Joint Public Review:

The authors present a carefully controlled set of experiments that demonstrate an additional complexity for GPCR signaling in that endosomal signaling may be different when beta-arrestin is or isn't associated with a G protein-bound V2 vasopressin receptor. It uses state of the art biosensor-based approaches and beta-arrestin KO lines to assess this. It adds to a growing body of evidence that G proteins and beta-arresting can associate with GPCR complexes simultaneously. They also demonstrate the possibility that Gq might also be activated by the V2 receptor. My sense is one thing they may need to be considered is the possibility of such "megacomplexes" might actually involve receptor dimers or oligomers. They have added significant amounts of new data to address concerns I had about the sole use of mini-genes to assess G protein coupling and broadened discussions about the possible mechanisms underlying their observations. I would still argue that receptor oligomers are a more obvious way for such megacomplexes to be organized around.

Reviewer #1 (Public Review):

Summary:<br /> This manuscript by Estevam et al. reports new insights into the regulation of the receptor tyrosine kinase MET gained from two deep mutational scanning (DMS) datasets. In this paper, the authors use a classic selection system for oncogenic kinase signaling, the murine Ba/F3 cell line, to assess the functional effects of thousands of mutations in the kinase domains of MET in two contexts: (1) fusion of the whole MET intracellular region to the dimerization domain TPR, and (2) the same fusion protein, but with exon 14, which encodes part of the juxtamembrane region of MET, skipped. Critically, exon 14 skipping yields a version of MET that is found in many cancers and has higher signaling activity than the canonical MET isoform. The authors extensively analyze their DMS data to very convincingly show that their selection assay reports on kinase activity, by illustrating that many functionally important structural components of the kinase domain are not tolerant of mutation. Then, they turn their attention to a helical region of the juxtamembrane region (αJM), immediately after exon 14, which is posited to play a regulatory role in MET. Their DMS data illustrate that the strength and mutational tolerance of interactions between αJM and the key αC helix in the kinase domain depends on the presence or absence of exon 14. They also identify residues in the N-lobe of the kinase, such as P1153, which are not conserved across tyrosine kinases but appear to be essential for MET and MET-like kinases. Finally, the authors analyze their DMS data in the context of clinically-observed mutations and drug-resistance mutations.

Overall, this manuscript is exciting because it provides new insights into MET regulation in general, as well as the role of exon 14. It also reveals ways in which the JM region of MET is different from that of many other receptor tyrosinekinases. The exon 14-skipped fusion protein DMS data is somewhat underexplored and could be discussed in greater detail, which would elevate excitement about the work. Furthermore, some of the cell biological validation experiments and the juxtaposition with clinical data are perhaps not assessed/interpreted as clearly they could be. Some constructive suggestions are given below to enhance the impact of the manuscript.

Strengths:<br /> The main strengths of this paper, also summarized above in the summary, are as follows:

1. The authors very convincingly show that Ba/F3 cells can be coupled with deep mutational scanning to examine MET mutational effects. This is most clearly shown by highlighting how all of the known kinase structure and regulatory elements are highly sensitive to mutations, in accordance with a few other DMS datasets on other kinases.

2. A highlight of this paper is the juxtaposition of two DMS datasets for two different isoforms of the MET receptor. Very few comparisons like this exist in the literature, and they show how small changes to the overall architecture of a protein can impact its regulation and mutational sensitivity.

3. Another exciting advance in this manuscript is the deep structural analysis of the MET juxtamembrane region with respect to that of other tyrosine kinases - guided by the striking effect of mutations in the juxtamembrane helical region. The authors illustrate how the JM region of MET differs from that of other tyrosine kinases.

4. Overall, this manuscript will provide a resource for interpreting clinically relevant MET mutations.

Weaknesses:<br /> 1. The manuscript is front-loaded with extensive analysis of the first DMS dataset, in which exon 14 is present, however, the discussion and analysis of the exon 14-skipped dataset is somewhat limited. In particular, a deeper discussion of the differences between the two datasets is warranted, to lay out the full landscape of mutations that have different functional consequences in the two isoforms. Rather, the authors only focus on differences in the JM region. What are the broader structural effects of exon 14 skipping across the whole kinase domain?

2. It is unclear if gain-of-function mutations can actually be detected robustly in this specific system. This isn't a problem at face value, as different selection assays have different dynamic ranges. However, the authors don't discuss the statistical significance and reproducibility of gain- vs loss-of-function mutations, and none of the gain-of-function mutations are experimentally validated (some appear to show loss-of-function in their cellular validation assay with full-length MET). The manuscript would benefit from deeper statistical analysis (and discussion in the text) of gain-of-function mutations, as well as further validation of a broad range of activity scores in a functional assay. For the latter point, one option would be to express individual clones from their library in Ba/F3 cells and blot for MET activation loop phosphorylation (which is probably a reasonable proxy for activity/activation).

3. In light of point 2, above, much of the discussion about clinically-relevant gain-of-function mutations feels a bit stretched - although this section is definitely very interesting in premise. A clearer delineation of gain-of-function, with further statistical support and ideally also some validation, would greatly strengthen the claims in this section.

Reviewer #2 (Public Review):

Summary:<br /> The authors describe a deep mutational scanning (DMS) study of the kinase domain of the c-MET receptor tyrosine kinase. The screen is conducted with a highly activated fusion oncoprotein - Tpr-MET - in which the MET kinase domain is fused to the Tpr dimerization element. The mutagenized region includes the entire kinase domain and an alpha-helix in the juxtamembrane region that is essentially part of the MET kinase domain. The DMS screen is carried out in two contexts, one containing the entire cytoplasmic region of MET, and the other with an "exon 14 deletion" which removes a large portion of the juxtamembrane region (but retains the aforementioned alpha-helix). The work provides a robust and essentially exhaustive catalog of the effect of mutations (within the kinase domain) on the ability of the Tpr-MET fusion oncoproteins to drive IL3-independent growth of Ba/F3 cells. Every residue in the kinase is mutated to every natural amino acid. Given the design of the screen, one would expect it to be a powerful tool for identifying mutations that impair catalytic activity and therefore impair IL3-independent proliferation, but not the right tool for identifying gain-of-function mutations that operate by shifting the kinase from an inactive to active state (because the Tpr-Met fusion construct is already very highly activated). This is borne out by the data, which reveal many many deleterious mutations and few "gain-of-function" mutations (which are of uncertain significance, as discussed below).

