Reviewer #3 (Public review):

The central goal of this paper as I understand it is to extract the "integration hierarchy" of stimulus in the dorsal and ventrolateral visual fields. The segregation of these responses is different from what is thought to occur in bees and flies and was established in the authors' prior work. Showing how the stimuli combine and are prioritized goes beyond the authors' prior conclusions that separated the response into two visual regions. The data presented do indeed support the hierarchy reported in Figure 5 and that is a nice summary of the authors' work. The moths respond to combinations of dorsal and lateral cues in a mixed way but also seem to strongly prioritize avoiding dorsal optic flow which the authors interpret as a closed and potentially dangerous ecological context for these animals. The authors use clever combinations of stimuli to put cues into conflict to reveal the response hierarchy.

My most significant concern is that this hierarchy of stimulus responses might be limited to the specific parameters chosen in this study. Presumably, there are parameters of these stimuli that modulate the response (spatial frequency, different amounts of optic flow, contrast, color, etc). While I agree that the hierarchy in Figure 5 is consistent for the particular stimuli given, this may not extend to other parameter combinations of the same cues. For example, as the contrast of the dorsal stimuli is reduced, the inequality may shift. This does not preclude the authors' conclusions but it does mean that they may not generalize, even within this species. For example, other cue conflict studies have quantified the responses to ranges of the parameters (e.g. frequency) and shown that one cue might be prioritized or up-weighted in one frequency band but not in others. I could imagine ecological signatures of dorsal clutter and translational positioning cues could depend on the dynamic range of the optic flow, or even having spatial-temporal frequency-dependent integration independent of net optic flow.

The second part of this concern is that there seems to be a missed opportunity to quantify the integration, especially when the optic flow magnitude is already calculated. The discussion even highlights that an advantage of the conflict paradigm is that the weights of the integration hierarchy can be compared. But these weights, which I would interpret as stimulus-responses gains, are not reported. What is the ratio of moth response to optic flow in the different regions? When the moth balances responses in the dorsal and ventrolateral region, is it a simple weighted average of the two? When it prioritizes one over the other is the response gain unchanged? This plays into the first concern because such gain responses could strongly depend on the specific stimulus parameters rather than being constant.

The authors do explain the choice of specific stimuli in the context of their very nice natural scene analysis in Fig. 1 and there is an excellent discussion of the ecological context for the behaviors. However, I struggled to directly map the results from the natural scenes to the conclusions of the paper. How do they directly inform the methods and conclusions for the laboratory experiments? Most important is the discussion in the middle paragraph of page 12, which suggests a relationship with Figure 1B, but seems provocative but lacking a quantification with respect to the laboratory stimuli.

The central conclusion of the first section of the results is that there are likely two different pathways mediating the dorsal and the ventrolateral response. This seems reasonable given the data, however, this was also the message that I got from the authors' prior paper (ref 11). There are certainly more comparisons being done here than in that paper and it is perfectly reasonable to reinforce the conclusion from that study but I think what is new about these results needs to be highlighted in this section and differentiated from prior results. Perhaps one way to help would be to be more explicit with the open hypotheses that remain from that prior paper.

Reviewer #3 (Public review):

Summary:

This study by Glica and colleagues utilized EEG (i.e., Beta power, Gamma power, and aperiodic activity) and 7T MRS (i.e., MRS IE ratio, IE balance) to reevaluate the neural noise hypothesis in Dyslexia. Supported by Bayesian statistics, their results show convincing evidence of no differences in EI balance between groups, challenging the neural noise hypothesis.

Strengths:

Combining EEG and 7T MRS, this study utilized both the indirect (i.e., Beta power, Gamma power, and aperiodic activity) and direct (i.e., MRS IE ratio, IE balance) measures to reevaluate the neural noise hypothesis in Dyslexia.

Reviewer #3 (Public review):

The manuscript contains a carefully designed fMRI study, using MVPA pattern analysis to investigate which high-level associate cortices contain target-related information to guide visual search. A special focus is hereby on so-called 'target-associated' information, that has previously been shown to help in guiding attention during visual search. For this purpose the author trained their participants and made them learn specific target-associations, in order to then test which brain regions may contain neural representations of those learnt associations. They found that at least some of the associations tested were encoded in prefrontal cortex during the cue and delay period.

The manuscript is very carefully prepared. As far as I can see, the statistical analyses are all sound and the results integrate well with previous findings.

I have no strong objections against the presented results and their interpretation.

Reviewer #3 (Public review):

Summary:

The authors optogenetically stimulate 5 neurons all preferring the same pure tone frequency (16 or 54 kHz) in the mouse auditory cortex using a holography-based single cell resolution optogenetics during sound presentation. They demonstrate that the response boosting of target neurons leads to a broad suppression of surrounding neurons, which is significantly more pronounced in neurons that have the same pure tone tuning as the target neurons. This effect is immediate and spans several hundred micrometers. This suggests that the auditory cortical network balances its activity in response to excess spikes, a phenomenon already seen in visual cortex.

Strengths:

The study is based on a technologically very solid approach based on single-cell resolution two-photon optogenetics. The authors demonstrate the potency and resolution of this approach. The inhibitory effects observed upon targeted stimulation are clear and the relative specificity to co-tuned neurons is statistically clear although the effect size is moderate.

Weaknesses:

The evaluation of the results is brief and some aspects of the observed homeostatic are not quantified. For example, it is unclear whether stimulation produces a net increase or decrease of population activity, or if the homeostatic phenomenon fully balances activity. A comparison of population activity for all imaged neurons with and without stimulation would be instructive. The selectivity for co-tuned neurons is significant but weak. Although it is difficult to evaluate this issue, this result may be trivial, as co-tuned neurons fire more strongly. Therefore, the net activity decrease is expected to be larger, in particular, for the number of non-co-tuned neurons which actually do not fire to the target sound. The net effect for the latter neurons will be zero just because they do not respond. The authors do not make a very strong case for a specific inhibition model in comparison to a broad and non-specific inhibitory effect. Complementary modeling work would be needed to fully establish this point.

Reviewer #3 (Public review):

In this work, the authors present an open-source system called behaviourMate for acquiring data related to animal behavior. The temporal alignment of recorded parameters across various devices is highlighted as crucial to avoid delays caused by electronics dependencies. This system not only addresses this issue but also offers an adaptable solution for VR setups. Given the significance of well-designed open-source platforms, this paper holds importance.

Advantages of behaviorMate:

The cost-effectiveness of the system provided.<br /> The reliability of PCBs compared to custom-made systems.<br /> Open-source nature for easy setup.<br /> Plug & Play feature requiring no coding experience for optimizing experiment performance (only text based Json files, 'context List' required for editing).

Reviewer #3 (Public review):

Summary:

The study uses structural MRI to identify how the number, degree of experience, and phonemic diversity of language(s) that a speaker knows can influence the thickness of different sub-segments of auditory cortex. In both a primary and replication sample of adult speakers, the authors find key differences in cortical thickness within specific subregions of cortex due to either the age at which languages are acquired (degree of experience) or the diversity of the phoneme inventories carried by that/those language(s) (breadth of experience).

Strengths:

The results are first and foremost quite fascinating and I do think they make a compelling case for the different ways in which linguistic experience shapes auditory cortex.

The study uses a number of different measures to quantify linguistic experience, related to how many languages a person knows (taking into account the age at which each was learned) as well as the diversity of the phoneme inventories contained within those languages. The primary sample is moderately large for a study that focuses on brain-behaviour relationships; a somewhat smaller replication sample is also deployed in order to test the generality of the effects.

Analytic approaches benefit from the careful use of brain segmentation techniques that nicely capture key landmarks and account for vagaries in the structure of STG that can vary across individuals (e.g., the number of transverse temporal gyri varies from 1-4 across individuals).

Weaknesses:

The specificity of these effects is interesting; some effects really do appear to be localized to left hemisphere and specific subregions of auditory cortex e.g., TTG. There is an ancillary analysis that examines regions outside auditory cortex to examine whether these are the only brain regions for which such effects occur. Expanding the search space to a whole-brain analysis, and a more lenient statistical threshold, does reveal only small patches of the brain outside auditory cortex show similar effects. Notably, these could be due to inflated type-1 error, but overall we would need a much larger sample to be certain.

Discussion of potential genetic differences underlying the findings is interesting. It does represent one alternative account that does not have to do with plasticity/experience, as the authors acknowledge.

The replication sample is useful and a great idea. It does however feature roughly half the number of participants. As the authors are careful to point out, that statistical power is weaker and given small effects in some cases we should not be surprised that the results only partially replicated in that sample.

Reviewer #3 (Public review):

Summary:

m6Am is an abundant mRNA modification present on the TSN. Unlike the structurally similar and abundant internal mRNA modification m6A, m6Am's function has been controversial. One way to resolve controversies surrounding mRNA modification functions has been to develop new ways to better profile said mRNA modification. Here, Liu et al. developed a new method (based on GLORI-seq for m6A-sequencing), for antibody-independent sequencing of m6Am (CROWN-seq). Using appropriate spike-in controls and knockout cell lines, Liu et al. clearly demonstrated CROWN-seq's precision and quantitative accuracy for profiling transcriptome-wide m6Am. Subsequently, the authors used CROWN-seq to greatly expand the number of known m6Am sites in various cell lines and also determine m6Am stoichiometry to generally be high for most genes. CROWN-seq identified gene promoter motifs that correlate best with high stoichiometry m6Am sites, thereby identifying new determinants of m6Am stoichiometry. CROWN-seq also helped reveal that m6Am does not regulate mRNA stability or translation (as opposed to past reported functions). Rather, m6Am stoichiometry correlates well with transcription levels. Finally, Liu et al. reaffirmed that FTO mainly demethylates m6Am, not of mRNA but of snRNAs and snoRNAs.

Strengths:

This is a well-written manuscript that describes and validates a new m6Am-sequencing method: CROWN-seq as the first m6Am-sequencing method that can both quantify m6Am stoichiometry and profile m6Am at single-base resolution. These advantages facilitated Liu et al. to uncover new potential findings related to m6Am regulation and function. I am confident that CROWN-seq will likely be the gold standard for m6Am-sequencing henceforth.

Weaknesses:

Though the authors have uncovered a potentially new function for m6Am, they need to be clear that without identifying a mechanism, their data might only be demonstrating a correlation between the presence of m6Am and transcriptional regulation rather than causality.

Reviewer #3 (Public review):

Summary:

In this paper, Chang and Meliala et al. demonstrate that PEBP1 is a modulator of the ISR, specifically through the induction of mitochondrial stress. The authors utilize thermal proteome profiling (TPP) by which they identify PEPB1 as a thermally stabilized protein upon oligomycin treatment, indicating its role in mitochondrial stress. Moreover, RNA-sequencing analysis indicated that PEBP1 may be specifically modulating the mitochondrial stress-induced ISR, as PEBP1 knock-out reduces phosphorylation of eIF2α. They also show that PEBP1 function is independent of ER stress specifically tunicamycin treatment and loss of PEBP1 does affect mitochondrial ISR but in an OMA1, DELE1 independent manner. Thus, the authors hypothesized that PEBP1 interacts directly with eIF2α, functioning as a scaffolding protein. However, direct co-immunoprecipitation failed to demonstrate PEBP1 and eIF2α potential interaction. The authors then used a NanoBiT luminescence complementation assay to show the PEBP1-eIF2a interaction and its disruption by S51 phosphorylation.

Strengths:

Taken together, this work is novel, and the data presented suggests PEBP1 has a role as a modulator of the mitochondrial ISR, enhancing the signal to elicit the necessary response.

Weaknesses:

The one major issue of this work is the lack of a mechanism showing precisely how PEBP1 amplifies the mitochondrial integrated stress response. The work, as it is described, presents data suggesting PEBP1's role in the ISR but fails to present a more conclusive mechanism.

Reviewer #3 (Public Review):

This work addresses an important question aimed at understanding how membrane docking to the distal appendages is regulated during ciliogenesis. In this study, Tomoharu and colleagues identified interactions between CEP89 (important for RAB34-positive membrane localization to the mother centriole) and NCS1 and C3ORF14. Both these CEP89 interacting proteins were characterized as distal appendage localized proteins between CEP89 and RAB34 based on super-resolution microscopy. Ciliogenesis investigations using knockout cells indicated that NCS1 and CEP89 have similar impaired ciliation due to disruption in vesicle recruitment/RAB34 to the mother centriole, while C3ORF14 had less effect on ciliogenesis. The authors refer to the ciliogenesis requirement for CEP89/NCS1 as ciliary vesicles, which has been previously referred to as preciliary vesicle or distal appendage vesicles. NCS1 distal appendage localization was dependent on CEP89 and TTBK2, but it is not clear how TTBK2 affects NCS1. The authors subsequently performed double knockouts with NCS1 and other distal appendage proteins and showed stronger effects on mother centriole RAB34 levels, suggesting efficient membrane docking during ciliogenesis requires several distal appendage proteins. This is consistent with NCS1 knockout mice which do not display typical ciliopathy phenotypes. These mice do display obesity, which is associated with cilia dysfunction, and show reduced ciliary protein levels. As noted by the authors, the in vivo results for NCS1 knockouts could be affected by the mouse background which was not evaluated. The authors demonstrate the NCS1 myristoylation motif is required for RAB34 localization to the mother centrioles, providing a mechanistic explanation for how distal appendage proteins could interact with membranes during ciliogenesis. Overall the authors' findings support an important role for NCS1 in regulating ciliogenesis via myristoylation-dependent interaction with RAB34-positive membranes docked at the mother centriole.

Reviewer #3 (Public review):

The superfamily I 3'-5' DNA helicase Srs2 is well known for its role as an anti-recombinase, stripping Rad51 from ssDNA, as well as an anti-crossover factor, dissociating extended D-loops and favoring non-crossover outcome during recombination. In addition, Srs2 plays a key role in in ribonucleotide excision repair. Besides DNA repair defects, srs2 mutants also show a reduced recovery after DNA damage that is related to its role in downregulating the DNA damage signaling or checkpoint response. Recent work from the Zhao laboratory (PMID: 33602817) identified a role of Srs2 in downregulating the DNA damage signaling response by removing RPA from ssDNA. This manuscript reports further mechanistic insights into the signaling downregulation function of Srs2.

Using the genetic interaction with mutations in RPA1, mainly rfa1-zm2, the authors test a panel of mutations in Srs2 that affect CDK sites (srs2-7AV), potential Mec1 sites (srs2-2SA), known sumoylation sites (srs2-3KR), Rad51 binding (delta 875-902), PCNA interaction (delta 1159-1163), and SUMO interaction (srs2-SIMmut). All mutants were generated by genomic replacement and the expression level of the mutant proteins was found to be unchanged. This alleviates some concern about the use of deletion mutants compared to point mutations. Double mutant analysis identified that PCNA interaction and SUMO sites were required for the Srs2 checkpoint dampening function, at least in the context of the rfa1-zm2 mutant. There was no effect of this mutants in a RFA1 wild type background. This latter result is likely explained by the activity of the parallel pathway of checkpoint dampening mediated by Slx4, and genetic data with an Slx4 point mutation affecting Rtt107 interaction and checkpoint downregulation support this notion. Further analysis of Srs2 sumoylation showed that Srs2 sumoylation depended on PCNA interaction, suggesting sequential events of Srs2 recruitment by PCNA and subsequent sumoylation. Kinetic analysis showed that sumoylation peaks after maximal Mec1 induction by DNA damage (using the Top1 poison camptothecin (CPT)) and depended on Mec1. This data are consistent with a model that Mec1 hyperactivation is ultimately leading to signaling downregulation by Srs2 through Srs2 sumoylation. Mec1-S1964 phosphorylation, a marker for Mec1 hyperactivation and a site found to be needed for checkpoint downregulation after DSB induction, did not appear to be involved in checkpoint downregulation after CPT damage. The data are in support of the model that Mec1 hyperactivation when targeted to RPA-covered ssDNA by its Ddc2 (human ATRIP) targeting factor, favors Srs2 sumoylation after Srs2 recruitment to PCNA to disrupt the RPA-Ddc2-Mec1 signaling complex. Presumably, this allows gap filling and disappearance of long-lived ssDNA as the initiator of checkpoint signaling, although the study does not extend to this step.

Strengths<br /> (1) The manuscript focuses on the novel function of Srs2 to downregulate the DNA damage signaling response and provide new mechanistic insights.<br /> (2) The conclusions that PCNA interaction and ensuing Srs2-sumoylation are involved in checkpoint downregulation are well supported by the data.

Weaknesses<br /> (1) Additional mutants of interest could have been tested, such as the recently reported Pin mutant, srs2-Y775A (PMID: 38065943), and the Rad51 interaction point mutant, srs2-F891A (PMID: 31142613).<br /> (2) The use of deletion mutants for PCNA and RAD51 interaction is inferior to using specific point mutants, as done for the SUMO interaction and the sites for post-translational modifications.<br /> (3) Figure 4D and Figure 5A report data with standard deviations, which is unusual for n=2. Maybe the individual data points could be plotted with a color for each independent experiment to allow the reader to evaluate the reproducibility of the results.

Comments on revisions:

In this revision, the authors adequately addressed my concerns. The only issue I see remaining is the site of Srs2 action. The authors argue in favor of gaps and against R-loops and ssDNA resulting from excessive supercoiling. The authors do not discuss ssDNA resulting from processing of one-sided DSBs, which are expected to result from replication run-off after CPT damage but are not expected to provide the 3'-junction for preferred PCNA loading. Can the authors exclude PCNA at the 5'-junction at a resected DSB?

Reviewer #3 (Public Review):

Summary:

This study characterizes classical and nonclassical osteoblasts as both types were analyzed independently (integrated ATAC-seq and RNAseq). It was found that gene expression in classical and nonclassical osteoblasts is not regulated in the same way. In classical osteoblasts, Dlx family factors seem to play an important role, while Hox family factors are involved in the regulation of spinal ossification by nonclassical osteoblasts. In the second part of the study, the authors focus on the promoter structure of entpd5a. Through the identification of enhancers, they reveal complex modes of regulation of the gene. The authors suggest candidate transcription factors that likely act on the identified enhancer elements. All the results taken together provide comprehensive new insights into the process of bone development, and point to spatio-temporally regulated promoter/enhancer interactions taking place at the entpd5a locus.

Strengths:

The authors have succeeded in justifying a sound and consistent buildup of their experiments, and meaningfully integrating the results into the design of each of their follow-up experiments. The data are solid, insightfully presented, and the conclusion valid. This makes this manuscript of great value and interest to those studying (fundamental) skeletal biology.

Weaknesses:

The study is solidly constructed, the manuscript is clearly written and the discussion is meaningful - I see no real weaknesses.

Reviewer #4 (Public review):

Summary:

The manuscript by Graça et al. explores the role of MftG in the ethanol metabolism of mycobacteria. The authors hypothesise that MftG functions as a mycofactocin dehydrogenase, regenerating mycofactocin by shuttling electrons to the respiratory chain of mycobacteria. Although the study primarily uses M. smegmatis as a model microorganism, the findings have more general implications for understanding mycobacterial metabolism. Identifying the specific partner to which MftG transfers its electrons within the respiratory chain of mycobacteria would be an important next step, as pointed out by the authors.

Strengths

The authors have used a wide range of tools to support their hypothesis, including co-occurrence analyses, gene knockout and complementation experiments, as well as biochemical assays and transcriptomics studies.<br /> An interesting observation that the mftG deletion mutant grown on ethanol as the sole carbon source exhibited a growth defect resembling a starvation phenotype.<br /> MftG was shown to catalyse the electron transfer from mycofactocinol to components of the respiratory chain, highlighting the flexibility and complexity of mycobacterial redox metabolism.

The authors have taken on the majority of recommendations by the reviewers and made changes in the manuscript accordingly. I don't have any further suggestions.

Reviewer #3 (Public review):

Summary:

This is a valuable study providing solid evidence that the putative non-canonical initiation factor eIF2A has little or no role in the translation of any expressed mRNAs in cultured human (primarily HeLa) cells. Previous studies have implicated eIF2A in GTP-independent recruitment of initiator tRNA to the small (40S) ribosomal subunit, a function analogous to canonical initiation factor eIF2, and in supporting initiation on mRNAs that do not require scanning to select the AUG codon or that contain near-cognate start codons, especially upstream ORFs with non-AUG start codons, and may use the cognate elongator tRNA for initiation. Moreover, the detected functions for eIF2A were limited to, or enhanced by, stress conditions where canonical eIF2 is phosphorylated and inactivated, suggesting that eIF2A provides a back-up function for eIF2 in such stress conditions. CRISPR gene editing was used to construct two different knock-out cell lines that were compared to the parental cell line in a large battery of assays for bulk or gene-specific translation in both unstressed conditions and when cells were treated with inhibitors that induce eIF2 phosphorylation. None of these assays identified any effects of eIF2A KO on translation in unstressed or stressed cells, indicating little or no role for eIF2A as a back-up to eIF2 and in translation initiation at near-cognate start codons, in these cultured cells.

The study is very thorough and generally well executed, examining bulk translation by puromycin labeling and polysome analysis and translational efficiencies of all expressed mRNAs by ribosome profiling, with extensive utilization of reporters equipped with the 5'UTRs of many different native transcripts to follow up on the limited number of genes whose transcripts showed significant differences in translational efficiencies (TEs) in the profiling experiments. They also looked for differences in translation of uORFs in the profiling data and examined reporters of uORF-containing mRNAs known to be translationally regulated by their uORFs in response to stress, going so far as to monitor peptide production from a uORF itself. The high precision and reproducibility of the replicate measurements instil strong confidence that the myriad of negative results they obtained reflects the lack of eIF2A function in these cells rather than data that would be too noisy to detect small effects on the eIF2A mutations. They also tested and found no evidence for a recent claim that eIF2A localizes to the cytoplasm in stress and exerts a global inhibition of translation. Given the numerous papers that have been published reporting functions of eIF2A in specific and general translational control, this study is important in providing abundant, high-quality data to the contrary, at least in these cultured cells.

Strengths:

The paper employed two CRISPR knock-out cell lines and subjected them to a combination of high-quality ribosome profiling experiments, interrogating both main coding sequences and uORFs throughout the translatome, which was complemented by extensive reporter analysis, and cell imaging in cells both unstressed and subjected to conditions of eIF2 phosphorylation, all in an effort to test previous conclusions about eIF2A functioning as an alternative to eIF2.

Weaknesses:

There is some question about whether their induction of eIF2 phosphorylation using tunicamycin was extensive enough to state forcefully that eIF2A has little or no role in the translatome when eIF2 function is strongly impaired. Also, similar conclusions regarding the minimal role of eIF2A were reached previously for a different human cell line from a study that also enlisted ribosome profiling under conditions of extensive eIF2 phosphorylation; although that study lacked the extensive use of reporters to confirm or refute the identification by ribosome profiling of a small group of mRNAs regulated by eIF2A during stress.

Reviewer #3 (Public review):

Summary:

Mitochondrial injury activates eiF2α kinases-PERK, GCN2, HRI and PKR-which collectively regulate the Integrated Stress Response (ISR) to preserve mitochondrial function and integrity. Previous work has demonstrated that stress-induced and pharmacologic stress-independent ISR activation promotes adaptive mitochondrial elongation via the PERK and GCN2 kinases, respectively. Here, the authors demonstrate that pharmacologic ISR inducers of HRI and GCN2 enhance mitochondrial elongation and suppress mitochondrial fragmentation in two disease models, illustrating the therapeutic potential of pharmacologic ISR activators. Specifically, the authors first used an innovative ISR translational reporter to screen for nucleoside mimetic compounds that induce ISR signaling, and identified two compounds, 0357 and 3610, that preferentially activate HRI. Using a mitochondrial-targeted GFP MEF cell line, the authors next determined that these compounds (as well as the GCN2 activator, halofuginone) enhance mitochondrial elongation in an ISR-dependent manner. Moreover, pretreatment of MEFs with these ISR kinase activators suppressed pathological mitochondrial fragmentation caused by a calcium ionophore. Finally, pharmacologic HRI and GCN2 activation was found to preserve mitochondrial morphology in human fibroblasts expressing a pathologic variant in MFN2, a defect that leads to mitochondrial fragmentation and is a cause of Charcot Marie Tooth Type 2A disease.

Strengths:

This well-written manuscript has several notable strengths, including the demonstration of the potential therapeutic benefit of ISR modulation. New chemical entities with which to further interrogate this stress response pathway are also reported. In addition, the authors used an elegant screen to isolate compounds that selectively activate the ISR and identify which of the four kinases was responsible for activation. Special attention was also paid to a thorough evaluation of the effect of their compounds on other stress response pathways (i.e. the UPR, and heat and oxidative stress responses), thereby minimizing the potential for off-target effects. The implementation of automated image analysis rather than manual scoring to quantify mitochondrial elongation is not only practical but also adds to the scientific rigor, as does the complementary use of both the calcium ionophore and MFN2 models to enhance confidence and the broad therapeutic potential for pharmacology ISR manipulation.

Weaknesses:

The only minor concerns are with regard to effects on cell health and the timing of pharmacological administration.

Comments on revisions:

In this revised manuscript the authors demonstrate that pharmacological activation of the eiF2α kinases, HRI and GCN2, induce adaptive mitochondrial elongation and suppress mitochondrial fragmentation in two disease models, illustrating the translational potential of pharmacological ISR modulation.

In revising their manuscript the authors adequately addressed the concerns. In response to comments about the potential toxicity of their compounds, 0357 and 3610, the authors furnish evidence that neither compound significantly reduced viability of HEK293 cells (Figure S1G). Understandably, the authors focused the present work on the acute effects of their compounds. Several other attributes are noteworthy: First, that injury attributable to chronic ISR activation in cell culture may ultimately be circumvented by altering the in vivo pharmacodynamic and pharmacodynamic properties of the compounds, thereby preserving the translation potential for these (and related) compounds. Second, the authors also reasonably explain that the rapidity of ionomycin-induced injury, necessitating that the inducers are administered prior to treatment. Their assessment of the effects of the compounds on mitochondrial fragmentation in MFN2 mutant fibroblasts-in combination with the preserved viability of HEK293 cells-is sufficient to demonstrate the practical pharmacological potential for these (or related) agents.

Reviewer #3 (Public review):

Summary:

This study characterizes classical and nonclassical osteoblasts as both types were analyzed independently (integrated ATAC-seq and RNAseq). It was found that gene expression in classical and nonclassical osteoblasts is not regulated in the same way. In classical osteoblasts Dlx family factors seem to play an important role, while Hox family factors are involved in the regulation of spinal ossification by nonclassical osteoblasts. In the second part of the study, the authors focus on the promoter structure of entpd5a. Through the identification of enhancers they reveal complex modes of regulation of the gene. The authors suggest candidate transcription factors that likely act on the identified enhancer elements. All the results taken together provide comprehensive new insights into the process of bone development, and point to spatio-temporally regulated promoter/enhancer interactions taking place at the entpd5a locus.

