Reviewer #3 (Public Review):

In this study, the authors present the first comprehensive transcriptome map of the human locus coeruleus using two independent but complementary approaches, spatial transcriptomics and single nucleus RNA sequencing. Several canonical features of locus coeruleus neurons that have been described in rodents were conserved, but potentially important species differences were also identified. This work lays the foundation for future descriptive and experimental approaches to understand the contribution of the locus coeruleus to healthy brain function and disease.

This study has many strengths. It is the first reported comprehensive map of the human LC transcriptome, and uses two independent but complementary approaches (spatial transcriptomics and snRNA-seq). Some of the key findings confirmed what has been described in the rodent LC, as well as some intriguing potential genes and modules identified that may be unique to humans and have the potential to explain LC-related disease states. The main limitations of the study were acknowledged by the authors and include the spatial resolution probably not being at the single cell level and the relatively small number of samples (and questionable quality) for the snRNA-seq data. Overall, the strengths greatly outweigh the limitations. This dataset will be a valuable resource for the neuroscience community, both in terms of methodology development and results that will no doubt enable important comparisons and follow-up studies.

Major comments:

Overall, the discovery of some cells in the LC region that express serotonergic markers is intriguing. However, no evidence is presented that these neurons actually produce 5-HT.

Concerning the snRNA-seq experiments, it is unclear why only 3 of the 5 donors were used, particularly given the low number of LC-NE nuclear transcriptomes obtained, why those 3 were chosen, and how many 100 um sections were used from each donor. It is also unclear if the 295 nuclei obtained truly representative of the LC population or whether they are just the most "resilient" LC nuclei that survive the process.

The LC displays rostral/caudal and dorsal/ventral differences, including where they project, which functions they regulate, and which parts are vulnerable in neurodegenerative disease (e.g. Loughlin et al., Neuroscience 18:291-306, 1986; Dahl et al., Nat Hum Behav 3:1203-14, 2019; Beardmore et al., J Alzheimer's Dis 83:5-22, 2021; Gilvesy et al., Acta Neuropathol 144:651-76, 2022; Madelung et al., Mov Disord 37:479-89, 2022). It was not clear which part(s) of the LC was captured for the SRT and snRNAseq experiments.

The authors mention that in other human SRT studies, there are typically between 1-10 cells per expression spot. I imagine that this depends heavily on the part of the brain being studied and neuronal density, but it was unclear how many LC cells were contained in each expression spot.

Regarding comparison of human LC-associated genes with rat or mouse LC-associated genes (Fig. 2D-F), the authors speculate that the modest degree of overlap may be due to species differences between rodents and human and/or methodological differences (SRT vs microarray vs TRAP). Was there greater overlap between mouse and rat than between mouse/rat and human? If so, that is evidence for the former. If not, that is evidence for the latter. Also would be useful for more in-depth comparison with snRNA-seq data from mouse LC: https://www.biorxiv.org/content/10.1101/2022.06.30.498327v1.

The finding of ACHE expression in LC neurons is intriguing, especially in light of work from Susan Greenfield suggesting that ACHE has functions independent of ACH metabolism that contributes to cellular vulnerability in neurodegenerative disease.

High mitochondrial reads from snRNA-seq can indicate lower quality. It was not clear why, given the mitochondrial read count, the authors are confident in the snRNA-seq data from presumptive LC-NE neurons.

Reviewer #3 (Public Review):

The manuscript by Sidhaye et al. aims to integrate proteomic and transcriptomic analyses of human stem cell-derived cortical brain organoids to identify post-transcriptional regulatory mechanisms during human cortical development. The authors use an innovative and useful dual-reporter strategy to isolate NPCs and neurons separately and integrate proteomic and transcriptomic analyses in each cell type. The data analysis is robust and identifies gene modules with cell class specificity.

While there is no large overlap between the proteomic and transcriptomic datasets, the authors focus additional experiments on one candidate pathway, mTOR-mediated regulation of translation in progenitors, and validate this pathway's role in progenitor development.

The authors also identified a stress-related role for processes in corticogenesis, although, without comparison to human tissue, it's possible that some of the results are due to the artificial nature of the organoids as they have been reported to have elevated stress (Bhaduri et al.,).

The data is from organoids from one human stem cell line, the female H9 human embryonic stem cell line and so it is critical to validate the results on 1-2 additional stem cell lines, to rule out the possibility that these results are unique to this one cell line.

The major concerns in this paper can be addressed through validation of the results in other systems (e.g. human tissue) or in additional cell lines.

The results provide a valuable resource and address some of the limitations of current organoid and tissue single-cell data by focusing on proteomics.

Reviewer #3 (Public Review):

The paper by Rahsepar et al. employed a closed-loop optogenetic approach to stimulate mouse dentate gyrus (DG) 'engram cells' at different phases of the ongoing theta rhythm. While stimulation of DG engram cells in fear conditioning paradigms has been conducted several times before (with similar results to those presented here), the current approach constitutes a significant methodological improvement over typical 'open loop' designs. The authors first characterize the performance of their closed-loop theta phase prediction method and show that it outperforms constant frequency stimulation in achieving a theta phase-specific stimulation, albeit with some limitations. A prominent theory in the field has proposed that memory encoding and recall preferentially take place at the peak and trough of theta respectively. Based on this framework, the authors compared the behavioral and physiological effects of stimulating engram cells at either the theta peak or trough as well as with constant frequencies. They found that, as predicted by the theory, stimulation at the theta through was the most effective in inducing enhanced fear memory recall (measured as freezing during re-exposure to a neutral context). Finally, the authors examined theta-gamma hippocampal LFP dynamics to provide physiological support for the observed behavioral differences of the different stimulation patterns.

Overall, this work illustrates an interesting methodological development that will be of relevance for future studies conducting manipulations of engram cells and provides additional experimental support for an influential theory in the memory field. Experiments are well conducted and the results presented support the main interpretation of the authors, but several aspects of the interpretation and discussion of the work need to be improved. Likewise, several aspects of data analysis and interpretation, in particular in reference to hippocampal oscillations and regional differences need to be improved.

Reviewer #3 (Public Review):

Elimination of aberrant cells from epithelial tissues is important for normal tissue physiology. Here the authors study a specific type of cell elimination that is dedicated to the removal of miss-specified cells. This type of elimination is dependent on interface contractility. The authors now identified an important role for JNK signaling, which is activated at this interface, where contractility is highest.

Strength: The authors use a large variety of cell specification mutants and different drivers to manipulate cell specification. Together, this shows that the observed phenotypes are of a general nature and not dependent on single signaling pathways.<br /> Weakness: Quantitative characterization of much of the data is missing. Only single representative images are shown for many of the experiments. The manuscript would strengthen massively when these images are supported with a quantitative measurement. For example (but not limited to), TRE-GFP in correctly vs mis-specified clones in Figure 2K-L, TRE-GFP intensity in Figure 3, clonal analysis in Figure 5.

Type of elimination:<br /> The authors describe a very distinct and specific phenotype of smooth rounded clones with high contractility. It is obvious that this is, on a phenotypic scale, different from other types of cell elimination, such as live extrusion and cell-cell competition. Throughout the manuscript the authors emphasize that the underlying nature of interface contractility is different to cell competition. Because cell competition "responds to a clearly defined fitness gradient between two neighbouring cells, which ensures that always the aberrant loser cell dies, independent of spatial context." And "linking apoptosis to a fixed loser genotype". However, this only holds true for the classical types of cell competition (e.g. Minute), while many examples of cell competition have been reported where elimination of cells is not set in stone, but also highly context dependent. For example, HRasV12 expressing cells are eliminated from epithelia in mice on a normal diet, while a high fat diet prevents their elimination (Sasaki et al, Cell Reports 2018). Without the experimental support that relative differences in cell specification do not cause a difference in cellular fitness it is hard to grasp the conceptual difference. Instead, the concept reported by the authors is better described as a variety of cell competition.

Clone size<br /> The authors claim that remove aberrant cells by interface contractility is dependent on clone size and only occurs when aberrant cells are the minority compared to the surrounding tissue. Currently, there is no data in the manuscript that supports this claim. The only analysis of tissues containing a majority of miss-specified cells (Figures 2I-2J) shows a bilateral activation of JNK, similar to a minority of miss-specified cells. To support the claim that the phenotype is size dependent further analysis of clone size in relation to apoptosis and JNK activation is essential.

JNK and cell autonomous regulation:<br /> The authors validate that expression of TRE-GFP is dependent on JNK signaling, through over-expression of a dominant negative variant of the JNK kinase (BSKDN) in clones of miss-specified cells (ey or tkv). This experiment nicely shows that activation of JNK in surrounding WT cells is not altered. This furthermore illustrates that JNK signaling in the miss-specified cells is not needed for activation of JNK in their neighbors. However, this does not support the conclusion that JNK is activated in a cell autonomous fashion in either of these populations. The interaction of the two cell types can still cause signaling, but through inhibition of one of the kinases within the pathway, this just does not lead to downstream activation of TRE-GFP. In fact, one could argue that the expression of TRE-GFP is not cell-autonomous, because tkvCA clones that are not mis-specified (within dad4-LacZ regions) do not show induction of TRE-GFP (Fig 2L). The only way to untangle cell autonomous vs non-autonomous effects is through manipulation of upstream communication between the different cell populations. Such experiments, for example manipulation of contractility, are likely beyond the scope of this study. Therefore, I would suggest rephrasing this paragraph.

Apoptosis:<br /> A large part of the manuscript is dedicated to the characterization of elimination of miss-specified cells through apoptosis. This process is important for maintenance of tissue integrity and a crucial part of the manuscript. Some conclusions are not fully supported by the data represented in the current form of this manuscript;<br /> The authors claim that fkh- and ey-expressing cells are not eliminated when apoptosis is blocked by expression of p35. This is based on analysis of apical vs basal clone count (Figure 1T). This analysis reflects a combination of induction efficiency and clone retention. Therefore, information on the cellular behavior within clones is lacking and only provides information on survival of cells when complete clones are eliminated. The conclusion should be supported by additional analysis on clone size and total clone area, ideally based on cell number. In addition, statistical analysis of conditions with and without expression of p35 should be included.<br /> Furthermore, the analysis of apoptosis at clonal interfaces does not support the conclusion that "many, but not all apoptotic events occur at interfaces". Overall, there is increased apoptosis within clones compared to wild-type tissue. However, the rates of apoptosis are higher (ey, Fig S5B) or similar (fkh and tkvCA, Fig 5B-C) in clonal cells compared to clonal interface cells. The authors should revise these statements or provide more compelling analysis.

Reviewer #3 (Public Review):

This manuscript describes a villin-2a-Flp-based intersectional strategy for selectively targeting EEC in the intestine and uses it to examine the function of subsets. The approach for targeting select subsets of enteroendocrine cells described here will be important for neuroscientists, endocrinologists, microbiologists, and other scientists studying nutritional biology. Here single-cell sequencing is used, primarily, to confirm what was already known about EEC classes at a transcriptomic level. The intersectional approach described here has the potential to provide broad access to EECs. However, from the relatively limited characterization of targeted EEC cells, it appears that the genes that have been combined with the villin driver largely fail to selectively target transcriptomically defined cell types. Thus, at present, this manuscript fails to convincingly target transcriptome-defined enteroendocrine cell types, and conclusions on gut motility, feeding behavior, and flavor avoidance are overstated.

Some aspects of the study are compelling including the use of villin drivers as a means to restrict recombination to the epithelium containing EECs. The single-cell data (although not unique to this study) proved a basis for a better understanding of EECs and also their developmental specification. The charcoal-based gut motility assay appears valuable (although the results are perhaps not surprising given what was already known). In addition, some of the care taken characterizing extra-EEC expression is commendable. However, the manuscript is difficult to read with important details scattered in different figures and text (e.g., the characterization of expression patterns of the various lines). Moreover, whereas some things like the genetic makeup of the lines are always specified in full (excruciating) details, the expression patterns of the various lines are often casually dealt with e.g., describing separate targeting of L and I cells despite no evidence that this is actually being done. I would hope that the authors will address these issues and devote significant attention to making the paper more accessible to its readers.

Reviewer #3 (Public Review):

Porter, Li et al. investigate the roles of SA1 and SA2 in cohesin loading, and as well as roles that are independent of the cohesin ring. Using co-IP and imaging approaches, they show that both SA1 and SA2 interact with CTCF and they use auxin-induced degradation of Rad21 to show that this is only partially dependent on cohesin. The authors next use IP followed by mass spectrometry to identify additional SA binding partners, which include many RNA binding proteins including factors involved in RNA modification, export, splicing, and translation. Unlike the interaction with CTCF, these interactions are enhanced in cohesin depletion conditions. In fact, CLIP experiments show that SA binds RNA directly, in an R-loop-dependent manner. This co-localisation of SA with R-loops is confirmed by STORM.

To address whether SA proteins are involved in cohesin loading, the authors measure chromatin-bound cohesin levels after auxin washoff in the presence and absence of NIPBL and SA. They find that SA knockdown has a comparable impact on cohesin binding to chromatin compared to NIPBL knockdown, and that combining the knockdowns reduces cohesin loading further. This newly synthesised cohesin co-localises with R-loop domains by STORM, and this localisation is sensitive to RNAse H. The authors propose that SA promotes cohesin loading at R-loops, and that SA1 is the main contributor to this. Finally, they provide evidence that differential usage of a conserved exon between SA1 and SA2 may be responsible for differences between SA1 and SA2 in this system, as SA2 with this exon included has higher RBP binding and is more enriched at R-loops.

This paper provides convincing evidence that SA proteins associate with R-loops and various RNA-binding proteins, suggesting that they may have a cohesin-independent role related to RNA processing or R-loops specifically. Additionally, the paper provides evidence for a NIPBL-independent role of SA proteins at cohesin loading, which may occur at R-loops. These results will be of broad interest in relation to chromatin organisation and the role of SA proteins/cohesin in cancer.

Overall, the experiments are thorough and well-controlled, including some nice validations such as the use of siRNA-mediated cohesin depletion and a different cell line to confirm the SA-CTCF interactions. In many cases STORM imaging is used to provide complementary evidence to western blots / IP experiments.

However, one weakness is that imaging approaches can only address co-localisation. Although the vast majority of cohesin complexes will be bound to DNA, imaging approaches cannot distinguish between chromatin-bound and unbound nuclear proteins. For example, although cohesin co-localises with R-loops and SA after auxin washoff, and this is dependent on R-loops, it is not possible to tell from imaging whether this cohesin is chromatin bound and whether this is bound to specific genomic loci that contain R-loops or just associated with them in 3D space. Therefore it would be preferable to have a clearer distinction in terminology depending on whether the evidence discussed can demonstrate chromatin binding (e.g. chromatin fractionation experiments), or just co-localisation.

Reviewer #3 (Public Review):

Although initially discovered as axon guidance molecules in the nervous system, Semaphorins, signaling through their receptors the Neuropilins and Plexins, regulate a variety of cell-cell signaling events in a variety of cell types. In addition, cells often express multiple Semas and receptors. Thus, one important question that has yet to be adequately understood about these important signaling proteins is: how does specificity of function arise from a ubiquitously expressed signaling family?

This study addresses that important question by investigating the role of cysteine palmitoylation on the localization and function of the Neuropilin-2 (Nrp-2) receptor. It was already known that Sema3F signaling through a complex of Nrp-2 and Plexin-A3 regulates pruning of dendritic spines in cortical neurons while Sema3A signals through Nrp-1/PlexA4 to regulate dendritic arborization. The major finding of this study which is well-supported by the data is that palmitoylation of Nrp-2 regulates its cell surface clustering and dendritic spine pruning activity in cortical neurons. Interestingly, palmitoylation of Nrp-1 at homologous residue does not appear to regulate its localization or known neuronal function.

A clear strength of this manuscript is the many techniques that are utilized to examine the question: this study represents a tour de force of biochemical, molecular, genetic, pharmacological and cell biological assays performed both in vitro and in vivo. The authors carefully dissect the function of distinct palmitoylated cysteine residues on Nrp-2 localization and function, concluding that palmitoylation of juxtamembrane cysteines predominates over C-terminal palmityolyation for the Nrp-2 dependent processes assayed in this study. The authors also demonstrate that a specific palmityl transferase (DHHC15) acts on Nrp-2 but not Nrp-1 and is required for Nrp-2 clustering and dendritic spine pruning. These findings are important because they demonstrate one mechanism by which different signaling pathways, even from a related family of proteins, can achieve signaling specificity in the cell.

A minor weakness of the paper is that one would like to see a connection between palmitoylation-dependent cell membrane clustering of Nrp-2 on the cell surface and Nrp-2 regulation of dendritic spine pruning. Although the two phenotypes frequently correlate in the data presented, there are a few notable exceptions: e.g. Nrp-2TCS forms larger clusters in cortical neurons while Nrp-2FullCS is diffuse on the cell surface; both mutants affect spine pruning. In the future, it would also be interesting to know if increased clustering of Nrp-2 was observed at spines that were eliminated, for example. Nonetheless this manuscript represents an important advance in our understanding of synaptic pruning and cellular mechanisms that constrain protein surface localization and signaling pathways.

Reviewer #3 (Public Review):

This manuscript builds upon prior work showing that alpha-actinin-2 binds to the regulatory domain of the major postsynaptic protein kinase, CaMKII. The authors report the structure of a complex between the relevant domain in alpha-actinin-2 and a peptide based on the CaMKII regulatory domain. Data are presented indicating that the interaction of the NMDA receptor GluN2B subunit with the CaMKII catalytic domain stabilizes the complex with alpha-actinin-2. Furthermore, the authors present proximity ligation assay (PLA) data obtained in cultured neurons demonstrating that NMDA receptor activation strongly enhances the colocalization of CaMKII with alpha-actinin-2. Data obtained using mutated proteins indicate that this co-localization is mediated by the interaction characterized structurally.

Strengths:

Significant strengths of this work are:<br /> 1. The high-quality structures of the complex that are reported.<br /> 2. Integration of these findings with the much better-studied complex of CaMKII and GluN2B.<br /> 3. The convincing PLA analyses show that NMDA receptor activation increases CaMKII colocalization with alpha-actinin-2.<br /> 4. The careful comparisons of data from these new studies with data reported in previous publications.

Weaknesses:

Despite the significant strengths of the work, there are some gaps/weaknesses.<br /> 1. Although there is abundant published evidence that activated CaMKII colocalizes with NMDA receptors, the evidence for the involvement of GluN2B in the CaMKII-alpha-actinin-2 complex in neurons is lacking.<br /> 2. The evidence supporting a role for the EF1 and EF2 domains of alpha-actinin-2 in binding to CaMKII is not very convincing.<br /> 3. CaMKII autophosphorylation at multiple sites plays an important role in regulating the subcellular localization of CaMKII, but the role of autophosphorylation is not explored here.

Taken to together the manuscript describes novel data that provide a significant extension to prior work, and the data convincingly, but perhaps only partially, support an interesting proposed model for the control of CaMKII targeting in spines.

This more sophisticated delineation of the mechanisms underlying CaMKII targeting synapses will be of interest to the broader field of investigators studying the molecular basis for the regulation of excitatory synaptic transmission, learning, and memory.

Reviewer #3 (Public Review):

This manuscript entitled "PASK relays metabolic signals to mitotic Wdr5-APC/C complex to drive exit from self-renewal" by Xiao et al presents an interesting story on the role of PASK in the control of muscle stem cell fate by controlling the decision between self-renewal and differentiation. While the biochemistry presented is fairly compelling, the experiments revolving around the myogenic cells are lacking in quality and data.

Major concerns:

1. The isolation method used by this group to isolate muscle stem cells is inappropriate for the experiments used and may contribute to the misinterpretation of some of the results. It is simply a preplating method that results in a very heterogenous cell population in terms of cell type, comprised of numerous fibroblasts. While preplating can be used to isolate muscle stem cells and culture them as myoblasts, it takes days of growth and multiple rounds of passaging that are not used in this paper in order to get a more pure population of myogenic cells. This would also explain the high number of Pax7 negative cells in their primary myoblast experiments (~50% in some conditions) as they are most likely fibroblasts, which the authors could show by staining for fibroblast markers. The increase in Pax7 cells in certain conditions could also simply be due to the loss of contaminating cell types due to the treatment. Every single experiment that was performed on myoblasts must be redone using a more appropriate cell isolation method (i.e. FACS) or by culturing these isolated cells for a much longer period of time to eventually get a more pure cell population. As it stands, none of the data from the primary myoblast experiments are trustworthy.<br /> 2. The authors possess a genetic mouse model where PASK is knocked out. However, the mouse model is never described and the paper that is referenced also does not describe it. Please detail your mouse model.<br /> 3. The majority of experiments are performed on C2C12 cells. While C2C12s are adequate for biochemistry and proof of concepts, when it comes to biological significance primary myoblasts should be used. While the authors try to explain this use by claiming that primary myoblasts undergo precocious differentiation that can be avoided by using an appropriate growth media (F10, 20% FBS, 1% P/S, 5ng/mL of bFGF).<br /> 4. The authors possess a genetic mouse model, yet performed RNA-Seq on C2C12 myoblasts that were either untreated or treated with a PASK inhibitor. It would be much more informative and valuable to sequence the primary myoblasts from WT and PASK KO mice, thereby providing a more biologically relevant model.<br /> 5. The KO mouse model is rarely used and the cells isolated from it would be very useful in determining the biological role of PASK in muscle cells. The authors should isolate WT and KO cells and perform basic muscle functional experiments such as EDU incorporation for proliferation, and fusion index for differentiation to see whether the loss of PASK has an effect on these cells.<br /> 6. The authors never look at quiescent muscle stem cells and early activated muscle stem cells in terms of PASK protein expression and dynamics. The authors should isolate EDL myofibers and stain for PASK and PAX7 at 0, 24, 48, and 72-hour post isolation. This would allow the authors to quantify the changes in PASK expression and cell localization, as well as confirm the number of muscle stem cells in WT and KO mice, during quiescence and during the process of muscle stem cell activation, proliferation, and differentiation in a near in vivo context.<br /> 7. Contrary to their claim, MyoD is not a stemness/self-renewal gene.<br /> 8. The authors state that PASK is necessary for exit from self-renewal and establishment of a progenitor population but this is a vast overstatement. In the genetic KO mouse model, the mice are able to regenerate their muscle after injury, therefore PASK cannot be a necessary protein for the formation of progenitor cells.<br /> 9. In numerous figure panels, the y-axis represents the # of cells, rather than a percentage or ratio. This is uninformative as the number of cells will never be the same between conditions and experiments. These panels need to be replaced with a more appropriate y-axis.

Reviewer #3 (Public Review):

In this paper, the authors model brain responses for visual objects and the effect of attention on these brain responses. The authors compare three models that have been studied in the literature to account for the effect of attention on brain responses to multiple stimuli: a normalization model, a weighted average model, and a weighted sum model.

The authors presented human volunteers with images of houses and bodies, presented in isolation or together, and measured fMRI brain activity. The authors fit the fMRI data to the predictions of these three models, and argue that the normalization model best accounts for the data.

The strengths of this study include a relatively large number of participants (N=19), and data collected in a variety of different visual brain regions. The blocked design paradigm and the large number of fMRI runs enhance the quality of the dataset.

Regarding the interpretation of the findings, there are a few points that should be considered: 1) The different models that are being studied have different numbers of free parameters. The normalization model has the highest number of free parameters, and it turns out to fit the data the best. Thus, the main finding could be due to the larger number of parameters in the model. The more parameters a model has, the higher "capacity" it has to potentially fit a dataset. 2) In the abstract, the authors claim that the normalization model best fits the data. However, on closer inspection, this does not appear to be the case systematically in all conditions, but rather more so in the attended conditions. In some of the other conditions, the weighted average model also appears to provide a reasonable fit, suggesting that the normalization model may be particularly relevant to modeling the effects of attention. 3) In the primary results, the data are collapsed across five different conditions (isolated/attended for preferred and null stimuli), making it difficult to determine how each model fares in each condition. It would be helpful to provide data separately for the different conditions.

Reviewer #3 (Public Review):

Mann and colleagues have generated a knock-in mouse model carrying a recently identified mutation in the Mfn2 gene that leads to a syndrome of severe upper body adipose overgrowth in humans (Mfn2R707W). The goal was to gain a better mechanistic understanding on how this mutation leads to such a dramatic phenotype in humans. The authors consistently demonstrate how the knock-in mutation leads to abnormalities in mitochondrial shape, mtDNA content, as well as in the abundance of some mitochondrial proteins, most notably in brown adipose tissue. The authors detect some stress response signatures, which could explain the decreased leptin and adiponectin levels observed in the knockin mice.

The authors have to be praised for their effort in trying to provide mechanistic insights to such a rare condition. This work constitutes a real tour de force in the characterization of Mfn2R707W mice. The path, however, was full of surprises. On one side, the knockin mouse model fails to recapitulate multiple aspects of the human syndrome. This is, of course, beyond the control of the researchers, but somehow tells us that there are some elements missing in our understanding of the effects of this Mfn2 mutation at the cellular level (not just organismal), and on why it impacts so much adipose tissues. A second layer of complexity is that the authors find an interesting connection between Mfn2R707W, the integrated stress response and a severe decrease in the expression of leptin and adiponectin. However, whether these elements have any causal role in the human syndrome or in the phenotypes observed in the mice, remains an open question.

Reviewer #3 (Public Review):

The manuscript by Barthe et al compares the effects derived from the application of isoprenaline (Iso) or isoprenaline covalently linked to PEG (PEG-Iso) on adult rat ventricular myocytes (ARVM). Iso is a well-characterized β-AR agonist and the authors work under the assumption that PEGylation of Iso prevents it from accessing the T-tubules. Therefore, due to its larger size, PEG-Iso is only able to activate β-ARs located on the outer surface membrane (OSM), and any additional effect observed by Iso stimulation is attributed to the activation of β-ARs located in T-tubules. First, the authors determined that the affinity of PEG-Iso for β-ARs is about 100 times lower than the one of Iso. Then, they analyze the effects of Iso (10 nM) and PEG-Iso (1 µM) on calcium channel currents, contractility, calcium transients, and cytosolic and nuclear PKA activity. They only found a stronger effect of Iso on nuclear pKA activity. Therefore they conclude that, while OSM β-ARs stimulation mainly results in positive inotropy and lusitropy, T-tubules ARs stimulation mainly results in increased nuclear pKA activity.

Overall the manuscript is well written and the findings are biologically important from the perspective of understanding the mechanism of β-AR stimulation as well as in assigning the functional contribution of β-ARs in the OSM and in the T-tubules. However, the major conclusion is not strongly supported by the data. The interpretation of the results is all based on the assumption that PEG-Iso is excluded by the T-tubules, but no experiment presented here rigorously demonstrates this.

1. The only indication that PEG-Iso may be excluded by the T-tubules is one confocal image in which FITC or PEG-FITC were applied on ARVM. No experiment has been performed to assess if PEG-Iso is indeed not able to enter the T-tubules.<br /> The treatment of ARVM with neuraminidase made the T-tubules accessible to PEG-FITC. If the authors could demonstrate that neuraminidase treatment followed by PEG-Iso would result in similar nuclear pKA activity as Iso, this would strengthen their conclusion.<br /> 2. The fact that PEG-Iso treatment resulted in a lower increase of intracellular cAMP (Figure 3) could also be due to the activation of a smaller fraction of β-ARs, independent of their localization.