Strengths:<br /> The authors take a very scholarly and thorough approach to interpreting the effect of mutations in light of available information for the structure and regulation of MET and other kinases. They examine the effect of mutations in the so-called catalytic (C) and regulatory (R) spines, the interface between the JM alpha-helix and the C-helix, the glycine-rich loop, and other key elements of the kinase, providing a structural rationale for the deleterious effect of mutations. Comparison of the panoply of deleterious mutations in the TPR-met versus TPR- exon14del-MET DMS screens reveals an interesting difference - the exon14 deletion MET is much more tolerant of mutations in the JM alpha-helix/C-helix interface. The reason for this is unclear, however.

Weaknesses:<br /> Because the screens were conducted with highly active Tpr-MET fusions, they have limited power to reveal gain-of-function mutations. Indeed, to the extent that Tpr-MET is as active or even more active than ligand-activated WT MET, one could argue that it is "fully" activated and that any additional gain of fitness would be "super-physiologic". I would expect such mutations to be rare (assuming that they could be detected at all in the Ba/F3 proliferation assay). Consistent with this, the authors note that gain-of-function mutations are rare in their screen (as judged by being more fit than the average of synonymous mutations). In their discussion of cancer-associated mutations, they highlight several "strong GOF variants in the DMS". It is unclear what the authors mean by "strong GOF", indeed it is unclear to this reviewer whether the screen has revealed any true gain of function mutations at all. A few points in this regard:

1) more active than the average of synonymous mutations (nucleotide changes that have no effect on the sequence of the expressed protein) seems to be an awfully low bar for GOF - by that measure, several synonymous mutations would presumably be classified as GOF.

2) In the +IL3 heatmap in supplemental Figure 1A, there is as much or more "blue" indicating GOF as in the -IL3 heatmap, which could suggest that the observed level of gain in fitness is noise, not signal.

3) And finally, consistent with this interpretation, in Supplemental Figure 1C, comparing the synonymous and missense panels in the IL3 withdrawal condition suggests that the most active missense mutations (characterized here as strong GOF) are no more active than the most active synonymous mutations.

My other major concern with the work as presented is that the authors conflate "activity" and "activation" in discussing the effects of mutations. "Activation" implies a role in regulation - affecting a switch between inactive and active conformations or states - at least in this reviewer's mind. As discussed above, the screen per se does not probe activation, only activity. To the extent that the residues discussed are important for activation/regulation of the kinase, that information is coming from prior structural/functional studies of MET and other kinases, not from the DMS screen conducted here. Of course, it is appropriate and interesting for the authors to consider residues that are known to form important structural/regulatory elements, but they should be careful with the use of activity vs. activation and make it clear to the reader that the screen probes the former. One example - in the abstract, the authors rightly note that their approach has revealed a critical hydrophobic interaction between the JM segment and the C-helix, but then they go on to assert that this points to differences in the regulation of MET and other RTKs. There is no evidence that this is a regulatory interaction, as opposed to simply a structural element present in MET (and indeed the authors' examination of prior crystal structures shows that the interaction is present in both active and inactive states.

Reviewer #1 (Public Review):

Summary:<br /> The article by Siachisumo, Luzzi and Aldalaquan et al. describes studies of RBMX and its role in maintaining proper splicing of ultra-long exons. They combine CLIP, RNA-seq, and individual example validations with manipulation of RBMX and its family members RBMY and RBMXL2 to show that the RBMX family plays a key role in maintaining proper splicing of these exons.

Strengths:<br /> I think one of the main strengths of the manuscript is its ability to explore a unique but interesting question (splicing of ultra-long exons), and derive a relatively simple model from the resulting genomics data. The results shown are quite clean, suggesting that RBMX plays an important role in the proper regulation of these exons. The ability of family members to rescue this phenotype (as well as only particular domains) is also quite intriguing and suggests that the mechanisms for keeping these exons properly spliced may be a quite important and highly conserved mechanism.

Weaknesses:<br /> I think my main critique is that a lot of the conclusions in the text are written with very broad and general claims, but these are often based on either a small number of examples or a non-transcriptome-wide analysis that I think would be necessary for such broad conclusions. For example, pg 5 - "The above data indicated that RBMX has a major role in repressing cryptic splicing patterns in human somatic cells." is based on seeing ~120 exons with a 2:1 ratio of exclusion to inclusion (and doesn't include analysis confirming which of these are cryptic). Similarly, on page 15, line 31 "The above experiments showed that RBMXL2 is able to globally replace RBMX activity" and Fig 5 as well - I think the 'globally' term here is a bit too much with most of the analysis derived from n=3 events.

Another weakness I think is the lack of context in the paper, where the basic description of how many 'long' and 'ultra-long' exons there are and what percent of those are bound by and/or regulated by RBMX is missing. The text (including the title, which to me is written to imply a general role for ultra-long exons') seems to imply that RBMX maintains proper splicing of ultra-long exons globally (which to me implies a significant percent of them), but I don't think the manuscript succeeds in strongly proving this global role.

Along those same lines, I think the manuscript claims that the described principles are specific to the RBMX family, but I think the lack of negative examples weakens the strength of this claim. For example, for Figure 2 (D/E/F/G), what I think would make this more powerful is a negative example - if you take CLIP + knockdown/RNA-seq data for a different splicing regulator (RBFOX2, PTBP1, etc.), do you not see this size difference? I think the analysis described here is sufficient to show that there is an overlap for RBMX, but I think this would make it much stronger in confirming it's not just a 'longer genes get more CLIP tags' artifact.