Strengths:

The authors have succeeded in justifying a sound and consistent buildup of their experiments, and meaningfully integrate the results into the design of each of their follow-up experiments. The data are solid, insightfully presented, and the conclusion valid. This makes this manuscript of great value and interest to those studying (fundamental) skeletal biology.

Weaknesses:

The study is solidly constructed, the manuscript is clearly written and the discussion is meaningful - I see no real weaknesses.

Reviewer #3 (Public review):

Summary:

The relationships of proteins and lipids: it's complicated. This paper illustrates how cardiolipins can stabilize membrane protein subunits - and not surprisingly, positively charged residues play an important role here. But more and stronger binding of such structural lipids does not necessarily translate to stabilization of oligomeric states, since many proteins have alternative binding sites for lipids which may be intra- rather than intermolecular. Mutations which abolish primary binding sites can cause redistribution to (weaker) secondary sites which nevertheless stabilize interactions between subunits. This may be at first sight counterintuitive but actually matches expectations from structural data and MD modelling. An analogous cardiolipin binding site between subunits is found in E.coli tetrameric GlpG, with cardiolipin (thermally) stabilizing the protein against aggregation.

Strengths:

The use of the artificial scaffold allows testing of hypothesis about the different roles of cardiolipin binding. It reveals effects which are at first sight counterintuitive and are explained by the existence of a weaker, secondary binding site which unlike the primary one allows easy lipid-mediated interaction between two subunits of the protein. Introducing different mutations either changes the balance between primary and secondary binding sites or introduced a kink in a helix - thus affecting subunit interactions which are experimentally verified by native mass spectrometry.

Weaknesses:

The artificial scaffold is not necessarily reflecting the conformational dynamics and local flexibility of real, functional membrane proteins. The example of GlpG, while also showing interesting cardiolipin dependency, illustrates the case of a binding site across helices further but does not add much to the main story. It should be evident that structural lipids can be stabilizing in more than one way depending on how they bind, leading to different and possibly opposite functional outcomes.

Reviewer #3 (Public review):

Summary:

The authors investigated the role of secretory leukocyte protease inhibitors (SLPI) in developing Lyme disease in mice infected with Borrelia burgdorferi. Using a combination of histological, gene expression, and flow cytometry analyses, they demonstrated significantly higher bacterial burden and elevated neutrophil and macrophage infiltration in SLPI-deficient mouse ankle joints. Furthermore, they also showed direct interaction of SLPI with B. burgdorferi, which likely depletes the local environment of SLPI and causes excessive protease activity. These results overall suggest ankle tissue inflammation in B. burgdorferi-infected mice is driven by unchecked protease activity.

Strengths:

Utilizing a comprehensive suite of techniques, this is the first study showing the importance of anti-protease-protease balance in the development of periarticular joint inflammation in Lyme disease.

Weaknesses:

Due to the limited sample availability, the authors investigated the serum level of SLPI in both in Lyme arthritis patients and patients with earlier disease manifestations.

Reviewer #3 (Public review):

Summary:

In this report, De Franceschi et al. purify components of the Cdv machinery in archaeon M. sedula and probe their interactions with membrane and with one-another in vitro using two main assays - liposome flotation and fluorescent imaging of encapsulated proteins. This has the potential to add to the field by showing how the order of protein recruitment seen in cells is related to the differential capacity of individual proteins to bind membranes when alone or when combined.

Strengths:

Using the floatation assay, they demonstrate that CdvA and CdvB bind liposomes when combined. While CdvB1 also binds liposomes under these conditions, in the floatation assay, CdvB2 lacking its C-terminus is not efficiently recruited to membranes unless CdvAB or CdvB1 are present. The authors then employ a clever liposome assay that generates chained spherical liposomes connected by thin membrane necks, which allows them to accurately control the buffer composition inside and outside of the liposome. With this, they show that all four proteins accumulate in necks of dumbbell-shaped liposomes that mimic the shape of constricting necks in cell division. Taken altogether, these data lead them to propose that Cdv proteins are sequentially recruited to the membrane as has also been suggested by in vivo studies of ESCRT-III dependent cell division in crenarchaea.

Weaknesses:

These experiments provide a good starting point for the in vitro study the interaction of Cdv system components with the membrane and their consecutive recruitment. However, several experimental controls are missing that complicate their ability to draw strong conclusions. Moreover, some results are inconsistent across the two main assays which make the findings difficult to interpret.

(1) Missing controls.

Various protein mixtures are assessed for their membrane-binding properties in different ways. However, it is difficult to interpret the effect of any specific protein combination, when the same experiment is not presented in a way that includes separate tests for all individual components. In this sense, the paper lacks important controls.

For example, Fig 1C is missing the CdvB-only control. The authors remark that CdvB did not polymerise (data not shown) but do not comment on whether it binds membrane in their assays. In the introduction, Samson et al., 2011 is cited as a reference to show that CdvB does not bind membrane. However, here the authors are working with protein from a different organism in a different buffer, using a different membrane composition and a different assay. Given that so many variables are changing, it would be good to present how M. sedula CdvB behaves under these conditions.

Similarly, there is no data showing how CdvB alone or CdvA alone behave in the dumbbell liposome assay. Without these controls, it's impossible to say whether CdvA recruits CdvB or the other way around.

The manuscript would be much stronger if such data could be added.

(2) Some of the discrepancies in the data generated using different assays are not discussed.

The authors show that CdvB2∆C binds membrane and localizes to membrane necks in the dumbbell liposome assay, but no membrane binding is detected in the flotation assay. The discrepancy between these results further highlights the need for CdvB-only and CdvA-only controls.

(3) Validation of the liposome assay.

The experimental setup to create dumbbell-shaped liposomes seems great and is a clever novel approach pioneered by the team. Not only can the authors manipulate liposome shape, they also state that this allows them to accurately control the species present on the inside and outside of the liposome. Interpreting the results of the liposome assay, however, depends on the geometry being correct. To make this clearer, it would seem important to include controls to prove that all the protein imaged at membrane necks lie on the inside of liposomes. In the images in SFig3 there appears to be protein outside of the liposome. It would also be helpful to present data to show test whether the necks are open, as suggested in the paper, by using FRAP or some other related technique.

(4) Quantification of results from the liposome assay.

The paper would be strengthened by the inclusion of more quantitative data relating to the liposome assay. Firstly, only a single field of view is shown for each condition. Because of this, the reader cannot know whether this is a representative image, or an outlier? Can the authors do some quantification of the data to demonstrate this? The line scan profiles in the supplemental figures would be an example of this, but again in these Figures only a single image is analyzed.

We would recommend that the authors present quantitative data to show the extent of co-localization at the necks in each case. They also need a metric to report instances in which protein is not seen at the neck, e.g. CdvB2 but not CdvB1 in Fig2I, which rules out a simple curvature preference for CdvB2 as stated in line 182.

Secondly, the authors state that they see CdvB2∆C recruited to the membrane by CdvB1 (lines 184-187, Fig 2I). However, this simple conclusion is not borne out in the data. Inspecting the CdvB2∆C panels of Fig 2I, Fig3C, and Fig3D, CdvB2∆C signal can be seen at positions which don't colocalize with other proteins. The authors also observe CdvB2∆C localizing to membrane necks by itself (Fig 2E). Therefore, while CdvB1 and CdvB2∆C colocalize in the flotation assay, there is no strong evidence for CdvB2∆C recruitment by CdvB1 in dumbbells. This is further underscored by the observation that in the presented data, all Cdv proteins always appear to localize at dumbbell necks, irrespective of what other components are present inside the liposome. Although one nice control is presented (ZipA), this suggests that more work is required to be sure that the proteins are behaving properly in this assay. For example, if membrane binding surfaces of Cdv proteins are mutated, does this lead to the accumulation of proteins in the bulk of the liposome as expected?

(5) Rings.

The authors should comment on why they never observe large Cdv rings in their experiments. In crenarchaeal cell division, CdvA and CdvB have been observed to form large rings in the middle of the 1 micron cell, before constriction. Only in the later stages of division are the ESCRTs localized to the constricting neck, at a time when CdvA is no longer present in the ring. Therefore, if the in vitro assay used by the authors really recapitulated the biology, one would expect to see large CdvAB rings in Figs 1EF. This is ignored in the model. In the proposed model of ring assembly (line 252), CdvAB ring formation is mentioned, but authors do not discuss the fact that they do not observe CdvAB rings - only foci at membrane necks. The discussion section would benefit from the authors commenting on this.

(6) Stoichiometry

It is not clear why 100% of the visible CdvA and 100% of the the visible CdvB are shifted to the lipid fraction in 1C. Perhaps this is a matter of quantification. Can the authors comment on the stoichiometry here?

(7) Significance of quantification of MBP-tagged filaments.

Authors use tagging and removal of MBP as a convenient, controllable system to trigger polymerisation of various Cdv proteins. However, it is unclear what is the value and significance of reporting the width and length of the short linear filaments that are formed by the MBP-tagged proteins. Presumably they are artefactual assemblies generated by the presence of the tag? Similar Figure 2C doesn't seem a useful addition to the paper.

Reviewer #3 (Public review):

Summary:<br /> In this paper, Xu, Dantu and coworkers report a protocol for analyzing coevolutionary and dynamical information to identify a subset of communities that capture functionally relevant sites in beta-lactamases.

Strengths:<br /> The combination of coevolutionary information and metrics from MD simulations is interesting for capturing functionally relevant sites, which can have implications in the fields of drug discovery but also in protein design.

Weaknesses:<br /> The combination of coevolutionary information and metrics from MD simulations is not new as other protocols have been proposed along the years (the current version of the paper neglects some of them, see below), and there are a few parameters of the protocol that, in my opinion, should be better analyzed and discussed.

(1) As mentioned, the introduction of the paper lacks some important publications in the field of using graph theory to represent important interaction networks extracted from MD simulations (DOI: 10.1002/pro.4911), and also combining MD data with MSA to identify functionally relevant sites for enzyme design (doi: 10.1021/acscatal.4c04587, 10.1093/protein/gzae005).<br /> (2) The matrix used to apply graph theory (J_ij) is built from summing the scaled coevolution and degree of correlation values. The alpha and beta weights are defined, and the authors mention that alpha is set to 0.5, thus beta as well to fulfil with the alpha + beta = 1. Why a value of 0.5 has been selected? How this affects the overall results and conclusions extracted? The finding that many catalytically relevant residues are identified in the communities is not surprising given that such sites usually present a high conservation score.<br /> (3) Another important point that needs further explanation is the selection of the relevant descriptor of protein dynamics. In this study two different strategies have been used (one more global the other more local), but more details should be provided regarding their choice. What is the best strategy according to the authors? Why not using the same strategy for both related systems? The obtained results using one methodology or the other will have a large impact on the dynamical score. Another related point is: what is the impact of the MD simulation length, how the MSA is generated and number of sequences used for MSA construction?

Reviewer #3 (Public review):

Summary:

Fibroblast growth factor receptor 2 (FGFR2) is a receptor tyrosine kinase that can be amplified in gastric cancer and serves as a potential therapeutic target for this patient population. However, targeting FGFR2 has shown limited efficacy. Thus, this study seeks to identify additional molecules that can be effectively targeted in FGFR2 amplified gastric cancer, with a focus on Src homology region 2-containing protein tyrosine phosphatase 2 (SHP2). The authors first demonstrate that 6% of gastric cancer patients in a cohort of human patient samples exhibit FGFR2 amplification. Furthermore, they demonstrate that FGFR2 mRNA expression is positively correlated with PTPN11 gene expression (which is the gene that encodes the SHP2 protein). Using human gastric cancer cell lines with amplified FGFR2, the authors then test the effects of combining the FGFR inhibitor AZD4547 with the SHP2 inhibitor SHP099 on tumor cell death and signaling molecules. They demonstrate that combining the two inhibitors is more effective at tumor cell killing and reducing activation of downstream signaling pathways than either inhibitor alone. In further studies, the authors obtained gastric cancer cells with FGFR2 amplification from a patient that was treated with FGFR2 inhibitor. While this patient initially showed a partial response, the patient ultimately progressed, demonstrating resistance to FGFR2 inhibition. Following isolation of tumor cells from the patient's ascites, the authors demonstrate that these cells are sensitive to the combination treatment of AZD4547 and SHP099. Further studies were performed using a xenograft model using athymic nude mice in which the combination of SHP099 and AZD4547 were found to reduce tumor growth more significantly than either treatment alone. Finally, the authors demonstrate using an in vitro culture model that this combination treatment enhances T cell mediated cytotoxicity. The authors conclude that targeting FGFR2 and SHP2 represents a potential combination strategy in gastric patients with FGFR2 amplification.

Strengths:

The authors demonstrate that FGFR2 amplification positively correlates with PTPN11 in human gastric cancer samples, providing rationale for combination therapies. Furthermore, convincing data are provided demonstrating that targeting both FGFR and SHP2 is more effective than targeting either pathway alone using in vitro and in vivo models. The use of cells derived from a gastric cancer patient that progressed following treatment with an FGFR inhibitor is also a strength. The findings from this study support the conclusion that SHP2 inhibitors enhance the efficacy of FGFR-targeted therapies in cancer patients. This study also suggests that targeting SHP2 may also be an effective strategy for targeting cancers that are resistant to FGFR-targeted therapies.

Weaknesses:

The main caveat with these studies is the lack of an immune competent model with which to test the finding that this combination therapy enhances T cell cytotoxicity in vivo. Discussing this limitation within the context of these findings and future directions for this work, particularly since the combination therapy appears to work quite well without the presence of T cells in the environment, would be beneficial.

Reviewer #3 (Public review):

Xiaoyu Wu and colleagues examined the potential role in sleep of a Drosophila ribosomal RNA methyltransferase, mettl5. Based on sleep defects reported in CRISPR generated mutants, the authors performed both RNA-seq and Ribo-seq analyses of head tissue from mutants and compared to control animals collected at the same time point. While these data were subjected to a thorough analysis, it was difficult to understand the relative direction of differential expression between the two genotypes. In any case, a major conclusion was that the mutant showed altered expression of circadian clock genes, and that the altered expression of the period gene in particular accounted for the sleep defect reported in the mettl5 mutant. As noted above, a strength of this work is its relevance to a human developmental disorder as well as the transcriptomic and ribosomal profiling of the mutant. However, there are numerous weaknesses in the manuscript, most of which stem from misinterpretation of the findings, some methodological approaches, and also a lack of method detail provided. The authors seemed to have missed a major phenotype associated with the mettl5 mutant, which is that it caused a significant increase in period length, which was apparent even in a light: dark cycle. Thus the effect of the mutant on clock gene expression more likely contributed to this phenotype than any associated with changes in sleep behavior.

Reviewer #3 (Public review):

Summary:

The authors describe important new biochemical elements in the synthesis of a class of critical developmental signaling molecules, BMP4. They also present a highly detailed description of developmental anomalies in mice bearing known human mutations at these specific elements.

Strengths:

Exceptionally detailed descriptions of pathologies occurring in mutant mice. Novel findings regarding the interaction of propeptide phosphorylation and convertase cleavage, both of which will move the field forward. Provocative hypothesis regarding furin access to cleavage sites, supported by Alphafold predictions.

Weaknesses:

Figure 6A presents two testable models for pre-release access of furin to cleavage sites since physical separation of enzyme from substrate only occurs in one model; could immunocytochemistry resolve?

Reviewer #3 (Public review):

Summary:

In this report, the authors tested how manipulating the contiguous set of stimuli on the screen that should be used to guide behavior - that is, the scope of visual spatial attention - impacts the magnitude and profile of well-established attentional enhancements in visual retinotopic cortex. During fMRI scanning, participants attended to a cued section of the screen for blocks of trials and performed a letter vs digit discrimination task at each attended location (and judged whether the majority of characters were letters/digits). Importantly, the visual stimulus was identical across attention conditions, so any observed response modulations are due to top-down task demands rather than visual input. The authors employ population receptive field (pRF) models, which are used to sort voxel activation with respect to the location and scope of spatial attention and fit a Gaussian-like function to the profile of attentional enhancement from each region and condition. The authors find that attending to a broader region of space expands the profile of attentional enhancement across the cortex (with a larger effect in higher visual areas), but does not strongly impact the magnitude of this enhancement, such that each attended stimulus is enhanced to a similar degree. Interestingly, these modulations, overall, mimic changes in response properties caused by changes to the stimulus itself (increase in contrast matching the attended location in the primary experiment). The finding that attentional enhancement primarily broadens, but does not substantially weaken in most regions, is an important addition to our understanding of the impact of distributed attention on neural responses, and will provide meaningful constraints to neural models of attentional enhancement.

Strengths:

- Well-designed manipulations (changing location and scope of spatial attention), and careful retinotopic/pRF mapping, allow for a robust assay of the spatial profile of attentional enhancement, which has not been carefully measured in previous studies<br /> - Results are overall clear, especially concerning width of the spatial region of attentional enhancement, and lack of clear and consistent evidence for reduction in the amplitude of enhancement profile<br /> - Model-fitting to characterize spatial scope of enhancement improves interpretability of findings

Weaknesses:

- Task difficulty seems to vary as a function of spatial scope of attention, with varying ratios of letters/digits across spatial scope conditions, which may complicate interpretations of neural modulation results<br /> - Some aspects of analysis/data sorting are unclear (e.g., how are voxels selected for analyses?)<br /> - While the focus of this report is on modulations of visual cortex responses due to attention, the lack of inclusion of results from other retinotopic areas (e.g. V3AB, hV4, IPS regions like IPS0/1) is a weakness<br /> - Additional analyses comparing model fits across amounts of data analyzed suggest the model fitting procedure is biased, with some parameters (e.g., FWHM, error, gain) scaling with noise.

Reviewer #3 (Public review):

Summary:

This manuscript describes the characterization of mycobacterial cytoskeleton protein Wag31, examining its role in orchestrating protein-lipid and protein-protein interactions essential for mycobacterial survival. The most significant finding is that Wag31, which directs polar elongation and maintains the intracellular membrane domain, was revealed to have membrane tethering capabilities.

Strengths:

The authors provided a detailed analysis of Wag31 domain architecture, revealing distinct functional roles: the N-terminal domain facilitates lipid binding and membrane tethering, while the C-terminal domain mediates protein-protein interactions. Overall, this study offers a robust and new understanding of Wag31 function.

Weaknesses:

The following major concerns should be addressed.

• Authors use 10-N-Nonyl-acridine orange (NAO) as a marker for cardiolipin localization. However, given that NAO is known to bind to various anionic phospholipids, how do the authors know that what they are seeing is specifically visualizing cardiolipin and not a different anionic phospholipid? For example, phosphatidylinositol is another abundant anionic phospholipid in mycobacterial plasma membrane.

• Authors' data show that the N-terminal region of Wag31 is important for membrane tethering. The authors' data also show that the N-terminal region is important for sustaining mycobacterial morphology. However, the authors' statement in Line 256 "These results highlight the importance of tethering for sustaining mycobacterial morphology and survival" requires additional proof. It remains possible that the N-terminal region has another unknown activity, and this yet-unknown activity rather than the membrane tethering activity drives the morphological maintenance. Similarly, the N-terminal region is important for lipid homeostasis, but the statement in Line 270, "the maintenance of lipid homeostasis by Wag31 is a consequence of its tethering activity" requires additional proof. The authors should tone down these overstatements, or provide additional data to support their claims.

• Authors suggest that Wag31 acts as a scaffold for the IMD (Fig. 8). However, Meniche et. al. has shown that MurG as well as GlfT2, two well-characterized IMD proteins, do not colocalize with Wag31 (DivIVA) (https://doi.org/10.1073/pnas.1402158111). IMD proteins are always slightly subpolar while Wag31 is located to the tip of the cell. Therefore, the authors' biochemical data cannot be easily reconciled with microscopic observations in the literature. This raises a question regarding the validity of protein-protein interaction shown in Figure 7. Since this pull-down assay was conducted by mixing E. coli lysate expressing Wag31 and Msm lysate expression Wag31 interactors like MurG, it is possible that the interactions are not direct. Authors should interpret their data more cautiously. If authors cannot provide additional data and sufficient justifications, they should avoid proposing a confusing model like Figure 8 that contradicts published observations.

Reviewer #3 (Public review):

Summary:

In their manuscript titled "Multiplexed Assays of Human Disease‐relevant Mutations Reveal UTR Dinucleotide Composition as a Major Determinant of RNA Stability" the authors aim to investigate the effect of sequence variations in 3'UTR and 5'UTRs on the stability of mRNAs in two different human cell lines.

To do so, the authors use a massively parallel reporter assay (MPRA). They transfect cells with a set of mRNA reporters that contain sequence variants in their 3' or 5' UTRs, which were previously reported in human diseases. They follow their clearance from cells over time relative to the matching non-variant sequence. To analyze their results, they define a set of factors (RBP and miRNA binding sites, sequence features, secondary structure etc.) and test their association with differences in mRNA stability. For features with a significant association, they use clustering to select a subset of factors for LASSO regression and identify factors that affect mRNA stability.<br /> They conclude that the TA dinucleotide content of UTRs is the strongest destabilizing sequence feature. Within that context, elevated GC content and protein binding can protect susceptible mRNAs from degradation. They also show that TA dinucleotide content of UTRs affects native mRNA stability and that it is associated with specific functional groups. Finally, they link disease associated sequence variants with differences in mRNA stability of reporters.

Strengths:

(1) This work introduces a different MPRA approach to analyze the effect of genetic variants. While previous works in tissue culture use DNA transfections that require normalization for transcription efficiency, here the mRNA is directly introduced into cells at fixed amounts, allowing a more direct view of the mRNA regulation.

(2) The authors also introduce a unique analysis approach, which takes into account multiple factors that might affect mRNA stability. This approach allows them to identify general sequence features that affect mRNA stability beyond specific genetic variants, and reach important insights on mRNA stability regulation. Indeed, while the conclusions to genetic variants identified in this work are interesting, the main strength of the work involves general effect of sequence features rather than specific variants.

(3) The authors provide adequate support for their claims and validate their analysis using both their reporter data and native genes. For the main feature identified, TA di-nucleotides, they perform follow-up experiments with modified reporters that further strengthen their claims, and also validate the effect on native cellular transcripts (beyond reporters), demonstrating its validity also within native scenarios.

(4) The work provides a broad analysis of mRNA stability, across two mRNA regulatory segments (3'UTR and 5'UTR) and is performed in two separate cell-types. Comparison between two different cell-types is adequate, and the results demonstrate, as expected, the dependence of mRNA stability on the cellular context. Analysis of 3'UTR and 5'UTR regulatory effects also shows interesting differences and similarities between these two regulatory regions.

Weaknesses:

In their revised manuscripts, the authors successfully address many of the weaknesses raised in the original review, including the effect of possible confounding effects, and additional methodology details. Notably, two of the issues raised in the original report, have only been partially addressed in the revision.

(1) The analysis and regression models built in this work are not thoroughly investigated relative to native genes within cells.<br /> While using MPRAs indeed allows to isolate regulatory effects that are less influential in-vivo, the resulting effects still provide some regulatory function in-vivo. The goal of such an analysis would not be to demonstrate the predictive power of the models, or to make any claims regarding using these models to fully explain or predict the stability of native transcripts. Clearly, additional more prominent factors could function in controlling endogenous RNA stability.<br /> Instead, the goal of such an investigation is to simply assess the fraction of in-vivo regulation that the factors identified in this work contribute in native contexts, and what is the relative contribution of the phenomena captured by the well-controlled MPRA study.<br /> This reviewer believes that even if the effects identified by the current MPRA study only contribute a small fraction of in-vivo variation, an analysis that aim to estimate what this fraction is, will be very relevant to this study for several reasons. First, in order to appreciate the results of this study within their in-vivo context. Second, in light of the questions raised as motivation for this study, and particularly the need to identify the effect of disease-associated 3'UTR variants, which clearly have an in-vivo effect.

(2) Methodology validation can be performed with simulated data (generated in-silico by the authors) to provide an independent support for the ability of the current methodology to correctly extract regulatory effects from the data.

Reviewer #3 (Public review):

Summary:

Li et al. describe an audiovisual temporal recalibration experiment in which participants perform baseline sessions of ternary order judgments about audiovisual stimulus pairs with various stimulus-onset asynchronies (SOAs). These are followed by adaptation at several adapting SOAs (each on a different day), followed by post-adaptation sessions to assess changes in psychometric functions. The key novelty is the formal specification and application/fit of a causal-inference model for the perception of relative timing, providing simulated predictions for the complete set of psychometric functions both pre and post adaptation.

Strengths:

(1) Formal models are preferable to vague theoretical statements about a process, and prior to this work, certain accounts of temporal recalibration (specifically those that do not rely on a population code) had only qualitative theoretical statements to explain how/why the magnitude of recalibration changes non-linearly with the stimulus-onset asynchrony of the adaptor.<br /> (2) The experiment is appropriate, the methods are well described, and the average model prediction is a good match to the average data (Figure 4). Conclusions are supported by the data and modelling.<br /> (3) The work should be impactful. There seems a good chance that this will become the go-to modelling framework for those exploring non population-code accounts of temporal recalibration (or comparing them with population-code accounts).<br /> (4) Key issues for the generality of the model, such as recalibration asymmetries reported by other authors that are inconsistent with those reported here, are thoughtfully discussed.

Weaknesses:

(1) Models are not compared using a gold-standard measure such as leave-one-out cross validation. However, this is legitimate given lengthy model fitting times, and a sensible approximation is presented.<br /> (2) The model misses in a systematic way for the psychometric functions of some participants/conditions. In addition to misses relating to occasional failures to estimate the magnitude of recalibration, some of the misses are because all functions are only permitted to shift in central tendency (whereas some participants show changes better characterized at one or both decision criteria). Given the fact that the modelling in general embraces individual differences, it might have been worth allowing different kinds of change for different participants. However, this is not really critical for the central concern (changes in the magnitude of recalibration for different adaptors) and there is a limit to how much can be done along these lines without making the model too flexible to test.<br /> (3) As a minor point, the model relies on simulation, which may limit its take-up/application by others in the field (although open access code will be provided).

Reviewer #3 (Public review):

Summary:

In this manuscript, Bimbard and colleagues describe a new implant apparatus called "Apollo Implant", which should facilitate recording in freely moving rodents (both mice and rats) using Neuropixels probes. The authors collected data from both mice and rats, they used 3 different versions of Neuropixels, multiple labs have already adopted this method, which is impressive. They openly share their CAD designs and surgery protocol to further facilitate the adaptation of their method.

Strengths:

Overall, the "Apollo Implant" is easy to use and adapt, as it has been used in other laboratories successfully and custom modifications are already available. The device is reproducible using common 3D printing services and can be easily modified thanks to its CAD design (the video explaining this is extremely helpful). The weight and price are amazing compared to other systems for rigid silicon probes allowing a wide range of use of the "Apollo Implant".