Reviewer #3 (Public Review):

The authors use hydrogen-deuterium exchange mass spectrometry (HDXMS) to assess the dynamics of several relevant mutant forms of SARS-CoV 2 Spike protein including the most recent Omicron variant. The Spike protein is heavily glycosylated and is a trimer so is a very difficult protein to study by HDXMS. The authors confirm the glycosylation sites, which can't be covered by the HDXMS experiment, yet they still manage to cover nearly 50% of the sequence revealing many interesting changes in dynamics in the prevalent circulating mutant forms. The beautiful HDXMS data reveal consistent trends as SARS-CoV2 mutates to survive including stabilization of the stalk and increased dynamics of the N-terminal domain where ACE2 receptor binding occurs. The authors incubate the protein at 37C and discover additional stabilization of the trimer occurs under these conditions explaining a lot of conflicting data in the literature done at different temperatures. These results have profound implications for the development of small molecule inhibitors of the Spike protein-ACE2 interaction.

Reviewer #3 (Public Review):

This paper shows that RecA-mediated recombination between two insertion sequence elements can drive the duplication of a large (~200 kb) region that leads to a growth advantage in biofilms, but a disadvantage during planktonic growth. The experiments presented are incisive and definitive. While IS elements are more commonly implicated in gene inactivation, this paper reveals that they can provide a benefit by driving a reversible genome modification in the form of a large-scale duplication. The paper should appeal to readers interested in mechanisms of genome evolution, phase variation, biofilms, and bacterial pathogenesis. The final model is convincing and also lays the foundation for future studies aimed at identifying which gene(s) in the duplicated region are ultimately responsible for the biofilm growth benefit. The paper also serves to correct this lab's prior interpretation of related data in which they concluded that the genomic region being investigated excised and circularized. They very nicely lay out what led them to conclude this previously and how their new data led to a revised model, as well as many additional, important new insights. To be clear, there were no issues with the prior data, just the interpretation/model. So in my view, this is exactly how science should unfold - new data can and should lead to revised models. I applaud the authors for laying this trajectory out in such a straightforward, open manner.

Reviewer #3 (Public Review):

In this manuscript, the authors consider a rate model with recurrently connections excitatory-inhibitory (E-I) modules coupled by distance-dependent excitatory connections. The rate-based formulation with adaptive threshold has been previously shown to agree well with simulations of spiking neurons, and simplifies both analytical analysis and simulations of the model. The cycles of beta oscillations are driven by fluctuating external inputs, and traveling waves emerge from the dephasing by external inputs. The authors constrain the parameters of external inputs so that the model reproduces the power spectral density of LFPs, the correlation of LFPs from different channels and the velocity of propagation of traveling waves. They propose that external inputs are a combination of spatially homogeneous inputs and more localized ones. A very interesting finding is that wave propagation speed is on the order of 30 cm/s in their model which is consistent with the data but does not depend on propagation delays across E-I modules which may suggest that propagation speed is not a consequence of unmylenated axons as has been suggested by others. Overall, the analysis looks solid, and we found no inconsistency in their mathematical analysis. However, we think that the authors should discuss more thoroughly how their modeling assumptions affect their result, especially because they use a simple rate-based model for both theory and simulations, and a very simplified proxy for the LFPs.

The authors introduce anisotropy in the connectivity to explain the findings of Rubino et al. (2006), showing that motor cortical traveling waves propagate preferentially along a specific axis. They introduce anisotropy in the connectivity by imposing that the long range excitatory connections be twice as long along a given axis, and they observe waves propagating along the orthogonal axis, where the connectivity is shorter range. Referring specifically to the direction of propagation found by Rubino et al, could the authors argue why we should expect longer range connections along the orthogonal axis? In fact, Gatter and Powell (1978, Brain) documented a preponderance of horizontal axons in layers 2/3 and 5 of motor cortex in non-human primates that were more spatially extensive along the rostro-caudal dimension as compared with the medio-lateral dimension, and Rubino et al. (2006) showed the dominant propagation direction was along the rostro-caudal axis. This is inconsistent with the modeling work presented in the current manuscript.

The clarity and significance of the work would greatly improve if the authors discussed more thoroughly how their modeling assumptions affect their result. In particular, the prediction that external inputs are a combination of local and global ones relies on fitting the model to the correlation between LFPs at distant channels. The authors note that when the model parameter c=1, LFPs from distant channels are much more correlated than in the data, and thus have to include the presence of local inputs. We wonder whether the strong correlation between distant LFPs would be lower in a more biologically realistic model, for example a spiking model with sparse connectivity and a spiking external population, where all connections are distant dependent. While the analysis of such a model is beyond the scope of the present work, it would be helpful if the authors discussed if their prediction on the structure of external inputs would still hold in a more realistic model.

Reviewer #3 (Public Review):

Ras mutations are found in almost 25 percent of cancer patients. It has been difficult to directly target Ras proteins due to the lack of druggable pockets on the surface of the protein and the extremely high binding affinity of nucleotides to Ras proteins. Recently a mutant specific irreversible drug that targets the mutation G12C has been FDA approved. This drug binds to a shallow pocket on the surface of Ras and attacks the G12C mutation irreversibly. Another approach is to compete with the nucleotides bound to Ras. An attempt to generate nucleotide competitors that can take advantage of the G12C mutant has been proposed. Nevertheless, these published competitors had much lower affinities compared to endogenous nucleotides which would hinder the covalent modification in the presence of other nucleotides.

To overcome this, the authors propose to introduce a warhead in the ribose ring. Indeed, this modification did not affect the reversible binding affinity of these nucleotides to Ras wild type, in comparison to GDP and GTP. This finding represents a new opportunity to target G13C ras by competing with the nucleotides in cells. The authors support their claims with the appropriate in vitro experiments. Nevertheless, these experiments were performed at non physiologically high pH (9.5) and those compounds were not able to cross the cellular membrane. Thus, it is too early to draw conclusions regarding the appropriateness of the approach and whether it will prove successful in cells or if it will have medical application.

Reviewer #3 (Public Review):

This study by Aggad, Pujol, and colleagues provides some exciting new insights into a largely overlooked organelle/structure present in C. elegans epidermial cells, the "meiosome". Although noted by several previous researchers, this folded-membrane structure was never fully characterized. In particular, the authors provide an important and thorough characterization of meiosome morphology during development. The authors also provide data suggesting that meiosomes may function to provide attachment points between the epidermis and overlying cuticle, although this portion was less clear cut. In addition, the authors show that certain cuticle collagens can affect the morphology and position of meiosomes in addition to the formation of molting-associated actin cables. Some of these latter results, which suggest an 'outside-in' type of patterning regulation, run counter to certain previous models.

The major strengths of the paper are the novelty of describing a 'new organelle' and the thoroughness and clarity of the morphological analysis. The various EM studies were particularly well done and likely required a good deal of technical development, which may be of use to others in the field. One clear weakness is that it's not currently clear if the reported cuticle detachment defect is due to altered meiosomes, to the altered cuticle composition, or perhaps both, and thus the exact function(s) of meiosomes is left open. Other concerns include the use of extrachromosomally expressed VHA-5::GFP as a meiosome-specific marker. Although this could certainly be the case, it wasn't proven.

Reviewer #3 (Public Review):

In this paper, the authors examine the fate of exophers ejected from C. elegans neurons overexpressing a presumably aggregated mCherry protein. They show that exophers are taken up by adjacent hypodermal cells, split into smaller fragments, and eventually degraded by lysosome fusion. They identify a number of small GTPases and accessory components, as well as the phagocytic receptor (CED-1) and the likely eat-me signal (phosphatidylserine).

The manuscript follows up on previous exopher work from some members of the current collaboration, and provides a detailed analysis of exopher fate, that will likely be useful for understanding similar events in other settings. The studies are well done, the images and data are convincing, and the interpretations are generally appropriate.

Reviewer #3 (Public Review):

The manuscript " S-adenosylmethionine synthases specify distinct H3K4me3 populations and gene expression patterns during heat stress " by Godbole et al proposes a novel mechanism by which different S-adenosylmethionine (SAM) synthase enzymes exhibit specificity towards target sequences, thereby providing a layer of control over H3K4 trimethylation (H3K4me3) in Caenorhabditis elegans. The authors detail an extensive investigation of the function of two C. elegans SAM synthase enzymes, SAMS-1 and SAMS-4. They provide evidence that mutation or knockdown of these two enzymes affected gene expression of distinct gene sets and that loss of these enzymes has opposite effects on survival under heat stress. These differential effects are linked to differential effects on histone modification H3K4me3 of specific target gene sets. It is unclear from this work how exactly this specificity may be achieved and some of the data regarding the role of other components of the methylation machinery are somewhat superficial and confusing. Nevertheless, the study suggested a novel mechanism by which H3K4me3 of specific gene sets may be controlled and this mechanism is novel and potentially important.

Reviewer #3 (Public Review):

In this article, the authors examined color evolution in the kingfishers, a group of birds that have achieved a spectacular diversity of colors and color patterns as they have diverged across the continents and island chains of the globe. Like many other avian taxa, kingfishers on islands often exhibit color patterns distinct from their close relatives. The authors focus here on putting this informally recognized pattern of evolutionary change to a formal test, asking if plumage color diversity and evolutionary rate are elevated on islands. They also explore whether a notable characteristic of some kingfishers - their simultaneous use of many of the coloration mechanisms available in birds - contributes to the evolutionary lability of their color patterns.

The authors have previously explored how when color varies in birds it is not just in dimensions of color, but also in the distribution of those colors in patches on the body. Summarizing this variation is challenging, and there are statistical obstacles to comparing it in a holistic manner. In this study, the authors use an exceptional set of analyses to study color in total as a multivariate trait. These are the major strengths of the paper. The authors' efforts are somewhat less convincing when they pursue a univariate model fitting on a small number of principal components, but these analyses are not central to the study. And as with all studies using ancestral state reconstruction to test hypotheses, it's an important tool and one that contributes to this study's effectiveness, but we should acknowledge some level of uncertainty with its results.

The authors report two important relationships in this study. They provide convincing evidence that rates of color evolution are elevated in island kingfishers, without convergence towards a particular island phenotype. They also describe a relationship between the complexity of plumage patterns and the rate at which they evolve, which has fundamental implications for our understanding of the tempo of trait evolution.

Islands make up a tiny portion of the earth's surface but are home to a seemingly disproportionate amount of life's diversity. This paper makes an important contribution to our understanding of how this diversity is generated, by showing that the evolutionary rate is elevated on islands for traits relevant to mate choice and recognition. The authors find that "plumage complexity, rather than uniformity, provides more phenotypic traits for natural selection to act upon". Given the number of different coloration mechanisms they express, the kingfishers are a unique group in which to study this issue, so I look forward to reading and hearing more from the authors on this issue in the future.

Reviewer #3 (Public Review):

Activity-based anorexia (ABA), which combines access to a running wheel and restricted access to food, is a most common paradigm used to study anorexic behavior in rodents. And yet, the field has been plagued by persistent questions about its validity as a model of anorexia nervosa (AN) in humans. This group's previous studies supported the idea that the ABA paradigm captures cognitive inflexibility seen in AN. Here they describe a fully automated touchscreen cognitive testing system for rats that makes it possible to ask whether cognitive inflexibility predisposes individuals to severe weight loss in the ABA paradigm. They observed that cognitive inflexibility was predictive of resistance to weight loss in the ABA, the opposite of what was predicted. They also reported reciprocal effects of ABA and cognitive testing on subsequent performance in the other paradigm. Prior exposure to the ABA decreased subsequent cognitive performance, while prior exposure to the cognitive task promoted resistance to the ABA. Based on these findings, the authors argue that the ABA model can be used to identify novel therapeutic targets for AN.

The strength of this manuscript is primarily as a methods paper describing a novel automated cognitive behavioral testing system that obviates the need for experimentalist handling and single housing, which can interfere with behavioral testing, and accelerate learning on the task. Together, these features make it feasible to perform longitudinal studies to ask whether cognitive performance is predictive of behavior in a second paradigm during adolescence, a peak period of vulnerability for many psychiatric disorders. The authors also used machine learning tools to identify specific behaviors during the cognitive task that predicted later susceptibility to the ABA paradigm. While the benefits of this system are clear, the rigor and reproducibility of experiments using this paradigm would be enhanced if the authors provided clear guidelines about which parameters and analyses are most useful. In their absence, the large amount of data generated can promote p-hacking.

The authors use their automated behavioral testing paradigm to ask whether cognitive inflexibility is a cause or consequence of susceptibility to ABA, an issue that cannot be addressed in AN. They provide compelling evidence that there are reciprocal effects of the two behavioral paradigms, but do not perform the controls needed to evaluate the significance of these observations. For example, the learning task involves sucrose consumption and food restriction, conditions that can independently affect susceptibility to the ABA. Similarly, the ABA paradigm involves exercise and restricted access to food, which can both affect learning.

In the Discussion, the authors hypothesize that the ABA paradigm produces cognitive inflexibility and argue that uncovering the underlying mechanism can be used to identify new therapeutic targets for AN. The rationale for their claim of translational relevance is undermined by the fact that the biggest effect of the ABA paradigm is seen in the pair discrimination task, and not reversal learning. This pattern does not fit clinical observations in AN.

In summary, the significance of this manuscript lies in the development of a new system to test cognitive function in rats that can be combined with other paradigms to explore questions of causality. While the authors clearly demonstrate that cognitive flexibility does not promote susceptibility to ABA, the experiments presented do not provide a compelling case that their model captures important features of the pathophysiology of AN.

Reviewer #3 (Public Review):

The authors have developed a new form of transparent surface multielectrode integrated into an imaging window, enabling simultaneous recording of electrical activity at the surface of the cortex combined with two-photon imaging through the window and electrode. The authors characterise the electrical signals and use simulations to argue that they reflect the activity of axons in layer 1. This is then correlated with calcium imaging signals from layer 2/3 pyramidal cells. A subset of these displayed strong correlations with the layer 1 activity.

The raw electrical recordings appear to be contaminated by large movement artefacts. The authors attempt to decompose the signal into neuronal activity and artefact. The independent component analysis (ICA) employed yields plausible results. However, there is no definitive validation of this procedure.

The simulations strongly suggest that only layer 1 axons will generate significant neuronal signals at the surface, but the authors have not attempted to reconstruct the multiunit activity in the simulations, which could provide additional assurance for their interpretation.

A small fraction of pyramidal cells has activity strongly correlated with the signal at the surface electrode. However, the authors have not examined whether the distance from neuron to the electrode influences the strength of correlation. It remains possible that the differential correlation reflects a distance effect rather than the existence of two populations.

Reviewer #3 (Public Review):

Dominant pathogenic variants of the Aac2/Ant1 ATP transporter cause disease by an unknown mechanism. In this manuscript the authors aim to reveal how these gain of function mutants impair cellular and mitochondrial health. To characterize the phenotype of Aac2 mutants in yeast, the authors use a series of single and double Aac2 mutations, within the 2nd and 3rd transmembrane domains that are associated with human diseases. Aac2A128P,A137D mutant, which caused high toxicity and damaged the mitochondrial DNA was selected for further analysis. This mutant was not imported efficiently into mitochondria and exhibited an increased association with TOM, suggesting that it clogs the TOM translocase. As a result, expression of Aac2A128P,A137D led to impaired import of other mitochondrial proteins. Several findings suggested that the single mutant Aac2A128P impaired mitochondrial import in a similar manner: 1. mass spec analysis revealed its increased association with cytosolic chaperones, TOM and TIM22 subunits, 2. Aac2A128P overexpression led to global mitochondrial protein import deficiency, demonstrated by HSP60 precursor accumulation and activation of stress responses (transcription of chaperons, proteosome induction, and CIS1).<br /> Parallel mutants of human Ant1 (AntA114P and Ant1A114P,A123D) were ectopically expressed in HeLa cells. The mutants were demonstrated to clog TOM and cause a global defect in mitochondrial protein import. This was confirmed in tissues from Ant1A114P,A123D/+ knock-in mice. The Ant1A114P,A123D/+ mice exhibited decreased maximal mitochondrial respiration in muscles. Examination of the skeletal muscle myofiber diameter and COX and SDH activity revealed that Ant1A114P,A123D expression in heterozygous mice acts dominantly and causes a myopathic phenotype and in some case neurodegeneration.

Major strengths -

The ability of proteins to clog TOM and sequentially disrupt protein import into mitochondria was demonstrated in recent years. However, till now this was achieved using chemicals, artificial cloggers and overexpression of mitochondrial proteins. This study reveals, for the first time, that disease associated variants of native mitochondrial proteins can clog the entry into the organelle. Thus, this work demonstrates that TOM clogging is a physiological relevant phenomenon that is involved in human diseases.

The manuscript is well-written and the experiments are well-designed, presenting convincing data that mostly support the conclusions. The methods used are well-establish and suitable techniques that are often used in the field. This work took advantage of 3 different biological systems/model organism, yeast, cell culture, and mice tissues, to validate the results, show conservation, and exploit the strengths of each system.

Overall, this study is impactful, greatly contributes to the field and should be of interest to the general scientific community. The work sheds light of the mechanisms by which Ant1 pathogenic mutants impact cellular health and provides evidence for the involvement of translocases clogging and impaired protein import in human diseases. The gain of function Aac2/Ant1 mutants will provide a new and powerful tool for future studies of mitochondrial quality control and repair mechanisms.

Major weaknesses -

1. The evidence for clogging of mitochondrial translocases and for general defect in protein import are solid. However, there are not enough evidence to conclude that all phenotype seen in mice and yeast are directly connected to clogging.

2. This work implies that Aac2/Ant1 variants can clogg TOM, TIM22, or both. Clogging of TIM22 is novel and interesting but is not fully discussed in the manuscript, as well as the possibility that clogging of different translocases can result in different defects.

Reviewer #3 (Public Review):

In this paper, Yeung et al., use patch-clamp electrophysiology measurements combined with structural analyses and mutagenesis to compellingly reveal how the tubular aggregate myopathy (TAM)-associated Orai1 L138F mutation leads to the gain of CRAC channel function. They discover that L138F not only constitutively activates Orai1-composed channels but also enhances Ca2+-dependent inactivation (CDI). The authors find that the L138F gain of function occurs due to a steric clash with T92 from an adjacent subunit and that introduction of a bulky residue at the T92 position similarly activates CRAC channels and enhances CDI in the absence of STIM1. Nevertheless, co-expression of STIM1 with strongly activating T92W or L138F mutants regularized the CDI to wild-type levels. Collectively, the work represents an important conceptual advancement, exposing that STIM1 is not necessary for CDI and that Orai1 likely contains the Ca2+ sensor intrinsically for this phenomenon.

Strengths:<br /> The authors use rigorous and careful electrophysiological measurements to probe how the TAM-related mutation (L138F) affects the biophysical properties of CRAC channels. The extensive and systematic mutagenesis (i.e. substitution to every possible amino acid at the T92 and L138 sites) coupled with these functional assessments reveal a steric clash between L138F and T92 and provide a complete picture of how any residue type at the so-called T92/L138 lever point may contribute to constitutive CRAC and CDI activity. The use of available high-resolution structural data to interpret functional data, rationalize the consequence of new mutations related to the mechanisms of L138F dysfunction, and generate new hypotheses is a strength of the research. Overall, the work provides a considerable conceptual advance in terms of understanding the molecular requirements for CRAC and CDI activity; in particular, the discovery that CDI can occur independently of STIM1 and the notion that Orai1 may contain an intrinsic Ca2+ sensor that regulates CDI are important steps forward for the field.

Weaknesses:<br /> While the work provides a phenomenological advancement regarding CRAC channel regulation and pinpoints new important residues for function, some aspects of the study appear incomplete. It was shown that STIM1 can normalize the enhanced CDI caused by the T92W mutation, but it is not clear how this happens. Further, the authors propose a "push" - "pull" mechanism for the complementary roles L138 and H134 in channel regulation but do not provide any structural dynamics data to support this idea. The authors provide a mathematical explanation for chelator-specific differences in CDI observed for the T92W compared to WT Orai1 but do not show any fitted data to accompany and support the model. Finally, the authors show that a considerable portion of the CDI can be eliminated after a C-terminal Orai1 deletion (i.e. residues 267-301) and probe the idea that N-terminal W76, Y80, and R83 residues may contribute to the residual CDI effect; however, after W76E, Y80E, R83E mutations showed enhanced CDI (rather than suppressed) in the context of the T92W mutation, no further experiments were pursued to account for the residual CDI.

Overall, the strengths far outweigh the weaknesses of this study, and the conclusions drawn based on the data are compelling. The work represents an important conceptual advancement as future studies can now steer towards identifying the STIM-independent Ca2+ sensor underlying the CDI of CRAC channels and revealing structural mechanisms by which Ca2+ sensing leads to pore closure.

Reviewer #3 (Public Review):

The authors start by examining the COOLAIR promoter and identifying a CRT/DRE motif that is bound by the CBF transcription factor family that is involved in the short-term cold. This is confirmed by gel shift assays and chromatin immunoprecipitation. However, it should be noted that the gel shift assays are an in vitro assay and the chromatin immunoprecipitation is carried out with plants over-expressing CBF3-myc from the pSuper promoter and so do not necessarily reflect the native state. The authors then examine COOLAIR expression in lines over-expressing each of the three CBF proteins of Arabidopsis and found COOLAIR expression elevated in the warm in all three, but with small differences in the variants of COOLAIR that are expressed. Examination of the expression of COOLAIR after short-term cold shows that transcript abundance increases after 6 hours, this expression was not observed in the cbfs-1 where all three CBFs are knocked out. Taken together this provides good evidence that COOLAIR transcription is rapidly induced via CBFs on exposure to cold.

The authors then go on to look at the roles of CBFs in longer-term cold. COOLAIR has previously been shown to increase during long-term cold (multiple weeks duration), so the question was whether this increase is CBF-dependent. The increase in COOLAIR abundance is similar to other CBF targets but does begin to decline with 40-day cold periods, presumably reflecting the shutdown of the FLC locus. The lack of COOLAIR expression in the cbfs-1 mutant is good evidence that increased COOLAIR expression is CBF-dependent. The authors also present evidence that CBFs are required for COOLAIR induction by the first seasonal frost, which is consistent with this being a short-term cold response.

The authors then examine deletions of the COOLAIR promoter. In agreement with the hypothesis that CBFs regulate COOLAIR transcription via the CRT/DREs in the COOLAIR promoter, deletions that include the two elements do not show cold induction of COOLAIR, while one that contains them does. It should be noted that these deletions are relatively coarse so could include other elements than the CRT/DREs.

The authors then use the finding that COOLAIR is not induced in the cbfs-1 mutant or in the deltaCOOLAIR1 and 3 lines to ask whether COOLAIR is required for the repression of FLC in the vernalization response. The data in Figures 6 and 7 show that these lines don't show different responses to vernalization treatment at the FLC expression, FLC chromatin modifications, or flowering time/leaf number to flowering. This supports the conclusion that the COOLAIR transcript does not play an essential role in the vernalization response.

The Discussion is well-balanced and considers previous publications in this area and highlights differences with this study. The conservation of COOLAIR in other brassica species suggests that it does have a biological function, but the data here suggest it isn't an essential component of the vernalization response. Whether there is a function in more natural conditions where the temperature fluctuates in a diurnal manner during the vernalization period is a possibility that is considered. When the data presented here are taken with other publications, the precise biological role of COOLAIR remains enigmatic.

Reviewer #3 (Public Review):

Based on studies over the last two decades, tomosyns participate in processes as diverse as synaptic SNARE complex stability (Yu H et al., 2014), dendritic spine density (Saldate JJ et al., 2018), mossy fiber synaptic plasticity (Ben-Simon Y et al., 2015), inhibition of mast cell degranulation (Madera-Salcedo IK et al., 2018), insulin-stimulated GLUT4 exocytosis by adipocytes (Wang S, et al., 2020), and both basal and stimulated secretion by PC12 cells (Williams et al., 2011). In yeast, which lacks storage granules, two tomosyn orthologs control the formation of post-Golgi vesicles. The actions of tomosyn are cell-type specific and subject to regulation by phosphorylation and the ubiquitin-proteasome system (Saldate JJ et al., 2018; Williams et al., 2011; Madera-Salcedo IK et al., 2018). In beta-cells, the ability of tomosyn to decrease insulin secretion by binding syntaxin1A requires its SUMOylation (Ferdaoussi M, et al., 2017). The carefully designed and validated mouse line developed by the authors will facilitate detailed, mechanistic studies of the diverse, cell-type specific actions of tomosyns.

Using cultures derived from the hippocampi of this new mouse strain, multiple differences were observed between two-week-old WT and DKO (double knockout of tomosyn-1 and -2) cultures. Analysis of dense core vesicle release by single neurons revealed no change in their exocytosis, but identified a decrease in levels of the dense core vesicle reporter, leading to the discovery of a decrease in levels of two endogenous dense core vesicle proteins, BDNF and IA-2. In contrast, levels of two lysosomal/endocytic markers were unaltered, demonstrating granule specificity.

WT and DKO cultures were compared using mass spectrometry. Significant changes in the levels of 3% of the proteins were identified. Strikingly, levels of several additional dense core vesicle proteins were decreased in DKO cultures. In contrast, levels of multiple mitochondrial proteins were greatly increased in DKO cultures. In addition, significant increases in VGLUT2 (a marker of glutamatergic neurons) and in GAD67, GAT1, and GAT3 (GABAergic markers) confirmed the presence of widespread differences in hippocampal cultures that matured in the absence of tomosyns. Focusing on BDNF and other dense core vesicle proteins, qPCR studies revealed decreases in mRNA levels for a subset of dense core vesicle proteins.

The use of multiple culture systems allowed the authors to employ different approaches, ranging from monitoring the release of single granules expressing a dense core vesicle reporter to quantifying the accelerated trafficking of a tagged cargo protein from the ER through the TGN and into DCVs in the absence of tomosyns. While no changes in synaptic complex formation were observed, both electron microscopy and analysis of single vesicles expressing a dense core vesicle reporter revealed a decrease in granule diameter.

Weaknesses of methods and results. Within 8 h of plating, hippocampal cultures prepared from a single litter were transduced with a lentivirus encoding active or inactive mCherry-tagged Cre-recombinase, generating WT and DKO cultures; expression of Cre-recombinase was limited to neurons using the synapsin promoter. Cultures were generally examined after two weeks. Culture conditions were varied to allow comparison of dense core vesicle exocytosis by single neurons (a neuron on a glial microisland) or protein and mRNA levels in dense neuronal networks plated on coated plastic without a glial feeder layer in WT vs. DKO cultures. Whether cultures allowed to develop under these vastly different conditions respond to the absence of tomosyns in a different manner is unknown. No attempt was made to rescue any of the differences observed by expressing tomosyn in DKO neurons. Successful rescue experiments would alleviate concerns about the effects of developmental differences on the phenotypes observed.

Immunocytochemical studies revealed an approximately two-fold drop in BDNF protein levels in the soma and neurites of DKO neurons. In contrast, BDNF, which was detectable in WT cultures using mass spectrometry, was not detectable using mass spectrometry to analyze DKO cultures. No explanation for this discrepancy between immunocytochemistry and mass spectrometry is offered. Despite the fact that neither BDNF secretion nor BDNF degradation was assessed, the authors state in their Abstract that "tomosyns regulate neuropeptide and neurotrophin secretion via control of DCV cargo production".

