such zones may contain many replication origins. Conversely, techniques such as SNS-seq and ini-seq can localise replication origins down to less than 1kb. Indeed, the application of these different approaches has led to a degree of controversy in the field about whether human replication does indeed initiate at discrete sites (origins), or whether it initiates randomly in large zones with no recurrent sites being used. However, more recent work has shown that elements of both models are correct i.e. there are recurrent and efficient sites of replication initiation in the human genome, but these tend to be clustered and correspond to the demonstrated initiation zones (Guilbaud et al., 2022).

These different scales and methodologies are important when considering the approach of Tian et al. The premise that combining all available data from five techniques will increase accuracy and confidence in identifying the most important origins is flawed for two principal reasons. First, as noted above, of the different techniques combined in this manuscript, only SNS-seq can actually identify origins rather than initiation zones. It is the former that matters when comparing sites of ORC binding with replication origin sites if a conclusion is to be drawn that the two do not co-localise.

Second, the authors give equal weight to all datasets. Certainly, in the case of SNS-seq, this is not appropriate. The technique has evolved over the years and some earlier versions have significantly different technical designs that may impact the reliability and/or resolution of the results e.g. in Foulk et al. (Foulk et al., 2015), lambda exonuclease was added to single stranded DNA from a total genomic preparation rather than purified nascent strands), which may lead to significantly different digestion patterns (ie underdigestion). Curiously, the authors do not make the best use of the largest SNS-seq dataset (Akerman et al., 2020) by ignoring these authors separation of core and stochastic origins. By blending all data together any separation of signal and noise is lost. Further, I am surprised that the authors have chosen not to use data and analysis from a recent study that provides subsets of the most highly used and efficient origins in the human genome, at high resolution (Guilbaud et al., 2022).

References:

Akerman I, Kasaai B, Bazarova A, Sang PB, Peiffer I, Artufel M, Derelle R, Smith G, Rodriguez-Martinez M, Romano M, Kinet S, Tino P, Theillet C, Taylor N, Ballester B, Méchali M (2020) A predictable conserved DNA base composition signature defines human core DNA replication origins. Nat Commun, 11: 4826

Foulk MS, Urban JM, Casella C, Gerbi SA (2015) Characterizing and controlling intrinsic biases of lambda exonuclease in nascent strand sequencing reveals phasing between nucleosomes and G-quadruplex motifs around a subset of human replication origins. Genome Res, 25: 725-735

Guilbaud G, Murat P, Wilkes HS, Lerner LK, Sale JE, Krude T (2022) Determination of human DNA replication origin position and efficiency reveals principles of initiation zone organisation. Nucleic Acids Res, 50: 7436-7450

Reviewer #2 (Public Review):

Tian et al. perform a meta-analysis of 113 genome-wide origin profile datasets in humans to assess the reproducibility of experimental techniques and shared genomics features of origins. Techniques to map DNA replication sites have quickly evolved over the last decade, yet little is known about how these methods fare against each other (pros and cons), nor how consistent their maps are. The authors show that high-confidence origins recapitulate several known features of origins (e.g., correspondence with open chromatin, overlap with transcriptional promoters, CTCF binding sites). However, surprisingly, they find little overlap between ORC/MCM binding sites and origin locations.

Overall, this meta-analysis provides the field with a good assessment of the current state of experimental techniques and their reproducibility, but I am worried about: (a) whether we've learned any new biology from this analysis; (b) how binding sites and origin locations can be so mismatched, in light of numerous studies that suggest otherwise; and (c) some methodological details described below.

Major comments:

-- Line 26: "0.27% were reproducibly detected by four techniques" -- what does this mean? Does the fragment need to be detected by ALL FOUR techniques to be deemed reproducible? And what if the technique detected the fragment is only 1 of N experiments conducted; does that count as "detected"? Later in Methods, the authors (line 512) say, "shared origins ... occur in sufficient number of samples" but what does *sufficient* mean? Then on line 522, they use a threshold of "20" samples, which seems arbitrary to me. How are these parameters set, and how robust are the conclusions to these settings? An alternative to setting these (arbitrary) thresholds and discretizing the data is to analyze the data continuously; i.e., associate with each fragment a continuous confidence score.

-- Line 20: "50,000 origins" vs "7.5M 300bp chromosomal fragments" -- how do these two numbers relate? How many 300bp fragments would be expected given that there are ~50,000 origins? (i.e., how many fragments are there per origin, on average)? This is an important number to report because it gives some sense of how many of these fragments are likely nonsense/noise. The authors might consider eliminating those fragments significantly above the expected number, since their inclusion may muddle biological interpretation.

-- Line 143: I'm not terribly convinced by the PCA clustering analysis, since the variance explained by the first 2 PCs is only ~25%. A more robust analysis of whether origins cluster by cell type, year etc is to simply compute the distribution of pairwise correlations of origin profiles within the same group (cell type, year) vs the correlation distribution between groups. Relatedly, the authors should explain what an "origin profile" is (line 141). Is the matrix (to which PCA is applied) of size 7.5M x 113, with a "1" in the (i,j) position if the ith fragment was detected in the jth dataset?

-- It's not clear to me what new biology (genomic features) has been learned from this meta-analysis. All the major genomic features analyzed have already been found to be associated with origin sites. For example, the correspondence with TSS has been reported before:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6320713/<br /> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547456/

So what new biology has been discovered from this meta-analysis?

-- Line 250: The most surprising finding is that there is little overlap between ORC/MCM binding sites and origin locations. The authors speculate that the overlap between ORC1 and ORC2 could be low because they come from different cell types. Equally concerning is the lack of overlap with MCM. If true, these are potentially major discoveries that butts heads with numerous other studies that have suggested otherwise. More needs to be done to convince the reader that such a mis-match is true. Some ideas are below:

Idea 1) One explanation given is that the ORC1 and ORC2 data come from different cell types. But there must be a dataset where both are mapped in the same cell type. Can the authors check the overlap here? In Fig S4A, I would expect the circles to not only strongly overlap but to also be of roughly the same size, since both ORC's are required in the complex. So something seems off here.

Idea 2) Another explanation given is that origins fire stochastically. One way to quantify the role of stochasticity is to quantify the overlap of origin locations performed by the same lab, in the same year, in the same experiment, in the same cell type -- i.e., across replicates -- and then compute the overlap of mapped origins. This would quantify how much mis-match is truly due to stochasticity, and how much may be due to other factors.

Idea 3) A third explanation is that MCMs are loaded further from origin sites in human than in yeast. Is there any evidence of this? How far away does the evidence suggest, and what if this distance is used to define proximity?

Idea 4) How many individual datasets (i.e., those collected and published together) also demonstrate the feature that ORC/MCM binding locations do not correlate with origins? If there are few, then indeed, the integrative analysis performed here is consistent. But if there are many, then why would individual datasets reveal one thing, but integrative analysis reveal something else?

Idea 5) What if you were much more restrictive when defining "high-confidence" origins / binding sites. Does the overlap between origins and binding sites go up with increasing restriction?

Overall, I have the sense that these experimental techniques may be producing a lot of junk. If true, this would be useful for the field to know! But if not, and there are indeed "unexplored mechanisms of origin specification" that would be exciting. But I'm not convinced yet.

-- It would be nice in the Discussion for the authors to comment about the trade-offs of different techniques; what are their pros and cons, which should be used when, which should be avoided altogether, and why? This would be a valuable prescription for the field.

Reviewer #3 (Public Review):

Summary: The authors present a thought-provoking and comprehensive re-analysis of previously published human cell genomics data that seeks to understand the relationship between the sites where the Origin Recognition Complex (ORC) binds chromatin, where the replicative helicase (Mcm2-7) is situated on chromatin, and where DNA replication actually beings (origins). The view that these should coincide is influenced by studies in yeast where ORC binds site-specifically to dedicated nucleosome-free origins where Mcm2-7 can be loaded and remains stably positioned for subsequent replication initiation. However, this is most certainly not the case in metazoans where it has already been reported that chromatin bindings sites of ORC, Mcm2-7, and origins do not necessarily overlap, likely because ORC loads the helicase in transcriptionally active regions of the genome and, since Mcm2-7 retains linear mobility (i.e., it can slide), it is displaced from its original position by other chromatin-contextualized processes (for example, see Gros et al., 2015 Mol Cell, Powell et al., 2015 EMBO J, Miotto et al., 2016 PNAS, and Prioleau et al., 2016 G&D amongst others). This study reaches a very similar conclusion: in short, they find a high degree of discordance between ORC, Mcm2-7, and origin positions in human cells.

Strengths: The strength of this work is its comprehensive and unbiased analysis of all relevant genomics datasets. To my knowledge, this is the first attempt to integrate these observations and the analyses employed were suited for the questions under consideration.

Weaknesses: The major weakness of this paper is that this comprehensive view failed to move the field forward from what was already known. Further, a substantial body of relevant prior genomics literature on the subject was neither cited nor discussed. This omission is important given that this group reaches very similar conclusions as studies published a number of years ago. Further, their study seems to present a unique opportunity to evaluate and shape our confidence in the different genomics techniques compared in this study. This, however, was also not discussed.

Reviewer #1 (Public Review):

In this paper, Schalcher et al. examined how barn owls' landing force affects their hunting success during two hunting strategies: strike hunting and sit-and-wait hunting. They tracked tens of barn owls that raised their nestlings in nest boxes and utilized high-resolution GPS and acceleration loggers to monitor their movements. In addition, camcorders were placed near their nest boxes and used to record the prey they brought to the nest, thus measuring their foraging success.

This study generated a unique dataset and provided new insights into the foraging behavior of barn owls. The researchers discovered that the landing force during hunting strikes was significantly higher compared to the sit-and-wait strategy. Additionally, they found a positive relationship between landing force and foraging success during hunting strikes, whereas, during the sit-and-wait strategy, there was a negative relationship between the two. This suggests that barn owls avoid detection by generating a lower landing force and producing less noise. Furthermore, the researchers observed that environmental characteristics affect barn owls' landing force during sit-and-wait hunting. They found a greater landing force when landing on buildings, a lower landing force when landing on trees, and the lowest landing force when landing on poles. The landing force also decreased as the time to the next hunting attempt decreased. These findings collectively suggest that barn owls reduce their landing force as an acoustic camouflage to avoid detection by their prey.

The main strength of this work is the researchers' comprehensive approach, examining different aspects of foraging behavior, including high-resolution movement, foraging success, and the influence of the environment on this behavior, supported by impressive data collection. The weakness of this study is that the results only present a partial biological story contained within the data. The focus is on acoustic camouflage without addressing other aspects of barn owls' foraging strategy, leaving the reader with many unanswered questions. These include individual differences, direct measurements of owls' fitness, a detailed analysis of the foraging strategy of males and females, and the collective effort per nest box. However, it is possible that these data will be published in a separate paper.

The results presented support the authors' conclusion that lower landing force during sit-and-wait hunting increases hunting success, likely due to a decreased probability of detection by their prey, resulting in acoustic camouflage. The authors also argue that hunting success is crucial for survival, and thus, acoustic camouflage has a direct link to fitness. While this statement is reasonable, it should be presented as a hypothesis, as no direct evidence has been provided here. However, since information about nestling survival is typically monitored when studying behavior during the breeding period, the authors' knowledge of the effect of acoustic camouflage on owls' fitness can probably be provided. Furthermore, it will be interesting to further examine the foraging strategies used by different individuals during foraging, the joint foraging success of both males and females within each nest box, and the link between landing force and foraging success if the data are available. However, even without this additional analysis on survival, this paper provides an unprecedented dataset and the first measurement of landing force during hunting in the wild. It is likely to inspire many other researchers currently studying animal foraging behavior to explore how animals' movements affect foraging success.

Reviewer #2 (Public Review):

Summary:<br /> The authors provide new evidence for motion-induced sound camouflage and can link the hunting approach to hunting success (detailing the adaptation and inferring a fitness consequence).

Strengths:<br /> Strong evidence by combining high-resolution accelerometer data with a ground-truthed data set on prey provisioning at nest boxes. A good set of co-variates to control for some of the noise in the data provides some additional insights into owl hunting attempts.

Weaknesses:<br /> There is a disconnect between the hypotheses tested and the results presented, and insufficient detail is provided on the statistical approach. R2 values of the presented models are very small compared to the significance of the effect presented. Without more detail, it is impossible to assess the strength of the evidence. The authors seem to overcome persisting challenges associated with the validation and calibration of accelerometer data by ground-truthing on-board measures with direct observations in captivity, but here the methods are not described any further and sample sizes (2 owls - how many different loggers were deployed?) might be too small to achieve robust behavioural classifications.

Reviewer #1 (Public Review):

After revision, the manuscript is clearly improved and I thank the authors for their efforts. Yet, two contentious issues remain.

Firstly, I am skeptical whether the circularity issue has been resolved.

The authors equate uncertainty in the outcome of interactions with social complexity and they then diagnose for these three species that higher social complexity correlates with higher communicative complexity. Yet, there is still an inherent link between the occurrence of signals and other behaviours that allow the authors to determine the outcome of an interaction.

I do agree with the authors' conclusion that the three species vary in terms of the predictability of their signaling behaviour and the outcome of interactions. I just think the observed link between the two is not very surprising or informative, but rather inevitable.

Secondly, I am still not convinced that visual communication is more prevalent in situations with higher predation pressure. There are two reasons: relying on visual communication requires that the recipients, typically one's group members, are actually looking at the signaler when they produce the signal. The vocal-auditory channel in contrast, has a much higher potential to reach all recipients, even when visual communication in impaired. In addition, the idea that predators use acoustic signals to single out individuals and preferentially attack them, is poorly corroborated by data, especially for terrestrial predators. In contrast, there is ample evidence that prey species direct their calls at terrestrial predators (mobbing calls against snakes, antelope vigorously snorting against lions and leopards). See also this paper by Griesser (PMID 23941356).

Reviewer #2 (Public Review):

This is a well-written manuscript about a strong comparative study of diversity of facial movements in three macaque species to test arguments about social complexity influencing communicative complexity.

Reviewer #1 (Public Review):

There are a number of outstanding questions concerning how cohesin turnover on DNA is controlled by various accessory factors and how such turnover is controlled by post-translational modification. In this paper, Nasmyth et al. perform a series of AlphaFold structure predictions that aim to address several of these outstanding questions. Their structure predictions suggest that the release factor WAPL forms a ternary complex with PDS5 and SA/SCC3. This ternary complex appears to be able to bind the N-terminal end of SCC1, suggesting how formation of such a complex could stabilize an open state of the cohesin ring. Additional calculations suggest how the Eco/ESCO acetyltransferases and Sororin engage the SMC3 head domain presumably to protect against WAPL-mediated release.

This work thus demonstrates the power of AF prediction methods and how they can lead to a number of interesting and testable hypotheses that can transform our understanding of cohesin regulation. These findings require orthogonal experimental validation, but authors argue convincingly that such validation should not be a pre-requisite to publication.

In their revised version, the authors did not systematically include model confidence scores, and it therefore remains difficult for the reader to evaluate the reliability of the models obtained. The authors correctly point out that such metrics are available on Figshare. It is therefore possible to obtain such information. The caveat is that it remains to the user to identify and extract the relevant information. While they claim that they have labeled N- and C-termini in their figures, no such labeling can be seen in the revised version. Addition of such labels, at least for some of the figures, would help the user to navigate the models.

Also, PAE plots still contain chain labels (A,B,C etc.) and it is not always clear which protein is being referred to. Which segment does the reader need to focus on? The authors claim that PAE plots are now amended but no such changes can be seen. At least for the key models proposed, the authors should have facilitated access and help readers interpret the different plots/models. While it is possible to load the different PDB files from Figshare, the current version still requires that the reader then works out what segments are used and how they correspond to chain labels shown.

It is exciting to see AF-multimer predictions being applied to cohesin. As some of the reported interactions are not universally conserved and some involve relatively small interfaces the possibility arises that these interfaces show poor or borderline confidence scores. As some of these interfaces map to mutants that have previously been obtained by hypothesis-free genetic screens and mutational analyses, they appear nevertheless valid. Thus, an important point to make is that even interfaces that show modest confidence scores may turn out to be valid while others may be not.

Reviewer #2 (Public Review):

The ATPase protein machine cohesin shapes the genome by loop extrusion and holds sister chromatids together by topological entrapment. When executing these functions, cohesin is tightly regulated by multiple cofactors, such as Scc2/Nipbl, Pds5, Wapl, and Eco1/Esco1/2, and it undergoes dynamic conformational changes with ATP binding and hydrolysis. The mechanisms by which cohesin extrudes DNA loops and medicates siter-chromatid cohesion are still not understood. A major reason for the lack of understanding of cohesin dynamics and regulation is the failure to capture the structures of intact cohesin in different nucleotide-bound states and in complex with various regulators. So far only the ATP state cohesin bound to NIPBL and DNA have been experimentally determined.

In this manuscript, Nasmyth et al. made use of the powerful protein structure prediction tool, AlphaFold2 (AF), to predict the models of tens of cohesin subcomplexes from different species. The results provide important insight into how the Smc3-Scc1 DNA exiting gate is opened, how Pds5 and Wapl maintain the opened gate, how Pds5 and Scc3/SA recruit different cofactors, how Eco1 and Sororin antagonize Wapl, and how Scc2/Nipbl interacts with Scc3/SA. The models are for the most part consistent with published mutations in these proteins that affect cohesin's functions in vitro and in vivo and raise testable hypotheses of cohesin dynamics and regulation. This study also serves as an example of how to use AF to build models of protein complexes that involve the docking of flexible regions to globular domains.

Major points

(1)The revised manuscript is still too long and would be difficult for readers to read. While the authors have made some efforts to streamline their presentations and remove excessive speculations and models of minor importance, the changes are not enough.<br /> (2) AF has been accurate in predicting both the fold and sidechain conformations of globular domains. It is less accurate in predicting structural regions with conformational flexibility. Comparisons of predicted and determined structures of large protein complexes have shown considerable differences, particularly with respect to regions lacking tertiary fold. The authors should be more cautious in interpreting some of their models, particularly when the predicted models are inconsistent with determined structures and published biochemical data. For example, human WAPL-C in isolation does not interact with the SA-SCC1 complex while the N-terminal region of WAPL does.<br /> (3) The predicted SA/Scc3-Pds5-Scc1-WaplC quaternary complex is fascinating. Can the authors provide some experimental evidence to support the formation of this quaternary complex or at least the formation of the SA/Scc3-Pds5-WaplC ternary complex? In vitro pulldown or gel filtration can be used to test their predictions. The authors have decided not the test their models experimentally.

Reviewer #1 (Public Review):

Cell death plays a critical role on regulating organogenesis. During tooth morphogenesis, apoptosis of embryonic dental tissue plays critical roles on regulating tooth germ development. The current study focused on ferroptosis, another way of cell death which has rarely been investigated in tooth development, and showed it may also play an important role on regulating the tooth dimension. The topic is novel and interesting, but the experimental design has many flaws which significantly compromised the study.

1. The entire study was based on ex vivo tooth germ explant culture. Mandibular tooth germs of E15.5 (bell stage) were isolated for ex vivo culture. Most tooth germ explant culture experiments were actually using tooth germ of much earlier stages (E11.5-E13.5) for organ culture. After E16.5, both the large size and initially formed enamel/dentin could prevent nutrition from penetrating inside. Also, using tooth germ of earlier stage will help identify impact of ferroptosis upon early tooth development.<br /> 2. Due to limited penetration, the ex vivo culture in the study lasted for no more than 5 days. I would recommend the authors to perform kidney capsule transplantation as an alternative approach, which can support tooth germ development much longer even into root formation.<br /> 3. The major justification of using tooth germ ex vivo culture as the model in the study was to "conduct high-throughput analysis". However, the study could hardly be qualified as a high-throughput analysis. I would recommend the authors perform RNA sequencing for comparing tooth germs before/after erastin treatment. Such experiments won't take too much time or resource.<br /> 4. Although the study mostly used molars as the model, the in vivo iron concentration was only demonstrated on incisors, but not molars (Figure 1).<br /> 5. Phenotype analysis in Figure 2 is too superficial. Only dimensional information was provided. Cusps number, cusps distribution pattern and rooth/furcation formation were not evaluated. Differentiation of amelobast/odontoblast was not evaluated. The proliferation rate in the dental epithelium/mesenchyme was not analyzed.<br /> 6. Low magnification images should be included in Figure 3 to display the entire tooth germs.<br /> 7. In Figure 4, does ferroptotic inhibitor eliminate the iron accumulation in the tooth germ? How about the expression level of several target genes shown in Figure 3?<br /> 8. The manuscript has many typos and grammar mistakes. All "submandibular" should be simply "mandibular". "eastin" should be "erastin" (line 92). "partly" should be "partially" (line 611).

Reviewer #2 (Public Review):

The present study by Ye et al. characterizes some of the major effects of ferroptotic stress on tooth morphogenesis.

The strengths of this study are its innovative nature and beautiful histology. Mechanistic data are convincing Overall, the study is well done.

Reviewer #3 (Public Review):

This is an interesting work reporting ferroptosis that is involved in the tooth morphogenesis. The authors showed that Gpx4, the core anti-lipid peroxidation enzyme in ferroptosis, is upregulated in tooth development using ex vivo culture system.

Reviewer #1 (Public Review):

Comments on the original submission:

Trypanosoma brucei undergoes antigenic variation to evade the mammalian host's immune response. To achieve this, T. brucei regularly expresses different VSGs as its major surface antigen. VSG expression sites are exclusively subtelomeric, and VSG transcription by RNA polymerase I is strictly monoallelic. It has been shown that T. brucei RAP1, a telomeric protein, and the phosphoinositol pathway are essential for VSG monoallelic expression. In previous studies, Cestari et al. (ref. 24) has shown that PIP5pase interacts with RAP1 and that RAP1 binds PI(3,4,5)P3. RNAseq and ChIPseq analyses have been performed previously in PIP5pase conditional knockout cells, too (ref. 24). In the current study, Touray et al. did similar analyses except that catalytic dead PIP5pase mutant was used and the DNA and PI(3,4,5)P3 binding activities of RAP1 fragments were examined. Specifically, the authors examined the transcriptome profile and did RAP1 ChIPseq in PIP5pase catalytic dead mutant. The authors also expressed several C-terminal His6-tagged RAP1 recombinant proteins (full-length, aa1-300, aa301-560, and aa 561-855). These fragments' DNA binding activities were examined by EMSA analysis and their phosphoinositides binding activities were examined by affinity pulldown of biotin-conjugated phosphoinositides. As a result, the authors confirmed that VSG silencing (both BES-linked and MES-linked VSGs) depends on PIP5pase catalytic activity, but the overall knowledge improvement is incremental. The most convincing data come from the phosphoinositide binding assay as it clearly shows that N-terminus of RAP1 binds PI(3,4,5)P3 but not PI(4,5)P2, although this is only assayed in vitro, while the in vivo binding of full-length RAP1 to PI(3,4,5)P3 has been previously published by Cestari et al (ref. 24) already. Considering that many phosphoinositides exert their regulatory role by modulate the subcellular localization of their bound proteins, it is reasonable to hypothesize that binding to PI(3,4,5)P3 can remove RAP1 from the chromatin. However, no convincing data have been shown to support the author's hypothesis that this regulation is through an "allosteric switch".

Comments on revised manuscript:

In this revised manuscript, Touray et al. have responded to reviewers' comments with some revisions satisfactorily. However, the authors still haven't addressed some key scientific rigor issues, which are listed below:

1. It is critical to clearly state whether the observations are made for the endogenous WT protein or the tagged protein. It is good that the authors currently clearly indicate the results observed in vivo are for the RAP1-HA protein. However, this is not as clearly stated for in vitro EMSA analyses. In addition, in discussion, the authors simply assumed that the c-terminally tagged RAP1 behaves the same as WT RAP1 and all conclusions were made about WT RAP1.

There are two choices here. The authors can validate that RAP1-HA still retains RAP1's essential function as a sole allele in T. brucei cells (as was recommended previously). Indeed, HA-tagged RAP1 has been studied before, but it is the N-terminally HA-tagged RAP1 that has been shown to retain its essential functions. Adding the HA tag to the C-terminus of RAP1 may well cause certain defects to RAP1. For example, N-terminally HA-tagged TERT does not complement the telomere shortening phenotype in TERT null T. brucei cells, while C-terminally GFP-tagged TERT does, indicating that HA-TERT is not fully functional while TERT-GFP likely has its essential functions (Dreesen, RU thesis). Although RAP1-HA behaves similar to WT RAP1 in many ways, it is still not fully validated that this protein retains essential functions of RAP1. By the way, it has been published that cells lacking one allele of RAP1 behave as WT cells for cell growth and VSG silencing (Yang et al. 2009, Cell; Afrin et al. 2020, mSphere). In addition, although RAP1 may interact with TRF weakly, the interaction is direct, as shown in yeast 2-hybrid analysis in (Yang et al. 2009, Cell).

Alternatively, if the authors do not wish to validate the functionality of RAP1-HA, they need to add one paragraph at the beginning of the discussion to clearly state that RAP1-HA may not behave exactly as WT RAP1. This is important for readers to better interpret the results. In addition, the authors need to tune down the current conclusions dramatically, as all described observations are made on RAP1-HA but not the WT RAP1.

For a similar reason, the current EMSA results truly reflect how C-terminally His6-tagged RAP1 and RAP1 fragments behave. If the authors choose not to remove the His6 tag, it is essential that they use "RAP1-His6" to refer to these recombinant proteins. It is also essential for the authors to clearly state in the discussion that the tagged RAP1 fragments bind DNA, but the current data do not reveal whether WT RAP1 binds DNA. In addition, the authors incorrectly stated that "disruption of the MybL domain sequence did not eliminate RAP1-telomere binding in vivo" (lines 165-166). In ref 29, deletion of Myb domain did not abolish RAP1-telomere association. However, point mutations in MybL domain that abolish RAP1's DNA binding activities clearly disrupted RAP1's association with the telomere chromatin. Therefore, the current observation is not completely consistent with that published in ref 29.

2. There is no evidence, in vitro or in vivo, that binding PI(3,4,5)P3 to RAP1 causes conformational change in RAP1. The BRCT domain of RAP1 is known for its ability to homodimerize (Afrin et al. 2020, mSphere). It is therefore possible that binding of PI(3,4,5)P3 to RAP1 simply disrupts its homodimerization function. The authors clearly have extrapolated their conclusions based on available data. It is therefore important to revise the discussion and make appropriate statements.

Reviewer #2 (Public Review):

In this manuscript, Touray et al investigate the mechanisms by which PIP5Pase and RAP1 control VSG expression in T. brucei and demonstrate an important role for this enzyme in a signalling pathway that likely plays a role in antigenic variation in T. brucei. While these data do not definitively show a role for this pathway in antigenic variation, the data are critical for establishing this pathway as a potential way the parasite could control antigenic variation and thus represent a fundamental discovery.

The methods used in the study are generally well-controlled. The authors provide evidence that RAP1 binds to PI(3,4,5)P3 through its N-terminus and that this binding regulates RAP1 binding to VSG expression sites, which in turn regulates VSG silencing. Overall their results support the conclusions made in the manuscript. Readers should take into consideration that the epitope tags on RAP1 could alter its function, however.

There are a few small caveats that are worth noting. First, the analysis of VSG derepression and switching in Figure 1 relies on a genome which does not contain minichromosomal (MC) VSG sequences. This means that MC VSGs could theoretically be mis-assigned as coming from another genomic location in the absence of an MC reference. As the origin of the VSGs in these clones isn't a major point in the paper, I do not think this is a major concern, but I would not over-interpret the particular details of switching outcomes in these experiments.

Another aspect of this work that is perhaps important, but not discussed much by the authors, is the fact that signalling is extremely poorly understood in T. brucei. In Figure 1B, the RNA-seq data show many genes upregulated after expression of the Mut PIP5Pase (not just VSGs). The authors rightly avoid claiming that this pathway is exclusive to VSGs, but I wonder if these data could provide insight into the other biological processes that might be controlled by this signaling pathway in T. brucei.

Overall, this is an excellent study which represents an important step forward in understanding how antigenic variation is controlled in T. brucei. The possibility that this process could be controlled via a signalling pathway has been speculated for a long time, and this study provides the first mechanistic evidence for that possibility.

Reviewer #3 (Public Review):

Summary: In this study, Peterson et al. longitudinally record and document the vocal repertoires of three Mongolian gerbil families. Using unsupervised learning techniques, they map the variability across these groups, finding that while overall statistics of, e.g., vocal emission rates and bout lengths are similar, families differed markedly in their distributions of syllable types and the transitions between these types within bouts. In addition, the large and rich data are likely to be valuable to others in the field.

Strengths:<br /> - Extensive data collection across multiple days in multiple family groups.<br /> - Thoughtful application of modern analysis techniques for analyzing vocal repertoires.<br /> - Careful examination of the statistical structure of vocal behavior, with indications that these gerbils, like naked mole rats, may differ in repertoire across families.

Weaknesses:<br /> - The work is largely descriptive, documenting behavior rather than testing a specific hypothesis.<br /> - The number of families (N=3) is somewhat limited.

Reviewer #1 (Public Review):

Summary:<br /> This research offers an in-depth exploration and quantification of social vocalization within three families of Mongolian gerbils. In an enlarged, semi-natural environment, the study continuously monitored two parent gerbils and their four pups from P14 to P34. Through dimensionality reduction and clustering, a diverse range of gerbil call types was identified. Interestingly, distinct sets of vocalizations were used by different families in their daily interactions, with unique transition structures exhibited across these families. The primary results of this study are compelling, although some elements could benefit from clarification

Strengths:<br /> Three elements of this study warrant emphasis. Firstly, it bridges the gap between laboratory and natural environments. This approach offers the opportunity to examine natural social behavior within a controlled setting (such as specified family composition, diet, and life stages), maintaining the social relevance of the behavior. Secondly, it seeks to understand short-timescale behaviors, like vocalizations, within the broader context of daily and life-stage timescales. Lastly, the use of unsupervised learning precludes the injection of human bias, such as pre-defined call categories, allowing the discovery of the diversity of vocal outputs.

Weaknesses:<br /> 1. While the notable differences in vocal clusters across families are convincing, the drivers of these differences remain unclear. Are they attributable to "dialect," call usage, or specific vocalizing individuals (e.g., adults vs. pups)? Further investigation, via a literature review or additional observation, into acoustic differences between adult and pup calls is recommended. Moreover, a consistent post-weaning decrease in the bottom-left cluster (Fig. S3) invites interpretation: could this reflect drops in pup vocalization?

2. Developmental progression, particularly during pre-weaning periods when pup vocal output remains unstable, might be another factor influencing cross-family vocal differences. Representing data from this non-stationary process as an overall density map could result in the loss of time-dependent information. For instance, were dominating call types consistently present throughout the recording period, or were they prominent only at specific times? Displaying the evolution of the density map would enhance understanding of this aspect.

3. Family-specific vocalizations were credited to the transition structure, a finding that may seem obvious if the 1-gram (i.e., the proportion of call types) already differs. This result lacks depth unless it can be demonstrated that, firstly, the transition matrix provides a robust description of the data, and secondly, different families arrange the same set of syllables into unique sequences.

Reviewer #2 (Public Review):

Peterson et al., perform a series of behavioral experiments to study the repertoire and variance of Mongolian gerbil vocalizations across social groups (families). A key strength of the study is the use of a behavioral paradigm which allows for long term audio recordings under naturalistic conditions. This experimental set-up results in the identification of additional vocalization types. In combination with state of the art methods for vocalization analysis, the authors demonstrate that the distribution of sound types and the transitions between these sound types across three gerbil families is different. This is a highly compelling finding which suggests that individual families may develop distinct vocal repertoires. One potential limitation of the study lies in the cluster analysis used for identifying distinct vocalization types. The authors use a Gaussian Mixed Model (GMM) trained on variational auto Encoder derived latent representation of vocalizations to classify recorded sounds into clusters. Through the analysis the authors identify 70 distinct clusters and demonstrate a differential usage of these sound clusters across families. While the authors acknowledge the inherent challenges in cluster analysis and provide additional analyses (i.e. maximum mean discrepancy, MMD), additional analysis would increase the strength of the conclusions. In particular, analysis with different cluster sizes would be valuable. An additional limitation of the study is that due to the methodology that is used, the authors can not provide any information about the bioacoustic features that contribute to differences in sound types across families which limits interpretations about how the animals may perceive and react to these sounds in an ethologically relevant manner.

The conclusions of this paper are well supported by data, but certain parts of the data analysis should be expanded and more fully explained.

• Can the authors comment on the potential biological significance of the 70 sound clusters? Does each cluster represent a single sound type? How many vocal clusters can be attributed to a single individual? Similarly, can the authors comment on the intra-individual and inter-individual variability of the sound types within and across families?<br /> • As a main conclusion of the paper rests on the different distribution of sound clusters across families, it is important to validate the robustness of these differences across different cluster parameters. Specifically, the authors state that "we selected 70 clusters as the most parsimonious fit". Could the authors provide more details about how this was fit? Specifically, could the authors expand upon what is meant by "prior domain knowledge about the number of vocal types...". If the authors chose a range of cluster values (i.e. 10, 30, 50, 90) does the significance of the results still hold?<br /> • While VAEs are powerful tools for analyzing complex datasets in this case they are restricted to analysis of spectrogram images. Have the authors identified any acoustic differences (i.e. in pitch, frequency, and other sound components) across families?

Reviewer #1 (Public Review):

This paper describes the role of WRNIP1 AAA+ ATPase, particularly its UBZ domain for ubiquitin-binding, but not ATPase, to prevent the formation of the R-loop when DNA replication is mildly perturbated. By combining cytological analysis for DNA damage, R-loop, and chromosome aberration with the proximity ligation assay for colocalization of various proteins involved in DNA replication and transcription, the authors provide solid evidence to support the claim. The authors also revealed a distinct role of WRNIP1 in the prevention of R-loop-induced DNA damage from FANCD2, which is inconsistent with the known relationship between WRNIP1 and FANCD2 in the repair of crosslinks.

Reviewer #2 (Public Review):

This paper aims at establishing the role of WRN-interacting protein 1 (WRNIP1) and its UBZ domain (an N-terminal ubiquitin-binding zinc finger domain) on genome instability caused by mild inhibition of DNA synthesis by aphidicolin. The authors used human MRC5 fibroblasts investigated with standard methods in the field. The results clearly showed that WRNIP1 silencing and UBZ-mutation (D37A) increased DNA damage, chromosome aberrations, and transcription-replication conflicts caused by aphidicolin.

The conclusions of the paper are overall well supported by results, however, aspects of some data analyses would need to be clarified and/or extended.

1 The methods (immunofluorescence microscopy and dot-blots) to determine R-loop levels can lack sensitivity and specificity. In particular, since the S9.6 antibody can bind to other structures besides heteroduplex, dot-blot analyses only grossly assess R-loop levels in cellular samples of purified nucleic acids, which are constituted by many different types of DNA/RNA structures.

2 Experimental plan has analyzed the impact of WRNIP1 lack or mutations at steady-state conditions. Thus, the possible role of WRNIP1 at an early step of the mechanism would require some sort of kinetics analysis of the molecular process, therefore not at steady-state conditions. The findings of a co-localization of R-loops and WRNIP1 have been obtained with the S9.6 antibody, which recognizes DNA-RNA heteroduplexes. Since WRNIP1 is known to be recruited at stalled forks and DNA cleavage sites, it is not surprising that WRNIP1 is very close to heteroduplexes, abundant structures at replication forks and cleavage sites. Similar interpretations may also be valid for Rad51/S9.6 co-localization findings.

3 Determination of DNA damage, chromosome aberration, and co-localization data are reported as means of measurements with appropriate statistics. However, the fold-change values relative to corresponding untreated samples are not reported. In some instances, it seems that WRNIP1 silencing or mutations actually reduce or do not affect aphidicolin effects. That leaves open the interpretation of specific results.

Reviewer #3 (Public Review):

Summary:<br /> In the manuscript by Valenzisi et al., the authors report on the role of WRNIP1 to prevent R-loop and TRC-associated DNA damage. The authors claim WRNIP1 localizes to TRCs in response to replication stress and prevents R-loop accumulation, TRC formation, replication fork stalling, and subsequent DNA damage. While the findings are of potential significance to the field, the strength of evidence in support of the conclusions is lacking.