Weaknesses:

The "Apollo Implant" can only handle Neuropixels probes. It cannot hold other widely used and commercially available silicon probes. Certain angles and distances may be better served by 2 implants.

Reviewer #3 (Public review):

Summary:

This study is focused on testing whether statistical learning (a mechanism for parsing the speech signal into smaller chunks) preferentially operates over certain features of the speech at birth in humans. The features under investigation are phonetic content and speaker identity. Newborns are tested in an EEG paradigm in which they are exposed to a long stream of syllables. In Experiment 1, newborns are familiarized with a sound stream that comprises regularities (transitional probabilities) over syllables (e.g., "pe" followed by "tu" in "petu" with 1.0 probability) while the voices uttering the syllables remain random. In Experiment 2, newborns are familiarized with the same sound stream but, this time, the regularities are built over voices (e.g., "green voice" followed by "red voice" with 1.0 probability) while the concatenation of syllables stays random. At the test, all newborns listened to duplets (individual chunks) that either matched or violated the structure of the familiarization. In both experiments, newborns showed neural entrainment to the regularities implemented in the stream, but only the duplets defined by transitional probabilities over syllables (aka word forms) elicited a N400 ERP component. These results suggest that statistical learning operates in parallel and independently on different dimensions of the speech already at birth and that there seems to be an advantage for processing statistics defining word forms rather than voice patterns.

Strengths:

This paper presents an original experimental design that combines two types of statistical regularities in a speech input. The design is robust and appropriate for EEG with newborns. I appreciated the clarity of the Methods section. There is also a behavioral experiment with adults that acts like a control study for newborns. The research question is interesting, and the results add new information about how statistical learning works at the beginning of postnatal life, and on which features of the speech. The figures are clear and helpful in understanding the methods, especially the stimuli and how the regularities were implemented.

Weaknesses:

I appreciated how the authors addressed my previous comments and concerns. I am satisfied with the changes made by the authors. I believe the paper reads much better. Also, the adjustment to the theoretical framework suits well.

Reviewer #3 (Public Review):

Distal appendages are multiprotein complexes that are only present on the mother centriole as a 9-fold symmetric structure that functions in ciliogenesis. How distal appendage proteins are organized and assembled still remains poorly understood. In this manuscript, Kanie et al. comprehensively analyzed the localizations of known and newly described distal appendage proteins using super-resolution microscopy. They investigated mechanisms associated with distal appendage assembly and their roles in the early stages of ciliogenesis in CRISPR-Cas9 knockout cells, which enabled a clearer investigation of these structures compared to previous RNAi depletion studies. These studies confirm previous findings for distal appendage protein ciliogenesis function and demonstrate the CEP83-SCLT1-CEP164-TTBK2 module is critical for both distal appendage assembly and the initiation of ciliogenesis. Notably, they find that CEP89 is dispensable for distal appendage assembly, but is needed for the recruitment of RAB34-positive ciliary vesicles to the mother centriole for ciliogenesis. Finally, this work introduces the application of single-molecule 3D super-resolution microscopy as a tool for interrogating the relationship between membranes and distal appendages. Overall this work extends our fundamental understanding of distal appendage structure/function in ciliogenesis.

An interesting observation from this work is that CEP83 is found localized both at the innermost region and the outermost region of the distal appendages when detected by antibodies that recognize a different epitope of CEP83 (Figure 1A), suggesting a helical structure that could serve as a platform for distal appendage assembly. A previous study using STORM imaging also showed that another distal appendage protein CEP164 occupies a wider region of the distal appendages when using an antibody recognizing the N-terminal residues of Cep164 (M Bowler et al. 2019). Together these studies show the importance of evaluating the structure of distal appendage proteins and the challenges of using antibody detection to reveal distal appendage hierarchy.

This work also highlights the potential differences in functional conclusions that can be drawn when comparing RNAi and CRISPR knockout depletion approaches. The latter which expectedly can lead to a more precise functional analysis of these small distal appendage structures, albeit with the potential for knockout cells to display compensatory regulation. Although not directly addressed in the text, the authors find that RPE-1 MYO5A knockout cells could ciliate which differs from a report by Wu et al. (2018). Furthermore, in the case of RAB34 knockout cells, the authors find CP110 removal from the mother centriole, while in previously published RAB34 KO studies this was not observed. In the case of the. RAB34 data a plausible explanation for the results given by the authors is that different assay conditions were used as was noted by the authors.

Reviewer #3 (Public review):

Summary:

The authors show that ELS induces a number of brain and behavioral changes in the adult lateral amygdala. These changes include enduring astrocytic dysfunction, and inducing astrocytic dysfunction via genetic interventions is sufficient to phenocopy the behavioral and neural phenotypes suggesting astrocyte dysfunction may play a causal role in ELS-associated pathologies.

Strengths:

A strength is the shift in focus to astrocytes to understand how ELS alters adult behavior.

Weaknesses:

The mechanistic links between some of the correlates - altered astrocytic function, changes in neural excitability and synaptic plasticity in the lateral amygdala and behavior - are underdeveloped.

Comments on revisions:

The authors have significantly improved the paper with the addition of new experimental data, analyses, and textual changes.

Reviewer #3 (Public review):

Summary:

The paper studies learning rules in a simple sigmoidal recurrent neural network setting. The recurrent network has a single layer of 10 to 40 units. It is first confirmed that feedback alignment (FA) can learn a value function in this setting. Then so-called bio-plausible constraints are added: (1) when value weights (readout) is non-negative, (2) when the activity is non-negative (normal sigmoid rather than downscaled between -0.5 and 0.5), (3) when the feedback weights are non-negative, (4) when the learning rule is revised to be monotic: the weights are not downregulated. In the simple task considered all four biological features do not appear to impair totally the learning.

Strengths:

(1) The learning rules are implemented in a low-level fashion of the form: (pre-synaptic-activity) x (post-synaptic-activity) x feedback x RPE. Which is therefore interpretable in terms of measurable quantities in the wet-lab.

(2) I find that non-negative FA (FA with non negative c and w) is the most valuable theoretical insight of this paper: I understand why the alignment between w and c is automatically better at initialization.

(3) The task choice is relevant since it connects with experimental settings of reward conditioning with possible plasticity measurements.

Weaknesses:

(4) The task is rather easy, so it's not clear that it really captures the computational gap that exists with FA (gradient-like learning) and simpler learning rule like a delta rule: RPE x (pre-synpatic) x (post-synaptic). To control if the task is not too trivial, I suggest adding a control where the vector c is constant c_i=1.

(5) Related to point 3), the main strength of this paper is to draw potential connection with experimental data. It would be good to highlight more concretely the prediction of the theory for experimental findings. (Ideally, what should be observed with non-negative FA that is not expected with FA or a delta rule (constant global feedback) ?).

(6a) Random feedback with RNN in RL have been studied in the past, so it is maybe worth giving some insights how the results and the analyzes compare to this previous line of work (for instance in this paper [1]). For instance, I am not very surprised that FA also works for value prediction with TD error. It is also expected from the literature that the RL + RNN + FA setting would scale to tasks that are more complex than the conditioning problem proposed here, so is there a more specific take-home message about non-negative FA? or benefits from this simpler toy task?<br /> (6b) Related to task complexity, it is not clear to me if non-negative value and feedback weights would generally scale to harder tasks. If the task in so simple that a global RPE signal is sufficient to learn (see 4 and 5), then it could be good to extend the task to find a substantial gap between: global RPE, non-negative FA, FA, BP. For a well chosen task, I expect to see a performance gap between any pair of these four learning rules. In the context of the present paper, this would be particularly interesting to study the failure mode of non-negative FA and the cases where it does perform as well as FA.

(7) I find that the writing could be improved, it mostly feels more technical and difficult than it should. Here are some recommendations:<br /> (7a) for instance the technical description of the task (CSC) is not fully described and requires background knowledge from other paper which is not desirable.<br /> (7b) Also the rationale for the added difficulty with the stochastic reward and new state is not well explained.<br /> (7c) In the technical description of the results I find that the text dives into descriptive comments of the figures but high-level take home messages would be helpful to guide the reader. I got a bit lost, although I feel that there is probably a lot of depth in these paragraphs.

(8) Related to the writing issue and 5), I wished that "bio-plausibility" was not the only reason to study positive feedback and value weights. Is it possible to develop a bit more specifically what and why this positivity is interesting? Is there an expected finding with non-negative FA both in the model capability? or maybe there is a simpler and crisp take-home message to communicate the experimental predictions to the community would be useful?

(1) https://www.nature.com/articles/s41467-020-17236-y

Reviewer #3 (Public review):

Summary:

This study reveals that sound exposure enhances drug delivery to the cochlea through the non-selective action of outer hair cells. The efficiency of sound-facilitated drug delivery is reduced when outer hair cell motility is inhibited. Additionally, low-frequency tones were found to be more effective than broadband noise for targeting substances to the cochlear apex. Computational model simulations support these findings.

Strengths:

The study provides compelling evidence that the broad action of outer hair cells is crucial for cochlear fluid circulation, offering a novel perspective on their function beyond frequency-selective amplification. Furthermore, these results could offer potential strategies for targeting and optimizing drug delivery throughout the cochlear spiral.

Reviewer #3 (Public review):

Summary:

The article provides the most comprehensive overview of primate MHC class I and class II genes to date, combining published data with an exploration of the available genome assemblies in a coherent phylogenetic framework and formulating new hypotheses about the evolution of the primate MHC genomic region.

Strengths:

I think this is a solid piece of work that will be the reference for years to come, at least until population-scale haplotype-resolved whole-genome resequencing of any mammalian species becomes standard. The work is timely because there is an obvious need to move beyond short amplicon-based polymorphism surveys and classical comparative genomic studies. The paper is data-rich and the approach taken by the authors, i.e. an integrative phylogeny of all MHC genes within a given class across species and the inclusion of often ignored pseudogenes, makes a lot of sense. The focus on primates is a good idea because of the wealth of genomic and, in some cases, functional data, and the relatively densely populated phylogenetic tree facilitates the reconstruction of rapid evolutionary events, providing insights into the mechanisms of MHC evolution. Appendices 1-2 may seem unusual at first glance, but I found them helpful in distilling the information that the authors consider essential, thus reducing the need for the reader to wade through a vast amount of literature. Appendix 3 is an extremely valuable companion in navigating the maze of primate MHC genes and associated terminology.

Weaknesses:

I have not identified major weaknesses and my comments are mostly requests for clarification and justification of some methodological choices.

Reviewer #3 (Public review):

Summary:

In this paper, Alonso-Caraballo et al. investigate sex-specific differences in oxycodone self-administration, withdrawal, and relapse behaviors in rats, as well as associated synaptic plasticity in the paraventricular thalamus to nucleus accumbens shell (PVT-NAcSh) circuit. The authors employ a combination of behavioral paradigms and ex vivo electrophysiology to examine how acute (1-day) and prolonged (14-day) abstinence from oxycodone self-administration affect cue-induced drug-seeking and synaptic transmission in male and female rats. Their findings reveal that while both sexes show similar oxycodone self-administration and acute withdrawal symptoms, females exhibit enhanced cue-induced relapse after prolonged abstinence. Furthermore, they show that prolonged abstinence is associated with increased synaptic strength in the PVT-NAcSh circuit (reduced paired-pulse ratio) and enhanced intrinsic excitability of NAcSh medium spiny neurons in both sexes. This study provides important insights into the sex-specific neural adaptations that may underlie vulnerability to opioid relapse and highlights the PVT-NAcSh circuit as a potential target for therapeutic interventions. However, although this study is well designed, no sex differences were observed in the synaptic activity within this pathway that could explain increased oxycodone seeking in females versus male rats. Additional experiments could strengthen the results and help clarify synaptic mechanisms underpinning behavioral sex differences.

Strengths:

The study exhibits several strengths. It provides a comprehensive behavioral analysis of oxycodone self-administration, withdrawal, and cue-induced relapse in both male and female rats at different time points (acute vs. protracted withdrawal) offering valuable insights into sex-specific differences (i.e., increased oxycodone seeking in females over time but not males). The authors examine synaptic plasticity in the PVT-NAcSh circuit at different abstinence time points, integrating behavioral and electrophysiological data to link circuit adaptations with relapse behaviors, although no sex differences in the electrophysiological parameters examined were evident. The investigation of intrinsic excitability changes in NAcSh medium spiny neurons further enhances the study's depth. Overall, the well-designed experiments provide important insights into the neural adaptations that may underlie vulnerability to opioid relapse, highlighting the PVT-NAcSh circuit as a potential target for therapeutic interventions in opioid use disorder.

Weaknesses:

Despite its strengths, the study has several notable limitations. A key weakness is the lack of observed sex differences in synaptic activity within the PVT-NAcSh pathway that could explain the behavioral results. The authors' failure to differentiate between D1 and D2 medium spiny neurons (MSNs) in the nucleus accumbens represents a missed opportunity to identify potential sex-specific differences at the cellular level, although they do discuss reasons for this omission. The only significant synaptic change observed - reduced paired-pulse ratio indicating increased synaptic strength - occurs in both males and females, failing to explain the sex-specific behavioral differences. Furthermore, the investigation of intrinsic excitability in NAc MSNs adds complexity to data interpretation, as the authors neither differentiate between D1 and D2 MSNs nor confirm that recorded neurons receive direct inputs from the PVT. This assumption potentially confounds the results. Overall, while the study provides valuable insights, additional experiments targeting specific cell populations and more detailed synaptic analyses are needed to elucidate the mechanisms underlying the observed behavioral sex differences in opioid relapse vulnerability.

Reviewer #3 (Public review):

Summary:

Jin, Briggs et al. made use of light-sheet 3D imaging and data analysis to assess the collective network activity in isolated mouse islets. The major advantage of using whole islet imaging, despite compromising on a speed of acquisition, is that it provides a complete description of the network, while 2D networks are only an approximation of the islet network. In static-incubation conditions, excluding the effects of perfusion, they assessed two subpopulations of beta cells and their spatial consistency and metabolic dependence.

Strengths:

The authors confirmed that coordinated Ca2+ oscillations are important for glycemic control. In addition, they definitively disproved the role of individual privileged cells, which were suggested to lead or coordinate Ca²⁺ oscillations. They provided evidence for differential regional stability, confirming the previously described stochastic nature of the beta cells that act as strongly connected hubs as well as beta cells in initiating regions (doi.org/10.1103/PhysRevLett.127.168101). This has not been a surprise to the reviewer.

The fact that islet cores contain beta cells that are more active and more coordinated has also been readily observed in high-frequency 2D recordings (e.g. DOI: 10.2337/db22-0952), suggesting that the high-speed capture of fast activity can partially compensate for incomplete topological information.

They also found an increased metabolic sensitivity of mantle regions of an islet with subpopulation of beta cells with a high probability of leading the islet activity and which can be entrained by fuel input. They discuss a potential role of alpha/delta cell interaction, however relative lack of beta cells in the islet border region could also be a factor contributing to less connectivity and higher excitability.

The Methods section contains a useful series of direct instructions on how to approach fast 3D imaging with currently available hardware and software.

The Discussion is clear and includes most of the issues regarding the interpretation of the presented results.

Taken together it is a strong technical paper to demonstrate the stochasticity regarding the functions subpopulations of beta cells in the islets may have and how less well-resolved approaches (both missing spatial resolution as well as missing temporal resolution) led us to jump to unjustified conclusions regarding the fixed roles of individual beta cells within an islet.

Weaknesses:

There are a few relevant issues that need to be addressed.

(1) The study is not internally consistent regarding the Results section. In the text the authors discuss changes in membrane potential (not been measured in this study), while in the figures they exclusively describe Ca2+ oscillations (which were measured). Examples are on lines 149, 150, 153, 154, 263... It is recommended that the silent and active phase in the Results section describe processes actually measured in this study as shown 6A.

(2) There are in fact no radially oriented networks in the core of an islet (l. 130, Fig. 4) apart from the fact that every hub has somewhat radially oriented edges. For radiality to have some general meaning, the normalized distance from the geometric center would need to be lower than 0.4. The networks are centrally located, which does not change the major conclusions of the study.

(3) The study would profit from acknowledging that Ca2+ influx is not a sole mechanism to drive insulin secretion and that KATP channels are not the sole target sensitive to changes in the cytosolic (global or local) ADP and ATP concentration or that there is an absolute concentration-dependence of these ligands on KATP channels. The relatively small conductance changes that have been found associated to active and silent phases (closing and opening of the KATP channels as interpreted by the authors, respectively, doi: 10.1152/ajpendo.00046.2013) and should be due to metabolic factors, could be also associated to desensitization of KATP channels to ATP due to the increase in cytosolic Ca2+ changes after intracellular Ca2+ flux (DOI: 10.1210/endo.143.2.8625) as they have been found to operate also at time scales, significantly faster (DOI: 10.2337/db22-0952) than reported before (refs. 21,22). Metabolic changes influence intracellular Ca2+ flux as well.

(4) There is no explanation for why KL divergence is so different between the pre-test regional consistency of the islets used to test the vehicle compared to those where GKa and PKa have been tested.

Reviewer #3 (Public review):

Summary:

The authors were trying to validate SARS-CoV-2 Mac1 as a drug discovery target and by extension other viral macrodomains.

Strengths:

The medicinal chemistry and structure based optimization is exemplary. Macrodomains and ADPribosyl hydrolases have a reputation for being undruggable, yet the authors managed to optimize hits from a fragment screen using structure based approaches and fragment linking to make a 20nM inhibitor as a tool compound to validate the target.<br /> In addition, the in vivo work is also a strength. The ability to reduce the viral count at a rate comparable to nirmatrelvir is impressive. Tracking the cytokine expression levels also supports much of the genetic data and mechanism of action for macrodomains.

Weaknesses:

The main compound AVI-4206, while being very potent and selective is not appreciably orally bioavailable. The fact that they have to use high doses of the compound IP to see in vivo effects may lead to questions regarding off target effects.

The cellular models are not as predictive of antiviral activity as one would expect. However, the authors had enough chutzpah to test the compound in vivo knowing that cellular models might not be an accurate representation of a living system with a fully functional immune system all of which is most likely needed in an antiviral response to test the importance of Mac1 as a target.

Reviewer #3 (Public review):

Summary:

The authors identified RBM20 expression in neural tissues using cell type-specific transcriptomic analysis. This discovery was further validated through in vitro and in vivo approaches, including RNA fluorescent in situ hybridization (FISH), open-source datasets, immunostaining, western blotting, and gene-edited RBM20 knockout (KO) mice. CLIP-seq and RiboTRAP data demonstrated that RBM20 regulates common targets in both neural and cardiac tissues, while also modulating tissue-specific targets. Furthermore, the study revealed that neuronal RBM20 governs long pre-mRNAs encoding synaptic proteins.

Strengths:

• Utilization of a large dataset combined with experimental evidence to identify and validate RBM20 expression in neural tissues.<br /> • Global and tissue-specific RBM20 KO mouse models provide robust support for RBM20 localization and expression.<br /> • Employing heart tissue as a control highlights the unique findings in neural tissues.

Weaknesses:

• Lack of physiological functional studies to explore RBM20's role in neural tissues.<br /> • Data quality requires improvement for stronger conclusions.<br /> • Western blot sample size should be increased for enhanced reliability.

Reviewer #3 (Public review):

Summary:

This study aims to explore the role of phosphorylated ubiquitin (pUb) in proteostasis and its impact on neurodegeneration. By employing a combination of molecular, cellular, and in vivo approaches, the authors demonstrate that elevated pUb levels contribute to both protective and neurotoxic effects, depending on the context. The research integrates proteasomal inhibition, mitochondrial dysfunction, and protein aggregation, providing new insights into the pathology of neurodegenerative diseases.

Strengths:

- The integration of proteomics, molecular biology, and animal models provides comprehensive insights.<br /> - The use of phospho-null and phospho-mimetic ubiquitin mutants elegantly demonstrates the dual effects of pUb.<br /> - Data on behavioral changes and cognitive impairments establish a clear link between cellular mechanisms and functional outcomes.

Weaknesses:

- While the study discusses the reciprocal relationship between proteasomal inhibition and pUb elevation, causality remains partially inferred.<br /> - The role of alternative pathways, such as autophagy, in compensating for proteasomal dysfunction is underexplored.<br /> - The immunofluorescence images in Figure 1A-D lack clarity and transparency. It is not clear whether the images represent human brain tissue, mouse brain tissue, or cultured cells. Additionally, the DAPI staining is not well-defined, making it difficult to discern cell nuclei or staging. To address these issues, lower-magnification images that clearly show the brain region should be provided, along with improved DAPI staining for better visualization. Furthermore, the Results section and Figure legends should explicitly indicate which brain region is being presented. These concerns raise questions about the reliability of the reported pUb levels in AD, which is a critical aspect of the study's findings.<br /> - Figure 4B should also indicate which brain region is being presented.

Reviewer #3 (Public review):

Summary:

The report by Shin, Lee, Kim, and Lee entitled "Progressive overfilling of readily releasable pool underlies short-term facilitation at recurrent excitatory synapses in layer 2/3 of the rat prefrontal cortex" describes electrophysiological experiments of short-term synaptic plasticity during repetitive presynaptic stimulation at synapses between layer 2/3 pyramidal neurons and nearby target neurons. Manipulations include pharmacological inhibition of PLC and actin polymerization, activation of DAG receptors, and shRNA knockdown of Syt7. The results are interpreted as support for the hypothesis that synaptic vesicle release sites are vacant most of the time at resting synapses (i.e., p_occ is low) and that facilitation (and augmentation) components of short-term enhancement are caused by an increase in occupancy, presumably because of acceleration of the transition from not-occupied to occupied. The report additionally describes behavioural experiments where trace fear conditioning is degraded by knocking down syt7 in the same synapses.

Strengths:

The strength of the study is in the new information about short-term plasticity at local synapses in layer 2/3, and the major disruption of a memory task after eliminating short-term enhancement at only 15% of excitatory synapses in a single layer of a small brain region. The local synapses in layer 2/3 were previously difficult to study, but the authors have overcome a number of challenges by combining channel rhodopsins with in vitro electroporation, which is an impressive technical advance.

Weaknesses:

The question of whether or not short-term enhancement causes an increase in p_occ (i.e., "readily releasable pool overfilling") is important because it cuts to the heart of the ongoing debate about how to model short term synaptic plasticity in general. However, my opinion is that, in their current form, the results do not constitute strong support for an increase in p_occ, even though this is presented as the main conclusion. Instead, there are at least two alternative explanations for the results that both seem more likely. Neither alternative is acknowledged in the present version of the report.

The evidence presented to support overfilling is essentially two-fold. The first is strong paired pulse depression of synaptic strength when the interval between action potentials is 20 or 25 ms, but not when the interval is 50 ms. Subsequent stimuli at frequencies between 5 and 40 Hz then drive enhancement. The second is the observation that a slow component of recovery from depression after trains of action potentials is unveiled after eliminating enhancement by knocking down syt7. Of the two, the second is predicted by essentially all models where enhancement mechanisms operate independently of release site depletion - i.e., transient increases in p_occ, p_v, or even N - so isn't the sort of support that would distinguish the hypothesis from alternatives (Garcia-Perez and Wesseling, 2008, https://doi.org/10.1152/jn.01348.2007).

Regarding the paired pulse depression: The authors ascribe this to depletion of a homogeneous population of release sites, all with similar p_v. However, the details fit better with the alternative hypothesis that the depression is instead caused by quickly reversing inactivation of Ca2+ channels near release sites, as proposed by Dobrunz and Stevens to explain a similar phenomenon at a different type of synapse (1997, PNAS,<br /> https://doi.org/10.1073/pnas.94.26.14843). The details that fit better with Ca2+ channel inactivation include the combination of the sigmoid time course of the recovery from depression (plotted backwards in Fig1G,I) and observations that EGTA (Fig2B) increases the paired-pulse depression seen after 25 ms intervals. That is, the authors ascribe the sigmoid recovery to a delay in the activation of the facilitation mechanism, but the increased paired pulse depression after loading EGTA indicates, instead, that the facilitation mechanism has already caused p_r to double within the first 25 ms (relative to the value if the facilitation mechanism was not active). Meanwhile, Ca2+ channel inactivation would be expected to cause a sigmoidal recovery of synaptic strength because of the sigmoidal relationship between Ca2+-influx and exocytosis (Dodge and Rahamimoff, 1967, https://doi.org/10.1113/jphysiol.1967.sp008367).

The Ca2+-channel inactivation hypothesis could probably be ruled in or out with experiments analogous to the 1997 Dobrunz study, except after lowering extracellular Ca2+ to the point where synaptic transmission failures are frequent. However, a possible complication might be a large increase in facilitation in low Ca2+ (Fig2B of Stevens and Wesseling, 1999, https://doi.org/10.1016/s0896-6273(00)80685-6).

On the other hand, even if the paired pulse depression is caused by depletion of release sites rather than Ca2+-channel inactivation, there does not seem to be any support for the critical assumption that all of the release sites have similar p_v. And indeed, there seems to be substantial emerging evidence from other studies for multiple types of release sites with 5 to 20-fold differences in p_v at a wide variety of synapse types (Maschi and Klyachko, eLife, 2020, https://doi.org/10.7554/elife.55210; Rodriguez Gotor et al, eLife, 2024, https://doi.org/10.7554/elife.88212 and refs. therein). If so, the paired pulse depression could be caused by depletion of release sites with high p_v, whereas the facilitation could occur at sites with much lower p_v that are still occupied. It might be possible to address this by eliminating assumptions about the distribution of p_v across release sites from the variance-mean analysis, but this seems difficult; simply showing how a few selected distributions wouldn't work - such as in standard multiple probability fluctuation analyses - wouldn't add much.

In any case, the large increase - often 10-fold or more - in enhancement seen after lowering Ca2+ below 0.25 mM at a broad range of synapses and neuro-muscular junctions noted above is a potent reason to be cautious about the LS/TS model. There is morphological evidence that the transitions from a loose to tight docking state (LS to TS) occur, and even that the timing is accelerated by activity. However, 10-fold enhancement would imply that at least 90 % of vesicles start off in the LS state, and this has not been reported. In addition, my understanding is that the reverse transition (TS to LS) is thought to occur within 10s of ms of the action potential, which is 10-fold too fast to account for the reversal of facilitation seen at the same synapses (Kusick et al, 2020, https://doi.org/10.1038/s41593-020-00716-1).

Individual points:

(1) An additional problem with the overfilling hypothesis is that syt7 knockdown increases the estimate of p_occ extracted from the variance-mean analysis, which would imply a faster transition from unoccupied to occupied, and would consequently predict faster recovery from depression. However, recovery from depression seen in experiments was slower, not faster. Meanwhile, the apparent decrease in the estimate of N extracted from the mean-variance analysis is not anticipated by the authors' model, but fits well with alternatives where p_v varies extensively among release sites because release sites with low p_v would essentially be silent in the absence of facilitation.