The authors do not adequately refer to the rich literature discussing the many secretory pathways used by different cell types, referring only to synaptic vesicles and dense core vesicles. Golgi by-pass pathways are known to take membrane proteins to dendrites and tomosyns are known to play a role in the trafficking of GLUT4 from endocytic compartments to the plasma membrane. Soluble cargo proteins such as BDNF are released both constitutively and in response to stimuli. Cargo proteins (proinsulin, proANP, and growth hormone, for example) can drive the appearance of dense core vesicles.

The mass spectrometry data presented in Fig. 3 are not well incorporated into the Discussion. KIF6, which plays a role in retrograde Golgi to ER traffic, is detectable in DKO cultures, but not in WT cultures and could contribute to the accelerated trafficking phenotype observed using RUSH. Coordinate control of the expression of dense core vesicle genes has been studied in a variety of systems, ranging from mammals to C. elegans to D. melanogaster. Levels of these gene products could have been assessed using existing mass spectrometric data or by additional qPCR studies. The diminished levels of dense core vesicle reporters observed in Fig.1 remain unexplained. Intracellular degradation and increased basal secretion, neither of which was assessed, could contribute to this observation.<br /> The authors did not take advantage of the structure/function studies used to dissect the roles of the beta-propeller and SNARE-domains of tomosyns. In yeast, loss of SR07/SR077, tomosyn orthologs which lack a SNARE-like domain, causes a defect in the exocytosis of post-Golgi vesicles and the accumulation of secretory vesicles with altered composition (Forsmark et al., 2011).

Are claims and conclusions justified by data: The title of the manuscript, "SNARE protein tomosyn regulates dense core vesicle composition but not exocytosis in mammalian neurons" is misleading. The authors present no evidence that the SNARE-domain of tomosyn is necessary for its effects on dense core vesicle composition. The yeast orthologs of tomosyn, which lack a SNARE domain, affect post-Golgi vesicular trafficking via their beta-propeller domains. Hippocampal neurons are not representative of all "mammalian" neurons. In rat sympathetic neurons, tomosyn depletion results in a decrease in neurotransmitter release. A key conclusion is that tomosyns regulate neuropeptide and neurotrophin secretion by controlling cargo production, not cargo release - this conclusion is not supported by the data presented.

Likely impact of work on the field: The mouse line developed for these studies will be of great use in mechanistic studies of the multiple roles of tomosyns. The authors identified a range of parameters that are altered in hippocampal neurons which develop in the absence of tomosyns. Additional mechanistic studies are needed to directly assess the manner in which the absence of tomosyns contributes to these changes.

Reviewer #3 (Public Review):

This is a well-designed and well conducted study on the effect of 4 months sustained exercise on atrioventricular function and cardiac remodeling in a clinically relevant large animal (canine) model. All methods are well described with proper controls. The findings support the conclusion. Potential limitations are the study are clearly stated. The findings advance the field and provide clear evidence for the susceptibility of ventricular arrhythmia in the canine model of endurance training.

Reviewer #3 (Public Review):

In this work, Bachschmid-Romano et al. propose a novel model of the motor cortex, in which the evolution of neural activity throughout movement preparation and execution is determined by the kinematic tuning of individual neurons. Using analytic methods and numerical simulations, the authors find that their networks share some of the features found in empirical neural data (e.g., orthogonal preparatory and execution-related activity). While the possibility of a simple connectivity rule that explains large features of empirical data is intriguing and would be highly relevant to the motor control field, I found it difficult to assess this work because of the modeling choices made by the authors and how the results were presented in the context of prior studies.

Overall, it was not clear to me why Bachschmid-Romano et al. couched their models within a cosine-tuning framework and whether their results could apply more generally to more realistic models of the motor cortex. Under cosine-tuning models (or kinematic encoding models, more generally), the role of the motor cortex is to represent movement parameters so that they can presumably be read out by downstream structures. Within such a framework, the question of how the motor cortex maintains a stable representation of movement direction throughout movement preparation and execution when the tuning properties of individual neurons change dramatically between epochs is highly relevant. However, prior work has demonstrated that kinematic encoding models provide a poor fit for empirical data. Specifically, simple encoding models (and the more elaborate extensions [e.g., Inoue, et al., 2018]) cannot explain the complexity of single-neuron responses (Churchland and Shenoy, 2007), and do not readily produce the population-level signals observed in the motor cortex (Michaels, Dann, and Scherberger, 2016) and cannot be extended to more complex movements (Russo, et al., 2018).

In both the Introduction and Discussion, the authors heavily cite an alternative to kinematic encoding models, the dynamical systems framework. Here, the correlations between kinematics and neural activity in the motor cortex are largely epiphenomenal. The motor cortex does not 'represent' anything; its role is to generate patterns of muscle activity. While the authors explicitly acknowledge the shortcomings of encoding models ('Extension to modeling richer movements', Discussion) and claim that their proposed model can be extended to 'more realistic scenarios', they neither demonstrate that their models can produce patterns of muscle activity nor that their model generates realistic patterns of neural activity. The authors should either fully characterize the activity in their networks and make the argument that their models better provide a better fit to empirical data than alternative models or demonstrate that more realistic computations can be explained by the proposed framework.

Major Comments<br /> 1. In the present manuscript, it is unclear whether the authors are arguing that representing movement direction is a critical computation that the motor cortex performs, and the proposed models are accurate models of the motor cortex, or if directional coding is being used as a 'proof of concept' that demonstrates how specific, population-level computations can be explained by the tuning of individual neurons.<br /> If the authors are arguing the former, then they need to demonstrate that their models generate activity similar to what is observed in the motor cortex (e.g., realistic PSTHs and population-level signals). Presently, the manuscript only shows tuning curves for six example neurons (Fig. S6) and a single jPC plane (Fig. S8). Regarding the latter, the authors should note that Michaels et al. (2016) demonstrated that representational models can produce rotations that are superficially similar to empirical data, yet are not dependent on maintaining an underlying condition structure (unlike the rotations observed in the motor cortex).<br /> If the authors are arguing the latter - and they seem to be, based on the final section of the Discussion - then they need to demonstrate that their proposed framework can be extended to what they call 'more realistic scenarios'. For example, could this framework be extended to a network that produces patterns of muscle activity?

2. Related to the above point, the authors claim in the Abstract that their models 'recapitulate the temporal evolution of single-unit activity', yet the only evidence they present is the tuning curves of six example units. Similarly, the authors should more fully characterize the population-level signals in their networks. The inferred inputs (Fig. 6) indeed seem reasonable, yet I'm not sure how surprising this result is. Weren't the authors guaranteed to infer a large, condition-invariant input during movement and condition-specific input during preparation simply because of the shape of the order parameters estimated from the data (Fig. 6c, thin traces)?

3. In the Abstract and Discussion (first paragraph), the authors highlight that the preparatory and execution-related spaces in the empirical data and their models are not completely orthogonal, suggesting that this near-orthogonality serves an important mechanistic purpose. However, networks have no problem transferring activity between completely orthogonal subspaces. For example, the generator model in Fig. 8 of Elsayed, et al. (2016) is constrained to use completely orthogonal preparatory and execution-related subspaces. As the authors point out in the Discussion, such a strategy only works because the motor cortex received a large input just before movement (Kaufman et al., 2016).

Reviewer #3 (Public Review):

This work provides a new tool, a comprehensive PhIP-seq library, containing 238,068 individual 62-amino acids peptides tiled every 25-amino acid peptide covering all known 8,980 proteins of the deadliest malaria parasite, Plasmodium falciparum, to systematically profile antibody targets in high resolution. This phage display library has been screened by plasma samples obtained from 198 Ugandan children and adults in high and moderate malaria transmission settings and 86 US controls. This work identified that repeat elements were commonly targeted by antibodies. Furthermore, extensive sharing of motifs associated with seroreactivity indicated the potential for extensive cross-reactivity among antigens in P. falciparum. This paper provides a new proteome-wide high-throughput methodology to identify antibody targets that have been investigated by protein arrays and alpha screens to date. Importantly, only this methodology (PhIP-seq library) is able to investigate repeat-containing antigens and cross-reactive epitopes in high resolution (25-amino acid resolution).

Strengths:<br /> 1) Novel technology<br /> Firstly, the uniqueness of this study is the use of novel technology, the PhIP-seq library. This PhIP-seq library in this study contains >99.5% of the parasite proteome and is the highest coverage among existing proteome-wide tools for P. falciparum. Moreover, this library can identify antibody responses in high resolution (25 amino acids).<br /> Secondly, the PhIP-seq converts a proteomic assay (ie. protein array and alpha screen) into a genomic assay, leveraging the massive scale and low-cost nature of next-generation short-read sequencing.<br /> Thirdly, the phage display system is the ability to sequentially enrich and amplify the signal to noise.<br /> Finally, a high-quality strategic bioinformatic analysis of PhIP-seq data was applied.

2) Novel findings<br /> The major findings of this study were obtained only by using this novel technology because of its full-proteome coverage and high resolution. Repeat elements were the common target of naturally acquired antibodies. Furthermore, extensive sharing of motifs associated with seroreactivity was observed among hundreds of parasite proteins, indicating the potential for extensive cross-reactivity among antigens in P. falciparum.

3) Usefulness for the future research<br /> Importantly, plasma samples from longitudinal cohort studies will give the scientific community important insights into protective humoral immunity which will be important for the identification of vaccine and exposure-marker candidates in the near future.

Weaknesses:<br /> Although the paper does have strengths in principle, the weaknesses of the paper are the insufficient description of the selected parasite proteins and seroreactivity ranking of the selected proteins such as TOP100 proteins.

Reviewer #3 (Public Review):

The general objective of this work is the dissection of osteoclast diversity; in particular, the authors intend to identify the specific features and properties that distinguish inflammatory and steady-state (tolerogenic) osteoclasts. To this end, the authors perform a transcriptional analysis of inflammatory and tolerogenic osteoclasts and identify the pattern recognition receptors TLR2, Dectin-1, and Mincle as differentially expressed genes. Agonists of these receptors or yeast probiotics regulating the elicited mechanisms in vitro and in vivo caused a specific inhibition of the differentiation of inflammatory rather than tolerogenic osteoclasts, thus highlighting the preferential use of different differentiation pathways by the two distinct osteoclast populations.

The project is based on the previous knowledge and know-how of the authors on this peculiar skeletal cell population. The work is well conceived; the experiments are clearly designed and exploit state-of-the-art technologies. The results confirm the heterogeneity of osteoclasts and provide new insights in this respect. The in vitro and in vivo studies suggest that osteoclast heterogeneity can be purposedly modulated; which might be useful and advisable for therapeutic purposes. Overall, the work provides hints for further implementation and future broad applications to diseases featuring pathological bone loss.

Reviewer #3 (Public Review):

This is a well-conducted phase 2 randomized trial testing outpatient therapeutics for Covid-19. In this report of the platform trial, they test ivermectin, demonstrating no virologic effect in humans with Covid-19.

Overall, the authors' conclusions are supported by the data.

The major contribution is their implementation of a new model for Phase 2 trial design. Such designs would have been ideal earlier in the pandemic.

Reviewer #3 (Public Review):

The authors provide a molecular dynamics (MD)-based detailed evaluation of the contribution of the two elongated loops (alpha3-beta7 and beta12-alpha5), present near each active site of the tetrameric Stenotrophomonas maltophilia class B Metallo-beta-lactamase (MBL) L1, towards the L1's lactamase activity with the premise that a better understanding of the categorical conformational states sampled by the loops would ultimately help in the design of a better lactamase inhibitor. This is to then ultimately alleviate the public health crisis arising from β-lactam antibiotic resistance. Using enhanced sampling MD, Markov state modeling (MSM), and convolutional variation autoencoder (CAVE)-based deep learning, the authors identify five key interacting residues in these two loops which contribute to the conformational states of loops.

The major strength of the study is that the authors carry out a detailed study (e.g., enhanced sampling MD, Markov state modeling, and convolutional variation autoencoder-based deep learning) of the conformational landscape of an important enzyme as these findings would help further experimental studies (e.g., NMR dynamics) for ligand binding, better design of inhibitory ligands of an important class of enzyme. One weakness would be that MBL L1 is a good representative of the class of MBL enzymes or not needs clarification.

The authors achieve the goal of capturing the various conformational states of the L1 enzyme loops and their computational results support the conclusion about the various loop conformations sampled during the dynamics. However, how the mutagenesis experiment supports the existence of different conformational states will likely benefit from more clarification. Further clarification on how detecting the existence of multiple conformers benefits better inhibitor design will be very beneficial.

Since details on macromolecular motion are often neglected in macromolecular experimental studies, the detailed MD methods described here will be a very useful companion in experimental studies of proteins and their interactions.

A discussion on how the study of one particular enzyme could benefit in understanding the molecular properties of a class of enzymes would enhance the generality of the study.

Reviewer #3 (Public Review):

It is a brilliant idea to combine the MS2-MCP system with Suntag. As the authors stated, it reduces the copies of the MS2 stem loops, which can create challenges during cloning process. The Suntag system can easily amplify the signal by several to tens of folds to boost the signal for live RNA tagging. One of the best ways to claim that MASS works better than the MS2 system by itself is to compare their signal-to-noise ratios (SNRs) within the same model system, such as HeLa cells or the C. elegans epidermis. Because the authors' main argument is that they made an improvement in live RNA tagging method, it is necessary to compare it with other methods side-by-side. The authors claim that MASS can significantly improves the efficiency of CRISPR by reducing the size of the insert, it still requires knocking in several transgenes, which can be even more challenging in some model systems where there are not many selection markers are available. Another possible issue is that the bulky, heavy tagging (384 scFv-sfGFP along with 24xSuntag) can affect the mobility or stability of the target mRNAs. If it also tags preprocessed RNA in the nucleus, it may affect the RNA processing and nuclear export. A few experiments to address these possibilities will strengthen the authors' arguments. I am proposing some experiments below in detailed comments.

1. For the experiments with HeLa cells, it is not clear whether the authors used one focal plane or the whole z-stack for their assessment of mRNA kinetics, such as fusion, fission, and anchoring. If it was from one z-plane, it was possible that many mRNAs move along the z-axis of the images to assume kinetics. If the kinetics is true, is it expected by the authors? Are beta-actin mRNAs bound to some RNA-binding proteins or clustered in RNP complexes?<br /> 2. Some quantifications on beta-actin mRNA kinetics, such as a plot of their movement speed or fusion rate, etc., would help readers better understand the behaviors of the mRNAs and assess whether the MASS tagging did not affect them.<br /> 3. Using another target gene for MASS tagging would further confirm the efficacy of the system. Assuming the authors generated a parental strain of HeLa cell, where MCP-24xSuntag and scFv-sfGFP are already stably expressed (shown in Fig. 1B), CRISPR-ing in another gene should be relatively easy and fast.<br /> 4. Adding a complementary approach to the data presented in Fig. 1, such as qRT-PCR for beta-actin, with or without the MASS system would ensure the intense tagging did not affect the mRNA expression or stability.<br /> 5. For experiments with the C. elegans epidermis, including at least one more MASS movie clip for c42d4.3 and a movie for mai-1 would be helpful for readers to appreciate the RNA labeling and its dynamics.<br /> 6. The difference between Fig. 2D and Fig. 2-fig supp. 3 is unclear. The authors should address the different patterns of RNA signal propagation. Is it due to the laser power used too much, resulting in photobleach in Fig. 2D?<br /> 7. Movie 7 is the key data the authors are presenting, but there are a few discrepancies between their arguments and what is seen from the movie. The authors say the RNAs are "gradually spread" (the line 120 in the manuscript). However, it seems that the green foci just appear here and there in the epidermis and the majority of them stay where they were throughout the timelapse. This pattern seems to be different from the montage in Fig. 2-fig supp. 3, which indeed looks like the mRNA spots are formed around the lesion and spread overtime. Additional explanation on this will strengthen the arguments. Given the dramatic increase of c42d4.3 mRNA abundance 1 min. after the laser wounding, there must be a tremendous boost of transcription at the active transcription sites, which should be captured as much bigger and fewer green foci that are located inside the nucleus. Is this simply because those nuclear sites are out of focus or in a similar size as mRNA foci? Regardless, this should be addressed in the discussion.<br /> 8. One clear way to confirm that MASS labels mRNAs and does not affect their stability/localization is to compare the imaging data with single-molecule RNA fluorescence in situ hybridization (smFISH) that the Singer lab developed decades ago. The authors can target the endogenous c42d4.3 or mai-1 RNAs using smFISH and compare their abundance and subcellular localization patterns with their data.<br /> 9. One of the main purposes to live image RNAs is to assess their dynamics. Adding some more analyses, such as the movement speed of the foci, would be helpful to show how effective this system is to assess those dynamics features.

Reviewer #3 (Public Review):

In this paper, Zhang et al. investigated the regulation of the meiotic checkpoint kinase CHK-2, whose inactivation is a necessary step in ensuring that chromosomes have synapsed and received crossovers before progression to later events of meiotic prophase. Using mass spectrometry, biochemistry, and cytological analysis of mutant and transgenic strains, they show that CHK-2 is phosphorylated and that CHK-2 activity is attenuated in a manner dependent on recruitment of the kinase PLK-2 to a conserved docking motif on the synaptonemal complex, which forms between pairs of homologous chromosomes. The results plausibly explain how CHK-2 can remain active and prolong the events of early prophase chromosome dynamics in response to delays in synapsis since unsynapsed chromosomes will not recruit PLK-2 to inactivate CHK-2 locally. While molecular details remain to be worked out (e.g., why the loss of crossover intermediates can also extend CHK-2 activity; why PLK-2 does not inactivate CHK-2 at pairing centers), this work provides an elegant explanatory unification of several disparate observations.

The authors made extensive use of the auxin-inducible degron system combined with the spatiotemporal arrangement of the C. elegans germline to examine the effect of conditional depletion of proteins in cells where the depleted protein was required for earlier events. This is a powerful approach that can give stronger evidence than an examination of genetic mutant backgrounds, especially when, as in this paper, controls are performed to confirm the timing of depletion by loss of immunofluorescence signal. The method of measuring the proportion of the gonad occupied by nuclei with bright COSA-1 foci is generally robust, but the criteria for demarcation could be more strictly defined. For example, does a single nucleus with a single bright COSA-1 spot suffice to mark the beginning of a zone?

A weakness of this paper is that the non-phosphorylatable alleles constructed to provide a functional test of CHK-2 phosphorylation, unfortunately, had severe meiotic defects, so the importance of CHK-2 phosphorylation in its deactivation remains uncertain. While the results overall point towards direct phosphorylation of CHK-2 by PLK-2 (and possibly PLK-1), the authors are careful to point out that this is not the only possible explanation. In this regard, the mass spectrometry data should be given a statistical analysis to see whether they are best explained by in vitro phosphorylation of CHK-2 by PLK-2.

Reviewer #3 (Public Review):

The work by Olson and colleagues provides novel, fundamental insights into the role of HLA polymorphisms in the processing of exogenous antigens via the non-canonical vacuolar and cytosolic pathways. The choice of the two exemplar HLA-B allotypes leverages a significant amount of background work done both by the Raghavan lab and others, together with a series of novel and very elegant in vitro assays to elucidate a trend where differences in peptide binding preferences and other molecular features can have a drastic effect on non-canonical processing of exogenous antigens. Finally, using two related cell types (monocytes and monocyte-derived DCs) it highlights important differences in endo-lysosomal assemble within different cell types, an aspect of the non-canonical antigen processing that has not been sufficiently addressed in previous studies. While the number of allotypes and cell types utilized in this study is small (n=2 in each case), it provides an elaborate view into the vacuolar processing pathway and motivates further studies on a more expanded set of alleles in future studies. Finally, it underscores the importance of defining the expression of HLA expression levels in the context of specific cell types, setting a standard for future studies in the field.

Moreover, the work outlined in this study is technically sound, with sufficient attention to detail, adequate control experiments, and a rigorous statistical analysis of the resulting data when needed. Overall, the conclusions are well supported by the data. The manuscript is written in a clear, succinct manner to comprehend by a wide audience of readers.

One shortcoming of the paper is a lack of molecular characterization of the peptide-receptive MHC-I species at different stages of their assembly and trafficking process. For instance, while the authors utilize a monoclonal antibody (HC10) to probe empty MHC-I conformers and their dynamics, they don't provide further analysis of interactions with the light chain, a component of the complex that is known to be critical for regulating the internalization and peptide-loading process, both on the cell surface and at different intracellular compartments. Finally, while the overall effects on the cross-presentation of specific EBV antigens by the two allotypes are well described, what is lacking is a more quantitative analysis of the number of molecules, their densities, and distribution on the cell surface, all of which are known to have important consequences for T cell stimulation.

Reviewer #3 (Public Review):

Yeatman et al. tested whether the emergence of brain regions that selectively process novel visual stimuli like words occur at the expense of cortical representations of other stimuli like faces and objects. They conducted a randomized controlled trial with preschool children (five years of age) that were either taught reading or oral language skills. They found that being taught reading versus oral language skills induced different patterns of change in category-selective regions of the visual cortex. Their main conclusion is that reading instruction enhanced the response to text but did not diminish the response to other categories.

The main novelty of this study seems to be that they conducted a randomized controlled trial. The study is well crafted and executed. However, based on the current methodology, it is unclear if they shed novel light on the cortical recycling hypothesis.

Reviewer #3 (Public Review):

The research question is highly relevant as far too little is known about the efferent olivocochlear system, and the methods are state-of-the-art. This is high-quality work both for molecular analysis as well as for LOC physiology. The study is well-designed and executed, the manuscript is elegantly prepared. The high-quality gene expression data from a region of the ventral brainstem at 3 different postnatal time points (P1, P5, P26-28) is impactful in terms of development, heterogeneity, and physiological relevance of OCNs. I expect the data of this study to become instrumental for future functional studies on the lateral efferent olivocochlear system.

One issue inherent to transcriptomics studies is the challenge of linking RNA levels to protein levels for functional interpretation. I would ask the authors to acknowledge this and (still more) carefully draw conclusions. For example, name the differentiation of LOC from MOC based on collagen (Col4a4) expression or Gad2 vs. Htr2c for differentiating OCNs from FMNs. Moreover, the lack of physiological differences in soma recordings would seem to suggest a rather homogeneous phenotype but certainly does not exclude the postulated different presynaptic functions of LOC2 and LOC1 neurons.

I am worried that the NPY-based identity in the sparse labeling experiment meant to selectively report LOC2 might not be such a safe approach. This is even more concerning considering that the NPY identity of presynaptic terminals varies within a given axon. Therefore, wonder why the authors did not perform more immunohistochemical labeling of LOC2 and LOC1 markers in the cochlea. Also, it would be great to see how LOC subtype specification changes in genetically deaf and noise-deafened mice.

Reviewer #3 (Public Review):

In this study, the authors investigate the genetic and environmental causes of elevated Mitochondrial Membrane Potential (MMP) in yeast, and also some physiological effects correlated with increased MMP.

The study begins with a reanalysis of transcriptional data from a yeast mutant lacking the gene MCT1 whose deletion has been shown to cause defects in mitochondrial fatty acid synthesis. The authors note that in raffinose mct1del cells, unlike WT cells, fail to induce expression of many genes that code for subunits of the Electron Transport Chain (ETC) and ATP synthase. The deletion of MCT1 also causes induction of genes involved in acetyl-CoA production after exposure to raffinose. The authors therefore conduct a screen to identify mutants that suppress the induction of one of these acetyl-CoA genes, Cit2. They then validate the hits from this screen to see which of their suppressor mutants also reduce expression in four other genes induced in a mct1del strain. This yielded 17 genes that abolished induction of all 5 genes tested in an mct1del background during growth on raffinose.

The authors chose to focus on one of these hits, the gene coding for the phosphatase SIT4 (related to human PP6) which also caused an increase in expression of two respiratory chain genes. The authors then investigated MMP and mitochondrial morphology in strains containing SIT4 and MCT1 deletions and surprisingly saw that sit4del cells had highly elevated MMP, more reticular mitochondria, and were able to fully import the acetolactate synthase protein Ilv2p and form ETC and ATP synthase complexes, even in cells with an mct1del background, rescuing the low MMP, fragmented mitochondria, low import of Ilv2 and an inability to form ETC and ATP synthase complexes phenotypes of the mct1del strain. Surprisingly, the authors find that even though MMP is high and ETC subunits are present in the sit4del mct1del double deletion strain, that strain has low oxygen consumption and cannot grow under respiratory conditions, indicating that the elevated MMP cannot come from fully functional ETC subunits. The authors also observe that deleting key subunits of ETC complex III (QCR2) and IV (COX5) strongly reduced the MMP of the sit4del mutant, which would suggest that the majority of the increase in MMP of the sit4del mutant was dependant on a partially functional ETC. The authors note that there was still an increase in MMP in the qcr2del sit4del and cox4del sit4del strains relative to qcr2del and cox4del strains indicating that some part of the increase in MMP was not dependent on the ETC.

The authors dismiss the possibility that the increase in MMP could have been through the reversal of ATP synthase because they observe that inhibition of ATP synthase with oligomycin led to an increase of MMP in sit4del cells. Indicating that ATP synthase is operating in a forward direction in sit4del cells.

Noting that genes for phosphate starvation are induced in sit4del cells, the authors investigate the effects of phosphate starvation on MMP. They found that phosphate starvation caused an increase in MMP and increased Ilv2p import even in the absence of a mitochondrial genome. They find that inhibition of the ADP/ATP carrier (AAC) with bongkrekic acid (BKA) abolishes the increase of MMP in response to phosphate starvation. They speculate that phosphate starvation causes an increase in MMP through the import and conversion of ATP to ADP and subsequent pumping of ADP and inorganic phosphate out of the mitochondria.

They further show that MMP is also increased when the cyclin dependent kinase PHO85 which plays a role in phosphate signaling is deleted and argue that this indicates that it is not a decrease in phosphate which causes the increase in MMP under phosphate starvation, but rather the perception of a decrease in phosphate as signalled through PHO85. Unlike in the case of SIT4 deletion, the increase in MMP caused by the deletion of pho85 is abolished when MCT1 is deleted.

Finally they show an increase in MMP in immortalized human cell lines following phosphate starvation and treatment with the phosphate transporter inhibitor phosphonoformic acid (PFA). They also show an increase in MMP in primary hepatocytes and in midgut cells of flies treated with PFA.

The link between phosphate starvation and elevated MMP is an important and novel finding and the evidence is clear and compelling. Based on their experiments in various mammalian contexts, this link appears likely to be generalizable, and they propose and begin to test an interesting hypothesis for how MMP might occur in response to phosphate starvation in the absence of the Electron Transport Chain.

The link between phosphate starvation and deletion of the conserved phosphatase SIT4 is also interesting and important, and while the authors' experiments and analysis suggest some connection between the two observations, that connection is still unclear.

Major points

Mitotracker is great fluorescent dye, but it measures membrane potential only indirectly. There is a danger when cells change growth rates, ion concentrations, or when the pH changes, all MMP indicating dyes change in fluorescence: their signal is confounded Change in phosphate levels can possibly do both, alter pH and ion concentrations. Because all conclusions of the manuscript are based on a change in MMP, it would be a great precaution to use a dye-independent measure of membrane potential, and confirm at least some key results.