Weaknesses:<br /> 1) The authors fail to utilize the proper controls throughout the manuscript in regard to the shWRNIP1, WT, and mutant cell lines. It is unclear why the authors failed to use the shWRNIP1WT line in the comet assay, DNA fiber assay, and the FANCD2 assays. This is a key control for i) the use of only a single shRNA (most studies will use at least 2 different shRNAs) and ii) the use of the mutant WRNIP1 lines. In several figures, the authors only show the effect of the UBZ mutant, but don't include the ATPase mutant or WT for comparison. Including these is essential.

2) The authors use the S9.6 antibody to conclude the loss of WRNIP1 causes more R-loops; however, it has been shown that this antibody detects dsRNA in addition to RNA-DNA hybrids. Accordingly, it cannot be ruled out that the increased S9.6 signal is due to increased dsRNA.

3) Multiple pieces of data do not support the conclusions. For example, Figure 1D shows shWRNIP1 to reduce damage in Aph+DRB cells compared to MRC5SV cells with Aph+DRB. This result suggests that WRNIP1 actually increases DNA damage in stressed cells with transcription blocked. Another result is seen in Figure 4a, where the number of PLA spots (presumably TRCs) increases in the shWRNIP1WT cells with Aph+RNH1 compared to Aph alone. If R-loops are required for TRC accumulation, then the RNH1 should decrease the PLA foci. This result instead suggests that WRNIP leads to increased TRCs in stressed cells with R-loops cleared by RNH1.

4) The data are mostly phenomenological and fail to yield mechanistic insight. For example, the authors state that "it remains unclear whether WRNIP1 is directly involved in the mechanisms of R-loop removal/resolution". Unfortunately, the data presented in this manuscript do not provide new insights into this unresolved question.

5) The authors only show merged images making it impossible to visualize differences in PLA foci.

Reviewer #3 (Public Review):

In this study, Zhu and authors investigate the expression and function of the clustered Protocadherins (cPcdhs) in synaptic connectivity in the mouse cortex. The cPcdhs encode a large family of cadherin-related transmembrane molecules hypothesized to regulate synaptic specificity through combinatorial expression and homophilic binding between neurons expressing matching cPcdh isoforms. But the evidence for combinatorial expression has been limited to a few cell types, and causal functions between cPcdh diversity and wiring specificity have been difficult to test experimentally. This study addresses two important but technically challenging questions in the mouse cortex: 1) Do single neurons in the cortex express different cPcdh isoform combinations? and 2) Does Pcdh isoform diversity or particular combinations among pyramidal neurons influence their connectivity patterns? Focusing on the Pcdh-gamma subcluster of 22 isoforms, the group performed 5'end-directed single-cell RNA sequencing from dissociated postnatal (P11) cortex. To address the functional role of Pcdhg diversity in cortical connectivity, they asked whether the Pcdhgs and isoform matching influence the likelihood of synaptic pairing between 2 nearby pyramidal neurons. They performed simultaneous whole-cell recordings of 6 pyramidal neurons in cortical slices, and measured paired connections by evoked monosynaptic responses. In these experiments, they measured synaptic connectivity between pyramidal neurons lacking the Pcdhgs, or overexpressing dissimilar or matching sets of Pcdhg isoforms introduced by electroporation of plasmids encoding Pcdhg cDNAs.

Overall, the study applies elegant methods that demonstrate that single cortical neurons express different combinations of Pcdh-gamma isoforms, including the upper layer Pyramidal cells that are assayed in paired recordings. The electrophysiology data demonstrate that nearby Pyramidal neurons lacking the entire Pcdhg cluster are more likely to be synaptically connected compared to the control neurons, and that overexpression of matching isoforms between pairs decreases the likelihood to be synaptically connected. These are important and compelling findings that advance the idea that the Pcdhgs are important for cortical synaptic connectivity, and that the repertoire of isoforms expressed by neurons influence their connectivity patterns potentially through a self/non-self discrimination mechanism. However, the findings are limited to probability in connectivity and do they do not support the authors' conclusions that Pcdhg isoforms regulate synaptic specificity, 'by preventing synapse formation with specific cells' or to 'unwanted partners'. Characterizations of the cellular basis of these defects are needed to determine whether they are secondary to other roles in cell positioning, axon/dendrite branching and synaptic pruning, and overall synaptic formation. Claims that Pcdh-alpha and Pcdhg C-type isoforms are not functionally required are premature, due to limitations of the experiments. Moreover, claims that 'similarity level of γ-PCDH isoforms between neurons regulate the synaptic formation' are not supported due to weak statistical analyses presented in Fig4. The overstatements should be corrected. There was also missed opportunity to clearly discuss these results in the context of other published work, including recent publications focused on the cortex.

Strengths:

- The 5' end sequencing with a Pcdhg-amplified library is a technical feat and addresses the pitfall of conventional scRNA-Seq methods due to the identical 3'sequences shared by all Pcdhg isoform and the low abundance of the variable exons. New figures with annotated cell types confirm that several pyramidal and inhibitory cortical subpopulations were captured.

-Statistical assessment of co-occurrence of isoform expression within clusters is also a strength.

- By establishing the combinatorial expression of Pcdhgs by maturing pyramidal cells, the study further substantiates the 'single neuron combinatorial code for cPcdhs' model. Although combinatorial expression is not universal (ie. serotonergic neurons), there was limited evidence. The findings that individual pyramidal neurons express ~1-3 variable Pcdhg transcripts plus the C-type transcripts aligns with single RT-PCR studies of single Purkinje cells (Esumi et al 2005; Toyoda et al 2014). They differ from the findings by Lv et al 2022, where C-type expression was lower among pyramidal neurons. OSNs also do not substantially express C-type isoforms (Mountoufaris et al 2017; Kiefer et al 2023). Differences, and the advantages of the 5'end -directed sequencing (vs. SmartSeq) could be raised in the discussion.

- Simultaneous whole-cell recordings and pairwise comparisons of pyramidal neurons is a technically outstanding approach. They assess the effects of Pcdhg OE isoform on the probability of paired connections.

- The connectivity assay between nearby pairs proved to be sensitive to quantify differences in probability in Pcdhg-cKO and overexpression mutants. The comparisons of connectivity across vertical vs lateral arrangement are also strengths. Overexpressing identical Pcdhg isoform (whether 1 or 6) reduces the probability of connectivity, but there are caveats to the interpretations (see below).

Weaknesses:

-The experiments support a role for the Pcdhgs in influencing the probability of synaptic connectivity between nearby pairs but are not sufficient evidence for synapse specificity. The cPcdhs play multiple roles in neurite arborization, synaptic density, and cell positioning. Kostadinov 2015 also showed that starburst cells lacking the Pcdhgs maintained increased % connectivity at maturity, suggesting a lack of refinement in the absence of Pcdhgs. The known roles raise questions on how these manipulations might have primary effects in these processes and then subsequently impact the probability of connectivity. Investigations of morphological aspects of pyramidal development would strengthen the study and potentially refine the findings. The authors should more clearly relate their findings to the body of cPcdh studies in the discussion.

- Pcdhg cKO-dependent effects on connectivity occur between closely spaced soma (50-100um - Figure 2E), highlighting the importance of spatial arrangement to connectivity (also noted by Tarusawa 2016). Was distance considered for the overexpression (OE) assays, and did the authors note changes in cell distribution which might diminish the connectivity? Recent work by Lv et al 2022 reported that manipulating Pcdhgs influences the dispersion of clonally-related pyramidal neurons, which also impacts the likelihood of connections. Overexpression of Pcdhgc3 increased cell dispersion and decreased the rate of connectivity between pairs. Though these papers are mentioned, they should be discussed in more detail and related to this work.

- Though the authors added suggested citations and improved the contextualization of the study, several statements do not accurately represent the cited literature. It is at the expense of crystalizing the novelty and importance of this present work. For instance, Garrett et al 2012 PMID: 22542181 was the first to describe roles for Pcdhgs in cortical pyramidal cells and dendrite arborization, and that pyramidal cell migration and survival are intact. Line 52 cited Wang et al 2002, but this was limited to gross inspection. Garrett et al is the correct citation for: 'The absence of γ-PCDH does not cause general abnormality in the development of the cerebral cortex, such as cell differentiation, migration, and survival (Wang et al., 2002).' Second, single cell cPcdh diversity is introduced very generally, as though all neuron types are expected to show combinatorial variable expression with ubiquitous C-Type expression. But those initial studies were limited to Purkinje cells (Esumi 2005 and Toyoda 2014). Profiling of serotonergic neurons and OSN reveals different patterns (citations needed for Chen 2017 PMID: 28450636; Mountofaris et al PMID: 2845063; Canzio 2023 PMID: 37347873), raising the idea that cPcdh diversity and ubiquitous C-type expression is not universal. Thus, the authors missed the opportunity to emphasize the gap regarding cPcdh diversity in the cortex.

- They have not shown rigorously and statistically that the rate of connectivity changes with% isoform matching. In Figure 4D, comparisons of % isoform matching in OE assays show a single statistical comparison between the control and 100% groups, but not between the 0%, 11% and 33% groups. Is there a significant difference between the other groups? Significant differences are claimed in the results section, but statistical tests are not provided. The regression analysis in 4E suggests a correlation between % isoform similarity and connectivity probability, but this is not sound as it is based on a mere 4 data points from 4D. The authors previously explained that they cannot evaluate the variance in these recordings as they must pool data together. However, there should be some treatment of variability, especially given the low baseline rate of connectivity. Or at the very least, they should acknowledge the limitations that prevent them from assessing this relationship. Claims in lines 230+ are not supported: ' Overall, our findings demonstrate a negative correlation between the probability of forming synaptic connections and the similarity level of γ-PCDH isoforms expressed in neuron pairs (Fig. 4E)".

-Figure 4 provides connectivity probability, but this result might be affected by overall synapse density. Did connection probability change with directionality (e.g between red to green cells, or green to red cells).

-Generally, the statistical approaches were not sufficiently described in the methods nor in the figure legends, making it difficult to assess the findings. They do not report on how they calculated FDR for connectivity data, when this is typically used for larger multivariate datasets.

- The possibility that the OE effects are driven by total Pcdhg levels, rather isoform matching, should be examined. As shown by qRT-PCR in Fig. 3, expression of individual isoforms can vary. It is reasonable that protein levels cannot be measured by IHC, although epitope tags could be considered as C-terminal tagging of cPcdhs preserves the function in mice (see Lefebvre 2008). Quantification of constant Pcdhg RNA levels by qRT-PCR or sc-RT-PCR would directly address the potential caveat that OE levels vary with isoform combinations.

-A caveat for the relative plasmid expression quantifications in Figure 3-S1 is that IHC was used to amplify the RFP-tagged isoform, and thus does not likely preserve the relationship between quantities and detection.

-Figure 1 didn't change in response to reviews to improve clarity. New panels relating to the scRNA-Seq analyses were added to supplementary data but many are central and should be included in Figure 1 (ie. S1-Fig6D). In the Results, the authors state that neuronal subpopulations generally show a combinatorial expression of some variable RNA isoforms and near ubiquitous C-type expression. But they only show data for the Layer 2/3 neuron-specific cluster in S1-Fig-6D, and so it is not clear if this pattern applies to other clusters. Fig. S1-5 show a low number of expressed isoforms per cell, but specific descriptions on whether these include C-type isoforms would be helpful. Figure 1F showing isoform profile in all neurons is not particularly meaningful. There is a lot of interest in neuron-type specific differences in cPcdh diversity, and the authors could highlight their data from S1-5 accordingly.

-The concept of co-occurrence and results should be explained within the results section, to more clearly relate this concept to data and interpretations. Explanations are now found in the methods, but this did not improve the clarity of this otherwise very interesting aspect of the study.

- The claim that C-type Pcdhgs do not functionally influence connectivity is premature. Tests were limited to PcdhgC4, which has unique properties compared to the other 2 C-type isoforms (Garrett et al 2019 PMID: 31877124; Mancia et al PMID: 36778455). The text should be corrected to limit the conclusion to PcdhgC4, and not generally to C-type. The authors should test PcdhgC3 and PcdhgC5 isoforms.

-The group generated a novel conditional Pcdh-alpha mouse allele using CRISPR methods, and state that there were no changes in synaptic connectivity in these Pcdh-alpha mutants. But this claim is premature. The Southern blots validate the targeting of the allele. But further validations are required to establish that this floxed allele can be efficiently recombined, disrupting Pcdha protein levels and function. Pcdha alleles have been validated by western blots and by demonstration of the prominent serotonergic axonal phenotype of Pcdha-KO (ie. Chen 2017 PMID: 28450636; Ing-Esteves 2018 PMID: 29439167).

-The Discussion would be strengthened by a deeper discussion of the findings to other cPcdh roles and studies, and of the limitations of the study. The idea that the Pcdhgs are influencing the rate of connectivity through a repulsion mechanism or synaptic formation (ie through negative interactions with synaptic organizers such as Nlgn - Molumby 2018, Steffen 2022) could be presented in a model, and supported by other literature.

Reviewer #1 (Public Review):

The manuscript by Zhu and colleagues aimed to clarify the importance of isoform diversity of PCDHg in establishing cortical synapse specificity. The authors optimized 5' single-cell sequencing to detect cPCDHg isoforms and showed that the pyramidal cells express distinct combinations of PCDHg isoforms. Then, the authors conducted patch-clamp recordings from cortical neurons whose PCDHg diversity was disrupted. In the elegant experiment in Figure 3, the authors demonstrated that the neurons expressing the same sets of cPCDHg isoforms are less likely to form synapses with each other, suggesting that identical cPCDHg isoforms may have a repulsive effect on synapse formation. Importantly, this phenomenon was dependent on the similarity of the isoforms present in neurons but not on the amount of proteins expressed.

One of the major concerns in an earlier version was whether PCDHg isoforms, which are expressed at a much lower level than C-type isoforms, have true physiological significance. The authors conducted additional experiments to address this point by using PCDHg cKO and provided convincing data supporting their conclusion. The results from PCDHg C4 overexpression, showing no impact on synaptic connectivity, further clarified the importance of isoforms. I have no further concerns, however, I would like to point out that the evidence for the necessity of the PCDHg isoform is still lacking because most experiments were done by overexpression. It would be helpful for the readers if the authors could add this point to the discussion.

Reviewer #2 (Public Review):

This short manuscript by Zhu et al. describes an investigation into the role of gamma protocadherins in synaptic connectivity in the mouse cerebral cortex. First, the authors conduct a single-cell RNA-seq survey of postnatal day 11 mouse cortical neurons, using an adapted 10X Genomics method to capture the 5' sequences that are necessary to identify individual gamma protocadherin isoforms (all 22 transcripts share the same three 3' "constant" exons, so standard 3'-biased methods can't distinguish them). This method adaptation is an advance for examining individual gamma transcripts, and it is helpful to publish the method, the characterization of which is improved in this revised manuscript. The results largely confirm what was known from other approaches, which is that a few of the 19 A and B subtype gamma protocadherins are expressed in an apparently stochastic and combinatorial fashion in each cortical neuron, while the 3 C subtype genes are expressed ubiquitously. Second, using elegant paired electrophysiological recordings, the authors show that in gamma protocadherin cortical slices, the likelihood of two neurons on layers 2/3 being synaptically connected is increased. That suggests that gamma protocadherins generally inhibit synaptic connectivity in the cortex; again, this has been reported previously using morphological assays, but it is important to see it confirmed here with physiology. Finally, the authors use an impressive sequential in utero electroporation method to provide evidence that the degree of isoform matching between two neurons negatively regulates their reciprocal synaptic connectivity. These are difficult experiments to do, and while some caveats remain, the main result is consistent. Strengths include the impressive methodology and improved demonstration of the previously-reported finding that gamma protocadherins work via homophilic matching to put a brake on synapse formation in the cortex. Weaknesses include the writing, which even in the revision fails to completely put the new results in context with prior work, which together has largely shown similar results; a still-incomplete characterization of a new alpha protocadherin KO mouse (a minor point but it should still be addressed); and a lack of demonstration of protein levels in electroporated brains. Because of the unique organization and expression pattern of the gamma protocadherins, it is unlikely that these results will be directly applicable to the broader understanding of the role of cell adhesion molecules in synapse development. However, the methodology, which is now better described, should be applicable more broadly and the improved demonstration of the role of gamma protocadherin's negative role in cortical synaptogenesis is helpful.

Reviewer #2 (Public Review):

Summary:

Spikol et al performed a technical tour de force by combining numerous novel tools and approaches to investigate for the first time the connectivity and motor functions of nucleus incertus subset of neurons genetically defined by the expression of specific markers in the larval zebrafish brain.

Strengths:

By using expression of the specific markers relaxin 3 and gsc2, the authors generated novel knock-in transgenic lines enabling them to investigate the connectivity, recruitment and roles of these neurons in locomotion. Their work should enable numerous subsequent studies in zebrafish & inspire new paths of investigations in other animal models.

Weaknesses:

More precision is required for the anatomical data and further analysis is needed to describe the recruitment and role in spontaneous exploration of the rln3- and gsc2- expressing neurons.

Reviewer #3 (Public Review):

This study uses a range of methods to characterize heterogeneous neural populations within the nucleus incertus (NI). The authors focus on two major populations, expressing gsc2 and rln3a, and present solid evidence that these cells have different patterns of efferent and afferent connectivity, calcium activity and function in control of behavior. Although the study does not go as far as clarifying the role of NI in any specific neural computation or aspect of behavioral control, the findings will be valuable in support of future endeavors to do so. In particular, the authors have made two beautiful knock-in lines that recapitulate endogenous expression pattern of gsc2 and rln3a which will be a powerful tool to study the roles of the relevant NI cells. Experiments are well done and data are high quality and most claims are well supported. However, there are a few issues, detailed below, where I believe additional analysis could strengthen the paper.

• The data very clearly show different patterns of neurites for gsc2 and rln3a neurons in the IPN and the authors interpret these are being axonal arbors. However, can they rule out that some arbors might be dendritic in nature? Notably, they cite the recent Portugues lab study that confirmed that, as in other species, tegmental neurons in zebrafish extend spatially segregated axonal and dendritic arbors into IPN, and the authors speculate that these GABAergic cells might in fact be part of NI.

Reviewer #1 (Public Review):

Spikol et al. investigate the roles of two distinct populations of neurons in the nucleus incertus (NI). The authors established two new transgenic lines that label gsc2- and rln3a-expressing neurons. They show that the gsc2+ and rln3a+ NI neurons show divergent projection patterns and project to different parts of the interpeduncular nucleus (IPN), which receive inputs from habenula (Hb). Furthermore, calcium imaging shows that gsc2 neurons are activated by the optogenetic activation of the dorsal Hb-IPN and respond to aversive electric shock stimuli, while rln3a neurons are highly spontaneously active. The ablation of rln3a neurons, but not gsc2 neurons, alters locomotor activity of zebrafish larvae.

The strength of the paper is their genetic approach that enabled the authors to characterize many different features of the two genetically targeted populations in the NI. These two neuronal populations are anatomically closely apposed and would have been indistinguishable without their genetic tools. Their analyses provide valuable information on the diverse anatomical, physiological and behavioral functions of the different NI subtypes. On the other hand, these pieces of evidence are only loosely linked with each other to reach a mechanistic understanding of how the NI works in a circuit. For example, the anatomical study revealed the connections from the NI to the IPN, while the optogenetic mapping experiments investigate the other way around, i.e. the connection from the IPN to the NI.

Reviewer #1 (Public Review):

In this manuscript, Davidsen and coworkers describe the development of a novel aspartate biosensor jAspSNFR3. This collaborative work supports and complements what was reported in a recent preprint by Hellweg et al., (bioRxiv; doi: 10.1101/2023.05.04.537313). In both studies, the newly engineered aspartate sensor was developed from the same glutamate biosensor previously developed by the authors of this manuscript. This coincidence is not casual but is the result of the need to find tools capable of measuring aspartate levels in vivo. Therefore, it is undoubtedly a relevant and timely work carried out by groups experienced in aspartate metabolism and in the generation of metabolite biosensors.

Reviewer #2 (Public Review):

In this work the IGluSnFR3 sensor, recently developed by Marvin et al (2023) is mutated position S72, which was previously reported to switch the specificity from Glu to Asp. They made 3 mutations at this position, selected a S72P mutant, then made a second mutation at S27 to generate an Asp-specific version of the sensor. This was then characterized thoroughly and used on some test experiments, where it was shown to detect and allow visualization of aspartate concentration changes over time. It is an incremental advance on the iGluSnFR3 study, where 2 predictable mutations are used to generate a sensor that works on a close analog of Glu, Asp. It is shown to have utility and will be useful in the field of Asp-mediated biological effects.

Reviewer #3 (Public Review):

In this manuscript, Davidsen and collaborators introduce jAspSnFR3, a new version of aspartate biosensor derived from iGluSnFR3, that allows monitoring in real-time aspartate levels in cultured cells. A selective amino acids substitution was applied in a key region of the template to switch its specificity from glutamate to aspartate. The jAspSnFR3 does not respond to other tested metabolites and performs well, is not toxic for cultured cells, and is not affected by temperature ensuring the possibility of using this tool in tissues physiologically more relevant. The high affinity for aspartate (KD=50 uM) allowed the authors to measure fluctuations of this amino acid in the physiological range. Different strategies were used to bring aspartate to the minimal level. Finally, the authors used jAspSnFR3 to estimate the intracellular aspartate concentration. One of the highlights of the manuscript was a treatment with asparagine during glutamine starvation. Although didn't corroborate the essentiality of asparagine in glutamine depletion, the measurement of aspartate during this supplementation is a glimpse of how useful this sensor can be.

Reviewer #1 (Public Review):

The authors have developed an open-source high-resolution microscope that is easily accessible to scientists, students, and the general public. The microscope is specifically designed to work with incubators and can image cells in culture over long periods. The authors provide detailed instructions for building the microscope and the necessary software to run it using off-the-shelf components. The system has great potential for studying cell biology and various biological processes.

The authors' work will make scientific instruments more accessible and remove obstacles to the free diffusion of capabilities and know-how in science. This important contribution will enable more people to conduct scientific research.

Reviewer #2 (Public Review):

Making state-of-the-art (super-resolution) microscopy widely available has been the subject of many publications in recent years as correctly referenced in the manuscript. By advocating the ideas of open-microscopy and trying to replace expensive, scientific-grade components such as lasers, cameras, objectives, and stages with cost-effective alternatives, interested researchers nowadays have a number of different frameworks to choose from. In the iteration of the theme presented here, the authors used the existing modular UC2 framework, which consists of 3D printable building blocks, and combined a cheapish laser, detector and x,y,(z) stage with expensive filters/dichroics and a very expensive high-end objective (>15k Euros). This particular choice raises a first technical question, to which extent a standard NA 1.3 oil immersion objective available for <1k would compare to the chosen NA 1.49 one.

The choice of using the UC2 framework has the advantage, that the individual building blocks can be 3D printed, although it should be mentioned that the authors used injection-molded blocks that will have a limited availability if not offered commercially by a third party. The strength of the manuscript is the tight integration of the hardware and the software (namely the implementations of imSwitch as a GUI to control data acquisition, OS SMLM algorithms for fast sub-pixel localisation and access to Napari).

The presented experimental data is convincing, demonstrating (1) extended live cell imaging both using bright-field and fluorescence in the incubator, (2) single-particle tracking of quantum dots, and (3) and STORM measurements in cells stained against tubulin.

In the following I will raise two aspects that currently limit the clarity and the potential impact of the manuscript.

First, the manuscript would benefit from further refinement. Elements in Figure 1d/e are not described properly. Figure 2c is not described in the caption. GPI-GFP is not introduced. MMS (moment scaling spectrum) could benefit from a one sentence description of what it actually is. In Figure 6, the size of the STORM and wide-field field of views are vastly different, the distances between the peaks on the tubuili are given in micrometers rather than nanometers. (more in the section on recommendations for the author)

Second, and this is the main criticism at this point, is that although all the information and data is openly available, it seems very difficult to actually build the setup due to a lack of proper documentation (as of early July 2023).<br /> 1. The bill of materials (https://github.com/openUC2/UC2-STORM-and-Fluorescence#bill-of-material) should provide a link to the commercially available items. Some items are named in German. Maybe split the BoM in commercially available and 3D printable parts (I first missed the option to scroll horizontally).<br /> 2. The links to the XY and Z stage refer to the general overview site of the UC2 project (https://github.com/openUC2/) requiring a deep dive to find the actual information.<br /> 3. Detailed building instructions are unfortunately missing. How to assemble the cubes (pCad files showing exploded views, for example)? Trouble shooting?<br /> 4. Some of the hardware details (e.g. which laser was being used, lenses, etc) should be mentioned in the manuscript (or SI)

I fully understand that providing such level of detail is very time consuming, but I hope that the authors will be able to address these shortcomings.

Reviewer #1 (Public Review):

This is a very interesting paper which addresses how auditory cortex represents sound while an animal is performing an auditory task. The study involves psychometric and neurophysiological measurement from ferrets engaged in a challenging tone in noise discrimination task, and relates these measurements using neurometric analysis. A novel neural decoding technique (decoding-based dimensionality reduction or dDR, introduced in a previous paper by two of the authors) is used to reduce bias so that stimulus parameters can be read out from neuronal responses.

The central finding of the study is that, when an animal is engaged in a task, non-primary auditory cortex represents task-relevant sound features in a categorical way. In primary cortex, task engagement also affects representations, but in a different way - the decoding is improved (suggesting that representations have been enhanced), but is not categorical in nature. The authors argue that these results are compatible with a model where early sensory representations form an overcomplete representation of the world, and downstream neurons flexibly read out behaviourally relevant information from these representations.

I find the concept and execution of the study very interesting and elegant. The paper is also commendably clear and readable. The differences between primary and higher cortex are compelling and I am largely convinced by the authors' claim that they have found evidence that broadly supports a mixed selectivity model of neural disentanglement along the lines of Rigotti et al (2013). I think that the increasing body of evidence for these kinds of representations is a significant development in our understanding of higher sensory representations. I also think that the dDR method is likely to be useful to researchers in a variety of fields who are looking to perform similar types of neural decoding analysis.

Reviewer #2 (Public Review):

This study compares the activity of neural populations in the primary and non-primary auditory cortex of ferrets while the animals actively behaved or passively listened to a sound discrimination task. Using a variety of methods, the authors convincingly show differential effects of task engagement on population neural activity in primary vs non-primary auditory cortex; notably that in the primary auditory cortex, task-engagement (1) improves discriminability for both task-relevant and non-task relevant dimensions, and (2) improves the alignment between covariability and sound discrimination axes; whereas in the non-primary auditory cortex, task-engagement (1) improves discriminability for only task-relevant dimensions, and (2) does not affect the alignment between covariability and sound discrimination axes. They additionally show that task-engagement changes in gain can account for the selectivity noted in the discriminability of non-primary auditory neurons. They also admirably attempt to isolate task-engagement from arousal fluctuations, by using fluctuations in pupil size as a proxy for physiological arousal. This is a well-carried out study with thoughtful analyses which in large part achieves its aims to evaluate how task-engagement changes neural activity across multiple auditory regions. As with all work, there are several caveats or areas for future study/analysis. First, the sounds used here (tones, and narrow-band noise) are relatively simple sounds; previous work suggests that exactly what activity is observed within each region (e.g., sensory only, decision-related, etc) may depend in part upon what stimuli are used. Therefore, while the current study adds importantly to the literature, future work may consider the use of more varied stimuli. Second, the animals here were engaged in a behavioral task; but apart from an initial calculation of behavioral d', the task performance (and its effect on neural activity) is largely unaddressed.

Reviewer #1 (Public Review):

Summary:<br /> Tian et al. investigated the effects of emotional signals in biological motion on pupil responses. In this study, subjects were presented with point-light biological motion stimuli with happy, neutral, and sad emotions. Their pupil responses were recorded with an eye tracker. Throughout the study, emotion type (i.e., happy/sad/neutral) and BM stimulus type (intact/inverted/non-BM/local) were systematically manipulated. For intact BM stimuli, happy BM induced a larger pupil diameter than neutral BM, and neutral BM also induced a larger pupil diameter than sad BM. Importantly, the diameter difference between happy and sad BM correlated with the autistic trait of individuals. These effects disappeared for the inverted BM and non-BM stimuli. Interestingly, both happy and sad emotions show superiority in pupil diameter.

Strengths:<br /> 1. The experimental conditions and results are very easy to understand.<br /> 2. The writing and data presentation are clear.<br /> 3. The methods are sound. I have no problems with the experimental design and results.

Weaknesses:<br /> 1. My main concern is the interpretation of the intact and local condition results. The processing advantage of happy emotion is not surprising given a number of existing studies. However, the only difference here seems to be the smaller (or larger) pupil diameter for sad compared to neutral in the intact (or local, respectively) condition. The current form only reports this effect but lacks in-depth discussions and explanations as to why this is the case.

2. I also found no systematic discussion and theoretical contributions regarding the correlation with the autistric trait. If the main point of this paper is to highlight an implicit and objective behavioral marker of the autistric trait, more interpretation and discussion of the links between the results and existing findings in ASD are needed.

Reviewer #2 (Public Review):

Summary:<br /> Through a series of four experiments, Yuan, Wang and Jiang examined pupil size responses to emotion signals in point-light motion stimuli. Experiment 1 examined upright happy, sad and neutral point-light biological motion (BM) walkers. The happy BM induced a significantly larger pupil response than the neutral, whereas the sad BM evoked a significantly smaller pupil size than the neutral BM. Experiment 2 examined inverted BM walkers. Experiment 3 examined BM stimuli with acceleration removed. No significant effects of emotion were found in neither Experiment 2 nor Experiment 3. Experiment 4 examined scrambled BM stimuli, in which local motion features were preserved while the global configuration was disrupted. Interestingly, the scrambled happy and sad BM led to significantly greater pupil size than the scrambled neutral BM at a relatively early time, while no significant difference between the scrambled happy and sad BM was found. Thus, the authors argue that these results suggest multi-level processing of emotions in life motion signals.

Strengths:<br /> The experiments were carefully designed and well-executed, with point-light stimuli that eliminate many potential confounding effects of low-level visual features such as luminance, contrast, and spatial frequency.

Weaknesses:<br /> Correlation results with limited sample size should be interpreted with extra caution.

It would be helpful to add discussions as a context to compare the current results with pupil size reactions to emotion signals in picture stimuli.

Overall, I think this is a well-written paper with solid experimental results that support the claim of the authors, i.e., the human visual system may process emotional information in biological motion at multiple levels. Given the key role of emotion processing in normal social cognition, the results will be of interest not only to basic scientists who study visual perception, but also to clinical researchers who work with patients of social cognitive disorders. In addition, this paper suggests that examining pupil size responses could be a very useful methodological tool to study brain mechanisms underlying emotion processing.

Reviewer #3 (Public Review):

Summary:<br /> The overarching goal of the authors was to understand whether emotional information conveyed through point-light biological motion can trigger automatic physiological responses, as reflected in pupil size.

Strengths:<br /> This manuscript has several noticeable strengths: it addresses an intriguing research question that fills that gap in existing literature, presents a clear and accurate presentation of the current literature, and conducts a series of experiments and control experiments with adequate sample size. Yet, it also entails several noticeable limitations - especially in the study design and statistical analyses.

Weaknesses:<br /> 1. Study design:<br /> 1.1 Dependent variable:<br /> Emotional attention is known to modulate both microsaccades and pupil size. Given the existing pupillometry data that the authors have collected, it would be both possible and valuable to determine whether the rate of microsaccades is also influenced by emotional biological motion.

1.2 Stimuli:<br /> It appears that the speed of the emotional biological motion stimuli mimics the natural pace of the emotional walker. What is the average velocity of the biological motion stimuli for each condition?

When the authors used inverted biological motion stimuli, they didn't observe any modulation in pupil size. Could there be a difference in microsaccades when comparing inverted emotional biological motion stimuli?

2. Statistical analyses<br /> 2.1 Multiple comparisons:<br /> There are many posthoc comparisons throughout the manuscript. The authors should consider correction for multiple comparisons. Take Experiment 1 for example, it is important to note that the happy over neutral BM effect and the sad over neutral BM effect are no longer significant after Bonferroni correction, which is worth noting.

2.2 The authors present the correlation between happy over sad dilation effect and the autistic traits in Experiment 1, but do not report such correlations in Experiments 2-4. Did the authors collect the Autistic Quotient measure in Experiments 2-4? It would be informative if the authors could demonstrate the reproducibility (or lack thereof) of this happy-sad index in Experiments 2-4.

2.3 The observed correlation between happy over sad dilation effect and the autistic traits in Experiment 1 seems rather weak. It could be attributed to the poor reliability of the Autistic Quotient measure or the author-constructed happy-sad index. Did the authors examine the test-retest reliability of their tasks or the Autistic Quotient measure?

2.4 Relatedly, the happy over sad dilation effect is essentially a subtraction index. Without separately presenting the pipul size correlation with happy and sad BM in supplemental figures, it becomes challenging to understand what's primarily driving the observed correlation.

2.5 For the sake of transparency, it is important to report all findings, not just the positive results, throughout the paper.

3. Structure<br /> 3.1 The Results section immediately proceeds to the one-way repeated measures ANOVA. This section could be more reader-friendly by including a brief overview of the task procedures and variables, e.g., shifting Fig. 3 to this section.

Reviewer #1 (Public Review):

This study examines whether the human brain uses a hexagonal grid-like representation to navigate in a non-spatial space constructed by competence and trustworthiness. To test this, the authors asked human participants to learn the levels of competence and trustworthiness for six faces by associating them with specific lengths of bar graphs that indicate their levels in each trait. After learning, participants were asked to extrapolate the location from the partially observed morphing bar graphs. Using fMRI, the authors identified brain areas where activity is modulated by the angles of morphing trajectories in six-fold symmetry. The strength of this paper lies in the question it attempts to address. Specifically, the question of whether and how the human brain uses grid-like representations not only for spatial navigation but also for navigating abstract concepts, such as social space, and guiding everyday decision-making. This question is of emerging importance.

The weak points of this paper are that its findings are not sufficiently supporting their arguments, and there are several reasons for this:

1. Does the grid-like activity reflect 'navigation over the social space' or 'navigation in sensory feature space'? The grid-like representation in this study could simply reflect the transition between stimuli (the length of bar graphs). Participants in this study associated each face with a specific length of two bars, and the 'navigation' was only guided by the morphing of a bar graph image. Moreover, any social cognition was not required to perform the task where they estimate the grid-like activity. To make social decision-making that was conducted separately, we do not know if participants needed to navigate between faces in a social space. Instead, they can recall bar graphs associated with faces and compute the decision values by comparing the length of bars. Notably, in the trust game in this study, competence and trustworthiness are not equally important to make a decision (Equation 1). The expected value is more sensitive to one over the other. This also suggests that the space might not reflect social values but perceptual differences.

2. Does the brain have a common representation of faces in a social space? In this study, participants don't need to have a map-like representation of six faces according to their levels of social traits. Instead, they can remember the values of each trait. The evidence of neural representations of the faces in a 2-dimensional social space is lacking. The authors argued that the relationship between the reaction times and the distances between faces provides evidence of the formation of internal representations. However, this can be found without the internal representation of the relationships between faces. If the authors seek internal representations of the faces in the brain, it would be important to show that this representation is not simply driven by perceptual differences between bar graphs that participants may recall in association with each face.

Considering these caveats, it is hard for me to agree if the authors provide evidence to support their claims.

Reviewer #2 (Public Review):

Summary:<br /> In this work, Liang et al. investigate whether an abstract social space is neurally represented by a grid-like code. They trained participants to 'navigate' around a two-dimensional space of social agents characterized by the traits of warmth and competence, then measured neural activity as participants imagined navigating through this space. The primary neural analysis consisted of three procedures: 1) identifying brain regions exhibiting the hexagonal modulation characteristic of a grid-like code, 2) estimating the orientation of each region's grid, and 3) testing whether the strength of the univariate neural signal increases when a participant is navigating in a direction aligned with the grid, compared to a direction that is misaligned with the grid.<br /> From these analyses, the authors find the clearest evidence of a grid-like code in the prefrontal cortex and weaker evidence in the entorhinal cortex.