(2) Figure S4A: I like the TTX part of this control, but the 4-AP part needs a positive control to be meaningful (e.g., absence of TTX).

(3) Line 251: At least some of the previous studies that concluded these drugs affect vesicle dynamics used logic that was based on some of the same assumptions that are problematic for the present study, so the reasoning is a bit circular.

(4) Line 329 and Line 461: A similar problem with circularity for interpreting earlier syt7 studies.

Reviewer #3 (Public review):

Summary:

Mirkovic et al explore the cause underlying development of aneuploidy during aging. This paper provides a compelling insight into the basis of chromosome missegregation in aged cells, tying this phenomenon to the established Nuclear Pore Complex architecture remodeling that occurs with aging across a large span of diverse organisms. The authors first establish that aged mother cells exhibit aberrant error correction during mitosis. As extrachromosomal rDNA circles (ERCs) are known to increase with age and lead to NPC dysfunction that can result in leakage of unspliced pre-mRNAs, Mirkovic et al search for intron-containing genes in yeast that may be underlying chromosome missegregation, identifying three genes in the aurora B-dependent error correction pathway: MCM21, NBL1, and GLC7. Interestingly, intron-less mutants in these genes suppress chromosome loss in aged cells, with a significant impact observed when all three introns were deleted (3x∆i). The 3x∆i mutant also suppresses the increased chromosome loss resulting from nuclear basket destabilization in a mlp1∆ mutant. The authors then directly test if aged cells do exhibit aberrant mRNA export, using RNA FISH to identify that old cells indeed leak intron-containing pre-mRNA into the cytoplasm, as well as a reporter assay to demonstrate translation of leaked pre-mRNA, and that this is suppressed in cells producing less ERCs. Mutants causing increased pre-mRNA leakage are sufficient to induce chromosome missegregation, which is suppressed by the 3x∆i.

Strengths:

The finding that deleting the introns of 3 genes in the Aurora B pathway can suppress age-related chromosome missegregation is highly compelling. Additionally, the rationale behind the various experiments in this paper is well-reasoned and clearly explained.

Weaknesses:

In some cases, controls for experiments were not presented or were depicted in other figures. High variability was seen in chromosome loss data, leading to large error bars. The text could have been more polished.

Reviewer #3 (Public review):

Summary:

The authors of this work are trying to understand the role dopaminergic terminals coming from VTA have on hippocampal mechanisms of memory consolidation, with emphasis on the replay of hippocampal patterns of activity during periods of consummatory behavior in reward locations. Previous work suggested that replay of relevant spatial trajectories supports reward localization and influences behavior.

The authors then tried to separate two conditions that were known to cause an increase in replay activity - spatial novelty encoding and variation of reward magnitude - and evaluate how these changed when VTA dopamine neurons were inactivated by a chemogenetic tool. They found that the rate of reverse replay (trajectory going away from the goal location) is increased with reward only in novel, but not in familiar environments. Overall this suggests that the VTA dopamine signal is critical during learning of novel locations, but not during explorations of already familiar environments.

Strengths:

The inactivation of VTA projections during goal-oriented behavior and in-vivo analysis of patterns of hippocampal activity during both novelty and reward variability. This work adds to the body of evidence that reverse replay constitutes an important mechanism in learning spatial goal locations. Furthermore, this work also points to the role of VTA in reward prediction error with consequences for spatial navigation and consolidation of spatial memories.

The authors addressed very carefully all the points raised during the revision and I am very pleased with the revised manuscript.

Reviewer #3 (Public review):

Summary:

Combining electrophysiological recording, circuit tracing, single cell RNAseq, and optogenetic and chemogenetic manipulation, Howe and colleagues have identified a graded division between anterior and posterior plCoA and determined the molecular characteristics that distinguish the neurons in this part of the amygdala. They demonstrate that the expression of slc17a6 is mostly restricted to the anterior plCoA whereas slc17a7 is more broadly expressed. Through both anterograde and retrograde tracing experiments, they demonstrate that the anterior plCoA neurons preferentially projected to the MEA whereas those in the posterior plCoA preferentially innervated the nucleus accumbens. Interestingly, optogenetic activation of the aplCoA drives avoidance in a spatial preference assay whereas activating the pplCoA leads to preference. The data support a model that spatially segregated and molecularly defined populations of neurons and their projection targets carry valence specific information for the odors. The discoveries represent a conceptual advance in understanding plCoA function and innate valence coding in the olfactory system.

Strengths:

The strongest evidence supporting the model comes from single cell RNASeq, genetically facilitated anterograde and retrograde circuit tracing, and optogenetic stimulation. The evidence clear demonstrates two molecularly defined cell populations with differential projection targets. Stimulating the two populations produced opposite behavioral responses.

Weaknesses:

There are a couple of inconsistencies that may be addressed by additional experiments and careful interpretation of the data.

Stimulating aplCoA or slc17a6 neurons results in spatial avoidance, and stimulating pplCoA or slc17a7 neurons drives approach behaviors. On the other hand, the authors and others in the field also show that there is no apparent spatial bias in odor-driven responses associated with odor valence. This discrepancy may be addressed better. A possibility is that odor-evoked responses are recorded from populations outside of those defined by slc17a6/a7. This may be addressed by marking activated cells and identifying their molecular markers. A second possibility is that optogenetic stimulation activates a broad set of neurons that and does not recapitulate the sparseness of odor responses. It is not known whether sparsely activation by optogenetic stimulation can still drive approach of avoidance behaviors.

The authors show that inhibiting slc17a7 neurons blocks approaching behaviors toward 2-PE. Consistent with this result, inhibiting NAc projection neurons also inhibits approach responses. However, inhibiting aplCOA or slc17a6 neurons does not reduce aversive response to TMT, but blocking MEA projection neurons does. The latter two pieces of evidence are not consistent with each other. One possibility is that the MEA projecting neurons may not be expressing slc17a6. It is not clear that the retrogradely labeling experiments what percentage of MEA- and NAC-projecting neurons express slc17a6 and slc17a7. It is possible that neurons expressing neither VGluT1 nor VGluT2 could drive aversive or appetitive responses. This possibility may also explain that silencing slc17a6 neurons does not block avoidance.

Reviewer #3 (Public review):

Summary

The study uses publicly available sequences of classical and non-classical genes from a number of primate species to assess the extent and depth of TSP across the primate phylogeny. The analyses were carried out in a coherent and, in my opinion, robust inferential framework and provided evidence for ancient (even > 30 million years) TSP at several classical class I and class II genes. The authors also characterise evolutionary rates at individual codons, map these rates onto MHC protein structures, and find that the fastest evolving codons are extremely enriched for autoimmune and infectious disease associations.

Strengths

The study is comprehensive, relying on a large data set, state-of-the-art phylogenetic analyses and elegant tests of TSP. The results are not entirely novel, but a synthesis and re-analysis of previous findings is extremely valuable and timely.

Weaknesses

I've identified weaknesses in several areas (details follow in the next section):<br /> - Inadequate description and presentation of the data used<br /> - Large parts of the results read like extended figure captions, which breaks the flow.<br /> - Older literature on the subject is duly cited, but the authors don't really discuss their findings in the context of this literature.<br /> - The potential impact of mechanisms other than long-term maintenance of allelic lineages by balancing selection, such as interspecific introgression and incorrect orthology assessment, needs to be discussed.

Reviewer #3 (Public Review):

Summary:

Previous research on the Drosophila mushroom body (MB) has made this structure the best-understood example of an associative memory center in the animal kingdom. This is in no small part due to the generation of cell-type specific driver lines that have allowed consistent and reproducible genetic access to many of the MB's component neurons. The manuscript by Shuai et al. now vastly extends the number of driver lines available to researchers interested in studying learning and memory circuits in the fly. It is an 800-plus collection of new cell-type specific drivers target neurons that either provide input (direct or indirect) to MB neurons or that receive output from them. Many of the new drivers target neurons in sensory pathways that convey conditioned and unconditioned stimuli to the MB. Most drivers are exquisitely selective, and researchers will benefit from the fact that whenever possible, the authors have identified the targeted cell types within the Drosophila connectome. Driver expression patterns are beautifully documented and are publicly available through the Janelia Research Campus's Flylight database where full imaging results can be accessed. Overall, the manuscript significantly augments the number of cell type-specific driver lines available to the Drosophila research community for investigating the cellular mechanisms underlying learning and memory in the fly. Many of the lines will also be useful in dissecting the function of the neural circuits that mediate sensorimotor circuits.

Strengths:

The manuscript represents a huge amount of careful work and leverages numerous important developments from the last several years. These include the thousands of recently generated split-Gal4 lines at Janelia and the computational tools for pairing them to make exquisitely specific targeting reagents. In addition, the manuscript takes full advantage of the recently released Drosophila connectomes. Driver expression patterns are beautifully illustrated side-by-side with corresponding skeletonized neurons reconstructed by EM. A comprehensive table of the new lines, their split-Gal4 components, their neuronal targets, and other valuable information will make this collection eminently useful to end-users. In addition to the anatomical characterization, the manuscript also illustrates the functional utility of the new lines in optogenetic experiments. In one example, the authors identify a specific subset of sugar reward neurons that robustly promotes associative learning.

Reviewer #3 (Public review):

Summary:

This work provides insights into predictive coding models of visual cortex processing. These models predict that visual cortex neurons will show elevated responses when there are unexpected changes to learned sequential stimulus patterns. This model is currently controversial, with recent publications providing conflicting evidence. In this work, the authors test two types of unexpected pattern variations in layer 2/3 of the mouse visual cortex. They show that pattern omission evokes elevated responses, in favor of a predictive coding model, but find no evidence for prediction errors with substituted patterns, which conflicts with both prior results in L4, and with the expectations of a predictive coding model. They also report that with sequence training, responses sparsify and decorrelate, but surprisingly find no changes in the ability of an ideal observer to decode stimulus identity or timing.

These results are an important contribution to the understanding of how temporal sequences and expectations are encoded in the primary visual cortex

Comments on revisions:

In this revision, the authors address several of the concerns in the original manuscript. However, the primary issue, raised by all three reviewers, was the block design of the experiments. This design makes disentangling the effects of any rapid (within block) plasticity from any longer term (across days) plasticity-which nominally is the subject of the paper-extremely difficult.

Although it may be the case that re-running the experiments with an interleaved design is beyond the scope of this paper, unfortunately, the revised manuscript still does not adequately discuss this potential confound. The authors note that stimulus A in ABCD, ABBD, and ACBD could be distinguished on day 0, indicating that within block changes do occur. In both the original and revised manuscript this finding is discussed in terms of representational drift, but the authors fail to discuss how such within block plasticity may impact their primary findings of prediction error effects.

This remains a significant concern with the revised manuscript.

Many of the other issues in the original manuscript have been addressed, and in these areas the revised manuscript is both clearer and more accurately reflects the presented data. The additional analyses and controls shown in the supplemental figures aid in the interpretation of the findings.

Reviewer #3 (Public review):

Yonk and colleagues investigate the role of the thalamostriatal pathway. Specifically, they studied the interaction of the posterior thalamic nucleus (PO) and the dorsolateral striatum in the mouse. First, they characterize connectivity by recording DLS neurons in in vitro slices and optogenetically activating PO terminals. PO is observed to establish depressing synapses onto D1 and D2 spiny neurons as well as PV neurons. Second, the image PO axons are imaged by fiber photometry in mice trained to discriminate textures. Initially, no trial-locked activity is observed, but as the mice learn PO develops responses timed to the audio cue that marks the start of the trial and precedes touch. PO does appear to encode the tactile stimulus type or outcome. Optogenetic suppression of PO terminals in striatum slow task acquisition. The authors conclude that PO provides a "behaviorally relevant arousal-related signal" and that this signal "primes" striatal circuitry for sensory processing.

A great strength of this paper is its timeliness. Thalamostriatal processing has received almost no attention in the past, and the field has become very interested in the possible functions of PO. Additionally, the experiments exploit multiple cutting-edge techniques.

There seem to be some technical/analytical weaknesses. The in vitro experiments appear to have some contamination of nearby thalamic nuclei by the virus delivering the opsin, which could change the interpretation. Some of the statistical analysis of these data also appear inappropriate. The correlative analysis of Pom activity in vivo, licking, and pupil could be more convincingly done.

The bigger weakness is conceptual - why should striatal circuitry need "priming" by thalamus in order to process sensory stimuli? Why would such circuitry even be necessary? Why is a sensory signal from cortex insufficient? Why should the animal more slowly learn the task? How does this fit with existing ideas of striatal plasticity? It is unclear from the experiments that the thalamostriatal pathway exists for priming sensory processing. In fact the optogenetic suppression of the thalamostriatal pathway seems to speak against that idea.

Comments on revisions:

The authors have only tweaked the Discussion and not necessarily in ways that addressed our previous comments. They could have fairly easily analyzed the effect of distance of recording from injection site and compared subsets of data depending on contamination beyond PO (my comments 1 and 2) or effects of movements (3 and 4). Minimally, they could have given caveats in the Results and Discussion about these, and I would strongly encourage them to be explicit about the caveats. The analyses would probably be better.

The suggestion that the effects have something to do with priming (5), seems a grasp for function of the circuit.

Reviewer #3 (Public review):

Summary:

The authors find that Sst-EPN neurons, which project to the lateral habenula, encode information about response directionality (left vs right) and outcome (rewarded vs unrewarded). Surprisingly, chronic impairment of vesicular signaling in these neurons onto their LHb targets did not impair probabilistic choice behavior.

Strengths:

Strengths of the current work include extremely detailed and thorough analysis of data at all levels, not only of the physiological data, but also an uncommonly thorough analysis of behavioral response patterns.

Weaknesses:

In this revised manuscript, the authors have addressed my earlier critiques.

Reviewer #3 (Public review):

Summary:

This manuscript introduces a differentiable variant of the Gillespie algorithm (DGA) that allows gradient calculation using backpropagation. The most significant contribution of this work is the development of the DGA itself, a novel approach to making stochastic simulations differentiable. This is achieved by replacing discontinuous operations in the traditional Gillespie algorithm with smooth, differentiable approximations using sigmoid and Gaussian functions. This conceptual advance opens up new avenues for applying powerful gradient-based optimization techniques, prevalent in machine learning, to studying stochastic biological systems.

The method was tested on a simple two-state promoter model of gene expression. The authors found that the DGA accurately captured the moments of the steady-state distribution and other major qualitative features. However, it was less accurate at capturing information about the distribution's tails, potentially because rare events result from frequent low-probability reaction events where the approximations made by the DGA have a greater impact. The authors could further use the DGA to design a four-state promoter model of gene regulation that exhibited a desired input-output relationship. The DGA could learn parameters that produced a sharper response curve, which was achieved by consuming more energy.

The authors conclude that the DGA is a powerful tool for analyzing and designing stochastic systems.

Strengths:

The DGA allows gradient-based optimization techniques to estimate parameters and design networks with desired properties.

The DGA efficacy in estimating kinetic parameters from both synthetic and experimental data. This capability highlights the DGA's potential to extract meaningful biophysical parameters from noisy biological data.

The DGA's ability to design a four-state promoter architecture exhibiting a desired input-output relationship. This success indicates the potential of the DGA as a valuable tool for synthetic biology, enabling researchers to engineer biological circuits with predefined behaviours.

Weaknesses:

The study primarily focuses on analysing the steady-state properties of stochastic systems. It is unclear how and if this framework can be used beyond the steady-state data presented in the case studies, where it is already quite computationally heavy.<br /> A more in-depth exploration of the DGA's performance in analysing dynamic trajectories, which capture the system's evolution over time, would provide a more comprehensive view of the algorithm's capabilities.<br /> Gradient computations in the DGA can be susceptible to numerical instability, particularly when the sharpness parameters of the sigmoid and Gaussian approximations are set to high values. This issue could lead to challenges in convergence during the optimization process.

Reviewer #3 (Public review):

Summary:

The study demonstrates the effectiveness of a cost-effective closed-loop feedback system for modulating brain activity and behavior in head-fixed mice. Authors have tested real-time closed-loop feedback system in head-fixed mice two types of graded feedback: 1) Closed-loop neurofeedback (CLNF), where feedback is derived from neuronal activity (calcium imaging), and 2) Closed-loop movement feedback (CLMF), where feedback is based on observed body movement. It is a python based opensource system, and authors call it CLoPy. The authors also claim to provide all software, hardware schematics, and protocols to adapt it to various experimental scenarios. This system is capable and can be adapted for a wide use case scenario.

Authors have shown that their system can control both positive (water drop) and negative reinforcement (buzzer-vibrator). This study also shows that using the close loop system mice have shown better performance, learnt arbitrary task and can adapt to change in the rule as well. By integrating real-time feedback based on cortical GCaMP imaging and behavior tracking authors have provided strong evidence that such closed-loop systems can be instrumental in exploring the dynamic interplay between brain activity and behavior.

Strengths:

Simplicity of feedback systems designed. Simplicity of implementation and potential adoption.

Weaknesses:

Long latencies, due to slow Ca2+ dynamics and slow imaging (15 FPS), may limit the application of the system.

Major comments:

(1) Page 5 paragraph 1: "We tested our CLNF system on Raspberry Pi for its compactness, general-purpose input/output (GPIO) programmability, and wide community support, while the CLMF system was tested on an Nvidia Jetson GPU device." Can these programs and hardware be integrated with windows-based system and a microcontroller (Arduino/ Tency). As for the broad adaptability that's what a lot of labs would already have (please comment/discuss)?

(2) Hardware Constraints: The reliance on Raspberry Pi and Nvidia Jetson (is expensive) for real-time processing could introduce latency issues (~63 ms for CLNF and ~67 ms for CLMF). This latency might limit precision for faster or more complex behaviors, which authors should discuss in the discussion section.

(3) Neurofeedback Specificity: The task focuses on mesoscale imaging and ignores finer spatiotemporal details. Sub-second events might be significant in more nuanced behaviors. Can this be discussed in the discussion section?

(4) The activity over 6s is being averaged to determine if the threshold is being crossed before the reward is delivered. This is a rather long duration of time during which the mice may be exhibiting stereotyped behaviors that may result in the changes in DFF that are being observed. It would be interesting for the authors to compare (if data is available) the behavior of the mice in trials where they successfully crossed the threshold for reward delivery and in those trials where the threshold was not breached. How is this different from spontaneous behavior and behaviors exhibited when they are performing the test with CLNF?

Reviewer #3 (Public review):

Summary:

In this study, the authors aimed to investigate if hemodynamic occlusion contributes to fluorescent signals measured with two-photon microscopy. For this, they image the activity-independent fluorophore GFP in 2 different cortical areas, at different cortical depths and in different behavioral conditions. They compare the evoked fluorescent signals with those obtained with calcium sensors and neuromodulator sensors and evaluate their relationship to vessel diameter as a readout of blood flow.<br /> They find that GFP fluorescence transients are comparable to GCaMP6f stimuli-evoked signals in amplitude, although they are generally smaller. Yet, they are significant even at the single neuronal level. They show that GFP fluorescence transients resemble those measured with the dopamine sensor GRAB-DA1m and the serotonin sensor GRAB-5HT1.0 in amplitude an nature, suggesting that signals with these sensors are dominated by hemodynamic occlusion. 
Moreover, the authors perform similar experiments with wide-field microscopy which reveals the similarity between the two methods in generating the hemodynamic signals. Together the evidence presented calls for the development and use of high dynamic range sensors to avoid measuring signals that have another origin from the one intended to measure. In the meantime, the evidence highlights the need to control for those artifacts such as with the parallel use of activity independent fluorophores.

Strengths:

- Comprehensive study comparing different cortical regions in diverse behavioral settings in controlled conditions.<br /> - Comparison to the state-of-the-art, i.e. what has been demonstrated with wide-field microscopy.<br /> - Comparison to diverse activity-dependent sensors, including the widely used GCaMP.

Weaknesses:

- The kinetics of GCaMP is stereotypic. An analysis/comment on if and how the kinetics of the signals could be used to distinguish the hemodynamic occlusion artefacts from calcium signals would be useful.<br /> - Is it possible that motion is affecting the signals in a certain degree? This issue is not made clear.<br /> - The causal relationship with blood flow remains open. Hemodynamic occlusion seems a good candidate causing changes in GFP fluorescence, but this remains to be well addressed in further research.

Reviewer #3 (Public review):

Summary:

The manuscript by Chang and colleagues provides compelling evidence that glia-derived Shriveled (Shv) modulates activity-dependent synaptic plasticity at the Drosophila neuromuscular junction (NMJ). This mechanism differs from the previously reported function of neuronally released Shv, which activates integrin signaling. They further show that this requirement of Shv is acute and that glial Shv supports synaptic plasticity by modulating neuronal Shv release and the ambient glutamate levels. However, there are a number of conceptual and technical issues that need to be addressed.

Major comments

(1) From the images provided for Fig 2B +RU486, the bouton size appears to be bigger in shv RNAi + stimulation, especially judging from the outline of GluR clusters.<br /> (2) The shv result needs to be replicated with a separate RNAi.<br /> (3) The phenotype of shv mutant resembles that of neuronal shv RNAi - no increased GluR baseline. Any insights why that is the case?<br /> (4) In Fig 3B, SPG shv RNAi has elevated GluR baseline, while PG shv RNAi has a lower baseline. In both cases, there is no activity induced GluR increase. What could explain the different phenotypes?<br /> (5) In Fig 4C, the rescue of PTP is only partial. Does that suggest neuronal shv is also needed to fully rescue the deficit of PTP in shv mutants?<br /> (6) The observation in Fig 5D is interesting. While there is a reduction in Shv release from glia after stimulation, it is unclear what the mechanism could be. Is there a change in glial shv transcription, translation or the releasing machinery? It will be helpful to look at the full shv pool vs the released ones.<br /> (7) In Fig 5E, what will happen after stimulation? Will the elevated glial Shv after neuronal shv RNAi be retained in the glia?<br /> (8) It would be interesting to see if the localization of shv differs based on if it is released by neuron or glia, which might be able to explain the difference in GluR baseline. For example, by using glia-Gal4>UAS-shv-HA and neuronal-QF>QUAS-shv-FLAG. It seems important to determine if they mix together after release? It is unclear if the two shv pools are processed differently.<br /> (9) Alternatively, do neurons and glia express and release different Shv isoforms, which would bind different receptors?<br /> (10) It is claimed that Sup Fig 2 shows no observable change in gross glial morphology, further bolstering support that glial Shv does not activate integrin. This seems quite an overinterpretation. There is only one image for each condition without quantification. It is hard to judge if glia, which is labeled by GFP (presumably by UAS-eGFP?), is altered or not.<br /> (11) The hypothesis that glutamate regulates GluR level as a homeostatic mechanism makes sense. What is the explanation of the increased bouton size in the control after glutamate application in Fig 6?<br /> (12) What could be a mechanism that prevents elevated glial released Shv to activate integrin signaling after neuronal shv RNAi, as seen in Fig 5E?<br /> (13) Any speculation on how the released Shv pool is sensed?

Reviewer #3 (Public review):

Summary:

In this work, Ryan et al. have performed a state-of-the-art full genome CRISP-based screen of iNEurons expressing a teggd version of TDP-43 in order to determine expression modifiers of this protein. Unexpectedly, using this approach the authors have uncovered a previously undescribed role of the BORC complex in affecting the levels of TDP-43 protein, but not mRNA expression. Taken together, these findings represent a very solid piece of work that will certainly be important for the field.

Strengths:

- BORC is a novel TDP-43 expression modifier that has never been described before and it seemingly acts on regulating protein half life rather than transcriptome level. It has been long known that different labs have reported different half-lives for TDP-43 depending on the experimental system but no work has ever explained these discrepancies. Now, the work of Ryan et al. has for the time identified one of these factors which could account for these differences and play an important role in disease (although this is left to be determined in future studies).<br /> - The genome wide CRISPR screening has demonstrated to yield novel results with high reproducibility and could eventually be used to search for expression modifiers of many other proteins involved in neurodegeneration or other diseases

Weaknesses:

- The fact that TDP-43 mRNA does not change following BORCS6 KD is based on a single qRT-PCR that does not really cover all possibilities. For example, the mRNA total levels may not change but the polyA sites may have switched from the highly efficient pA1 to the less efficient and nuclear retained pA4. There are therefore a few other experiments that could have been performed to make this conclusion more compelling, maybe also performing RNAscope experiments to make sure that no change occurred in TDP-43 mRNA localisation in cells.<br /> - Even assuming that the mRNA does not change, no explanation for the change in TDP-43 protein half life has been proposed by the authors. This will presumably be addressed in future studies: for example, are mutants that lack different domains of TDP-43 equally affected in their half-lives by BORC KD?. Alternatively, can a mass-spec be attempted to see whether TDP-43 PTMs change following BORCS6 KD?

Reviewer #3 (Public review):

Summary:

This manuscript by Cui et al., studies the mechanisms for the generation of sighing, an essential breathing pattern. This is an important and interesting topic, as sighing maintains normal pulmonary function and is associated with various emotional conditions. However, the mechanisms of its generation remain not fully understood. The authors employed different approaches, including optogenetics, chemogenetics, intersectional genetic approach, and slice electrophysiology and calcium imaging, to address the question, and found several neuronal populations are sufficient to induce sighing when activated. Furthermore, ectopic sighs can be triggered without the involvement of neuromedin B (NMB) or gastrin releasing peptide (GRP) or their receptors in the preBötzinger Complex (preBötC) region of the brainstem. Additionally, activating SST neurons in the preBötC region induces sighing, even when other receptors are blocked. Based on these results, the authors concluded that increased excitability in certain neurons (NMBR or GRPR neurons) activates pathways leading to sigh generation, with SST neurons serving as a downstream component in converting regular breaths into sighs.

Strengths:

The authors employed a combination of various sophisticated approaches, including optogenetics, chemogenetics, intersectional genetic approach, and slice electrophysiology and calcium imaging, to precisely pinpoint the mechanism responsible for sigh generation. They utilized multiple genetically modified mouse lines, enabling them to selectively manipulate and observe specific neuronal populations involved in sighing.<br /> Using genetics and calcium imaging, the authors record the neuronal activity of NMBR and GRPR neurons, respectively, and identified their difference in activity pattern. Furthermore, by applying the intersectional approach, the authors were able to genetically target and manipulate several distinct neuronal populations, such as NMBR+, GRPR- neurons and GRPR+, NMBR- neurons, and conducted a detailed characterization of their functions in influencing sighing.

Weaknesses:

(1) The authors employed two conditions for optogenetic activation: long pulse photostimulation (LPP) and short pulse photostimulation (SPP), with durations ranging from 4-10s for LPP and 100-500 ms for SPP. These could generate huge variability in the experiments. The rationale behind the selection of these conditions in each experiment remains unclear in the manuscript. Additionally, it is not explained why these specific durations were chosen. Furthermore, the interpretation for the varied responses observed under these conditions is not provided. Clarification on the rationale and interpretation of these experimental parameters would enhance the understanding of the results. The description of the experiment conditions should be consistent throughout the manuscript.