Mitochondrial MMP does strongly influence amino acid metabolism, and indeed the SIT4 knockout has a quite striking amino acid profile, with histidine, lysine, arginine, tyrosine being increased in concentration. http://ralser.charite.de/metabogenecards/Chr_04/YDL047W.html<br /> Could this amino acid profile support the conclusions of the authors? At least lysine and arginine are down in petites due to a lack of membrane potential and iron sulfur cluster export.- and here they are up. Along these lines, according to the same data resource, the knock-outs CSR2, ASF1, SSN8, YLR0358 and MRPL25 share the same metabolic profile. Due to limited time I did not re-analyse the data provided by the authors- but it would be worth checking if any of these genes did come up in the screens of the authors.

One important claim in the manuscript attempts to explain a mechanism for the MMP increase in response to phosphate starvation which is independent of the ETC and ATP synthase.

It seems to me the only direct evidence to support this claim is that inhibition of the AAC with BKA stops the increase of mitotracker fluorescence in response to phosphate starvation in both WT and rho0 cells (Figs 4B and 4C). It would strengthen the paper if the authors could provide some orthogonal evidence.

Introduction/Discussion The author might want to make the reader of the article aware that the 'reversal' of the ATP synthase directionality -i.e. ATP hydrolysis by the ATP synthase as a mechanism to create a membrane potential (in petites), has always been a provocative idea - but one that thus far could never be fully substantiated. Indeed some people that are very familiar with the topic, are skeptical this indeed happens. For instance, Vowinckel et al 2021 (PMID: 34799698) measured precise carbon balances for peptide cells, and found no evidence for a futile cycle - peptides grow slower, but accumulate the same biomass from glucose as peptides that re-evolve at a fast growth rate . Perhaps the manuscript could be updated accordingly.

In the introduction and conclusion there is discussion of MMP set points. In particular the authors state:

"Critically, we find that cells often prioritize this MMP setpoint over other bioenergetic priorities, even in challenging environments, suggesting an important evolutionary benefit."

This does not seem to be consistent with the central finding of the manuscript that MMP changes under phosphate starvation. MMP doesn't seem so much to have a 'set point' but rather be an important physiological variable that reacts to stimuli such as phosphate starvation.

The authors suggest that deletion of Pho85 causes an increase in MMP because of cellular signaling. However, they also state in the conclusion:

"Unlike phosphate starvation, the pho85D mutant has elevated intracellular phosphate concentrations. This suggests that the phosphate effect on MMP is likely to be elicited by cellular signaling downstream of phosphate sensing rather than some direct effect of environmental depletion of phosphate on mitochondrial energetics."

The authors should cite the study that shows deletion of PHO85 causes increased intracellular phosphate concentrations. It also seems possible that the 'cellular signaling' that causes the increase in MMP could be a result of this increase in intracellular phosphate concentrations, which could constitute a direct effect of an environmental overload of phosphate on mitochondrial energetics.

Related to this point, in the conclusion, the authors state:

"We now show that intracellular signaling can lead to an increased MMP even beyond the wild-type level in the absence of mitochondrial genome."

In sum, the data shows that signaling is important here- but signaling alone is only the message - not the biophysical process that creates a membrane potential. The authors then could revise this slightly.

The authors state in the conclusion that

"We first made the observation that deletion of the SIT4 gene, which encodes the yeast homologue of the mammalian PP6 protein phosphatase, normalized many of the defects caused by loss of mtFAS, including gene expression programs, ETC complex assembly, mitochondrial morphology, and especially MMP (Fig. 1)"

The data shown though indicates that a defect in mtFAS in terms of MMP, deletion of SIT4 causes a huge increase (and departure away from normality) whether or not mct1 is present (Fig 1D)

The language "SIT4 is required for both the positive and negative transcriptional regulation elicited by mitochondrial dysfunction" feels strong. SIT4 seems to influence positive transcriptional regulation in response to mitochondrial dysfunction caused by MCT1 deletion (but may not be the only thing as there appears to be an increase in CIT2 expression in a sit4del background following a further deletion of MCT1). In terms of negative regulation, SIT4 deletion clearly affects the baseline, but MCT1 deletion still causes down regulation of both examples shown in Fig 1B, showing that negative transcriptional regulation can still occur in the absence of SIT4. The authors might consider showing fold change of expression as they do in later figures (Figs 4B and C) to help the reader evaluate the quantitative changes they demonstrate.

The authors induce phosphate starvation by adding increasing amounts of potassium phosphate monobasic at a pH of 4.1 to phosphate dropout media supplemented with potassium. The authors did well to avoid confounding effects of removing potassium. The final pH of YNB is typically around 5.2. Is it possible that the authors are confounding a change in pH with phosphate starvation? One would expect the media in the phosphate starvation condition to have a higher pH than the phosphate replacement or control media. Is a change in pH possibly a confounding factor when interpreting phosphate starvation? Perhaps the authors could quantify the pH of the media they use for the experiment to understand how much of a factor that could be. One needs to be careful with Miotracker and any other fluorescent dye when pH changes. Albeit having constraints on its own, MitoLoc as a protein rather than small molecule marker of MMP might be a good complement.

Reviewer #3 (Public Review):

The authors' aim was to examine the early stages of the HIV-1 packaging process inside cells, with specific focus upon how the Gag protein and its cognate domains mediate the initial interaction with the packaging signal on the genomic RNA. The technique that has generated the majority of results in the paper is a modified version of CLIP. The authors have achieved this aim well, with data that clearly support the importance of Capsid, as well as the importance of two different aspects of RNA structure, the IP6 binding site, and various sites that help to form the dimer, trimer and hexamer interfaces on Gag. The major conclusions of the paper, that an immature Gag lattice is needed to form, that NC alone is insufficient to mediate specific recognition of the packaging signal within cells, and that various aspects of Capsid are necessary, are clearly supported by the data.

A particular strength of the paper is the way in which the viral protein and RNA are expressed within cells - these derive from the same construct, which is essentially the proviral genome with mutations to enable the authors to study the various truncations/mutations of Gag and/or the RNA structure. The authors could instead have transfected separate packaging signal/gRNA and viral protein plasmids, but in ensuring that the viral proteins are translated from the same RNA molecule that can also be packaged, they recapitulate the native viral situation in a state of the art experimental form. This is important in terms of the conclusions they can draw, because although HIV-1 can co-package some other lentiviruses, and HIV-1 packaging can occur in trans (ie where 2 gRNA molecules are packaged by molecules of Gag that have not been translated from them), the experiments determining copackaging ability are sometimes not performed in a competitive or limiting system, so it is difficult to say whether there is indeed some remaining importance of co-translational packaging in the very early stages of HIV-1 Gag-psi recognition. Expression of gRNA and protein from the same construct also ensures a balance in stoichiometry within the cytoplasm that is representative of a native infection.

The weakness within the paper is the lack of consideration of how Gag concentration within the cytosol may affects its binding kinetics, both with itself and with the RNA. The CLIP experiments are internally controlled in that they measure binding to the packaging signal relative to the rest of the genome; however, the authors do not appear to have checked that all constructs were expressing at roughly equivalent amounts. This is especially important when interpreting data from a protein such as Gag, which undergoes very complex multimerization, and when considering that the RNA also multimerizes. Both of these multi-step events may alter according to the actual concentrations of both Gag and RNA, and not just the stoichiometric ratio of the two. Some of the data that are needed to provide this evidence are present within the paper already, as western blots analysing multimerization of Capsid mutants, and look to broadly support the expression of the constructs at similar levels. More consideration of this point would strengthen the paper.

The authors place their findings in the context of the field very well. They appear to have considered multiple lines of evidence and to have accounted broadly for previous work done. I do find the discussion of Capsid mutants, and the dimer, trimer and hexamer interfaces quite protein-centric though. I wonder whether there might be a larger role for the RNA structure and structural changes in bringing together the precise Gag lattice structure in some sort of step-wise fashion.

Overall, the manuscript is of great value to the retroviral research community, as it provides data from a highly relevant biological setting. Such data has largely been lacking within the field.

Reviewer #3 (Public Review):

STRENGTHS

• This ambitious study is broad in scope, beginning with a bacterial GWAS study and extending all the way to in vivo guinea pig infection models.

• Numerous reports have attempted to identify Mtb strains with elevated mutation rates, and the results are conflicting. The present study sets out to thoroughly evaluate one such mutation that may produce a mutator phenotype, mutY-Arg262Gln.

WEAKNESSES

• While the authors follow-up experiments with the mutY-Arg262Gln allele are all consistent with the conclusion that this mutation elevates the mutation rate in Mtb and thus could promote the evolution of drug resistance, further work is needed to unambiguously demonstrate this link.

• The authors highlight five mutations in genes associated with DNA replication and or repair from their GWAS analysis:

o dnaA-Arg233Gln: as the authors note in the Discussion, Hicks et al. associate SNPs in dnaA with low-level isoniazid resistance, as a result of lowered katG expression. Since this is unrelated to their focus on DNA repair genes whose mutation could elevate mutation rates, I would consider removing this allele from the Table.

o mutY-Arg262Gln: querying publicly available whole genome sequences of clinical Mtb isolates, this SNP appears to be restricted to lineage 4.3 (L4.3). All of these L4.3 strains appear to be drug-resistant. How many times did the mutY-Arg262Gln mutation evolve in the authors dataset? If there is evidence of homoplastic evolution, this would strengthen their case. If not, it doesn't mean the authors findings are incorrect, but does elevate that risk that this mutation could be a passenger (i.e. not driver) mutation. To address this, the authors could attempt to date when the mutY-Arg262Gln arose. If it was before the evolution of drug-resistance conferring alleles in these L4.3 strains, that is consistent with (but not proof of) a driver mutation. If mutY-Arg262Gln arose after, this is much more consistent with a passenger mutation.

o uvrB-Ala524Val: curiously we don't see this SNP in our dataset of publicly available whole genome sequences of clinical Mtb isolates (~45,000 genomes).

o uvrA-Gln135Lys: this SNP also appears to be restricted to lineage 4.3. Same question as for mutY-Arg262Gln.

o recF-Gly269Gly: this is a very common mutation, is it unique to lineage 2.2.1? Same question as for mutY-Arg262Gln.

• The CRYPTIC consortium recently published a number of preprints on biorxiv detailing very large GWAS studies in Mtb. Did any of these reports also associate drug resistance with mutY? If yes, this should be stated. If not, the potential reasons for this discrepancy should be discussed.

• Based on the authors follow-up studies in vivo, MutY-Arg262Gln is presumed to be a loss-of-function allele. If the authors could convincingly demonstrate this biochemically with recombinant proteins, this would significantly strengthen their case.

• If the authors are correct and mutY-Arg262Gln strains have elevated mutation rates, presumably there would be evidence of this in the clinical strain sequencing data. Do mutY-Arg262Gln containing strains have elevated C→G or C→A mutations in their genomes? Presumably such strains would also have a higher number of SNPs than closely related strains WT for mutY- is this the case?

• While more work, mutation rates as measured by Luria-Delbruck fluctuation analysis are more accurate than mutation frequencies. I would recommend repeating key experiments by Luria-Delbruck fluctuation analysis. It is also important to report both drug-resistant colony counts and total CFU in these sorts of experiments. Given the clumpy nature of mycobacteria, mutation rates can appear to be artificially elevated due to low total CFU and not an increase in the number of drug-resistant colonies.

• Figure 4 would appear to measuring drug tolerance not resistance? Are the elevated CFU in the presence of drugs in the mutY-Arg262Gln strain due to an increase in the number of drug resistant strains or drug sensitive strains? This could be assessed by quantifying resulting CFU in the presence or absence the indicated drugs.

https://www.wsj.com/articles/david-rockefellers-famous-rolodex-is-astonishing-heres-a-first-peek-1512494592

Reviewer #3 (Public Review):

Wang et al. show a new role for the small heat-shock protein Hsp47 in the assembly and plasma membrane trafficking of GABAA receptors and other heptameric neuroreceptors. Hsp47 (SERPINH1) is primarily known as a collagen-specific molecular chaperone, but it has been increasingly recognized as important for other protein clients. In a prior mass spectrometry study from the same group, Hsp47 was identified as the most enriched interaction partner of GABAA neurotransmitter-gated ion channels. In this study, the authors now follow up on the functional role of Hsp47 for the GABAA heteromer assembly and its cell-surface trafficking.

Strengths:<br /> The authors show convincingly that Hsp47 plays an important role in promoting the cell surface expression and activity of GABAA receptors. Knockdown of Hsp47 in rat primary neurons decreases endogenous GABAA protein subunits on the cell surface and GABA-induced currents. Overexpression of Hsp47 in HEK293T increases abundance and cell surface trafficking of exogenously expressed GABAA subunits. Importantly, the overexpression of Hsp47 also rescues cell surface expression and channel currents of epilepsy-associated mutant GABAA receptors (alpha1 A332D), which could point to a future avenue to ameliorate pathogenic misfolding. The authors use a variety of experimental approaches to glean the mechanism by which Hsp47 promotes GABAA cell surface expression. In vitro GST pulldown experiments confirm a direct interaction between Hsp47 and the alpha1 and beta2 subunits. Site-directed mutagenesis and DTT addition indicate that the formation of a disulfide bond in the alpha1 subunits is critical for the Hsp47 interactions, leading the authors to conclude that Hsp47 is likely to bind to a more folded state of the subunit. In contrast, the ER Hsp70 chaperone BiP binds more strongly when the disulfide bond is disrupted, which corresponds to a more misfolded state as indicative of more alpha1 in the insoluble fraction. FRET assays and non-reducing gels to monitor GABAA receptor assembly again show that Hsp47 overexpression promotes the formation of the alpha1-beta2 complex. However, while these experiments are generally carried out thoroughly and the data is presented well, the results are interpreted too narrowly to only support their proposed models without considering alternative possibilities (see more below). Lastly, the authors show that Hsp47 overexpression also enhances the cell-surface expression and peak currents of another heteropentameric Cys-loop superfamily neuroreceptor, namely the a4b2 nicotinic acetylcholine receptor.

Weaknesses:<br /> The authors propose a compelling model in Figure 7 by which Hsp47 binds to a late-stage, largely folded alpha1 or beta2 subunit essentially acting as a holdase to promote assembly into larger dimers or other folding intermediates. However, the data in the manuscript would also support alternative models that the authors should more carefully consider. For instance, Hsp47 overexpression leads to a buildup of additional alpha1 and beta2 subunits (as described in lines 256-258 and seen in Fig. 4C), suggesting that Hsp47 may instead prevent subunits from getting degraded. Conclusions about Hsp47 binding after BiP to a largely folded state are indirectly based on shifts in the steady population of WT or misfolded GABAA subunits, but Hsp47 overexpression may in turn influence this equilibrium. Without any experiments examining the kinetics of protein interactions, degradation, or cell surface expression conclusions are difficult to interpret. Lastly, most experiments are carried out in HEK293T, which does not endogenously express GABAA or other neuroreceptors. There is a disconnect between the knockdown studies in rat primary hippocampal neurons and the overexpression experiments in HEK293T cells. The loss of GABAA receptor trafficking and function in the neurons could result from the secondary effect of the Hsp47 knockdown.

Overall, the study provides valuable new insights into the client scope of the ER small heat shock protein Hsp47, advances our understanding of neuroreceptor proteostasis, and provides potential corrective strategies to enhance the expression of epilepsy-associated mutations through targeting Hsp47. Hence, the paper should have broader relevance for a readership interested in proteostasis, membrane protein trafficking, and neuroreceptor signaling. However, I recommend addressing the following comments, mainly because the study in its current form only incompletely corroborates the authors' conclusions about the mechanism by which Hsp47 facilitates the neuroreceptor subunit assembly:

• For the in vitro experiments in Fig. 1, it would be important to show controls that the recombinantly expressed alpha1(ERD) adopts a well-folded state. Similarly, how did the authors ensure that the alpha1- and beta2-GST proteins adopt a folded (or near-folded) conformation?<br /> • In several experiments (e.g. Fig. 2A, Fig. 4B-C, Fig. 5B) IF staining or Western blots for the alpha1 and beta2 subunits are taken as a proxy for full GABA receptor assembly. Are the other subunits (e.g. gamma2) present and can they be detected?<br /> • Does Hsp47 knockdown in the primary hippocampal neurons leads to other changes in proteostasis network composition, e.g. UPR activation? This will be important to quantify to ensure that the reduced GABAA function can be directly attributed to the loss of Hsp47.<br /> • How are the Hsp47 knockdown and overexpression phenotype in the 2 different cell lines connected? If Hsp47 abundance is a limiting factor for GABAA proteostasis, it would be helpful to show (e.g. by lentivirus transduction) that additional Hsp47 can increase GABAA surface expression in the primary neurons.<br /> • Increased alpha1 and beta2 monomers in Fig. 4C suggest that the increase in receptor complex formation is likely due to more subunits being present when Hsp47 is overexpressed. Does Hsp47 prevent the degradation of excess or misfolded subunits? This can be easily tested with cycloheximide-chase or pulse-chase assays.<br /> • Does Hsp47 overexpression lead to more alpha1(A332D) monomer build up in cells (similarly to the WT alpha1)? The total level of alpha1(A332D) should be quantified for Fig. 5B. Similarly in Fig. 6A, does Hsp47 overexpression stabilize the abundance of nAChR subunits? The authors could easily quantify the abundance of individual subunits by Western blot.<br /> • Did the authors test the effect of Hsp47 overexpression on the trafficking of other misfolding-prone GABAA subunit variants? For therapeutic purposes, it will be important to evaluate a broader set of variants. Even if Hsp47 only restores select variants, these results would be useful for pinpointing a mechanism by which Hsp47 binds to the receptor subunits.

Reviewer #3 (Public Review):

The authors aimed to study and describe allosteric modulation of the pharmacologically important muscarinic acetylcholine receptor 4 (M4R). Developing orthosteric ligands (agonists and antagonists) has had limited success in the past, due to the conserved binding pocket of acetylcholine across all (five) homologous receptors. The study uses a broad spectrum of experimental results, using binding and signaling assays, structure determination by cryoEM, as well as some mutational studies to study species selectivity. These results were combined with expansive MD simulations, to correlate receptor 'rigidity' with binding affinities, as well as signaling. The main strength of this paper is the sheer breadth of results to study the important aspect of allosteric modulation from any possible angle. I do not see any noteworthy weaknesses in the manuscript. The work presented here will be an important reference for future drug discovery efforts.

Reviewer #3 (Public Review):

Liu et al. combined mechanistic modeling with in vitro experiments and data from a clinical trial to develop an in silico model to describe response of T cells against tumor cells when bi-specific T cell engager (BiTE) antigens, a standard immunotherapeutic drug, are introduced into the system. The model predicted responses of T cell and target cell populations in vitro and in vivo in the presence of BiTEs where the model linked molecular level interactions between BiTE molecules, CD3 receptors, and CD19 receptors to the population kinetics of the tumor and the T- cells. Furthermore, the model predicted tumor killing kinetics in patients and offered suggestions for optimal dosing strategies in patients undergoing BiTE immunotherapy. The conclusions drawn from this combined approach are interesting and are supported by experiments and modeling reasonably well. However, the conclusions can be tightened further by making some moderate to minor changes in their approach. In addition, there are several limitations in the model which deserves some discussion.

Strengths

A major strength of this work is the ability of the model to integrate processes from the molecular scales to the populations of T cells, target cells, and the BiTE antibodies across different organs. A model of this scope has to contain many approximations and thus the model should be validated with experiments. The authors did an excellent job in comparing the basic and the in vitro aspects of their approach with in vitro data, where they compared the numbers of engaged target cells with T cells as the numbers of the BiTE molecules, the ratio of effector and target cells, and the expressions of the CD3 and CD19 receptors were varied. The agreement with the model with the data were excellent in most cases which led to several mechanistic conclusions. In particular, the study found that target cells with lower CD19 expressions escape the T cell killing.

The in vivo extension of the model showed reasonable agreements with the kinetics of B cell populations in patients where the data were obtained from a published clinical trial. The model explained differences in B cell population kinetics between responders and non-responders and found that the differences were driven by the differences in the T cell numbers between the groups. The ability of the model to describe the in vivo kinetics is promising. In addition, the model leads to some interesting conclusions, e.g., the model shows that the bone marrow harbors tumor growth during the BiTE treatment. The authors then used the model to propose an alternate dosage scheme for BiTEs that needed a smaller dose of the drug.

Weaknesses

There are several weaknesses in the development of the model. Multiscale models of this nature contain parameters that need to be estimated by fitting the model with data. Some these parameters are associated with model approximations or not measured in experiments. Thus, a common practice is to estimate parameters with some 'training data' and then test model predictions using 'test data'. Though Supplementary file 1 provides values for some of the parameters that appeared to be estimated, it was not clear which dataset were used for training and which for test. The confidence intervals of the estimated parameters and the sensitivity of the proposed in vivo dosage schemes to parameter variations were unclear.

The model appears to show few unreasonable behaviors and does not agree with experiments in several cases which could point to missing mechanisms in the model. Here are some examples. The model shows a surprising decrease in the T cell-target cell synapse formation when the affinity of the BiTEs to CD3 was increased; the opposite should have been more intuitive. The authors suggest degradation of CD3 could be a reason for this behavior. However, this probably could be easily tested by removing CD3 degradation in the model. Another example is the increase in the % of engaged effector cells in the model with increasing CD3 expressions does not agree well with experiments (Fig. 3d), however, a similar fold increase in the % of engaged effector cells in the model agrees better with experiments for increasing CD19 expressions (Fig. 3e). It is unclear how this can be explained given CD3 and CD19 appears to be present in similar copy numbers per cell (~104 molecules/cell), and both receptors bind the BiTE with high affinities (e.g., koff < 10-4 s-1).

The model does not include signaling and activation of T cells as they form the immunological synapse (IS) with target cells. The formation IS leads to aggregation of different receptors, adhesion molecules, and kinases which modulate signaling and activation. Thus, it is likely the variations of the copy numbers of CD3, and the CD19-BiTE-CD3 will lead to variations in the cytotoxic responses and presumably to CD3 degradation as well. Perhaps some of these missing processes are responsible for the disagreements between the model and the data shown in Fig. 3. In addition, the in vivo model does not contain any development of the T cells as they are stimulated by the BiTEs. The differences in development of T cells, such as generation of dysfunctional/exhausted T cells could lead to the differences in responses to BiTEs in patients. In particular, the in vivo model does not agree with the kinetics of B cells after day 29 in non-responders (Fig. 6d); could the kinetics of T cell development play a role in this?

Addressing these concerns and a discussion of the limitations will make the conclusions of the study stronger and will provide cues for extending the approach for future studies.

Reviewer #3 (Public Review):

In this manuscript, Meyer and colleagues characterized the conserved dosage compensation complex (DCC) and its recruitment mechanisms to X chromosomes in C. briggsae. This paper features comparative analyses of the dosage compensation mechanisms between C. briggsae and C. elegans, which are separated by 15-30 million years in evolution. While the dosage compensation machinery and the regulatory hierarchy are conserved, the target specificity of the DCC complex, the density of the recruiting motifs, and the mode of recruitment have diverged between the two species. The authors speculated that the divergence of the X chromosome DCC target sites could have been a factor for nematode speciation.

Overall, this is a thorough work demonstrating how the dosage compensation mechanisms in C. briggsae compare with those in C. elegans. By employing a series of complementary assays, the authors provided compelling evidence, establishing how C. briggsae and C. elegans have diverged DCC recruitment sites and motifs, while the composition of the DCC and the regulatory hierarchy are conserved. The manuscript is clearly written, and all the experiments are rigorously performed with proper controls. The figures are also effective and nicely illustrate the experimental designs and the results. The conclusions drawn from the current work are compelling, and I have no major concerns.

Reviewer #3 (Public Review):

The paper uses multiple approaches in cultured cells to show that the rapid depletion of accessible plasma membrane cholesterol by 25-hydroxycholesterol is mediated by the activation of the cholesterol-esterifying enzyme acylCoA:cholesterol acyltransferase (ACAT). They carefully consider and exclude other potential mechanisms that could explain the effects of 25-OH cholesterol on the plasma membrane cholesterol pool, such as decreased cholesterol biosynthesis or activation of LXR transcription factors. Cell lines with mutations in ACAT and in cholesterol homeostatic factors are used in an ingenious fashion to support the role of ACAT and exclude these other mechanisms. The in vivo relevance of accessible membrane cholesterol and ACAT is then demonstrated for toxic cytolysin binding to cells, Listeria infection in vivo, and Zika and Coronavirus infections of cultured liver cells. Overall, the evidence is exceptional that ACAT modulates the plasma membrane accessible cholesterol pool as a strategy of the host to protect against various infectious agents. The discussion of the paper could be broadened to include other mechanisms that are known concerning the role of 25-OH cholesterol in infectious processes and the body's responses.

Reviewer #3 (Public Review):

The current manuscript undoubtedly demonstrates that gene expression associated with healthy or diseased donor cartilage used to derive iPSCs influences the iPSCs potential to differentiate to functional chondrocytes. Using comprehensively designed and described experimental approaches they have shown that even though AC-iPSC and OA-iPSC have similar characteristics in terms of stemness and pluripotency, they vary significantly in terms of their chondrogenic differentiation potential. Further, they showed that AC-iMSC and OA-iMSC which are derived from the AC and OA-iPSCs also show similar phenotypic characteristics but differ significantly in terms of their chondrogenic differentiation. The pan-transcriptional analysis confirmed that the AC and OA-iMSC preserve their epigenetic and metabolism-associated transcriptional memory from AC or OA donor cells which in turn regulate their differentiation to chondrocytes. In summary, these findings have significant implications for designing new approaches to enhance the differentiation potential of iPSCs to desired cells for regenerative research.

Reviewer #3 (Public Review):

This is a valuable addition to the currently available arsenal of methods to study the Drosophila brain.

There are many positives to the present manuscript as it is:<br /> (i) The introduction makes a clear and fair comparison with other available tracing methods.<br /> (ii) The authors do a systematic analysis of the factors that influence the labeling by retro-tango (age, temperature, male versus female, etc...)<br /> (iii) The authors acknowledge that there are some limitations to retro-TANGo. For example, the fact that retro-T does not label all the expected neurons as indicated by the EM connectome. This is fine because no technique is perfect, and it is very laudable that the authors did a serious study of what one should expect from retro-tango (for example, a threshold determined by the number of synapses between the connected neurons).

Reviewer #3 (Public Review):

In the study, the authors present a mathematical framework and data analysis approach that revisits an "old" idea in cell physiology: The role of co-substrate cycling as potential key determinant of reaction flux limits in enzyme-catalyzed reaction systems. The aim of the study is to identify metabolic network properties that indicate potential global flux regulatory capacities of co-substrate cycling.

The authors approached this aim in two steps. First, a mathematical framework, which is based on ODEs was developed and which reflects small abstract metabolic pathways including kinetic parameters of the involved reactions. While the modeled pathways are abstract, the considered pathway motifs are motivated by structures of known existing pathways such as glycolysis (as example of a linear pathway) and certain amino acid biosynthesis pathways (as example of branched pathways). The developed ODE-based models were used for steady state analysis and symbolic and numerical simulations of flux dynamics. As a main result of the first step, the authors highlight that co-substrate cycling can act as mechanism which limits specific metabolic fluxes across the metabolic network and that co-substrate cycling can facilitate flux regulation at branching points of the network. Second, the authors re-analyzed data on flux rates (experimental measurements and flux-balance-analysis predictions) from previous publications in order to assess whether the predicted role of co-substrate cycling could explain the observed flux distributions. In this data analysis, the author provide evidence that the fluxes of specific reactions in central metabolism could be constrained by co-substrate cycling, because their observed fluxes are often lower than expected by the kinetics of the corresponding enzymes.