Strengths:<br /> The work demonstrates the existence of a grid-like neural code for a socially-relevant task, providing evidence that such coding schemes may be relevant for a variety of two-dimensional task spaces.

Weaknesses:<br /> In various parts of this manuscript, the authors appear to use a variety of terms to refer to the (ostensibly) same neural regions: prefrontal cortex, frontal pole, ventromedial prefrontal cortex (vmPFC), and orbitofrontal cortex (OFC). It would be useful for the authors to use more consistent terminology to avoid confusing readers.

Claims about a grid code in the entorhinal cortex are not well-supported by the analyses presented. The whole-brain analysis does not suggest that the entorhinal cortex exhibits hexagonal modulation; the strength of the entorhinal BOLD signal does not track the putative alignment of the grid code there; multivariate analyses do not reveal any evidence of a grid-like representational geometry.

On a conceptual level, it is not entirely clear how this work advances our understanding of grid-like encoding of two-dimensional abstract spaces, or of social cognition. The study design borrows heavily from Constantinescu et al. 2016, which is itself not an inherent weakness, but the Constantinescu et al. study already suggests that grid codes are likely to underlie two-dimensional spaces, no matter how abstract or arbitrary. If there were a hypothesis that there is something unique about how grid codes operate in the social domain, that would help motivate the search for social grid codes specifically, but no such theory is provided. The authors do note that warmth and competence likely have ecological importance as social traits, but other past studies have used slightly different social dimensions without any apparent loss of generality (e.g., Park et al. 2021). There are some (seemingly) exploratory analyses examining how individual difference measures like social anxiety and avoidance might affect the brain and behavior in this study, but a strong theoretical basis for examining these particular measures is lacking.

I found it difficult to understand the analyses examining whether behavior (i.e., reaction times) and individual difference measures (i.e., social anxiety and avoidance) can be predicted by the hexagonal modulation strength in some region X, conditional on region X having a similar estimated grid alignment with some other region Y. It is possible that I have misunderstood the authors' logic and/or methodology, but I do not feel comfortable commenting on the correctness or implications of this approach given the information provided in the current version of this manuscript.

It was puzzling to see passing references to multivariate analyses using representational similarity analysis (RSA) in the main text, given that RSA is only used in analyses presented in the supplementary material.

References:<br /> Constantinescu, A. O., O'Reilly, J. X., & Behrens, T. E. (2016). Organizing conceptual knowledge in humans with a gridlike code. Science, 352(6292), 1464-1468.

Park, S. A., Miller, D. S., & Boorman, E. D. (2021). Inferences on a multidimensional social hierarchy use a grid-like code. Nature Neuroscience, 24(9), 1292-1301.

Reviewer #3 (Public Review):

Liang and colleagues set out to test whether the human brain uses distance and grid-like codes in social knowledge using a design where participants had to navigate in a two-dimensional social space based on competence and warmth during an fMRI scan. They showed that participants were able to navigate the social space and found distance-based codes as well as grid-like codes in various brain regions, and the grid-like code correlated with behavior (reaction times).

On the whole, the experiment is designed appropriately for testing for distant-based and grid-like codes and is relatively well-powered for this type of study, with a large amount of behavioral training per participant. They revealed that a number of brain regions correlated positively or negatively with distance in the social space, and found grid-like codes in the frontal polar cortex and posterior medial entorhinal cortex, the latter in line with prior findings on grid-like activity in the entorhinal cortex. The current paper seems quite similar conceptually and in design to previous work, most notably by Park et al., 2021, Nature Neuroscience.

Below, I raise a few issues and questions on the evidence presented here for a grid-like code as the basis of navigating abstract social space or social knowledge.

1. The authors claim that this study provides evidence that humans use a spatial / grid code for abstract knowledge like social knowledge.

This data does specifically not add anything new to this argument. As with almost all studies that test for a grid code in a similar "conceptual" space (not only the current study), the problem is that when the space is not a uniform, square/circular space, and 2-dimensional then there is no reason the code will be perfectly grid-like, i.e., show six-fold symmetry. In real-world scenarios of social space (as well as navigation, semantic concepts), it must be higher dimensional - or at least more than two-dimensional. It is unclear if this generalizes to larger spaces where not all part of the space is relevant. Modelling work from Tim Behrens' lab (e.g., Whittington et al., 2020) and Bradley Love's lab (e.g., Mok & Love, 2019) have shown/argued this to be the case. In experimental work, like in mazes from the Mosers' labs (e.g., Derdikman et al., 2009), or trapezoid environments from the O'Keefe lab (Krupic et al., 2015), there are distortions in mEC cells, and would not pass as grid cells in terms of the six-fold symmetry criterion.

The authors briefly discuss the limitations of this at the very end but do not really say how this speaks to the goal of their study and the claim that social space or knowledge is organized as a grid code and if it is in fact used in the brain in their study and beyond. This issue deserves to be discussed in more depth, possibly referring to prior work that addressed this, and raising the issue for future work to address the problem - or if the authors think it is a problem at all.

Data and analysis

2. Concerning the negative correlation of distance with activation in the fusiform gyrus and visual cortex: this is a slightly puzzling but potentially interesting finding. However, could this be related to reaction times? The larger the distance, the longer the reaction times, so the original finding might reflect larger activations with smaller distances.

3. Concerning the correlation of grid-like activity with behavior: is the correlation with reaction time just about how long people took (rather than a task-related neural signal)? The authors have only reported correlations with reaction time. The issue here is that the duration of reaction times also relates to the starting positions of each trial and where participants will navigate to. Considering the speed-accuracy tradeoff, could performance accuracy be negatively correlated with these grid consistency metrics? Or it could be positively correlated, which would suggest the grid signal reflects a good representation of the task.

Reviewer #1 (Public Review):

Summary:

In this study, the authors show that a long-non coding RNA lncDACH1 inhibits sodium currents in cardiomyocytes by binding to and altering the localization of dystrophin. The authors use a number of methodologies to demonstrate that lncDACH1 binds to dystrophin and disrupts its localization to the membrane, which in turn downregulates NaV1.5 currents. Knockdown of lncDACH1 upregulates NaV1.5 currents. Furthermore, in heart failure, lncDACH1 is shown to be upregulated which suggests that this mechanism may have pathophysiolgoical relevance.

Strengths:

1. This study presents a novel mechanism of Na channel regulation which may be pathophysiologically important.

2. The experiments are comprehensive and systematically evaluate the physiological importance of lncDACH1.

Weaknesses:

1. What is indicated by the cytoplasmic level of NaV1.5, a transmembrane protein? The methods do not provide details regarding how this was determined. Do you authors means NaV1.5 retained in various intracellular organelles?

2. What is the negative control in Fig. 2b, Fig. 4b, Fig. 6e, Fig. 7c? The maximum current amplitude in these seem quite different. -40 pA/pF in some, -30 pA/pF in others and this value seems to be different than in CMs from WT mice (<-20 pA/pF). Is there an explanation for what causes this variability between experiments and/or increase with transfection of the negative control? This is important since the effect of lncDACH1 is less than 50% reduction and these could fall in the range depending on the amplitude of the negative control.

3. NaV1.5 staining in Fig. 1E is difficult to visualize and to separate from lncDACH1. Is it possible to pseudocolor differently so that all three channels can be visualized/distinguished more robustly?

4. The authors use shRNA to knockdown lncDACH1 levels. It would be helpful to have a scrambled ShRNA control.

5. Is there any measurement on the baseline levels of LncDACH1 in wild-type mice? It seems quite low and yet is a substantial increase in NaV1.5 currents upon knocking down LncDACH1. By comparison, the level of LncDACH1 seems to be massively upregulated in TAC models. Have the authors measured NaV1.5 currents in these cells? Furthermore, does LncDACH1 knockdown evoke a larger increase in NaV1.5 currents?

6. What do error bars denote in all bar graphs, and also in the current voltage relationships?

Reviewer #2 (Public Review):

This manuscript by Xue et al. describes the effects of a long noncoding RNA, lncDACH1, on the localization of Nav channel expression, the magnitude of INa, and arrhythmia susceptibility in the mouse heart. Because lncDACH1 was previously reported to bind and disrupt membrane expression of dystrophin, which in turn is required for proper Nav1.5 localization, much of the findings are inferred through the lens of dystrophin alterations.

The results report that cardiomyocyte-specific transgenic overexpression of lncDACH1 reduces INa in isolated cardiomyocytes; measurements in whole heart show a corresponding reduction in conduction velocity and enhanced susceptibility to arrhythmia. The effect on INa was confirmed in isolated WT mouse cardiomyocytes infected with a lncDACH1 adenoviral construct. Importantly, reducing lncDACH1 expression via either a cardiomyocyte-specific knockout or using shRNA had the opposite effect: INa was increased in isolated cells, as was conduction velocity in heart. Experiments were also conducted with a fragment of lnDACH1 identified by its conservation with other mammalian species. Overexpression of this fragment resulted in reduced INa and greater proarrhythmic behavior. Alteration of expression was confirmed by qPCR.

The mechanism by which lnDACH1 exerts its effects on INa was explored by measuring protein levels from cell fractions and immunofluorescence localization in cells. In general, overexpression was reported to reduce Nav1.5 and dystrophin levels and knockout or knockdown increased them.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors report the first evidence of Nav1.5 regulation by a long noncoding RNA, LncRNA-DACH1, and suggest its implication in the reduction in sodium current observed in heart failure. Since no direct interaction is observed between Nav1.5 and the LncRNA, they propose that the regulation is via dystrophin and targeting of Nav1.5 to the plasma membrane.

Strengths:

1. First evidence of Nav1.5 regulation by a long noncoding RNA.<br /> 2. Implication of LncRNA-DACH1 in heart failure and mechanisms of arrhythmias.<br /> 3. Demonstration of LncRNA-DACH1 binding to dystrophin.<br /> 4. Potential rescuing of dystrophin and Nav1.5 strategy.

Weaknesses:

1. Main concern is that the authors do not provide evidence of how LncRNA-DACH1 regulates Nav1.5 protein level. The decrease in total Nav1.5 protein by about 50% seems to be the main consequence of the LncRNA on Nav1.5, but no mechanistic information is provided as to how this occurs.<br /> 2. The fact that the total Nav1.5 protein is reduced by 50% which is similar to the reduction in the membrane reduction questions the main conclusion of the authors implicating dystrophin in the reduced Nav1.5 targeting. The reduction in membrane Nav1.5 could simply be due to the reduction in total protein.

Reviewer #1 (Public Review):

Sukumar et al build on a body of work from the Palmer lab that seeks to unravel the transcriptional targets of Alk signaling (a receptor tyrosine kinase). Having uncovered its targets in the mesoderm in an earlier study, they seek to determine its targets in the central nervous system. To do this, they use Targeted DamID (TaDa) in the wild-type and Alk dominant negative background and identify about 1700 genes that might be under the control of Alk signalling. Using their earlier data and applying a set of criteria - upregulated in gain-of-Alk, downregulated in loss-of-Alk, and co-expressed with Alk positive cells in single cell datasets - they arrive upon a single gene, Sparkly, which is predicted to be a neuropeptide precursor.

They generate antibodies and mutants for Sparkly and determine that it is responsive to Alk signalling and is expressed in many neuroendocrine cells, as well as in clock neurons. Though the mutants survive, they have reduced lifespans and are hyperactive. In summary, the authors identify a previously unidentified transcriptional target of Alk signalling, which is likely cleaved into a neuropeptide and is involved in regulating circadian activity.

The data support claims made, are generally well presented and the manuscript clearly written. The link between circadian control of Alk signalling in Clock neurons > Spar expression > ultimately controlling circadian activity, however, was not clear.

Reviewer #2 (Public Review):

This manuscript illustrates the power of "combined" research, incorporating a range of tools, both old and new to answer a question. This thorough approach identifies a novel target in a well-established signalling pathway and characterises a new player in Drosophila CNS development.

Largely, the experiments are carried out with precision, meeting the aims of the project, and setting new targets for future research in the field. It was particularly refreshing to see the use of multi-omics data integration and Targeted DamID (TaDa) findings to triage scRNA-seq data. Some of the TaDa methodology was unorthodox (and should be justifed/caveats mentioned in the main text), however, this does not affect the main finding of the study.

Their discovery of Spar as a neuropeptide precursor downstream of Alk is novel, as well as its ability to regulate activity and circadian clock function in the fly. Spar was just one of the downstream factors identified from this study, therefore, the potential impact goes beyond this one Alk downstream effector.

Reviewer #3 (Public Review):

Summary:

The receptor tyrosine kinase Anaplastic Lymphoma Kinase (ALK) in humans is nervous system expressed and plays an important role as an oncogene. A number of groups have been signalling ALK signalling in flies to gain mechanistic insight into its various role. In flies, ALK plays a critical role in development, particularly embryonic development and axon targeting. In addition, ALK also was also shown to regulate adult functions including sleep and memory. In this manuscript, Sukumar et al., used a suite of molecular techniques to identify downstream targets of ALK signalling. They first used targeted DamID, a technique that involves a DNA methylase to RNA polymerase II, so that GATC sites in close proximity to PolII binding sites are marked. They performed these experiments in wild-type and ALK loss of function mutants (using an Alk dominant negative ALkDN), to identify Alk responsive loci. Comparing these loci with a larval single-cell RNAseq dataset identified neuroendocrine cells as an important site of Alk action. They further combined these TaDa hits with data from RNA seq in Alk Loss and Gain of Function manipulations to identify a single novel target of Alk signalling - a neuropeptide precursor they named Sparkly (Spar) for its expression pattern. They generated a mutant allele of Spar, raised an antibody against Spar, and characterised its expression pattern and mutant behavioural phenotypes including defects in sleep and circadian function.

Strengths:

The molecular biology experiments using TaDa and RNAseq were elegant and very convincing. The authors identified a novel gene they named Spar. They also generated a mutant allele of Spar (using CrisprCas technology) and raised an antibody against Spar. These experiments are lovely, and the reagents will be useful to the community. The paper is also well written, and the figures are very nicely laid out making the manuscript a pleasure to read.

Weaknesses:

My main concerns were around the genetics and behavioural characterisation which is incomplete. The authors generated a novel allele of Spar - Spar ΔExon1 and examined sleep and circadian phenotypes of this allele. However, they have only one mutant allele of Spar, and it doesn't appear as if this mutant was outcrossed, making it very difficult to rule out off-target effects. To make this data convincing, it would be better if the authors had a second allele, perhaps they could try RNAi?

Further, the sleep and circadian characterisation could be substantially improved. In Fig 8 E-F it appears as if sleep was averaged over 30 days! This is a little bizarre. They then bin the data as day 1 - 12 and 12-30. This is not terribly helpful either. Sleep in flies, as in humans, undergoes ontogenetic changes - sleep is high in young flies, stabilises between day 3-12, and shows defects by around 3 weeks of age (cf Shaw et al., 2000 PMID 10710313). The standard in the sleep field is to average over 3 days or show one representative day. The authors should reanalyse their data as per this standard, and perhaps show data from 3-10 day old flies, and if they like from 20-30 day old flies. Further, sleep data is usually analysed and presented from lights on to lights on. This allows one to quantify important metrics of sleep consolidation including bout lengths in day and night, and sleep latency. These metrics are of great interest to the community and should be included.

The authors also claim there are defects in circadian anticipatory activity. However, these data, as presented are not solid to me. The standard in the field is to perform eduction analyses and quantify anticipatory activity e.g. using the method of Harrisingh et al. (PMID: 18003827). Further, circadian period could also be evaluated. There are several free software packages to perform these analyses so it should not be hard to do.

Reviewer #1 (Public Review):

This study was designed to examine the bypass of Ras/Erk signaling defects that enable limited regeneration in a mouse model of hepatic regeneration. The authors show that this hepatocyte proliferation is marked by expression of CD133 by groups of cells. The CD133 appears to be located on intracellular vesicles associated with microtubules. These vesicles are loaded with mRNA. The authors conclude that the CD133 vesicles mediate an intercellular signaling pathway that supports cell proliferation. These are new observations that have broad significance to the fields of regeneration and cancer.

The primary observation is that the limited regeneration observed in livers with Ras/Erk signaling defects is associated with CD133 expression by groups of cells. The functional significance of CD133 was tested using Prom1 KO mice - the data presented are convincing.

The major weakness of the study is that some molecular mechanistic details are unclear - this is, in part, due to the extensive new biology that is described. Nevertheless, the data used to support some key points in this study are unclear:

a) What is the evidence that the observed CD133 groups of cells are not due to clonal growth. Is this conclusion based on the time course (the groups appear more rapidly than proliferation) or is this based on the GFP clonal analysis?

b) What is the evidence that the CD133 vesicles mediate intercellular communication. This is an exciting hypothesis, but what is the evidence that this happens? Is this inferred from IEG mRNA diversity? or some other data. Is there direct evidence of transfer - for example, the does the GFP clonal analysis show transfer of GFP that is not mediated by clonal proliferation? Moreover, since the hepatocytes are isogenic, what distinguishes the donor and recipient cells?

Increased clarity concerning what is hypothesis and what is directly supported by data - would improve the presentation of this study.

Reviewer #2 (Public Review):

The manuscript by Kaneko set out to understand the mechanisms underlying cell proliferation in hepatocytes lacking Shp2 signals. To do this, the authors focused on CD133 as the proliferating clusters of cells in the Shp2 knockout (SKO) livers are CD133 expressing. After excluding the contribution of progenitors that are CD133 to this cell population, the authors focused on the intrinsic regulation of CD133 by Met/Shp2 regulated Ras/Erk parthway and showed upregulation of CD133 to be a compensatory signal to overcome loss of Ras/Erk signal and suggested Wnt10a in the regulation of CD133 signal. The study then focused on the observed filament localization of CD133 in the CD133+ cluster of cells. The study went on to identify the CD133+ vesicles that contain primarily mRNA vs. microRNA like other EVs. Specifically, the authors identified several mRNA species that encode IEGs, indicating a potential role for these CD133+ vesicles in cell proliferation signal transmission to neighboring cells via delivery of the IEG mRNAs as cargos. Finally, they showed that the induction of CD133 (and by derivative, the CD133+ vesicles) are necessary for maintaining cell proliferation in the cell cluster with high proliferation capacities in the SKO livers; and in intestinal crypt organoids treated with Met inhibitors to block Ras/ERk signal. In the revised manuscript, the authors more definitively identified the CD133+ vesicles. The authors also provided additional experimental evidence demonstrating the role of these CD133+ vesicles in cell-cell communication. The functional significance of CD133 on this cell-cell communication was further demonstrated with genetic knockout studies.

Reviewer #1 (Public Review):

Summary:<br /> The authors use a combination of ChIP-seq, RNA-seq and ATAC-seq on FACS-purified germ cells to understand the changes in transcription and chromatin landscape of germline stem cells (GSCs) and their progeny during adult oogenesis.

Strengths:<br /> The major strengths of the paper include high quality -omics data, robust analyses of the data, and a well-written manuscript. The data strongly support the conclusions (1) that GSCs have more open chromatin than its differentiating daughter cells, (2) that H3K9me3 heterochromatin forms in 16-cell cyst stage and silences GSC-enriched genes, transposons, and testis-biased and somatic genes; (3) that GSC-enriched genes encoding cell cycle control, protein synthesis and signal transduction reside in clusters in autosomal pericentric regions; and (4) that there is a transcriptionally-driven metabolic reprogramming of nurse (germline) cells to aerobic glycolysis.

These data sets and analyses will have a high impact of the field of germline lifecycle (from GSC to primordial germ cells to GSCs again). The authors will make these data sets available through NCBI GEO and on Github. However, these are not incredibly user friendly and these data sets are extremely useful. I wonder if it is possible to incorporate these valuable data set into existing websites?

Weaknesses:<br /> There are no obvious weaknesses.

Reviewer #2 (Public Review):

Summary:

The preprint by Pang, Deluca, et al. investigates the molecular events occurring during germline stem cell (GSC) differentiation into an oocyte. The study highlights several critical observations:

1. Gene Expression and Chromatin State: GSCs exhibit an open chromatin state and express a large number of genes. However, during differentiation, the number of genes expressed decreases.<br /> 2. Gene Clustering and Chromatin Domains: Genes promoting GSC fate are found in clusters close to centric heterochromatin domains.<br /> 3. Epigenetic Marks: The transition from GSC fate to oocyte/nurse cell fate is marked by an increase in H3K27me3 and H3K9me3 on regions, including centric heterochromatin.<br /> 4. Metabolic Rewiring: Genes related to metabolism undergo changes during this fate transition, indicating metabolic rewiring.

Strengths:<br /> The conclusions are strongly supported by a substantial amount of data. Multiple complementary methods are employed, such as increased H3K9me3 heterochromatin and reporter assays, to validate the increase of H3K9me3 during meiosis.

The wealth of data presented will be valuable to the scientific community, providing further insights into critical molecular events during GSC differentiation.

The study uncovers new biology, notably the proximity of stem cell genes to centric heterochromatin and its regulation.

Key observations include the low H3K9me3 levels on transposons in GSCs, which warrant further investigation.

Weaknesses:<br /> To make the paper more accessible to a broader audience, the authors can use fewer jargon terms. In particular, the abbreviations used for staging can be confusing.

Some sections in the results contain extensive discussion that may be better suited for the discussion section. For example, see page 9.

Reviewer #1 (Public Review):

The current manuscript builds on a previous publication from the same group(s) (https://doi.org/10.7554/eLife.77779) that identified several new interacting partners of the ESCRT pathway. The authors show via fluorescence polarization anisotropy (FPA) and NMR spectroscopy that the microtubule-interacting and trafficking (MIT) domains of CALPAIN7 bind to the IST1 subunit of the ESCRT-III complex. The authors used a powerful combination of biochemical, structural, and cell biological tools. The experiments are designed well and are performed to a high standard. The vast majority of the conclusions are supported by the data.

The authors report the X-ray crystal structure of the MIT-IST complex show the exact residues involved in the interaction and the mode of binding. They validate their findings and put them in a biological context by introducing mutations into the key residues in the MIT domain of CALPAIN7 and IST domain of ESCRT-III that can disrupt and restore the molecular interactions using in vitro biochemical assays and in vivo immunofluorescence microscopy imaging.

The writing is exceptional. I could not spot a single typographical or grammatical error. The manuscript is easy to read. It is concise and is nicely supported by high-quality figures. It was a pleasure to read.

The authors provide a great amount of detailed information about the experiments performed and have deposited the majority (if not all) of the plasmids used in the study in a public depository. They should be commended for this decision.

Reviewer #2 (Public Review):

Please note that I am not a structural biologist and cannot critically evaluate the details of figures 1 to 3; my review focuses on the cell biology experiments in figures 4 and 5.

Paine and colleagues investigated structural requirements for the interaction between the ESCRT-III subunit IST1 and the protease CAPN7. This is a continuation of previous work by the same group (Wenzel et al., eLife 2022), which showed that Capn7 is recruited to the midbody by Ist1 and that Capn7 promotes both normal abscission and NoCut abscission checkpoint function. In this article, the structural determinants of the Ist1-Capn7 interaction are characterised in more detail, focusing on the structure of Capn7 MIT domains and their binding to Ist1. Notably, point mutations in Capn7 MIT domains known to mediate binding to Ist1 and midbody recruitment are shown here to be required for abscission functions, as expected from the authors' previous paper. Furthermore, the report shows that a Capn7 point mutant lacking proteolytic activity behaves as a loss-of-function in abscission assays, despite showing normal midbody localisation. These are important results that will help in future studies to understand how the Capn7 protease regulates abscission mechanistically.

The report is clearly written and the results support the main conclusions. Some technical limitations and alternative interpretations of the data should be discussed in the text, as outlined below.

1. It is not always clearly stated how the results presented in this report relate to those in the Wenzel paper. For example, the finding that Ist1 recruits Capn7 to midbodies (p. 6 and figure 4) was first shown in the Wenzel paper. The novelty here is not that Capn7 MIT mutants fail to localise to midbodies, but that they phenocopy the previously described knockdown of Capn7, failing to support normal abscission and NoCut function (fig. 5). This supports and extends the findings of Wenzel et al. It is important to make this explicit and explain the conceptual advances shown here more clearly.<br /> 2. The NoCut checkpoint can be triggered by chromatin bridges, DNA replication stress, and nuclear basket defects, but only basket defects are tested here. Therefore, it is not clear if NoCut is still functional in Capn7-defective cells after replication stress and/or with chromatin bridges. Ideally, this should be tested experimentally, or alternatively discussed in the text, especially since the molecular details of how NoCut is engaged under different conditions remain unclear. For example, "abscission checkpoint bodies" proposed to control abscission timing form in response to nuclear basket defects and aphidicolin treatment, but not in the presence of chromatin bridges (Strohacker et al., eLife 2021).<br /> 3. The current data suggest that Capn7 is a regulator of abscission timing, but in my opinion do not quite establish this, for two main reasons. First, abscission timing is not directly measured in this study. Time-lapse imaging would be required to rule out alternative interpretations of the data in figure 5. For example, a delay in an earlier cell cycle stage could in principle lead to a decrease in the overall fraction of midbody-stage cells. Second, the absence of the midbody is not necessarily a marker of complete abscission. Indeed, midbody disassembly is associated with the completion of abscission in unchallenged HeLa cells, but not in cells with chromatin bridges (Steigemann et al, Cell 2009). Midbodies remain a useful marker for pre-abscission cells, but the absence of midbodies should not be immediately interpreted as completion of abscission without further assays. Formally, a direct measurement of abscission timing would require imaging of the plasma membrane, for example using time-lapse phase-contrast microscopy (Fremont et al., 2016 Nat Comm). These limitations should be mentioned in the text.<br /> 4. IST1 plays a role in nuclear envelope sealing by recruiting the co-factor Spastin (Vietri et al., Nature 2015), a known IST1 co-factor also confirmed in the previous interactome screen (Wenzel et al. 2022). CAPN7 could have a role in maintaining nuclear integrity upon the KD of Nup153 and Nup50 (Mackay et al. 2010) instead of/in addition to its proposed role in delaying abscission as part of the NoCut checkpoint at the midbody. I don't think the authors can differentiate between these two possibilities, and it would be interesting to consider their possible implications on how the "NoCut" checkpoint is triggered.<br /> 5. Figure 5 should include images of representative cells, highlighting midbody-positive and multinucleated cells. Without images, it is not possible to evaluate the quality of these data.

Reviewer #3 (Public Review):

A central step in cell division is the formation of midbody abscission that separates two daughter cells at the end of cytokinesis. The ESCRT, endosomal sorting complexes required for transport, plays a critical role in this process. Specifically, the ESCRT-III proteins are actively recruited throughout the cell at the membrane fission sites, and their oligomerization into filaments is necessary to constrict the cell membranes to the fission point. Fundamental structural elements in ESCRT-III interactome are the so-called MIT-interacting motifs (MIMs) located at the protein's C terminal portion. Recently, Sundquist and co-workers (eLife 2022) identified several cofactors interacting with ESCRT-III subunits directly implicated in abscission. Among those cofactors, they identified Calpain-7, a cysteine protease whose function is still unclear. Calpain-7 comprises two MIT domains that target ESCRT-II subunit IST1. Here, the authors use structural methods and cell assays to characterize the interactions between Calpain-7 and IST1. For the structural studies, they constructed a minimalistic system in which MT1 and MT2 domains of Calpain-7 interact with the two MIMs localized in the IST1 construct. The truncated constructs interact with high affinity, recapitulating the strength of interaction expected for the full-length constructs in the cell. Using fluorescence polarization anisotropy binding isotherms, these researchers obtained solid binding data, showing a dissociation constant of 0.09 uM for the construct containing both MIMs, ~2 uM for the second MIM domain, and 100 uM for the first MIM. These data suggest a synergistic binding mechanism between the two MIM domains. The authors expressed and purified these constructs in recombinant systems and obtained purified isotopically labeled proteins to study by NMR. To characterize the binding by NMR, the authors studied the IST1 constructs with the two MIMs in the absence and presence of Calpain-7. The IST1 construct displays a well-resolved NMR fingerprint, with most resonances assigned to specific residues. Upon addition of the Calpain-7 construct, the resonances of the residues involved in the binding either broaden beyond detection or shift significantly, which supports the fluorescence binding studies. Given the high affinity, these authors were able to crystallize these complexes and identify the binding interfaces that parallel the solution NMR studies. Mutational studies confirm the hot spots for the interactions, and the authors concluded that the MIT:MIM binding interface is responsible for the association of the full-length constructs of Calpain-7 and IST1 in the cell. Using localization experiments, the authors concluded that IST1 is responsible for recruiting Calpain-7 to midbodies, and the presence of both MIT domains of Calpain-7 and MIM domains is required for localization. Taken together, the biophysical characterization of these complexes and the cell assays led the authors to conclude that IST1 binding to Calpain-7 is necessary for its role in abscission and Nocut checkpoint maintenance.<br /> In my opinion, the research is well executed and also supported by their previous finding (see Sundquist 2022 eLife). The paper is succinct and well-written.

Reviewer #1 (Public Review):

Iskusnykh et al. present an elegant and thorough analysis of the role of transcription factor Lmx1a as a master regulator of the cortical hem, which is a secondary organizer in the brain. The authors report that loss of Lmx1a in the hem alters expression levels of Wnts, that Lmx1a is critical for hem progenitors to exit the cell cycle properly, and that Lmx1a loss leads to defects in CR cell differentiation and migration. Furthermore, the authors show that hem-like fate can be induced by overexpressing Lmx1a. This is a fundamental role for a transcription factor that was long used as a hem marker but was never examined for its function in the hem. This study has broader implications for how secondary organizers are created in the embryo and would be of great interest to a wide readership. The conclusions are broadly well supported by the data, though there are a few points of interpretation that need to be addressed.

(1) Figure 3A shows staining intensity in WT and Lmx1a-/- whereas the quantification has Lmx1a+/-. Both genotypes are relevant, -/- and +/-, to test whether the loss of 1 copy of Lmx1a results in a partial diminution of Wnt3a levels. Likewise, it is necessary to examine Wnt3a expression levels in the Wnt3a+/- embryo. Together, these could explain why the Lmx1a+/-; Wnt3a+/- double heterozygote has a DG phenotype, otherwise, it remains an unexplained though interesting observation.

(2) Line 309: "to test Wnt3a as a downstream mediator of Lmx1a function in CH/DG development, we performed an analysis of Lmx1a/Wnt3a double heterozygotes rather than Wnt3a overexpression rescue experiments in Lmx1a -/- mice."

The authors' reasoning is unclear. The double het experiments do not go on to show that one gene acts via the other. It's entirely possible the two act via parallel pathways.<br /> However, since Lmx1a does indeed regulate Wnt3a levels, this is a good argument for suggesting it acts via Wnt3a, even without the overexpression rescue. The authors could reorganize the data and rephrase the definitive "acts via" statement (also in the heading of this section, line 289, and discussion, line 553) to better fit the data.

(3) In the discussion section, the authors should include that trans-hilar and supragranular scaffold is disrupted in Lrp6 and Lef1 single as well as double mutants, which indicates Wnt signaling has a role to play in the morphogenesis of this scaffold. In this context, the author may discuss how Lmx1a could regulate this process via modulating Wnt signaling.

(4) Reduction in Tbr2 levels (Fig4B): E 13.5, not all Tbr2+ cells in the hem show a visible decrease in Tbr2 levels. The CR cells in the marginal zone show faint Tbr2. It would be useful if the staining intensity within the hem was quantified by dividing the section into three bins along the radial axis: Ventricular Zone, "Intermediate" zone, and Marginal zone to get a sense of the intensity profile. Co-labeling with p73 would identify CR cells and distinguish them from hem progenitors.

(5) Are the total number of Prox1+ cells at E14.5 similar between control and Lmx1a-/- ? Might the decrease in Prox1+ cells in the DG of P21 Lmx1a-/- animals occur due to granule cell death or because fewer cells were specified due to lower Wnts from the compromised Lmx1a-/- hem? The authors should examine cell death, labeling with CC3 and Prox1 together to test the cell death angle and discuss if the specification angle applies.

(6) In figure 6, the authors show that Lmx1a OE is sufficient to induce hem-like features, and identify p73+ cells (CR cell lineage). Is the choroid lineage not induced or was it not examined? A line to this effect would be useful. Also, the validation that it is indeed ectopic hem could be stronger with a few additional markers, since this is a striking finding.

Reviewer #2 (Public Review):

The cortical hem is one of the main signaling centers in the vertebrate forebrain, regulating neurogenesis of the medial pallium and the generation of Cajal-Retzius neurons. The authors examine how this signaling center is formed and functions. Previously, transcription factors playing instructive roles in the development of the cortical hem have been identified, but a master regulator had not been found so far. The authors build on their previous work studying the transcription factor Lmx1a which is one of the earliest and most specific cortical hem markers.

By combining loss- and gain-of-function studies, RNA sequencing, histology, and analysis of downstream factors, the authors rigorously show Lmx1a is required for the expression of signaling molecules in the hem, the proliferation and functionality of dentate gyrus neurons, the cell cycle exit and differentiation (and also migration) of cajal-retzius cells and this by activating different downstream regulators.

They use golden standard experiments in the field such as BrdU-Ki67 cell-cycle exit measurements, RNA sequencing, and patch clamping; combined with state-of-the-art techniques such as RNAscope and laser capture microdissection. These convincingly show that Lmx1a regulates the proliferation of dentate gyrus progenitor cells and a malformation of the transhilar scaffold. The authors also claim a migration deficit for dentate gyrus progenitors, but they do not consider apoptosis or show direct evidence for migration abnormalities.<br /> In the hem, the authors report normal proliferation and apoptosis in the Lmx1a mutants, but aberrant cell-cycle-exit, from which the authors conclude a problem in differentiation. However, this could be a cell cycle progression problem too (stuck in a certain cell cycle phase?), as the RNAseq data suggest. The authors should acknowledge this possibility.

The RNAseq dataset provides candidate downstream regulators of the observed phenotypes and the authors test the functionality of Wnt3a, Tbr2, and Cdkn1a, showing they are involved in distinct processes.<br /> Strikingly, Wnt3a is not significantly downregulated in the RNAseq data in the Lmx1a mutant, but quantification of in situ hybridization signal (which is less robust) did reveal a significant difference. Is this a splice variant issue? A timing issue or specificity of the RNAscope probe? The authors should look into this more carefully.

To study the role of Cdkn1a, the authors performed rescue experiments using in utero electroporation, which is a standard in the field. However, they argued before that "CR cell migration and DG morphogenesis are complex processes that require precise expression levels of key genes" when studying downstream factors Wnt3a and Tbr2. Why is this no longer an issue studying Cdkn1a?<br /> To study cell-cycle exit in this model, the authors quantified GFP and Ki67. Since electroporation not only targets the progenitor cells (see e.g. Govindan et al. 2018, Nature protocols), the authors should confirm these results with a BrdU/Ki67 quantification as in previous experiments, or confirm electroporation only targeted progenitor cells in their model.

Lastly, the authors ectopically expressed Lmx1a and convincingly show its ability to generate a hem-like structure. Could the authors elaborate on the necessity for a medial signature? Can the hem be ectopically induced in the lateral pallium?