Reviewer #2 (Public Review):

Summary:<br /> One of the greatest challenges for the spliceosome is to be able to repress the many cryptic splice sites that can occur in both the intronic and exotic sequences of genes. Although many studies have focused on cryptic signals in introns (because of their common involvement in disease) the question still remained open as to the factors that repress cryptic exons in exons. Because exons are normally much shorter than introns, in many cases the problem does not exist. However, in human genes, a significant proportion of exons can be considerably longer than the average 150 nt length and this raises the question of how cryptic splicing can be prevented in long exons. To address this question, the authors have focused on the possible role played by an ancient mammalian RBD protein called RBMX. Using a combination of high-throughput and classic splicing methodologies, they have shown that there is a class of RBMX-dependent ultra-long exons connected where the RBMX, RBMXL2, and RBMY paralogs have closely related functional activity in repressing cryptic splice site selection.

Strengths:<br /> In general, the present work sheds light on what has been a rather understudied process in splicing research. The use of iCLIP and RNA-seq data has not only allowed us to identify the long exons where cryptic splicing is prevented by the RBMX proteins but has also allowed us to identify a network of genes mostly involved in genome stability and transcriptional control where these proteins seem to play a prominent role. This can therefore also shed additional information on the way splicing has shaped evolutionary processes in the mammalian lineage and will therefore be of interest to many researchers in this field.

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

Reviewer #3 (Public Review):

The manuscript by Siachisumo et al builds upon a previous publication from the same group of collaborators that showed that depletion of mouse RBMXL2 leads to a block in spermatogenesis associated with mis-splicing, particularly of large exons in genes associated with genome stability (Ehrmann et al eLife 2019). RBMXL2 is an RNA-binding protein and an autosomal retrotransposed paralog of the X-chromosomally encoded RBMX. RBMXL2 is expressed during meiosis when RBMX and the more distantly related RBMY (on the Y chromosome) are silenced. It is therefore an appealing hypothesis that RBMXL2 might provide cover for RBMX function during meiosis. To address this hypothesis the authors analysed the transcriptomic consequences of RBMX depletion by RNA-Seq in human cells (MDA-MB-231 and existing RNA-Seq data from HEK293 cells), complemented by iCLIP to analyze the binding targets of FLAG-tagged RBMX in HEK293 cells. The findings convincingly demonstrate that - like RBMXL2 - RBMX mainly acts as a splicing repressor and that it particularly acts to protect the integrity of very long ("ultra-long") exons. Upon RBMX depletion, many of these exons are shortened due to the use of cryptic 5' and/or 3' splice sites. Moreover, affected genes are particularly enriched for functions associated with genome integrity - indeed "comet assays" show that RBMX depletion leads to DNA damage defects.

The manuscrupt therefore delivers a clear affirmative answer to the question of whether the two highly related proteins have similar molecular functions, particularly with respect to suppressing cryptic splicing that affects ultra-long exons. This conclusion is reinforced by the ability of induced expression of either RBMXL2 or RBMY to fully complement the effects of RBMX knockdown upon three target events in the ETAA1, REV3L, and ATRX genes.

The manuscript also includes some experiments that address more mechanistic questions, such as the potential for RBMX to block access of spliceosome components to splice site elements and structure-function analyses of RBMX. These areas have a distinctly "preliminary" feel to them. For example, for one target (ETAA1) it is shown that CLIP tags are close to mapped branchpoints. However, no attempt is made to integrate the RNA-Seq and iCLIP data-sets to look for more generalized relationships between binding and activity. Likewise, one experiment shows that the RRM domain of RBMXL2 is not necessary for activity. Given that the RRM domain represents only ~25% of the total RBMXL2 sequence, this is a somewhat preliminary, albeit interesting, observation. Another surprising omission was that there was no global comparison of the consequences of RBMX depletion and complementation by RBMXL2, despite the fact that the relevant RNA-Seq data-sets had been generated (Figure 4 supplement 1 shows RNA-Seq IGV tracks that confirm the effects on ETAA1, REV3L and ATRX shown by RT-PCR in Figure 4).

In summary, this manuscript provides clear evidence to support the role of RBMX as a repressor of cryptic splice sites in ultra-long exons, similar to RBMXL2.

Reviewer #1 (Public Review):

Summary:<br /> Here, Boor et al focus on the regulation of daf-7 transcription in the ASJ chemosensory neurons, which has previously been shown to be sensitive to a variety of external and internal signals. Interestingly, they find that soluble (but not volatile) signals released by food activate daf-7 expression in ASJ, but that this is counteracted by signals from the ASIC channels del-3 and del-7, previously shown to detect the ingestion of food in the pharynx. Importantly, the authors find that ASJ-derived daf-7 can promote exploration, suggesting a feedback loop that influences locomotor states to promote feeding behavior. They also implicate signals known to regulate exploratory behavior (the neuropeptide receptor PDFR-1 and the neuromodulator serotonin) in the regulation of daf-7 expression in ASJ. Additionally, they identify a novel role for a pathway previously implicated in C. elegans sensory behavior, HEN-1/SCD-2, in the regulation of daf-7 in ASJ, suggesting that the SCD-2 homolog ALK may have a conserved role in feeding and metabolism.

Strengths:<br /> The studies reported here, particularly the quantitation of gene expression and the careful behavioral analysis, are rigorously done and interpreted appropriately. The results suggest that, with respect to food, DAF-7 expression encodes a state of "unmet need" - the availability of nearby food to animals that are not currently eating. This is an interesting finding that reinforces and extends our understanding of the neurobiological significance of this important signaling pathway. The identification of a role for ASJ-derived daf-7 in motor behavior is a valuable advance, as is the finding that SCD-2 acts in the AIA interneurons to influence daf-7 expression in ASJ.

Weaknesses:<br /> A limitation of the work is that some mechanistic relationships between the identified signaling pathways are not carefully examined, but this provides interesting opportunities for future work. A minor weakness concerns the experiment in which daf-7 is conditionally deleted from ASJ. This is an ideal approach for probing the function of daf-7, but these experiments seem to be carried out in the well-fed, on-food condition in which control animals should express little or no daf-7 in ASJ. Thus, the experimental design does not allow an assessment of the role of daf-7 under conditions in which its expression is activated (e.g., in animals exposed to un-ingestible food). An additional minor issue concerns the interpretation of the scd-2 experiments. The authors' findings do support a role for scd-2 signaling in the activation of daf-7 expression by un-ingestible food, but the data also suggest that scd-2 signaling is not essential for this effect, as there is still an effect in scd-2 mutants (Figure 4B).