A particular strength of the study is that the authors highlight that co-substrates are not limited to ATP and NAD(P)H, but could include a range of other metabolites and which could also be organism-specific. Building on this broad definition of co-substrates, the authors developed an abstract mathematical framework that can be used to study the general potential 'design principle' of co-substrate cycling in cellular metabolism and to adapt the framework to study different co-substrates in specific organisms in future works.

Experimental data (i.e. measured fluxes using mass-spectrometry data and labeled substrates) that is available to date is limited and therefore also limits the broad evaluation of the developed mathematical framework across various different organisms and environmental conditions. However, with advances in metabolomics and derived metabolic flux measurements, the mathematical framework will serve as a valuable resource to understand the potential role of co-substrate cycling in more biological systems. The framework might also guide new experiments that generate data for a systematic evaluation of when and to what extent co-substrate cycling governs flux distributions, e.g. depending on growth rates or response to environmental stress.

Reviewer #3 (Public Review):

This article analyzes retrospective follow-up data from 482914 patients in the Danish National Patient Registry, with the goal of characterizing the association between blood type, as measured by the ABO and RhD blood group systems, and the incidence of ICD-based phenotypes ('phecodes'). The primary statistical tool employed is a log-linear model, fit separately for each phecode, with the outcome being the number of recorded phecodes per person over the follow-up period. Because the ABO blood group systems contains four subgroups, the authors choose to compare each subgroup - one at at time - against all others. The primary findings are described in Manhattan plots (one for each subgroup), which visually identify statistically significant associations between that blood group and the phecode.

This study has a number of strengths. By using the Danish National Patient Registry, the study population is better characterizable than most phenome-wide association studies. The statistical models employed are appropriate. And the findings are clearly and concisely communicated.

A weakness of the underlying approach is that, by separately modeling each ABO blood subgroup one at a time and collapsing the remaining subgroups, the interpretation of the resulting estimated rate ratio is based upon an assumption that the remaining subgroups have a common incidence. But this cannot be simultaneously true unless all four subgroups have a common incidence, i.e. unless the null scenario holds everywhere. The number of statistically significant phecodes in each of the ABO subgroups reflects the underlying prevalence of each subgroup (more cases allows for greater precision in estimation and therefore smaller p-values) but does not necessarily reflect actual differences in the incidence.

Reviewer #3 (Public Review):

The work provides interesting information on human CARD8 for its role in sensing HIV-1 infection and subsequent inflammasome activation as a possible cause of HIV pathogenesis. Proteolytic cleavage at the N-terminus of human CARD8 was confirmed by western blotting of HEK293T cells co-transfected with a CARD8-expression vector and HIV proviral constructs. This analysis also allowed the definition of substrate/enzyme specificity - only human CARD8 is susceptible to proteases derived from HIV and SIV; CARD8s of other gibbons and Old-World monkeys are not due to a single amino acid variation at the P1' position. One thing to note is that the efficiency of this cleavage reaction appeared fairly low because this product (33 kD in Figure 1B) only consisted of a small portion of total CARD8 antibody reactive proteins. To define the correlation between HIV infection and CARD8-mediated inflammasome activation in THP-1 model cells, authors used cell death by propidium iodide staining and IL-1β secretion as inflammasome activation biomarkers. However, cell death measured by propidium iodide staining could be caused by a variety of factors/pathways and thus not specific for pyroptosis resulting from CARD8-mediated inflammasome activation, complicating data interpretation. With IL-1β secretion as an indicator, authors concluded that TLR2 priming (by Pam3CSK4) is required for inflammasome activation by HIV infection, which raises a question of whether HIV infection alone is sufficient at CARD8 activation in THP-1 cells. Data obtained with clonal CARD8 knockout THP cells by CRISPR/cas9 provide clean results confirming that CARD8-mediated inflammasome activation contributes to IL-1β secretion and cell death in parallel with other inflammasome pathways. Data obtained from CARD8KO cells complemented with CARD8 proteins with various substrate sequences provided vital evidence showing that proteolysis at the N-terminus of human CARD8 by HIV-1 protease contributed to CARD8-mediated inflammasome activation although at levels much lower than VbP-stimulated inflammasome activation that appeared to be independent of HIV PR catalyzed N-terminus cleavage. Taken together, this report presents evidence that supports the involvement of human CARD8-mediated inflammasome activation via the N-terminus cleavage by HIV PR, which added valuable information to advance the understanding of pathogenesis caused by HIV infection. However, how much it contributes to HIV-1 pathogenesis remains to be further defined as the contributions are expected to be diverse among cell types and homeostatic stages of infected cells.

Reviewer #3 (Public Review):

This study investigates the efficacy of exosomes of neuronal stem cells (NSC) derived from human iPSCs) in improving NSC therapy for neuroprotection in mouse stroke model. The results show that at one-week post-stroke, administration of NSCs through lateral ventricle injections in combination with exosomes significantly improved post-stroke survival, neurological function recovery and brain lesion attenuation in mice at 8-week post treatment. The strengths of this study include: 1) the positive outcomes from this combinatory treatment delivered at the subacute phase; 2) multiple assessments of neurological function impairments; 3) non-invasive, unbiased assessment of brain lesion with MRI. However, the evaluation of the possible underlying mechanisms is weak, which included reduction of reactive astrocytes, increased NeuN+ cells, and possible roles of anti-inflammatory miRNA profiles of exosomes from NSCs in the study. Further strengthening of the relationship in the above phenomena will be beneficial for developing cell therapy for ischemic stroke.

Reviewer #3 (Public Review):

The study investigates the consequences of mixing a ligase ribozyme, its substrates, and oligo(Lys) peptides of different lengths in the context of a coacervate droplet protocell in a 'Nucleic Acid World' as an early stage of life. The study shows convincingly several very interesting results that are certain to have an impact on origins-of-life studies: First, the activity of ribozymes in the coacervate droplets - the formation of longer RNAs - affects the size of the droplets, with inactive ribozymes leading to more droplet fusion. Second, this behavior is reflected in the adhesion to hydrophobic surfaces, showing that not only the size but also the physical properties of the droplets are changed by ribozyme catalysis. Third, the exchange rate of material between droplets is also affected by ribozyme catalysis, which has important implications for coacervates as model systems for early life forms.

More detailed information should be provided in the text that ribozyme catalysis actually proceeds in/on the coacervates, a discussion section needs to be devoted to the implication of ribozyme catalysis affecting the measured material exchange rates on the coupling of genotype/phenotype, molecular parasites, and the inflow/outflow of metabolites, and the importance of the system with longer peptides needs to be clarified and perhaps toned down.

Reviewer #3 (Public Review):

Zarzor et al. developed a new multifield computational model, which couples cell proliferation and migration at the cellular level with biological growth at the organ level, to study the effect of OSVZ on cortical folding. Their approach complements the classical experimental approach in answering open questions in brain development. Their simulation results found the existence of OSVZ triggers the emergence of secondary mechanical instabilities that leads to more complex folding patterns. Also, they found that mechanical forces not only fold the cortex but also deepen subcortical zones as a result of cortical folding. Their physics-based computational modeling approach offered a novel way to predictively assess the links between cellular mechanisms and cortical folding during early human brain development, further shedding light on identifying the potential controlling parameters for reverse brain study.

Strengths:<br /> The newly developed physics-based computational model has several advantages compared to previous existing computational brain models. First, it breaks the traditional double-layer computational brain model, gray matter layer and white matter layer, by introducing the outer subventricular zone. Second, it develops multiscale computational modeling by bringing the cellular level features, cell diffusion, and migration, into the macroscale biological growth model. Third, it could provide a cause-effect analysis of cortical folding and axonal fiber development. Finally, their approach could complement, but not substitute, sophisticated experimental approaches to answer some open questions in brain science.

Weaknesses:<br /> The cellular diffusion and migration seem determined and controlled by a single variable, cell density, which is one-way coupled with the deformation gradient of the brain model. However, cell migration and diffusion should be potentially coupled with stress and vice versa. Also, the current computational model can be improved by extending it to a 3D model. Finally, they can further improve the study of regional proliferation variation by introducing fully-randomized heterogenous cell density and growth in their model.

Reviewer #3 (Public Review):

This is a well-executed study, offering thorough analysis and insightful interpretations. It is well-written, and I find the conclusions interesting, important, and well-supported.

Reviewer #3 (Public Review):

Cahoon set out to demonstrate that sexual dimorphic outcomes of meiosis are caused by different regulations of the synaptonemal complex (SC). In the employed model organism C. elegans it has been shown that the SC consists of at least 6 different proteins (SYP-1-6) and that their assembly into this intricate structure is mutually dependent and that crossover formation is drastically, if not completely abolished, in the absence of individual SC mutants (SYP-5 and SYP-6 are functionally redundant).

The authors employ FRAP analysis and examine the rate of reincorporation of the synapsis components SYP-2 and SYP3 in three different regions of the gonad and compare the incorporation after photobleaching in hermaphrodite and male gonads. They find that SYP-2 dynamics is increased in spermatocytes, whereas in oocytes SYP-3 dynamics is increased. They also found differing profiles of incorporation during the progression of prophase I for those two synapsis components in the two sexes.

Furthermore, the authors show that syp-2/+ and syp-3/+ show signs of haploinsufficiency, as demonstrated by increased embryonic lethality and the missegregation of the X chromosome. In these mutants, the authors examined the kinetics of the appearance of recombination foci, where they used RAD-51 as a measure for progress of homologous recombination and repair pathway choice (repair via the sister versus the homolog and/or non-homologous end joining), MSH-5 for stabilisation of the strand invasion product and COSA-1 as a marker for crossover designation.<br /> The authors show that in the hypomorphs the behaviour of some recombination markers change. The counts of the numbers of COSA-1 are not explaining the missegregation of the X chromosome. The localisation of the crossovers shifts towards the pairing centre chromosome ends in the hypomorphs.

The manuscript is descriptive and the link that dimorphic incorporation rates of SYP-2 and SYP-3 are causative for recombination dimorphisms is not substantiated by the shown experiments. The observed phenomena in the heterozygous syp mutants could be due to general SC defects and not the lack of a critical amount at a specific point during recombination. Overall, the FRAP experiments do not address the possible different synthesis rates of the employed markers (it would be more meaningful to examine the incorporation under protein synthesis inhibitory conditions) or use a photoconvertible tag, that allows the assessment of new synthesis. It has been well documented that in the more distal regions of the gonad gene expression is upregulated. It is not clear what the contribution of differing gene expression of the examined synapsis proteins to the different dynamic behaviour actually is.

Reviewer #3 (Public Review):

The authors examine the role of secreted BAFF in senescence phenotypes in THP1 AML cells and primary human fibroblasts. In the former, BAFF is found to potentiate the inflammatory phenotype (SASP) and in the latter to potentiate cell cycle arrest. This is an important study because the SASP is still largely considered in generic and monolithic terms, and it is necessary to deconvolute the SASP and examine its many components individually and in different contexts.

Although the results show differences for BAFF in the two cell models, there are many places where key results are missing and the results over-interpreted and/or missing controls.

1. Figure 1. Test whether the upregulation of BAFF is specific to senescence, or also in reversible quiescence arrest.

2. Figure 1, Supplement 1G. Show negative control IgG for immunofluorescence.

3. All results with siRNA should be validated with at least 2 individual siRNAs to eliminate the possibility of off-target effects.

4. To confirm a role for IRF1 in the activation of BAFF, the authors should confirm the binding of IRF1 to the BAFF promoter by ChIP or ChIP-seq.

5. Key antibodies should be validated by siRNA knockdown of their targets, for example, TACI, BCMA, and BAFF-R in Figure 5. Note that there is an apparent discrepancy between BCMA data in Figure 5B vs 5C.

6. Figure 5E. Negative/specificity controls for this assay should be shown.

7. Hybridization arrays such as Figure 5H, Figure 6 - Supplement 1I, and Figure 6H should be shown as quantitated, normalized data with statistics from replicates.

8. Figure 6B - Supplement 1. Controls to confirm fractionation (i.e., non-contamination by cytosolic and nuclear proteins) should be shown.

9. Figure 6A. Knockdown of BAFF should be shown by western blot.

10. Figure 6G. Although BAFF knockdown decreases the expression of p53, p21 increases. How do the authors explain this?

Reviewer #3 (Public Review):

This paper by Padavannil et al. presents a new cryo-EM structure of mitochondrial complex I from Drosophila melanogaster. This is a timely and important study - the new structure and comparative analysis would allow new insights into mitochondrial complex I mechanism and regulation. The major strength is the advanced CryoEM analysis and structure resolution. The manuscript is well-written and scientifically sound, but a clear weakness is the lack of classical enzyme kinetic analysis of the A/D transition, even though this is supposed to be the foundation for the main conclusion of the manuscript. However, the interpretation of the data is rational and scientifically justified.

Reviewer #3 (Public Review):

In this manuscript, Kim et al. use a deep generative model (a Variational Auto Encoder previously applied to adult data) to characterize neonatal-fetal functional brain development. The authors suggest that this approach is suitable given the rapid non-linear development taking place in the human brain across this period. Using two large neonatal and one fetal datasets, they describe that the resultant latent variables can lead to improved characterization of prenatal-neonatal development patterns, stable age prediction and that the decoder can reveal resting state networks. The study uses already accessible public datasets and the methods have been also made available.

The manuscript is clearly written, the figures excellent and the application in this group novel. The methods are generally appropriate although there are some methodological concerns which I think would be important to address. Although the authors demonstrate that the methods are broadly generalisable across study populations - however, I am unsure about the general interest of the work beyond application of their previously described VAE approach to a new population and what new insight this offers to understanding how the human brain develops. This is a particular consideration given that the major results are age prediction (which is easily done with various imaging measures including something as simple as whole brain volume) and recapitulation of known patterns of functional activity in neonates. As such, the work will be of interest to researchers working in fMRI analysis methods and deep learning, but perhaps less so to a wider neuroscience/clinical readership.

Specific comments:<br /> 1. If I understand correctly, the method takes the functional data after volume registration into template space and then projects this data onto the surface. Given the complexities of changing morphology of the development brain. would it not be preferable to have the data in surface space for standard space alignment (rather than this being done later?). This would certainly help with one of the concerns expressed by the authors of "smoothing" in the youngest fetuses leading to a negative relationship between age and performance.<br /> 2. A key limitation which I feel is important to consider if the method is aiming to be used for fetuses is the effects of the analysis being limited only to the cortical surface - and therefore the role of subcortical tissue (such as developmental layers in the immature white matter and key structures like the thalami) cannot be included. This is important, as in the fetal (and preterm neonatal) brain, the cortex is still developing and so not only might there be not the same kind of organisation to the activity, but also there is likely an evolving relationship with activity in the transient developmental layers (like the subplate) and inputs from the thalamus.<br /> 3. As the authors correctly describe, brain development and specifically functional relationships are likely evolving across the study time window. Beyond predicting age and a different way of estimating resting state networks using the decoding step, it is not clear to me what new insight the work is adding to the existing literature - or how the method has been specifically adapted for working with this kind of data. Whilst I agree that these developmental processes are indeed likely non-linear, to put the work in context, I think the manuscript would benefit from explaining how (or if) the method has been adapted and explicitly mentioning what additional neuroscientific/biological gains there are from this method.<br /> 4. The unavoidable smoothing effect of VAE is very noticeable in the figures - does this suggest that the method will be relatively insensitive to the fine granularity which is important to understand brain development and the establishment of networks (such as the evolving boundaries between functional regions with age) - reducing inference to only the large primary sensory and associative networks? This will also be important to consider for the individual "reconstruction degree" - (which it would likely then overstate - and would need careful intersubject comparison also) if it was to be used as a biomarker or predictor of cognition as suggested by the authors.

Reviewer #3 (Public Review):

This study combines data from cryo-electron microscopy, electrophysiology and cellular localization studies to provide insight into the structure and potential function of two orthologues of the membrane protein Orf3a from the corona viruses SARS-CoV-1 and SARS-CoV-2. The work follows up on previous studies, which assigned these proteins as viral ion channels (viroporins). By using patch-clamp electrophysiology in different cellular systems and from reconstituted protein, the authors provide convincing evidence that these proteins do likely not function as ion channels and that previous conclusions in this direction were presumably based on experimental artifacts. The lack of functional evidence is supported by structures of both proteins in different lipid environments, which concur with previous structures of the same system, and which do not show characteristic features of an ion channel. Instead, the authors describe the localization of both proteins on the plasma membrane and endo-lysosomal compartments, and they show specific interactions of the orthologue from SARS-CoV2 but not SARS-CoV1 with the protein VPS39, which as part of the HOPS complex is involved in the fusion of late endosomes and autophagosomes with lysosomes.

The strength of this manuscript relies on the wealth of high-quality data and its careful analysis, which refutes the presumed function of the viral membrane protein Orf3a as viroporin. Instead, the work provides conclusive evidence for its involvement in a different process. The electrophysiology data is very well carried out and the authors make a convincing case that the observed lack of specific currents renders a role of Orf3a as ion channel as highly unlikely. Similarly, the structural data and the cellular studies are of high quality.

The main weakness of the study, which should be considered minor in light of the strong results, relates to the unclear relevance of structural features of Orf3a to the still poorly defined function of the protein. In this respect, I regard the discussion of potential lipid density at the cytoplasmic side as exaggerated. The only region that was assigned a functional importance in mediating interactions with the protein VPS39 is unstructured and only found in one of the two orthologs. Although the data describing the interaction between SARS-CoV-2 Orf3a and VPS39 is conclusive, a function of Orf3a that is common to both viral orthologs is still missing. These weaknesses can be addressed by some revision of the text whereas the clarification of the role of Orf3a is beyond the scope of the current study and should be addressed in future work.

Reviewer #3 (Public Review):

In some contexts, individual neurons in the hippocampus of rodents, called time cells, can spike selectively after a specific amount of time following a triggering event. Hippocampal neurons can also encode the traversal of a specific amount of distance (for example, running on a treadmill). Some hippocampal neurons also appear to represent mixtures of these features in addition to classical representations of place selectivity. In this manuscript, Abramson et al. hypothesize that the formation of these representations might be influenced by the task which the animal is performing in the context of the recording. To test this hypothesis, they exploit data from a previous maze-running study (Kraus et al., 2013) in which rats were trained to run on a treadmill across several trials of a session at experimentally-varied velocities. (This study had originally been done to tease apart potential confounds in the questions regarding representations of time versus distance.) In the Kraus et al. study, these walks occurred in one of two contexts or "session types." In a "fixed time" condition, on the other hand, the animal ran on the treadmill for a fixed amount of time before leaving the treadmill. In a "fixed-distance" condition, the animal ran on the treadmill for a "fixed-distance" (in the sense of self-motion). Abramson et al. conjectured that hippocampal pyramidal cells would be biased to represent elapsed time (from entering the treadmill) in the fixed-time condition, whereas they would be biased to represent elapsed distance in the fixed-distance condition. This conjecture appears to be due to the fact that the reward structure of the task motivates the prediction of elapsed time in the fixed time condition, whereas it motivates the prediction of elapsed distance in the fixed distance condition.

To test this hypothesis, the authors use the velocity of the treadmill in each trial to predict the onset of a cell's spiking activity after entering the treadmill. Such predictions would have quite different forms depending on whether the cell's representation correlates with time vs. distance, for example. The authors then use a comparison of the error in each of those two predictors, parametrically formulated, to build a classifier that predicts session type from the spiking onsets of a cell across the trials in that session. The classifier is fit to the Kraus et al. data and optimized to maximize rate of classification as distance cells in the fixed-distance sessions, and minimize rate of classification as time cells in distance sessions. By this metric, they find that 69% of cells in fixed-distance sessions are classified as distance cells, and 68% of cells in the fixed-time sessions are classified as time cells. Applying these results to a parametric hypothesis test, the null hypothesis that session type is independent of cell classifications is strongly rejected. Two other classifiers, based on similar comparisons, found similar results.

The authors conjecture that these findings may be due to the fact that the structure of the task was such that anticipation of reward would depend on "distance" traversed in the fixed-distance sessions, whereas it would depend on time elapsed in the fixed-time sessions. Thus the results are aimed to provide evidence supportive of widely-discussed theories which view the selectivity observed in hippocampal firing patterns as exemplars of predictive coding.

Weaknesses:

The original study of Kraus et al. consisted of 3 rats for which all sessions, including both training and recording, were of one type. Another 3 rats had a hybrid mixture of distance and time sessions. This is mentioned very briefly in the main text. It would appear that the theory of reward might lead to different predictions that could be verified by comparing these animals session to session at a finer grain. For example, are there examples of cells switching or transforming their "predictive" representations when a large number of trials in on session type is followed by a large number of trials of the opposite type? For another example, the transition from training to recording could give similar opportunities. It seems at least possible that ignoring these issues could cause a loss of power.

Some circularities in the construction and interpretation of the time-cell and distance-cell classifiers are not clearly addressed. The classifiers currently appear to be fit to predict the type of session a cell's response patterns are observed within. But it is tautological to use the session type to define the cell type. I sense this is ultimately reasonable because of how the classifier is built, but this concern is not addressed or explained.

Less parametric statistical thinking could be more convincing. Partly this could be a matter of explaining how and why the three classifiers were constructed and their respective scientific motivations. The strong literal finding is the rejection of the hypothesis of independence between cell response properties and session type. A measure of the strength of this effect is missing.

Reviewer #3 (Public Review):

The major strength of the study was the approach of using photosensitive protein variants to replace endogenous protein with the 1-step Crispr-based gene editing, which not only allowed acute manipulation of protein function but also mimicked the endogenous targeted protein. However, the same strategy has been used by the same first author previously in dividing cells, somewhat reducing the novelty of the current study. In addition, the results obtained from the study were the same as those from previous studies using different approaches. In other words, the current study only confirmed the known findings without any novel or unexpected results. As a result, the study did not provide strong evidence regarding the advantage of the new experimental approach in our understanding of the function of EB1. Some specific comments are listed below.

1. In Figure 1, to show that the photosensitive EB1 variant did not affect stem cell properties and their neuronal differentiation, Oct4 staining and western blot of KIF2C and EB3 were not strong evidence. Some new experiments more specifically related to stem cell properties or iPSC-derived neurons are necessary. In addition, the effect of EB1 inactivation on microtubule growth was quantified in stem cells but not in differentiated neurons, which supposed to be the focus of the study. In Figure S2D, quantification is needed to show the effect of blue light-induced EB1 inactivation in growth cones.

2. In Figure 2, the effect of blue light on microtubule retraction in the control cells was examined, showing little effect. However, it is still unclear if the blue light per se would have any effect on microtubule plus end dynamics, a more sensitive behavior than that of retraction. In Figure 2C, the length of individual microtubules in different growth cones was presented, showing microtubule retraction after blue light. Quantification and statistical analysis are necessary to draw a strong conclusion.

The results showed that EB3 did not seem to contribute to stabilizing microtubules in growth cones. It was discussed that EB3 might have a different function from that of EB1 in the growth cone, although they are markedly up-regulated in neurons. In the differentiated neuronal growth cones examined in the study, does EB3 actually bind to the microtubule plus ends? In the EB3 knockout cells without the blue light, the microtubules were stable, indicating that EB3 had no microtubule stabilization function in these cells. Is such a result consistent with previous studies? If not, some explanation and discussion are needed.

3. In Figure 3, for the potential roles of EB1 on actin organization and dynamics, only the rates of retrograde flow were measured for 5 min. and no change was observed. However, based on the images presented, it seemed that there was a reduced number of actin bundles after blue light and the actin structure was somewhat disrupted. Some additional examination and measurement of actin organization are necessary to get a clear result.

4. In Figure 4, the effect of blue light and EB1 inactivation on neurite extension need to be quantified in some way, such as the neurite length changes in a fixed time period, and the % of growth cones passing the blue light barrier compared with growth cones of the control cells.

5. For the quantification of growth cone turning, a control condition is needed to show that blue light itself has no effect on turning.

Reviewer #3 (Public Review):

Noonan et al. developed a clever reporter of TGFbeta signaling using human A375 melanoma cells to identify a TGFbeta-induced enhancer and generated a zebrafish transgenic line to monitor TGFbeta activation during the development of melanoma. They found that few discrete cells in advanced melanoma express the TIE:EGFP reporter, and used single-cell sequencing to identify differences in gene expression between these TGFbeta-responsive melanoma cells and the remaining population. They found that these cells downregulate interferon signaling and upregulate a gene signature compatible with chronic TGFbeta signaling that favours metastasis and requires AP-1 binding to regulatory elements of the target genes. Then they overexpressed SATB2, a known inducer of TGFbeta activation, in whole melanoma to increase the amount of TIE:EGFP positive cells for better characterization. Among the TIE:EGFP positive cells they retrieved a population of macrophages (Marco positive in single-cell analysis) and interpreted this observation as due to the phagocytic activity of macrophages that preferentially phagocytose TIE:EGFP positive melanoma cells. Since melanoma cells expressing TGFbeta upregulate a chronic TGFbeta signature that favours metastasis, downregulate interferon signaling, and are preferentially phagocytosed by macrophages that, as a consequence, turn on M2 markers (immunosuppressive), the authors conclude that this work highlights the need for the identification of a chronic TGFbeta biomarker signature to predict patient response to TGFbeta inhibitors.

The conclusions of this paper on melanoma cells are mostly well supported by data, while the data concerning macrophages and their interpretation need strengthening with better images and additional data analysis.

Reviewer #3 (Public Review):

The manuscript by Jia, Ratzan et al. is elegant and makes an important contribution to the hair cell and PCP field. Using a subtractive approach involving deep sequencing of the mouse Emx2 mutant and control mice, they identified Stk32a as a candidate gene regulated by EMX2. Next, they made a Stk32a mouse mutant and showed that STK32a is necessary/sufficient to determine hair bundle orientation in the vestibule. Moreover, they show that STK32A governs GPR156. The images are compelling. I have no major concerns.

Reviewer #3 (Public Review):

The manuscript by Ray et al. reports a massive body of work targeting the transport cycle of a class of LeuT-fold transporters that specializes in metal transport, the Nramps. The Gaudet laboratory has published extensively on this family of proteins and here they ask the question of how Nramps can transport one of their physiological substrates Mn2+ and how that differs structurally from a toxic metal like Cd2+. The authors capitalize on previously published mutations to trap the transporter in three states with and without Mn2+. Together with ITC data and MD simulations, they put together a plausible, albeit oversold, model of transport. I am not an expert on the details of the technical elements but overall given they appear sound and the corresponding author is a noted expert in crystallography. The structures recapitulate previously seen conformational changes. Nevertheless, the mechanistic story is new and of interest.

Reviewer #3 (Public Review):

In this work, the authors explored some of the oculomotor mechanisms that humans put in place when observing other people looking somewhere. This tendency is generally known as 'gaze following' and represents a fundamental behaviour to obtain fluid social interactions with both others and the environment.

The strengths of this work can be found in the approach of the analysis, which provides a rich perspective on how human eye movements are shaped by social cues. I have appreciated the combination of more traditional analyses with more sophisticated approaches such as artificial intelligence.