Reviewer #1 (Public Review):

Huang, Kevin Y. et al. perform a meta-analysis of single-cell RNA-seq (scRNA-seq) data derived from 11 studies and across six tissues (liver, lung, heart, skin, kidney, endometrium) to address a focused hypothesis: pro-fibrotic SPP1+ macrophages that have been found in liver and lung tissue of idiopathic pulmonary fibrosis patients exist in other human tissues which can result in broader fibrotic disease states. The authors use existing, state-of-the-art single-cell analysis tools to perform the meta-analysis. They convincingly show that the SPP1+ macrophage population can be identified in lung, liver, heart, skin, uterus (endometrium), and kidney clusters derived from each tissues' scRNA-seq data. They further identify three subpopulations of the SPP1+ macrophages: a matrisome-associated macrophages (MAMs) defined as SPP1+MAM+ and two others enriched for inflammatory and ribosomal processes which they group together and define as SPP1+MAM-. Pathway analysis of genes unregulated in SPP1+MAM+ vs SPP1+MAM- cells yields significant enrichment of extracellular matrix remodeling and metabolism-related pathways and genes. This allows them to arrive at SPP1+MAM+ and SPP1+MAM- gene expression signature scores to further highlight the upregulation of these pathways in SPP1+MAM+ macrophages and their role in fibrosis. They explicitly show enrichment for SPP1+MAM+ macrophages in disease compared to healthy control subjects in a variety of tissues and their associated fibrosis-related diseases. Cell differentiation trajectory analysis identified 2 main trajectories: both starting from FCN1+ infiltrating monocytes/macrophages with one moving toward a homeostatic state and another toward SPP1+MAM+. They verified this using an alternative trajectory analysis approach. Importantly, for all tissues and fibrotic diseases, they found SPP1+MAM+ were at the end of the trajectory preceded by the SPP1+MAM- state, suggesting SPP1+MAM+ represents a common polarization state of SPP1+ macrophages. They develop a probability-based score that estimates the propensity of SPP1+MAM- macrophages to differentiate into SPP1+MAM+ and show that this was significantly higher in fibrotic disease subjects compared to healthy controls. They go on to identify the transcription factor networks (regulons) associated with SPP1+MAM+ differentiation and activation. They find a number of enriched regulons/transcription factors and through a linear-modeling trajectory analysis highlight the regulons that are associated specifically with the SPP1+MAM- to SPP1+MAM+ transition. In this way, they prioritize the NFATC1 and HIVEP3 regulations as driving the differentiation of SPP1+MAM- macrophages toward the SPP1+MAM+ polarization state. Finally, given that age is a risk factor for fibrotic disease, they assessed the association of SPP1+MAM+ and SPP1+MAM- gene signatures in healthy control old and young human subjects as well as old and young mice and found SPP1+MAM+ was either exclusively (human) or more significantly (mice) elevated in old versus young compared to SPP1+MAM-.

The strengths of this paper are the authors gathered a number of relevant single-cell RNA-seq data sets from fibrosis-focused studies to address a highly focused hypothesis (stated above). They gained the power to detect the population of SPP1+MAM+ cells by integrating these datasets. The analysis is carried out well using existing state-of-the-art tools. With whatever metric or single cell analysis-based discovery they make about the SPP1+MAM+ subpopulations (e.g., gene signatures, endpoint of trajectory analysis, associated regulons, etc), they compare the relevant scoring metrics in fibrosis and control subjects at every stage of the meta-analysis and find the SPP11+MAM+ is consistently higher across tissues and fibrosis-related diseases.

There are only minor weaknesses in this paper. One is that some of the most highly significant or simply significant results are not shown in main figures but are summarized in supplementary tables (e.g., MYC TARGETS V1 would have appeared as the most significant, highest enriched, and among the largest in terms of set size). Another is analysis criteria that may not yield the most biologically relevant or impactful conclusion (e.g., while the regulon THRA does not display a shift in slopes it shows the strongest, progressive increase going toward the SPP1+MAM+ state).

Reviewer #2 (Public Review):

In the past few years, single-cell transcriptomics analysis has uncovered cellular states associated with disease in experimental models and humans, revealing previously unrecognized disease-associated macrophage states. In particular, a macrophage state characterized by high expression of SPP1 (encoding osteopontin), and by a specific gene expression signature including the expression of TREM2, has been observed in various pathologies and given various names depending on the context e.g. TREM2hi macrophages, lipid-associated macrophages (LAM), disease-associated microglia (DAM), Scar-associated macrophages (SAM), etc... However, a focused investigation and comparison of SPP1+ macrophages across disease contexts were lacking. Here, the authors aimed to systematically analyze SPP1+ macrophages in the context of tissue fibrosis, and integrated single-cell RNA-seq data of >200,000 human macrophages in 6 organs in health and tissue fibrosis.

Beyond confirming the presence of SPP1+ macrophages with a conserved gene expression module (TREM2, CD9, GPNMB, etc...) across tissues and their association with fibrosis, the authors identified a previously unknown cell subset within SPP1+ macrophages, that was enriched for the expression of genes involved in remodeling of the extracellular matrix, which they termed SPP1+ matrisome-associated macrophages (SPP1+MAM+). The authors further used computational tools to compare these SPP1+MAM+ macrophages to previously described SPP1+ macrophage states (LAM, DAM, SAM), investigate the differentiation and activation trajectory of SPP1+MAM+ macrophages, and identify potential transcriptional regulators involved in their differentiation. Finally, the authors show that SPP1+MAM+ macrophages are associated with ageing in both humans and mice.

Overall, the conclusions of the authors are well supported by the data. The authors made excellent use of available computational tools, and the figures are clear and informative. The methods are well-described and appropriately used. In particular, the authors made a nice effort in explaining and justifying some key decisions in their scRNA-seq data analysis workflow, including a data-driven approach to decisions in the clustering analysis.

The author's findings are of broad interest to the fields of tissue inflammation, fibrosis, macrophage biology, and immunology, and their report constitutes a valuable resource, and a basis for further investigations of macrophage differentiation mechanisms in tissue fibrosis, and how macrophages could be targeted to alleviate pathological tissue fibrosis.

Reviewer #1 (Public Review):

The manuscript by Salloum and colleagues examines the role of statin-mediated regulation of mitochondrial cholesterol as a determinant of epigenetic programming via JMJD3 in macrophages.

Key strengths of the work include:

1. Mechanistic analysis of how statin treatments can remodel the mitochondrial membrane content via cholesterol depletion which in turn affects JMJD3 levels is a novel concept.

2. Use of RNA-seq and ATAC-seq data provides an avenue for unbiased analysis of the statin effects.

3. Use of methyl-cyclodextrin (MCD) alongside statins increases the robustness of the findings and the use of NFKB inhibitors suggests a mechanistic role for NFKB.

The conclusions are only partially supported by the presented data:

1. There is a lack of any in vivo studies that are required to demonstrate that the concentrations of statins used to induce epigenetic programming of macrophages are physiologically relevant. There have been numerous studies that have examined the anti-inflammatory effects of statins but there is significant debate and controversy regarding the in vivo relevance. Much of the in vivo effects of statins are achieved via changes in systemic cholesterol levels but the direct effects on macrophages are not clear.

2. "Statins" is used globally and it is unclear which statins were used, which doses of statins, and the treatment durations

3. The RNA-seq, ATAC-seq, and selected H3K27 ChIP only show a snapshot of the results without leveraging the power of unbiased analysis. Such an unbiased analysis could show whether the examined genes are indeed the most relevant targets of statins.

4. CCCP depletion can have broad toxic effects and it is difficult to interpret specific roles of ATP synthase from potentially toxic mitochondrial uncoupling.

Reviewer #2 (Public Review):

In this study, the authors pursue a line of inquiry related to the impacts of cholesterol depletion on macrophage gene expression. The authors find that depletion of cholesterol with either statins or methyl-cyclodextrin induces robust gene expression changes, including changes to JMJD3 expression, an epigenetic regulator.

The authors then seek to dissect the mechanistic determinants of the regulation of JMJD3 in macrophages converging on a metabolic regulation hypothesis that requires mitochondrial activity.

A strength of the paper is the use of multiple macrophage cell models and multiple tools for perturbation to improve the rigor of their conclusions. A weakness of the paper is that it relies heavily on chemical approaches without ever using genetic tools to confirm that their conclusions can be supported using an alternative approach, and when perturbing metabolic pathways as described here, it is difficult to understand how the entire cell state has changed. In fact, the unique focus on JMJD3 without utilizing a control set of genes to show that the impacts of these metabolic perturbations are specific to JMJD3 makes it hard to understand if this is a truly specific pathway for JMJD3 or a general cellular health change.

The authors make an interesting claim in the early part of their manuscript about the potential for statins to regulate the epigenome which they show; however, in the present presentation, it is unclear if this is related to the JMJD3 effect or a separate form of regulation.

This work has the potential to contribute to an improved understanding of the impact of statins on immune function.

Reviewer #3 (Public Review):

The manuscript by Salloum et al., titled "Statin-mediated reduction in mitochondrial cholesterol primes an anti-inflammatory response in macrophages by upregulating JMJD3" reports an extensive characterization of the mechanisms underlying the anti-inflammatory role of statins using different in vitro studies. Based on these approaches, the authors observed that cholesterol reduction in response to statin treatment alters mitochondrial function and they identify JMJD3 as a potential critical driver of macrophage anti-inflammatory phenotype. Overall, the study is interesting and provides new findings that could shed light on the molecular effects of statins in these cells, but a number of issues remain confusing, and the experimental design is, on some occasions, not rigorous enough to support the drawn conclusions.

Major issues:

1. Focus on JMJD3 is justified by the authors as it was among the 40 genes commonly up-regulated in macrophages exposed to statin or methyl--cyclodextrin (MCD) by RNA-Seq analysis. However, this analysis has not been presented in the manuscript and it is unclear what genes (apart from JMJD3) might play an important role in the response of these cells. A detailed characterization of both up- and down-regulated genes in these experimental conditions and a better justification for JMJD3 are required to fully support further analysis.<br /> 2. In the same line, Figures 6A and B fail to fully describe the changes found by ATAC-seq and RNA-seq. A more comprehensive analysis of these three datasets (together with previous RNA-seq studies) would help to obtain a better understanding of overlapping dysregulated genes (not only those found up-regulated) and what other epigenetic modifying factors might be involved.<br /> 3. In Figure 6C and Supplementary Figure 7, it would be noteworthy to also measure the gene expression of Kdm6a/UTX homolog Kdm6c/UTY, as it has been shown to lack demethylate H3K27me3 demethylase activity due to mutations in the catalytic site of the Jumomji-C-domain.<br /> 4. The use of rather unspecific treatments such as MG-132 (proteasome inhibitor) and GSKj4 (inhibitor of both JMJD3 and UTX) may distort the results observed and might elude their correct interpretation. To avoid this limitation, additional silencing and/or overexpression experiments are currently needed.<br /> 5. Figure 3 and Supplementary Figure 3 seem to be duplicated, please correct them. Moreover, for a better representation of these data, please include representative Seahorse profile figures of each experimental condition in these figures.<br /> 6. As stated by the authors, macrophage phenotype is much more complex than M1/M2 polarization. In this view, assessing a very limited set of genes (i.e, Il-1, IL-10, TNF, IL-6, IL-12, Arg1, Ym1, Mrc1) appears to be inappropriate. A meaningful number of markers must be added.<br /> 7. For accurate quantification of H3K27me3 global levels, please add immunoblotting against histone H3 in Supplementary Figure 1.

Reviewer #1 (Public Review):

In this manuscript, Drs. Miura, Mori, and colleagues, first present lineage tracing data using PDGFRa-CreERT2 and Foxa2-Cre drivers to show that PDGFRa+ cells, when lineage-labeled early in development go on to form the lung mesenchyme (but little to none of the epithelium), whereas FOXA2 expressing cells go on to contribute to both the lung epithelium and lung mesenchyme. However, it is already well known that FOXA2 is expressed in the mesendoderm around the time of gastrulation, and that this population generates both endoderm and mesodermal derivatives. As a result, it is not surprising that lineage labeling this population would contribute to both the lung epithelium and lung mesenchyme. The authors use the term bona fide lung (BFL) generative lineage. However, since the mesendoderm contributes to both the endoderm and mesoderm, but is by no means specific to the lung, and as shown in this paper (Figure 2G) the FOXA2 population only generates 30-40% of the mesenchyme, the term BFL is both confusing and misleading.

In the second portion of the manuscript, the authors conditionally delete Fgfr2 using a Foxa2-Cre driver. Although loss of Fgf10 or Fgfr2 is known to result in lung agenesis, deletion of Fgfr2 within the FOXA2+ expressing cells is novel. However, since FOXA2 is broadly expressed within the nascent lung epithelium and Fgfr2 is known to be expressed within the lung epithelium, it isn't entirely clear how much information this adds beyond what already known from other Fgfr2 knockout studies. Perhaps the most interesting aspect of the reported phenotype is that the other organs (e.g. intestine) in these knockout animals appears to be relatively spared. This should be better characterized by the authors, as currently only a few H&E images are shown.

The authors then used conditional blastocyst complementation with nGFP+iPSCs from wild-type mice to rescue the phenotype of the Fgfr2 conditional knockout mice, showing that an embryonic lung is formed. However, blastocyst complementation has previously been performed with other knockout mouse models with severe lung hypoplasia/aplasia, including Dr. Mori's previous Nature Medicine paper. Although most of the previous mouse models target the endoderm/early epithelial cells (e.g. conditional deletion of Ctnnb1, Fgfr2, or global knockout of Nkx2.1; see Li E, et al. Dev Dyn 2021 Jul;250(7):1001-1020; Wen B, Am J Resp Crit Care Med. 2020; in addition to Mori M, Nature Medicine, 2019), Kitahara A, et al (Cell Rep. May 12 2020;31(6):107626) previously reported blastocyst complementation in in Fgf10 null mouse model, so it is not clear what the current study significantly adds contributes to this existing body of literature. The lungs of the mice undergoing blastocyst complementation are also incompletely characterized in the current version of this study. For example, it is unclear how functional these lungs are and whether they are capable of gas exchange after birth.

Reviewer #2 (Public Review):

For most organs including lung produced by blastocyst complementation, certain cells including the blood vessels are still derived from host tissues, making them unfit for transplantation. To address this issue, Miura et al. explored the origin and the program of whole lung epithelium and mesenchyme, and identified the crucial Foxa2 lineage for lung organogenesis by using lineage tracing mice and human iPSC derived lung differentiation. They found that Foxa2 lineage cells contribute to both lung epithelium and mesenchyme formation, which suggest targeting Fox2 lineage cells could create an empty developmental niche for blastocyst complementation in mice. They further deplete Fgfr2 gene in Foxa2 lineage cells to induce the lung agenesis phenotype in mice, and donor mouse iPSCs injected into Fgfr2 mutant blastocysts occupied the empty niche and formed the missing lung.

Strengths:

To fill our knowledge gap of the origin of all lung cell types, especially pulmonary mesenchyme and endothelium, the authors investigated the lineage hierarchy of specified lung precursors in gastrulating mesendoderm. Using mouse lineage trancing and human iPSC derived lung differentiation, they clarified the msendoderm gene Expression pattern and progression, and compared the contributions of Pdgfra and Foxa2 lineage cells during lung development. They further demonstrate that the defective Foxa2 lineage in critically important for efficient lung complementation, which provide insight for next generation lung transplant therapies.

Weakness:

1. Several lineage tracing experiment lack rigorous quantification, the authors using "partially labels" or "labels a part of" in the text to describe their finding and conclusion, which make the evidence less solid.

2. The ideal lung for transplant should be functional for gas exchange, the lung complementation was only analyzed at E17.5 and E14.5, these two stages were too early to determine the function of the lungs generated via CBC.

3. Immune cells contribute large proportion in the lung, and are critical for lung transplant, the chimerism analysis of immune cells is missing in this study.

Reviewer #1 (Public Review):

In this manuscript, the authors examine the role of Sirt2 on cardiac hypertrophy by using 2 in-vivo models- systemic KO of Sirt2 and cardiac-specific KO of Sirt 2. The authors show that Sirt2 is important for the development of heart failure and cardiac hypertrophy. Mechanistically, the authors show that Sirt2 regulates NRF2 and that deletion of Sirt2 is protective through stabilization and increased nuclear translocation of NRF2. The paper is clinically relevant and the data is of high quality.

Reviewer #2 (Public Review):

In this study, Yang et al. have shown that SIRT2 plays an adverse effect on the heart in response to injury. Further, the groups showed that the deletion of Sirt2 is protective through stabilization and increased nuclear translocation of NRF2, which leads to increased expression of antioxidant genes. They also show that pharmacological inhibition of SIRT2 protects the heart against the development of cardiac hypertrophy. Although this is an interesting finding, at the same time, this study contradicts the previous findings where Xiaoqiang Tang et al. https://doi.org/10.1161/CIRCULATIONAHA.117.028728Circulation. 2017;136:2051-2067) have shown that SITR2 as a cardioprotective deacetylase and Sirt2 knockout is markedly exaggerated cardiac hypertrophy and fibrosis. Although Yang et al. in the discussion part have mentioned that this could be due to mice background. In my opinion, this is not satisfactory. It is important for the scientific community to come to a conclusion about the function of SIRT2 in the heart. The author could use the Global germ-line Sirt2-KO mice (C57BL/6J background; stock no. 012772) TAC model to show the function of SITR2 in cardiac hypertrophy.

The strength of this article is the mechanism where the author showed that SIRT2 function is through the increased NRF2 deacetylation and its degradation and eventual reduction in the levels of antioxidant genes.

Reviewer #1 (Public Review):

Sangar and co-workers have shown the role of Syntaxin 6 on prion (PrP) protein aggregation and have claimed a possible molecular mechanism behind its role in pathogenesis of Prion diseases like CJD. Authors have elaborately shown the aggregation kinetics of PrP in absence and presence of Stx6 by their in-house developed NAA assay which allowed them to catch the interaction of PrP with other cellular proteins like Stx6 or Hspa1a. By in vitro aggregation kinetics assays, authors show that Stx6 delays the aggregation kinetics of PrP and leads to amorphous aggregates rather than well-formed fibrils. By a neurite length detection assay with treatment of preformed PrP-fibrils (with or without Stx6 interaction), they show enhanced toxicity of Prp-Stx6 aggregates compared to PrP fibrils. However, there are a number of concerns related to physiological relevance that need to be addressed by the authors.

Reviewer #2 (Public Review):

The work reports a minor modification in the protocol for Prp formation in vitro. Using this the authors evaluate the role of Syntaxin 6 in modulating prion formation in vitro and the toxicity of the amyloid fibrils in cell culture models. The authors show that while prions/amyloids formed by PrP are non-toxic, mixed aggregates formed by Stx6/PrP are toxic; they claim that this is due to the toxic aggregation intermediates that accumulate more in the presence of Stx6. However, the basis of enhanced toxicity of Stx6/PrP mixed aggregates is not clear and doesn't seem to be physiologically relevant; there is no evidence that Stx6 and PrP forms mixed aggregates in vivo. Which is the toxic component of the Stx6/Prp co-aggregate? Is it the Stx6 component or the Prp component? Additionally, the authors do not have mechanistic explanation for the effect of Stx6 on PrP prion formation

Reviewer #3 (Public Review):

The autocatalytic replication mechanism of misfolded Prion-like proteins (PrP) into amyloid aggregates is associated with a plethora of deleterious neurodegenerative diseases. Despite of the huge amount of research, the underlying molecular events of self-replication and identification of the toxic species are not fully understood. Many recent studies have indicated that non-fibrillar oligomeric intermediates could be more neurotoxic compared to the Prion fibrils. Various cellular factors, like the participation of other proteins and chaperone activity, also play an important role in PrP misfolding, aggregation, and neurotoxicity. The present work focuses on understanding the PrP aggregation mechanism with the identification of the associated toxic species and cellular factors. One of the significant strengths of the work is performing the aggregation assay in near-native conditions. In contrast, most in vitro studies use harsh conditions (such as high temperature, denaturant, detergent, low pH, etc.) to promote protein aggregation. The authors successfully observed the well-known seeding property of the PrP in this aggregation assay that bypasses the primary nucleation during aggregation. Moreover, the authors have shown that syntaxin 6 (Stx6), a known risk factor in prion-mediated Creutzfeldt-Jakob disease, delays fibril formation and prolongs the persistence of toxic intermediates, thus playing an anti-chaperone activity. This study will contribute to understanding the molecular mechanism of PrP aggregation and neurotoxicity. However, further studies are required to identify and characterize the toxic intermediate in the near future precisely.

Reviewer #1 (Public Review):

In this manuscript, the authors compare the behavior of the intracellular ion channel TPC1 in two species of plants. TPC1 channels are cation permeable pseudo tetramers which in plants are expressed in the intracellular vacuole and whose function is not well understood.

It was previously known that calcium ions are modulators of the function of these channels and the authors identify a cluster of negative charges facing the lumen of the vacuole that can regulate the action of calcium and modulate the voltage dependence of the channels. Interestingly, this cluster is not entirely present in the faba bean (Vicia faba) vfTPC1 channel.

Through electrophysiological recordings of transfected channels into TPC1-lacking vacuoles, the authors show that the vfTPC1 channels activate at more negative voltages, even in the presence of high concentrations of calcium, leading to cation entrance into the vacuole and increased excitability, as assessed by action potential firing.

Though the findings are interesting and the methods are of high quality, the authors fail to convey the importance of the problem they are tackling and do not frame their findings in the broad physiology of the plant species they study.

These findings should be of interest to plant physiologists and channel biophysicists interested in TPC1 channels.

Reviewer #2 (Public Review):

This manuscript describes the structural differences between the prototypical TPC1 channel from Arabidopsis thaliana and its ortholog in Vicia faba that are responsible for divergent channel sensitivity to luminal Ca2+ and in turn make the Vf vacuoles hyperexcitable. It is speculated that these differences might be responsible for species-specific adaptation of these plant species to their environments. Luminal Ca2+ inhibits both of these TPCs (to a different extent) by slowing down the voltage activation and shifting the voltage dependence towards positive potentials. Previously, authors demonstrated that site 3 residues (E605, D606 and D607) in AtTPC1 sense inhibitory luminal Ca2+ that is allosterically coupled to the voltage sensor.

The main strength of the current manuscript is that authors cloned the VfTPC1 channel, and then using a combination of mutagenesis and electrophysiology to demonstrate that only two of the above three residues at site 3 (that are acidic in At but neutral in Vf) are primarily responsible for the luminal Ca2+-sensitivity differences observed between these two species (At and Vf). These modifications make Vf vacuoles hyperexcitable relative to At. The experimental data is robust, and the primary conclusions are mostly justified.

Although the results are fascinating, they are not entirely surprising based on the data presented in a previous publication from the same group. The exact significance of these findings with respect to species-specific plant physiology is not clear, yet this presents a promising and fertile ground for future research.

Reviewer #3 (Public Review):

In this manuscript by Lu et al., the authors cloned TPC1 from Vicia faba (VfTPC1) and characterized its channel properties by patching the vacuoles isolated from VfRPC1 expressing TPC1-loss-of-function Arabidopsis mutant tpc1-2. They found that VfTPC1 displayed faster kinetics, higher voltage dependence, and less sensitivity to luminal calcium than its Arabidopsis orthologue (AtTPC1). Mutating three luminal residues (E457, E605 and D606) in AtTPC1 to the corresponding ones in VfTPC1 converted the channel into one that resembles VfTPC1: hyperactive and desensitized to luminal Ca2+. By constructing a VfTPC1 model based on the published Ca2+-bound AtTPC1-D454N (fou2) cryo-EM structures, the authors proposed a Ca2+-dependent interaction between the E605/D606 motif and a Ca2+ coordination site at the luminal entrance of the selectivity filter (D269/E637; in VfTPC1, D271/E639). Finally, they showed that vacuoles with VfTPC1 or AtTPC1- triple mutant were hyperexcitable. Overall, this is an interesting study that might have both evolutional and functional implications.

Reviewer #2 (Public Review):

Summary:<br /> The authors sought to identify the impact skin viscoelasticity has on neural signalling of contact forces that are representative of those experienced during normal tactile behaviour. The evidence presented in the analyses indicates there is a clear effect of viscoelasticity on the imposed skin movements from a force-controlled stimulus. Both skin mechanics and evoked afferent firing were affected based on prior stimulation, which has not previously been thoroughly explored. This study outlines that viscoelastic effects have an important impact on encoding in the tactile system, which should be considered in the design and interpretation of future studies. Viscoelasticity was shown to affect the mechanical skin deflections and stresses/strains imposed by previous and current interaction force, and also the resultant neuronal signalling. The result of this was an impaired coding of contact forces based on previous stimulation. The authors may be able to strengthen their findings, by using the existing data to further explore the link between skin mechanics and neural signalling, giving a clearer picture than demonstrating shared variability. This is not a critical addition, but I believe would strengthen the work and make it more generally applicable.

Strengths:<br /> -Elegant design of the study. Direct measurements have been made from the tactile sensory neurons to give detailed information on touch encoding. Experiments have been well designed and the forces/displacements have been thoroughly controlled and measured to give accurate measurements of global skin mechanics during a set of controlled mechanical stimuli.<br /> -Analytical techniques used. Analysis of fundamental information coding and information representation in the sensory afferents reveals dynamic coding properties to develop putative models of the neural representation of force. This advanced analysis method has been applied to a large dataset to study neural encoding of force, the temporal dynamics of this, and the variability in this.

Weaknesses:<br /> -Lack of exploration of the variation in neural responses. Although there is a viscoelastic effect that produces variability in the stimulus effects based on prior stimulation, it is a shame that the variability in neural firing and force-induced skin displacements have been presented, and are similarly variable, but there has been no investigation of a link between the two. I believe with these data the authors can go beyond demonstrating shared variability. The force per se is clearly not faithfully represented in the neural signal, being masked by stimulation history, and it is of interest if the underlying resultant contact mechanics are.

Validity of conclusions:<br /> The authors have succeeded in demonstrating skin viscoelasticity has an impact on skin contact mechanics with a given force and that this impacts the resultant neural coding of force. Their study has been well-designed and the results support their conclusions. The importance and scope of the work is adequately outlined for readers to interpret the results and significance.

Impact:<br /> This study will have important implications for future studies performing tactile stimulation and evaluating tactile feedback during motor control tasks. In detailed studies of tactile function, it illustrates the necessity to measure skin contact dynamics to properly understand the effects of a force stimulus on the skin and mechanoreceptors.

Reviewer #1 (Public Review):

The authors investigate how the viscoelasticity of the fingertip skin can affect the firing of mechanoreceptive afferents and they find a clear effect of recent physical skin state (memory), which is different between afferents. The manuscript is extremely well-written and well-presented. It uses a large dataset of low threshold mechanoreceptive afferents in the fingertip, where it is particularly noteworthy that the SA-2s have been thoroughly analyzed and play an important role here. They point out in the introduction the importance of the non-linear dynamics of the event when an external stimulus contacts the skin, to the point at which this information is picked up by receptors. Although clearly correlated, these are different processes, and it has been very well-explained throughout. I have some comments and ideas that the authors could think about that could further improve their already very interesting paper. Overall, the authors have more than achieved their aims, where their results very much support the conclusions and provoke many further questions. This impact of the previous dynamics of the skin affecting the current state can be explored further in so many ways and may help us to better understand skin aging and the effects of anatomical changes of the skin.

At the beginning of the Results, it states that FA-2s were not considered as stimuli and did not contain mechanical events with frequency components high enough to reliably excite them. Was this really the case, did the authors test any of the FA-2s from the larger dataset? If FA-2s were not at all activated, this is also relevant information for the brain to signal that it is not a relevant Pacinian stimulus (as they respond to everything). Further, afferent receptive fields that were more distant to the stimulus were included, which likely fired very little, like the FA-2s, so why not consider them even if their contribution was low?

One question that I wondered throughout was whether you have looked at further past history in stimulation, i.e. not just the preceding stimulus, but 2 or 3 stimuli back? It would be interesting to know if there is any ongoing change that can be related back further. I do not think you would see anything as such here, but it would be interesting to test and/or explore in future work (e.g. especially with sticky, forceful, or sharp indentation touch). However, even here, it could be that certain directions gave more effects.

Did the authors analyze or take into account the difference between receptive field locations? For example, did afferents more on the sides have lower responses and a lesser effect of history?

Was there anything different in the firing patterns between the spontaneous and non-spontaneously active SA-2s? For example, did the non-spontaneous show more dynamic responses?

Were the spontaneously active SA-2 afferents firing all the time or did they have periods of rest - and did this relate to recent stimulation? Were the spontaneously active SA-2s located in a certain part of the finger (e.g. nail) or were they randomly spread throughout the fingertip? Any distribution differences could indicate a more complicated role in skin sensing.

Did the authors look to see if the spontaneous firing in SA-2s between trials could predict the extent to which the type 1 afferents encode the proceeding stimulus? Basically, does the SA-2 state relate to how the type 1 units fire?

In the discussion, it is stated that "the viscoelastic memory of the preceding loading would have modulated the pattern of strain changes in the fingertip differently depending on where their receptor organs are situated in the fingertip". Can the authors expand on this or make any predictions about the size of the memory effect and the distance from the point of stimulation?

In the discussion, it would be good if the authors could briefly comment more on the diversity of the mechanoreceptive afferent firing and why this may be useful to the system.

Also, the authors could briefly discuss why this memory (or recency) effect occurs - is it useful, does it serve a purpose, or it is just a by-product of our skin structure? There are examples of memory in the other senses where comparisons could be drawn. Is it like stimulus adaptation effects in the other senses (e.g. aftereffects of visual motion)?

One point that would be nice to add to the discussion is the implications of the work for skin sensing. What would you predict for the time constant of relaxation of fingertip skin, how long could these skin memory effects last? Two main points to address here may be how the hydration of the skin and anatomical skin changes related to aging affect the results. If the skin is less viscoelastic, what would be the implications for the firing of mechanoreceptors?

How long does it take for the effect to end? Again, this will likely depend on the skin's viscoelasticity. However, could the authors use it in a psychophysical paradigm to predict whether participants would be more or less sensitive to future stimuli? In this way, it would be possible to test whether the direction modifies touch perception.

The explicit x.type assignment here is redundant, because TypeTest will have already done it (in this case because the third argument is false).

Reviewer #1 (Public Review):

Guan et al. explored the mechanisms responsible for the development, maintenance, and functional properties of a specific subset of unconventional T cells expressing a Va3.2 T cell receptor that recognizes a peptide, QFL, presented by the class Ib protein Qa-1. Prior studies from this group showed that cells from mice deficient in the ER protease ERAAP elicit responses in wild-type animals enriched for Qa-1-restricted CD8 T cells. They further showed that a significant proportion of these responses were directed against the QFL peptide derived from a conserved protein with incompletely understood functions. Many of these so-called QFL T cells expressed Va3.2-Ja21, were present in the spleen of wild-type mice, and exhibited a memory-like phenotype. Due to their relatively low frequency and weak staining with Qa-1 tetramers, analyzing QFL T cells has been challenging. Therefore, the authors generated dextramers, which permitted them to more rigorously identify these cells. They confirmed some of their previous findings and further showed that Va3.2+ and Va3.2- QFL T cells were present in the intestinal epithelium, where they also express CD8alpha homodimers, a characteristic of most small intestinal intraepithelial lymphocytes (siIELs), and most similar to the so-called natural siIELs that acquire their innate functions in the thymus. The authors show that TAP but not Qa-1 or ERAAP expression are required for the development of these cells, and both Qa-1 and ERAAP are required for the natural siIEL phenotype. Some of these findings were confirmed using a new TCR transgenic mouse expressing the QFL TCR. They further show that retention but not homing of QFL T cells to the intestinal epithelium involves commensal microorganisms, and using in silico approaches, they identify a commensal that contains a peptide similar to QFL that can activate QFL T cells. Finally, they show that this organism, P. pentosaceus, can promote gut retention of QFL T cells when it is introduced into germ-free mice. From these findings, the authors conclude that the microbiota influences the maintenance of Qa-1-restricted T cells.

Comments:<br /> 1. Overall, the authors employ a number of new reagents and elegant approaches to explore the development, maintenance, and functional properties of QFL T cells.<br /> 2. Generally, conclusions made are well supported by the data presented.<br /> 3. One limitation of the work is that the immunological functions of QFL T cells remain unclear.<br /> 4. The work covers a lot of ground (intestinal IELs, unconventional T cells, innate/virtual memory T cells, Qa-1/HLA-E, etc) that may not be familiar to many readers.<br /> 5. A few questions remain:<br /> a) Regarding the results for TAP knockout animals, since Qa-1 does not appear to be required for QFL T cell development, the absence of these cells in TAP KO mice cannot be easily explained.<br /> b) The Va3.2 T cells display similarities with previously identified innate/virtual memory T cells, some of which require IL-4 production by CD1d-restricted NKT cells for their intrathymic development, which is not fully discussed.<br /> c) Qa-1/peptide complexes may also be recognized by CD94/NKG2 (both inhibitory and activating) receptors on NK cells and subsets of CD8 T cells, which may complicate data interpretation, but is not noted in the text.<br /> d) Are these conclusions relevant to the human homolog of Qa-1, HLA-E?

Reviewer #2 (Public Review):

Summary:<br /> CD8+ QFL T cells recognize a peptide, FYAEATPML (FL9), presented on Erap1-deficient cells. QFL T cells are present at a high frequency in the spleen of naïve mice. They express an antigen-experienced phenotype, and about 80% express an invariant TCRα chain Vα3.2Jα21.

Here, Guan and colleagues report that QFL T cells are present not only in the spleen but also in the intestinal epithelium, where they display several phenotypic and functional peculiarities. The establishment of spleen and gut Vα3.2+ QFL T cells is TAP-dependent, and their phenotype is regulated by the presence/absence of Qa-1b and Erap1. Maintenance of gut Vα3.2+ QFL T cells depends on the gut microbiota and is associated with colonization by Pediococcus pentosaceus.

Strengths:<br /> This article contains in-depth studies of a peculiar and interesting subset of unconventional CD8 T cells, based partly on generating two novel TCR-transgenic models.

The authors discovered a clear relation between the gut microbiome and the maintenance of gut QFL T cells. One notable observation is that monocolonization of the gut with Pediococcus pentosaceus is sufficient to sustain gut QFL T cells.

Weaknesses:<br /> In the absence of immunopeptidomic analyses, the presence or absence of the FL9 peptide on various cell types is inferred based on indirect evidence.

Analyses of the homology between the FL9 and bacterial peptides were limited to two amino acid residues (P4 and P6).

The potential function of QFL T cells remains elusive.

Reviewer #3 (Public Review):

The authors investigate the role of commensal microbes and molecules in the antigen presentation pathway in the development and phenotype of CD8 T cells specific for the Qa-1b-restricted peptide FL9 (QFL). The studies track both endogenous QFL-specific T cells and utilize a recently generated TCR transgenic model. The authors confirm that QFL-specific T cells in the spleen and small intestine intraepithelial lymphocyte (IEL) pool show an antigen-experienced phenotype as well as unique phenotypic and innate-like functional traits, especially among CD8+ T cells expressing Va3.2+ TCRs. They find that deficiency in the TAP transporter leads to almost complete loss of QFL-specific T cells but that loss of either Qa1 or the ERAAP aminopeptidase does not impact QFL+ T cell numbers but does cause them to maintain a more conventional, naïve-like phenotype. In germ-free (GF) mice, the QFL-specific T cells are present at similar numbers and with a similar phenotype to SPF animals, but in older animals (>18w) there is a notable loss of IEL QFL-specific cells. This drop can be avoided by neonatal colonization of GF mice with the commensal microbe Pediococcus pentosaceus but not a different commensal, Lactobacillus johnsonii, and the authors show that P. pentosaceus encodes a peptide that weakly stimulates QFL-specific T cells, while the homologous peptide from L. johnsonii does not stimulate such cells.

This study provides new insights into the way in which the differentiation, phenotype, and function of CD8+ T cells specific for Qa-1b/FL9 is regulated by peptide processing and Qa1 expression, and by interactions with the microbiota. The approaches are well designed, the data compelling, and the interpretation, for the most part, appropriate. There are a few relatively minor concerns.

1) For most of the report, the authors use a set of phenotypic traits to highlight the unique features of QFL-specific CD8+ T cells - specifically, CD44high, CD8aa+ve, CD8ab-ve. In Supp. Fig. 4, however, completely distinct phenotypic characteristics are presented, indicating that IEL QFL-specific T cells are CD5low, Thy-1low. No explanation is provided in the text about whether this is a previously reported phenotype, whether any elements of this phenotype are shared with splenic QFL T cells, what significance the authors ascribe to this phenotype (and to the fact that Qa1-deficiency leads to a more conventional Thy-1+ve, CD5+ve phenotype), and whether this altered phenotype is also seen in ERAAP-deficient mice. At least some explanation for this abrupt shift in focus and integration with prior published work is needed. On a related note, CD5 expression is measured in splenic QFL-specific CD8+ T cells from GF vs SPF mice (Supp. Fig. 9), to indicate that there is no phenotypic impact in the GF mice - but from Supp. Fig. 4, it would seem more appropriate to report CD5 expression in QFL-specific cells from the IEL, not the spleen.