(2) Regarding the fiber optics, my understanding is that they are placed outside of the brainstem from the ventral side. Given the locations of the pF and preBötC neurons, could the differences in responses be attributed to the varying distances of each population from the ventral surface? In fact, in Figure 8, NMBR is illustrated as being closer to the ventral surface. Does it represent the actual location of these neurons?

(3) The results of recording on NMBR neurons in Figure 4 were compelling. However, I'm curious why the recording of GRPR neurons and their response to the neuropeptide were not presented or examined. Additionally, considering the known cross-reaction between peptides and their receptors, it might be worthwhile to investigate how GRP modulates NMBR neurons and how NMB modulates GRPR neurons.

(4) The authors found that activation of several preBötC populations, including NMBR, GRPR, and SST neurons, despite pharmacological inhibition of NMBR and GRPR, can still induce sighing, and concluded that "activation of preBötC NMBRs and/or GRPRs is not necessary for sigh production". I disagree with this conclusion. Even when the receptors are silenced, artificial (optogenetic or chemogenetic) activation could still activate the same downstream pathways. This cannot be used as evidence to claim that the receptors are not required for sighing in vivo, because it is possible that the receptors are still necessary for the activation of these neurons under natural conditions. For instance, while diaphragm activation induces breathing, it does not negate the crucial role of the nervous system in regulating this process in physiological conditions.

(5) The authors noted varied responses upon activating specific subpopulations of the preBötC neurons, namely NMBR, GRPR, and SST neurons. Could these differences be attributed to variations in viral labeling efficiency among different mouse genetic lines? Are there discrepancies in the number of labeled neurons across the lines? Additionally, the authors did not thoroughly characterize the specificities of AAV targeting in their Cre and Flp lines. It's uncertain whether the AAV-labeled neurons are strictly restricted to the designated population without notable leakage into other populations. This is particularly crucial for the experiments manipulating SST neurons. If there's substantial labeling of NMBR or GRPR neurons, it could undermine the conclusions drawn. Further examination of the precision and selectivity of the labeling techniques is necessary to ensure the accurate interpretation of the experimental findings.

(6) The authors have addressed some of the reviewers' concerns in the revision; however, many important issues remain unaddressed.

Reviewer #3 (Public review):

In this study, Dong and colleagues set to dissect the role of Rab10 small GTPase on the intracellular trafficking and exocytosis of dense core vesicles (DCVs). While the authors have already shown that Rab3 plays a central role in the exocytosis of DVC in mammalian neurons, the roles of several other Rab-members have been identified genetically, but their precise mechanism of action in mammalian neurons remains unclear. In this study, the authors use a carefully designed and thoroughly executed series of experiments, including live-cell imaging, functional calcium-imaging, proteomics, and electron microscopy, to identify that DCV secretion upon Rab10 depletion in adult neurons is primarily a result of dysregulated protein synthesis and, to a lesser extent, disrupted intracellular calcium buffering. Given that the full deletion of Rab10 has deleterious effect on neurons and that Rab10 has a major role in axonal development, the authors cautiously employed the knock-down strategy from 7 DIV, to focus on the functional impact of Rab10 in mature neurons. The experiments in this study were meticulously conducted, incorporating essential controls and thoughtful considerations, ensuring rigorous and comprehensive results that fully support the conclusions.

Comments on revisions:

The authors have addressed all the comments and suggestions raised by reviewers, making this an excellent and timely study.

Reviewer #3 (Public review):

Summary:

The manuscript by Hallam et al describes the analysis of various biomarkers in patients undergoing complement factor I supplementation treatment (PPY988 gene therapy) as part of the FOCUS Phase I/II clinical trial. The authors used validated methods (multiplexed assays and OLINK proteomics) for measuring multiple soluble complement proteins in the aqueous humour (AH) and vitreous humour (VH) of 28 patients over a series of timepoints, up to and including 96 weeks. Based on biomarker comparisons, the levels of FI synthesised by PPY988 were believed to be insufficient to achieve the desired level of complement inhibition. Subsequent comparative experiments showed that PPY988-delievred FI was much less efficacious than Pegceptacoplan (FDA approved complement inhibitor under the name SYFORVE) when tested in an artificial VH matrix.

Strengths:

The manuscript is well written with data clearly presented and appropriate statistics used for the analysis itself. It's great to see data from real clinical samples that can help support future studies and therapeutic design. The identification that complement biomarker levels present in the AH do not represent the levels found in the VH is an important finding for the field, given the number of complement-targeting therapies in development and the desperate need for good biomarkers for target engagement. This study also provides a wealth of baseline complement protein measurements in both human AH and VH (and companion measurements in plasma) that will prove useful for future studies.

Weaknesses:

No real weaknesses in the manuscript itself. It is only a shame that it would appear that FI supplementation is not a viable way forward for treating GA secondary to AMD.

Comments on revisions:

I think the authors have done all that they can to present this study in the most robust manner possible.

Reviewer #3 (Public review):

Summary:

"Decoding Phase Separation of Prion-Like Domains through Data-Driven Scaling Laws" by Maristany et al. offers a significant contribution to the understanding of phase separation in prion-like domains (PLDs). The study investigates the phase separation behavior of PLDs, which are intrinsically disordered regions within proteins that have the propensity to undergo liquid-liquid phase separation (LLPS). This phenomenon is crucial in forming biomolecular condensates, which play essential roles in cellular organization and function. The authors employ a data-driven approach to establish predictive scaling laws that describe the phase behavior of these domains.

Strengths:

The study benefits from a robust dataset encompassing a wide range of PLDs, which enhances the generalizability of the findings. The authors' meticulous curation and analysis of this data add to the study's robustness. The scaling laws derived from the data provide predictive insights into the phase behavior of PLDs, which can be useful in the future for the design of synthetic biomolecular condensates.

Reviewer #3 (Public review):

This manuscript examines the impact of congenital visual deprivation on the excitatory/inhibitory (E/I) ratio in the visual cortex using Magnetic Resonance Spectroscopy (MRS) and electroencephalography (EEG) in individuals whose sight was restored. Ten individuals with reversed congenital cataracts were compared to age-matched, normally sighted controls, assessing the cortical E/I balance and its interrelationship and to visual acuity. The study reveals that the Glx/GABA ratio in the visual cortex and the intercept and aperiodic signal are significantly altered in those with a history of early visual deprivation, suggesting persistent neurophysiological changes despite visual restoration.

First of all, I would like to disclose that I am not an expert in congenital visual deprivation, nor in MRS. My expertise is in EEG (particularly in the decomposition of periodic and aperiodic activity) and statistical methods. Although the authors addressed some of the concerns of the previous version, major concerns and flaws remain in terms of methodological and statistical approaches along with the (over)interpretation of the results. Specific concerns include:

(1 3.1) Response to Variability in Visual Deprivation<br /> Rather than listing the advantages and disadvantages of visual deprivation, I recommend providing at least a descriptive analysis of how the duration of visual deprivation influenced the measures of interest. This would enhance the depth and relevance of the discussion.

(2 3.2) Small Sample Size<br /> The issue of small sample size remains problematic. The justification that previous studies employed similar sample sizes does not adequately address the limitation in the current study. I strongly suggest that the correlation analyses should not feature prominently in the main manuscript or the abstract, especially if the discussion does not substantially rely on these correlations. Please also revisit the recommendations made in the section on statistical concerns.

(3 3.3) Statistical Concerns<br /> While I appreciate the effort of conducting an independent statistical check, it merely validates whether the reported statistical parameters, degrees of freedom (df), and p-values are consistent. However, this does not address the appropriateness of the chosen statistical methods.

Several points require clarification or improvement:<br /> (4) Correlation Methods: The manuscript does not specify whether the reported correlation analyses are based on Pearson or Spearman correlation.<br /> (5) Confidence Intervals: Include confidence intervals for correlations to represent the uncertainty associated with these estimates.<br /> (6) Permutation Statistics: Given the small sample size, I recommend using permutation statistics, as these are exact tests and more appropriate for small datasets.<br /> (7) Adjusted P-Values: Ensure that reported Bonferroni corrected p-values (e.g., p > 0.999) are clearly labeled as adjusted p-values where applicable.<br /> (8) Figure 2C<br /> Figure 2C still lacks crucial information that the correlation between Glx/GABA ratio and visual acuity was computed solely in the control group (as described in the rebuttal letter). Why was this analysis restricted to the control group? Please provide a rationale.<br /> (9 3.4) Interpretation of Aperiodic Signal<br /> Relying on previous studies to interpret the aperiodic slope as a proxy for excitation/inhibition (E/I) does not make the interpretation more robust.<br /> (10) Additionally, the authors state:<br /> "We cannot think of how any of the exploratory correlations between neurophysiological measures and MRS measures could be accounted for by a difference e.g. in skull thickness."<br /> (11) This could be addressed directly by including skull thickness as a covariate or visualizing it in scatterplots, for instance, by representing skull thickness as the size of the dots.<br /> (12 3.5) Problems with EEG Preprocessing and Analysis<br /> Downsampling: The decision to downsample the data to 60 Hz "to match the stimulation rate" is problematic. This choice conflates subsequent spectral analyses due to aliasing issues, as explained by the Nyquist theorem. While the authors cite prior studies (Schwenk et al., 2020; VanRullen & MacDonald, 2012) to justify this decision, these studies focused on alpha (8-12 Hz), where aliasing is less of a concern compared of analyzing aperiodic signal. Furthermore, in contrast, the current study analyzes the frequency range from 1-20 Hz, which is too narrow for interpreting the aperiodic signal as E/I. Typically, this analysis should include higher frequencies, spanning at least 1-30 Hz or even 1-45 Hz (not 20-40 Hz).<br /> (13) Baseline Removal: Subtracting the mean activity across an epoch as a baseline removal step is inappropriate for resting-state EEG data. This preprocessing step undermines the validity of the analysis. The EEG dataset has fundamental flaws, many of which were pointed out in the previous review round but remain unaddressed. In its current form, the manuscript falls short of standards for robust EEG analysis. If I were reviewing for another journal, I would recommend rejection based on these flaws.<br /> (14) The authors mention:<br /> "The EEG data sets reported here were part of data published earlier (Ossandón et al., 2023; Pant et al., 2023)." Thus, the statement "The group differences for the EEG assessments corresponded to those of a larger sample of CC individuals (n=38) " is a circular argument and should be avoided."<br /> The authors addressed this comment and adjusted the statement. However, I do not understand, why not the full sample published earlier (Ossandón et al., 2023) was used in the current study?

Reviewer #3 (Public review):

Summary:

In this work, Casu et al. have reported the characterization of a previously uncharacterized membrane protein CisA encoded in a non-canonical contractile injection system of Streptomyces coelicolor, CISSc, which is a cytosolic CISs significantly distinct from both intracellular membrane-anchored T6SSs and extracellular CISs. The authors have presented the first high-resolution structure of extended CISSc structure. It revealed important structural insights in this conformational state. To further explore how CISSc interacted with cytoplasmic membrane, they further set out to investigate CisA that was previously hypothesized to be the membrane adaptor. However, the structure revealed that it was not associated with CISSc. Using fluorescence microscope and cell fractionation assay, the authors verified that CisA is indeed a membrane-associated protein. They further determined experimentally that CisA had a cytosolic N-terminal domain and a periplasmic C-terminus. The functional analysis of cisA mutant revealed that it is not required for CISSc assembly but is essential for the contraction, as a result, the deletion significantly affects CISSc-mediated cell death upon stress, timely differentiation, as well as secondary metabolite production. Although the work did not resolve the mechanistic detail how CisA interacts with CISSc structure, it provides solid data and a strong foundation for future investigation toward understanding the mechanism of CISSc contraction, and potentially, the relation between the membrane association of CISSc, the sheath contraction and the cell death.

Strengths:

The paper is well-structured, and the conclusion of the study is supported by solid data and careful data interpretation was presented. The authors provided strong evidence on (1) the high-resolution structure of extended CISSc determined by cryo-EM, and the subsequent comparison with known eCIS structures, which sheds light on both its similarity and different features from other subtypes of eCISs in detail; (2) the topological features of CisA using fluorescence microscopic analysis, cell fractionation and PhoA-LacZα reporter assays, (3) functions of CisA in CISSc-mediated cell death and secondary metabolite production, likely via the regulation of sheath contraction.

Weaknesses:

The data presented are not sufficient to provide mechanistic details of CisA-mediated CISSc contraction, as authors are not able to experimentally demonstrate the direct interaction between CisA with baseplate complex of CISSc (hypothesized to be via Cis11 by structural modeling), since they could not express cisA in E. coli due to its potential toxicity. Therefore, there is a lack of biochemical analysis of direct interaction between CisA and baseplate wedge. In addition, there is no direct evidence showing that CisA is responsible for tethering CISSc to the membrane upon stress, and the spatial and temporal relation between membrane association and contraction remains unclear. Further investigation will be needed to address these questions in future.

Discussion:

Overall, the work provides a valuable contribution to our understanding on the structure of a much less understood subtype of CISs, which is unique compared to both membrane-anchored T6SSs and host-membrane targeting eCISs. Importantly, the work serves as a good foundation to further investigate how the sheath contraction works here. The work contributes to expanding our understanding of the diverse CIS superfamilies.

Reviewer #3 (Public review):

In this manuscript, Natarajan and colleagues report on the role of a prophage, termed SfPat, in the regulation of motility and biofilm formation by the marine bacterium Shewanella fidelis. The authors investigate the in vivo relevance of prophage carriage by studying the gut occupation patterns of Shewanella fidelis wild-type and an isogenic SfPat- mutant derivative in a model organism, juveniles of the marine tunicate Ciona robusta. The role of bacterial prophages in regulating bacterial lifestyle adaptation and niche occupation is a relatively underexplored field, and efforts in this direction are appreciated.

While the research question is interesting, the work presented lacks clarity in its support for several major claims, and, at times, the authors do not adequately explain their data.

Major concerns:

(1) Prophage deletion renders the SfPat- mutant derivative substantially less motile and with a higher biofilm formation capacity than the WT (Fig. 2a-b). The authors claim the mutant is otherwise isogenic to the WT strain upon sequence comparison of draft genome sequences (I'll take the opportunity to comment here that GenBank accessions are preferable to BioSample accessions in Table 1). Even in the absence of secondary mutations, complementation is needed to validate functional associations (i.e., phenotype restoration). A strategy for this could be phage reintegration into the mutant strain (PMID: 19005496).

(2) The authors claim that the downshift in motility (concomitant with an upshift in biofilm formation) is likely mediated by the activity of c-di-GMP turnover proteins. Specifically, the authors point to the c-di-GMP-specific phosphodiesterase PdeB as a key mediator, after finding lower transcript levels for its coding gene in vivo (lines 148-151, Fig. 2c), and suggesting higher activity of this protein in live animals (!)(line 229). I have several concerns here:<br /> (2.1) Findings shown in Fig. 2a-b are in vitro, yet no altered transcript levels for pdeB were recorded (Fig. 2c). Why do the authors base their inferences only on in vivo data?<br /> (2.2) Somewhat altered transcript levels alone are insufficient for making associations, let alone solid statements. Often, the activity of c-di-GMP turnover proteins is local and/or depends on the activation of specific sensory modules - in the case of PdeB, a PAS domain and a periplasmic sensor domain (PMID: 35501424). This has not been explored in the manuscript, i.e., specific activation vs. global alterations of cellular c-di-GMP pools (or involvement of other proteins, please see below). Additional experiments are needed to confirm the involvement of PdeB. Gaining such mechanistic insights would greatly enhance the impact of this study.<br /> (2.3) What is the rationale behind selecting only four genes to probe the influence of the prophage on Ciona gut colonization by determining their transcript levels in vitro and in vivo? If the authors attribute the distinct behavior of the mutant to altered c-di-GMP homeostasis, as may be plausible, why did the authors choose those four genes specifically and not, for example, the many other c-di-GMP turnover protein-coding genes or c-di-GMP effectors present in the S. fidelis genome? This methodological approach seems inadequate to me, and the conclusions on the potential implication of PdeB are premature.

(3) The behavior of the WT strain and the prophage deletion mutant is insufficiently characterized. For instance, how do the authors know that the higher retention capacity reported for the WT strain with respect to the mutant (Fig. 3b) is not merely a consequence of, e.g., a higher growth rate? It would be worth investigating this further, ideally under conditions reflecting the host environment.

(4) Related to the above, sometimes the authors refer to "retention" (e.g., line 162) and at other instances to "colonization" (e.g., line 161), or even adhesion (line 225). These are distinct processes. The authors have only tracked the presence of bacteria by fluorescence labeling; adhesion or colonization has not been assessed or demonstrated in vivo. Please revise.

(5) The higher CFU numbers for the WT after 24 h (line 161) might also indicate a role of motility for successful niche occupation or dissemination in vivo. The authors could test this hypothesis by examining the behavior of, e.g., flagellar mutants in their in vivo model.

(6) The endpoint of experiments with a mixed WT-mutant inoculum (assumedly 1:1? Please specify) was set to 1 h, I assume because of the differences observed in CFU counts after 24 h. In vivo findings shown in Fig. 3c-e are, prima facie, somewhat contradictory. The authors report preferential occupation of the esophagus by the WT (line 223), which seems proficient from evidence shown in Fig. S3. Yet, there is marginal presence of the WT in the esophagus in experiments with a mixed inoculum (Fig. 3d) or none at all (Fig. 3e). Likewise, the authors claim preferential "adhesion to stomach folds" by the mutant strain (line 225), but this is not evident from Fig. 3e. In fact, the occupation patterns by the WT and mutant strain in the stomach in panel 3e appear to differ from what is shown in panel 3d. The same holds true for the claimed "preferential localization of the WT in the pyloric cecum," with Fig. 3d showing a yellow signal that indicates the coexistence of WT and mutant.

(7) In general, and especially for in vivo data, there is considerable variability that precludes drawing conclusions beyond mere trends. One could attribute such variability in vivo to the employed model organism (which is not germ-free), differences between individuals, and other factors. This should be discussed more openly in the main text and presented as a limitation of the study. Even with such intrinsic factors affecting in vivo measurements, certain in vitro experiments, which are expected, in principle, to yield more reproducible results, also show high variability (e.g., Fig. 5). What do the authors attribute this variability to?

(8) Line 198-199: Why not look for potential prophage excision directly rather than relying on indirect, presumptive evidence based on qPCR?

Reviewer #3 (Public review):

This manuscript by Sarkar et al. examines the infection of the liver and hepatocytes during M. tuberculosis infection. They demonstrate that aerosol infection of mice and guinea pigs leads to appreciable infection of the liver as well as the lung. Transcriptomic analysis of HepG2 cells showed differential regulation of metabolic pathways including fatty acid metabolic processing. Hepatocyte infection is assisted by fatty acid synthesis in the liver and inhibiting this caused reduced Mtb growth. The nuclear receptor PPARg was upregulated by Mtb infection and inhibition or agonism of its activity caused a reduction or increase in Mtb growth, respectively, supporting data published elsewhere about the role of PPARg in lung macrophage Mtb infection. Finally, the authors show that Mtb infection of hepatocytes can cause upregulation of enzymes that metabolize antibiotics, resulting in increased tolerance of these drugs by Mtb in the liver.

Overall, this is an interesting paper on an area of TB research where we lack understanding. However, some additions to the experiments and figures are needed to improve the rigor of the paper and further support the findings. Most importantly, although the authors show that Mtb can infect hepatocytes in vitro, they fail to describe how bacteria get from the lungs to the liver in an aerosolized infection. They also claim that "PPARg activation resulting in lipid droplets formation by Mtb might be a mechanism of prolonging survival within hepatocytes" but do not show a direct interaction between PPARg activation and lipid droplet formation and lipid metabolism, only that PPARg promotes Mtb growth. Thus, the correlations with PPARg appear to be there but causation, implied in the abstract and discussion, is not proven.

The human photomicrographs are important and overall well done (lung and liver from the same individuals is excellent). However, in lines 120-121, the authors comment on the absence of studies on the precise involvement of different cells in the liver. In this study there is no attempt to immunophenotype the nature of the cells harboring Mtb in these samples (esp. hepatocytes). Proving that hepatocytes specifically harbor the bacteria in these human samples would add significant rigor to the conclusions made.

Reviewer #3 (Public review):

Summary:

The manuscript demonstrates that starvation induces persister formation in M. abscesses. They also utilized Tn-Seq for the identification of genes involved in persistence. They identified the role of catalase-peroxidase KatG in preventing death from translation inhibitors Tigecycline and Linezolid. They further demonstrated that a combination of these translation inhibitors leads to the generation of ROS in PBS-starved cells.

Strengths:

The authors used high-throughput genomics-based methods for identification of genes playing a role in persistence.

Weaknesses:

The findings could not be validated in clinical strains.

Reviewer #3 (Public review):

The manuscript describes the use of CRISPR gene editing coupled with phenotyping mosaic zebrafish larvae to characterize functions of genes implicated in heritable fragile bone disorders (FBDs). Authors targeted six high-confident candidate genes implicated in severe recessive forms of FBDs and four Osteoporosis GWAS-implicated genes and observe varied developmental phenotypes across all crispants, in addition to adult skeletal phenotypes. While the study lacks insight on underlying mechanisms that contribute to disease phenotypes, a major strength of the paper is the streamlined method that produced significant phenotypes for all candidate genes tested. It also represents a significant increase in number of candidate genes tested using their crispant approach beyond the single mutant that was previously published.

One weakness was the variability of developmental phenotypes, addressed by authors in the Discussion. This might be a product of maternal transcripts not targeted by CRISPR or genetic compensation, which authors have not fully explored. Overall, the paper was well-written and easy to read.

Comments on latest version:

The authors have addressed many concerns in this revision. Figure 1 and Table 2 are much improved.

While details of orthologous gene expression profiles of target genes is a welcome addition, other features of target genes remain unaddressed. For example, do genes with maternally deposited transcript exhibit dampened phenotypes? Or does genetic compensation impact certain genes more than others? Since authors state that the study represents a methods paper, it will be important for users to understand the caveats of gene selection to effectively implement and interpret results of the approach.

Reviewer #3 (Public review):

Summary:

This work is a valuable study that aims to decipher the molecular mechanisms underlying the translation process in Japanese encephalitis virus (JEV), a relevant member of the genus Flavivirus. The authors provide evidence that cap-independent translation, which has already been demonstrated for other flaviviruses, could also account in JEV. This process depends on the genomic 3' UTR, as previously demonstrated in other flaviviruses. Further, the authors find that cellular proteins such as DDX3 or PABP1 could contribute to JEV translation in a cap-independent way. Both DDX3 and PABP1 had previously been described to have a role in cellular protein synthesis and also in the translation step of other flaviviruses distinct from JEV; therefore, this work would expand the cap-independent translation in flaviviruses as a general mechanism to bypass the translation repression exerted by the host cell during viral infection. Further, the findings can be relevant for the development of specific drugs that could interfere with flaviviral translation in the future. Nevertheless, the conclusions are not fully supported by the provided results.

Strengths:

The results provide a good starting point to investigate the molecular mechanism underlying the translation in flaviviruses, which even today is an area of knowledge with many limitations.

Weaknesses:

The main limit of the work is related to the fact that the role of the 3' UTR structural elements and DDX3 is not only circumscribed to translation, but also to replication and encapsidation. In fact, some of the provided results suggest this idea. Particularly, it is intriguing why the virus titer can be completely abrogated while the viral protein levels are only partially affected by the knockdown of DDX3. This points to the fact that many of the drawn conclusions could be overestimated or, at least, all the observed effect cannot be attributed only to the DDX3 effect on translation. Finally, it is noteworthy that the use of uncapped transcripts could be misleading, since this is not the natural molecular context of the viral genome.

Reviewer #3 (Public review):

Summary:

Retroviruses have been endogenized into the genome of all vertebrate animals. The envelope protein of the virus is not well conserved and acquires many mutations hence can be used to monitor viral evolution. Since they are incorporated into the host genome, they also reflect the evolution of the hosts. In this manuscript the authors have focused their analyses on the env genes of endogenous retroviruses in primates. Important observations made include the extensive recombination events between these retroviruses that were previously unknown and the discovery of HML species in genomes prior to the splitting of old and new world monkeys.

Strengths:

They explored a number of databases and made phylogenetic trees to look at the distribution of retroviral species in primates. The authors provide a strong rationale for their study design, they provide a clear description of the techniques and the bioinformatics tools used.

Weaknesses:

The manuscript is based on bioinformatics analyses only. The reference genomes do not reflect the polymorphisms in humans or other primate species. The analyses thus likely under estimates the amount of diversity in the retroviruses. Further experimental verification will be needed to confirm the observations.<br /> Not sure which databases were used, but if not already analyzed, ERVmap.com and repeatmesker are ones that have many ERVs that are not present in the reference genomes. Also, long range sequencing of the human genome has recently become available which may also be worth studying for this purpose.

Reviewer #3 (Public review):

The manuscript by Lu et al. explores the role of the Arp2/3 complex and the actin nucleators N-WASP and WAVE in myoblast fusion during muscle regeneration. The results are clear and compelling, effectively supporting the main claims of the study. However, the manuscript could benefit from a more detailed molecular and cellular analysis of the fusion synapse. Additionally, while the description of macrophage extravasation from ghost fibers is intriguing, it seems somewhat disconnected from the primary focus of the work.

Despite this, the data are robust, and the major conclusions are well supported. Understanding muscle fusion mechanism is still a widely unexplored topic in the field and the authors make important progress in this domain.

I have a few suggestions that might strengthen the manuscript as outlined below.

(1) Could the authors provide more detail on how they defined cells with "invasive protrusions" in Figure 4C? Membrane blebs are commonly observed in contacting cells, so it would be important to clarify the criteria used for counting this specific event.

(2) Along the same line, please clarify what each individual dot represents in Figure 4C. The authors mention quantifying approximately 83 SCMs from 20 fibers. I assume each dot corresponds to data from individual fibers, but if that's the case, does this imply that only around four SCMs were quantified per fiber? A more detailed explanation would be helpful.

(3) Localizing ArpC2 at the invasive protrusions would be a strong addition to this study. Furthermore, have the authors examined the localization of Myomaker and Myomixer in ArpC2 mutant cells? This could provide insights into potential disruptions in the fusion machinery.

(4) As a minor curiosity, can ArpC2 WT and mutant cells fuse with each other?

(5) The authors report a strong reduction in CSA at 14 dpi and 28 dpi, attributing this defect primarily to failed myoblast fusion. Although this claim is supported by observations at early time points, I wonder whether the Arp2/3 complex might also play roles in myofibers after fusion. For instance, Arp2/3 could be required for the growth or maintenance of healthy myofibers, which could also contribute to the reduced CSA observed, since regenerated myofibers inherit the ArpC2 knockout from the stem cells. Could the authors address or exclude this possibility? This is rather a broader criticism of how things are being interpreted in general beyond this paper.