At the same time, the complexity of the data analysis could lead to difficulties in understanding the whole picture emerging from here. The task itself should be described in more detail. In addition, I have also the feeling that some theoretical aspects concerning gaze following and social attention, in general, have been little discussed, leaving room for more technical and formal aspects. For instance, I am wondering if a control condition in which the gazer is looking towards a non-social item (such as an object) could be of interest and potentially important to better qualify these data within a social dimension.

Reviewer #3 (Public Review):

In this paper, Baker and colleagues present a model for the evolutionary dynamics of PRDM9 - the protein that determines where recombinations occur in many species. PRDM9 is one of the most rapidly evolving proteins and theoretical models have been developed to understand why it evolves so rapidly. The most popular of these models assumes that PRDM9 (indirectly) causes double-strand breaks where it binds DNA, and this in turn causes the erosion of its binding sites. Over time, this reduces the number of double-strand breaks, ultimately imperiling the proper segregation of chromosomes and hence causing selection for a new PRDM9 allele that can bind new sites. Unfortunately, recent experimental evidence has shown that PRDM9 merely positions where double-strand breaks occur and that the number of double-strand breaks is controlled independently of PRDM9. This new understanding of the biology of PRDM9 then casts doubt on the previous model for why PRDM9 evolves so rapidly, demanding a new explanation.

This paper takes this updated view of the biology of PRDM9 and formalizes it into a mathematical model of how evolution will act on different PRDM9 alleles and their binding sites. The model is very carefully couched in our current understanding of PRDM9 and is solidly analyzed. Altogether, this paper convincingly reconciles the rapid evolution of PRDM9 and the rapid erosion of its hotspots with the biological finding that PRDM9 itself does not drive double-strand break formation.

Reviewer #3 (Public Review):

Bavard & Palminteri extend their research program by devising a task that enables them to disassociate two types of normalisation: range normalisation (by which outcomes are normalised by the min and max of the options) and divisive normalisation (in which outcomes are normalised by the average of the options in ones context). By providing 4 different training contexts in which the range of outcomes and number of options vary, they successfully show using 'ex ante' simulations that different learning approaches during training (unbiased, divisive, range) should lead to different patterns of choice in a subsequent probe phase during which all options from the training are paired with one another generating novel choice pairings. These patterns are somewhat subtle but are elegantly unpacked. They then fit participants' training choices to different learning models and test how well these models predict probe phase choices. They find evidence - both in terms of quantitive (i.e. comparing out-of-sample log-likelihood scores) and qualitative (comparing the pattern of choices observed to the pattern that would be observed under each mode) fit - for the range model. This fit is further improved by adding a power parameter which suggests that alongside being relativised via range normalisation, outcomes were also transformed non-linearly.

I thought this approach to address their research question was really successful and the methods and results were strong, credible, and robust (owing to the number of experiments conducted, the design used and combination of approaches used). I do not think the paper has any major weaknesses. The paper is very clear and well-written which aids interpretability.

This is an important topic for understanding, predicting, and improving behaviour in a range of domains potentially. The findings will be of interest to researchers in interdisciplinary fields such as neuroeconomics and behavioural economics as well as reinforcement learning and cognitive psychology.

Reviewer #3 (Public Review):

Mtb antigens were traditionally discovered through crude direct methods such as immune-blotting of Mycobacterium tuberculosis (Mtb) culture filtrate (or whole cell lysate), or indirectly through T cell / APC stimulation experiments. The manuscript addresses the critical question of which Mycobacterium tuberculosis (Mtb) antigens are presented in peptide form on the surface of macrophages that are actually infected with Mtb. The identification of such antigens is particularly important for defining targets for TB vaccine design since CD8 T cells are an important component of the adaptive immune response to Mtb and macrophages are the most important phagocyte target of Mtb infection. The authors directly isolate MHC-I molecules from human monocyte-derived macrophages, elute MHC-I bound peptides from several HLA types, and screen for sequences found among Mtb antigens, which they find to represent only 0.1% of all peptides screened. The authors make the interesting observation that the majority of peptides identified (13 of 16) correspond to antigens secreted by the unique Type-7 Secretion System (T7SS) of Mtb. Another strength is the experiments to determine whether these T7SS substrates preferentially gain access to the cytosol for MHC-I loading via phagosome permeabilization by identifying the colocalization of Mtb with markers of phagosomal membrane damage (rather than MHC-I). The authors used quantitative mass spec to quantify and compare the expression of two peptides presented on HLA-A*02:01 and -B*57:01, demonstrating similar expression after infection with H37Rv, but that infection with an Esx1-deficient Mtb mutant did not lead to the presentation of either peptide even though one of these peptides was part of a separate Esx locus. Although only two peptides were assessed and compared using quantitative mass spec, these data imply that Esx1 was required for the presentation of the antigens from which both peptides were derived. While the exact mechanism of antigen processing for HLA-I presentation is still unclear for the EsxA and EsxJKPW peptides, the authors tested several pathways including inhibitors of proteasome activity, cysteine cathepsin activity, and lysosomal acidification. In future follow-up studies, it would also be useful to know whether the pulldown of a broader selection of HLA-I alleles would yield the same peptides/classes of peptides vs. a broader repertoire. The conclusions of this paper are well-supported by the data. This rigorous analysis of peptides presented on macrophages in the context of Mtb infection will establish a precedent for use of these techniques to discover additional antigens and will inform vaccine development efforts.

Reviewer #3 (Public Review):

T-tubules are an elaborate series of membrane invaginations that bring membrane voltage-activated Ca2+ channels in close apposition to the sarcoplasmic reticulum containing RyR, allowing for Ca2+-induced Ca2+ release. They serve as critical hubs of excitation-contraction coupling and play a central role in myopathies and inherited and acquired cardiomyopathies. Several membrane structures and proteins have been implicated in striated muscle t-tubule biogenesis, but the specific mechanisms of early t-tubule biogenesis are not defined.

Lemerle et al here investigate the biogenesis of transverse tubules in skeletal muscle. They use skeletal myoblasts from murine and human muscle as well as sophisticated high-resolution microscopy, live cell imaging, and adenoviral targeting to forward a model of BIN1 mediated caveolae ring formation which give rise to DHPR enriched t-tubules and associate with SR. While they demonstrate that BIN1 and Cav3 enriched caveolae act together to form t-tubules, the precise pathophysiological mechanisms by which this process acts in disease remain unclear.

Strengths of the study consist in the use of both murine and human skeletal muscle experiments, suggesting a conserved molecular mechanism; the innovative approach of correlative light and electron microscopy, and the use of pathological specimens. The live cell timelapse provides imaging evidence of Cav3-enriched caveolae-rings forming in centers of high BIN1 enrichment, from which t-tubules emanate. This is novel evidence in support of the biogenesis model proposed by the authors.

The pathological correlation of their model is promising but limited. Specifically, while the study of Cav3 mutant specimens is used to show the Cav3 dependence of BIN 1 action (in experiments using BIN 1 overload), the authors have not tested the sufficiency of their proposed mechanism by rescuing the pathologic state. Moreover, the conditions of development likely have an important effect on the studied mechanism - such as mechanical loading, contractile state, neurohormonal environment, and so on. Furthermore, a more complete description of the precise molecular binding sites between BIN1 and Cav3 would be important. While exon11 is required for tubulation, BIN1 not expressing exon 11 appears sufficient to assemble caveolar rings, suggesting this is mediated by other specific BIN1 regions.

Overall, the study provides new details on early t-tubule biogenesis in skeletal muscle (likely shared with other striated muscle) and lays the foundations for further definition of the precise molecular mechanisms.

Reviewer #3 (Public Review):

This study aims to define the factors that regulate the material properties of the viral inclusion bodies of influenza A virus (IAV). In a cellular model, it shows that the material properties were not affected by lowering the temperature nor by altering the concentration of the factors that drive their formation. Impressively, the study shows that IAV inclusions may be hardened by targeting vRNP interactions via the known pharmacological modulator (also an IAV antiviral), nucleozin, both in vitro and in vivo. The study employs current state-of-the-art methodology in both influenza virology and condensate biology, and the conclusions are well-supported by data and proper data analysis. This study is an important starting point for understanding how to pharmacologically modulate the material properties of IAV viral inclusion bodies.

Reviewer #3 (Public Review):

This work aims to elucidate the evolutionary origins of disulfide-rich spider toxin superfamilies and to determine the modes of natural selection and associated ecological pressures acting upon them. The authors provide a compelling line of evidence for a single evolutionary origin and differing factors (e.g., prey capture strategies and methods of anti-predator defense) that have shaped the evolution of these toxins. Additionally, the two major spider infraorders are claimed to have experienced differing selective pressures regarding these toxins.

The results presented here are novel and generally well-presented. The evidence for a single origin of DRP toxins in spiders is exciting and changes the paradigm of spider venom evolution.

The data are well analyzed, but the methods lack enough detail to reproduce the results. More information regarding the parameters passed to each software package, version numbers of all software employed, and models of molecular evolution employed in phylogenetic analyses are among the necessary missing information.

The differences in the evolutionary pressures between mygalomorphs and RTA-clade spider DRP toxins are clear, but expanding RTA results to all araneomorphs may be overreaching. Additional araneomorph sequence data is available, despite the claims within this manuscript (e.g., see Jiang et al. 2013 Toxins; He et al. 2013 PLoS ONE; and Zobel-Thropp et al. 2017 PEERJ). These papers include cDNA sequences of spider venom glands and contain representatives of inhibitory cysteine knot toxins, which are DRP toxins. These data would greatly enhance the strengths of the results presented herein.

Goitein's zettelkasten is comprised of about 20,000 3 x 5" index cards and 7,000 5 x 8" index cards.

Link to: https://hypothes.is/a/TEiQ5H1rEe2_Amfzi4XXmg

While not directly confirmed (yet), due to the seeming correspondence of the number of cards and their corpus descriptions, it's likely that the 20,000 3 x 5" cards were his notes covering individual topics while the 7,000 5 x 8" cards were his notes and descriptions of a single fragment from the Cairo Geniza.

Reviewer #3 (Public Review):

This is an important paper anchored by the observation that cultures of Neurospora undergoing amino acid starvation lose circadian rhythmicity if orthologs in the classic GCN2/CPC-3 cross-pathway control system are absent. Data convincingly show that Neurospora orthologs of Saccharomyces GCN2 and GCN4 (CPC-3 and CPC-1 respectively) are needed to promote histone acetylation at the core clock gene frequency to facilitate rhythmicity. While the binding of CPC-1 and thereby GCN-5 are plainly rhythmic, the explanation of exactly where rhythmicity enters the pathway is incomplete.

Figure 1 shows that inhibition of the HIS-3 activity affected by 3-AT, which should trigger cross-pathway control, is correlated with a graded reduction in the amplitude of the rhythm, and eventually to arrhythmicity at 3 mM 3-AT. While normalized data are shown in Figure 1B, raw data should also be provided in the Supplement as sometimes normalization hides aspects of the data. Ideally, this would be on the same scale in wt and in mutant strains.

Figure 2. The logical conclusion from Fig 1 is that circadian frq expression driven by the WCC has been impacted by amino acid starvation in the mutants. If so, either WC-1/WC-2 levels might be low, or else they might not be able to bind to DNA. When this was assessed, ChIP assays showed a loss of DNA binding. Although documented, an interesting result is that WCC protein amounts are sharply increased, especially for WC-1. The authors could comment on possible causes for this.

Line 176, "hypophosphorylation of WC-1 and WC-2 (which is normally associated with WC activation . . . )". While the authors are correct that this is often the case it is not always the case and this introduces a potentially interesting caveat. That is, the overall phosphorylation status of WCC does not always reflect its activity in driving frq transcription. This was first noticed by Zhou et al., (2018 PLOS Genetics) who reported that even though WCC is always hyperphosphorylated in ∆csp-6, the core clock maintains a normal circadian period with only minor amplitude reduction. This should be noted, cited, and discussed.

Figure 2 and Figure 2 Suppl. report different gel conditions and show that the sharply increased WC1/WC-2 levels seen in Fig 2 resulting from 3-AT treatment of the cpc pathway mutants are due to the accumulation of hypophosphorylated WC-1/2. The conclusion would be stronger if the gels in the Supplement showed the same degree of difference between wt and mutants as seen in Fig 2. In any case, these hypophosphorylated WC should be active and able to bind DNA but plainly are not based on Fig 2.

Figure 3 correlates the unexpected loss of DNA binding by hypophosphorylated WCC with reduced histone H3 acetylation at frq. The 3 mM 3-AT reported to result in arrhythmicity in cpc mutants in Figures 1 and 2 results in a small (~20%?) and not statistically significant reduction in H3 acetylation in wt, compatible with the sustained rhythms seen in wt in Figure 1, but in a substantial (~5 fold) loss of binding in the ∆cpc-1 background; so CPC-1 is needed for H3 acetylation at frq to sustain the rhythm during amino acid starvation. The simplest explanation here then is that the hypophosphorylated WCC cannot bind to DNA because the chromatin is closed due to decreased AcH3.

Figure 4. Title:" Figure 4. CPC-1 recruits GCN-5 to activate frq transcription in response to amino acid starvation"; the conditions of amino acid starvation should be mentioned here for the reader's benefit. (In the unlikely case that there was no amino acid starvation here then many things about the manuscript need to be reconsidered.)<br /> Based on the model from yeast where amino acid starvation activates GCN2 (aka CPC-3 in Neurospora) kinase which activates the transcriptional activator GCN4 (aka CPC-1) which recruits the SAGA complex containing the histone acetylase GCN5 to regulated promoters, CPC-1 was tagged and shown by ChIP to bind rhythmically at frq. Co-IP experiments establish the interaction of components of the SAGA complex in Neurospora and Neurospora GCN-5 indeed is bound to frq, likely recruited by CPC-1. This part all follows the Saccharomyces model with the interesting twist that the binding CPC-1 is weakly rhythmic and GCN-5 strongly rhythmic in a CPC-1-dependent manner. Based on the figure legend title, these cultures should always be starved for amino acids (although as noted this should be made explicit in the figure legend). In any case, given this, from where does the rhythmicity in GCN-5-binding arise? This question is developed more below.<br /> Line 224, "low in the cpc-1KO strain, suggesting that CPC-1 rhythmically recruit GCN-5".<br /> Because ChIP was done only for a half circadian cycle (DD10-22), it is hard to conclude "rhythmically". The statement should be modified.

Figure 5 shows that rhythmicity in general and of frq/FRQ specifically requires GCN-5 even under conditions of normal amino acid sufficiency, and that normal levels of H3 acetylation and its rhythm at frq require GCN-5. Not surprisingly, high H3 acetylation at frq correlated with high WC-2 DNA binding, and ADA-2 is required for SAGA functions.<br /> As earlier, raw bioluminescence data corresponding to panel B should be provided in the figure or Supplement.<br /> Also, if CPC-3 and CPC-1 regulate frq transcription through GCN-5, why is the frq level extremely low in the cpc-3KO or cpc-1KO(Fig.1D) but remains normal in gcn-5KO (Fig. 5D)?

Figure 6 documents the counter effects of TSA which inhibits histone deacetylation and shortens the period versus 3-AT which decreases (via CPC-3 to CPC-1 to GCN-5) histone acetylation and causes period lengthening or arrhythmicity. HDA-1 is necessary for histone deacetylation at frq.

Figure 7 documents extensive changes in gene expression associated with 3-AT-induced amino acid starvation and the CPC-3 to CPC-1 pathway. How do these results compare with other previously studied systems, particularly Saccharomyces, where similar experiments have been done? Are the same genes regulated to the same extent or are there some interesting differences?

Figure 8 provides a model consistent with the role of the CPC-3/GCN2 pathway in regulating genes in response to amino acid starvation. It seems this could be any gene responding to amino acid starvation.<br /> Not accounted for in the model is the data from Fig 4 which show the rhythmic binding of CPC-1 and stronger rhythmic binding of GCN-5 to frq, both under amino acid starvation. In the presence of 3-AT, amino acid starvation is constant, which should mean that CPC-3 and CPC-1 would always be "on". Why doesn't CPC-1 recruit GCN5 at the same level at all times leading to constant high H3 acetylation rather than rhythmic H3 acetylation as seen in Figure 3? Perhaps, unlike the statement in lines 345-34, it is WCC that regulates rhythmic GCN-5 binding and facilitates rhythmic histone acetylation at frq. Or perhaps the clock introduces rhythmicity upstream from GCN5. Without an answer to the question of where rhythmicity comes into the pathway, the story is only about how the CPC-3/GCN2 pathway in regulating genes in response to amino acid starvation; without explaining the rhythmicity the story seems incomplete.

Reviewer #3 (Public Review):

In this work the authors show, using different computational methods (molecular dynamics simulations, Markov state modeling, docking) that the probability of pocket opening in the isoforms of the protein myosin is an important determinant of the potency of the allosteric inhibitor blebbistatin. The data from the work supports the conclusions, and clearly shows that blebbistatin inhibits more potently myosin isoforms with a higher probability of pocket opening. The authors developed a protocol combining the probability of pocket opening from Markov state modeling with docking scores to estimate the IC50 values of blebbistatin for different myosin isoforms, achieving a good correlation between computed and experimental IC50 values (coefficient of determination of 0.82). The authors also tested their computational protocol prospectively, providing an estimate of IC50 for blebbistatin for the myosin isoform Myh7b which was in line with the experimental results. The computational protocol developed by the authors can be very useful for the community, since it can be applied to any protein containing cryptic pockets.

A major strength of the work is the prospective test of the computational protocol they developed, and the subsequent conclusion that the IC50 estimated by their method, 0.67 µM, was similar to the value obtained in the experiments, 0.36 {plus minus} 0.08 µM.

A major weakness of the work is the use of docking scores to compute the IC50 of blebbistatin for the different isoforms of myosin. Docking scores are usually empirical and previous works have shown that they are usually poorly correlated with experimental binding affinities.

Reviewer #3 (Public Review):

In this study, the authors use recently published single nucleus RNA sequencing data and a newly generated single cell RNA sequencing dataset to determine the transcriptional profiles of the different cell types in the Drosophila ovary. Their analysis of the data and experimental validation of key findings provide new insight into testis biology and create a resource for the community. The manuscript is clearly written, the data provide strong support for the conclusions, and the analysis is rigorous. Indeed, this manuscript serves as a case study demonstrating best practices in the analysis of this type of genomics data and the many types of predictions that can be made from a deep dive into the data. Researchers who are studying the testis will find many starting points for new projects suggested by this work, and the insightful comparison of methods, such as between slingshot and Monocle3 and single cell vs single nucleus sequencing will be of interest beyond the study of the Drosophila testis.

Reviewer #3 (Public Review):

This manuscript uses the NDUFS4-/- mouse, which models severe mitochondrial disease Leigh Syndrome, to examine if changes in iron homeostasis modify disease progression. They report that iron limitation delays the phenotype of "clasping", a neurologic change associated with loss of NDUFS4. The study is mostly observational and has little mechanism regarding how possible alterations in iron homeostasis contribute to disease progression. Therefore, it does not advance our understanding of how changes in iron homeostasis add to the progression of Leigh Syndrome.

Strengths:

The authors propose that iron homeostasis may be altered in the absence of NDUFS4 in mice, which is utilized as a model for the human disease Leigh Syndrome. To test this hypothesis, the authors show that limiting iron by either iron chelation or restriction in the diet delays disease progression (clasping is delayed and longer survival). They show by ICP-MS elevated iron in NDUFS4-/- mouse livers, kidney and duodenum and that "overall" tissue iron levels are elevated in the absence of NDUFS4. They show the predicted changes in iron levels in those tissues when the iron content in the diet is limited. They also show that other metals are changed in the absence of NDUFS4 and that when iron is limited in the diet there are increased levels of other metals with the most significant changes in Mn. They show a significant correlation between increased peroxidation of PUFAs in the liver of NDUFS4-/- mice and increased clasping, a neurologic measure of disease progression.

Weaknesses<br /> Unfortunately, the authors do not detect changes in iron levels in neurologic tissues (brain) in the absence of NDUFS4 nor do they show changes in iron levels in the brain upon limiting iron in the diet. In addition, the authors do not provide any imaging of the brain or brain stem to support slowed progression of lesions in this model. That a change in iron in the diet affects RBC levels simply confirms that the diet is limiting for erythropoiesis and does not provide supporting evidence that iron levels may be changing in the brain.

The authors spend a lot of experimental effort measuring metal levels in all tissues without evidence of changes in neurologic tissues and then focus on changes in metals in the liver and increased lipid peroxidation in the liver. It is unclear to this reviewer if the authors are suggesting that the iron loading in the liver is contributing to the neurologic phenotypes associated with loss of NDUFS4 or if they are suggesting that there must also be inappropriate iron loading in neurologic tissues (with no supportive data) that gives rise to disease progression. The authors did not measure if iron loading in the liver, kidney or duodenum in NDUFS4-/- mice resulted in decreased organ function thus leaving open the possibility that other organ dysfunction contributes to the observed neurologic phenotypes associated with this disease.

It is unclear why the authors did not measure lipid peroxidation in the brain tissue or other neurologic tissues, nor did they measure lactate levels in blood and CSF upon dietary iron limitation.

There is no mechanistic experimental data that inform on how iron changes accelerate the progression of disease.

Fig 4 -They measure metal levels in different tissues, however, they do not show any changes in iron levels in neurologic tissues nor do they assess iron protein levels in neurologic tissues.

Together, this study does not determine the how of increased iron in tissues of NDUFS4-/- mice, and if there are changes in mitochondrial function upon dietary iron restriction, whether the location of iron in tissues is different (e.g., it is unclear whether there is increased mitochondrial iron, often a phenotype associated with mitochondrial dysfunction).

Reviewer #3 (Public Review):

Chen et al. perform an innovative screen using retinal organoids derived from rd16 mice to identify small molecules to treat CEP290 hypomorphic mutations linked to ciliopathies such as LCA. The authors identify reserpine which promotes photoreceptor development and viability in retinal organoids derived from LCA patient iPSCs and rd16 mouse retinas. The authors finally propose a mechanistic model where reserpine restores proteostasis thereby improving ciliogenesis.

The authors present a highly effective drug screen that utilizes the benefits of retinal organoids while also accounting for the inherent variability of retinal organoids by performing a screen on 2D cultures derived from the organoids. This is an innovated approach to using retinal organoids in drug screens and is of interest to the greater community. The success of the screen is reflected in the effectiveness of reserpine in the in vivo rd16 mouse retinal model where it promotes photoreceptor survival. However there are multiple issues with the LCA patient organoid screen that must be resolved.

The patient derived iPSC lines are not controlled sufficiently enough to make conclusions stated in the manuscript. The authors rely on single iPSC clones from disease patients to perform experiments, and it is not clear whether karyotyping to validate normal chromosomal integrity was performed. In the case of the RNAseq experiment one patient clone does not show any differences calling into question the findings from the other clone. Patient derived iPSC studies would benefit from the use of multiple independently derived iPSC clones per patient, or rescuing the LCA10 mutation using CRISPR editing to validate the correlation of the mutation with the differences observed.

This study could be strengthened by parallel RNAseq studies is the rd16 mouse retina and patient iPSC retinal organoids.

Reviewer #3 (Public Review):

The authors set out to examine the roles of multiple cell death pathways during a Shigella infection. Shigella oral infection has been classically difficult to perform because wild type C57BL/6 mice naturally resist Shigella infection, likely reflecting the fact that Shigella species are human-specific pathogens. The authors recently developed an oral Shigella infection model that successfully allows mice to be infected orally with Shigella. In this model, NLRC4 inflammasome knockout mice are treated with streptomycin 1 day prior to infection. Streptomycin depletes the microbiota and opens a microbial niche for intestinal infection (this is the same method that is used for Salmonella typhimurium oral infections in C57BL/6 mice). The Nlrc4 deletion removes one innate immune barrier to infection. Now the authors examine additional deletions in other regulated cell death genes on this Nlrc4-/- background.

Their results show that three distinct pathways to cell death are important in defending against Shigella infection, but that some pathways are more protective than others. In their previous paper, the authors showed a difference in phenotype between Nlrc4-/- mice on a C57BL/6 (B6) versus a 129S1/SvImJ (129) mouse background. The authors now show that the difference in these phenotypes is primarily driven by Casp11, in which 129 mice are naturally genetically deficient. The authors show that Casp11 is capable of protecting IECs from colonization. This is conceptually at odds with the knowledge that Shigella encodes OspC3, which is a type III secretion effector that inhibits caspase-11. However, it turns out to be that both inhibition by OspC3 and defense by caspase-11 occur in parallel with partial efficiency. The attenuation of the ospC3 Shigella mutant was abolished in mice lacking Casp11.

Further, they show that counter to assumptions in the field, neither myeloid pyroptosis nor IL-1 affected Shigella pathogenesis during this oral infection model.

The authors next examine the role of TNF driven cell death through caspase-8 and RIPK3. They show that TNF does contribute to defense against Shigella infection, but that this protection is secondary to the roles of Nlrc4 and Casp11. Finally, the authors show that quadruple knockout Casp1/11/8-/-Ripk3-/- mice lacking all four of these pathways display far worse disease pathogenesis than any of the other knockout mice studied.

In summary, NLRC4 provides the strongest defense, and caspase-11 and caspase-8/RIP3 provide weaker defense. The authors show that the weakness of the caspase-11 pathway is caused by the OspC3 effector that inhibits caspase-11. We can extrapolate form this to speculate that the weakness of caspase-8 is caused by OspC1 inhibiting it, and the weakness of RIPK3 is caused by OspD3 inhibiting it. This could be proved in future work.

One formal weakness is that Figure 1 is data from just one experiment, however, the key conclusion is verified in Figure 2 by the use of targeted Casp11 knockout.

One omission from the paper is that in Figure 3 and Figure 4, WT mice were not infected with an ospC3 mutant to show the baseline attenuation. It is stated that oral infections have not been studied with this mutant.

One weakness inherent in the use of Casp8-/- mice is that they are not viable unless they carry the Ripk3-/- or equivalent mutation. Therefore, the authors can only assess the simultaneous loss of both pathways. This can be compared to a single Ripk3-/- situation, but, here caspase-8-driven apoptosis could be sufficient. Often RIPK3 serves as a backup defense when a pathogen inhibits caspase-8, thus a hypothetical Casp8-deficient Ripk3-sufficient mouse might remain resistant due to RIPK3 activation. This might be achieved in future work by using recently developed mouse lines that carry specific Casp8 point mutations that cause the loss of apoptosis while retaining mouse viability.

One limitation of the study is that littermate controls arising from heterozygous by knockout breeding were not always used. Co-housing was used for at least 3 weeks, which often, but not always, normalizes the microbiota. This noted, it should be acknowledged that littermate controls would be extremely burdensome to accomplish in the case of some strains where multiple knockouts are used.

Reviewer #3 (Public Review):

The findings by Latshaw et al. identify Amtyr1 as a major regulator of latent inhibition - a neurological mechanism whereby non-productive stimuli are down-ranked in reward:stimuli association - in honeybees. The authors utilize intracolony variation in exhibited latent inhibition in male honey bees to map Quantitative Trait Loci associated with this phenotype, then use the identified regulatory regions (associated with Amtyr1) to target Amtyr1 using several perturbation methods to demonstrate the centrality of this locus to latent inhibition, and neurophysiology methods to assess the neuronal effect. Overall their results are convincing and approaches appear rigorous.

Overall I found this paper to be relatively easy or hard to review, depending on how you rate reviewing a paper that does many of the things you would have suggested to assess the functional centrality of a target gene to an observed phenotype.