2) The authors suggest the finding that QFL-specific cells from ERAAP-deficient mice have a more "conventional" phenotype indicates some form of negative selection of high-affinity clones (this result being somewhat unexpected since ERAAP loss was previously shown to increase the presentation of Qa-1b loaded with FL9, confirmed in this report). It is not clear how this argument aligns with the data presented, however, since the authors convincingly show no significant reduction in the number of QFL-specific cells in ERAAP-knockout mice (Fig. 3a), and their own data (e.g. Fig. 2a) do not suggest that CD44 expression correlates with QFL-multimer staining (as a surrogate for TCR affinity/avidity). Is there some experimental basis for suggesting that ERAAP-deficient lacks a subset of high-affinity QFL-specific cells?

3) The rationale for designing FL9 mutants, and for using these data to screen the proteomes of various commensal bacteria needs further explanation. The authors propose P4 and P6 of FL9 are likely to be "critical" but do not explain whether they predict these to be TCR or Qa-1b contact sites. Published data (e.g., PMID: 10974028) suggest that multiple residues contribute to Qa-1b binding, so while the authors find that P4A completely lost the ability to stimulate a QFL-specific hybridoma, it is unclear whether this is due to the loss of a TCR- or a Qa-1-contact site (or, possibly, both). This could easily be tested - e.g., by determining whether P4A can act as a competitive inhibitor for FL9-induced stimulation of BEko8Z (and, ideally, other Qa-1b-restricted cells, specific for distinct peptides). Without such information, it is unclear exactly what is being selected in the authors' screening strategy of commensal bacterial proteomes. This, of course, does not lessen the importance of finding the peptide from P. pentosaceus that can (albeit weakly) stimulate QFL-specific cells, and the finding that association with this microbe can sustain IEL QFL cells.

Reviewer #1 (Public Review):

By identifying a loss of function mutant of IQCH in an infertile patient, Ruan et al. show that IQCH is essential for spermiogenesis by generating a knockout mouse model of IQCH. Similar to infertile patients with a mutant of IQCH, IQCH knockout mice are characterized by a cracked flagellar axoneme and abnormal mitochondrial structure. Mechanistically, IQCH regulates the expression of RNA-binding proteins (especially HNRPAB), which are indispensable for spermatogenesis.

Although this manuscript contains a potentially interesting piece of work that delineates a mechanism of IQCH that associates with spermatogenesis, this reviewer feels that a number of issues require clarification and re-evaluation for a better understanding of the role of IQCH in spermatogenesis. With the shortage of logic and supporting data, causal relationships are still not clear among IQCH, CaM, and HNRPAB. The most serious point in this manuscript could be that the authors try to generalize their interpretations with a model that is too simplified from limited pieces of their data. The way the data and the logic are presented needs to be largely revised, and several interpretations should be supported by direct evidence.

Reviewer #2 (Public Review):

The manuscript "IQCH regulates spermatogenesis by interacting with CaM to promote RNA-binding proteins' expression" by Ruan et al. identified a homozygous variant affecting the splicing of IQCH in two infertile men from a Chinese family. The authors also generated an IQCH knockout mouse model to confirm the abnormal sperm phenotypes associated with IQCH deficiency. Further molecular biological assays supported the important role and mechanism of IQCH in spermatogenesis. This manuscript is informative for clinical and basic research on male infertility.

Reviewer #3 (Public Review):

In this study, Ruan et al. investigate the role of the IQCH gene in spermatogenesis, focusing on its interaction with calmodulin and its regulation of RNA-binding proteins. The authors examined sperm from a male infertility patient with an inherited IQCH mutation as well as IQCH CRISPR knockout mice. The authors found that both human and mouse sperm exhibited structural and morphogenetic defects in multiple structures, leading to reduced fertility in ICHQ-knockout male mice. Molecular analyses such as mass spectrometry and immunoprecipitation indicated that RNA-binding proteins are likely targets of IQCH, with the authors focusing on the RNA-binding protein HNRPAB as a critical regulator of testicular mRNAs. The authors used in vitro cell culture models to demonstrate an interaction between IQCH and calmodulin, in addition to showing that this interaction via the IQ motif of IQCH is required for IQCH's function in promoting HNRPAB expression. In sum, the authors concluded that IQCH promotes male fertility by binding to calmodulin and controlling HNRPAB expression to regulate the expression of essential mRNAs for spermatogenesis. These findings provide new insight into molecular mechanisms underlying spermatogenesis and how important factors for sperm morphogenesis and function are regulated.

The strengths of the study include the use of mouse and human samples, which demonstrate a likely relevance of the mouse model to humans; the use of multiple biochemical techniques to address the molecular mechanisms involved; the development of a new CRISPR mouse model; ample controls; and clearly displayed results. There are some minor weaknesses in that more background details could be provided to the reader regarding the proteins involved; some assays could benefit from more rigorous quantification; some of the mouse testis images and analyses could be improved; and larger sample sizes, especially for the male mouse breeding tests, could be increased. Overall, the claims made by the authors in this manuscript are well-supported by the data provided and there are only minor technical issues that could increase the robustness and rigor of the study.

1. More background details are needed regarding the proteins involved, in particular IQ proteins and calmodulin. The authors state that IQ proteins are not well-represented in the literature, but do not state how many IQ proteins are encoded in the genome. They also do not provide specifics regarding which calmodulins are involved, since there are at least 5 family members in mice and humans. This information could help provide more granular details about the mechanism to the reader and help place the findings in context.

2. The mouse fertility tests could be improved with more depth and rigor. There was no data regarding copulatory plug rate; data was unclear regarding how many WT females were used for the male breeding tests and how many litters were generated; the general methodology used for the breeding tests in the Methods section was not very explicitly or clearly described; the sample size of n=3 for the male breeding tests is rather small for that type of assay; and, given that ICHQ appears to be expressed in testicular interstitial cells (Fig. S10) and somewhat in other organs (Fig. S2), another important parameter of male fertility that should be addressed is reproductive hormone levels (e.g., LH, FSH, and testosterone).

3. The Western blots in Figure 6 should be rigorously quantified from multiple independent experiments so that there is stronger evidence supporting claims based on those assays.

4. Some of the mouse testis images could be improved. For example, the PNA and PLCz images in Figure S7 are difficult to interpret in that the tubules do not appear to be stage-matched, and since the authors claimed that testicular histology is unaffected in knockout testes, it should be feasible to stage-match control and knockout samples. Also, the anti-ICHQ and CaM immunofluorescence in Figure S10 would benefit from some cell-type-specific co-stains to more rigorously define their expression patterns, and they should also be stage-matched.

Reviewer #1 (Public Review):

Recent studies in plants and human cell lines argued for a central role of 1,5-InsP8 as the central nutrient messenger in eukaryotic cells, but previous studies concluded that this function is performed by 1-InsP7 in baker's yeast. Chabert et al now performed an elegant set of capillary electrophoresis coupled to mass spectrometry time course experiments to define the cellular concentrations of different inositol pyrophosphosphates (PP-InsPs) in wild-type yeast cells under normal and phosphate (Pi) starvation growth conditions. These experiments, in my opinion, form the center of the present study and clearly highlight that the levels of all major PP-InsPs drop under Pi starvation, with the 1,5-InsP8 isomer showing the most rapid changes.

The analysis of known mutants in the PP-InsP biosynthetic pathways furthermore demonstrate that loss-of-function of the PPIP5K enzymes Kcs1 and Vip1 result in a loss of 1,5-InsP8 and a hyperaccumulation of 5-InsP7, respectively. In line with this, loss-of-function of known PP-InsP phosphatases Ddp1 and Swi14 result in hyperaccumulation of either 1- or 5-InsP7, as anticipated from their in vitro substrate specificities. These experiments are of high technical quality and add to our understanding of the kinetics of PP-InsP metabolism/catabolism in yeast.

Next, the authors use changes in subcellular localisation of the central transcription factor Pho4 to assay at which time point after onset of Pi starvation the PHO pathway becomes activated. The early onset of the response, the behavior of the kcs1D mutant and of the ksc1D/vip1D all strongly argue for 1,5-InsP8 as the central nutrient messenger. I find this part of the manuscript well argued, nicely correlating PP-InsP levels, dynamics and the different mutant phenotypes.

The third part of the manuscript is a structure-function study of the CDK inhibitor Pho81, basically using a reverse genetics approach. This analysis demonstrates at the genetic level that the Pho81 SPX domain is required for activation of the PHO pathway. Next, the authors design point mutations that should block either interaction of Pho81-SPX with 1,5-InsP8 or interaction of Pho81 with the Pho80/Pho85 complex. In my opinion, these data can only provide limited insight into the molecular mechanism, as no complementary in vitro binding assays / in vivo co-IP experiments with the wild-type and mutant forms of Pho81 are presented. This seems to be due to technical limitations in recombinantly expressing and purifying the respective Pho81 protein for in vitro PP-InsP binding and protein - protein interaction assays.

Taken together, the work by Chabert et al, reinvestigates and clarifies the activation of the yeast PHO pathway by PP-InsP nutrient messengers and their cellular SPX receptors. From this work, a more unified eukaryotic mechanism emerges, in which 1,5-InsP8 represents the central signaling molecule in different species, with conserved SPX receptors sensing this signaling molecule.

Reviewer #2 (Public Review):

The manuscript by Chambert et al. describes a thorough and careful characterization of inositol pyrophosphate isomers and the PHO pathways in different genetic backgrounds in S. cerevisiae. The paper ultimately arrives at a proposed model in which the inositol pyrophosphate 1,5-IP8 signals phosphate abundance to SPX-domain containing proteins. To arrive at their conclusion, the authors rely heavily on CE-MS analysis of inositol pyrophosphates in different yeast strains, and monitoring inositol pyrophosphate depletion over time in response to phosphate starvation. This analysis is complemented by different reporter systems of PHO pathway activation, such as Pho4 translocation and Pho81 expression.

The experiments are well-designed and the results interpreted with care. With their findings, the authors demonstrate convincingly, that a previous study by O'Shea and co-workers (reference 15 and 16) had been misleading. Lee et al. claimed that the PHO pathway in S. cerevisiae is triggered by an increase in 1-IP7. This claim has been debated heavily in the community, and several groups were not able to reproduce this putative increase of inositol pyrophosphates (references 6, 11, 18). The confusion regarding these discrepancies has been resolved by the current study and is of significant importance to the community.

Reviewer #3 (Public Review):

Summary. This study sought to clarify the connection between inositol pyrophosphates (IPPs) and their regulation of phosphate homeostasis in the yeast Saccharomyces cerevisiae to answer the question of whether any of the IPPs (1-IP7, 5-IP7, and IP8) or only particular IPPs are involved in regulation. IPPs bind to SPX domains in proteins to affect their activity, and there are several key proteins in the PHO pathway that have an SPX domain, including Pho81. The authors use the latest methodology, capillary electrophoresis and mass spectrometry (CE-MS), to examine the cytosolic concentrations of PP-IPs in wild-type and strains carrying mutations in the enzymes that metabolize these compounds in rich medium and during a phosphate starvation time-course for the wild-type.

Major strengths and weaknesses. The authors have strong premises for performing these experiments: clarifying the regulatory molecule(s) in yeast and providing a unifying mechanism across eukaryotes. They use the latest methodologies and a variety of approaches including genetics, biochemistry, cell biology and protein structure to examine phosphate regulation. Their experiments are rigorous and well controlled, and the story is clearly told. The consideration of physiological levels of IPPs throughout the study was critical to interpretation of the data and a strength of the manuscript. The investigation of the structure of Pho81, its regulation by IPPs, and its interactions with Pho80 provide a vivid model for regulation.

Appraisal. The authors achieved their goal of determining the mechanistic details for phosphate regulation, revising the prior model with new insights. Additionally, they provided strong support for the idea that IP8 regulates phosphate metabolism across eukaryotes - including animals and plants in addition to fungi.

Impact. This study is likely to have broad impact because it addresses prior findings that are inconsistent with current understanding, and they provide good reasoning as to how older methods were inadequate.

Reviewer #1 (Public Review):

The authors of the manuscript cultivated a Planctomycetes strain affiliated with Phycisphaerae. The strain was one of the few Planctomycetes from deep-sea environments and demonstrated several unique characteristics, such as being the only known Phycisphaerae using a budding mode of division, extensive involvement in nitrate assimilation, and being able to release phage particles without cell death. The manuscript is generally well-written. However, a few issues need to be more clearly addressed, especially regarding the identification and characterization of the phage.

Reviewer #2 (Public Review):

Summary:

Planctomycetes encompass a group of bacteria with unique biological traits, the compartmentalized cells make them appear to be organisms in between prokaryotes and eukaryotes. However, only a few of the Planctomycetes bacteria are cultured thus far, and this hampers insight into the biological traits of these evolutionarily important organisms.

This work reports the methodology details of how to isolate the deep-sea bacteria that could be recalcitrant to laboratory cultivation, and further reveals the distinct characteristics of the new species of a deep-sea Planctomycetes bacterium, such as the chronic phage release without breaking the host and promote the host and related bacteria in nitrogen utilization. Therefore, the finding of this work is of importance in extending our knowledge of bacteria.

Strengths:

Through the combination of microscopic, physiological, genomics, and molecular biological approaches, this reports the isolation and comprehensive investigation of the first anaerobic representative of the deep-sea Planctomycetes bacterium, in particular in that of the budding division, and release phage without lysis of the cells. Most of the results and conclusions are supported by the experimental evidence.

Weaknesses:

1. While EMP glycolysis is predicted to be involved in energy conservation, no experimental evidence indicated any sugar utilization by the bacterium.<br /> 2. "anaerobic representative" is indicated in the Title, the contrary, TCA in energy metabolism is predicted by the bacterium.<br /> 3. The possible mechanisms of the chronic phage release without breaking the host are not discussed.

Reviewer #1 (Public Review):

This paper describes the development and initial validation of an approach-avoidance task and its relationship to anxiety. The task is a two-armed bandit where one choice is 'safer' - has no probability of punishment, delivered as an aversive sound, but also lower probability of reward - and the other choice involves a reward-punishment conflict. The authors fit a computational model of reinforcement learning to this task and found that self-reported state anxiety during the task was related to a greater likelihood of choosing the safe stimulus when the other (conflict) stimulus had a higher likelihood of punishment. Computationally, this was represented by a smaller value for the ratio of reward to punishment sensitivity in people with higher task-induced anxiety. They replicated this finding, but not another finding that this behavior was related to a measure of psychopathology (experiential avoidance), in a second sample. They also tested test-retest reliability in a sub-sample tested twice, one week apart and found that some aspects of task behavior had acceptable levels of reliability. The introduction makes a strong appeal to back-translation and computational validity. The task design is clever and most methods are solid - it is encouraging to see attempts to validate tasks as they are developed. The lack of replicated effects with psychopathology may mean that this task is better suited to assess state anxiety, or to serve as a foundation for additional task development.

Reviewer #2 (Public Review):

Summary:

The authors develop a computational approach-avoidance-conflict (AAC) task, designed to overcome the limitations of existing offer based AAC tasks. The task incorporated likelihoods of receiving rewards/ punishments that would be learned by the participants to ensure computational validity and estimated model parameters related to reward/punishment and task induced anxiety. Two independent samples of online participants were tested. In both samples participants who experienced greater task induced anxiety avoided choices associated with greater probability of punishment. Computational modelling revealed that this effect was explained by greater individual sensitivities to punishment relative to rewards.

Strengths:

Large internet-based samples, with discovery sample (n = 369), pre-registered replication sample (n = 629) and test-retest sub group (n = 57). Extensive compliance measures (e.g. audio checks) seek to improve adherence.

There is a great need for RL tasks that model threatening outcomes rather than simply loss of reward. The main model parameters show strong effects and the additional indices with task based anxiety are a useful extension. Associations were broadly replicated across samples. Fair to excellent reliability of model parameters is encouraging and badly needed for behavioral tasks of threat sensitivity.

The task seems to have lower approach bias than some other AAC tasks in the literature.

Weaknesses:

The negative reliability of punishment learning rate is concerning as this is an important outcome.

The Kendall's tau values underlying task induced anxiety and safety reference/ various indices are very weak (all < 0.1), as are the mediation effects (all beta < 0.01). The interaction with P(punishment|conflict) does explain some of this.

The inclusion of only one level of reward (and punishment) limits the ecological validity of the sensitivity indices.

Appraisal and impact:

Overall this is a very strong paper, describing a novel task that could help move the field of RL forward to take account of threat processing more fully. The large sample size with discovery, replication and test-retest gives confidence in the findings. The task has good ecological validity and associations with task-based anxiety and clinical self-report demonstrate clinical relevance. Test-retest of the punishment learning parameter is the only real concern. Overall this task provides an exciting new probe of reward/threat that could be used in mechanistic disease models.

Additional context:

The sex differences between the samples are interesting as effects of sex are commonly found in AAC tasks. It would be interesting to look at the main model comparison with sex included as a covariate.

Reviewer #3 (Public Review):

This study investigated cognitive mechanisms underlying approach-avoidance behavior using a novel reinforcement learning task and computational modelling. Participants could select a risky "conflict" option (latent, fluctuating probabilities of monetary reward and/or unpleasant sound [punishment]) or a safe option (separate, generally lower probability of reward). Overall, participant choices were skewed towards more rewarded options, but were also repelled by increasing probability of punishment. Individual patterns of behavior were well-captured by a reinforcement learning model that included parameters for reward and punishment sensitivity, and learning rates for reward and punishment. This is a nice replication of existing findings suggesting reward and punishment have opposing effects on behavior through dissociated sensitivity to reward versus punishment.

Interestingly, avoidance of the conflict option was predicted by self-reported task-induced anxiety. Importantly, when a subset of participants were retested over 1 week later, most behavioral tendencies and model parameters were recapitulated, suggesting the task may capture stable traits relevant to approach-avoidance decision-making.

The revised paper commendably adds important additional information and analyses to support these claims. The initial concern that not accounting for participant control over punisher intensity confounded interpretation of effects has been largely addressed in follow-up analyses and discussion.

This study complements and sits within a broad translational literature investigating interactions between reward/punishers and psychological processes in approach-avoidance decisions.

Reviewer #2 (Public Review):

The study is performed with old tool Spamo (12 year ago), source data from Encode (2010-2012), even peak caller tool version MACS is old ~ 2013. De novo motif search tool is old too (new one STREME is not mentioned). Any composite element search tool published for the recent 12 years are not cited, there are some issues in data analysis in presentation. Almost all references are from about 8-10 year ago (the most recent date is 2019)

The title is misleading<br /> Instead of<br /> A new pipeline SPICE identifies novel JUN-IKZF1 composite elements<br /> It should be written as<br /> Application of SpaMo tool identifies novel JUN-IKZF1 composite elements<br /> It reflects the pipeline better but honestly shows that the novelty is missed.

The study was performed on too old data from ENCODE, authors mentioned 343 Encode ChIP-Seq libraries, but authors even did not care even about to set for each library the name of target TF (Figure 1E, Figure S2, Table 2).

Reviewer #3 (Public Review):

The authors of this study have designed a novel screening pipeline to detect DNA motif spacing preferences between TF partners using publicly available data. They were able to recapitulate previously known composite elements, such as the AP-1/IRF4 composite elements (AICE) and predict many composite elements that are expected to be very useful to the community of researchers interested in dissecting the regulatory logic of mammalian enhancers and promoters. The authors then focus on a novel, SPICE predicted interaction between JUN and IKZF1, and show that under LPS and IL-21 treatment, JUN and IKZF1 in B cells have significant overlap in their genomic localization. Next, to know whether the two TFs physically interact, a co-immunoprecipitation experiment was performed. While JUN immunoprecipitated with an anti-IKZF1 antibody, curiously IKZF1 did not immunoprecipitate with an anti-JUN antibody. Finally, EMSA and luciferase experiments were performed to show that the two TFs bind cooperatively at an IL20 upstream probe.

Major strengths:<br /> 1. SPICE was able to recapitulate previously known composite elements, such as the AP-1/IRF4 composite elements (AICE).<br /> 2. Under LPS and IL-21 treatment, JUN and IKZF1 in B cells have significant overlap in their genomic localization. This is very good supporting evidence for the efficacy of SPICE in detecting TF partners.

Major weaknesses:<br /> 1. The authors fail to convincingly show that IKZF1 and Jun physically interact. A quantitative measurement of their interaction strength would have been ideal.<br /> 2. The super-shift experiment to show that the proteins bound to their EMSA probe were indeed IKZF1 and JUN are not very convincing and would benefit from efforts to quantify the shift (Figure 3E). Nuclear extracts from cells with single or double CRISPR knock outs of the two TFs would have been ideal.<br /> 3. There is a second band beneath the more prominent band in the EMSA experiment with recombinant IKZF1 and JUN (Figure 4C). This second band is most probably bound by IKZF1 because it becomes weaker when the IKZF1 site is mutated and is completely absent when only JUN is added. This is completely ignored by the authors. Therefore, experiments with EMSA fail to convincingly show that IKZF1 and Jun bind cooperatively. They could just as well bind independently to the two sites.

Reviewer #1 (Public Review):

The authors report a new bioinformatics pipeline ("SPICE") to predict pairwise cooperative binding-sites based on input ChIP-seq data for transcription factor (TF)-of-interest, analyzed against DNA-binding sites (DNA motifs) in a database (HOCOMOCO). The pipeline also predicts the optimal distance between the paired binding sites. The pipeline correctly predicted known/reported transcription factor cooperations, and also predicted new cooperations, not yet reported in literature. The authors choose to follow up on the predicted interaction between Ikaros and Jun. Using ChIP-seq in mouse B cells, they show extensive overlap in binding regions between Ikaros and Jun in LPS+IL21 stimulated cells. In a human B-lineage cell line (MINO) they show that anti-Ikaros Ab can co-immunoprecipitate Jun protein, and that the MINO cell extracts contain protein(s) that can bind to the CNS9 probe (conserved region upstream of IL10 gene), and that binding is lost upon mutation of two basepairs in the AP1 binding motif, and reduced upon mutation of two basepairs in the non-canonical Ikaros binding motif. Part of this protein complex is super-shifted with an anti-Jun antibody, and more DNA is shifted with addition of an anti-Ikaros antibody.

The authors perform EMSA showing that recombinant Jun can bind to the tested DNA-region (IL10 CNS9) and that addition of recombinant Ikaros (or anti-Ikaros antibody in Fig 3E) can enhance binding (increase amount of DNA shifted). The authors lastly show that the IL10 CNS9 DNA region can enhance transcription in B- and T-cells with a luciferase reporter assay, and that 2 bp mutation of the Ikaros or Jun DNA motifs greatly reduce or abolish this activity.

This is interesting work, with two main contributions: The SPICE pipeline (if made available to the scientific community), and the report of interaction between Ikaros and Jun. However, the distinction between DNA motifs, and the proteins actually binding and having a biological function, should be made clear consistently throughout the manuscript. The same DNA motifs can be bound by multiple factors, for instance within transcription factor families with highly homology in the DNA-binding regions of the proteins.

Some specific points:

SPICE: It is unclear if this is uploaded somewhere to be available to the scientific community.

It was unclear if Ikaros-Jun interaction was initially found from primary Jun ChIP-seq (and secondary Ikaros motif from HOCOMOCO) or from primary Ikaros CHIP-seq (and secondary Jun motif from HOCOMOCO). And - what were the two DNA motifs (primary and secondary, and their distance) from the SPICE analysis?

Authors have mostly careful considerations and statements. One additional comment is that binding does not equal function (Fig 2D), and that opening of chromatin (by any other factor(s)) can give DNA-binding factors (like Ikaros and Jun) the opportunity to bind, without functional consequence for the biological process studied.

Figure 2E: Ikaros is reported to be expressed at baseline in murine B cells, yet the Ikaros ChIP-seq in unstimulated cells had what looks to be no significant or low peaks. LPS stimulation induced strong Ikaros ChIP-seq signal. A western blot showing the Ikaros protein levels in the 3 conditions could help understand if the binding pattern is due to protein expression level induction. Similar for Jun (western in the 3 conditions), which seemed to mainly bind in the LPS+IL21 condition. Furthermore, as also suggested below, tracks showing Ikaros and Jun binding from all conditions (unstimulated, LPS only and LPS+IL21 stimulated cells), at select genomic loci, would be helpful in illustrating this difference in signal between the different cell conditions. This is relevant in regards to the point of cooperativity of binding.

ChIP-seq in mouse B cells showed that Ikaros bound strongly in LPS stimulated cells, in the (relative) absence of Jun binding (Fig. 2C). However, in EMSA (Fig 3C), there is no binding when the AP1 site is mutated, and the authors describe this as Ikaros binding site. What does the Ikaros binding look like at this genomic location in LPS (only) stimulated cells? The authors could show the same figure as in Fig 2F but show Ikaros and Jun ChIP-seq tracks at IL10 CNS9 locus from all conditions to compare binding in unstimulated, LPS and LPS+IL21 cells.

Also: How does this reconcile with the luciferase assay in Fig 4E, where LPS (only) stimulation is used, which in Fig 2E only/mainly induced Ikaros, and not Jun ChIP-seq signal (while EMSA indicate Ikaros cannot bind the site alone, but can enhance Jun-dependent binding).

Comment on statements in results section: The luciferase assays in B and T cells do not demonstrate the role of the proteins Ikaros or Jun directly (page 10, lines 208 and surrounding text). The assay measures an effect of the DNA sequences (implying binding of some transcription factor(s)), but does not identify which protein factors bind there.

Lastly, the authors only discuss Ikaros (using the term IKZF1 which is the gene symbol for the Ikaros protein). There are other Ikaros family members that have high homology and that are reported to bind similar DNA sequences (for instance Aiolos and Helios), which are expressed in B-cells and T-cells. A discussion of this is of relevance, as these are different proteins, although belonging to the same family (the Ikaros-family) of transcription factors. For instance, western for Aiolos and Helios will likely detect Aiolos in the B cells used, and Helios in the T cells used.

Reviewer #1 (Public Review):

This manuscript describes identification of influential organisms on rice growth and an attempt of validation. The analysis of eDNA on rice pot and mimic field provides rice growth promoting organisms. This approach is novel for plant ecology field. However current results did not fully support whether eDNA analysis-based detection of influencing organism.

The strength of this manuscript is to attempt application of eDNA analysis-based plant growth differentiation. The weakness is too preliminary data and experimental set-up to make any conclusion. The trials of authors experiments are ideal. However, the process of data analysis did not meet certain level. For example, eDNA analysis of different time points on rice growth stages resulted two influential organisms for rice growth. Then they cultivate two species and applied rice seedlings. Without understanding of fitness and robustness, how we can know the effect of the two species on rice growth.

The authors did not check the fate of two species after introducing into rice. If this is true, it is difficult to link between the rice gene expression after treatments and the effectiveness of two species. I think the validation experiment in 2019 needs to be re-conducted.

As authorized gave answered, no strong rationale to select the two species was found. However, I insist that the method has enough novelty to present to general audiences.

Reviewer #2 (Public Review):

Most farming is done by subtracting or adding what people want based in nature. However, in nature, crops interact with various objects, and mostly we are unaware of their effects. In order to increase agricultural productivity, finding useful objects is very important. However, in an uncontrolled environment, it coexists with so many biological objects that it is very inefficient to verify them all experimentally. It is therefore necessary to develop an effective screening method to identify external environmental factors that can increase crop productivity. This study identified factors presumed to be important to crop growth based on metabarcoding analysis, field sampling, and non-linear analysis/information theory, and conducted a mesocosm experiment to verify them experimentally. In conclusion, the object proposed by the author did not increase rice yield, but rather rice growth rate.

The authors responded to my general concerns and all of my specific comments. The manuscript has significantly improved. The flow of aims and approaches is more understandable. Extra supplementary material -especially the visual ones, is useful.

I agree with the other reviewers that the study needs more data and evidence. However, this study aims to introduce ecological concepts and advanced statistical methods to the field. Also, most time series analyses require absolute abundance data, but the manuscript provides solutions for the sequencing data.

Reviewer #1 (Public Review):

Previous experimental studies demonstrated that membrane association drives avidity for several potent broadly HIV-neutralizing antibodies and its loss dramatically reduces neutralization. In this study, the authors present a tour de force analysis of molecular dynamics (MD) simulations that demonstrate how several HIV-neutralizing membrane-proximal external region (MPER)-targeting antibodies associate with a model lipid bilayer.

First, the authors compared how three MPER antibodies, 4E10, PGZL1, and 10E8, associated with model membranes, constructed with a lipid composition similar to the native virion. They found that the related antibodies 4E10 and PGZL1 strongly associate with a phospholipid near heavy chain loop 1, consistent with prior crystallographic studies. They also discovered that a previously unappreciated framework region between loops 2-3 in the 4E10/PGZL1 heavy chain contributes to membrane association. Simulations of 10E8, an antibody from a different lineage, revealed several differences from published X-ray structures. Namely, a phosphatidylcholine binding site was offset and includes significant interaction with a nearby framework region.

Next, the authors simulate another MPER-targeting antibody, LN01, with a model HIV membrane either containing or missing an MPER antigen fragment within. Of note, LN01 inserts more deeply into the membrane when the MPER antigen is present, supporting an energy balance between the lowest energy conformations of LN01, MPER, and the complex. Additional contacts and conformational restraints imposed by ectodomain regions of the envelope glycoprotein, however, remain unaddressed-the size of such simulations likely runs into technical limitations including sampling and compute time.

The authors next established course-grained (CG) MD simulations of the various antibodies with model membranes to study membrane embedding. These simulations facilitated greater sampling of different initial antibody geometries relative to membrane. Distinct geometries derived from CG simulations were then used to initialize all-atom MD simulations to study insertion in finer detail (e.g., phospholipid association), which largely recapitulate their earlier results, albeit with more unbiased sampling. The multiscale model of an initial CG study with broad geometric sampling, followed by all-atom MD, provides a generalized framework for such simulations.

Finally, the authors construct velocity pulling simulations to estimate the energetics of antibody membrane embedding. Using the multiscale modelling workflow to achieve greater geometric sampling, they demonstrate that their model reliably predicts lower association energetics for known mutations in 4E10 that disrupt lipid binding. However, the model does have limitations: namely, its ability to predict more subtle changes along a lineage-intermediate mutations that reduce lipid binding are indistinguishable from mutations that completely ablate lipid association. Thus, while large/binary differences in lipid affinity might be predictable, the use of this method as a generative model are likely more limited.

The MD simulations conducted throughout are rigorous and the analysis are extensive. However, given the large amount of data presented within the manuscript, the text would benefit from clearer subsections that delineate discrete mechanistic discoveries, particularly for experimentalists interested in antibody discovery and design. One area the paper does not address involves the polyreactivity associated with membrane binding antibodies-MD simulations and/or pulling velocity experiments with model membranes of different compositions, with and without model antigens, would be needed. Finally, given the challenges in initializing these simulations and their limitations, the text regarding their generalized use for discovery, rather than mechanism, could be toned down.

Overall, these analyses provide an important mechanistic characterization of how broadly neutralizing antibodies associate with lipids proximal to membrane-associated epitopes to drive neutralization.

Reviewer #2 (Public Review):

In this study, Maillie et al. have carried out a set of multiscale molecular dynamics simulations to investigate the interactions between the viral membrane and four broadly neutralizing antibodies that target the membrane proximal exposed region (MPER) of the HIV-1 envelope trimer. The simulation recapitulated in several cases the binding sites of lipid head groups that were observed experimentally by X-ray crystallography, as well as some new binding sites. These binding sites were further validated using a structural bioinformatics approach. Finally, steered molecular dynamics was used to measure the binding strength between the membrane and variants of the 4E10 and PGZL1 antibodies.

The conclusions from the paper are mostly well supported by the simulations, however, they remain very descriptive and the key findings should be better described and validated. In particular:

It has been shown that the lipid composition of HIV membrane is rich in cholesterol [1], which accounts for almost 50% molar ratio. The authors use a very different composition and should therefore provide a reference. It has been shown for 4E10 that the change in lipid composition affects dynamics of the binding. The robustness of the results to changes of the lipid composition should also be reported.

The real advantage of the multiscale approach (coarse grained (CG) simulation followed by a back-mapped all atom simulation) remains unclear. In most cases, the binding mode in the CG simulations seem to be an artifact.

The results reported in this study should be better compared to available experimental data. For example how does the approach angle compare to cryo-EM structure of the bnAbs engaging with the MPER region, e.g. [2-3]? How do these results from this study compare to previous molecular dynamics studies, e.g.[4-5]?

References<br /> 1. Brügger, Britta, et al. "The HIV lipidome: a raft with an unusual composition." Proceedings of the National Academy of Sciences 103.8 (2006): 2641-2646.<br /> 2. Rantalainen, Kimmo, et al. "HIV-1 envelope and MPER antibody structures in lipid assemblies." Cell Reports 31.4 (2020).<br /> 3. Yang, Shuang, et al. "Dynamic HIV-1 spike motion creates vulnerability for its membrane-bound tripod to antibody attack." Nature Communications 13.1 (2022): 6393.<br /> 4. Carravilla, Pablo, et al. "The bilayer collective properties govern the interaction of an HIV-1 antibody with the viral membrane." Biophysical Journal 118.1 (2020): 44-56.<br /> 5. Pinto, Dora, et al. "Structural basis for broad HIV-1 neutralization by the MPER-specific human broadly neutralizing antibody LN01." Cell host & microbe 26.5 (2019): 623-637.

Reviewer #1 (Public Review):

The authors of the manuscript "High-resolution kinetics of herbivore-induced plant volatile transfer reveal tightly clocked responses in neighboring plants" assessed the effects of herbivory-induced maize volatiles on receiver plants over a period of time in order to assess the dynamics of the responses of receiver plants. Different volatile compound classes were measured over a period of time using PTR-ToF-MS and GC-MS, under both natural light:dark conditions, and continuous light. They also measured gene expression of related genes as well as defense-related phytohormones. The effects of a secondary exposure to GLVs on primed receiver plants were also measured.

The paper addresses some interesting points, however, some questions arise regarding some of the methods employed. Firstly, I am wondering why VOCs (as measured by GC-MS) were not quantified. While I understand that quantification is time-consuming and requires more work, it allows for comparisons to be made between lines of the same species, as well as across other literature on the subject. As experiments with VOC dispensers were also used in this experiment, I find it even more baffling that the authors didn't confirm the concentration of the emission from the plants they used to make sure they matched. The references cited justifying the concentration used (saying it was within the range of GLVs emitted by their plants) to prepare the dispenser were for either a different variety of maize (delprim versus B73) or arabidopsis. Simply relying on the area under the curve and presenting results using arbitrary units is not enough for analyses like these.

With regards to the correlation analyses shown in Figure 6, the results presented in many of the correlation plots are not actually informative. By blindly reporting the correlation coefficient important trends are being ignored, as there are clearly either bimodal relationships (e.g. upper left panel, HAC/TMTT, HAC/MNT) or even stranger relationships (e.g. upper left panel, IND/SQT, IND/MNT) that are not being well explained by a correlation plot. It is not appropriate to discuss the correlation factors presented here and to draw such strong conclusions on emission kinetics. The comparison between plants under continuous light and normal light:dark conditions is interesting, but I think there are better ways to examine these relationships, for example, multivariate analysis might reveal some patterns.

In Figure 2, the elevated concentrations of beta-caryophyllene found in the control plants at 8h and 16.75h measurement timepoints are curious. Is this something that is commonly seen in B73? While there can be discrepancies between emissions and compounds actually present within leaf tissue, it is a little bit odd that such high levels of b-caryophyllene were found at these timepoints, however, this is not reflected in the PTR-ToF-MS measurements of sesquiterpenes. It would be beneficial to include an overview of the mechanism of production and storage of sesquiterpenes in maize leaves, which would clarify why high amounts were found only in the GC-MS analysis and not the PTR-ToF-MS analysis, which is a more sensitive analytical tool. It is possible that the amounts of b-caryophyllene present in the leaf are actually extremely low, however as the values are not given as a concentration but rather arbitrary units, it is not possible to tell. I would include a line explaining what is seen with b-caryophyllene. Additionally, it seems like the amounts of TMTT within the leaf are extraordinarily high (judging only by the au values given for scale), far higher than one would expect from maize.