Reviewer #2 (Public Review):

Summary:<br /> In this work, Boor and colleagues explored the role of microbial food cues in the regulation of neuroendocrine-controlled foraging behavior. Consistent with previous reports, the authors find that C. elegans foraging behavior is regulated by the neuroendocrine TGFβ ligand encoded by daf-7. In addition to its known role in the neuroendocrine/sensory ASI neurons, Boot and colleagues show that daf-7 expression is dynamically regulated in the ASJ sensory neurons by microbial food cues - and that this regulation is important for exploration/exploitation balance during foraging. They identify at least two independent pathways by which microbial cues regulate daf-7 expression in ASJ: a likely gustatory pathway that promotes daf-7 expression and an opposing interoceptive pathway, also likely chemosensory in nature but which requires microbial ingestion to inhibit daf-7 expression. Two neuroendocrine pathways known to regulate foraging (serotonin and PDF-1) appear to act at least in part via daf-7 induction. They further identify a novel role for the C. elegans ALK orthologue encoded by scd-2, which acts in interneurons to regulate daf-7 expression and foraging behavior. These results together imply that distinct cues from microbial food are used to regulate the balance between exploration and exploitation via conserved signaling pathways.

Strengths:<br /> The findings that gustatory and interoceptive inputs into foraging behavior are separable and opposing are novel and interesting, which they have shown clearly in Figure 1. It is also clear from their results that removal of the interoceptive cue (via transfer to non-digestible food) results in rapid induction of daf-7::gfp in ASJ, and that ASJ plays an important role in the regulation of foraging behavior.

The role of the hen-1/scd-2 pathway in mediating the effects of ingested food is also compelling and well-interpreted. The use of precise gain-of-function alleles further supports their conclusions. This implies that important elements of this food-sensing pathway may be conserved in mammals.

Weaknesses:<br /> What is less clear to me from the work at this stage is how the gustatory input fits into this picture and to what extent can it be strongly concluded that the daf-7-regulating pathways that they have identified (del-3/7, 5-HT, PDFR-1, scd-2) act via the interoceptive pathway as opposed to the gustatory pathway. It follows from the work of the Flavell lab that del-3/7 likely acts via the interoceptive pathway in this context as well but this isn't shown directly - e.g. comparing the effects of aztreonam-treated bacteria and complete food removal to controls. The roles of 5-HT and PDFR-1 are even a bit less clear. Are the authors proposing that these are entirely parallel pathways? This could be explained in better detail.

It would also be helpful to elaborate more on why the identified transcriptional positive feedback loop is predicted to extend roaming state duration - as opposed to some other mechanism of increasing roaming such as increased probability of roaming state initiation. This doesn't seem self-evident to me. Related to this point is the somewhat confusing conclusion that the effects of tph-1 and pdfr-1 mutations on daf-7 expression are due to changes in ingestion during roaming/dwelling. From my understanding (e.g. Cermak et al., 2020), pharyngeal pumping rate does not reliably decrease during roaming - so is it clear that there are in fact lower rates of ingestion during roaming in their experiments? If so, why does increased roaming (via tph-1 mutation) result in further increases in daf-7 expression in animals fed aztreonam-treated food (Fig 3B)? Alternatively, there could be a direct signaling connection between the 5-HT/PDFR-1 pathways and daf-7 expression which could be acknowledged or explained.

Reviewer #3 (Public Review):

Summary:<br /> In this interesting study, the authors examine the function of a C. elegans neuroendocrine TGF-beta ligand DAF-7 in regulating foraging movement in response to signals of food and ingestion. Building on their previous findings that demonstrate the critical role of daf-7 in a sensory neuron ASJ in behavioral response to pathogenic P. aeruginosa PA14 bacteria and different foraging behavior between hermaphrodite and male worms, the authors show, here, that ingestion of E. coli OP50, a common food for the worms, suppresses ASJ expression of daf-7 and secreted water-soluble cues of OP50 increases it. They further showed that the level of daf-7 expression in ASJ is positively associated with a higher level of roaming/exploration movement. Furthermore, the authors identify that a C. elegans ortholog of Anaplastic Lymphoma Kinase, scd-2, functions in an interneuron AIA to regulate ASJ expression of daf-7 in response to food ingestion and related cues. These findings place the DAF-7 TGF-beta ligand in the intersection of environmental food conditions, food intake, and food-searching behavior to provide insights into how orchestrated neural functions and behaviors are generated under various internal and external conditions.

Strengths:<br /> The study addresses an important question that appeals to a wide readership. The findings are demonstrated by generally strong results from carefully designed experiments.

Weaknesses:<br /> However, a few questions remain to provide a complete picture of the regulatory pathways and some analyses need to be strengthened. Specifically,

1. The authors show that diffusible cues of bacteria OP50 increase daf-7 expression in ASJ which is suppressed by ingestible food. Their results on del-3 and del-7 suggest that NSM neuron suppresses daf-7 ASJ expression. What sensory neurons respond to bacterial diffusible cues to increase daf-7 expression of ASJ? Since ASJ is able to respond to some bacterial metabolites, does it directly regulate daf-7 expression in response to diffusible cues of OP50 or does it depend on neurotransmission for the regulation? Some level of exploration in this question would provide more insights into the regulatory network of daf-7.

2. The results including those in Figure 2 strongly support that daf-7 in ASJ is required for roaming. Meanwhile, authors also observe increased daf-7 expression in ASJ under several conditions, such as non-ingestible food. Does non-ingestible food induce more roaming? It would complete the regulatory loop by testing whether a higher (than wild type) level of daf-7 in ASJ could further increase roaming. The results in pdf-1 and scd-2 gain-of-function alleles support more ASJ leads to more roaming, but the effect of these gain-of-function alleles may not be ASJ-specific and it would be interesting to know whether ASJ-specific increase of daf-7 leads to a higher level of roaming. In my opinion, either outcome would be informative and strengthen our understanding of the critical function of daf-7 in ASJ demonstrated here.