I really do not have many criticisms of the approach, findings, or rigor of major note. I would appreciate it if the authors noted (acceptable as supplementary) the other QTL loci identified (lines 123-124), as the text implies other genes may have been identified in their QTL mapping. If so, this may be of interest to the general community.

I also personally prefer exact p-values reported (e.g., line 253) instead of the "<<0.01" or (line 257) "<0.01".

Honestly, I'm a little disappointed in how little I could criticize, which is only partially related to my not being an expert in the field. The paper was clear, well written, rigorous (as far as I could tell), validates findings via multiple routes, and extends their locus-focused (lol) results into neurotransmitter differences, empirically determined.

Reviewer #3 (Public Review):

The authors analyse the role of bisphosphoglycerate mutase (BPGM), an enzyme unique to erythrocytes and placental cells. The authors assess the role of BPGM in the pathogenesis of fetal growth restriction (FGR).

Strength of the work: The authors have analysed a murine model of hypoxia (acute and chronic) as well as human placental samples.

Impact of the work on the field: FGR is linked to many short- and long-term medical complications. The authors have done important efforts to understand the role of hypoxia and the placenta in the pathogenesis of FGR. The identification of BPGM as a potential link between FGR and adverse intrauterine is relatively novel.

Reviewer #3 (Public Review):

DeCalciOn is an innovative contribution to the toolbox of real-time processing of calcium imaging data. It provides calcium traces from hippocampal CA1 neurons with a roughly two-millisecond latency and uses them to decode the position of rats running along a linear track - setting the stage for closed-loop experiments requiring fast interpretation of neural activity. The manuscript would be strengthened by a more systematic, empirical comparison to other, currently available alternative approaches. In addition, the decoding analysis does not fully account for the possibility of artifactual motion in the imaging video being informative of position.

We suggest strengthening this manuscript by addressing the following four points:

1) In the discussion of other platforms, the authors state that "Any system that lacks motion stabilization would also be vulnerable to artifactually decoding behavior from brain motion (which can be correlated with behavior) rather than neural activity." It follows that the same problem might also occur with incomplete motion correction. While the motion-corrected video shown in Supplementary Video 1 has reduced motion compared to the raw video, motion is still visible, including outside of the marked jitter. It remains possible that the linear decoders for the position in the linear track are utilizing brain motion-induced, as opposed to calcium fluorescence-induced, signal changes. A critical first step to assess this issue is to ask whether the motion in the video is related to the rat's behavior. One could test whether the 2D motion displacement traces can be used to predict rat position using linear classifiers.

2) The manuscript would benefit from repeating the experiment in a more complex environment, such as a 2D arena. This would increase the generalizability of the findings. In addition, increasing the complexity of the environment would reduce the possibility that particular types of brain motion are closely linked with positions in the environment.

3) The authors present an interesting comparison between "contour-free" and traditional contour-based source extraction. A more comprehensive discussion on the history or novelty of "contour-free" calcium imaging processing would contextualize this result.

4) In the discussion, the authors compare DeCalciOn to two previous online calcium imaging algorithms. The technical innovations of this work would be better highlighted by directly testing all three of these algorithms, ideally on similar datasets.

Reviewer #3 (Public Review):

This is an interesting study to examine how alveolar bone responds to oral infection using unbiased scRNA-seq. The manuscript is well-written and the results are convincing.

1) The authors should revise the abstract. The study did nothing with the understanding of healing. The whole conditions were performed under infection and inflammation which actually induce bone loss, but not healing.

2) Since periapical inflammation causes progressive bone loss, how MSC with increasing osteogenic potentials contributes to bone loss? The authors should discuss it.

3) Did the authors detect osteoclasts by scRNA-seq? If not, are there any precursors of osteoclasts identified in inflammatory alveolar bones? 1) I suggest that the authors provide a more detailed analysis of inflammation since this is a unique model to study oral bone inflammation.

4) It is known that macrophages can be classified into M1 and M2. Based on scRNA-seq, did the authors observe these two types?

Reviewer #3 (Public Review):

The study titled "MCT1-dependent energetic failure and neuroinflammation underlie optic nerve degeneration in Wolfram syndrome mice" has illustrated one of the possible molecular mechanism of Retino-ganglion cells (RGCs) degeneration leading to optic atrophy observed in the patients of Wolfram syndrome (WS). It is very crucial to understand the molecular details of optic atrophy and progressive vision loss in patients of WS. The main reason for the optic atrophy and loss of vision in Wolfram syndrome is the degeneration of specific cells in the retina- Retino-ganglion cells (RGCs). There have been many studies in different model systems of WS but the study addressing the loss of vision is limited. A recent study in a zebrafish model of WS shows thinning of the optic nerve layer, loss of RGCs, and loss of vision, however, the molecular mechanism for the specific degeneration of RGCs is limiting. Therefore, it is of utmost need to understand the molecular mechanism/s which could be the possible reason for the loss of RGCs in WS.

In this study, the authors have illustrated one of the possible molecular mechanisms leading to the loss of RGCs and eventually resulting in progressive loss of vision in mice models of WS. The study shows that MCT1 and Wolframin interact with each other and help in lactate transport to meet the high energy demand of RGCs. In the absence of wolfamin, MCT1 dependant energy failure leads to demyelination of optic nerve axons further leading to the degeneration of RGCs and progressive loss of vision. This study is one of its kind which investigates the molecular mechanism for the selective loss of RGCs in the wolfram syndrome. This finding will enable therapeutic screening of promising drug molecules that could rescue the RGCs degeneration.

Reviewer #3 (Public Review):

The authors explore the use of SRT as a host-directed therapy for use in combination with other first-line TB antibiotics. This manuscript is of substantial importance since TB is a major world health concern, and there is growing interest in the development of host-directed therapies to augment existing therapies for TB. Demonstrating the effectiveness of adding an FDA-approved drug to existing cocktails of anti-TB drugs has potentially exciting implications.

The manuscript is bolstered by their use of multiple in vitro and in vivo models of infection, as well as a clinically relevant strain of TB. While their findings generally support the use of SRT as an effective HDT/treatment, the mechanistic details underlying the effectiveness of SRT remain somewhat obscure, and as presented, the in vitro experiments support more limited conclusions.

Major concerns:

In vitro studies (i.e. bacterial culture) were only performed with SRT up to 6 uM while the cultured cell experiments used a range up to 20 uM. 5 uM had almost no effect on the viability/growth of Mtb in macrophages. The authors should use the same concentrations in vitro as their macrophage studies to test whether SRT directly impacts Mtb viability to be able to rule in/out that SRT does not impact Mtb viability when cultured.

The mechanism of action of SRT during TB infection and the conclusions drawn by the authors are not supported by the limited experimentation. SRT is presented as an antagonist of polyI:C-induced type I IFNs, but during TB infection, cytosolic DNA sensing via the cGAS/STING axis constitutes the major pathway through which type I IFNs are induced in macrophages.

To offer more support that SRT inhibits type I IFN, the authors should consider measuring the the actual amount of type I IFN using an IFNb ELISA. Additionally, the authors should use human/mouse primary macrophages (not just THP1 reporter cells) and measure transcript levels (at key time points post infection) and protein levels of type I IFN and other proinflammatory mediators (e.g. TNFa, IL-1, IL-6) +/- SRT to determine if SRT is specific to the type I IFN response. If this is indeed the case, other NFkB genes/cytokines should not be impacted.

Moreover, to draw the conclusion that "augmentation property of SRT is due to its ability to inhibit IFN signaling" a set of experiments using an IFN blocking antibody would enhance Figure 2, as both cGAS and STING KO macs have significant differences in basal gene expression and their ability to respond to innate immune stimuli.

Because the first half of the paper focuses on type I IFNs during macrophage infection to explain the mechanism of action for SRT, additional analysis of the mouse infections to examine levels of type I IFNs, as well as IL-1B and IFN-g (in serum/tissues?), is important for connecting the two halves of the manuscript. The in vivo data would also be strengthened by quantitative analysis of histological changes by, for example, blinded pathology scoring. This type of quantitation would also permit statistical analyses of this important pathology readout.

The authors conclude that SRT functions through an inflammasome-related function, but this conclusion requires further support of actual inflammasome activation, such as IL-1B secretion by ELISA or IL-1B processing by western blot analysis, rather than Il1b gene expression alone. Additional functional readouts of inflammasome activation like cell death assays would also strengthen this conclusion.

What strain of TB was used in these studies? The results and methods do not indicate the strain used, which is critical to know since different strains have varying pathogenesis phenotypes.

Minor concerns:

It might be worth consistently using the more common INH and RIF abbreviations to increase the clarity/readability of the MS and figures.

What is the physiological concentration of SRT when taken for depression and how does that compare to the concentrations used in vitro? Are the in vitro concentrations feasible to achieve in patients?

In Figure 3B, why is there a spike in TNF-a in the HRS treated cells only at 42h?

Was statistical analysis performed on the data in Figure 3B and D?

A description/discussion of the different mouse strains use in infection - what benefits each has as a model and why several were used - would help convey the impact of the in vivo studies.

Since antibiotics and SRT were administered ad libitum, how did the authors ensure that mice took enough of the antibiotics and especially SRT? Is it known whether these drugs affect the water taste enough to affect a mouse's willingness to drink them?

Was statistical analysis performed on time-to-death experiments?

Were CFUs measured in mice from Figure 4 to determine empirically how effective the antibiotic treatments were? And if SRT impacted their effectiveness?

The H&E images could use some additional labels to more easily discern what groups they belong to.

Reviewer #3 (Public Review):

The Rcs phosphorelay plays an important role in regulating gene expression in bacteria; most of the current knowledge about the Rcs proteins is from E. coli. Yersinia pestis, carrying mutations in two central components of the Rcs machinery, provides an interesting example of how evolution has shaped this system to fit the life cycle of this bacteria. In bacteria other than Y. pestis, most Rcs activating signals are sensed via the outer membrane lipoprotein RcsF; from there, signalling depends on inner membrane protein IgaA, a negative regulator of RcsD. Histidine kinase RcsC is the source of the phosphorylation cascade that goes from the histidine kinase domain of RcsC to the response regulator domain of RcsC, from there to the histidine phosphotransfer (Hpt) domain of RcsD, and finally to the response regulator RcsB. RcsB, alone or with other proteins, regulates transcription of many genes, both positively and negatively. These authors have previously shown that RcsA, a co-regulator that acts with RcsB at some promoters, is functional in Y. pseudotuberculosis but mutant in Y. pestis, and that this leads to increased biofilm in the flea. The authors also noted that rcsD in Y. pestis contains a frameshift after codon 642 in this 897 aa protein; in theory that should eliminate the Hpt domain from the expressed protein. However, they found evidence that the frame-shifted gene had a role in regulation. This paper investigates this in more depth, providing clear evidence for expression of the Hpt domain (without the N-terminal domain), and demonstrating a critical role for this domain in repressing biofilm formation. The Y. pseudotuberculosis RcsD does not express a detectable amount of the Hpt domain nor does it repress biofilm formation. The ability of the Hpt domain protein to keep biofilm formation low explains most of what is observed for the full-length frame-shifted protein.

1. The authors provide a substantial amount of data supporting the expression of the C-terminus of RcsD is sufficient and necessary for low biofilm levels, and that this is dependent upon the active site His in the RcsD Hpt domain (H844A) as well as other components of the basic phosphorelay (RcsC and RcsB). However, it is only possible to see this protein by Western blot in 100-fold "Enriched" lysates (Figure 2). No small protein was detected in the RcsDpstb strain, although the enriched lysate was not shown for this. Without that experiment, it is not possible to evaluate whether the small protein is also made from the rcsDpstb gene. Either answer would be interesting, and would allow other conclusions to be drawn. Is the RBS and start codon the same for the HPT region of this rcsD gene (it could be added to Supplementary Table 6). If the small protein is made, is its ability to function blocked by the excess full length protein in terms of interactions with RcsC? Or is the expression of the small protein dependent upon loss of overlapping translation from the upstream start?<br /> 2. In many phosphorelays, the protein kinase also acts as a phosphatase, and which direction P flows is critical for regulation. It is often difficult to follow what the model for this is in this paper, and that is important to understand for evaluating the results. Most of this paper uses two assays, biofilm formation and crystal violet staining (also related to biofilm formation) to assess the functioning of the Rcs phosphorelay. Based on the behavior of the rcsB mutant, it would seem that functional Yersinia pestis Rcs (RcsDpe) represses this behavior, and this correlates with RcsB phosphorylation (Fig. 4). What is the basis (line 443-44) for saying that RcsD phosphorylates RcsB while RcsDHpt dephosphorylates? Yersinia pseudotuberculosis RcsD(pstb) shows no difference with the rcsB mutant. Doesn't that suggest that RcsDpstb is no longer repressing (phosphorylating)? In the presence of the RcsDpstb as well as multicopy RcsF, an activating signal in other organisms, RcsDpstb seems able to phosphorylate. This all suggests that the full-length protein, like the Hpt domain, is capable of phosphorylating, but that it may be doing nothing in the absence of signal (or dephosphorylating). Given these results, saying that RcsDpstb is positively regulating biofilm formation (Fig.1 title, and elsewhere) is somewhat misleading. What it presumably does is prevent the Hpt domain, expressed from the chromosomal locus in Fig. 1b, from signalling to RcsB. By itself, it is not clear it is doing anything. Understanding this clearly is important for interpreting this system and the tested mutants. A clear model and how phosphate is flowing in the various situations would help a lot. Currently Supplementary Fig. 3 seems to reflect the appropriate directional arrows, but the text does not. Moving the rcsB data earlier in the paper (after Fig. 1, 2, or maybe earlier, before Fig. 3) would certainly help.<br /> 3. The authors show (in their pull-down) that there is a bit of full-length RcsD even in the frame-shifted protein. Is there any clear evidence this does anything here? Does the N-terminus (truncated after the frame-shift) have a function?<br /> 4. While the RNA seq data is useful addition here, it is difficult to interpret without a bit more data on the strain used for the RNA seq, including the biofilm phenotypes of the WT and mutant derivatives, as well as the relevant rcsD sequences, and maybe expression of a few genes or proteins (Hms or hmsT). Are these similar in the parallel strains used earlier in the paper and the one for RNA seq, in WT, rcsB- and the RcsDpstb derivative? It would appear that rcsB- and rcsDpstb have opposite effects, at least at 25{degree sign}C, while in Fig. 4, these two derivatives have similar effects on biofilm. Is this due to temperature, strains, or biofilm genes that are not shown here? It is certainly possible that the ability of the full-length RcsD changes its kinase/phosphatase balance as a function of temperature, or dependent on other differences in these Y. pestis strains.

Reviewer #3 (Public Review):

The study addresses a tough question in the study of wild bats: what and where they eat, using both acoustic bio-logging and DNA metabarcoding. As a result, it was found that greater mouse-eared bats made more frequent attack attempts against passively gleaning prey with lower predation success but higher prey profitability than aerial hawking with higher predation success. This is a precious study that reveals essential new insights into the foraging strategies of wild bats, whose foraging behavior has been challenging to measure. On the other hand, the detection of capture attempts, success or failure of predation, and whether it was by passively gleaning prey or aerial hawking were determined from the audio and triaxial accelerometer analysis, and all results of this study depend entirely on the veracity of this analysis. Also, although two different weights and a tag nearly 15% of its weight were used, it is essential for the results of this data that there be no effect on foraging behavior due to tag attachment. Since this is an excellent study design using state-of-the-art methods and very valuable results, readers should carefully consider the supplemental data as well.

Reviewer #3 (Public Review):

In this manuscript, Chu and colleagues first studied the differentiation of hypertrophic chondrocytes into osteoblasts using lineage tracing and single-cell transcriptomics on dissociated bone tissues. In analyzing these data, they identified MMP14 as upregulated in immature osteoblasts derived from hypertrophic chondrocytes. This observation prompted them to study the relationship between MMP14 and signals that regulate osteoblast differentiation such as a parathyroid hormone. Interestingly, MMP14 was found to cleave the ectodomain of the PTH receptor and blunt its signaling activity. Accordingly, MMP14 deficiency in these cells augmented PTH-induced bone anabolism.

This work builds upon multiple previous studies demonstrating that a subset of hypertrophic chondrocytes (or, at least, cells marked by collagen X Cre strategies) can become osteoblasts. The use of lineage tracing to try to divide osteoblasts into those derived from HCs or other progenitors is interesting, although technical challenges are present in data interpretation. The study then pivots dramatically into loosely-connected mechanistic studies investigating links between MMP14 (identified from their single-cell RNA-seq studies) and the PTH receptor. Gaps exist in the logic linking this work to the beginning of the paper, and major questions remain about MMP14-mediated PTH receptor cleavage. The work then returns to in vivo studies investigating the skeletal and cellular phenotype of PTH-treated mice where MMP14 is deleted using collagen X Cre.

While several interesting threads are suggested by these findings, the scope of the work is quite broad and it is difficult to appreciate the direct relationship between some of the findings that are presented in successive figures. GPCR cleavage by an MMP is exciting and interesting. However, the cleavage patterns observed in vitro do not match the PTH receptor fragments noted in vivo. Moreover, much remains to be described regarding differences in PTH efficacy in cells with and without MMP14. Of course, the possibility remains that MMP14 targets other than the PTH receptor contribute to the phenotypes that are observed in mice.

This work adds to an already-large body of evidence demonstrating that collagen X-labeled cells contribute to the osteoblast pool. The use of single-cell RNA-seq here is appealing and demonstrates the heterogeneity of collagen X-labeled cells and their descendants for the first time. The scRNAseq data will be useful for the entire bone biology community. In addition, a comparison between global and ColX-mediated MMP14 deletion is well done and of interest. Overall, my impression of the impact of the work is mixed. The most novel/exciting finding here is that MMP14 cleaves the PTH receptor and regulates its activity: the evidence supporting this new finding is incomplete, and the other data presented on hypertrophic chondrocyte differentiation may be viewed as a distraction to the central message of this manuscript.

Reviewer #3 (Public Review):

Resting stage fMRI studies have revealed functional associations between cerebral cortical networks and cerebellar regions. However, it remains unknown whether specific regions of the cerebellar cortex integrate information from functionally related areas of the cerebral cortex. Here, the authors used a task-based fMRI approach to infer the degree of convergence of cerebral cortical inputs at the level of the cerebellar cortex. Models that allow for integration of cerebral cortical inputs, rather than one-to-one relationships between cerebral cortical and cerebellar regions best explained cerebellar task-related activity. A higher degree of convergence was needed to explain activity in non-motor cerebellar regions.

Strengths:<br /> - Innovative task-based approach to assess the level of cerebral cortical inputs to the cerebellar cortex.<br /> - Used a large multi-domain battery of fMRI tasks.<br /> - Multiple models of interactions between the cerebral cortex and cerebellum were assessed.<br /> - Predictive accuracy of models was assessed across multiple parcellations of the cerebral cortex.<br /> - Connectivity models can be useful in predicting new cerebellar functional data in new participants.

Weaknesses:<br /> - One limitation of the approach that is not discussed is that the motor responses that can be performed in the scanner are inherently simple, whereas non-motor tasks can be more varied and have a higher degree of complexity. Thus, it is unclear if the types of tasks used in multi-domain batteries are sufficient to substantiate the finding that there is less functional integration in non-motor regions of the cerebellar cortex.

Likely impact and utility:<br /> - The study provides insightful evidence that regions of the cerebellar cortex may integrate inputs from different regions of the cerebral cortex. This finding is useful for theories of cerebellar function and for guiding future studies of how integration may occur at the level of the cerebellar cortex.

https://www.govinfo.gov/content/pkg/CHRG-107jhrg96166/html/CHRG-107jhrg96166.htm

Reviewer #3 (Public Review):

The authors sought to propose a mechanism by which cancer-causing mutations in the thrombopoietin receptor (TpoR) activate the receptor. To do so, they used a systematic approach of introducing non-native and naturally occurring mutations into the receptor and use a combination of in-vivo and cell-based assays and solid-state NMR spectroscopy. They propose that the proximity of the asparagine mutations to the cytosolic boundary influences the secondary structure of the receptor and suggests that this structural change induces receptor activation.

The strengths of this work are the importance of the system being studied and tackling a problem that is not yet fully resolved. The authors acquired a large and convincing set of biological data, including in vivo experiments that support the gain-of-function/activating role of the mutations studied. The solid-state NMR data are of high quality as well. In particular, the INEPT data in figure 6a display very clear differences within one region of the wild-type compared to the mutants.

One significant weakness is the validity of the conclusions given the limited atomistic measurements presented. Namely, the authors make rather specific conclusions about protein folding based on a single set of 13C alanine carbonyl chemical shifts in the wild-type and mutant TM peptides. Essentially, the authors observe chemical shift perturbations at this carbonyl carbon when mutations are introduced into a protein and use this information to make conclusions about secondary structure. I am not convinced that the authors have presented sufficient evidence to justify the conclusion that the helix unwinds and that this is responsible for the mechanism of activation. While the other cell-based experiments in mutations are interesting, deciphering such a specific folding mechanism with limited atomistic data is not justified.

Reviewer #3 (Public Review):

Soutschek and Tobler provide an intriguing re-analysis of inter-temporal choice data on amisulpride versus placebo which provides evidence for an as-yet untested hypothesis that dopamine interacts with proximity to bias choices.

The modeling methods are sound with a robust and reasonably exhaustive set of models for comparison, with good posterior predictive checks at the single subject level, and decent evidence of parameter recoverability. Importantly, they show that while there is no main effect of drug on the proportion of larger, later (LL) versus smaller, sooner (SS) choices, this obscures conflicting-directional effects on drift rate versus starting point bias which are under-the-hood, yet anticipated by the hypothesis of interest.

While I have no major concerns about methodology, I think the Authors should consider an alternative interpretation - albeit an interpretation which would actually support the hypothesis in question more directly than their current interpretation. Namely, the Authors should re-consider the possibility that amisulpride's effects are mediated primarily by acting at pre-synaptic receptors. If the D2R antagonist were to act pre-synaptically, it would drive more versus less post-synaptic dopamine signaling.

There are multiple reason for this inference. First, the Authors observe that the drug increases sensitivity to differences in the relative offer amounts (in terms of effects on the drift rate). With respect to the canonical model of dopamine signaling in the direct versus indirect pathway, greater post-synaptic signaling should amplify sensitivity to reward benefits - which is what the Authors observe.

Second, the Authors also observe an effect on the starting bias which may also be consistent with an increase in post-synaptic dopamine signaling. Note that according to the Westbrook & Frank hypothesis, a proximity bias in delay discounting should favor the SS over the LL reward, yet the Authors primarily observe a starting bias in the direction of the LL reward. This contradiction can be resolved with the ancillary assumption that, independent of any choice attribute, participants are on average predisposed to select the LL option. Indeed, the Authors observe a reliable non-zero intercept in their logistic regression model indicating that participants selected the LL more often, on average . As such, the estimated starting point may reflect a combination of a heightened predisposition to select the LL option, opposed by a proximity bias towards the sooner option. Perhaps the estimated DDM starting point is positive because the predisposition to select the LL option has a larger effect on choices than the proximity bias towards sooner rewards does in this data set. To the extent that amisulpride increases post-synaptic dopamine signaling (by antagonizing pre-synaptic D2Rs) it should amplify the proximity bias arising from the differences in delay, shifting the starting bias towards the SS option. Indeed, this is also what the Authors observe.

Note that it remains unclear why an increase in post-synaptic dopamine signaling would amplify one kind of proximity bias (towards sooner over later rewards) without amplifying the other (towards a predisposition to select the LL option). Perhaps the cognitive / psychological nature of the sooner bias is more amenable to interacting with dopamine signaling than the latter. Or maybe proximity bias effects are most sensitive to dopamine signaling when they are smaller, and the LL predisposition bias is already at ceiling in the context of this task. These assumptions would help explain why a potential increase in post-synaptic dopamine signaling both amplified the proximity effect of delay when it was smallest (when the differences in delay were smaller), and also failed to amplify the predisposition to select the LL option (which may already be maxed out). More importantly, the assumption that there are opposing proximity biases would also help explain why there is a negative effect of delay magnitude on the estimated starting point on placebo. Namely - as the delay gets larger, the psychological proximity of sooner over later rewards grows, counteracting the proximity bias arising from choice predisposition / repetition.

Regardless of the final interpretation, showing that pharmacological intervention into striatal dopamine signaling can simultaneously modify a starting point bias and drift rate (in opposite directions - thus having systematic effects on choice biases without altering the average proportion of LL choices) provides crucial first evidence for the hypothesis that dopamine and proximity interact to influence decision-making. These results thereby enrich our understanding of the neuromodulatory mechanisms influencing inter-temporal choice, and take an important step towards resolving prior contradictions in this literature. They also have implications for how striatal dopamine might impact decision-making in diverse domains of impulsivity beyond inter-temporal choice, ranging from cognitive neuroscience (e.g. in numerous cognitive control tasks) to psychiatry (treating diverse disorders of impulse control).

Reviewer #3 (Public Review):

The primary objectives of this manuscript were to characterize "the baseline phenotypic diversity in B cells and B cell receptors (BCRs) in the Kymouse" and draw comparisons to existing mouse and human datasets. Specifically, the authors place an emphasis on investigating whether the BCR repertoire has characteristics in common with repertoires from healthy humans (as expected), rather than wild-type mice (C57BL/6). In my opinion, the authors have met these basic objectives. The authors conclude that while the Kymouse repertoires have distinct heavy chain variables, diversity, and joining gene usage profiles and that their CDRH3 length is intermediate to the group averages of their control samples (C57BL/6, n=5; human, n-10), other important features, such as kappa and lambda light chain ratios, and CDRH3 structures were more "human-like". The data presented here will be useful for setting a foundation for the use of this model in future studies (as well as other similar transgenic models). Ultimately, how the Kymouse model can be best utilized for different objectives will be important to determine. As outlined by the authors in the first paragraph of the introduction, whether the repertoires and associated immune responses mounted by these animals can be "considered representative of humans" will likely need additional demonstration through investigations under various experimental conditions.

Reviewer #3 (Public Review):

This work uses an agent-based model of SARS-CoV-2 transmission (calibrated to the first wave in the Netherlands) to examine how the societal impact of interventions could have been reduced - while maintaining epidemiological impact - if they were implemented at a subnational (eg, municipality) rather than a national level. After more than two years of lockdowns and mobility restrictions, the societal cost of such measures is becoming better understood, and it is important to evaluate the effectiveness of such measures and reflect upon how they can be deployed in a minimally disruptive fashion. Mathematical and computational models are a natural choice for such investigations as they enable researchers to explore counter-factual scenarios ("what might have happened had we acted differently?")

The authors conclude that subnational interventions, triggered via prevalence in a particular municipality, could have controlled the first wave of SARS-CoV-2 in the Netherlands with minimal health cost but less societal disruption than national interventions. This claim is supported by reference to Figure 4 showing the impact on (a) hospital admissions and (b) municipalities without interventions through different phases of the outbreak. For more remote/rural municipalities, the use of interventions is delayed by ~1 week, although some (6%) of municipalities avoid interventions altogether.

Strengths:

As noted above, the general objective of this study is important and of potentially broad interest. The agent-based model is complex, but not unreasonably so, and makes good use of rich demographic, mobility, epidemiological/clinical, etc. data for calibration. The simulations conducted using the model support the specific conclusions of the manuscript.