Reviewer #2 (Public Review):

The exact dynamics of responses to volatiles from herbivore-attacked neighbouring plants have been little studied so far. Also, we still lack evidence of whether herbivore-induced plant volatiles (HIPVs) induce or prime plant defences of neighbours. The authors investigated the volatile emission patterns of receiver plants that respond to the volatile emission of neighbouring sender plants which are fed upon by herbivorous caterpillars. They applied a very elegant approach (more rigorous than the current state-of-the-art) to monitor temporal response patterns of neighbouring plants to HIPVs by measuring volatile emissions of senders and receivers, senders only and receivers only. Different terpenoids were produced within 2 h of such exposure in receiver plants, but not during the dark phase. Once the light turned on again, large amounts of terpenoids were released from the receiver plants. This may indicate a delayed terpene burst, but terpenoids may also be induced by the sudden change in light. A potential caveat exists with respect to the exact timing and the day-night cycle. The timing may be critical, i.e. at which time-point after onset of light herbivores were placed on the plants and how long the terpene emission lasted before the light was turned off. If the rhythm or a potential internal clock matters, then this information should also be highly relevant. Moreover, light on/off is a rather arbitrary treatment that is practical for experiments in the laboratory but which is not a very realistic setting. Particularly with regard to terpene emission, the sudden turning on of light instead of a smooth and continuous change to lighter conditions may trigger emission responses that are not found in nature. As one contrasting control, the authors also studied the time-delay in volatile emission when plants were just kept under continuous light (just for the experiment or continuously?). Here they also found a delayed terpenoid production, but this seemed to be lower compared to the plants exposed to the day-night-cycle. Another helpful control would be to start the herbivory treatment in the evening hours and leave the light on. If then again plants only release volatiles after a 17 h delay, the response is indeed independent of the diurnal clock of the plant.

Interestingly, internal terpene pools of one of the leaves tested here remained more comparable between night and day, indicating that their pools stay higher in plants exposed to HIPVs. In contrast, terpene synthases were only induced during the light-phase, not in the dark-phase. Moreover, jasmonates were only significantly induced 22 h after the onset of the volatile exposure and thus parallel with the burst of terpene release.

An additional experiment exposing plants to the green leaf volatile (glv) (Z)-3-hexenyl acetate revealed that plants can be primed by this glv, leading to a stronger terpene burst. The results are discussed with nice logic and considering potential ecological consequences. Some data are not discussed, e.g. the jasmonate and gene induction pattern.

Overall, this study provides intriguing insights into the potential interplay between priming and induction, which may co-occur, enhancing (indirect and direct) plant defence. Follow-up studies are suggested that may provide additional evidence.

Reviewer #1 (Public Review):

In this paper, the authors show that disruption of calcineurin, which is encoded by tax-6 in C. elegans, results in increased susceptibility to P. aeruginosa, but extends lifespan. In exploring the mechanisms involved, the authors show that disruption of tax-6 decreases the rate of defecation leading to intestinal accumulation of bacteria and distension of the intestinal lumen. The authors further show that the lifespan extension is dependent on hlh-30, which may be involved in breaking down lipids following deficits in defecation, and nhr-8, whose levels are increased by deficits in defecation. The authors propose a model in which disruption of the defecation motor program is responsible for the effect of calcineurin on pathogen susceptibility and lifespan, but do not exclude the possibility that calcineurin affects these phenotypes independently of defecation.

Reviewer #2 (Public Review):

The manuscript titled "Calcineurin Inhibition Enhances Caenorhabditis elegans Lifespan by Defecation Defects-Mediated Calorie Restriction and Nuclear Hormone Signaling" by Priyanka Das, Alejandro Aballay, and Jogender Singh reveals that inhibiting calcineurin, a conserved protein phosphatase, in C. elegans affects the defecation motor program (DMP), leading to intestinal bloating and increased susceptibility to bacterial infection. This intestinal bloating mimics calorie restriction, ultimately resulting in an enhanced lifespan. The research identifies the involvement of HLH-30 and NHR-8 proteins in this lifespan enhancement, providing new insights into the role of calcineurin in C. elegans DMP and mechanisms for longevity.

The authors present novel findings on the role of calcineurin in regulating the defecation motor program in C. elegans and how its inhibition can lead to lifespan enhancement. The evidence provided is solid with multiple experiments supporting the main claims.

Strengths:<br /> The manuscript's strength lies in the authors' use of genetic and biochemical techniques to investigate the role of calcineurin in regulating the DMP, innate immunity, and lifespan in C. elegans. Moreover, the authors' findings provide a new mechanism for calcineurin inhibition-mediated longevity extension, which could have significant implications for understanding the molecular basis of aging and developing interventions to promote healthy aging.

1. The study uncovers a new role for calcineurin in the regulation of C. elegans DMP and a potential novel pathway for enhancing lifespan via calorie restriction involving calcineurin, HLH-30, and NHR-8 in C. elegans.<br /> 2. Multiple signaling pathways involved in lifespan enhancement were investigated with fairly strong experimental evidence supporting their claims.

Weaknesses:<br /> The manuscript's weaknesses include the lack of mechanistic details regarding how calcineurin inhibition leads to defects in the DMP and induces calorie restriction-like effects on lifespan.

The exact site of calcineurin action, i.e., whether in the intestine or enteric muscles (Lee et al., 2005), and the possible molecular mechanisms linking calcineurin inhibition, DMP defects, and lifespan were not adequately explored. Although characterization of the full mechanism is probably beyond the scope of this paper, given the relative simplicity and advantages of using C. elegans as a model organism for this study, some degree of rigor is expected with additional straightforward control experiments as listed below:

The authors state that tax-6 knockdown animals had drastically reduced expulsion events (Figure 2G), leading to irregular DMP (Lines 144-145), but did not describe the nature of DMP irregularity. For example, did the reduced expulsion events still occur with regular intervals but longer cycle lengths? Or was the rhythmicity completely abolished? The former would suggest the intestine clock is still intact, and the latter would indicate that calcineurin is required for the clock to function. Therefore, ethograms of DMP in both wild-type and tax-6 mutant animals are warranted to be included in the manuscript. Along the same line, besides the cycle length, the three separable motor steps (aBoc, pBoc, EMC) are easily measurable, with each step indicating where the program goes wrong, hence the site of action, which is precisely the beauty of studying C. elegans DMP. Unfortunately, the authors did not use this opportunity to characterize the exact behavior phenotypes of the tax-6 mutant to guide future investigations. Furthermore, it is interesting that about 64% of tax-6 (p675) animals had normal DMP. The authors attributed this to p675 being a weak allele. It would be informative to further examine tax-6 RNAi as in other experiments or to make a tax-6 null mutant with CRISPR. In addition, in one of the cited papers (Lee et al., 2005), the exact calcineurin loss-of-function strain tax-6(p675) was shown to have normal defecation, including normal EMC, while the gain-of-function mutant of calcineurin tax-6(jh107) had abnormal EMC steps. It wasn't clear from Lee et al., 2005, if the reported "normal defecation" was only referring to the expulsion step or also included the cycle length. Nevertheless, this potential contradiction and calcineurin gain-of-function mutant is highly relevant to the current study and should be further explored as a follow-up to previously reported results. For some of the key experiments, such as tax-6's effects on susceptibility to PA14, DMP, intestinal bloating, and lifespan, additional controls, as the norm of C. elegans studies, including second allele and rescue experiments, would strengthen the authors' claims and conclusions.

The second weakness of this manuscript is the data presentation for all survival rate curves. The authors stated that three independent experiments or biological replicates were performed for each group but only showed one "representative" curve for each plot. Without seeing all individual datasets or the averaged data with error bars, there is no way to evaluate the variability and consistency of the survival rate reported in this study.

Overall, the authors' claims and conclusions are justified by their data, but further experiments are needed to confirm their findings and establish the detailed mechanisms underlying the observed effects of calcineurin inhibition on the DMP, calorie restriction, and lifespan in C. elegans.

Reviewer #1 (Public Review):

In this study the authors first perform global knockout of the gene coding for the polarity protein Crumbs 3 (CRB3) in the mouse and show that this leads to perinatal lethality and anopthalmia. Next, they create a conditional knockout mouse specifically lacking CRB3 in mammary gland epithelial cells and show that this leads to ductal epithelial hyperplasia, impaired branching morphogenesis and tumorigenesis. To study the mechanism by which CRB3 affects mammary epithelial development and morphogenesis the authors turn to MCF10A cells and find that CRB3 shRNA-mediated knockdown in these cells impairs their ability to form properly polarized acini in 3D cultures. Furthermore, they find that MCF10A cells lacking CRB3 display reduced primary ciliation frequency compared to control cells, which is supported by rescue experiments and is in agreement with previous studies implicating CRB3 in primary cilia biogenesis. Using a combination of biochemical, molecular- and imaging approaches the authors then provide evidence indicating that CRB3 promotes ciliogenesis by mediating Rab11-dependent recruitment of gamma-tubulin ring complex (gamma-TuRC) component GCP6 to the centrosome/ciliary base, and they also show that CRB3 itself is localized to the base of primary cilia. Finally, to assess the functional consequences of CRB3 loss on ciliary signaling function, the authors analyze the effect of CRB3 loss on Hedgehog and Wnt signaling using cell-based assays or a mouse model.

Overall, the described findings are interesting and in agreement with previous studies showing an involvement of CRB3 in epithelial cell biology, tumorigenesis and ciliogenesis. The results showing a role for CRB3 in mammary epithelial development and morphogenesis in vivo seem convincing. Although the authors provide evidence that CRB3 promotes ciliogenesis via (indirect) physical association with Rab11 and gamma-TuRC, the precise mechanism by which CRB3 promotes ciliogenesis remains to be clarified.

Reviewer #1 (Public Review):

Summary:<br /> This manuscript provides some valuable findings concerning the hippocampal circuitry and the potential role of adult-born granule cells in an interesting long-term social memory retrieval. The behavior experiments and strategy employed to understand how adult-born granule cells contribute to long-term social discrimination memory are interesting.

I have a few concerns, however with the strength of the evidence presented for some of the experiments. The data presented and the method described is incomplete in describing the connection between cell types in CA2 and the projections from abGCs. Likewise, I worry about the interpretation of the data in Figures 1 and 2 given the employed methodology. I think that the interpretation should be broadened. This second concern does not impact the interest and significance of the findings.

Strengths:<br /> The behavior experiments are beautifully designed and executed. The experimental strategy is interesting.

Weaknesses:<br /> The interpretation of the results may not be justified given the methods and details provided.

Reviewer #2 (Public Review):

Summary:<br /> Laham et al. investigate how the projection from adult-born granule cells into CA2 affects the retrieval of social memories at various developmental points. They use chemogenetic manipulations and electrophysiological recordings to test how this projection affects hippocampal network properties during behavior. I find the study to be very interesting, the results are important for our understanding of how social memories of different natures (remote or immediate) are encoded and supported by the hippocampal circuitry. I have some points that I added below that I think could help clarify the conclusions:<br /> - My major concern with the manuscript was that making the transitions between the different experiments for each result section is not very smooth. Maybe they can discuss a bit in a summary conclusion sentence at the end of each result section why the next set of experiments is the most logical step.<br /> - In line 113, the authors say that "the DG is known to influence hippocampal theta-gamma coupling and SWRs". Another recent study Fernandez-Ruiz et al. 2021, examined how various gamma frequencies in the dentate gyrus modulate hippocampal dynamics.<br /> - Having no single cells in the electrophysiological recordings makes it difficult to interpret the ephys part. Perhaps having a discussion on this would help interpret the results. If more SWRs are produced from the CA2 region (perhaps aided by projections from abGC), more CA2 cells that respond to social stimuli (Oliva et al. 2020) would reactivate the memories, therefore making them consolidate faster/stronger. On the other hand, the projections from abGC that the authors see, also target a great deal of PV+ interneurons, which have been shown to pace the SWRs frequency (Stark et al 2014, Gan et al 2017), which further suggests that this projection could be involved in SWRs modulation.<br /> - The authors should cite and discuss Shuo et al., 2022 (A hypothalamic novelty signal modulates hippocampal memory).<br /> - I think the authors forgot to refer to Fig 3a-f, maybe around lines 163-168.<br /> - Are the SWRs counted only during interaction time or throughout the whole behavior session for each condition?<br /> - Figure 3t shows a shift in the preferred gamma phase within theta cycles as a result of abGC projections to CA2 ablation with CNO, especially during Mother CNO condition. I think this result is worth mentioning in the text.<br /> - Figure 3u in the legend mention "scale bars = 200um", what does this refer to?<br /> - What exactly is calculated as SWR average integral? Is it a cumulative rate? Please clarify.<br /> - Alexander et al 2017, "CA2 neuronal activity controls hippocampal oscillations and social behavior", examined some of the CA2 effects in the hippocampal network after CNO silencing, and the authors should cite it.

Strengths:<br /> Behavioral experiments after abGC projections to CA2 are compelling as they show clearly distinct behavioral readout.

Weaknesses:<br /> Electrophysiological experiments are difficult to interpret without additional quantifications (single-cell responses during interactions etc.)

Reviewer #3 (Public Review):

Laham et al. present a manuscript investigating the function of adult-born granule cells (abGCs) projecting to the CA2 region of the hippocampus during social memory. It should be noted that no function for the general DG to CA2 projection has been proposed yet. The authors use targeted ablation, chemogenetic silencing, and in vivo ephys to demonstrate that the abGCs to CA2 projection is necessary for the retrieval of remote social memories such as the memory of one's mother. They also use in vivo ephys to show that abGCs are necessary for differential CA2 network activity, including theta-gamma coupling and sharp wave-ripples, in response to novel versus familiar social stimuli.

The question investigated is important since the function of DG to CA2 projection remained elusive a decade after its discovery. Overall, the results are interesting but focused on the social memory of the mother, and their description in the manuscript and figures is too cursory. For example, raw interaction times must be shown before their difference. The assumption that mice exhibit social preference between familiar or novel individuals such as mother and non-mother based on social memory formation, consolidation, and retrieval should be better explained throughout the manuscript. Thus, when describing the results, the authors should comment on changes in preference and how this can be interpreted as a change in social memory retrieval. Several critical experimental details such as the total time of presentation to the mother and non-mother stimulus mice are also lacking in the manuscript. The in vivo e-phys results are interesting as well but even more succinct with no proposed mechanism as to how abGCs could regulate SWR and PAC in CA2.

The manuscript is well-written with the appropriate references. The choice of the behavioral test is somewhat debatable, however. It is surprising that the authors chose to use a direct presentation test (presentation of the mother and non-mother in alternation) instead of the classical 3-chamber test which is particularly appropriate to investigate social preference. Since the authors focused exclusively on this preference, the 3-chamber test would have been more adequate in my opinion. It would greatly strengthen the results if the authors could repeat a key experiment from their investigation using such a test. In addition, the authors only impaired the mother's memory. An additional experiment showing that disruption of the abGCs to CA2 circuit impairs social memory retrieval would allow us to generalize the findings to social memories in general. As the manuscript stands, the authors can only conclude the importance of this circuit for the memory of the mother. Developmental memory implies the memory of familiar kin as well.

The in vivo ephys section (Figure 3) is interesting but even more minimalistic and it is unclear how abGCs projection to CA2 can contribute to SWR and theta-gamma PAC. In Figure 1, the authors suggest that abGCs project preferentially to PV+ neurons in CA2. At a minimum, the authors should discuss how the abGCs to PV+ neurons to CA2 pyramidal neurons circuit can facilitate SWR and theta-gamma PAC.

Finally, proposing a function for 4-6-week-old abGCs projecting to CA2 begs two questions: What are abGCs doing once they mature further, and more generally, what is the function of the DG to CA2 projection? It would be interesting for the authors to comment on these questions in the discussion.

Reviewer #1 (Public Review):

The evolution of dioecy in angiosperms has significant implications for plant reproductive efficiency, adaptation, evolutionary potential, and resilience to environmental changes. Dioecy allows for the specialization and division of labor between male and female plants, where each sex can focus on specific aspects of reproduction and allocate resources accordingly. This division of labor creates an opportunity for sexual selection to act and can drive the evolution of sexual dimorphism.

In the present study, the authors investigate sex-biased gene expression patterns in juvenile and mature dioecious flowers to gain insights into the molecular basis of sexual dimorphism. They find that a large proportion of the plant transcriptome is differentially regulated between males and females with the number of sex-biased genes in floral buds being approximately 15 times higher than in mature flowers. The functional analysis of sex-biased genes reveals that chemical defense pathways against herbivores are up-regulated in the female buds along with genes involved in the acquisition of resources such as carbon for fruit and seed production, whereas male buds are enriched in genes related to signaling, inflorescence development and senescence of male flowers. Furthermore, the authors implement sophisticated maximum likelihood methods to understand the forces driving the evolution of sex-biased genes. They highlight the influence of positive and relaxed purifying selection on the evolution of male-biased genes, which show significantly higher rates of non-synonymous to synonymous substitutions than female or unbiased genes. This is the first report (to my knowledge) highlighting the occurrence of this pattern in plants. Overall, this study provides important insights into the genetic basis of sexual dimorphism and the evolution of reproductive genes in Cucurbitaceae.

There are, however, parts of the manuscript that are not clearly described or could be otherwise improved.

- The number of denovo-assembled unigenes seems large and I would like to know how it compares to the number of genes in other Cucurbitaceae species. The presence of alternatively assembled isoforms or assembly artifacts may be still high in the final assembly and inflate the numbers of identified sex-biased genes.

- It is interesting that the majority of sex-biased genes are present in the floral buds but not in the mature flowers. I think this pattern could be explored in more detail, by investigating the expression of male and female sex-biased genes throughout the flower development in the opposite sex. It is also not clear how the expression of the sex-biased genes found in the buds changes when buds and mature flowers are compared within each sex.

- The statistical analysis of evolutionary rates between male-biased, female-biased, and unbiased genes is performed on samples with very different numbers of observations, therefore, a permutation test seems more appropriate here.

- The impact of pleiotropy on the evolutionary rates of male-biased genes is speculative since only two tissue samples (buds and mature flowers) are used. More tissue types need to be included to draw any meaningful conclusions here.

Reviewer #2 (Public Review):

Summary:<br /> This study uses transcriptome sequence from a dioecious plant to compare evolutionary rates between genes with male- and female-biased expression and distinguish between relaxed selection and positive selection as causes for more rapid evolution. These questions have been explored in animals and algae, but few studies have investigated this in dioecious angiosperms, and none have so far identified faster rates of evolution in male-biased genes (though see Hough et al. 2014 https://doi.org/10.1073/pnas.1319227111).

Strengths:<br /> The methods are appropriate to the questions asked. Both the sample size and the depth of sequencing are sufficient, and the methods used to estimate evolutionary rates and the strength of selection are appropriate. The data presented are consistent with faster evolution of genes with male-biased expression, due to both positive and relaxed selection.

This is a useful contribution to understanding the effect of sex-biased expression in genetic evolution in plants. It demonstrates the range of variation in evolutionary rates and selective mechanisms, and provides further context to connect these patterns to potential explanatory factors in plant diversity such as the age of sex chromosomes and the developmental trajectories of male and female flowers.

Weaknesses:<br /> The presence of sex chromosomes is a potential confounding factor, since there are different evolutionary expectations for X-linked, Y-linked, and autosomal genes. Attempting to distinguish transcripts on the sex chromosomes from autosomal transcripts could provide additional insight into the relative contributions of positive and relaxed selection.

Reviewer #3 (Public Review):

The potential for sexual selection and the extent of sexual dimorphism in gene expression have been studied in great detail in animals, but hardly examined in plants so far. In this context, the study by Zhao, Zhou et al. al represents a welcome addition to the literature.

Relative to the previous studies in Angiosperms, the dataset is interesting in that it focuses on reproductive rather than somatic tissues (which makes sense to investigate sexual selection), and includes more than a single developmental stage (buds + mature flowers).

The main limitation of the study is the very low number of samples analyzed, with only three replicate individuals per sex (i.e. the whole study is built on six individuals only). This provides low power to detect differential expression. Along the same line, only three species were used to evaluate the rates of non-synonymous to synonymous substitutions, which also represents a very limited dataset, in particular when trying to fit parameter-rich models such as those implemented here.

A third limitation relates to the absence of a reference genome for the species, making the use of a de novo transcriptome assembly necessary, which is likely to lead to a large number of incorrectly assembled transcripts. Of course, the production of a reference transcriptome in this non-model species is already a useful resource, but this point should at least be acknowledged somewhere in the manuscript.

Each of these shortcomings is relatively important, and together they strongly limit the scope of the conclusions that can be made, and they should at least be acknowledged more prominently. The study is valuable in spite of these limitations and the topic remains grossly understudied, so I think the study will be of interest to researchers in the field, and hopefully inspire further, more comprehensive analyses.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript of Zhao et al. aimed at investigating the relationships between type 2 diabetes, bone mineral density (BMD) and fracture risk using Mendelian Randomization (MR) approach.<br /> The authors found that genetically predicted T2D was associated with higher BMD and lower risk of fracture, and suggested a mediated effect of RSPO3 level. Moreover, when stratified by the risk factors secondary to T2D, they observed that the effect of T2D on the risk of fracture decreased when the number of risk factors secondary to T2D decreased.

Strengths:<br /> - Important question<br /> - Manuscript is overall clear and well-written<br /> - MR analyses have been conducted properly, which include the usage of various MR methods and sensitivity analyses, and likely meet the criteria of the MR-strobe checklist to report MR results.

Weaknesses:<br /> - Previous MR studies on that topic have not been discussed<br /> - Multivariable MR could have been used to better assessed the mediative effect of BMI or RSPO3 on the relationships between T2D and fracture risk.

Reviewer #2 (Public Review):

The authors employed the Mendelian Randomization method to analyze the association between type 2 diabetes (T2D) and fracture using the UK Biobank data. They found that "genetically predicted T2D was associated with higher BMD and lower risk of fracture". Additionally, they identified 10 loci that were associated with both T2D and fracture risk, with the SNP rs4580892 showing the highest signal. While the negative relationship between T2D and fracture has been previously observed, the discovery of these 10 loci adds an intriguing dimension to the findings, although the clinical implications remain uncertain.

Reviewer #1 (Public Review):

In this manuscript, the authors investigate differences between Tibetans and Han Chinese at altitude in terms of placental transcriptomes during full-term pregnancy. Most importantly, they found that the inter-population differentiation is mostly male-specific and the observed direction of transcriptional differentiation seems to be adaptive at high altitude. In general, it is of great importance and provides new insights into the functional basis of Tibetan high-altitude adaptations, which so far have been mostly studied via population genetic measures only. More specifically, I firmly believe that we need more phenotype data (including molecular phenotypes such as gene expression data) to fully understand Tibetan adaptations to high altitude, and this manuscript is a rare example of such a study. I have a few suggestions and/or questions with which I hope to improve the manuscript further, especially in terms of 1) testing if the observed DEG patterns are truly adaptive, and 2) how and whether the findings in this study can be linked to EPAS1 and EGLN1, the signature adaptation genes in Tibetans.

Major Comments:

1. The DEG analysis is the most central result in this manuscript, but the discrepancy between sex-combined and sex-specific DEGs is quite mind-boggling. For those that were differentially expressed in the sex-specific sets but not in the sex-combined one, the authors suggest an opposite direction of DE as an explanation (page 11, Figure S5). But Figure S5A does not show such a trend, showing that down-regulated genes in males are mostly not at all differentially expressed in females. Figure S6B does show such a trend, but it doesn't seem to be a dominant explanation. I would like to recommend the authors test alternative ways of analysis to boost statistical power for DEG detection other than simply splitting data into males and females and performing analysis in each subset. For example, the authors may consider utilizing gene-by-environment interaction analysis schemes here biological sex as an environmental factor.

2. Please clarify how the authors handled multiple testing correction of p-values.

3. The "natural selection acts on the placental DEGs ..." section is potentially misleading readers to assume that the manuscript reports evidence for positive selection on the observed DEG pattern between Tibetans and Han, which is not.<br /> a) Currently the section simply describes an overlap between DEGs and a set of 192 genes likely under positive selection in Tibetans (TSNGs). The overlap is quite small, leading to only 13 genes in total (Figure 6). The authors are currently not providing any statistical measure of whether this overlap is significantly enriched or at the level expected for random sampling.<br /> b) The authors are describing sets of DEGs that seem to affect important phenotypic changes in a consistent and adaptive direction. A relevant form of natural selection for this situation may be polygenic adaptation while the authors only consider strong positive selection at a single variant/gene level.<br /> c) The manuscript is currently providing no eQTL information that can explain the differential expression of key genes. The authors can actually do this based on the genotype and expression data of the individuals in this study. Combining eQTL info, they can set up a test for polygenic adaptation (e.g. Berg and Coop; https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1004412). This will provide a powerful and direct test for the adaptiveness of the observed DEG pattern.

4. The manuscript is currently only minimally discussing how findings are linked to EPAS1 and EGLN1 genes, which show the hallmark signature of positive selection in Tibetans. In fact, the authors' group previously reported male-specific association between EPAS1 SNPs and blood hemoglobin level. Many readers will be intrigued to see a discussion about this point.

Reviewer #2 (Public Review):

In this manuscript, the authors use newly-generated, large-scale transcriptomic data along with histological data to attempt to dissect the mechanisms by which individuals with Tibetan ancestry are able to mitigate the negative effects of high elevation on birth weight. They present detailed analyses of the transcriptomic data and find significant sex differences in the placenta transcriptome.

I have significant concerns about the conclusions that are presented. The analyses also lack the information necessary to evaluate their reliability.

The experimental design does not include a low elevation comparison and thus cannot be used to answer questions about how ancestry influences hypoxia responses and thus birthweight at high elevations. Importantly, because the placenta tissues (and trophoblasts specifically) are quickly evolving, there are a priori good reasons to expect to find population differences irrespective of adaptive evolution that might contribute to fetal growth protection. There are also significant details missing in the analyses that are necessary to substantiate and replicate the analyses presented.

Although the datasets are ultimately valuable as reference sets, the absence of low elevation comparisons for Tibetans and Han Chinese individuals undermines the ability of the authors to assess whether differences observed between populations are linked to hypoxia responses or variation in the outcomes of interest (i.e., hypoxia-dependent fetal growth restriction).

The authors attempt to tackle this phenotypic association by looking for correlations between gene networks (WGCNA) and individual genes with birthweight and other measurements collected at birth. I have some reservations about this approach with only two groups (i.e., missing the lowland comparison), but it is further problematic that the authors do not present data demonstrating that there are differences in birthweight or any other traits between the populations in the samples they collected.

Throughout, I thus find conclusions about the adaptive value and hypoxia-responses made by the authors to be unsubstantiated and/or the data to be inadequate. There are also a gratuitous number of speculative statements about mechanisms by which differential gene expression leads to the protection of birthweight that are not evaluated and thus cannot be substantiated by the data presented.

As currently presented and discussed, these results thus can only be used to evaluate population differences and tissue-specific variation therein.

There is also some important methodological information missing that makes it difficult or impossible to assess the quality of the underlying data and/or reproduce the analyses, further limiting the potential impact of these data:<br /> 1. Transcriptome data processing and analyses: RNA quality information is not mentioned (i.e., RIN). What # of reads are mapped to annotated regions? How many genes were expressed in each tissue (important for contextualizing the # of DE genes reported - are these a significant proportion of expressed genes or just a small subset?).<br /> 2. The methods suggest that DE analyses were run using data that were normalized prior to reading them into DESeq2. DESeq2 has an internal normalization process and should not be used on data that was already normalized. Please clarify how and when normalization was performed.<br /> 3. For enrichment analyses, the background gene set (all expressed genes? all genes in the genome? or only genes expressed in the tissue of interest?) has deterministic effects on the outcomes. The background sets are not specified for any analyses.<br /> 4. In the WGCNA analysis, P-values for correlations of modules with phenotype data (birthweight etc.) should be corrected for multiple testing (i.e., running the module correlation for each outcome variables) and p.adjust used to evaluate associations to limit false positives given the large number of correlations being run.<br /> 6. The plots for umbilical histological data (Fig 5 C) contain more than 5 points, but the use of replicate sections is not specified. If replicate sections were used, the authors should control for non-independence of replicate sections in their analyses (i.e., random effects model).

On more minor notes:<br /> There is significant and relevant published data on sex differences and hypoxia in rodents (see Cuffe et al 2014, "Mid- to late-term hypoxia in the mouse alters placental morphology, glucocorticoid regulatory pathways, and nutrient transporters in a sex-specific manner" and review by Siragher and Sferuzzi-Perro 2021, "Placental hypoxia: What have we learnt from small animal models?"), and historical work reporting sex differences in placental traits associated with high elevation adaptation in Andeans (series of publications by Moira Jackson in the late 1980s, reviewed in Wilsterman and Cheviron 2021, "Fetal growth, high altitude, and evolutionary adaptation: A new perspective").

Reviewer #3 (Public Review):

More than 80 million people live at high altitude. This impacts health outcomes, including those related to pregnancy. Longer-lived populations at high altitudes, such as the Tibetan and Andean populations show partial protection against the negative health effects of high altitude. The paper by Yue sought to determine the mechanisms by which the placenta of Tibetans may have adapted to minimise the negative effect of high altitude on fetal growth outcomes. It compared placentas from pregnancies from Tibetans to those from the Han Chinese. It employed RNAseq profiling of different regions of the placenta and fetal membranes, with some follow-up of histological changes in umbilical cord structure and placental structure. The study also explored the contribution of fetal sex in these phenotypic outcomes.

A key strength of the study is the large sample sizes for the RNAseq analysis, the analysis of different parts of the placenta and fetal membranes, and the assessment of fetal sex differences.

A main weakness is that this study, and its conclusions, largely rely on transcriptomic changes informed by RNAseq. Changes in genes and pathways identified through bioinformatic analysis were not verified by alternate methods, such as by western blotting, which would add weight to the strength of the data and its interpretations. There is also a lack of description of patient characteristics, so the reader is unable to make their own judgments on how placental changes may link to pregnancy outcomes. Another weakness is that the histological analyses were performed on n=5 per group and were rudimentary in nature.

Reviewer #2 (Public Review):

In this manuscript, Xie and colleagues investigate the contribution of osteocytes to bone metastasis of non-small cell lung carcinoma (NSCLC) using a combination of clinical samples and in vitro and in vivo data. They find that metastatic NSCLC cells exhibit lower levels of the proliferation marker Ki-67 when located in areas adjacent to the bone surface in both NSCLC patients and an intraosseous animal model of NSCLC. Using in vitro approaches, they show that osteocyte-like cells inhibit the proliferation of NSCLC cells through the secretion of small extracellular vesicles (sEVs). They identify miR-99b-3p as a component of sEVs and demonstrate that miR-99b3p inhibits the proliferation of NSCLC cells by targeting the transcription factor MDM2. Interestingly, the data also shows that mechanical stimulation of osteocytes enhances the inhibitory effect of osteocytes on NSCLC cell proliferation via increasing sEVs release. By performing different in vivo studies, the authors show that tibial loading and moderate exercise (treadmill running), before and after tumor cell inoculation, suppress tumor progression in bone and protect bone mass. Intriguingly, the moderate exercise regime shows additive/synergistic effects with the co-administration of anti-resorptive therapy. These data add to the growing evidence pointing towards osteocytes as important cells of the tumor microenvironment capable of influencing the progression of tumors in bone.

The conclusions of the paper, however, are not well supported by the data, and some critical aspects of image analysis and data analysis need to be clarified and extended.

1) The histological images are analyzed in a qualitative manner, with no description of the methodology used. In bone metastases, cancer cells are frequently mixed with bone marrow cells. The lack of cell markers to identify NSCLC cells versus bone marrow cells makes the interpretation of the imaging data difficult. The authors rely on KI-67 as a marker of proliferation. Yet, it is intriguing that some osteocytes, non-proliferating cells by definition, are often positive for this marker, which questions the specificity of the staining. To make these results more solid, the authors should have provided the proper immunostaining controls to check for specificity and use additional markers of proliferation.

2) Adding control groups to fully assess the impact of the in vivo interventions (tibial loading, moderate exercise, anti-resorptive therapy) on bone mass would be needed. The authors should have used naive mice or analyzed the bones from the non-injected contralateral legs. Further, validating the in vivo work with other osteocyte-like cells or primary osteocytes would have strengthened the results.

3) The data on miRNA99b-3p on NSCLC in Supplementary Figure 3 is not convincing. The positive cells are difficult to see and most of the osteocyte lack nuclei. Better data, in humans and the mouse model, would have helped to confirm that osteocytes produce miRNA99b-3p.

4) The conclusions of the paper are not fully supported by the data provided. Osteocytes, as well as other bone cells, can respond to mechanical stimulation and thus could virtually be responsible for the protective effects of mechanical loading or moderate exercise. In vivo experiments demonstrating a direct role of osteocytes-produced miRNA99b-3p are needed to support the notion that osteocytes maintain tumor dormancy in NSCLC bone metastasis. Further, the authors solely rely on Ki-67 as a marker of dormancy. Completing this analysis with an assessment of a dormant gene expression signature or in vivo studies assessing tumor dormancy directly would be needed to confirm this notion.

Reviewer #1 (Public Review):

Xie and Colleagues propose here to investigate the mechanism by which exercise inhibits bone metastasis progression. The authors describe that osteocyte, sensing mechanical stimulation generated by exercise, inhibit NSCLC cell proliferation and sustain the dormancy thereof by releasing sEVs with tumor suppressor microRNAs. Furthermore, mechanical loading of the tibia inhibited the bone metastasis progression of NSCLC. Interestingly, exercise preconditioning effectively suppressed bone metastasis progression.

Reviewer #1 (Public Review):

In this manuscript, the authors explored the benefits of intermittent fasting on the cardiac physiology through a multi-omics approach and compared different fasting times (IF12; IF 16 and EOD) for a duration of 6 months. Combining the RNA-sequencing, proteomics and phosphor-proteomics analysis, the authors have made an interesting observation that different fasting times would lead to different changes that could be important for the cardiac physiology. Moreover, the changes observed at transcriptional level are different from protein level, suggesting a post-transcriptional regulation mechanism. Using western blot, the authors have confirmed the key signaling pathways, including AMPK, IRS pathway to be significantly altered upon intermittent fasting for 16hrs. Lastly, as a proof of concept for better cardiac function, the animals were challenged with dobutamine and echocardiography was performed to show the mice subjected to intermittent fasting have better cardiac systolic function.

The impact of intermittent fasting on cardiovascular health has been well characterized in several studies. This report appears to be the first one utilizing a multi-omics approach and provided an interesting dataset at transcriptome, proteome and phosphor-proteome levels, and would serve as a valuable data resource for the field. I have the following concerns:

Major concerns:

1) The rationale for choosing the intermittent fasting pattern and timing<br /> While the 16:8 intermittent fasting is relatively standard, what is the rationale to test IF 12 hours? As a 4 hour fasting difference might not cause dramatic changes in transcriptome and proteome. Also, what is the rationale to perform 6 months study? The dobutamine stress test is not a terminal procedure, have the authors examined the cardiac function prior to 6 months to see whether there is a difference?

2) Lack of validation study<br /> One interesting observation from this study is the changes of transcriptome does not reflect all the changes at protein level and there is a differential gene expression pattern in IF12, IF16 and EOD. If this is the case, the authors should select a few important targets and provide both mRNA and protein level analysis, as a proof of concept for the bioinformatics analysis accuracy.

3) Poor western blot image quality<br /> The quality of the western blot has several issues: a. the change of pAMPK/AMPK appears to be a decrease of total AMPK instead of change at p-AMPK level. Same with GSK3a/b. There appears to be an increase of total GSK3a/b. The AKT should also be blotted and quantified at phosphorylation level. The western blot should be clearly labeled, for the ones with double bands, including GSK3a/b, the author should clearly label which is GSK3a and which is GSK3b. For the IRS with non-specific band, the author should point out IRS-1 band itself.

Reviewer #2 (Public Review):

Summary:

This work presents a previously undescribed neuroanatomical and neurophysiological analog between mammals and songbirds. Juvenile zebra finches learn to sing by memorizing an adult song and then, through practice, converging to a close copy of the stored template. Previous work identified pathways emanating from the avian auditory cortical regions (AIV) and basal ganglia that, through ventral pallium (VP), and the subthalamic nucleus, innervate the finches' ventral tegmental area (VTA). As in mammals, the dopaminergic projections of the VTA onto the avian striatopallidal nucleus, area X, deliver a prediction error signal. This signal encodes a surprisingly better or worse performance of the ongoing song and therefore allows the birds to improve.