3. The analyses in Figure 4 cannot fully support "We further observed that the magnitude of upregulation of daf-7 expression in the ASJ neurons when animals were moved from ingestible food to non-ingestible food was reduced in scd-2(syb2455) to levels only about one-fourth of those seen in wild-type animals (Figure 4D)...", because the authors tested and found the difference in daf-7 expression between ingestible and non-ingestible food conditions in both wild type and the mutant worms. The authors did not analyze whether the induction was different between wild type and mutant. Under the ingestible food condition, ASJ expression of daf-7 already looks different in scd-2(syb2455).

4. The authors used unpaired two-tailed t-tests for all the statistical analyses, including when there are multiple groups of data and more than one treatment. In their previous study Meisel et al 2014, the authors used one-way ANOVA, followed by Dunnett's or Tukey's multiple comparison test when they analyzed daf-7 expression or lawn leaving in different mutants or under different bacterial conditions. It is not clear why a two-tailed t-test was used in similar analyses in this study.

Reviewer #2 (Public Review):

Clarkson et al investigated the impact of in vivo ESR1 gene disruption selectively in preoptic area GABA neurons on the estrogen regulation of LH secretion. The hypothalamic pathways by which estradiol controls the secretion of gonadotrophins are incompletely understood and relevant to a better understanding of the mechanisms driving fertility and reproduction. Using CRISPR-Cas9 methodology, the authors were able to effectively reduce the expression of estrogen receptor (ER)-alpha in GABA neurons located in the preoptic area of adult female mice. The results obtained were rather variable except in the animals with concomitant suppression of kisspeptin in the rostral periventricular region of the third ventricle (RP3V), which displayed interruption of ovarian cyclicity and an altered estradiol-induced LH surge. The experimental approach used allowed for a cell-selective, temporally-controlled suppression of ER-alpha expression, providing further evidence of the critical role of RP3V kisspeptin neurons in the estrogen positive-feedback effect. Nevertheless, the assessment of the estradiol-induced LH surge was limited to only one terminal blood collection. The preovulatory LH surge is a variable phenomenon and would require serial blood sampling for a conclusive evaluation of the surge occurrence or alteration, such as in shape, amplitude, or timing. The animals were not assessed for ovulation either, which might be a functional readout for the effectiveness of the LH surge. Thus, the actual effect on the preovulatory LH surge was not fully characterized. Finally, the study leaves unanswered the role of GABA itself. As there was no evident phenotype for the ESR1 knockdown in GABA neurons that do not coexpress kisspeptin, this suggests that GABA neurotransmission in the preoptic area is not involved in the estrogen regulation of LH secretion.

Reviewer #3 (Public Review):

Summary:<br /> Although the key role of estrogen receptor alpha (ERα ; encoded by ESR1 gene) in the control of reproduction has been known for more than two decades, the identity of the neuronal population(s) underlying the control of the negative and positive feedbacks exerted by estrogens on the hypothalamic pituitary ovary axis has been more complicated to pinpoint. Among the factors contributing to the difficulty in this endeavor are the cellular heterogeneity of the preoptic area and hypothalamus and the pulsatile activity of the axis. Several neuronal populations have been identified that control the activity of GnRH neurons, the hypothalamic headmasters of the axis. Among them, the kisspeptin neurons of the rostral periventricular aspect of the third ventricle (RP3V) have been considered the major candidates to convey preovulatory estrogen signals to GnRH neurons, which do not express ERα. Yet, the existence of other populations of kisspeptin neurons (notably in the arcuate nucleus) has made it difficult to selectively ablate ESR1 in one population. A first study (Wang et al., 2019) reported that knocking down ESR1 specifically in RP3V kisspeptin neurons led to decreased excitability of Kp neurons, blunted spontaneous as well estrogen-induced preovulatory LH surge, and reduced or absent corpora lutea indicative of impaired ovulation, but cyclicity was left unaltered.

As GABAergic afferences to GnRH neurons are also implicated in mediating the effects of estrogens on the HPG axis, the present study sought to investigate their role in the positive feedback using genetically driven Crispr-Cas9 mediated knockdown of ERα in VGAT expressing neurons in a specific subregion of the preoptic area. To this end, they stereotaxically delivered viral vectors expressing validated guide RNA into the preoptic area and evaluated their impact on estrus cyclicity and the ability of mice to mount an LH surge induced by estrogens and associated activation of GnRH neurons assessed by the co-expression of Fos. The results demonstrate that knocking down ESR1 in preoptic gabaergic neurons leads to an absence of LH surge and acyclicity when associated with severely reduced kisspeptin expression suggesting that a subpopulation of neurons co-expressing Kp and VGAT neurons are key for LH surge since total absence of Kp is associated with an absence of GnRH neuron activation and reduced LH surge (although this was not confirmed by the post-hoc). Although the implication of kisspeptin neurons was highly suspected already, the novelty of these results lies in the fact that estrogen signaling is necessary for only a selected fraction of them to maintain both regular cycles and LH surge capacity.

Strengths:<br /> Remarkable aspects of this study are, its dataset which allowed them to segregate animals based on distinct neuronal phenotypes matching specific physiological outcomes, the transparency in reporting the results (e.g. all statistical values being reported, all grouping variables being clearly defined, clarity about animals that were excluded and why) and the clarity of the writing. This allows the reader to understand clearly what has been done and how the analyses have been carried out. The same applies to the discussion which describes clearly possible interpretations as well as the limitations of this study based on a single in vivo experiment.

Another remarkable feature of this work lies in the analysis of the dataset. As opposed to the cre-lox approach which theoretically allows for the complete ablation of specific neuronal populations, but may lack specificity regarding timing of action and location, genetically driven in vivo Crispr-Cas9 editing offers both temporal and neuroanatomic selectivity but cannot achieve a complete knockdown. This approach based on stereotaxic delivery of the AAV-encoded guide RNAs comes with inevitable variability in the location where gene knockdown is achieved. By adjusting their original grouping of the animals based on the evaluation of the extent of kisspeptin expression in the target region, the authors obtained a much clearer and interpretable picture. Although only a few animals (n=4) displayed absent kisspeptin expression, the convergence of observations suggesting a central impairment of the reproductive axis is convincing.

In particular, the lack of activation of GnRH neurons in these mice despite a non-significant effect on the reduced LH levels in the post-hoc following a significant ANOVA (which is likely due to the limited number of concerned animals [n=4]), is convincing. Did the authors test whether LH concentrations correlated with the percentage of GnRH+ESR1 positive neurons? This could reinforce the conclusion.