Weaknesses:

While the motivation and approach are strong points of this work, the analysis and interpretation would benefit from further development. The robustness of model behaviour to the threshold used to trigger subnational interventions is explored; however, there are other aspects of the model that are not subjected to sensitivity analysis, including:

1. The impact of imperfect surveillance (eg, due to asymptomatic transmission, reporting delays, etc);

2. The impact of non-compliance, which could potentially differ for subnational versus national interventions;

3. The impact of pathogens/variants with transmission/severity characteristics different from the original SARS-CoV-2 strain.

In the absence of such analyses, it is difficult to generalise the findings beyond "this is how subnational interventions could have been used to control the first wave of SARS-CoV-2 in the Netherlands" to "this is how subnational interventions could be used effectively in the event of future outbreaks" (of a SARS-CoV-2 variant or other pathogen).

The discussion focuses on limitations associated with the model but does not consider other potential implications of subnational interventions. For example:

1. Subnational interventions may produce unintended consequences if populations respond by relocating from regions with interventions (high prevalence) to regions without interventions (low prevalence).

2. Subnational interventions would require extremely effective public health messaging to avoid confusing populations. Particularly in densely populated regions where municipalities may be small and tightly connected, the feasibility of communicating (and enforcing compliance with) interventions may be challenging.

3. A proposal to implement subnational interventions - following the results of this work - may raise ethical questions about cost-benefit trade-offs (eg, whether 355 additional hospital admissions is an acceptable price to pay for 36 million person-days without interventions; ie, two days per citizen, on average). The fact that such decisions would (in the even of a future outbreak) need to be made rapidly, in the face of potential uncertainty about pathogen characteristics, heightens the need for clear understanding of how situational factors may affect the likely effectiveness of interventions (at any scale).

Impact and broader utility:

As noted, the question addressed - how we can reduce the disruption caused by interventions for transmission control - is important. Thus, the work presented in this manuscript has the potential for broad utility. Currently, this is limited by the focus on specific outbreak instance.

Reviewer #3 (Public Review):

The authors first demonstrated in bone marrow-derived macrophages (BMMs) that IL-4 treatment of BMMs led to a significant reduction of BCG- and TDB-induced MINCLE expression (Fig. 1). While IL-4 treatment did not impact BCG phagocytosis by BMMs, it led to a reduced production of the cytokines G-CSF and TNF by BMMs (Fig. 2). In an elegant model using hydrodynamic injection of mini-circle DNA encoding IL-4, the authors show that IL-4 overexpression abrogated the increased MINCLE expression in monocytes upon BCG infection in vivo. Similar findings were observed in a co-infection model with the hookworm Nippostrongylus brasiliensis, where MINCLE expression on inflammatory monocytes from BCG-infected mice was reduced compared to control mice infected only with BCG (Fig. 3). The key findings of the manuscript include the two murine helminth infection models, S. mansoni as a chronic infection, and N. brasiliensis as a transient infection, in both of which the authors showed an organ-specific inhibition of the Th17 response in a vaccination setting with a MINCLE-dependent adjuvant (Fig. 4 and 5).

Data shown in the manuscript represents a major advance over previous studies because for the first time a relation between IL-4 and MINCLE expression and function is demonstrated in vivo in relevant co-infection models. All experiments have been done with care. Appropriate controls have been included and conclusions are largely supported by the data. Future studies in human patients will be needed to determine the clinical relevance of the findings observed in the murine helminth infection models.

Reviewer #3 (Public Review):

This manuscript by Jagoda et al. addresses the genetic mechanism of the haplotype at chromosome 3 where introgressed from Neanderthals shows the strong association with COVID-19 severity in Europeans. They re-evaluate the adoptively introgressed segment using Sprime and U and Q95 methods and analyze cis- and trans- eQTLs based on the whole blood dataset. All the 361 Sprime-identified introgressed variants act as eQTLs in the whole blood and alter the expression of 14 genes including seven chemokine receptor genes.

Then they tested the 613 variants using a Massively Parallel Reporter Assay (MPRA) in K562 cells and narrow downed the 20 emVars. In the end, they selected the four variants based on four criteria regarding the association of COVID-19 severity, eQTL data, chromosomal interaction, and epigenetic marks in immune cells. They highlighted variant rs35454877 (CCR5 regulation), rs71327024, rs71327057, and rs34041956 (CCR1 regulation).

Narrowing down the four critical variants from the around 800 kb introgressed region is impressive work. However, MPRA and eQTL data are not consistent, and these data don't support clinical gene expression data (increased expression of CCR1 in severe COVID-19 patients).

Reviewer #3 (Public Review):

Previous work on HO-2 null mice suggest that the increased occurrence of central and obstructive sleep apneas observed in these animals is linked to hyperactivation of carotid bodies through a CO-dependent H2S increase mechanism within the carotid bodies. Hyperoxia, genetic ablation or pharmacological bloc of CSE (a CO-dependent H2S producing enzyme) reduced the occurrence of both central and obstructive apneas.

Here, the authors propose an alternate, or complementary view to address occurrence of OSA in HO-2 null mice. In in vitro medullary slice preparations they used the same pharmacological and genetic approaches to manipulate levels of CO and H2S and observe that inhibition or elimination of HO-2 induces a transmission failure between the preBotC and hypoglossal motoneurons that is potentially linked to a post-synaptic effect on hypoglossal motoneurons, in particular at the level of apamin sensitive small conductance potassium channels.

Although drugs were bath applied rather than local applied to XII motoneurons, the authors provide evidence that HO-2 and CSE modulation affects the Input/Output relationship between the preBötC and the hypoglossal nucleus.

Given the occurrence on central apneas in these mice in vivo, the potential effects of H2S on preBotC neurons, the use of bath application in these experiments and the apparent effects on rhythmogenesis, additional assessment of preBötC function in these mice would benefit the study.

Reviewer #3 (Public Review):

In this research, the authors explore a novel mechanism of CDK4/6 inhibitor dalpiciclib in HER2+HR+ breast cancers, in which dalpiciclib could reverse the process of ER intra-nuclear transportation upon HER2 degradation. The conclusions are significant to gain insight into the biological behavior of TPBC and provided a conceptual basis for the ideal efficacy in the published clinical trial. The findings are supported by supplemented in vivo assay and transcriptomic analysis.

Reviewer #3 (Public Review):

In this manuscript, the authors found upregulation of PCA3 and downregulation of PRUNE2 in prostate cancer as compared with normal prostate in two retrospective and independent patient cohorts, supporting that PCA3 and PRUNE3 function as an oncogene and a tumor suppressor gene, respectively. The findings presented here represent additional evidence for the functional reciprocal co-regulation of PCA3 and PRUNE2 in the setting of early tumorigenesis but not in late events in human prostate cancer. But further studies of PCA3/PRUNE2 dysregulation are still needed.

Reviewer #3 (Public Review):

This study examines cellular deficits in human neural precursor cells derived from ASD individuals and unaffected controls. The ASD cases include idiopathic ASD individuals and 16p Deletion ASD individuals. These are rigorous studies employing multiple differentiations and multiple clones for all experiments. The authors report common deficits in neurite outgrowth and migration in these distinct ASD samples, and further demonstrate common deficits in downstream mTOR signaling. Outgrowth and migration deficits could be mimicked or rescued by manipulating mTOR signaling, further supporting a role for mTOR in these deficits. Differences in EF responsiveness identify ASD-subtype specific deficits, and the effects of subthreshold concentrations of EFs represent novel and interesting findings.

The results on the mTOR signaling pathway as a point of convergence in these particular ASD subtypes is interesting, but the discussion should address that this has been demonstrated for other autism syndromes, and in the present manuscript, there should be some recognition that other signaling pathways are also implicated as common factors between the ASD subtypes.

The conclusions of this paper are mostly well supported by data, but for the cell migration assay, it is not clear if the authors control for initial differences in the inner cell mass area of the neurospheres in control vs ASD samples, which would affect the measurement of migration. Also, in Fig 5 and 6, panels I and J omit the effects of drug on mtTOR phosphorylation as shown for other conditions.

Reviewer #3 (Public Review):

A problem in synthetic ecology is that one can't brute-force complex community design because combinatorics make it basically impossible to screen all possible communities from a bank of possible species. Therefore, we need a way to predict phenomena in complex communities from phenomena in simple communities. This paper aims to improve this predictive ability by comparing a few different simple models applied to a large dataset obtained with the use of the author's "kchip" microfluidics device. The main question they ask is whether the effect of two species on a focal species is predicted from the mean, the sum, or the max of the effect of each single "affecting" species on the focal species. They find that the max effect is often the best predictor, in the sense of minimizing the difference between predicted effect and measured effect. They also measure single-species trait data for their library of strains, including resource niche and antibiotic resistance, and then find that Pearson correlations between distance calculations generated from these metrics and the effect of added species are weak and unpredictive. This work is largely well-done, timely and likely to be of high interest to the field, as predicting ecosystem traits from species traits is a major research aim.

My main criticism is that the main take-home from the paper (fig 3B)-that the strongest effect is the best predictor-is oversold. While it is true that, averaged over their six focal species, the "strongest effect" was the best overall predictor, when one looks at the species-specific data (S9), we see that it is not the best predictor for 1/3 of their focal species, and this fraction grows to 1/2 if one considers a difference in nRMSE of 0.01 to be negligible.

The same criticism applies to the result from figure 2-that pairs of affecting species have more negative effects than single species. Considered across all focal species this is true (though minor in effect size, Fig 2A). But there is only a significant effect within two individual species. Again, this points to the effects being focal-species-specific, and perhaps not as generalizable as is currently being claimed.

Another thing that points to a focal-species-specific response is Fig 2D, which shows the distributions of responses of each focal species to pairs. Two of these distributions are unimodal, one appears bimodal, and three appear tri-modal. This suggests to me that the focal species respond in categorically different ways to species addition.

These differences occur even though the focal bacteria are all from the same family. This suggests to me that the generalizability may be even less when a more phylogenetically dispersed set of focal species are used.

Considering these points together, I argue that the conclusion should be shifted from "strongest effect is the best" to "in 3 of our focal species, strongest effect was the best, but this was not universal, and with only 6 focal species, we can't know if it will always be the best across a set of focal species".

My second main criticism is that it is hard to understand exactly how the trait data were used to predict effects. It seems like it was just pearson correlation coefficients between interspecies niche distances (or antibiotic distances) and the effect. I'm not very surprised these correlations were unpredictive, because the underlying measurements don't seem to be relevant to the environment tested. What if, rather than using niche data across 20 nutrients, only the growth data on glucose (the carbon source in the experiments) was used? I understand that in a field experiment, for example, one might not know what resources are available, and so measuring niche across 20 resources may be the best thing to do. Here though it seems imperative to test using the most relevant data.

Additionally and relatedly, it would be valuable to show the scatterplots leading to the conclusion that trait data were uninformative. Pearson's r only works on an assumption of linearity. But there could be strong relationships between the trait data and effect that are monotonic but not linear, or even that are non-monotonic yet still strong (e.g. U-shaped). For the first case, I recommend switching to Spearman's rho over Pearson's r, because it only assumes monotonicity, not linearity. If there are observable relationships that are not monotonic, a different test should be used.

In general, I think the analyses using the trait data were too simplistic to conclude that the trait data are not predictive.

Reviewer #3 (Public Review):

In this manuscript, Caspy et al. present a detailed structural analysis of eukaryotic photosystem II (PSII) isolated from the green alga Dunaliella salina. By combining single-particle cryo-EM with multibody refinement, the authors not only reveal a high-resolution (2.4Å) structure of the eukaryotic PSII, but also demonstrate alternate conformations and intrinsic flexibility of the overall complex. Stretched and compact conformations of the PSII dimer were readily identified within the single-particle dataset. From this structural analysis, the authors propose that excitation energy transfer properties may be modulated by changes in transfer distance between key chlorophyll molecules observed in different conformational states of the PSII dimer. Due to the high resolution of the maps obtained, the authors identify post-translational modifications and a sodium binding site based on the observed cryo-EM maps. Additionally, the authors analyze PSII complexes in stacked and unstacked configurations, and find that compact and stretched states also exist within the stacked PSII complexes. From their cryo-EM maps, the authors demonstrate that there is no direct protein-protein interaction between stacked PSII complexes, and rather propose a model wherein long-range electrostatic interactions mediated by divalent cations such as magnesium, can facilitate PSII stacking.

The conclusions and models presented in the manuscript are mostly well justified by the data. The cryo-EM maps are high quality and the models appear generally well refined. However, some aspects of data processing and analysis, as well as the resultant conclusions need to be clarified.

1. In general, it is not clear from the cryo-EM processing workflow (suppl. Fig 1) or the methods section when exactly symmetry was applied during 3D classification and refinement. In the case of C2S2 unstacked particles, when was symmetry first applied in the overall processing workflow? To identify the compact and stretched configurations of C2S2, did the 3D classification without alignment (and/or the refinement preceding this classification) have C2 symmetry applied? If so, have you considered the possibility that some particles may actually be asymmetric in some regions?

2. Following multibody refinement in Relion individual maps and half-maps for each body will be generated. There is no mention in the methods of how these individual maps for each C2S2 "monomer" were combined to produce an overall map of the dimer following multibody refinement. There are several methods currently used to combine such maps, including taking the maximum or average of the two maps or using a model-based approach in phenix. The authors should be explicit about the method they used, any potential artifacts that may develop from this map combination process, and/or the interface between masks used in multibody refinement.

3. In addition to the point raised above, following multibody refinement there will be an individual FSC curve and resolution for each body. However, in supplemental figure 2 and supplemental table 1, only a single FSC curve and resolution are reported. Are these FSC curves/resolutions only reported for the better of the two bodies? If not, how was a single resolution calculated for the overall map of combined bodies?

4. One of the major conclusions from the 3D classification and multibody refinement is that conformational changes and inherent flexibility of the PSII dimers have the potential to change distances between cofactors in the complex, ultimately leading to altered excitation energy transfer. However, it is unclear whether or not the authors believe one conformation over another may more readily support the evolution of oxygen. It would be nice if the authors could elaborate slightly upon this topic in the discussion.

5. Along the lines of point 4 above, on line 95 the authors claim that "the high specific activity of 816 umol O2/ (mg Chl * hr) suggest that" both the C2S2 compact and stretched conformation are highly active. However, it is not clear to me why this measure of specific activity would suggest that both PSII conformations should have "high" activity. Maybe a reference here would help guide readers to previous measures of specific activity?

6. It is claimed that "more than 2100 water molecules were detected in the C2S2 compressed model", and the water distribution is shown in Figure 3. Obtaining resolutions capable of visualizing waters with cryo-EM is still a significant challenge. Upon visual inspection of the map supplied, it appears that several of the waters that were built into the atomic model simply do not have supporting peaks in the coulomb potential map above the level of noise. While some of the modeled waters are certainly supported by the map, in my opinion, there are many waters that simply are not, or at best are questionable. What method or tool was originally used to build waters into the model, and how were these waters subsequently validated during structure refinement?

7. The authors claim to identify several unique map densities during model building. One of these is a sodium ion close to the OEC, which is coordinated by D1-His337, several backbone carbonyls, and a water molecule. When looking closely at the cryo-EM map supplied, it appears that the coulomb potential map is quite weak for this sodium, and is only visible at quite low contour levels. In fact, the features for the coordinating water, and chloride ions located ~7-9A away are much stronger than the sodium. Do the authors have any explanation for why the cryo-EM map is significantly weaker for the sodium compared to the coordinating water or chloride ions in the same general vicinity? Similar to what they did for the other post-translational modifications, the authors should consider showing the actual cryo-EM map for the bound sodium in supplemental Figure 10 a,b.

8. The cryo-EM maps showing CP29-Ser84 phosphorylation and CP47-Cys218 sulfinylation are quite convincing. However, it is interesting that these modifications are only observed in the compact conformation, and not in the stretched conformation. Can the authors elaborate on whether or not they believe the compact and stretched conformations could be a result of these posttranslational modifications, or vice versa?

9. Do the authors believe that PSII dimers in the solution can readily interconvert between compact and stretched conformations? Or is the relative ratio of these conformations fixed at the time of membrane solubilization with decyl-maltoside?

10. The model proposed for divalent cation-mediated stacking of PSII dimers is compelling, and seems to be in agreement with previous investigations that observed a lack of stacked dimers in cryo-EM preparations lacking calcium/magnesium. However, my understanding from reading the methods section is that the observed lack of density between the stacked PSII dimers was inferred from maps obtained after multibody refinement. Based on the way the masks to define bodies were created for multibody refinement (Fig. 4A), the region between stacked dimers would be highly prone to map artifacts following multibody refinement. Have the authors looked closely at the interfacial region between stacked dimers following conventional 3D classification/refinement to ensure that there are indeed no features observed in the interfacial region even at low contour levels?

Reviewer #3 (Public Review):

This study aims at classifying central amygdala neurons based on their expression of marker genes along with their spatial, morphological, and connectivity properties. The use of state-of-the-art experimental and analysis approaches to disentangle the functional complexity and heterogeneity of this brain region is a clear strength of the study. The detailed spatial description, including rostral-caudal dimensions and specific CeA subnuclei in all of their analyses as well as the co-expression of multiple marker genes and description of various long-range projection targets, will be valuable, potentially allowing for the targeting of anatomically distinct CeA subregions in future mechanistic studies. The major weaknesses are the exclusion of female subjects in their experiments and the incomplete acknowledgement of previous studies that have addressed transcript expression and cell-type specific function in the CeA.

Reviewer #3 (Public Review):

The nuclear transport machinery is aberrantly regulated in many cancers in a context-dependent fashion, and mounting evidence with cultured cell and animal models indicates that reducing the activity or expression of certain nuclear transport proteins can selectively kill cancer cells while sparing nontransformed cells. Here the authors further explore this concept using a zebrafish model for hepatocellular carcinoma (HCC) induced by liver-specific transgenic expression of oncogenic krasG12V. The transgene causes greatly increased liver size by day 7 in larvae, associated with a gene expression profile that resembles early-stage human HCC. This study focuses on Ahctf1, a nuclear pore complex (NPC) protein known to be essential for postmitotic NPC assembly. Using the krasG12V background, the authors analyze animals that are heterozygous for a recessive mutation in the ahctf1 gene that leads to ~50% reduction in ahctf1 mRNA (and likely the encoded protein). The authors show that the ~4-fold increase in liver volume of krasG12V animals is reduced by ~1/3 in the ahctf1 heterozygous mutants. This is associated with increased apoptosis, decreased DNA replication, up-regulation of pro-apoptotic and cdk-inhibitor genes, and down-regulation of anti-apoptotic gene. These effects found to be substantially Tp53-dependent. Consistent with previous Ahctf1 depletion studies, hepatocytes of ahctf1 heterozygotes show decreased NPC density at the nuclear surface, elevated levels of aberrant mitoses and increased DNA damage/double stranded breaks. Finally, the authors show that combining the achtf1 heterozygous mutant with a heterozygous mutation in another NPC protein- RanBP2- or treating animals with a chemical inhibitor of exportin-1 (Selinexor) can further reduce liver volume. Overall they suggest that combinatorial targeting of the nuclear transport machinery can provide a therapeutic approach for targeting HCC.

This is an interesting study that bolsters the notion that reduction in the levels of discrete nucleoporins (and/or inhibiting specific nuclear transport pathways) can result in cancer cell-selective killing. Moreover, the work extends previous studies involving cultured cell and mouse xenografts to a new cancer model (HCC) and nucleoporin (Ahctf1). Whereas the authors describe multiple aberrant cellular phenotypes associated with the dosage reduction in ahctf1, the exact causes for reduction in liver size in the krasG12V model remain unclear. Although it would be desirable to parse effects of Ahctf1 related to NPC number, aberrant mitoses, licensing of DNA replication and chromatin regulation, this is a tall order at present, given the limited understanding of Ahctf1. However, useful insight on these and related questions could be gained with further analysis of the system as outlined below.

1) In the krasG12V model, it would be helpful to distinguish the contribution of increased cell death vs decreased cell proliferation to the change in liver size seen with heterozygous ahctf1. Is this predominantly due to decreased proliferation?

2) It would be good to know whether the heterozygous ahctf1 state blunts the overall level of Ras activity in krasG12V animals.

3) Notwithstanding the analysis of Tp53 target genes presented in this study, it would be helpful to see detailed transcriptional profiling of hepatocytes in the krasG12V model with the heterozygous ahctf1 mutation, and to assess the effects of Selinexor. GSEA type analysis offers a way to start untangling the effects of these pathways. Moreover this analysis could provide insight on the relevance of this model to human HCC.

4) Functions of Achtf1 in regard to chromatin regulation could be compromised in this model. Scholz et al (Nat Gen 2019) report that Ahctf1 is involved in increasing Myc expression via gene gating mechanism. It would be good to know what the effects are in this system. Indeed, anti-cancer effects from depletion of Nup93 in a breast cancer model was reported to involve a role of Nup93 in chromatin regulation (Bersini et al, Life Sci Alliance 2020).

5) If feasible, it would be important to know if loss/reduction in Tp63, proposed to compensate with Tp53 loss, would alter the effects of Achtf1 depletion.

6) The synthetic lethality argument pressed in this manuscript seems exaggerated. Standard anti-cancer treatments typically target several cellular pathways, and nucleoporins directly affect a multiplicity of pathways besides nuclear transport.

Reviewer #3 (Public Review):

The manuscript by Hoces et al uses a small set of genetically barcoded B. theta strains to quantify population bottlenecks during colonization based on a Poisson model. They then estimate the decrease in niche size as a function of microbiota complexity. Although there was a surprising similarity between the WT and CPS mutant when colonizing separately, they showed that the competitive disadvantage during co-colonization was due to a lag before growth initiation in the gut. Overall, they make the interesting finding that capsule may be more important to deal with microbiota interactions rather than the host. In general, I find the manuscript well-constructed and interesting, using a clever method to understand an important question in microbiome biology. The titration experiments in particular led to very clean results.

Reviewer #3 (Public Review):

In this manuscript, the authors compared the accuracy of 3 machine learning (ML) algorithms for predicting incident diabetic kidney disease (DKD) by using longitudinal data from 1,365 Chinese, Malay, and Indian participants from the Singapore Epidemiology of Eye Diseases (SEED) study cohort (median follow up 6 years). They report that their ML model "Elastic Net" had the highest AUC (0.85) of the 3 ML models, compared to a logistic regression model (AUC 0.79). The LR model was based on age, sex, ethnicity, duration of diabetes, systolic blood pressure, HbA1c, and body mass index. In 3 ML models, the authors included a range of variables including > 200 blood metabolites, single nucleotide polymorphisms, and eye imaging parameters.

A major weakness of this study is the definition of incident DKD and the lack of albuminuria data - the authors define incident DKD as eGFR < 60 cc/min/1.73 m2. This may underestimate the incidence of DKD, and further may label non-DKD as DKD (e.g. in an individual who experiences acute kidney injury without full recovery). Another major weakness is the treatment of ethnicity as a biological variable - in the strongest prediction model, Chinese vs Malay vs Indian ethnicity was one of the top 15 variables in the ML model. More explanation is needed around why ethnicity was included in both the ML models and the LR model. Further, a subgroup analysis of each of these groups was not performed. Finally, the rationale for the selection of the >200 metabolites is unclear. Several of the top 15 variables in all 3 models are these metabolites. Another top-15 variable in one of the models was noted to be "anti-diabetes medications", though the authors do not separate insulin vs non-insulin medications.

Reviewer #3 (Public Review):

Caligaris and colleagues show a new mechanism by which AMPK/Snf1 inhibits TORC1 signaling during glucose starvation. They propose that under glucose starvation, Snf1 inhibits the unscheduled activation of TORC1 by phosphorylating Pib2 and Sch9, upstream and downstream effectors of TORC1. The study also provides a resource for novel substrates of Snf1 which can be useful for future studies. Specific comments are below.

1. Conceptually, the manuscript shows that Snf1 activity is important for the acute inhibition of TORC1 during glucose starvation. However, this is mainly restricted to 10 and 15 minutes of glucose starvation. After 20 minutes, TORC1 is inhibited by some unknown mechanisms independent of Snf1 (Hughes Hallet et al). This raises concern regarding the physiological relevance of Snf1-mediated TORC1 inhibition during acute glucose stress. The authors show that this regulation is important for the survival of cells under TORC1 inhibition. How do the authors envision that the acute role of Snf1 plays an important long-term physiological relevance during rapamycin treatment? Providing more support for the physiological relevance of this regulation will make this study of interest to a broad readership.

2. Another major concern of the manuscript is the inconsistencies between the various representative immunoblots and their quantifications. The effect of AMPK activity on TORC1 signaling under glucose starvation seems very subtle. A few specific concerns are mentioned below:

a) In figure 1A, the increase in TORC1 activity upon inhibition of analogue sensitive Snf1as by 2NM-PP1 is very marginal. Although quantification shows a significant increase, a representative western blot figure should be shown.

b) Does deleting Snf1 itself have any effect on TORC1 activity? Lane 4 of figure 1A shows reduced activity compared to lane 1.

c) To show the effect of Snf1 on the repression of TORC1, the time-course experiments are run on two separate gels in figure 1C. Hence, it is difficult to compare the effect of Snf1 on unscheduled reactivation of TORC1 under glucose starvation.

d) In figure 1E, the effect of Reg1 deletion on TORC1 activity seems minor as both phospho- and total levels of Sch9 are reduced.

Since further mechanistic insights are based on these initial findings of figure 1, solidifying these observations is very important.

3. In figure S1, the analogue sensitive Snf1as shows significant reduction in its activity (reduced S79 phosphorylation of ACC1-GFP). This raises the concern of whether this genetic background is an ideal system to resolve the mechanism of TORC1 suppression.

4. In figure 2, during glucose restimulation, there is increased retention of Snf1as-pThr210 in the presence of 2NM-PP1. This suggests that the upstream glucose sensing pathway as well as Snf1 might be more active than in DMSO-treated cells. This also raises concerns regarding the suitability of the genetic background for the study. Can authors comment on why this phosphorylation persists? Does the phosphoproteomic analysis give any hint for this phenotype?

5. In figure 4H, where authors claim reduced binding of Kog1 to Pib2SESE, levels of Kog1 in input are also reduced. Can authors provide further support using colocalization studies? Also, does Pib2SESE has any defect in forming Kog1 bodies?

6. In figure 5F, where the authors claim the Sch9SE mutant has lower TORC1 activity, the difference is very minor. Furthermore, corresponding lanes also show reduced levels of Snf1as expression. Hence, improved blots are required here. Also, an in vitro kinase assay with full-length Sch9 KD with and without the Ser288 mutation could solidify the observation that phosphorylation of Ser288 indeed affects TORC1-mediated phosphorylation.

7. In figure 6E, the Sch9SE mutant shows no effect in the presence of rapamycin. Thus, in vivo, phosphorylation at Ser288 may not be perturbing the phosphorylation of Sch9 by TORC1.

8. According to the author's proposed mechanism, TORC1 activity in Pib2SASA or Pib2SASA/Sch9SA backgrounds should be higher during glucose starvation compared to the control strains. However, glucose starvation shows a similar level of reduction in TORC1 activity in these backgrounds. This raises concern regarding the proposed mechanism. The authors mainly base their conclusions on Ser to Glutamate mutants. The authors should be cautious that Ser to Glutamate changes may also affect the protein structure which can confer similar phenotypes. How do the authors justify this discrepancy?