Reviewer #3 (Public review):

Summary:

The article presents a meticulous and quantitative anatomical reconstruction of the compound eye of a tiny wasp at the level of subcellular structures, and cellular and optical organization of the ommatidia and reveals the ectopic photoreceptors, which are decoupled from the eye's dioptrical apparatus.

Strengths:

The graphic material is of very high quality, beautifully organized, and presented in a logical order. The anatomical analysis is fully supported by quantitative numerical data at all scales, from organelles to cells and ommatidia, which should be a valuable source for future studies in cellular biology and visual physiology. The 3D renders are highly informative and a real eye candy.

Weaknesses:

The claim that the large dorsal part of the eye is the dorsal rim area (DRA), supported by anatomical data on rhabdomere geometry and connectomics in authors' earlier work, would eventually greatly benefit from additional evidence, obtained by immunocytochemical staining, that could also reveal a putative substrate for colour vision. The cell nuclei that are located in the optical path in the DRA crystalline cone have only a putative optical function, which may be either similar to pore canals in hymenopteran DRA cornea (scattering) or to photoreceptor nuclei in camera-type eyes (focussing), both explanations being mutually exclusive.

Reviewer #3 (Public review):

Summary:

The authors suggest a mechanism that explains the preference of viral protein 35 (VP35) homologs to bind the backbone of double-stranded RNA versus blunt ends. These preferences have a biological impact in terms of the ability of different viruses to escape the immune response of the host.<br /> The proposed mechanism involves the existence of a cryptic pocket, where VP35 binds the blunt ends of dsRNA when the cryptic pocket is closed and preferentially binds the RNA double-stranded backbone when the pocket is open.<br /> The authors performed MD simulation results, thiol labelling experiments, fluorescence polarization assays, as well as point mutations to support their hypothesis.

Strengths:

This is a genuinely interesting scientific question, which is approached through multiple complementary experiments as well as extensive MD simulations. Moreover, structural biology studies focused on RNA-protein interactions are particularly rare, highlighting the importance of further research in this area.

Weaknesses:

- Sequence similarity between Ebola-Zaire (94% similarity) explains their similar behaviour in simulations and experimental assays. Marburg instead is a more distant homolog (~80% similarity relative to Ebola/Zaire). This difference is sequence and structure can explain the propensities, without the need to involve the existence of a cryptic pocket.<br /> - No real evidence for the presence of a cryptic pocket is presented, but rather a distance probability distribution between two residues obtained from extensive MD simulations. It would be interesting to characterise the modelled RNA-protein interface in more detail.

Reviewer #3 (Public review):

Summary:

Nestor and colleagues identify genes escaping X chromosome inactivation (XCI) in rare individuals with non-mosaic XCI (nmXCI) whose tissue-specific RNA-seq datasets were obtained from the GTEX database. Because XCI is non-mosaic, read counts representing a second allele are tested for statistically significant escape, in this case > 2.5% of active X expression. Whereas a prior GTEX analysis found only one nmXCI female, this study finds two additional donors in GTEX, therefore expanding the number of assessed X-linked genes to 380. Although this is fewer than half of X-linked genes, the study demonstrates that although rare, nmXCI females are represented in RNA-seq databases such as GTEX. Therefore this analytical approach is worthwhile pursuing in other (larger) databases as well, to provide deeper insight into escape from XCI which is relevant to X-linked diseases and sex differences.

Strengths:

The analysis is well-documented, straightforward, and valuable. The supplementary tables are useful, and the claims in the main text well-supported.

Weaknesses:

There are very few, except that this escape catalogue is limited to 3 donors, based on a single (representative) tissue screen in 285 female donors, mostly using muscle samples. However, if only pituitary samples had been screened, nmXCI-1 would have been missed. Additional donors in the 285 representative samples cross a lower threshold of AE = 0.4. It would be worthwhile to query all tissues of the 285 donors to discover more nmXCI cases, as currently fewer than half of X-linked genes received a call using this very worthwhile approach.

Reviewer #3 (Public review):

Summary:

The authors performed time-resolved proteomics and phospho-proteomics in Xenopus oocytes from prophase I through the MII arrest of the unfertilized egg. The data contains protein abundance and phosphorylation sites of a large number set of proteins at different stages of oocyte maturation. The large sets of the data are of high quality. In addition, the authors discussed several key pathways critical for the maturation. The data is very useful for the researchers not only researchers in Xenopus oocytes but also those in oocyte biology in other organisms.

Strengths:

The data of proteomics and phospho-proteomics in Xenopus oocyte maturation is very useful for future studies to understand molecular networks in oocyte maturation.

Weaknesses:

Although the authors offered molecular pathways of the phosphorylation in the translation, protein degradation, cell cycle regulation, and chromosome segregation. The author did not check the validity of the molecular pathways based ontheir proteomic data by the experimentation.

Reviewer #3 (Public review):

Summary:

The present work by Suzuki et al seeks to develop a new embryonic olfactory epithelium organoid culture model, to study OR gene expression and mechanisms involved in epithelium-to-bulb targeting. They characterize an organoid culture derived from E13 mouse olfactory tissue, using RT-qPCR, immunostaining, limited calcium imaging, and single-cell RNA-seq. Main findings show that the cultures produce major olfactory cell types; many olfactory neurons express a single OR; scSeq analysis identifies transcriptional programs associated with specific OR class expressions that may help define mechanisms involved in projection to specific bulb sites (glomeruli).

Strengths:

The organoid model is generally well-characterized and may be a useful approach for studying this question and other problems, such as basal cell lineage choice or damage and repair mechanisms. Overall, the paper is well-written, and the figures are of high quality.

The cultures, produced from E13 mice, appear to produce HBCs, GBCs, neurons, and non-neural cells, providing an important tool. I think a really interesting question is: when do HBCs first appear in these cultures? Developmentally, in rodents, HBCs do not arise until near the end of gestation, and the OE cell populations are instead made from a more GBC-like cell (keratin negative, p63 negative) that proliferates as an apical or basal progenitor. The cell type and architectural descriptions used here repeatedly are really descriptions of the adult OE, yet the cultures are made from E13 mouse olfactory epithelium. Perhaps an important question could be addressed by this model - how this specific adult reserve epithelial stem cell (the HBC) is generated remains unclear. HBCs are a reserve multipotential cell that reconstitutes the entire olfactory epithelium in adults following severe injury, yet is not present during embryonic development until after the epithelium has been largely generated.

Weaknesses:

The paper should discuss the transcriptional programs identified here that correlate with OR class expression in the context of findings from Tsukahara et al, Cell 2021. Tsukahara identified from in vivo olfactory neuron scSeq fixed gene expression programs defining olfactory neuron position in AP or DV axes correlating highly with OR expression.

While the current findings do define the expression of putative targeting, guidance or adhesion molecules in specific OR-expressing neurons in culture, the current results do not provide any experimental evidence that glomerulus targeting is actually mediated by these factors. Further discussion of this limitation may be helpful, along with a discussion of additional approaches to explore these questions.

Calcium imaging: it is not clear why isovaleric acid was chosen as a stimulus for Ca imaging. Is it's known receptor expressed widely in these cultures? Why not use a cocktail of odorants, to activate a broader range of ORs, as has been widely used in in vitro calcium imaging studies of olfactory neurons? Can you show positive control activation (i.e. high potassium)?

How many unique ORs are identified as expressed in the cultures? Figure 5 indicates only 78 genes. Since mice express about 1200 ORs, is this a limitation? How many replicates (individual cells) are found to express each of the ORs? Again, Figure 5 suggests only 202 cells are OR+? Is this enough to define the gene expression programs reliably associated with a given OR or OR class? More detail on this analysis would be helpful.

Reviewer #3 (Public review):

Summary:

The authours present a variant of a previously described fluorescence lifetime sensor for calcium. Much of the manuscript describes the process of developing appropriate assays for screening sensor variants, and thorough characterization of those variants (inherent fluorescence characteristics, response to calcium and pH, comparisons to other calcium sensors). The final two figures show how the sensor performs in cultured cells and in vivo drosophila brains.

Strengths:

The work is presented clearly and the conclusion (this is a new calcium sensor that could be useful in some circumstances) is supported by the data.

Weaknesses:

There are probably few circumstances where this sensor would facilitate experiments (calcium measurements) that other sensors would prove insufficient.

Reviewer #3 (Public review):

Summary:<br /> In this work, the authors present a chromatin polymer model with some specific pattern of transcription units (TUs) and diffusing TFs; they simulate the model and study TFclustering, mixing, gene expression activity, and their correlations. First, the authors designed a toy polymer with colored beads of a random type, placed periodically (every 30 beads, or 90kb). These colored beads are considered a transcription unit (TU). Same-colored TUs attract with each other mediated by similarly colored diffusing beads considered as TFs. This led to clustering (condensation of beads) and correlated (or anti-correlation) "gene expression" patterns. Beyond the toy model, when authors introduce TUs in a specific pattern, it leads to emergence of specialized and mixed cluster of different TFs. Human chromatin models with realistic distribution of TUs also lead to the mixing of TFs when cluster size is large.

Strengths:<br /> This is a valuable polymer model for chromatin with a specific pattern of TUs and diffusing TF-like beads. Simulation of the model tests many interesting ideas. The simulation study is convincing and the results provide solid evidence showing the emergence of mixed and demixed TF clusters within the assumptions of the model.

Weaknesses:<br /> Weakness of the work: The model has many assumptions. Some of the assumptions are a bit too simplistic. Concerns about the work are detailed below:

The authors assume that when the diffusing beads (TFs) are near a TU, the gene expression starts. However, mammalian gene expression requires activation by enhancer-promoter looping and other related events. It is not a simple diffusion-limited event. Since many of the conclusions are derived from expression activity, will the results be affected by the lack of looping details?

Authors neglect protein-protein interactions. Without protein-protein interactions, condensate formation in natural systems is unlikely to happen.

What is described in this paper is a generic phenomenon; many kinds of multivalent chromatin-binding proteins can form condensates/clusters as described here. For example, if we replace different color TUs with different histone modifications and different TFs with Hp1, PRC1/2, etc, the results would remain the same, wouldn't they? What is specific about transcription factor or transcription here in this model?<br /> What is the logic of considering 3kb chromatin as having a size of 30 nm? See Kadam et al. (Nature Communications 2023). Also, DNA paint experimental measurement of 5kb chromatin is greater than 100 nm (see work by Boettiger et al.).

Reviewer #3 (Public review):

Summary:

This work investigates computational consequences of assemblies containing both excitatory and inhibitory neurons (E/I assembly) in a model with parameters constrained by experimental data from the telencephalic area Dp of zebrafish. The authors show how this precise E/I balance shapes the geometry of neuronal dynamics in comparison to unstructured networks and networks with more global inhibitory balance. Specifically, E/I assemblies lead to the activity being locally restricted onto manifolds - a dynamical structure in-between high-dimensional representations in unstructured networks and discrete attractors in networks with global inhibitory balance. Furthermore, E/I assemblies lead to smoother representations of mixtures of stimuli while those stimuli can still be reliably classified, and allows for more robust learning of additional stimuli.

Strengths:

Since experimental studies do suggest that E/I balance is very precise and E/I assemblies exist, it is important to study the consequences of those connectivity structures on network dynamics. The authors convincingly show that E/I assemblies lead to different geometries of stimulus representation compared to unstructured networks and networks with global inhibition. This finding might open the door for future studies for exploring the functional advantage of these locally defined manifolds, and how other network properties allow to shape those manifolds.

The authors also make sure that their spiking model is well-constrained by experimental data from the zebrafish pDp. Both, spontaneous and odor stimulus triggered spiking activity is within the range of experimental measurements. But the model is also general enough to be potentially applied to findings in other animal models and brain regions.

Weaknesses:

All my previous points have been addressed.

Reviewer #3 (Public review):

Summary:

Using a combination of optogenetic tools and single-photon calcium imaging, the authors collected a set of high-quality data and conducted thorough analyses to demonstrate the importance of cholinergic input to the prelimbic cortex in probabilistic spatial learning, particularly pertaining to threat.

Strengths:

Given the importance of the findings, this paper will appeal to a broad audience in the systems, behavioural, and cognitive neuroscience community.

Weaknesses:

I have only a few concerns that I consider need to be addressed.

(1) Can the authors describe the basic effect of cholinergic stimulation on PL neurons' activity, during pretraining, probabilistic, and random stages? From the plot, it seems that some neurons had an increase and others had a decrease in activity. What are the percentages for significant changes in activities, given the intensity of stimulation? Were these changes correlated with the neurons' selectivity for the location? If they happen to have the data, a dose-response plot would be very helpful too.

(2) Figure 2B: The current sorting does not show the effects of puff and LED well. Perhaps it's best to sort based on the 'puff with no stim' condition in the middle, by the total activity in 2s following the puff, and then by the timing in the rise/drop of activity (from early to late). This way perhaps the optogenetic stimulation would appear more striking. Figure 3Aa and Ba have the same issue: by the current sorting, the effects are not very visible at all. Perhaps they want to consider not showing the cells that did not show the effect of puff and/or LED.

Also, I would recommend that the authors use ABCD to refer to figure panels, instead of Aa, Ab, etc. This is very hard to follow.

(3) The authors mentioned the laminar distribution of ACh receptors in discussion. Can they show the presence/absence of topographic distribution of neurons responding to puff and/or LED?

(4) Figure 2C seems to show only neurons with increased activity to an air puff. It's also important to know how neurons with an inhibitory response to air-puff behaved, especially given that in tdTomato animals, the proportion of these neurons was the same as excitatory responders.

(5) Page 5, lines 107 and 110: Following 2-way ANOVA, the authors used a 'follow-up 1-way rmANOVA' and 'follow-up t-test' instead of post hoc tests (e.g. Tukey's). This doesn't seem right. Please use post hoc tests instead to avoid the problem of multiple comparisons.

(6) Figure 1H: in the running speed analysis, were all trials included, both LED+ and LED-? This doesn't affect the previous panels in Figure 1 but it could affect 1H. Did stimulation affect how the running speed recovers?

On a related note, does a surprising puff/omission affect the running speed on the subsequent trial?

(7) On Page 7, line 143, it says "In the absence of LED stimulation, the magnitude of their puff-evoked activity was reduced in ChrimsonR-expressing mice...", but then on line 147 it says "This group difference was not detected without the LED stimulation". I don't follow what is meant by the latter statement, it seems to be conflicting with line 143. The red curves in the left vs right panels do not seem different. The effect of air puff seems to differ, but is this due to a higher gray curve ('no puff' condition) in the ChrimsonR group?

(8) Did the neural activity correlate with running speed? Since the main finding was the absence of difference in running speed modulation by probability in ChrimsonR mice, one would expect to see PL cells showing parallel differences.

Reviewer #3 (Public review):

Summary:

This manuscript seeks to understand how nerve injury-induced signaling to the nucleus is influenced, and it establishes a new location where these principles can be studied. By identifying and mapping specific bifurcated neuronal innervations in the Drosophila larvae, and using laser axotomy to localize the injury, the authors find that sparing a branch of a complex muscular innervation is enough to impair Wallenda-puc (analogous to DLK-JNK-cJun) signaling that is known to promote regeneration. It is only when all connections to the target are disconnected that cJun-transcriptional activation occurs.

Overall, this is a thorough and well-performed investigation of the mechanism of spared-branch influence on axon injury signaling. The findings on control of wnd are important because this is a very widely used injury signaling pathway across species and injury models. The authors present detailed and carefully executed experiments to support their conclusions. Their effort to identify the control mechanism is admirable and will be of aid to the field as they continue to try to understand how to promote better regeneration of axons.

Strengths:

The paper does a very comprehensive job of investigating this phenomenon at multiple locations and through both pinpoint laser injury as well as larger crush models. They identify a non-hiw based restraint mechanism of the wnd-puc signaling axis that presumably originates from the spared terminal. They also present a large list of tests they performed to identify the actual restraint mechanism from the spared branch, which has ruled out many of the most likely explanations. This is an extremely important set of information to report, to guide future investigators in this and other model organisms on mechanisms by which regeneration signaling is controlled (or not).

Weaknesses:

The weakest data presented by this manuscript is the study of the actual amounts of Wallenda protein in the axon. The authors argue that increased Wnd protein is being anterogradely delivered from the soma, but no support for this is given. Whether this change is due to transcription/translation, protein stability, transport, or other means is not investigated in this work. However, because this point is not central to the arguments in the paper, it is only a minor critique.

As far as the scope of impact: because the conclusions of the paper are focused on a single (albeit well-validated) reporter in different types of motor neurons, it is hard to determine whether the mechanism of spared branch inhibition of regeneration requires wnd-puc (DLK/cJun) signaling in all contexts (for example, sensory axons or interneurons). Is the nerve-muscle connection the rule or the exception in terms of regeneration program activation?

Because changes in puc-lacZ intensity are the major readout, it would be helpful to better explain the significance of the amount of puc-lacZ in the nucleus with respect to the activation of regeneration. Is it known that scaling up the amount of puc-lacZ transcription scales functional responses (regeneration or others)? The alternative would be that only a small amount of puc-lacZ is sufficient to efficiently induce relevant pathways (threshold response).

Reviewer #3 (Public review):

Summary:

Microexons are highly conserved alternative splice variants, the individual functions of which have thus far remained mostly elusive. The inclusion of microexons in mature mRNAs increases during development, specifically in neural tissues, and is regulated by SRRM proteins. Investigation of individual microexon function is a vital avenue of research since microexon inclusion is disrupted in diseases like autism. This study provides one of the first rigorous screens (using zebrafish larvae) of the functions of individual microexons in neurodevelopment and behavioural control. The authors precisely excise 21 microexons from the genome of zebrafish using CRISPR-Cas9 and assay the downstream impacts on neurite outgrowth, larvae motility, and sociality. A small number of mild phenotypes were observed, which contrasts with the more dramatic phenotypes observed when microexon master regulators SRRM3/4 are disrupted. Importantly, this study attempts to address the reasons why mild/few phenotypes are observed and identify transcriptomic changes in microexon mutants that suggest potential compensatory gene regulatory mechanisms.

Strengths:

(1) The manuscript is well written with excellent presentation of the data in the figures.

(2) The experimental design is rigorous and explained in sufficient detail.

(3) The identification of a potential microexon compensatory mechanism by transcriptional alterations represents a valued attempt to begin to explain complex genetic interactions.

(4) Overall this is a study with a robust experimental design that addresses a gap in knowledge of the role of microexons in neurodevelopment.

Reviewer #3 (Public review):

Summary:

In this manuscript, Sumegi et al. use calcium imaging in head-fixed mice to test whether new place fields tend to emerge due to events that resemble behavioral time scale plasticity (BTSP) or other mechanisms. An impressive dataset was amassed (163 sessions from 45 mice with 500-1000 neurons per sample) to study the spontaneous emergence of new place fields in area CA1 that had the signature of BTSP. The authors observed that place fields could emerge due to BTSP and non-BTSP-like mechanisms. Interestingly, when non-BTSP mechanisms seemed to generate a place field, this tended to occur on a trial with a spontaneous reset in neural coding (a remapping event). Novelty seemed to upregulate non-BTSP events relative to BTSP events. Finally, large calcium transients (presumed plateau potentials) were not sufficient to generate a place field.

Strengths:

I found this manuscript to be exceptionally well-written, well-powered, and timely given the outstanding debate and confusion surrounding whether all place fields must arise from BTSP event. Working at the same institute, Albert Lee (e.g. Epszstein et al., 2011 - which should be cited) and Jeff Magee (e.g. Bittner et al., 2017) showed contradictory results for how place fields arise. These accounts have not fully been put toe-to-toe and reconciled in the literature. This manuscript addresses this gap and shows that both accounts are correct - place fields can emerge due to a pre-existing map and due to BTSP.

Weaknesses:

I find only three significant areas for improvement in the present study:

First, can it be concluded that non-BTSP events occur exclusively due to a global remapping event, as stated in the manuscript "these PFF surges included a high fraction of both non-BTSP- and BTSP-like PFF events, and were associated with global remapping of the CA1 representation"? Global remapping has a precise definition that involves quantifying the stability of all place fields recorded. Without a color scale bar in Figure 3D (which should be added), we cannot know whether the overall representations were independent before and after the spontaneous reset. It would be good to know if some neurons are able to maintain place coding (more often than expected by chance), suggestive of a partial-remapping phenomenon.

Second, BTSP has a flip side that involves the weakening of existing place fields when a novel field emerges. Was this observed in the present study? Presumably place fields can disappear due to this bidirectional BTSP or due to global remapping. For a full comparison of the two phenomena, the disappearance of place fields must also be assessed.

Finally, it would be good to know if place fields differ according to how they are born. For example, are there differences in reliability, width, peak rate, out-of-field firing, etc for those that arise due to BTSP vs non-BTSP.

Reviewer #3 (Public review):

Summary:

In this study, Banse et al., demonstrate that combining computer prediction with genetic analysis in distinct Caenorhabditis species can streamline the discovery of aging interventions by taking advantage of the diverse pool of compounds that are currently available. They demonstrate that through careful prioritization of candidate compounds, they are able to accomplish a 30% positive hit rate for interventions that produce significant lifespan extensions. Within the positive hits, they focus on all-trans retinoic acid (atRA) and discover that it modulates lifespan through conserved longevity pathways such as AKT-1 and AKT-2 (and other conserved Akt-targets such as Nrf2/SKN-1 and HSF1/HSF-1) as well as through AAK-2, a conserved catalytic subunit of AMPK. To better understand the genetic mechanisms behind lifespan extension upon atRA treatment, the authors perform RNAseq experiments using a variety of genetic backgrounds for cross-comparison and validation. Using this current state-of-the-art approach for studying gene expression, the authors determine that atRA treatment produces gene expression changes across a broad set of stress-response and longevity-related pathways. Overall, this study is important since it highlights the potential of combining traditional genetic analysis in the genetically tractable organism C. elegans with computational methods that will become even more powerful with the swift advancements being made in artificial intelligence. The study possesses both theoretical and practical implications not only in the field of aging but also in related fields such as health and disease. Most of the claims in this study are supported by solid evidence, but the conclusions can be refined with a small set of additional experiments or re-analysis of data.

Strengths:

(1) The criteria for prioritizing compounds for screening are well-defined and easy to replicate (Figure 1), even for scientists with limited experience in computational biology. The approach is also adaptable to other systems or model organisms.

(2) I commend the researchers for doing follow-up experiments with the compound propranolol to verify its effect on lifespan (Figure 2 Supplement 2), given the observation that it affected the growth of OP50. To prevent false hits in the future, the reviewer recommends the use of inactivated OP50 for future experiments to remove this confounding variable.

(3) The sources of variation (Figure 3, Figure Supplement 2) are taken into account and demonstrate the need for advancing our understanding of the lifespan phenotype due to inter-individual variation.

(4) The addition of the C. elegans swim test in addition to the lifespan assays provides further evidence of atRA-induced improvement in longevity.

(5) The RNAseq approach was performed in a variety of genetic backgrounds, which allowed the authors to determine the relationship between AAK-2 and HSF-1 regulation of the retinoic acid pathway in C. elegans, specifically, that the former functions downstream of the latter.

Weaknesses:

(1) The filtering of compounds for testing using the DrugAge database requires that the database is consistently updated. In this particular case, even though atRA does not appear in the database, the authors themselves cite literature that has already demonstrated atRA-induced lifespan extension, which should have precluded this compound from the analysis in the first place.

(2) The threshold for determining positive hits is arbitrary, and in this case, a 30% positive hit rate was observed when the threshold is set to a lifespan extension of around 5% based on Figure 1B (the authors fail to explicitly state the cut-off for what is considered a positive hit).

(3) The authors demonstrate that atRA extends lifespan in a species-specific manner (Figure 3). Specifically, this extension only occurs in the species C. elegans yet, the title implies that atRA-induced lifespan extension occurs in different Caenorhabditis species when it is clearly not the case. While the authors state that failure to observe phenotypes in C. briggsae and C. tropicalis is a common feature of CITP tests, they do not speculate as to why this phenomenon occurs.

(4) There are discrepancies between the lifespan curves by hand (Figure 3 Figure Supplement 1) and using the automated lifespan machine (Figure 3 Supplement 3). Specifically, in the automated lifespan assays, there are drastic changes in the slope of the survival curve which do not occur in the manual assays. This may be due to improper filtering of non-worm objects, improper annotation of death times, or improper distribution of plates in each scanner.

(5) The authors miss an opportunity to determine whether the lifespan extension phenotype attributed to the retinoic acid pathway is mostly transcriptional in nature or whether some of it is post-transcriptional. The authors even state "that while aak-2 is absolutely required for the longevity effects of atRA, aak-2 is required only for a small proportion (~1/4) of the transcriptional response", suggesting that some of the effects are post-transcriptional. Further information could have been obtained had the authors also performed RNAseq analysis on the tol-1 mutant which exhibited an enhanced response to atRA compared to wild-type animals, and comparing the magnitude of gene expression changes between the tol-1 mutant and all other genetic backgrounds for which RNAseq was performed.

Reviewer #3 (Public review):

Summary:

The authors address the role of ORC in DNA replication and that this protein complex is not essential for DNA replication in hepatocytes. They provide evidence that ORC subunit levels are substantially reduced in cells that have been induced to delete multiple exons of the corresponding ORC gene(s) in hepatocytes. They evaluate replication both in purified isolated hepatocytes and in mice after hepatectomy. In both cases, there is clear evidence that DNA replication does not decrease at a level that corresponds with the decrease in detectable ORC subunit and that endoreduplication is the primary type of replication observed. It remains possible that small amounts of residual ORC are responsible for the replication observed, although the authors provide arguments against this possibility. The mechanisms responsible for DNA replication in the absence of ORC are not examined.

Strengths:

The authors clearly show that there are dramatic reductions in the amount of the targeted ORC subunits in the cells that have been targeted for deletion. They also provide clear evidence that there is replication in a subset of these cells and that it is likely due to endoreduplication. Although there is no replication in MEFs derived from cells with the deletion, there is clearly DNA replication occurring in hepatocytes (both isolated in culture and in the context of the liver). Interestingly, the cells undergoing replication exhibit enlarged cell sizes and elevated ploidy indicating endoreduplication of the genome. These findings raise the interesting possibility that endoreduplication does not require ORC while normal replication does.

Weaknesses:

There are two significant weaknesses in this manuscript. The first is that although there is clearly robust reduction of the targeted ORC subunit, the authors cannot confirm that it is deleted in all cells. For example, the analysis in Fig. 4B would suggest that a substantial number of cells have not lost the targeted region of ORC2. Although the western blots show stronger effects, this type of analysis is notorious for non-linear response curves and no standards are provided. The second weakness is that there is no evaluation of the molecular nature of the replication observed. Are there changes in the amount of location of Mcm2-7 loading that is usually mediated by ORC? Does an associated change in Mcm2-7 loading lead to the endoreduplication observed? After numerous papers from this lab and others claiming that ORC is not required for eukaryotic DNA replication in a subset of cells, we still have no information about an alternative pathway that could explain this observation.