Moreover, the apparent complete absence of kisspeptin expression in these 4 animals is compelling as it provides indirect confirmation of the key role of Kisspeptin neurons in this phenomenon using a different LH surge induction paradigm than Wang et al., 2019. Yet, the quality of the kisspeptin immunostaining in control animals does seem suboptimal and casts doubts about this conclusion (see the section on weaknesses for more details).

It is also interesting that a few animals with unilateral reduction in Kp expression also showed deficits in GnRH neuron activation suggesting that the impact of Kp may not be limited to the side of the brain where it is produced or the existence of a dose effect of Kp activation of GnRH neurons.

Finally, the observation that the pulsatile secretion of LH is maintained in the absence of Kp expression in the RP3V lends support to the notion that LH surge and pulsatility are regulated independently by distinct neuronal populations, a model put forward by the corresponding author a few years ago.

Weaknesses:<br /> One aspect for which I have ambiguous feelings is the minimal level of detail regarding the HPG axis and its regulation by estrogens. This limited amount of detail allows for an easy read with the well-articulated introduction quickly presenting the framework of the study. Although not presenting the axis itself nor mentioning the position of GnRH neurons in this axis or its lack of ERα expression is not detrimental to the understanding of the study, presenting at least the position of GnRH neurons in the axis and their critical role for fertility would likely broaden the impact of this work beyond a rather specialist audience.

The expression of kisspeptin constitutes a key element for the analysis and conclusion of the present work. However, the quality of the kisspeptin immunostaining seems suboptimal based on the representative images. The staining primarily consists of light punctuated structures and it is very difficult to delineate cytoplasmic immunoreactive material defining the shape of neurons in LacZ animals. For some of the cells marked by an arrow, it is also sometimes difficult to determine whether the staining for ESR1 and Kp are in the same focal plane and thus belong to the same neurons. Although this co-expression is not critical for the conclusions of the study, this begs the question of whether Kp expression was determined directly at the microscope (where the focal plan can be adjusted) or on the picture (without possible focal adjustment). Moreover, in the representative image of Kp loss, several nuclei stained for fos (black) show superimposed brown staining looking like a dense nucleus (but smaller than an actual nucleus). This suggests some sort of condensed accumulation of Kp immunoproduct in the nucleus which is not commented. Given the critical importance of this reported change in Kp expression for the interpretation of the present results, it is important to provide strong evidence of the quality/nature of this staining and its analysis which may help interpret the observed functional phenotype.

As acknowledged in the introduction, this study is not the first to use in vivo Crisp-Cas editing to demonstrate the role of kisspeptin neurons in the control of positive feedback. Although the present work achieved this indirectly by targeting VGAT neurons, I was surprised that the paper did not include more comparison of their results with those of Wang et al., 2019. In particular, why was the present approach more successful in achieving both lack of surge and complete acyclicity? Moreover, why is it that targeting ESR1 in a selected fraction of GABAergic neurons can lead to a near-complete absence of Kp expression in this region? This is briefly discussed in the penultimate paragraph but mostly focuses on the non-kisspeptinergic GABAneurons rather than those co-expressing the two markers.

Joint Public Review:

This study describes a group of CRH-releasing neurons, located in the paraventricular nucleus of the hypothalamus, which, in mice, affects both the state of sevoflurane anesthesia and a grooming behavior observed after it. PVH-CRH neurons showed elevated calcium activity during the post-anesthesia period. Optogenetic activation of these PVH-CRH neurons during sevoflurane anesthesia shifts the EEG from burst-suppression to a seemingly activated state (an apparent arousal effect), although without a behavioral correlate. Chemogenetic activation of the PVH-CRH neurons delays sevoflurane-induced loss of righting reflex (another apparent arousal effect). On the other hand, chemogenetic inhibition of PVH-CRH neurons delays recovery of the righting reflex and decreases sevoflurane-induced stress (an apparent decrease in the arousal effect). The authors conclude that PVH-CRH neurons are a common substrate for sevoflurane-induced anesthesia and stress. The PVH-CRH neurons are related to behavioral stress responses, and the authors claim that these findings provide direct evidence for a relationship between sevoflurane anesthesia and sevoflurane-mediated stress that might exist even when there is no surgical trauma, such as an incision. In its current form, the article does not achieve its intended goal.

Strengths<br /> The manuscript uses targeted manipulation of the PVH-CRH neurons, and is technically sound. Also, the number of experiments is substantial.

Weaknesses<br /> The most significant weaknesses are a) the lack of consideration and measurement of GABAergic mechanisms of sevoflurane anesthesia, b) the failure to use another anesthetic as a control, c) a failure to document a compelling post-anesthesia stress response to sevoflurane in humans, d) limitations in the novelty of the findings. These weaknesses are related to the primary concerns described below:

Concerns about the primary conclusion, that PVH-CRH neurons mediate "the anesthetic effects and post-anesthesia stress response of sevoflurane GA".

1) Just because the activity of a given neural cell type or neural circuit alters an anesthetic's response, this does not mean that those neurons play a role in how the anesthetic creates its anesthetic state. For example, sevoflurane is commonly used in children. Its primary mechanism of action is through enhancement of GABA-mediated inhibition. Children with ADHD on Ritalin (a dopamine reuptake inhibitor) who take it on the day of surgery can often require increased doses of sevoflurane to achieve the appropriate anesthetic state. The mesocortical pathway through which Ritalin acts is not part of the mechanism of action of sevoflurane. Through this pathway, Ritalin is simply increasing cortical excitability making it more challenging for the inhibitory effects of sevoflurane at GABAergic synapses to be effective. Similarly, here, altering the activity of the PVHCRH neurons and seeing a change in anesthetic response to sevoflurane does not mean that these neurons play a role in the fundamental mechanism of this anesthetic's action. With the current data set, the primary conclusions should be tempered.

2) It is important to compare the effects of sevoflurane with at least one other inhaled ether anesthetic. Isoflurane, desflurane, and enflurane are ether anesthetics that are very similar to each other, as well as being similar to sevoflurane. It is important to distinguish whether the effects of sevoflurane pertain to other anesthetics, or, alternatively, relate to unique idiosyncratic properties of this gas that may not be a part of its anesthetic properties.