In mammals, lateral Habenula (LHb) neurons contribute to learning by signaling disappointing trial outcomes or aversive stimuli. Using viral tract tracing Roesner et al. identify projections from the zebra finch VP and AIV to the LHb as well as from the LHb to the VTA. The authors use functional mapping to show that the VP activates the LHb and that the LHb suppresses the Area X-projecting VTA neurons. Then, the authors show that lesioning the LHb in juvenile finches does not prevent them from copying their tutor's song but still leads to worse performance than controls due to the production of highly abnormal vocalizations, peppered in both lone and female-directed songs. In contrast, lesioning the LHb in adult finches has no effect on the song. Together, these findings suggest that the LHb may be part of a song evaluation system and may participate in learning by signaling vocalizations that deviate from the desired tutor template.

The LHb is an evolutionarily conserved structure that connects the forebrain and midbrain with the epithalamus in vertebrates. By identifying the LHb as a component in song learning, the authors lay the grounds for a trove of new research into the various emotional, biophysical, memory, and sensory processes that contribute to learning within and through the LHb. Most conclusions of this paper are well supported by data, but some conceptual and analytic aspects require framing with respect to methodological limitations.

Strengths:<br /> The use of both anatomical tracing and functional circuit mapping is a uniquely-powerful approach to addressing the main line of inquiry in this work. Specifically, collision testing and antidromic identification allow identifying LHb-->VTA and VTA-->X projecting neurons and therefore testing the response of these specific learning-related projections to stimulation in VP and LHb (respectively).

The evaluation of abnormal vocalizations using a variational autoencoder (VAE) is a particularly strong approach that is immune to observer biases. By training this artificial neural network model with sham or pre-lesion animals, the authors clearly distinguish abnormal syllables because of their significantly poorer reconstruction through the VAE. This approach allowed the authors to provide strong quantitative support to the effect of LHb lesion in juvenile finches on their adult song.

Weaknesses:<br /> The lesions in juveniles, as the authors discuss, were histologically examined at the end of the song development, months after their creation. The authors mention not being able to rule out damage to the medial part of the Hb. But the effect of the lesions could perhaps be mediated by damage to other brain regions, such as DLM, or passing fibers (when using electrolytic lesions).

Additionally, the effect on learning could also be mediated indirectly. In mammals, the outputs of the LHb target dopaminergic regions, serotonergic regions, and a cholinergic region. In birds, the LHb may also have a diverse impact on neuromodulators and therefore an impact on behavior states and on sleep. Disrupted behavior states may lead to poorer or less frequent practice and indirectly to abnormal results that do not stem from erroneous performance evaluation.

Reviewer #1 (Public Review):

Reinforcement mechanisms play a central role in learning structured behaviors, and recent studies in the songbird have shown that reinforcement learning is also integral to the imitation of the internally motivated singing behavior of songbirds. In this study, Roeser, Teoh et al. investigate the role of the lateral habenula in this process. The lateral habenula is thought to signal unexpected aversive outcomes, like reward omission, and inhibit dopaminergic neurons in the ventral tegmental area (VTA) via direct synaptic projections. Thus, the lateral habenula could logically play a key role in the trial-and-error learning of song by signaling worse performance outcomes (as evaluated by comparing to a memory of the tutor song) as birds practice copying their father's song.

The authors show that both the anatomical and functional connectivity of the lateral habenula in songbirds resembles what has been described in other vertebrates, including in afferent inputs from the ventral pallidum and efferent projections to the VTA that suppresses activity of putative dopaminergic neurons. Additionally, they show the lateral habenula circuits appear to be integrated with circuits known to be important for learning song, including receiving input from an auditory region, AIV, thought to be important in relaying song evaluation signals and providing inputs to VTA that overlap with neurons projecting to areas of the striatum essential for vocal learning (VTA-Area X neurons). They conclude that lesions of the lateral habenula early in song development do not disrupt a bird's ability to accurately imitate the song of their tutor but result in either the retention or development of unusual vocalizations that have qualities observed in the songs of zebra finches that have been experimentally raised without having access to a song tutor. The analysis of the adult song behavior is particularly compelling and provides novel approaches for identifying outlier vocalizations. Lastly, the authors show that birds will include these isolate-like syllables during courtship behaviors and that lesions of the lateral habenula do lead to disruptions in adult birds.

The conclusions stemming from the analysis of habenula connectivity require stronger support, and incomplete evidence is provided to link lesions of the lateral habenula to the observed disruptions in song learning.

This study has several strengths. First, the goal of understanding the role of the lateral habenula in natural learning of a complex behavior, like birdsong, is a valuable research avenue that can ultimately better link how natural learning of intrinsically rewarded behaviors may (or may not) harness similar learning mechanisms that have been well delineated in laboratory trained and externally reinforced behaviors. Second, the computational approaches brought to bear on the analysis of song, including variational autoencoders to help define the range of control song syllables from abnormal song syllables and anomaly scores, help provide a good framework for examining and conveying disruptions in behavior that might be associated with lesions of the lateral habenula. Lastly, the manuscript is well-written and clearly presented, and the authors do acknowledge some of the weaknesses mentioned below.

The major weakness of the article is that the authors do not verify the completeness (i.e., how much of the lateral habenula is lesioned in individual animals) or the extent (if neuronal regions adjacent to the lateral habenula neural are also lesioned) of their lesions. It is argued that this is not possible because of the timeframe (long survival times) of the experiments. However, there are standard ways of addressing this technical hurdle. One simple approach would be to first examine the correlation in the number of retrogradely labeled neurons in LHb, VP, and Area X following injections of tracer into VTA. For convergent anatomical pathways, there is typically a strong positive correlation across input circuits. Therefore, given the number of retrogradely labeled neurons in VP and Area X following VTA injections, one can make reasonable predictions for how many retrogradely labeled neurons would be expected in LHb. Using tracer injections at the end of the experiments and quantification of the retrograde labeling would allow the authors to reasonably estimate the completeness of their lesions.

This unfortunate problem with the design of the experiments significantly weakens any interpretations for the role of the lateral habenula in song learning. This is particularly important because the lateral habenula is a small area that has several adjacent brain structures that could also play significant roles in song development, most of which have not been well studied in this context. These include the medial habenula, the thalamic nuclei DMP and UVA, and forebrain axons from RA, as well as axons flowing into, out of, and interconnecting the structures previously mentioned. Additional tracer injections with different color tracers could be used to provide reasonable assurance that these other adjacent circuits are still intact at the end of each lesion experiment.

There are two weaknesses with the assessment of the functional connectivity of the lateral habenula. First, the anatomical tracing experiments are not particularly compelling. Very little data is shown and there is no quantification of any of the results. In the inset for retrograde labeling of VP-LHb and VP-VTA neurons, it is unclear that neurons of either population are shown in that image. Likewise, terminals from LHb in VTA are very sparse and it is not clear how well they overlap with VTA-X neurons which are intermingled with dopaminergic neurons projecting to other areas of the brain. The images shown seem out of focus and blurry. Although the electrophysiological experiments provide better assurance of these pathways, the sample sizes in these neurophysiology experiments seem preliminary. Stronger evidence in both regards would provide better assurance of LHb circuitry.

The interpretations and theoretical implications of these results are unclear. This is in part because it is not possible to fully tie behavioral outcomes specifically to lesions of the lateral habenula, but also because, albeit interesting, the behavioral results are somewhat confusing. The developmental lesions did not impact the ability of zebra finches to learn how to copy the song of their tutor over development, indicating, in a strict sense, this circuit is not needed for vocal imitation of a social model. However, birds clearly exhibit unusual song syllables that they throw into their song bouts, even when singing in courtship displays. What this may reflect is not addressed in this study. It could be that lesions disrupt a bird's ability to prune away poor syllables over development, and/or that lesions result in birds being unable to suppress unwanted vocal behaviors during performances. Analysis of song over development could provide insights into these possibilities and help provide a better understanding of what the lateral habenula contributes to the song-learning process.

Reviewer #1 (Public Review):

The manuscript focused on roles of a key fatty-acid synthesis enzyme, acetyl-coA-carboxylase 1 (ACC1), in the metabolism, gene regulation and homeostasis of invariant natural killer T (NKT_ cells and impact on these T cells' roles during asthma pathogenesis. The authors presented data showing that the acetyl-coA-carboxylase 1 enzyme regulates the expression of PPARg then the function of NKT cells including the secretion of Th2-type cytokines to impact on asthma pathogenesis. The results are clearcut and data were logically presented.

Reviewer #2 (Public Review):

In this study the authors sought to investigate how the metabolic state of iNKT cells impacts their potential pathological role in allergic asthma. The authors used two mouse models, OVA and HDM-induced asthma, and assessed genes in glycolysis, TCA, B-oxidation and FAS. They found that acetyl-coA-carboxylase 1 (ACC1) was highly expressed by lung iNKT cells and that ACC1 deficient mice failed to develop OVA-induced and HDM-induced asthma. Importantly, when they performed bone marrow chimera studies, when mice that lacked iNKT cells were given ACC1 deficient iNKT cells, the mice did not develop asthma, in contrast to mice given wildtype NKT cells. In addition, these observed effects were specific to NKT cells, not classic CD4 T cells. Mechanistically, iNKT cell that lack AAC1 had decreased expression of fatty acid-binding proteins (FABPs) and peroxisome proliferator-activated receptor (PPAR)γ, but increased glycolytic capacity and increased cell death. Moreover, the authors were able to reverse the phenotype with the addition of a PPARg agonist. When the authors examined iNKT cells in patient samples, they observed higher levels of ACC1 and PPARG levels, compared to healthy donors and non-allergic-asthma patients.

Reviewer #1 (Public Review):

Summary: A well-executed series of experiments that will likely be of immense interest to (a) vector-borne disease researchers and (b) gram-negative sepsis/bacteremia researchers. The study uses comparative transcriptomics to begin probing what makes Peromyscus leucopus a unique host for numerous pathogens. Most issues with the paper are trivial, relating to descriptions of statistical cutoffs. While the paper does not provide mechanistic insight into how P. leucopus restrains its immune response to LPS or other microbial invaders, it is likely that this paper will be frequently consulted by researchers trying to understand that phenomenon.

Strengths:

o Use of outbred M. musculus is a commendable choice for the studies here.<br /> o Excellent decision by the authors to use their published dataset (with appropriate statistical normalization) to improve their statistical power to examine sex-biased gene expression. Is it possible to go one step further and briefly incorporate their prior BALB/c data to see how the BALB/c compare to the outbred mice. This could perhaps be just a PCA plot to see if they cluster with the outbred mice and/or Peromyscus, or are separate.<br /> o The correlations and ratios used to try to understand immune cell dynamics are clever and likely reflect interesting biology, but caution should be used when interpreting these indirect measures. As there are no tools for cell separation in P. leucopus, the authors should continue to include these data to stimulate ideas in the field, but readers should understand the "conclusions" are hypotheses due to the nature of the bulk RNAseq.

Weaknesses:

o Supplemental Table 1 only lists genes that passed the authors statistical thresholds. The full list of genes detected in their analysis should be included with read counts, statistics, etc. as supplemental information<br /> o While P. leucopus is a critical reservoir for B. burgdorferi, caution should be taken in directly connecting the data presented here and the Lyme disease spirochete. While it's possible that P. leucopus have a universal mechanism for limiting inflammation in response to PAMPs, B. burgdorferi lack LPS and so it is also possible the mechanisms that enable LPS tolerance and B. burgdorferi tolerance may be highly divergent.<br /> o Statistical significance is binary and p-values should not be used as the primary comparator of groups (e.g. once a p-value crosses the deigned threshold for significance, the magnitude of that p-value no longer provides biological information). For instance, in comparing GO-terms, the reason for using of high p-value cutoffs ("None of these were up-regulated gene GO terms with p values < 1011 for M. musculus.") to compare species is unclear. If the authors wish to compare effect sizes, comparing enrichment between terms that pass a cutoff would likely be the better choice. Similarly, comparing DEG expression by p-value cutoff and effect size is more meaningful than analyses based on exclusively on p-value: "Of the top 100 DEGs for each species by ascending FDR p value." Description in later figures (e.g. Figure 4) is favored.<br /> o The ability to use of CD45 to normalize data is unclear. Authors should elaborate both on the use of the method and provide some data how the data change when they are normalized. For instance, do correlations between untreated Mus and Peromyscus gene expression improve? The authors seem to imply this should be a standard for interspecies comparison and so it would be helpful to either provide data to support that or, if applicable, use of the technique in literature should be referenced.<br /> o Regarding the ISG data-is a possible conclusion not that Peromyscus don't upregulate the antiviral response because it's already so high in untreated rodents? It seems untreated Peromyscus have ISG expression roughly equivalent to the LPS mice for some of the genes. This could be compared more clearly if genes were displayed as bar plots/box and whisker plots rather than in scatter plots. It is unclear why the linear regression is the key point here rather than normalized differences in expression.<br /> o Some sections of the discussion are under supported:<br />  The claim that low inflammation contributes to increased lifespan is stated both in the introduction and discussion. Is there justification to support this? Do aged pathogen-free mice show more inflammation than aged Peromyscus?<br />  The claim that reduced Peromyscus responsiveness could lead to increased susceptibility to infection is prominently proposed but not supported by any of the literature cited.<br />  References to B. burgdorferi, which do not have LPS, in the discussion need to ensure that the reader understands this and the potential that responses could be very different.

Reviewer #2 (Public Review):

Milovic, Duong, and Barbour investigate the inflammatory response of three species of small mammals (P. leucopus, M. musculus, and R. norvegicus) to endotoxin lipopolysaccharide (LPS) injection via genome-wide transcriptomics from blood samples. Understanding the inflammation response of P. leucopus is of importance as they are a reservoir for several pathogens. The study is a thorough, controlled, well researched analysis that will be valuable for designing and interpreting future studies. The authors discuss the limitations of the data and the potential directions. Clearly P. leucopus respond differently to the LPS exposure which is very interesting and opens the door for numerous other comparative studies.

The conclusions of the manuscript are thoughtful and mostly supported by the data, but there are a couple of points for clarification.

1) How were the number of animals for each experiment selected? Was a power analysis conducted?

2) The authors conducted a cursory evaluation of sex differences of P. leucopus and reported no difference in response except for Il6 and Il10 expression being higher in the males than the females in the exposed group. The data was not presented in the manuscript. Nor was sex considered for the other two species. A further discussion of the role that sex could play and future studies would be appreciated.

3) The ratio of Nos2 and Arg1 copies for LPS treated and control P. leucopus and M.musculus in Table 3 show that in P. leucopus there is not a significant difference but in M.musculus there is an increase in Nos2 copies with LPS treatment. The authors then used a targeted RNA-seq analysis to show that in P. leucopus the number of Arg1 reads after LPS treatment is significantly higher than the controls. These results are over oversimplified in the text as an inverse relationship for Nos2/Arg1 in the two species.

Reviewer #1 (Public Review):

The article by Reversade and colleagues reports new mutations in the PYCR1 in a progeroid disease associated with premature skin aging. Using human cell culture and a newly generated mouse model of PYCR1deficiency they identify a role for this factor in maintaining dermal homeostasis and ECM production. I have some minor concerns about the role of PYCR1 in fibroblast survival vs function and the quantification of western blots.

Reviewer #2 (Public Review):

Summary:<br /> Sotiropoulou et al. present an interesting study of an incredibly rare premature aging disease (De Barsy syndrome), examining both the underlying mechanisms at play behind the condition as well as how that biology may have a larger role in understanding features of normal aging, and in particular, human skin aging. The authors link one of the underlying genetic defects in De Barsy syndrome (PYCR1 mutations) to its phenotypic manifestations and then extrapolate those findings to present more preliminary data to suggest that a loss of PYCR1 may be a biomarker of normal human skin aging.

Strengths:<br /> - The study is important as De Barsy syndrome is challenging to study given its rarity, thus making it an understudied condition. Here the authors combine both human patient samples and murine models to offer a nice contribution to further understanding the pathophysiology of this disease.

- The authors are able to link some of the observed features in De Barsy syndrome preliminarily to more common aging models and processes (senescence, human skin dermal aging). They nicely show that the loss of Pycr1 in mice can provoke thinning of the dermis of mice while not affecting the epidermis. Furthermore, they present compelling data to suggest that Pycr2 may be compensating in mice (while not in humans) and this may contribute to the differences in lifespan observed between the mice and humans.

- Should these results be further verified, this could suggest that further study of Pycr1 and Pycr2 biology may offer new insights into aging and senescence in other tissues.

Weaknesses:<br /> - Some of the data appears preliminary and seems like it needs further analysis as described further below in my suggestions for the authors:

1) While the authors report that there is no difference in the lifespan of the Pycr1-KO mice, can they report whether there was overall weight loss or any size differences between the mice? This is helpful particularly when comparing the dermal thickness as well as considering how the global loss of Pycr1 may affect overall systemic health.

2) In Figure S2E, the comparison "pairs" seems somewhat arbitrarily chosen and it seems from the quantifications of these pairs that depending upon which young sample you compare to which old sample, you may end up with differing results. I think the more appropriate way to make this quantitative comparison would be to average the young samples and average the old samples and then compare them and perform statistics. This seems critical to really assess whether PYCR1 loss would be a consistent marker of human skin dermal aging. Additionally, it would be helpful to also look at Pycr2 expression in the normal young versus old dermis to see if the reported difference in Pycr1 is really something specific for Pycr1 and not something more general.

3) Are the labels mixed up in Figures 1J and 1K or am I reading it incorrectly? From what I can see the graph is showing that the dermal thickness and collagen intensity is higher in the Pycr1-/- mice. Similarly, the authors state that there is "significantly less collagen fiber staining", although in Figure S1G neither the quantification of collagen I or collagen III are shown to be significant. These discrepancies need to be discussed or corrected.

4) Can the authors speculate further on why Pycr2 is also diminished in human patients (while it clearly remains present in the mice).

5) Can the authors comment on whether other canonical senescence features are seen in De Barsy syndrome (p16 positivity, senescence associated secretory phenotype, etc.)? Along these lines, there is an abundance of publicly available RNA-seq datasets from various forms of senescent cells. It would be interesting to examine these and see whether there is any loss of expression of PYCR1 or PYCR2 in these data, or is the loss of PYCR1 only seen at the protein level?

Reviewer #1 (Public Review):

Summary:

In this excellent manuscript by Egan et al., the authors very carefully dissect the roles of inflammasome components in restricting Salmonella Typhimurium (STm) replication in human macrophages. They show that caspase-1 is essential to mediating inflammasome responses and that caspase-4 contributes to bacterial restriction at later time points. The authors show very clear roles for the host proteins that mediate terminal lysis, gasdermin D and ninjurin-1. The unique finding in this study is that in the absence of inflammasome responses, Salmonella hypereplicates within the cytosol of macrophages. These findings suggest that caspase-1 and possibly caspase-4 play roles in restricting the replication of Salmonella in the cytosol as well as in the Salmonella containing vacuole.

Strengths:

1) The genetic and biochemical approaches have shown for the first time in human macrophages that the caspase-1-GSDMD-NINJ1 axis is very important for restricting intracellular STm replication. In addition, they demonstrate a later role for Casp4 in control of intracellular bacterial replication.

2) In addition, they show that in macrophages deficient in the caspase-1-GSDMD-NINJ1 axis that STm are found replicating in the cytosol, which is a novel finding. The electron microscopy is convincing that STm are in the cytosol.

3) The authors go on to use a chloroquine resistance assay to show that inflammasome signaling also restricts STm within SCVs in human macrophages.

4) Finally, they show that the Type 3 Secretion System encoded on Salmonella Pathogenicity Island 1 contributes to STm's cytosolic access in human macrophages.

Weaknesses:

1) Their results with human macrophages suggest that there are differences between murine and human macrophages in inflammasome-mediated restriction of STm growth. For example, Thurston et al. showed that in murine macrophages that inflammasome activation controls the replication of mutant STm that aberrantly invades the cytosol, but only slightly limits replication of WT STm. In contrast, here the authors found that primed human macrophages rely on caspase-1, gasdermin D and ninjurin-1 to restrict WT STm. I wonder if the priming of the human macrophages in this study could account for the differences in these studies. Along those lines, do the authors see the same results presented in this study in the absence of priming the macrophages with Pam3CSK4. I think that determining whether the control of intracellular STm replication is dependent on priming is very important. Another difference with the Thurston et al. paper is the way that the STm inoculum was prepared - stationary phase bacteria that were opsonized. Could this also account for differences between the two studies rather than differences between murine and human macrophages in inflammasome-dependent control of STm?<br /> 2) The authors show that the pore-forming proteins GSDMD and Ninj1 contribute to control of STm replication in human macrophages. Is it possible that leakage of gentamicin from the media contributes to this control?

3) One major question that remains to be answered is whether casp-1 plays a direct role in the intracellular localization of STm. If the authors quantify the percentage of vacuolar vs. cytosolic bacteria at early time points in WT and casp-1 KO macrophages, would that be the same in the presence and absence of casp-1? If so, then this would suggest that there is a basal level of bacterial-dependent lysis of the SCV and in WT macrophages the presence of cytosolic PAMPS trigger cell death and bacteria can't replicate in the cytosol. However, in the inflammasome KO macrophages, the host cell remains alive and bacteria can replicate in the cytosol.

Reviewer #2 (Public Review):

Summary:

This work addresses the question of how human macrophages restrict intracellular replication of Salmonella.

Strengths:

Through a series of genetic knockouts and using specific inhibitors, Egan et al. demonstrated that the inflammasome components caspase-1, caspase-4, gasdermin D (GSDMD), and the final lytic death effector ninjurin-1 (NINJ1) are required for control of Salmonella replication in human macrophages. Interestingly, caspase-1 proved crucial in restricting Salmonella early during infection, whereas caspase-4 was essential in the later stages of infection. Furthermore, using a chloroquine resistance assay and state-of-the-art microscopy, the authors found that NAIP receptor and caspase-1 mostly regulate replication of cytosolic bacteria, with smaller, yet significant, impact on the vacuolar bacteria.

The finding that inflammasomes are critical in the restriction of replication of intracellular Salmonella in human macrophages contrasts with the published minimal role of inflammasomes in restriction of replication of intracellular Salmonella in murine macrophages. These findings demonstrate yet another example of interspecies and intercellular differences in regulation of bacterial infections by the immune system.

Weaknesses: none.

Reviewer #3 (Public Review):

The manuscript by Egan and coworkers investigates how Caspase-1 and Caspase-4 mediated cell death affects replication of Salmonella in human THP-1 macrophages in vitro.

Overall evaluation:

Strength of the study include the use of human cells, which exhibit notable differences (e.g., Caspase 11 vs Caspase-4/5) compared to commonly used murine models. Furthermore, the study combines inhibitors with host and bacterial genetics to elucidate mechanistic links.

The main weaknesses of the study are the inherent limitations of tissue culture models. For example, to study interaction of Salmonella with host cells in vitro, it is necessary to kill extracellular bacteria using gentamicin. However, since Salmonella-induced macrophage cell death damages the cytosolic membrane, gentamicin can reach intracellular bacteria and contribute to changes in CFU observed in tissue culture models (major point 1). This can result in tissue culture "artefacts" (i.e., observations/conclusions that cannot be recapitulated in vivo). For example, intracellular replication of Salmonella in murine macrophages requires T3SS-2 in vitro, but T3SS-2 is dispensable for replication in macrophages of the spleen in vivo (Grant et al., 2012).

Major comments:

In Figure 1: are increased CFU in WT vs CASP1-deficient THP-1 cells due to Caspase 1 restricting intracellular replication or due to Caspase-1 causing pore formation to allow gentamicin to enter the cytosol thereby restricting bacterial replication? The same question arises about Caspase-4 in Figure 2, where differences in CFU are observed only at 24h when differences in cell death also become apparent. The idea that gentamicin entering the cytosol through pores is responsible for controlling intracellular Salmonella replication is also consistent with the finding that GSDMD-mediated pore formation is required for restricting intracellular Salmonella replication (Figure 3). Similarly, the finding that inflammasome responses primarily control Salmonella replication in the cytosol could be explained by an intact SCV membrane protecting Salmonella from gentamicin (Figure 5).

Reviewer #1 (Public Review):

The manuscript by Sun and colleagues followed their previous findings on the tumor-suppressive role of PDLIM2 in lung cancer. They further investigated various mechanisms, including epigenetic modification, copy number variation, and LOH, that led to the decreased expression of PDLIM2 in human lung cancer. Next, they used a nanoparticle-based approach to specifically restore the expression in mouse lung tumors. They showed that over-expression of PDLIM2 in lung cancer repressed its progression in vivo. Also, this treatment could synergize with chemotherapy and checkpoint inhibitor anti-PD-1. Overall, the results were quite promising and convincing, using a treatment combination that would appear to have the potential for clinical implementation.

Reviewer #2 (Public Review):

Summary: The authors have previously demonstrated that the E3 ligase PDLIM2 inhibits NF-kB and STAT3 and is epigenetically repressed in human lung cancers (Sun et al. Nat. Comm. 2019 10: 5324); therefore, PDLIM2 is a tumor suppressor in lung cancer. In this manuscript, they follow up on their previous findings and show that expression of PDLIM2 is downregulated in human lung cancers by both genetic deletion and promoter methylation. They further describe a novel approach to restore the expression of PDLIM2 in mouse lung tumors by systemically administering PDLIM2 plasmids encapsulated in nanoparticles (termed "nanoPDLIM2"). The nanoPDLIM2 approach was shown to exhibit efficacy with low toxicity in a urethane-induced mouse lung cancer model. The authors further demonstrated the synergy of nanoPDLIM2 with chemotherapy and PD-1 blockade immunotherapy. The combination therapy of nanoPDLIM2, chemotherapy, and immunotherapy proved most effective with complete tumor remission in 60% of mice. Mechanistically, nanoPDLIM2 upregulated MHC-I expression, enhanced CD4/CD8 T cell activation and tumor infiltration, and suppressed MDR1 induction and nuclear expression of STAT3, RelA and prosurvival genes in tumors. Overall, this study is important because it reinforces the critical roles of PDLIM2 in suppressing lung cancer, and also identifies a potential approach to restoring PDLIM2 expression in lung tumors. The experiments were well executed; the data are convincing and support the conclusions made by the authors.

Reviewer #3 (Public Review):

Strengths:

NanoPDLIM2, nanotechnologies that efficiently deliver lentivirus overcomes resistance to chemotherapy and anti-PD-1 immunotherapy. This is a new strategy for enhancing the efficiency of immune checkpoint inhibitors. This finding is important from a clinical translation perspective, but I have several minor concerns.

Weaknesses:

1. Please describe the mechanism of increased MHC class I and PD-L1 by PDLIM2.<br /> 2. Please describe the mechanism of decreased MDR1, nuclear RelA and STAT3 by PDLIM2.<br /> 3. Please determine whether PDLIM2 expression directly impacts immune cells (function and number)?<br /> 4. What is the efficiency of PDLIM2 delivery? Does delivery efficiency determine anti-tumor effect?<br /> 5. Authors used a non-immunogenic tumor model. Can you demonstrate the combination effect with PDLIM2 in immunogenic lung cancer models to determine whether the combination of PDLIM2 with anti-PD-1 Ab confers a synergistic effect without chemotherapy?<br /> 6. On page 11, % change can make one over-interpret data.<br /> 7. In Figure 5, what is the difference between 5A and 5D?<br /> 8. It is unclear whether PDLIM2 confers an additive or a synergistic effect with anti-PD-1/chemo.<br /> 9. Have the authors tested any toxicity in normal lungs?

Reviewer #1 (Public Review):

In this manuscript, the authors demonstrated that YAP/TAZ promotes P-body formation in a series of cancer cell lines. YAP/TAZ modulates the transcription of multiple P-body-related genes, especially repressing the transcription of the tumor suppressor proline-rich nuclear receptor coactivator 1 (PNRC1) through cooperation with the NuRD complex. PNRC1 functions as a critical repressor in YAP-induced biogenesis of P-bodies and tumorigenesis in colorectal cancer (CRC). Reexpression of PNRC1 or disruption of P-bodies attenuated the protumorigenic effects of YAP. Overall, these findings are interesting and the study was well conducted.

Major concerns:

1. RNAseq data indicated that Yap has the capacity to suppress the expression of numerous genes. In addition to PNRC1, could there be additional Yap targeting factors involved in Yap-mediated the formation of P-bodies?<br /> 2. It is still not clear how PNRC1 regulates P-bodies. Knockdown of PNRC1 prevented the reduction of P-bodies caused by Yap knockdown. How do the genes related to P-bodies that are positively regulated by Yap, such as SAMD4A, AJUBA, and WTIP, change in this scenario? Given that the expression of Yap can differ considerably among various cell types, is it possible for P-bodies to be present in tumor cells lacking Yap expression?<br /> 3. The authors demonstrated that CHD4 can bind to Yap target genes, such as CTGF, AJUBA, SAMD4A (Figure 4 - Figure Supplement 1D). Does the NuRD complex repress the expression of these genes? the NuRD complex could prevent the formation of P-bodies?<br /> 4. YAP/TAZ promotes the formation of P-bodies which contradicts the previous study's conclusion (PMID: 34516278). Please address these inconsistent findings.

Reviewer #2 (Public Review):

In a study by Shen et al., the authors investigated YAP/TAZ target genes that play a role in the formation of processing bodies (P-bodies). P-bodies are membraneless cytoplasmic granules that contain translationally repressed mRNAs and components of mRNA turnover. GO enrichment analysis of the RNA-Seq data of colorectal cancer cells (HCT116) after YAP/TAZ knockdown showed that the downregulated genes were enriched in P-body resident proteins. Overexpression, knockdown, and ChIP-qPCR analyses showed that SAMD4A, PNRC1, AJUBA, and WTIP are YAP-TEAD target genes that also play a role in P-body biogenesis. Using P-body markers such as DDX6 and DCP1A, the authors showed that the knockdown of YAP in the HCT116 cell line causes a reduction in the number of P-bodies. Similarly, overexpression of constitutively active YAP (YAP 5SA) increased the P-body number. The YAP-TEAD target genes SAMD4A and AJUBA positively regulate P-body formation, because lowering their expression levels using siRNA reduces the number of P-bodies. The other YAP target gene, PNRC1, is a negative regulator of P-body biogenesis and consistently YAP suppresses its expression through the recruitment of the NuRD complex. YAP target genes that modulate P-body formation play prominent roles in oncogenesis. PNRC1 suppression is key to YAP-mediated proliferation, colony formation, and tumorigenesis in HCT116 xenografts. Similarly, SAMD4 and AJUBA knockdown abrogated cell viability. In summary, this study demonstrated that SAMD4, AJUBA, WTIP, and PNRC1 are bona fide YAP-TEAD target genes that play a role in P-body formation, which is also linked to the oncogenesis of colon cancer cells.

Major Strengths:

The majority of the experiments were appropriately planned so that the generated data could support the conclusions drawn by the authors. The phenotype observed with YAP/TAZ knockdown correlated inversely with YAP5SA overexpression, which is complementary. Where possible, the authors also used point mutations that selectively disrupt protein-protein interactions, such as YAP S94A and PNRC1 W300A. The CRC cell line HCT116 was used throughout the study; additionally, data from other cancer cell lines were used to support the generality of the findings.

Weaknesses:

The authors did not elucidate the mechanistic link between P-body formation and oncogenesis; therefore, it is unclear why an increase in the number of P-bodies is pro-tumorigenic. AJUBA and SAMD4 may have housekeeping functions and reduce the proliferation of YAP-independent cell lines. Figure 6 - Figure Supplement 4 shows a reduction in cell viability and migration in control HCT116 cell lines upon AJUBA/SAMD4 knockdown. Therefore, it is unclear whether their tumor suppressive role is YAP-dependent. The authors extrapolated and suggested that their findings could be exploited therapeutically, without providing much detail. How do they plan to stimulate the expression of PNRC1? It is not necessary for every scientific finding to lead to a therapeutic benefit; therefore, they can tone down such statements if therapeutic exploitation is not realistic. The authors elucidated a mechanism for PNRC1 repression and one wonders why no attempts were made to understand the mechanism of activation of SAMD4, AJUBA, and WTIP expression.

Reviewer #1 (Public Review):

This is a technically sound paper focused on a useful resource around the DRGP phenotypes which the authors have curated, pooled, and provided a user-friendly website. This is aimed to be a crowd-sourced resource for this in the future.

The authors should make sure they coordinate as well as possible with the NC datasets and community and broader fly community. It looks reasonable to me but I am not from that community.

I have only one major concern which in a more traditional review setting I would be flagging to the editor to insist the authors did on resubmission. I also have some scene setting and coordination suggestions and some minor textual / analysis considerations.

The major concern is that the authors do not comment on the distribution of the phenotypes; it is assumed it is a continuous metric and well-behaved - broad gaussian. This is likely to be more true of means and medians per line than individual measurements, but not guaranteed, and there could easily be categorical data in the future. The application of ANOVA tests (of the "covariates") is for example fragile for this.

The simplest recommendation is in the interface to ensure there is an inverse normalisation (rank and then project on a gaussian) function, and also to comment on this for the existing phenotypes in the analysis (presumably the authors are happy). An alternative is to offer a kruskal test (almost the same thing) on covariates, but note PLINK will also work most robustly on a normalised dataset.

Minor points:<br /> On the introduction, I think the authors would find the extensive set of human GWAS/PheWAS resources useful; widespread examples include the GWAS Catalog, Open Targets PheWAS, MR-base, and the FinnGen portal. The GWAS Catalog also has summary statistics submission guidelines, and I think where possible meta-data harmonisation should be similar (not a big thing). Of course, DRGP has a very different structure (line and individuals) and of course, raw data can be freely shown, so this is not a one-to-one mapping.

For some authors coming from a human genetics background, they will be interpreting correlations of phenotypes more in the genetic variant space (eg LD score regression), rather than a more straightforward correlation between DRGP lines of different individuals. I would encourage explaining this difference somewhere.

This leads to an interesting point that the inbred nature of the DRGP allows for both traditional genetic approaches and leveraging the inbred replication; there is something about looking at phenotype correlations through both these lenses, but this is for another paper I suspect that this harmonised pool of data can help.

I was surprised the authors did not crunch the number of transcript/gene expression phenotypes and have them in. Is this because this was better done in other datasets? Or too big and annoying on normalisation? I'd explain the rationale to leave these out.

I think 25% FDR is dangerously close to "random chance of being wrong". I'd just redo this section at a higher FDR, even if it makes the results less 'exciting'. This is not the point of the paper anyway.

I didn't buy the extreme line piece as being informative. Something has to be on the top and bottom of the ranks; the phenotypes are an opportunity for collection and probably have known (as you show) and cryptic correlations. I think you don't need this section at all for the paper and worry it gives an idea of "super normals" or "true wild types" which ... I just don't think is helpful.

I'd say "well-established inversion genotypes and symbiot levels" rather than generic covariates. Covariates could mean anything. You have specific "covariates" which might actually be the causal thing.

I wouldn't use the adjective tedious about curation. It's a bit of a value judgement and probably places the role of curation in the wrong way. Time-consuming due to lack of standards and best practice?

Reviewer #2 (Public Review):

Summary:<br /> ​In the present study, Gardeux et al provide a web-based tool for curated association mapping results from DRP studies. The tool lets users view association results for phenotypes and compare mean phenotype ~ phenotype correlations between studies. In the manuscript, the authors provide several example utilities associated with this new resource, including pan-study summary statistics for sex, traits, and loci. They highlight cross-trait correlations by comparing studies focused on longevity with phenotypes such as oxphos and activity.

Strengths:<br /> -Considerable efforts were dedicated toward curating the many DRG studies provided.<br /> -Available tools to query large DRP studies are sparse and so new tools present appeal

Weaknesses:<br /> The creation of a tool to query these studies for a more detailed understanding of physiologic outcomes seems underdeveloped. These could be improved by enabling usages such as more comprehensive queries of meta-analyses, molecular information to investigate given genes or pathways, and links to other information such as in mouse rat or human associations.

Reviewer #1 (Public Review):

General comments:<br /> This paper investigates the pH-specific enzymatic activity of mouse acidic mammalian chitinase (AMCase) and aims to elucidate its function's underlying mechanisms. The authors employ a comprehensive approach, including hydrolysis assays, X-ray crystallography, theoretical calculations of pKa values, and molecular dynamics simulations to observe the behavior of mouse AMCase and explore the structural features influencing its pH-dependent activity.