The authors frequently use the presence of a Cre-dependent eYFP expression as evidence that the ORC1 or ORC2 genes have been deleted. Although likely the best visual marker for this, it is not demonstrated that the presence of eYFP ensures that ORC2 has been targeted by Cre. For example, based on the data in Fig. 4B, there seems to be a substantial percentage of ORC2 genes that have not been targeted while the authors report that 100% of the cells express eYFP.

Reviewer #3 (Public review):

In this study, the authors investigate the requirements for the formation of CPSF6 puncta induced by HIV-1 under a high multiplicity of infection conditions. Not surprisingly, they observe that mutation of the Phe-Gly (FG) repeat responsible for CPSF6 binding to the incoming HIV-1 capsid abrogates CPSF6 punctum formation. Perhaps more interestingly, they show that the removal of other domains of CPSF6, including the mixed-charge domain (MCD), does not affect the formation of HIV-1-induced CPSF6 puncta. The authors also present data suggesting that CPSF6 puncta form individual before fusing with nuclear speckles (NSs) and that the fusion of CPSF6 puncta to NSs requires the intrinsically disordered region (IDR) of the NS component SRRM2. While the study presents some interesting findings, there are some technical issues that need to be addressed and the amount of new information is somewhat limited. Also, the authors' finding that deletion of the CPSF6 MCD does not affect the formation of HIV-1-induced CPSF6 puncta contradicts recent findings of Jang et al. (https://doi.org/10.1093/nar/gkae769).

Reviewer #3 (Public review):

Summary:

In this article, Toshniwal et al. investigate the role of pyruvate metabolism in controlling cell growth. They find that elevated expression of the mitochondrial pyruvate carrier (MPC) leads to decreased cell size in the Drosophila fat body, a transformed human hepatocyte cell line (HepG2), and primary rat hepatocytes. Using genetic approaches and metabolic assays, the authors find that elevated pyruvate import into cells with forced expression of MPC increases the cellular NADH/NAD+ ratio, which drives the production of oxaloacetate via pyruvate carboxylase. Genetic, pharmacological, and metabolic approaches suggest that oxaloacetate is used to support gluconeogenesis rather than amino acid synthesis in cells over-expressing MPC. The reduction in cellular amino acids impairs protein synthesis, leading to impaired cell growth.

Strengths:

This study shows that the metabolic program of a cell, and especially its NADH/NAD+ ratio, can play a dominant role in regulating cell growth.

The combination of complementary approaches, ranging from Drosophila genetics to metabolic flux measurements in mammalian cells, strengthens the findings of the paper and shows a conservation of MPC effects across evolution.

Weaknesses:

In general, the strengths of this paper outweigh its weaknesses. However, some areas of inconsistency and rigor deserve further attention.

The authors comment that MPC overrides hormonal controls on gluconeogenesis and cell size (Discussion, paragraph 3). Such a claim cannot be made for mammalian experiments that are conducted with immortalized cell lines or primary hepatocytes.

Nuclear size looks to be decreased in fat body cells with elevated MPC levels, consistent with reduced endoreplication, a process that drives growth in these cells. However, acute, ex vivo EdU labeling and measures of tissue DNA content are equivalent in wild-type and MPC+ fat body cells. This is surprising - how do the authors interpret these apparently contradictory phenotypes?

In Figure 4d, oxygen consumption rates are measured in control cells and those over-expressing MPC. Values are normalized to protein levels, but protein is reduced in MPC+ cells. Is oxygen consumption changed by MPC expression on a per-cell basis?

Trehalose is the main circulating sugar in Drosophila and should be measured in addition to hemolymph glucose. Additionally, the units in Figure 4h should be related to hemolymph volume - it is not clear that they are.

Measurements of NADH/NAD ratios in conditions where these are manipulated genetically and pharmacologically (Figure 5) would strengthen the findings of the paper. Along the same lines, expression of manipulated genes - whether by RT-qPCR or Western blotting - would be helpful to assess the degree of knockdown/knockout in a cell population (for example, Got2 manipulations in Figures 6 and S8).

Reviewer #3 (Public review):

Summary:

In this study, Fang et al. systematically investigate the effects of culture conditions on gene expression, genome architecture, and gene dependency. To do this, they cultivate the murine HCC line NEJF10 under standard culture conditions (2D), then under similar conditions but under hypoxia (1% oxygen, 2D hypoxia) and under normoxia as spheroids (3D). NEJF10 was isolated from a marine HCC model that relies exclusively on MYC as a driver oncogene. In principle, (1) RNA-seq, (2) ATAC-seq and (3) genetic screens were then performed in this isogenic system and the results were systematically compared in the three cultivation methods. In particular, genome-wide screens with the CRISPR library Brie were performed very carefully. For example, in the 2D conditions, many different time points were harvested to control the selection process kinetically. The authors note differential dependencies for metabolic processes (not surprisingly, hypoxia signaling is affected) such as the regulation and activity of mitochondria, but also organogenesis signaling and epigenetic regulation.

Strengths:

The topic is interesting and relevant and the experimental set-up is carefully chosen and meaningful. The paper is well written. While the study does not reveal any major surprises, the results represent an important resource for the scientific community.

Weaknesses:

However, this presupposes that the statistical analysis and processing are carried out very carefully, and this is where my main suggestions for revision begin. Firstly, I cannot find any information on the number of replicates in RNA- and ATAC-seq. This should be clearly stated in the results section and figure legends and cut-offs, statistical procedures, p-values, etc. should be mentioned as well. In principle, all NGS experiments (here ATAC- and RNA-seq) should be performed in replicates (at least duplicates, better triplicates) or the results should be validated by RT-PCR in independent biological triplicates. Secondly, the quantification of the analyses shown in the figures and especially in the legends is not sufficiently careful. Units are often not mentioned. Example Figure 4a: The legend says: 'gRNA reads' but how can the read count be -1? I would guess these are FC, log2FC, or Z-values. All figure legends need careful revision.

Furthermore, I would find a comparison of the sgRNA abundances at the earliest harvesting time with the distribution in the library interesting, to see whether and to what extent selection has already taken place before the three culture conditions were established (minor point).

Reviewer #3 (Public review):

Summary:

The authors have put forth a compelling argument that NOLC1 is indispensable for gastric cancer resistance in both in vivo and in vitro models. They have further elucidated that NOLC1 silencing augments cisplatin-induced ferroptosis in gastric cancer cells. The mechanistic underpinning of their findings suggests that NOLC1 modulates the p53 nuclear/plasma ratio by engaging with the p53 DNA Binding Domain, which in turn impedes p53-mediated transcriptional regulation of ferroptosis. Additionally, the authors have shown that NOLC1 knockdown triggers the release of ferroptosis-induced damage-associated molecular patterns (DAMPs), which activate the tumor microenvironment (TME) and enhance the efficacy of the anti-PD-1 and cisplatin combination therapy.

Strengths:

The manuscript presents a robust dataset that substantiates the authors' conclusion. They have identified NOLC1 as a potential oncogene that confers resistance to immuno-chemotherapy in gastric cancer through the mediation of ferroptosis and subsequent TME reprogramming. This discovery positions NOLC1 as a promising therapeutic target for gastric cancer treatment. The authors have delineated a novel mechanistic pathway whereby NOLC1 suppresses p53 transcriptional functions by reducing its nuclear/plasma ratio, underscoring the significance of p53 nuclear levels in tumor suppression over total protein levels.

Weaknesses:

While the overall findings are commendable, there are specific areas that could benefit from further refinement. The authors have posited that NOLC1 suppresses p53-mediated ferroptosis; however, the mRNA levels of ferroptosis genes regulated by p53 have not been quantified, which is a critical gap in the current study. In Figure 4A, transmission electron microscopy (TEM) results are reported solely for the MGC-803 cell line. It would be beneficial to include TEM data for the MKN-45 cell line to strengthen the findings. The authors have proposed a link between NOLC1-mediated reduction in the p53 nuclear/plasma ratio and gastric cancer resistance, yet the correlation between this ratio and patient prognosis remains unexplored, which is a significant limitation in the context of clinical relevance.

Reviewer #3 (Public review):

Summary:

The manuscript "SARS-CoV-2 nsp16 is regulated by host E3 ubiquitin ligases, UBR5 and MARCHF7" is an interesting work by Tian et al. describing the degradation/ stability of NSP16 of SARS CoV2 via K48 and K27-linked Ubiquitination and proteasomal degradation. The authors have demonstrated that UBR5 and MARCHF7, an E3 ubiquitin ligase bring about the ubiquitination of NSP16. The concept, and experimental approach to prove the hypothesis looks ok. The in vivo data looks ok with the controls. Overall, the manuscript is good. However, several major and minor changes/points need to be addressed.

Strengths:

The study identified important E3 ligases (MARCHF7 and UBR5) that can ubiquitinate NSP16, an important viral factor.

Weaknesses:

Most of the in vitro experiments (IP, overexpression) lack appropriate controls. The summary figure in actual terms does not show/correlate to the experimental findings.

Reviewer #3 (Public review):

Summary:

Kim et al. present a study of the neural dynamics underlying reversal learning in monkey PFC and neural networks. The concept of studying neural dynamics throughout the task (including intervening behaviour) is interesting, and the data provides some insights into the neural dynamics driving reversal learning. The modelling seems to support the analyses, but both the modelling and analyses also leave several open questions.

Strengths:

The paper addresses an interesting topic of the neural dynamics underlying reversal learning in PFC, using a combination of biological and simulated data. Reversal learning has been studied extensively in neuroscience, but this paper takes a step further by analysing neural dynamics throughout the trials instead of focusing on just the evidence integration epoch.

The authors show some close parallels between the experimental data and RNN simulations, both in terms of behaviour and neural dynamics. The analyses of how rewarded and unrewarded trials differentially affect dynamics throughout the trials in RNNs and PFC were particularly interesting. This work has the potential to provide new insights into the neural underpinnings of reversal learning.

Weaknesses:

Conceptual:

A substantial focus of the paper is on the within-trial dynamics associated with "intervening behaviour", but it is not clear whether that is well-modelled by the RNN. In particular, since there is little description of the experimental task, and the RNN does not have to do any explicit computation during the non-feedback parts of the trial, it is unclear whether the RNN 'non-feedback' dynamics can be expected to reasonably model the experimental data.

Data analyses:

While the basic analyses seem mostly sound, it seems like a potential confound that they are all aligned to the inferred reversal trial rather than the true experimental reversal trial. For example, the analyses showing that 'x_rev' decays strongly after the reversal trial, irrespective of the reward outcome, seem like they are true essentially by design. The choice to align to the inferred reversal trial also makes this trial seem 'special' (e.g. in Figure 2, Figure 5A), but it is unclear whether this is a real feature of the data or an artifact of effectively conditioning on a change in behaviour. It would be useful to investigate whether any of these analyses differ when aligned to the true reversal trial. It is also unsurprising that x_rev increases before the reversal and decreases after the reversal (it is hard to imagine a system where this is not the case), yet all of Figure 5 and much of Figure 4 is devoted to this point.

Most of the analyses focus on the dynamics specifically in the x_rev subspace, but a major point of the paper is to say that biological (and artificial) networks may also have to do other things at different times in the trial. If that is the case, it would be interesting to also ask what happens in other subspaces of neural activity, that are not specifically related to evidence integration or choice - are there other subspaces that explain substantial variance? Do they relate to any meaningful features of the experiment?

On a related note, descriptions of the task itself, the behaviour of the animal(s?), and the neural recordings are largely absent, making it difficult to know what we should expect from neural dynamics throughout a trial. In fact, we are not even told how many monkeys were used for the paper or which part of PFC the recordings are from.

Modelling:

There are a number of surprising and non-standard modelling choices made in this paper. For example, the choice to only use inhibitory neurons is non-conventional and not consistent with prior work. The authors cite van Vreeswijk & Sompolinsky's balanced network paper, but this and most other balanced networks use a combination of excitatory and inhibitory neurons.

It also seems like the inputs are provided without any learnable input weights (and the form of the inputs is not described in any detail). This makes it hard to interpret the input-driven dynamics during the different phases of a trial, despite these dynamics being a central topic of the paper.

It is surprising that the RNN is "trained to flip its preferred choice a few trials after the inferred scheduled reversal trial", with the reversal trial inferred by an ideal Bayesian observer. A more natural approach would be to directly train the RNN to solve the task (by predicting the optimal choice) and then investigate the emergent behaviour & dynamics. If the authors prefer their imitation learning approach (which should at least be motivated), it is also surprising that the network is trained to predict the reversal trial inferred using Bayesian smoothing instead of Bayesian filtering.

Reviewer #3 (Public review):

Summary:

This paper sought to understand how microexons influence early brain function. By selectively deleting a large number of conserved microexons and then phenotyping the mutants with behavior and brain activity assays, the authors find that most microexons have minimal effects on the global brain activity and broad behaviors of the larval fish-- although a few do have phenotypes.

Strengths:

The work takes full advantage of the scale that is afforded in zebrafish, generating a large mutant collection that is missing microexons and systematically phenotyping them with high throughput behaviour and brain activity assays. The work lays an important foundation for future studies that seek to uncover the likely subtle roles that single microexons will play in shaping development and behavior.

Weaknesses:

The work does not make it clear enough what deleting the microexon means, i.e. is it a clean removal of the microexon only, or are large pieces of the intron being removed as well-- and if so how much? Similarly, for the microexon deletions that do yield phenotypes, it will be important to demonstrate that the full-length transcript levels are unaffected by the deletion. For example, deleting the microexon might have unexpected effects on splicing or expression levels of the rest of the transcript that are the actual cause of some of these phenotypes.

Reviewer #3 (Public review):

Summary:

Ruan and colleagues consider a branching process model (in their terminology the "Haldane model") and the most basic Wright-Fisher model. They convincingly show that offspring distributions are usually non-Poissonian (as opposed to what's assumed in the Wright-Fisher model), and can depend on short-term ecological dynamics (e.g., variance in offspring number may be smaller during exponential growth). The authors discuss branching processes and the Wright-Fisher model in the context of 3 "paradoxes" --- 1) how Ne depends on N might depend on population dynamics; 2) how Ne is different on the X chromosome, the Y chromosome, and the autosomes, and these differences do match the expectations base on simple counts of the number of chromosomes in the populations; 3) how genetic drift interacts with selection. The authors provide some theoretical explanations for the role of variance in the offspring distribution in each of these three paradoxes. They also perform some experiments to directly measure the variance in offspring number, as well as perform some analyses of published data.

Strengths:

- The theoretical results are well-described and easy to follow.<br /> - The analyses of different variances in offspring number (both experimentally and analyzing public data) are convincing that non-Poissonian offspring distributions are the norm.<br /> - The point that this variance can change as the population size (or population dynamics) change is also very interesting and important to keep in mind.<br /> - I enjoyed the Density-Dependent Haldane model. It was a nice example of the decoupling of census size and effective size.<br /> - Equation (10) is a nice result (but see below)

Weaknesses:

- I am not convinced that these types of effects cannot just be absorbed into some time-varying Ne and still be well-modeled by the Wright-Fisher process. As a concrete example, Mohle and Sagitov 2001 show that a "coalescent Ne" for the WF model should be (N-1)/Var(K). This resolves the exponentially growing bacteria "paradox" raised in the present paper --- when the bacteria are growing Var(K) ~ 0, and hence there should be very little drift. This exactly resolves the "paradox" raised by the authors. Instead, it merely underscores that Ne does not need to be equal to (or even positively correlated!) with N. I absolutely do not see this as a failure of the WF model. Whether one finds branching processes or the WF model more biologically intuitive is a matter of taste, but to say that WF models cannot explain this "paradox" is false, when a well-known paper from more than 20 years ago does just that.<br /> - Along these lines, the result that Ne in the Wright-Fisher process might not be related to N in any straightforward (or even positively correlated) way are well-known (e.g., Neher and Hallatschek 2012; Spence, Kamm, and Song 2016; Matuszewski, Hildebrandt, Achaz, and Jensen 2018; Rice, Novembre, and Desai 2018; the work of Lounès Chikhi on how Ne can be affected by population structure; etc...)<br /> - I was also missing some discussion of the relationship between the branching process and the Wright-Fisher model (or more generally Cannings' Exchangeable Models) when conditioning on the total population size. In particular, if the offspring distribution is Poisson, then conditioned on the total population size, the branching process is identical to the Wright-Fisher model.<br /> - Given that Cannings' exchangeable models decouple N and Ne, it would not surprise me if something like equation (10) could be derived under such a model. I have not seen such a derivation, and the authors' result is nice, but I do not see it as proof that WF-type models (i.e., Cannings' models) are irreparably broken.

Reviewer #3 (Public review):

Authors first use rG-RPA to reproduce two observed trends. Caprin1 does not phase separate at very low salt but then undergoes LLPS with added salt while further addition of salt reduces its propensity to LLPS. On the other hand pY-Caprin1 exhibits a monotonic trend where the propensity to phase separate decreases with the addition of salt. This distinction is captured by a two component model and also when salt ions are explicitly modeled as a separate species with a ternary phase diagram. The predicted ternary diagrams (when co and counter ions are explicitly accounted for) also predict the tendency of ions to co-condense or exclude proteins in the dense phase. Predicted trends are generally in line with the measurement for Cparin1. Next, the authors seek to explain the observed difference in phase separation when Arginines are replaced by Lysines creating different variants. In the current rG-RPA type models both Arginine (R) and Lysine (K) are treated equally since non-electrostatic effects are only modeled in a mean-field manner that can be fitted but not predicted. For this reason, coarse grain MD simulation is suitable. Moreover, MD simulation affords structural features of the condensates. They used a force field that is capable of discriminating R and K. The MD predicted degrees of LLPS of these variants again is consistent with the measurement. One additional insight emerges from MD simulations that a negative ion can form a bridge between two positively charged residues on the chain. These insights are not possible to derive from rG-RPA. Both rG-RPA and MD simulation become cumbersome when considering multiple types of ions such as Na, Cl, [ATP] and [ATP-Mg] all present at the same time. FTS is well suited to handle this complexity. FTS also provides insights into the co-localization of ions and proteins that is consistent with NMR. By using different combinations of ions they confirm the robustness of the prediction that Caprin1 shows salt-dependent reentrant behavior, adding further support that the differential behavior of Caprin1, and pY-Caprin1 is likely to be mediated by charge-charge interactions.

Comments on revisions:

The authors addressed my comments and it is ready for publication.

Reviewer #3 (Public review):

Summary:

Zawieja et al. aimed to identify the pacemaker cells in the lymphatic collecting vessels. Authors have used various Cre-based expression systems and optogentic tools to identify these cells. Their findings suggest these cells are lymphatic muscle cells that drive the pacemaker activity in the lymphatic collecting vessels.

Strengths:

The authors have used multiple approaches to test their hypothesis. Some findings are presented as qualitative images, while some quantitative measurements are provided.

Weaknesses:

- More quantitative measurements.<br /> - Possible mechanisms associated with the pacemaker activity.<br /> - Membrane potential measurements.

Comments on revisions:

The authors have answered my comments with additional experiments, data and manuscript edits.

Reviewer #3 (Public review):

Summary:

The major novel finding in this study is that SFSWAP, a splicing factor containing an RS domain but no canonical RNA binding domain, functions as a negative regulator of splicing. More specifically, it promotes retention of specific introns in a wide variety of transcripts including transcripts from the OGT gene previously studied by the Conrad lab. The balance between OGT intron retention and OGT complete splicing is an important regulator of O-GlcNAc expression levels in cells.

Strengths:

An elegant CRISPR knockout screen employed a GFP reporter, in which GFP is efficiently expressed only when the OGT retained intron is removed (so that the transcript will be exported from the nucleus to allow for translation of GFP). Factors whose CRISPR knockdown causes decreased intron retention therefore increase GFP, and can be identified by sequencing RNA of GFP-sorted cells. SFSWAP was thus convincingly identified as a negative regulator of OGT retained intron splicing. More focused studies of OGT intron retention indicate that it may function by regulating a decoy exon previously identified in the intron, and that this may extend to other transcripts with decoy exons.

Weaknesses:

The mechanism by which SFSWAP represses retained introns is unclear, although some data suggests it can operate (in OGT) at the level of a recently reported decoy exon within that intron. Interesting/appropriate speculation about possible mechanisms are provided and will likely be the subject of future studies.

Overall the study is well done and carefully described but some figures and some experiments should be described in more detail.

Reviewer #3 (Public review):

Summary:

The authors of this study provide evidence that Drosophila immune cells show upregulated SAM transmethylation pathway and adenosine recycling upon wasp infection. Blocking this pathway compromises the lamellocyte formation, developmental delay, and host survival, suggesting its physiological relevance.

Strengths:

Snapshot quantification of the metabolite pool does not provide evidence that the metabolic pathway is active or not. The authors use an ex vivo isotope labelling to precisely monitor the SAM and adenosine metabolism. During infection, the methionine metabolism and adenosine recycling are upregulated, which is necessary to support the immune reaction. By combining the genetic experiment, they successfully show that the pathway is activated in immune cells.

Weaknesses:

The authors knocked down Ahcy to prove the importance of SAM methylation pathway. However, Ahcy-RNAi produces a massive accumulation of SAH, in addition to blocking adenosine production. To further validate the phenotypic causality, it is necessary to manipulate other enzymes in the pathway, such as Sam-S, Cbs, SamDC, etc. The authors do not demonstrate how infection stimulates the metabolic pathway given the gene expression of metabolic enzymes is not upregulated by infection stimulus.

Reviewer #3 (Public review):

Summary:

This study employed an implicit task, showing vignettes to participants while a bold signal was acquired. The aim was to capture automatic causal inferences that emerge during language processing and comprehension. In particular, the authors compared causal inferences about illness with two control conditions, causal inferences about mechanical failures and non-causal phrases related to illnesses. All phrases that were employed described contexts with people, to avoid animacy/inanimate confound in the results. The authors had a specific hypothesis concerning the role of the precuneus (PC) in being sensitive to causal inferences about illnesses.

These findings indicate that implicit causal inferences are facilitated by semantic networks specialized for encoding causal knowledge.

Strengths:

The major strength of the study is the clever design of the stimuli (which are nicely matched for a number of features) which can tease apart the role of the type of causal inference (illness-causal or mechanical-causal) and the use of two localizers (logic/language and mentalizing) to investigate the hypothesis that the language and/or logical reasoning networks preferentially respond to causal inference regardless of the content domain being tested (illnesses or mechanical).

Weaknesses:

I have identified the following main weaknesses:

(1) Precuneus (PC) and Temporo-Parietal junction (TPJ) show very similar patterns of results, and the manuscript is mostly focused on PC (also the abstract). To what extent does the fact that PC and TPJ show similar trends affect the inferences we can derive from the results of the paper? I wonder whether additional analyses (connectivity?) would help provide information about this network.

(2) Results are mainly supported by an univariate ROI approach, and the MVPA ROI approach is performed on a subregion of one of the ROI regions (left precuneus). Results could then have a limited impact on our understanding of brain functioning.

(3) In all figures: there are no measures of dispersion of the data across participants. The reader can only see aggregated (mean) data. E.g., percentage signal changes (PSC) do not report measures of dispersion of the data, nor do we have bold maps showing the overlap of the response across participants. Only in Figure 2, we see the data of 6 selected participants out of 20.

(4) Sometimes acronyms are defined in the text after they appear for the first time.

Reviewer #3 (Public review):

Valencia et al. aim to elucidate the biochemical and cellular mechanisms through which the human formin FHOD3 drives sarcomere assembly in cardiomyocytes. To do so, they combined rigorous in vitro biochemical assays with comprehensive in vivo characterizations, evaluating two wild-type FHOD3 isoforms and two function-separating mutants. Surprisingly, they found that both wild-type FHOD3 isoforms can nucleate new actin filaments, as well as elongate existing actin filaments in conjunction with profilin following barbed-end capping. This is in addition to FHOD3's proposed role as an actin bundler. Next, the authors asked whether FHOD3L promotes sarcomere assembly in cardiomyocytes through its activity in actin nucleation or rather elongation. With two function-separating mutants, the authors evaluated the numbers and morphology of sarcomeres, as well as their ability to beat and generate cardiac rhythm. The authors found that while the wild-type FHOD3L and the K1193L mutant can rescue sarcomere morphology and physiology, the GS-FH1 mutant fails to do so. Given that in GS-FH1 mainly elongation activity is compromised, the authors concluded that the elongation activity of FHOD3 is essential for its role in sarcomere assembly in cardiomyocytes, while its nucleator activity is dispensable. Overall, this important study provided a broadened view on the biochemical activities of FHOD3, and a pioneering view on a possible cellular mechanism of how FHOD3L drives sarcomere assembly. If further validated, this can lead to new mechanistic models of sarcomere assembly and potentially new therapeutic targets of cardiomyopathy.

The conclusions of this paper are mostly well supported by the comprehensive biochemical analyses performed by the authors. However, the sarcomere assembly defect phenotype in the GS-FH1 rescue condition requires further investigation, as the extremely low level of GS-FH1 signal in transfected cells in Figure 6A may reflect a failure of actin-binding by this construct in vivo, rather than its inability to drive elongation. Though the authors do show in Figure 6 that GS-FH1 can bind to normal-looking sarcomeres when they are present, this may be due to a lack of siRNA activity in these cells, such that endogenous FHOD3L is still present. In this possible scenario, GS-FH1 may dimerize with endogenous FHOD3L. The authors should demonstrate that GS-FH1 alone can indeed interact with existing actin filaments in vivo. While this has been clearly demonstrated in vitro, given the more complex biochemical environment in vivo where additional unknown binding partners may present, cautions should be made when extrapolating findings from the former to the latter.

Reviewer #3 (Public review):

Summary:

In this study, Seguchi & Izawa investigate the formation of male-male affiliative relationships within triads of large-billed crows. They then administered a vasopressin 1a receptor (V1aR) antagonist to either the dominant or subordinate individual within affiliative dyads, to examine whether blocking V1aR disrupts affiliative behavior. They discovered that affiliative dyads can be induced in large-billed crows by housing them in triads. They also found that blocking V1aRs significantly decreased allopreening (an affiliative behavior) within dyads. In addition, it increased aggression by dominant individuals and submissive calls by subordinate individuals.

Strengths:

This manuscript uses an especially interesting species - a highly intelligent and highly social corvid, with complex dominance hierarchies - to extend previous work into the effects of the oxytocin and vasopressin peptides hormones on social behaviors. The results are surprisingly clear, despite a small sample size. The authors use the correct statistical approaches to account for a complex, nested design. The introduction and discussion both reflect a strong understanding of the relevant literature, including the limitations of extrapolating from peripheral (intramuscular) versus central (into the brain) injections of the V1aR antagonist. In addition, the authors appear to have been transparent about the data and results, accounting for some of the challenges and limitations of the data and study.