For example, one study cited by the authors (Marana et al.. 2013) concludes that there is weak evidence for differences in stress-related hormones between sevoflurane and desflurane, with lower levels of cortisol and ACTH observed during the desflurane intraoperative period. It is not clear that this difference in some stress-related hormones is modeled by post-sevoflurane excess grooming in the mice, but using desflurane as a control could help determine this.

Concerns about the clinical relevance of the experiments<br /> In anesthesiology practice, perioperative stress observed in patients is more commonly related to the trauma of the surgical intervention, with inadequate levels of antinociception or unconsciousness intraoperatively and/or poor post-operative pain control. The authors seem to be suggesting that the anesthetic itself is causing stress, but there is no evidence of this from human patients cited. We were not aware that this is a documented clinical phenomenon. It is important to know whether sevoflurane effectively produces behavioral stress in the recovery room in patients that could be related to the putative stress response (excess grooming) observed in mice. For example, in surgeries or procedures that required only a brief period of unconsciousness that could be achieved by administering sevoflurane alone (comparable to the 30 min administered to the mice), is there clinical evidence of post-operative stress?

Patients who receive sevoflurane as the primary anesthetic do not wake up more stressed than if they had had one of the other GABAergic anesthetics. If there were signs of stress upon emergence (increased heart rate, blood pressure, thrashing movements) from general anesthesia, the anesthesiologist would treat this right away. The most likely cause of post-operative stress behaviors in humans is probably inadequate anti-nociception during the procedure, which translates into inadequate post-op analgesia and likely delirium. It is the case that children receiving sevoflurane do have a higher likelihood of post-operative delirium. Perhaps the authors' studies address a mechanism for delirium associated with sevoflurane, but this is not considered. Delirium seems likely to be the closest clinical phenomenon to what was studied.

Concerns about the novelty of the findings<br /> CRH is associated with arousal in numerous studies. In fact, the authors' own work, published in eLife in 2021, showed that stimulating the hypothalamic CRH cells leads to arousal and their inhibition promotes hypersomnia. In both papers, the authors use fos expression in CRH cells during a specific event to implicate the cells, then manipulate them and measure EEG responses. In the previous work, the cells were active during wakefulness; here- they were active in the awake state that follows anesthesia (Figure 1). Thus, the findings in the current work are incremental.

The activation of CRH cells in PVN has already been shown to result in grooming by Jaideep Bains (cited as reference 58). Thus, the involvement of these cells in this behavior is expected. The authors perform elaborate manipulations of CRH cells and numerous analyses of grooming and related behaviors. For example, they compare grooming and paw licking after anesthesia with those after other stressors such as forced swim, spraying mice with water, physical attack, and restraint. However, the relevance of these behaviors to humans and generalization to other types of anesthetics is not clear.

Reviewer #1 (Public Review):

Like the "preceding" co-submitted paper, this is again a very strong and interesting paper in which the authors address a question that is raised by the finding in their co-submitted paper - how does one factor induce two different fates. The authors provide an extremely satisfying answer - only one subset of the cells neighbors a source of signaling cells that trigger that subset to adopt a specific fate. The signal here is Delta and the read-out is Notch, whose intracellular domain, in conjunction with, presumably, SuH cooperates with Bsh to distinguish L4 from L5 fate (L5 is not neighbored by signal-providing cells). Like the back-to-back paper, the data is rigorous, well-presented and presents important conclusions. There's a wealth of data on the different functions of Notch (with and without Bsh). All very satisfying.

I have again one suggestion that the authors may want to consider discussing. I'm wondering whether the open chromatin that the author convincingly measure is the CAUSE or the CONSEQUENCE of Bsh being able to activate L4 target genes. What I mean by this is that currently the authors seem to be focused on a somewhat sequential model where Notch signaling opens chromatin and this then enables Bsh to activate a specific set of target genes. But isn't it equally possible that the combined activity of Bsh/Notch(intra)/SuH opens chromatin? That's not a semantic/minor difference, it's a fundamentally different mechanism, I would think. This mechanism also solves the conundrum of specificity - how does Notch know which genes to "open" up? It would seem more intuitive to me to think that it's working together with Bsh to open up chromatin, with chromatin accessibility than being a "mere" secondary consequence. If I'm not overlooking something fundamental here, there is actually also a way to distinguish between these models - test chromatin accessibility in a Bsh mutant. If the author's model is true, chromatin accessibility should be unchanged.<br /> I again finish by commending the authors for this terrific piece of work.

Reviewer #2 (Public Review):

Summary:

In this work, the authors explore how Notch activity acts together with Bsh homeodomain transcription factors to establish L4 and L5 fates in the lamina of the visual system of Drosophila. They propose a model in which differential Notch activity generates different chromatin landscapes in presumptive L4 and L5, allowing the differential binding of the primary homeodomain TF Bsh (as described in the co-submitted paper), which in turn activates downstream genes specific to either neuronal type. The requirement of Notch for L4 vs. L5 fate is well supported, and complete transformation from one cell type into the other is observed when altering Notch activity. However, the role of Notch in creating differential chromatin landscapes is not directly demonstrated. It is only based on correlation, but it remains a plausible and intriguing hypothesis.

Strengths:

The authors are successful in characterizing the role of Notch to distinguish between L4 and L5 cell fates. They show that the Notch pathway is active in L4 but not in L5. They identify L1, the neuron adjacent to L4 as expressing the Delta ligand, therefore being the potential source for Notch activation in L4. Moreover, the manuscript shows molecular and morphological/connectivity transformations from one cell type into the other when Notch activity is manipulated.

Using DamID, the authors characterize the chromatin landscape of L4 and L5 neurons. They show that Bsh occupies distinct loci in each cell type. This supports their model that Bsh acts as a primary selector gene in L4/L5 that activates different target genes in L4 vs L5 based on the differential availability of open chromatin loci.