The study's key findings include determining kinetic parameters (Kcat and Km) under a broad range of pH conditions, spanning from strong acid to neutral. The results reveal pH-dependent changes in enzymatic activity, suggesting that mouse AMCase employs different mechanisms for protonation of the catalytic glutamic acid residue and the neighboring two aspartic acids at the catalytic motif under distinct pH conditions.

The novelty of this research lies in the observation of structural rearrangements and the identification of pH-dependent mechanisms in mouse AMCase, offering a unique perspective on its enzymatic activity compared to other enzymes. By investigating the distinct protonation mechanisms and their relationship to pH, the authors reveal the adaptive nature of mouse AMCase, highlighting its ability to adjust its catalytic behavior in response to varying pH conditions. These insights contribute to our understanding of the pH-specific enzymatic activity of mouse AMCase and provide valuable information about its adaptation to different physiological conditions.

Overall, the study enhances our understanding of the pH-dependent activity and catalytic properties of mouse AMCase and sheds light on its adaptation to different physiological pH environments.

Reviewer #2 (Public Review):

Summary: In this study of the mouse homolog of acidic mammalian chitinase, the overall goal is to provide a mechanistic explanation for the unusual observation of two pH optima for the enzyme. The study includes biochemical assays to establish kinetic parameters at different solution pH, structural studies of enzyme/substrate complexes, and theoretical analysis of amino acid side chain pKas and molecular dynamics.

Strengths: The biochemical assays are rigorous and nicely complemented by the structural and computational analysis. The mechanistic proposal that results from the study is well rationalized by the observations in the study.

Weaknesses: The overall significance of the work could be made more clear. Additional details could be provided about the limitations of prior biochemical studies of mAMC that warranted the kinetic analysis. The mouse enzyme seems unique in terms of its behavior at high and low pH, so it remains unclear how the work will enhance broader understanding of this enzyme class. It was also not clear can the findings be used for therapeutic purposes, as detailed in the abstract, if the human enzyme works differently.

Reviewer #1 (Public Review):

Summary:<br /> This study focuses on the defining cellular pathways critical for tRNA export from the nucleus. While a number of these pathways have been identified, the observation that the primary transport receptors identified thus far (Los1 and Msn5) are not essential and that cells are viable even when both the genes are deleted supports the idea that there are as yet unidentified mediators of tRNA export from the nucleus. This study implicates the helicase Dbp5 in one of these parallel pathways arguing that Dbp5 works in a pathway that is independent of Los1 and/or Msn5. The authors present genetic data to support this conclusion. At least one result suggests that the idea of these pathways in parallel may be too simplistic as deletion of the LOS1 gene, which is not essential decreases the interaction of tRNA export substrate with Dbp5 (Figure 2A). If the two pathways were working in parallel, one might have expected removing one pathway to lead to an increase in the use of the other pathway and hence the interaction with a receptor in that pathway. The authors provide solid evidence that Dbp5 interacts with tRNA directly and that the addition of the factor Gle1 together with the previously identified co-factor InsP6 can trigger helicase activity and release of tRNA. The combination of in vivo studies and biochemistry provides evidence to consider how Dbp5 contributes to the export of tRNA and more broadly adds to the conversation about how coding and non-coding RNA export from the nucleus might be coordinated to control cell physiology.

Strengths and weaknesses:<br /> A major strength of this manuscript is the multi-pronged approach to explore a potential role for the helicase Dbp5 in one of the multiple export pathways for tRNA from the nucleus.

The obvious missing experiment here with respect to genetics is the test of whether deletion of the MSN5 gene in the cells, which combines deletion of LOS1 and the dbp5_R423A allele, shown in Figure 1D would be lethal. This key experiment would lend substance to the argument that Dbp5 functions in a tRNA export pathway that is parallel to the Los1 and Msn5 pathways.

While some of the binding assays show rather modest band shifts (Figure 4B for example), the data in Figure 4A showing that there is no binding detected unless a non-hydrolyzable ATP analogue is employed, argues for specificity in nucleic acid binding. The question that does arise is whether the binding is specific for tRNA.

With the exception of the binding studies, which also employ a mixture of yeast tRNAs, this study relies primarily on a single tRNA species to come to the conclusions drawn. Many other studies have used multiple tRNAs to explore whether pathways characterized are generalizable to other tRNAs.

The authors provide evidence of a model where the helicase Dbp5 plays a role in tRNA export from the nucleus. Further evidence is required to determine whether Dbp5 could function in the same pathway as the previously defined tRNA export receptors, Los1 and Msn5. There are genetic tests that could be performed to explore this question. Some of the biochemistry presented would show when Los1 is absent that the interaction of Dbp5 with tRNA decreases, which could support a model where Dbp5 plays a role in coordination with Los1.

This work allows insight into key questions which still remain about the multiple pathways that are required for tRNA trafficking as well as how transport pathways for coding and non-coding RNAs might be coordinated. These questions are important as many of these pathways may be regulated in response to cellular conditions or during development and defining the fundamental pathways will be critical to understanding these dynamic processes.

Reviewer #2 (Public Review):

This submission is about the role of Dbp5/Gle1 in tRNA export. The manuscript provides data showing that Dbp5/Gle1 are involved in tRNA export from the nucleus which is an essential process critical to translation. The authors provide data that largely supports conclusions, however, there are some pieces of data that are misinterpreted. (Figure 1A and B look the same; in Fig 1E, the DAPI staining is abnormal; in Fig 4 the bands can't be seen.)

Additionally, the methods used are fairly standard so the article does not contain any new technical achievements.

Reviewer #1 (Public Review):

The authors present a study focused on addressing the key challenge in drug discovery, which is the optimization of absorption and affinity properties of small molecules through in silico methods. They propose active learning as a strategy for optimizing these properties and describe the development of two novel active learning batch selection methods. The methods are tested on various public datasets with different optimization goals and sizes, and new affinity datasets are curated to provide up-to-date experimental information. The authors claim that their active learning methods outperform existing batch selection methods, potentially reducing the number of experiments required to achieve the same model performance. They also emphasize the general applicability of their methods, including compatibility with popular packages like DeepChem.

Strengths:

Relevance and Importance: The study addresses a significant challenge in the field of drug discovery, highlighting the importance of optimizing the absorption and affinity properties of small molecules through in silico methods. This topic is of great interest to researchers and pharmaceutical industries.

Novelty: The development of two novel active learning batch selection methods is a commendable contribution. The study also adds value by curating new affinity datasets that provide chronological information on state-of-the-art experimental strategies.

Comprehensive Evaluation: Testing the proposed methods on multiple public datasets with varying optimization goals and sizes enhances the credibility and generalizability of the findings. The focus on comparing the performance of the new methods against existing batch selection methods further strengthens the evaluation.

Weaknesses:

Lack of Technical Details: The feedback lacks specific technical details regarding the developed active learning batch selection methods. Information such as the underlying algorithms, implementation specifics, and key design choices should be provided to enable readers to understand and evaluate the methods thoroughly.

Evaluation Metrics: The feedback does not mention the specific evaluation metrics used to assess the performance of the proposed methods. The authors should clarify the criteria employed to compare their methods against existing batch selection methods and demonstrate the statistical significance of the observed improvements.

Reproducibility: While the authors claim that their methods can be used with any package, including DeepChem, no mention is made of providing the necessary code or resources to reproduce the experiments. Including code repositories or detailed instructions would enhance the reproducibility and practical utility of the study.

Suggestions for Improvement:

Elaborate on the Methodology: Provide an in-depth explanation of the two active learning batch selection methods, including algorithmic details, implementation considerations, and any specific assumptions made. This will enable readers to better comprehend and evaluate the proposed techniques.

Clarify Evaluation Metrics: Clearly specify the evaluation metrics employed in the study to measure the performance of the active learning methods. Additionally, conduct statistical tests to establish the significance of the improvements observed over existing batch selection methods.

Enhance Reproducibility: To facilitate the reproducibility of the study, consider sharing the code, data, and resources necessary for readers to replicate the experiments. This will allow researchers in the field to validate and build upon your work more effectively.

Conclusion:

The authors' study on active learning methods for optimizing drug discovery presents an important and relevant contribution to the field. The proposed batch selection methods and curated affinity datasets hold promise for improving the efficiency of drug discovery processes. However, to strengthen the study, it is crucial to provide more technical details, clarify evaluation metrics, and enhance reproducibility by sharing code and resources. Addressing these limitations will further enhance the value and impact of the research.

Reviewer #2 (Public Review):

The authors presented a well-written manuscript describing the comparison of active-learning methods with state-of-art methods for several datasets of pharmaceutical interest. This is a very important topic since active learning is similar to a cyclic drug design campaign such as testing compounds followed by designing new ones which could be used to further tests and a new design cycle and so on. The experimental design is comprehensive and adequate for proposed comparisons. However, I would expect to see a comparison regarding other regression metrics and considering the applicability domain of models which are two essential topics for the drug design modelers community.

Reviewer #1 (Public Review):

The authors developed an extension to the pairwise sequentially Markov coalecent model that allows to simultaneously analyze multiple types of polymorphism data. In this paper, they focus on SNPs and DNA methylation data. Since methylation markers mutate at a much faster rate than SNPs, this potentially gives the method better power to infer size history in the recent past. Additionally, they explored a model where there are both local and regional epimutational processes.

Integrating additional types of heritable markers into SMC is a nice idea which I like in principle. However, a major caveat to this approach seems to be a strong dependence on knowing the epimutation rate. In Fig. 6 it is seen that, when the epimutation rate is known, inferences do indeed look better; but this is not necessarily true when the rate is not known. A roughly similar pattern emerges in Supp. Figs. 4-7; in general, results when the rates have to be estimated don't seem that much better than when focusing on SNPs alone. This carries over to the real data analysis too: the interpretation in Fig. 7 appears to hinge on whether the rates are known or estimated, and the estimated rates differ by a large amount from earlier published ones.

Overall, this is an interesting research direction, and I think the method may hold more promise as we get more and better epigenetic data, and in particular better knowledge of the epigenetic mutational process. At the same time, I would be careful about placing too much emphasis on new findings that emerge solely by switching to SNP+SMP analysis.

Reviewer #2 (Public Review):

A limitation in using SNPs to understand recent histories of genomes is their low mutation frequency. Tellier et al. explore the possibility of adding hypermutable markers to SNP based methods for better resolution over short time frames. In particular, they hypothesize that epimutations (CG methylation and demethylation) could provide a useful marker for this purpose. Individual CGs in Arabidopsis tends to be either close to 100% methylated or close to 0%, and are inherited stably enough across generations that they can be treated as genetic markers. Small regions containing multiple CGs can also be treated as genetic markers based on their cumulative methylation level. In this manuscript, Tellier et al develop computational methods to use CG methylation as a hypermutable genetic marker and test them on theoretical and real data sets. They do this both for individual CGs and small regions. My review is limited to the simple question of whether using CG methylation for this purpose makes sense at a conceptual level, not at the level of evaluating specific details of the methods. I have a small concern in that it is not clear that CG methylation measurements are nearly as binary in other plants and other eukaryotes as they are in Arabidopsis. However, I see no reason why the concept of this work is not conceptually sound. Especially in the future as new sequencing technologies provide both base calling and methylating calling capabilities, using CG methylation in addition to SNPs could become a useful and feasible tool for population genetics in situations where SNPs are insufficient.

Reviewer #3 (Public Review):

I very much like this approach and the idea of incorporating hypervariable markers. The method is intriguing, and the ability to e.g. estimate recombination rates, the size of DMRs, etc. is a really nice plus. I am not able to comment on the details of the statistical inference, but from what I can evaluate it seems sound and reasonable. This is an exciting new avenue for thinking about inference from genomic data. I have a few concerns about the presentation and then also questions about the use of empirical methylation data sets.

I think a more detailed description of demographic accuracy is warranted. For example, in L245 MSMC2 identifies the bottleneck (albeit smoothed) and only slightly overestimates recent size. In the same analysis the authors' approach with unknown mu infers a nonexistent population increase by an order of magnitude that is not mentioned.

Similarly, it seems problematic that (L556) the approach requiring estimation of site and region parameters (as would presumably be needed in most empirical systems like endangered nonmodel species mentioned in the introduction) does no better than using only SNPs. Overall, I think a more objective and perhaps quantitative comparison of approaches is warranted.

The authors simulate methylated markers at 2% (and in some places up to 20%). In many plant genomes a large proportion of cytosines are methylated (e.g. 70% in maize: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496265/). I don't know what % of these may be polymorphic, but this leads to an order of magnitude more methylated cytosines than there are SNPs. Couldn't this mean that any appreciable error in estimating methylation threatens to be of a similar order of magnitude to the SNP data? I would welcome the authors' thoughts here.

A few points of discussion about the biology of methylation might be worth including. For example, methylation can differ among cell types or cells within a tissue, yet sequencing approaches evaluate a pool of cells. This results in a reasonable fraction of sites having methylation rates not clearly 0 or 1. How does this variation affect the method? Similarly, while the authors cite literature about the stable inheritance of methylation, a sentence or so more about the time scale over which this occurs would be helpful. Finally, in some species methylated cytosines have mutation rates an order of magnitude higher than other nucleotides. The authors mention they assume independence, but how would violation of this assumption affect their inference?

Reviewer #1 (Public Review):

Summary:<br /> The precise mechanism of how tetraspanin proteins engage in the generation of discs is still an open question in the field of photoreceptor biology. This question is of significance as the lack of photoreceptor discs or defects in disc morphogenesis due to mutations in tetraspanin proteins is a known cause of vision loss in humans. The authors of this study combine TEM and mouse models to tease out the role of tetraspanin proteins, peripherin, and Rom1 in the genesis of the photoreceptor discs. They show that the absence of Rom1 leads to an increase in peripherin and changes in disc morphology. Further rise in peripherin alleviates some of the defects observed in Rom1 knockout animals leading to the conclusion that peripherin can substitute for the absence of Rom1.

Strengths:<br /> A mouse model of Rom1 generated by the McInnes group in 2000 predicted a role for Rom1 in rim closure. They also showed enlarged discs in the absence of Rom1. This study confirmed this finding and showed the compensatory changes in peripherin, maintaining the total levels of tetraspanin proteins. Lack of Rom1 leads to excessive open disks demonstrated by darkly stained tannic acid-accessible areas in TEM. Interestingly, increased peripherin expression can rescue some morphological defects, including maintaining normal disc diameters and incisures. Overall, these observations lead authors to propose a model that ROM1 can be replaced by peripherin.

Weaknesses:<br /> The compensatory increase in peripherin and morphological rescue in the absence of ROM1 is expected, given the previous work from authors showing i) absence of peripherin showing increased ROM1 and ii) "Eliminating Rom1 also increased levels of Prph2/RRCT: mean Prph2/RRCT levels in P30 Prph2+/R retinas were 34% of WT, while levels in Prph2+/R/Rom1−/− retinas were 59% of WT" from Conley, 2019. The current study provides a comprehensive quantitative analysis. However, the mechanism behind the mechanism is unclear and warrants discussion.

Photoreceptor morphology appears better when peripherin is overexpressed. Is there a rescue of rod function (assessed by ERG or equivalent measures) in peripherin OE/Rom1-/- mice? Given the extensive work in this area and the implications the authors allude to at the end, it is important to investigate this aspect.

Reviewer #2 (Public Review):

In this study, Lewis et al seek to further define the role of ROM1. ROM1 is a tetraspanin protein that oligomerizes with another tetraspanin, PRPH2, to shape the rims of the membrane discs that comprise the light-sensitive outer segment of vertebrate photoreceptors. ROM1 knockout mice and several PRPH2 mutant mice are reexamined. The conclusion reached is that ROM1 is redundant to PRPH2 in regulating the size of newly forming discs, although excess PRPH2 is required to compensate for the loss of ROM1.

This replicates earlier findings while adding rigor using a mass spectrometry-based approach to quantitate the ratio of ROM1 and PRPH2 to rhodopsin (the protein packed in the body of the disc membranes) and careful analysis of tannic acid labeled newly forming discs using transmission electron microscopy.

In ROM1 knockout mice PRPH2 expression was found to be increased so that the level of PRPH2 in those mice matches the combined amount of PRPH2 and ROM1 in wildtype mice. Despite this, there are defects in disc formation that are resolved when the ROM1 knockout is crossed to a PRPH2 overexpressing line. A weakness of the study is that the molar ratios between ROM1, PRPH2 and rhodopsin were not measured in the PRPH2 overexpressing mice. This would have allowed the authors to be more precise in their conclusion that a 'sufficient' excess of PRPH2 can compensate for defects in ROM1.

Reviewer #3 (Public Review):

In this manuscript, Lewis et al. investigate the role of tetraspanins in the formation of discs - the key structure of vertebrate photoreceptors essential for light reception. Two tetraspanin proteins play a role in this process: PRPH2 and ROM1. The critical contribution of PRPH2 has been well established and loss of its function is not tolerated and results in gross anatomical pathology and degeneration in both mice and humans. However, the role of ROM1 is much less understood and has been considered somewhat redundant. This paper provides a definitive answer about the long-standing uncertainty regarding the contribution of ROM1 firmly establishing its role in outer segment morphogenesis. First, using an ingenious quantitative proteomic technique the authors show PRPH2 compensatory increase in ROM1 knockout explaining the redundancy of its function. Second, they uncover that despite this compensation, ROM1 is still needed, and its loss delays disc enclosure and results in the failure to form incisures. Third, the authors used a transgenic mouse model and show that deficits seen in ROM1 KO could be completely compensated by the overexpression of PRPH2. Finally, they analyzed yet another mouse model based on double manipulation with both ROM1 loss and expression of PRPH2 mutant unable to form dimerizing disulfide bonds further arguing that PRPH2-ROM1 interactions are not required for disc enclosure. To top it off the authors complement their in vivo studies by a series of biochemical assays done upon reconstitution of tetraspanins in transfected cultured cells as well as fractionations of native retinas. This report is timely, addresses significant questions in cell biology of photoreceptors, and pushes the field forward in a classical area of photoreceptor biology and mechanics of membrane structure as well. The manuscript is executed at the top level of technical standard, exceptionally well written, and does not leave much more to desire. It also pushes standards of the field- one such domain is the quantitative approach to analysis of the EM images which is notoriously open to alternative interpretations - yet this study does an exceptional job unbiasing this approach.

According to my expertise in photoreceptor biology, there is nothing wrong with this manuscript either technically or conceptually and I have no concerns to express.

Reviewer #1 (Public Review):

In this study, the authors investigated the role of MAM and the Notch signaling pathway in the onset of the atrophic phenotype in both in vivo and in vitro models. The rationale used to obtain the data is one of the main strengths of the study. Already from the reading, the reasoning scheme used by the authors in setting up the study and evaluating the data obtained is clear. Using both cellular and mouse models in vivo consolidates the data obtained. The authors also methodologically described all the choices made in the supplementary section. A weakness, on the other hand, is the failure to include averages and statistical data in the results that would give a quantifiable idea of the data obtained. To complete the picture, the authors could also investigate the possible involvement of the intrinsic apoptosis pathway as well as describe probable metabolic shifts to muscle cells in atrophic conditions. The rationale used by the authors to obtain the result is linear. The data obtained are useful for understanding the onset and characterization of the atrophic phenotype under disuse and microgravity conditions. The methods used are in line with those used in the field and can be a starting point for other studies. The cellular models are well described in the materials and methods section. The selected mouse models followed a logical rationale and were in line with the intended aim.

Reviewer #2 (Public Review):

In this study, the authors examined how the maintenance of mitochondrial-associated endoplasmic reticulum membranes (MAM) is critical for the prevention of muscle atrophy under microgravity conditions. They observed, a reduction in MAM in myotubes placed in a microgravity condition; in addition, MFN2-deficient human iPS cells showed a decrease in the number of MAM, similar to in myotubes differentiated under microgravity conditions, in addition to the activation of the Notch signaling pathway. The authors, moreover, observed that treatment with the gamma-secretase inhibitor with DAPT preserved the atrophic phenotype of differentiated myotubes in microgravity and improve the regenerative capacity of Mfn2-deficient muscle stem cells in dystrophic mice.

The entire study was well conducted, bringing an interesting analysis in vitro and in vivo of aging conditions. In my opinion, it is necessary to improve the analysis of both genes and proteins to better support the conclusions

The study can contribute to a better understanding of one of the major problems of aging, such as muscle atrophy and inhibition of muscle regeneration, emphasizing the importance of the NOTCH pathway in these pathological situations. The work will be of interest to all scientists working on aging.

Reviewer #1 (Public Review):

Summary:

Sender et al describe a model to estimate what fraction of DNA becomes cell-free DNA in plasma. This is of great interest to the community, as the amount of DNA from a certain tissue (for example, a tumor) that becomes available for detection in the blood has important implications for disease detection.

However, the authors' methods do not consider important variables related to cell-free DNA shedding and storage, and their results may thus be inaccurate. At this stage of the paper, the methods section lacks important detail. Thus, it is difficult to fully assess the manuscript and its results.

Strengths:

The question asked by the authors has potentially important implications for disease diagnosis. Understanding how genomic DNA degrades in the human circulation can guide towards ways to enrich for DNA of interest or may lead to unexpected methods of conserving cell-free DNA. Thus, the question "how much genomic DNA becomes cfDNA" is of great interest to the scientific and medical community. Once the weaknesses of the manuscript are addressed, I believe this manuscript has the potential to be a widely used resource.

Weaknesses:

There are two major weaknesses in how the analysis is presented. First, the methods lack detail. Second, the analysis does not consider key variables in their model.

Issues pertaining to the methods section.<br /> The current manuscript builds a flux model, mostly taking values and results from three previous studies:

1- The amount of cellular turnover by cell type, taken from Sender & Milo, 2021<br /> 2- The fractions of various tissues that contribute DNA to the plasma, taken from Moss et al, 2018 and Loyfer et al, 2023

My expertise lies in cell-free DNA, and so I will limit my comments to the manuscripts in (2).

Paper by Loyfer et al (additional context):

Loyfer et al is a recent landmark paper that presents a computational method for deconvoluting tissues of origin based on methylation profiles of flow-sorted cell types. Thus, the manuscript provides a well-curated methylation dataset of sorted cell-types. The majority of this manuscript describes the methylation patterns and features of the reference methylomes (bulk, sorted cell types), with a smaller portion devoted to cell-free DNA tissue of origin deconvolution.

I believe the data the authors are retrieving from the Loyfer study are from the 23 healthy plasma cfDNA methylomes analyzed in the study, and not the re-analysis of the 52 COVID-19 samples from Cheng et al (MED 2021).

Paper by Moss et al (additional context):

Moss et al is another landmark paper that predates the Loyfer et al manuscript. The technology used in this study (methylation arrays) is outdated but is an incredible resource for the community. This paper evaluates cfDNA tissues of origin in health and different disease scenarios. Again, I assume the current manuscript only pulled data from healthy patients, although I cannot be sure as it is not described in the methods section.

This manuscript:

The current manuscript takes (I think) the total cfDNA concentration from males and females from the Moss et al manuscript (pooled cfDNA; 2 young male groups, 2 old male groups, 2 young female groups, 2 old female groups, Supplementary Dataset; "total_cfDNA_conc" tab). I believe this is the data used as total cfDNA concentration. It would be beneficial for all readers if the authors clarified this point.

The tissues of origin, in the supplemental dataset ("fraction" tab), presents the data from 8 cell types (erythrocytes, monocytes/macrophages, megakaryocytes, granulocytes, hepatocytes, endothelial cells, lymphocytes, other). The fractions in the spreadsheet do not match the Loyfer or Moss manuscripts for healthy individuals. Thus, I do not know what values the supplementary dataset represents. I also don't know what the deconvolution values are used for the flux model.

The integration of these two methods lack detail. Are the authors here using yields (ie, cfDNA concentrations) from Moss et al, and tissue fractions from Loyfer et al? If so, why? There are more samples in the Loyfer manuscript, so why are the samples from Moss et al. being used? The authors are also selectively ignoring cell-types that are present in healthy individuals (Neurons from Moss et al, 2018). Why?

Appraisal:

At this stage of the manuscript, I think additional evidence and analysis is required to confirm the results in the manuscript.

Impact:

Once the authors present additional analysis to substantiate their results, this manuscript will be highly impactful on the community. The field of liquid biopsies (non-invasive diagnostics) has the potential to revolutionize the medical field (and has already in certain areas, such as prenatal diagnostics). Yet, there is a lack of basic science questions in the field. This manuscript is an important step forward in asking more "basic science" questions that seek to answer a fundamental biological question.

Reviewer #2 (Public Review):

Summary:

Cell-free DNA (cfDNA) are short DNA fragments released into the circulation when cells die. Plasma cfDNA level is thought to reflect the degree of cell-death or tissue injury. Indeed, plasma cfDNA is a reliable diagnostic biomarker for multiple diseases, providing insights into disease severity and outcomes. In this manuscript, Dr. Sender and colleagues address a fundamental question: What fraction of DNA released from cell death is detectable as plasma cfDNA? The authors use public data to estimate the amount of DNA produced from dying cells. They also utilize public data to estimate plasma cfDNA levels. Their calculations showed that <10% of DNA released is detectable as plasma cfDNA, the fraction of detectable cfDNA varying by tissue sources. The study demonstrates new and fundamental principles that could improve disease diagnosis and treatment via cfDNA.

Strengths:

1. The experimental approach is resource-mindful taking advantage of publicly available data to estimate the fraction of detectable cfDNA in physiological states. The authors did not assess if the fraction of detectable cfDNA changes in disease conditions. Nonetheless, their pioneering study lays the foundation and provides the methods needed for a similar assessment in disease states.<br /> 2. The findings of this study potentially explain discrepancies in measured versus expected tissue-specific cfDNA from some tissues. For example, the gastrointestinal tract is subject to high cell turnover and release of DNA. Yet, only a small fraction of that DNA ends up in plasma as gastrointestinal cfDNA.<br /> 3. The study proposes potential mechanisms that could account for the low fraction of detectable cfDNA in plasma relative to DNA released. This includes intracellular or tissue machinery that could "chew up" DNA released from dying cells, allowing only a small fraction to escape into plasma as cfDNA. Could this explain why the gastrointestinal track with an elaborate phagosome machinery contributes a small fraction of plasma cfDNA? Given the role of cfDNA as damage-associated molecular pattern in some diseases, targeting such a machinery may provide novel therapeutic opportunities.

Weaknesses: In vitro and in vivo studies are needed to validate these findings and define tissue machinery that contribute to cfDNA production. The validation studies should address the following limitations of the study design: -

1. Align the cohorts to estimate DNA production and plasma cfDNA levels. Cellular turnover rate and plasma cfDNA levels vary with age, sex, circadian clock, and other factors (Madsen AT et al, EBioMedicine, 2019). This study estimated DNA production using data abstracted from a homogenous group of healthy control males (Sender & Milo, Nat Med 2021). On the other hand, plasma cfDNA levels were obtained from datasets of more diverse cohort of healthy males and females with a wide range of ages (Loyfer et al. Nature, 2023 and Moss et al., Nat Commun, 2018).<br /> 2. "cfDNA fragments are not created equal". Recent studies demonstrate that cfDNA composition vary with disease state. For example, cfDNA GC content, fraction of short fragments, and composition of some genomic elements increase in heart transplant rejection compared to no-rejection state (Agbor-Enoh, Circulation, 2021). The genomic location and disease state may therefore be important factors to consider in these analyses.<br /> 3. Alternative sources of DNA production should be considered. Aside from cell death, DNA can be released from cells via active secretion. This and other additional sources of DNA should be considered in future studies. The distinct characteristics of mitochondrial DNA to genomic DNA should also be considered.

Reviewer #1 (Public Review):

The association of vitamin D supplementation in reducing Asthma risk is well studied, although the mechanistic basis for this remains unanswered. In the presented study, Kilic and co-authors aim to dissect the pathway of Vitamin D mediated amelioration of allergic airway inflammation. They use initial leads from bioinformatic approaches, which they then associate with results from a clinical trial (VDAART) and then validate them using experimental approaches in murine models. The authors identify a role of VDR in inducing the expression of the key regulator Ikzf3, which possibly suppresses the IL-2/STAT5 axis, consequently blunting the Th2 response and mitigating allergic airway inflammation.

Strengths:<br /> The major strength of the paper lies in its interdisciplinary approach, right from hypothesis generation, and linkage with clinical data, as well as in the use of extensive ex vivo experiments and in vivo approaches using knock-out mice.

The study presents some interesting findings including an inducible baseline absence/minimal expression of VDR in lymphocytes, which could have physiological implications and needs to be explored in future studies.

Weaknesses:<br /> The core message of the study relies on the role of vitamin D and its receptor in suppressing the Th2 response. However, there is scope for further dissection of relevant pathophysiological parameters in the in vivo experiments, which would enable stronger translation to allergic airway diseases like Asthma.

To a large extent, the authors have been successful in validating their results, although a few inferences could be reinforced with additional techniques, or emphasised in the discussion section (possibly utilising the ideas and speculative section offered by the journal).

The study inferences also need to be read in the context of the different sub-phenotypes and endotypes of Asthma, where the Th2 response may not be predominant. Moreover, the authors have referenced vitamin D doses for the murine models from the VDAART trials and performed the experiments in the second generation of animals. While this is appreciated, the risk of hypervitaminosis-D cannot be ignored, in view of its lipid solubility. Possibly comparison and justification of the doses used in murine experiments from previous literature, as well as the incorporation of an emphasised discussion about the side effects and toxicity of Vitamin D, is an important aspect to consider.

In no way do the above considerations undermine the importance of this elegant study which justifies trials for vitamin D supplementation and its effects on Asthma. The work possesses tremendous potential.

Reviewer #2 (Public Review):

Summary:<br /> This study seeks to advance our knowledge of how vitamin D may be protective in allergic airway disease in both adult and neonatal mouse models. The rationale and starting point are important human clinical, genetic/bioinformatic data, with a proposed role for vitamin D regulation of 2 human chromosomal loci (Chr17q12-21.1 and Chr17q21.2) linked to the risk of immune-mediated/inflammatory disease. The authors have made significant contributions to this work specifically in airway disease/asthma. They link these data to propose a role for vitamin D in regulating IL-2 in Th2 cells implicating genes associated with these loci in this process.

Strengths:<br /> Here the authors draw together evidence from multiple lines of investigation to propose that amongst murine CD4+ T cell populations, Th2 cells express high levels of VDR, and that vitamin D regulates many of the genes on the chromosomal loci identified to be of interest, in these cells. The bottom line is the proposal that vitamin D, via Ikfz3/Aiolos, suppresses IL-2 signalling and reduces IL-2 signalling in Th2 cells. This is a novel concept and whilst the availability of IL-2 and the control of IL-2 signalling is generally thought to play a role in the capacity of vitamin D to modulate both effector and especially regulatory T cell populations, this study provides new data.

Weaknesses:<br /> Overall, this is a highly complicated paper with numerous strands of investigation, methodologies etc. It is not "easy" reading to follow the logic between each series of experiments and also frequently fine detail of many of the experimental systems used (too numerous to list), which will likely frustrate immunologists interested in this. There is already extensive scientific literature on many aspects of the work presented, much of which is not acknowledged and largely ignored. For example, reports on the effects of vitamin D on Th2 cells are highly contradictory, especially in vitro, even though most studies agree that in vivo effects are largely protective. Similarly, other reports on adult and neonatal models of vitamin D and modulation of allergic airway disease are not referenced. In summary, the data presentation is unwieldy, with numerous supplementary additions, which makes the data difficult to evaluate and the central message lost. Whilst there are novel data of interest to the vitamin D and wider community, this manuscript would benefit from editing to make it much more readily accessible to the reader.

Wider impact: Strategies to target the IL-2 pathway have long been considered and there is a wealth of knowledge here in autoimmune disease, transplantation, GvHD etc - with some great messages pertinent to the current study. This includes the use of IL-2, including low dose IL-2 to boost Treg but not effector T cell populations, to engineered molecules to target IL-2/IL-2R.

Reviewer #1 (Public Review):

Hwang et al., report that LRRC23 is required for RS3 head assembly and sperm motility, and the truncating LRRC23 is associated with asthenozoospermia in humans. They identified an LRRC23 variant in a consanguineous Pakistani family with infertile males diagnosed as asthenozoospermia and found this variant leads to early termination of LRRC23 translation with loss of 136 amino acids at the C-terminus. They generated Lrrc23 mutant mice that mimic the predicted outcome in human patients and found the truncated LRRC23 specifically disorganizes RS3 and the junctional structure between RS2 and RS3 in the sperm axoneme, which causes sperm motility defects and male infertility. These dates try to elucidate the pathogenicity of LRRC23 in asthenozoospermia. The conclusions of this paper are mostly well supported by data, but many aspects of data analyses and data interpretations need to be improved.

1) The pathogenesis of truncating LRRC23 in asthenozoospermia needs to be further considered. The molecular mechanism of LRRC23 demonstrated in mice should be tested in patients with the LRRC23 variant. As it may be difficult to determine the structures of RS3 in the infertile male sperm, the LRRC23 localization should be observed in the sperm from patients with the LRRC23 variant.<br /> 2) The absence of the RS3 head in LRRC23Δ/Δ mouse sperm is not sufficient to support the specific localization of LRRC23 in RS3 head. Although LRRC23 might bind to RS head protein RSPH9, the authors state that "RSPH9 is a head component of RS1 and RS2 like in C. reinhardtii (Gui et al, 2021), but not of RS3" as the protein level and the localization of RSPH9 is not altered in LRRC23Δ/Δ sperm. Thus, the specific localization of LRRC23 in RS3 head should be further confirmed.<br /> 3) The interaction between LRRC23 and RSPH9 needs to be defined. AlphaFold models could help determine the likelihood of a direct interaction. In addition, the structure of the 96-nm modular repeats of axonemes from the flagella of human respiratory cilia has been determined (PMID: 37258679), and the localization of LRRC23 in RS could be further predicted.<br /> 4) The ortholog of the RSP15 may also be predicted or confirmed by using the reported structure in human respiratory cilia (PMID: 37258679). Whether the LRCC34 in RS2 is LRRC34?

Reviewer #2 (Public Review):

Summary:<br /> The present study explores the molecular function of LRRC23 in male fertility, specifically in the context of the regulation of spermiogenesis. The author initiates the investigation by identifying LRRC23 mutations as a potential cause of male sterility based on observations made in closely related individuals affected by asthenozoospermia (ASZ). To further investigate the function of LRRC23 in spermatogenesis, mutant mice expressing truncated LRRC23 proteins are created, aligning with the identified mutation site. Consequently, the findings confirm the deleterious effects of LRRC23 mutations on sperm motility in these mice while concurrently observing no significant abnormalities in the overall flagella structure. Furthermore, the study reveals LRRC23's interaction with the RS head protein RSPH9 and its active involvement in the assembly of the axonemal RS. Notably, LRRC23 mutations result in the loss of the RS3 head structure and disruption of the RS2-RS3 junction structure. Therefore, the author claimed that LRRC23 is an indispensable component of the RS3 head structure and suggests that mutations in LRRC23 underlie sterility in mice.

Strengths:<br /> The key contribution of this article lies in confirming LRRC23's involvement in assembling the RS3 head structure in sperm flagella. This finding represents a significant advancement in understanding the complex architecture of the RS3 structural complex, building upon previous studies. Moreover, the article's topic is interesting and originates from clinical research, which holds significant implications for potential clinical applications.

Weaknesses:<br /> 1. While the author generated mutant mice expressing truncated LRRC23 proteins, the expression of these truncated proteins was not detected in sperm. This implies that, in terms of sperm structure, the mutant LRRC23 protein behaves similarly to the complete knockout of the LRRC23 protein, which has been previously reported and characterized (Zhang et al., 2021).

2. This reviewer questions the proposal that LRRC23 is an integral component of RS3, as the results indicate not only the loss of the RS3 head structure but also an incomplete RS2-RS3 junction structure. In addition, the interaction of LRRC23 with RSPH9 alone does not fully explain its involvement solely in RS3 assembly. Additional evidence is required to examine the influence of LRRC23 on the RS2-RS3 junction.

3. The article does not explore how these mutations affect the flagella structure in human sperm, which needs further study. Expanding the study to include human sperm structure would undoubtedly enhance the quality of the article.