Weaknesses:

There are two major concerns. First, the study has a very low sample size (8 triads for Experiment 1, and only 5 triads for Experiment 2). Despite the surprisingly convincing findings, the sample size is too small to support the claim that the vasopressin system "universally mediates same sex relationships. Secondly, the study does not account for the effects of V1aR on non-social behaviors. This is especially true because vasopressin/V1aR (and the particular antagonist used in this study) is known to have effects on osmotic balance, food intake, and stress, including in birds. My concern is that the behavioral effects could be accounted before by differences in general stress or activity levels. Allopreening is usually an activity performed in periods of relative inactivity with aggression being more characterized by high activity levels. The authors discuss these different effects of vasopressin/V1aR in the Discussion, but they do not account for these effects in the study design.

Reviewer #3 (Public Review):

Strengths:<br /> The study used optogenetics together with in vivo electrophysiology to monitor CGRP neuron activity in response to various aversive stimuli including robot chasing to determine whether they encode noxious stimuli differentially. The study used an interesting conditioning paradigm to investigate the role of CGRP neurons in the PBN in both freezing and flight behaviors.

Weakness:<br /> The major weakness of this study is that the chasing robot threat conditioning model elicits weak unconditioned and conditioned flight responses, making it difficult to interpret the robustness of the findings. Furthermore, the conclusion that the CGRP neurons are capable of inducing flight is not substantiated by the data. No manipulations are made to influence the flight behavior of the mouse. Instead, the manipulations are designed to alter the intensity of the unconditioned stimulus.

Reviewer #3 (Public review):

Summary:

This manuscript by Luo et al. applied SHAPE-Map to analyze the secondary structure of the Porcine Epidemic Diarrhoea Virus (PEDV) RNA genome in infected cells. By combining SHAPE reactivity and Shannon entropy, the study indicated that the folding of the PEDV genomic RNA was nonuniform, with the 5' and 3' untranslated regions being more compactly structured, which revealed potentially antiviral targetable RNA regions. Interestingly, the study also suggested that compounds bound to well-folded RNA structures in vitro did not necessarily exhibit antiviral activity in cells, because the binding of these compounds did not necessarily alter the functions of the well-folded RNA regions. Later in the manuscript, the authors focus on guanine-rich regions, which may form G-quadruplexes and be potential targets for small interfering RNA (siRNA). The manuscript shows the binding effect of Braco-19 (a G-quadruplex-binding ligand) to a predicted G4 region in vitro, along with the inhibition of PEDV proliferation in cells. This suggests that targeting high SHAPE-high Shannon G4 regions could be a promising approach against RNA viruses. Lastly, the manuscript identifies 73 single-stranded regions with high SHAPE and low Shannon entropy, which demonstrated high success in antiviral siRNA targeting.

Strengths:

The paper presents valuable data for the community. Additionally, the experimental design and data analysis are well documented.

Weakness:

The manuscript presents the effect of Braco-19 on PQS1, a single G4 region with high SHAPE and high Shannon entropy, to suggest that "the compound can selectively target the PQS1 of the high SHAPE-high Shannon region in cells" (lines 625-626). While the effect of Braco-19 on PQS1 is supported by strong evidence in the manuscript, the conclusion regarding the G4 region with high SHAPE and high Shannon entropy is based on a single target, PQS1.

Reviewer #3 (Public review):

Although insulin release is essential in the control of metabolism, adjusted to nutritional state, and plays major roles in normal brain function as well as in aging and disease, our knowledge about the activity of insulin-producing (and releasing) cells (IPCs) in vivo in limited.

In this technically demanding study, IPC activity is studied in the Drosophila model system by fine in vivo patch clamp recordings with parallel behavioral analyses and various optogenetic as well as feeding manipulations.

The data provide compelling evidence that IPC activity is increased with a slow time course after feeding a high glucose diet. By contrast, IPC activity is not directly affected by rising blood glucose levels. This is reminiscent of the incretin effect known from vertebrates and points to a conserved mechanism in insulin production and release upon sugar feeding.

Moreover, the data confirm earlier studies that nutritional state strongly affects locomotion. Surprisingly, strong evidence shows that IPC activity makes only a negligible contribution to this. Instead, other modulatory neurons that are directly sensitive to blood glucose levels strongly affect locomotion. Together, these data reveal a network of multiple parallel and interacting neuronal layers to orchestrate the physiological, metabolic, and behavioral responses to the nutritional state. Together with the data from a previous study, this work sets the stage to dissect the architecture and function of this network.

Strengths:

State-of-the-art current clamp in situ patch clamp recordings in behaving animals are a demanding but powerful method to provide novel insight into the interplay of nutritional state, IPC activity, and locomotion. The patch clamp recordings and the parallel behavioral analyses are of high quality, as are the optogenetic manipulations. The data showing that starvation silences IPC activity in young flies (younger than 1 week) are excellent. The evidence for the claim that locomotor activity is not increased upon IPC activity but upon the activity of other blood glucose sensitive modulatory neurons (Dh44) is compelling, too. The study provides a great system to experimentally dissect the interplay of insulin production and release with metabolism, physiology, nutritional state, and behavior. Demonstrating the incretin effect in Drosophila provides novel experimental routes to further study it. During the revision process, compelling evidence has been added to underscore the incretin effect, the finding that IPCs themselves do not sense sugars, and that feeding a high sugar diet does not cause unspecific stress responses.

I found no more weaknesses: The authors have carefully addressed all of my previous critiques by adding compelling new data and carefully revising the text. This paper provides a prime example of how responsible authors can utilize this constructive (but relatively new) reviewing procedure to make a very good manuscript even better.

Reviewer #3 (Public review):

This manuscript presents a meta-analysis of 23 studies, which report 297 effect sizes, on the effect of SO-spindle coupling on memory performance. The analysis has been done with great care, and the results are described in great detail. In particular, there are separate analyses for coupling phase, spindle amplitude, coupling strength (e.g., measured by vector length or modulation index), and coupling percentage (i.e., the percentage of SPs coupled with SOs). The authors conclude that the precision and strength of coupling showed significant correlations with memory retention.

There are two main points where I do not agree with the authors.

First, the authors conclude that "SO-SP coupling should be considered as a general physiological mechanism for memory consolidation". However, the reported effect sizes are smaller than what is typically considered a "small effect" (0.10<br /> Second, the study implements state-of-the-art Bayesian statistics. While some might see this as a strength, I would argue that it is the greatest weakness of the manuscript. A classical meta-analysis is relatively easy to understand, even for readers with only a limited background in statistics. A Bayesian analysis, on the other hand, introduces a number of subjective choices that render it much less transparent. This becomes obvious in the forest plots. It is not immediately apparent to the reader how the distributions for each study represent the reported effect sizes (gray dots). Presumably, they depend on the Bayesian priors used for the analysis. The use of these priors makes the analyses unnecessarily opaque, eventually leading the reader to question how much of the findings depend on subjective analysis choices (which might be answered by an additional analysis in the supplementary information). However, most of the methods are not described in sufficient detail for the reader to understand the proceedings. It might be evident for an expert in Bayesian statistics what a "prior sensitivity test" and a "posterior predictive check" are, but I suppose most readers would wish for a more detailed description. However, using a "Markov chain Monte Carlo (MCMC) method with the no-U-turn Hamiltonian Monte Carlo (HMC) sampler" and checking its convergence "through graphical posterior predictive checks, trace plots, and the Gelman and Rubin Diagnostic", which should then result in something resembling "a uniformly undulating wave with high overlap between chains" is surely something only rocket scientists understand. Whether this was done correctly in the present study cannot be ascertained because it is only mentioned in the methods and no corresponding results are provided. This kind of analysis seems not to be made to be intelligible to the average reader. It follows a recent trend of using more and more opaque methods. Where we had to trust published results a decade ago because the data were not openly available, today we must trust the results because the methods can no longer be understood with reasonable effort.

In one point the method might not be sufficiently justified. The method used to transform circular-linear r (actually, all references cited by the authors for circular statistics use r² because there can be no negative values) into "Z_r", seems partially plausible and might be correct under the H0. However, Figure 12.3 seems to show that under the alternative Hypothesis H1, the assumptions are not accurate (peak Z_r=~0.70 for r=0.65). I am therefore, based on the presented evidence, unsure whether this transformation is valid. Also, saying that Z_r=-1 represents the null hypothesis and Z_r=1 the alternative hypothesis can be misinterpreted, since Z_r=0 also represents the null hypothesis and is not half way between H0 and H1.

Reviewer #3 (Public review):

Summary:

The authors presented a data-centric ML approach for virtual ligand screening. They used BRAF as an example to demonstrate the predictive power of their approach.

Strengths:

The performance of predictive models in this study is superior (nearly perfect) with respect to exiting methods.

Comments on revisions:

In the revised manuscript, the presented approach has been robustly tested and can be very useful for ligand prediction.

Reviewer #3 (Public review):

Summary:

This study by Hu et al. examined the role of tachykinin1 (Tac1)-expressing neurons in the para subthalamic nucleus (PSTH) in active avoidance of electric shocks. Bulk recording of PSTH Tac1 neurons or axons of these neurons in PVT showed activation of a shock-predicting tone and shock itself. Ablation of these neurons or optogenetic manipulation of these neurons or their projection to PVT suggests the causality of this pathway with the learning of active avoidance.

Strengths:

This work found an understudied pathway potentially important for active avoidance of electric shocks. Experiments were thoroughly done and the presentation is clear. The amount of discussion and references are appropriate.

Weaknesses:

Critical control experiments are missing for most experiments, and statistical tests are not clear or not appropriate in most parts. Details are shown below.

(1) There are some control experiments missing. Notably, optogenetic manipulation is not verified in any experiments. It is important to verify whether neural activation with optogenetic activation is at the physiological level or supra-physiological level, and whether optogenetic inhibition does not cause unwanted activity patterns such as rebound activation at the critical time window.

(2) Neural ablation with caspase was confirmed by GFP expression. However, from the present description, a different virus to express EITHER caspase or GFP was injected, and then the numbers of GFP-expressing neurons were compared. It is not clear how this can detect ablation.

(3) In many places, statistical approaches are not clear from the present figures, figure legends, and Methods. It seems that most statistics were performed by pooling trials, but it is not described, or multiple "n" are described. For example, it is explicitly mentioned in Figure 4H, "n = 3 mice, n = 213 avoidance trials and n = 87 failure trials". The authors should not pool trials, but should perform across-animal tests in this and other figures, and "n" for statistical tests should be clearly described in each plot.

(4) It is also unclear how the test types were selected. For example, in Figure 1K and O with similar datasets, one is examined by a paired test and the other is by an unpaired test. Since each animal has both early vs late trials, and avoidance vs failure trials, paired tests across animals should be performed for both.

(5) It is also strange to show violin plots for only 6 animals. They should instead show each dot for each animal, connected with a line to show consistent increases of activity in late vs early trials and avoidance vs failure trials.

(6) To tell specificity in avoidance learning, it is better to show escape in the current trials with optogenetic manipulation.

(7) For place aversion, % time decrease across days was tested. It is better to show the original number before normalization, as well.

(8) For anatomical results in Figure S6, it is important to show images with lower magnification, too.

(9) Inactivation of either pathway from PSTH to PBN or to CeA also inhibits active avoidance, but the authors conclude that these effects are "partial" compared to the inactivation of PSTH to PVT. It is not clear how the effects were compared since the effects of PSTH-CeA inactivation are quite strong, comparable to PSTH-PVT inactivation by eye. They should quantify the effects to conclude the difference.

(10) Supplementary table 1: as mentioned above, n for statistical tests should be clearer.

Reviewer #3 (Public review):

Summary:

The article explores the role of mother-child interactions in the development of children's social cognition, focusing on Theory of Mind (ToM) and Social Pain Matrix (SPM) networks. Using a naturalistic fMRI paradigm involving movie viewing, the study examines relationships among children's neural development, mother-child neural synchronization, and interaction quality. The authors identified a developmental pattern in these networks, showing that they become more functionally distinct with age. Additionally, they found stronger neural synchronization between child-mother pairs compared to child-stranger pairs, with this synchronization and neural maturation of the networks associated with the mother-child relationship and parenting quality.

Strengths:

This is a well-written paper, and using dyadic fMRI and naturalistic stimuli enhances its ecological validity, providing valuable insights into the dynamic interplay between brain development and social interactions. However, I have some concerns regarding the analysis and interpretation of the findings. I have outlined these concerns below in the order they appear in the manuscript, which I hope will be helpful for the revision.

Weaknesses:

(1) Given the importance of social cognition in this study, please cite a foundational empirical or review paper on social cognition to support its definition. The current first citation is primarily related to ASD research, which may not fully capture the broader context of social cognition development.

(2) It is standard practice to report the final sample size in the Abstract and Introduction, rather than the initial recruited sample, as high attrition rates are common in pediatric studies. For example, this study recruited 50 mother-child dyads, and only 34 remained after quality control. This information is crucial for interpreting the results and conclusions. I recommend reporting the final sample size in the abstract and introduction but specifying in the Methods that an additional 16 mother-child dyads were initially recruited or that 50 dyads were originally collected.

(3) In the "Neural maturity reflects the development of the social brain" section, the authors report the across-network correlation for adults, finding a negative correlation between ToM and SPM. However, the cross-network correlations for the three child groups are not reported. The statement that "the two networks were already functionally distinct in the youngest group of children we tested" is based solely on within-network positive correlations, which does not fully demonstrate functional distinctness. Including cross-network correlations for the child groups would strengthen this conclusion.

(4) The ROIs for the ToM and SPM networks are defined based on previous literature, applying the same ROIs across all age groups. While I understand this is a common approach, it's important to note that this assumption may not fully hold, as network architecture can evolve with age. The functional ROIs or components of a network might shift, with regions potentially joining or exiting a network or changing in size as children develop. For instance, Mark H. Johnson's interactive specialization theory suggests that network composition may adapt over developmental stages. Although the authors follow the approach of Richardson et al. (2018), it would be beneficial to discuss this limitation in the Discussion. An alternative approach would be to apply data-driven analysis to justify the selection of the ROIs for the two networks.

(5) The current sample size (N = 34 dyads) is a limitation, particularly given the use of SEM, which generally requires larger samples for stable results. Although the model fit appears adequate, this does not guarantee reliability with the current sample size. I suggest discussing this limitation in more detail in the Discussion.

(6) Based on the above comment, I believe that conclusions regarding the relationship between social network development, parenting, and support for Bandura's theory should be tempered. The current conclusions may be too strong given the study's limitations.

(7) The SPM (pain) network is associated with empathic abilities, also an important aspect of social skills. It would be relevant to explore whether (or explain why) SPM development and child-mother synchronization are (or are not) related to parenting and the parent-child relationship.

Reviewer #3 (Public review):

Summary:

This work provides graphical tools for reconstructing the detailed anatomy of a nervous system from a series of sections imaged by electron microscopy. Contact between neuronal processes can direct outgrowth and is necessary for connectivity and, thus function. A bioinformatic approach is used to group neurons according to shared features (e.g., contact, synapses) in a hierarchy of "relatedness" that can be interrogated at each step. In this work, Koonze et al analyze vEM data sets for the C. elegans nerve ring (NR), a dense fascicle of processes from181 neurons. In a bioinformatic approach, the clustering algorithm Diffusion Condensation (DC) groups neurons according to similar cell biological features in iterations that remove chunks of differences in feature data with each step ultimately merging all NR neurons in one cluster. DC results are displayed with C-Phate a 3D visualization tool to produce a trajectory that can be interrogated for cell identities and other features at each iterative step. In previous work by these authors, this approach was utilized to identify subgroups of neuronal processes or "strata" in the NR that can be grouped by physical contact and connectivity. Here they expand their analysis to include a series of available vEM data sets across C. elegans larval development. This approach suggests that strata initially established during embryonic development are largely preserved in the adult. Importantly, exceptions involving stage-specific reorganization of neuronal placement in specific strata were also detected. A case study featured in the paper demonstrates the utility of this approach for visualizing the integration of newly generated neurons into the existing NR anatomy. Visualization tools used in this work are publicly available at NeuroSCAN.

Strengths:

A web-based app, NeuroSCAN, that individual researchers can use to interrogate the structure and organization of the C. elegans nerve ring across development

Weaknesses:

In the opinion of this reviewer, only minor revisions are required.

Reviewer #3 (Public review):

Summary:

In their study, McDermott et al. investigate the neurocomputational mechanism underlying sensory prediction errors. They contrast two accounts: representational sharpening and dampening. Representational sharpening suggests that predictions increase the fidelity of the neural representations of expected inputs, while representational dampening suggests the opposite (decreased fidelity for expected stimuli). The authors performed decoding analyses on EEG data, showing that first expected stimuli could be better decoded (sharpening), followed by a reversal during later response windows where unexpected inputs could be better decoded (dampening). These results are interpreted in the context of opposing process theory (OPT), which suggests that such a reversal would support perception to be both veridical (i.e., initial sharpening to increase the accuracy of perception) and informative (i.e., later dampening to highlight surprising, but informative inputs).

Strengths:

The topic of the present study is of significant relevance to the field of predictive processing. The experimental paradigm used by McDermott et al. is well designed, allowing the authors to avoid several common confounds in investigating predictions, such as stimulus familiarity and adaptation. The introduction of the manuscript provides a well-written summary of the main arguments for the two accounts of interest (sharpening and dampening), as well as OPT. Overall, the manuscript serves as a good overview of the current state of the field.

Weaknesses:

In my opinion, several details of the methods, results, and manuscript raise doubts about the quality and reliability of the reported findings. Key concerns are:

(1) The results in Figure 2C seem to show that the leading image itself can only be decoded with ~33% accuracy (25% chance; i.e. ~8% above chance decoding). In contrast, Figure 2E suggests the prediction (surprisingly, valid or invalid) during the leading image presentation can be decoded with ~62% accuracy (50% chance; i.e. ~12% above chance decoding). Unless I am misinterpreting the analyses, it seems implausible to me that a prediction, but not actually shown image, can be better decoded using EEG than an image that is presented on-screen.

(2) The "prediction decoding" analysis is described by the authors as "decoding the predictable trailing images based on the leading images". How this was done is however unclear to me. For each leading image decoding the predictable trailing images should be equivalent to decoding validity (as there were only 2 possible trailing image categories: 1 valid, 1 invalid). How is it then possible that the analysis is performed separately for valid and invalid trials? If the authors simply decode which leading image category was shown, but combine L1+L2 and L4+L5 into one class respectively, the resulting decoder would in my opinion not decode prediction, but instead dissociate the representation of L1+L2 from L4+L5, which may also explain why the time-course of the prediction peaks during the leading image stimulus-response, which is rather different compared to previous studies decoding predictions (e.g. Kok et al. 2017). Instead for the prediction analysis to be informative about the prediction, the decoder ought to decode the representation of the trailing image during the leading image and inter-stimulus interval. Therefore I am at present not convinced that the utilized analysis approach is informative about predictions.

(3) I may be misunderstanding the reported statistics or analyses, but it seems unlikely that >10 of the reported contrasts have the exact same statistic of Tmax= 2.76. Similarly, it seems implausible, based on visual inspection of Figure 2, that the Tmax for the invalid condition decoding (reported as Tmax = 14.903) is substantially larger than for the valid condition decoding (reported as Tmax = 2.76), even though the valid condition appears to have superior peak decoding performance. Combined these details may raise concerns about the reliability of the reported statistics.

(4) The reported analyses and results do not seem to support the conclusion of early learning resulting in dampening and later stages in sharpening. Specifically, the authors appear to base this conclusion on the absence of a decoding effect in some time-bins, while in my opinion a contrast between time-bins, showing a difference in decoding accuracy, is required. Or better yet, a non-zero slope of decoding accuracy over time should be shown (not contingent on post-hoc and seemingly arbitrary binning).

(5) The present results both within and across trials are difficult to reconcile with previous studies using MEG (Kok et al., 2017; Han et al., 2019), single-unit and multi-unit recordings (Kumar et al., 2017; Meyer & Olson 2011), as well as fMRI (Richter et al., 2018), which investigated similar questions but yielded different results; i.e., no reversal within or across trials, as well as dampening effects with after more training. The authors do not provide a convincing explanation as to why their results should differ from previous studies, arguably further compounding doubts about the present results raised by the methods and results concerns noted above.

Impact:

At present, I find the potential impact of the study by McDermott et al. difficult to assess, given the concerns mentioned above. Should the authors convincingly answer these concerns, the study could provide meaningful insights into the mechanisms underlying perceptual prediction. However, at present, I am not entirely convinced by the quality and reliability of the results and manuscript. Moreover, the difficulty in reconciling some of the present results with previous studies highlights the need for more convincing explanations of these discrepancies and a stronger discussion of the present results in the context of the literature.

Reviewer #3 (Public review):

This study investigates how effort influences reward evaluation during prosocial behaviour using EEG and experimental tasks manipulating effort and rewards for self and others. Results reveal a dissociable effect: for self-benefitting effort, rewards are evaluated more positively as effort increases, while for other-benefitting effort, rewards are evaluated less positively with higher effort. This dissociation, driven by reward system activation and independent of performance, provides new insights into the neural mechanisms of effort and reward in prosocial contexts.

This work makes a valuable contribution to the prosocial behaviour literature by addressing areas that previous research has largely overlooked. It highlights the paradoxical effect of effort on reward evaluation and opens new avenues for investigating the mechanisms underlying this phenomenon. The study employs well-established tasks with robust replication in the literature and innovatively incorporates ERPs to examine effort-based prosocial decision-making - an area insufficiently explored in prior work. Moreover, the analyses are rigorous and grounded in established methodologies, further enhancing the study's credibility. These elements collectively underscore the study's significance in advancing our understanding of effort-based decision-making.

Despite these contributions, there are several gaps in the analysis that leave the conclusions incomplete and warrant further investigation. These issues can be summarized as follows:

(1) Incomplete EEG Reporting: The methods indicate that EEG activity was recorded for both tasks; however, the manuscript reports EEG results only for the first task, omitting the decision-making task. If the authors claim a paradoxical effect of effort on self versus other rewards, as revealed by the RewP component, this should also be confirmed with results from the decision-making task. Omitting these findings weakens the overall argument.

(2) Neural and Behavioural Integration: The neural results should be contrasted with behavioural data both within and between tasks. Specifically, the manuscript could examine whether neural responses predict performance within each task and whether neural and behavioural signals correlate across tasks. This integration would provide a more comprehensive understanding of the mechanisms at play.

(3) Success Rate and Model Structure: The manuscript does not clearly report the success rate in the prosocial effort task. If success rates are low, risk aversion could confound the results. Additionally, it is unclear whether the models accounted for successful versus unsuccessful trials or whether success was included as a covariate. If this information is present, it needs to be explicitly clarified. The exclusion criteria for unsuccessful trials in both tasks should also be detailed. Moreover, the decision to exclude electrodes as independent variables in the models warrants an explanation.

(4) Prosocial Decision Computational Modelling: The prosocial decision task largely replicates prior behavioural findings but misses the opportunity to directly test the hypotheses derived from neural data in the prosocial effort task. If the authors propose a paradoxical effect of effort on self-rewards and an inverse effect for prosocial effort, this could be formalised in a computational model. A model comparison could evaluate the proposed mechanism against alternative theories, incorporating the complex interplay of effort and reward for self and others. Furthermore, these parameters should be correlated with neural signals, adding a critical layer of evidence to the claims. As it is, the inclusion of the prosocial decision task seems irrelevant.

(5) Contradiction Between Effort Perception and Neural Results: Participants reported effort as less effortful in the prosocial condition compared to the self condition, which seems contradictory to the neural findings and the authors' interpretation. If effort has a discounting effect on rewards for others, one might expect it to feel more effortful. How do the authors reconcile these results? Additionally, the relationship between behavioural data and neural responses should be examined to clarify these inconsistencies.

Necessary Revisions to Manuscript: If the authors address the issues above, corresponding updates to the introduction and discussion sections could strengthen the narrative and align the manuscript with the additional analyses.

Reviewer #3 (Public review):

Summary:

The authors use Alphafold2, Rosetta, and Molecular Dynamics to model structures of the hERG K channel in open, inactive, and closed states. Experimental CryoEM data for open hERG (Wang and Mackinnon 2017), and closed EAG (Mandala and Mackinnon, 2002) were used as the main templates for channel models presented here. Given the importance of hERG as a safety pharmacology target, the identification of a robust simulation method to assess drug block is an important addition to the field.

Strengths

The key findings here are new inactivated and closed hERG channel conformations and hERG channel conformations with drugs docked in the inner vestibule below the selectivity filter. Amino acid pathways and interaction networks for different states are also presented.

The inactive state and drug block models are carefully correlated with experimental data for the inactivated state of hERG (Lau et al, 2024) and with experimental free energy data for drug binding and have overall good agreement.

It is remarkable that using cytoplasmic domain structures of hERG as a starting point revealed inactivation state structures in the hERG selectivity filter in Figures 2,3.

Weaknesses

Figure 6, if each data point is for a different drug, then perhaps identify each point.

The PAS domain was not included in the models as stated in Methods page 14 but the PAS does appear in some of the templates used as starting points for models in Figure 1 a,b,c. Perhaps mentioning that the PAS was not included in some (all?) of the final models should be moved into the main text and discussed.

The drug block of 1b channels (which do not contain PAS) has been reported to be slightly different than that for 1a channels (which contain PAS) and for 1a/1b channels (see London et al., 1997; https://doi.org/10.1161/01.RES.81.5.870 and Abi-Gerges et. al., 2011; DOI: 10.1111/j.1476-5381.2011.01378.x) and this should be discussed since the models presented here appear to be performed in the absence of the PAS.

It also appears that the N-linker region (between PAS and the S1) and distal C region of hERG (post CNBHD-COOH) are not included in models, please state this if correct, and discuss.

Reviewer #3 (Public review):

Summary:

The manuscript presents a detailed study on the role of MmMYL3 in the viral entry of NNV, focusing on its function as a receptor that mediates viral internalization through the macropinocytosis pathway. The use of both in vitro assays (e.g., Co-IP, SPR, and GST pull-down) and in vivo experiments (such as infection assays in marine medaka) adds robustness to the evidence for MmMYL3 as a novel receptor for RGNNV. The findings have important implications for understanding NNV infection mechanisms, which could pave the way for new antiviral strategies in aquaculture.

Strengths:

The authors show that MmMYL3 directly binds the viral capsid protein, facilitates NNV entry via the IGF1R-Rac1/Cdc42 pathway, and can render otherwise resistant cells susceptible to infection. This multifaceted approach effectively demonstrates the central role of MmMYL3 in NNV entry.