Overall, the manuscript presents an interesting example of how Notch activity cooperates with TF expression to generate diverging cell fates. Together with the accompanying paper, it helps thoroughly describe how lamina cell types L4 and L5 are specified and provides an interesting hypothesis for the role of Notch and Bsh in increasing neuronal diversity in the lamina during evolution.

Weaknesses:

Differential Notch activity in L4 and L5:<br /> ● The manuscript focuses its attention on describing Notch activity in L4 vs L5 neurons. However, from the data presented, it is very likely that the pool of progenitors (LPCs) is already subdivided into at least two types of progenitors that will rise to L4 and L5, respectively. Evidence to support this is the activity of E(spl)-mɣ-GFP and the Dl puncta observed in the LPC region. Discussion should naturally follow that Notch-induced differences in L4/L5 might preexist L1-expressed Dl that affect newborn L4/L5. Therefore, the differences between L4 and L5 fates might be established earlier than discussed in the paper. The authors should acknowledge this possibility and discuss it in their model.<br /> ● The authors claim that Notch activation is caused by L1-expressed Delta. However, they use an LPC driver to knock down Dl. Dl-KD should be performed exclusively in L1, and the fate of L4 should be assessed.<br /> ● To test whether L4 neurons are derived from NotchON LPCs, I suggest performing MARCM clones in early pupa with an E(spl)-mɣ-GFP reporter.<br /> ● The expression of different Notch targets in LPCs and L4 neurons may be further explored. I suggest using different Notch-activity reporters (i.e., E(spl)-GFP reporters) to further characterize these differences. What cause the switch in Notch target expression from LPCs to L4 neurons should be a topic of discussion.

Notch role in establishing L4 vs L5 fates:<br /> ● The authors describe that 27G05-Gal4 causes a partial Notch Gain of Function caused by its genomic location between Notch target genes. However, this is not further elaborated. The use of this driver is especially problematic when performing Notch KD, as many of the resulting neurons express Ap, and therefore have some features of L4 neurons. Therefore, Pdm3+/Ap+ cells should always be counted as intermediate L4/L5 fate (i.e., Fig3 E-J, Fig3-Sup2), irrespective of what the mechanistic explanation for Ap activation might be. It's not accurate to assume their L5 identity. In Fig4 intermediate-fate cells are correctly counted as such.<br /> ● Lines 170-173: The temporal requirement for Notch activity in L5-to-L4 transformation is not clearly delineated. In Fig4-figure supplement 1D-E, it is not stated if the shift to 29{degree sign}C is performed as in Fig4-figure supplement 1A-C.<br /> ● Additionally, using the same approach, it would be interesting to explore the window of competence for Notch-induced L5-to-L4 transformation: at which point in L5 maturation can fate no longer be changed by Notch GoF?

L4-to-L3 conversion in the absence of Bsh<br /> ● Although interesting, the L4-to-L3 conversion in the absence of Bsh is never shown to be dependent on Notch activity. Importantly, L3 NotchON status is assumed based on their position next to Dl-expressing L1, but it is not empirically tested. Perhaps screening Notch target reporter expression in the lamina, as suggested above, could inform this issue.<br /> ● Otherwise, the analysis of Bsh Loss of Function in L4 might be better suited to be included in the accompanying manuscript that specifically deals with the role of Bsh as a selector gene for L4 and L5.

Different chromatin landscape in L4 and L5 neurons<br /> ● A major concern is that, although L4 and L5 neurons are shown to present different chromatin landscapes (as expected for different neuronal types), it is not demonstrated that this is caused by Notch activity. The paper proves unambiguously that Notch activity, in concert with Bsh, causes the fate choice between L4 and L5. However, that this is caused by Notch creating a differential chromatin landscape is based only in correlation (NotchON cells having a different profile than NotchOFF). Although the authors are careful not to claim that differential chromatin opening is caused directly by Notch, this is heavily suggested throughout the text and must be toned down.<br /> e.g.: Line 294: "With Notch signaling, L4 neurons generate distinct open chromatin landscape" and Line 298: "Our findings propose a model that the unique combination of HDTF and open chromatin landscape (e.g. by Notch signaling)" . These claims are not supported well enough, and alternative hypotheses should be provided in the discussion. An alternative hypothesis could be that LPCs are already specified towards L4 and L5 fates. In this context, different early Bsh targets in each cell type could play a pioneer role generating a differential chromatin landscape.

● The correlation between open chromatin and Bsh loci with Differentially Expressed genes is much higher for L4 than L5. It is not clear why this is the case, and should be discussed further by the authors.

Reviewer #1 (Public Review):

In this very strong and interesting paper the authors present a convincing series of experiments that reveal molecular mechanism of neuronal cell type diversification in the nervous system of Drosophila. The authors show that a homeodomain transcription factor, Bsh, fulfills several critical functions - repressing an alternative fate and inducing downstream homeodomain transcription factors with whom Bsh may collaborate to induce L4 and L5 fates (the author's accompanying paper reveals how Bsh can induce two distinct fates). The authors make elegant use of powerful genetic tools and an arsenal of satisfying cell identity markers.

I believe that this is an important study because it provides some fundamental insights into the conservation of neuronal diversification programs. It is very satisfying to see that similar organizational principles apply in different organisms to generate cell type diversity. The authors should also be commended for contextualizing their work very well, giving a broad, scholarly background to the problem of neuronal cell type diversification.

My one suggestion for the authors is to perhaps address in the Discussion (or experimentally address if they wish) how they reconcile that Bsh is on the one hand: (a) continuously expressed in L4/L4, (b) binding directly to a cohort of terminal effectors that are also continuously expressed but then, on the other hand, is not required for their maintaining L4 fate? A few questions: Is Bsh only NOT required for maintaining Ap expression or is it also NOT required for maintaining other terminal markers of L4? The former could be easily explained - Bsh simply kicks of Ap, Ap then autoregulates, but Bsh and Ap then continuously activate terminal effector genes. The second scenario would require a little more complex mechanism: Bsh binding of targets (with Notch) may open chromatin, but then once that's done, Bsh is no longer needed and Ap alone can continue to express genes. I feel that the authors should be at least discussing this. The postmitotic Bsh removal experiment in which they only checked Ap and depression of other markers is a little unsatisfying without further discussion (or experiments, such as testing terminal L4 markers). I hasten to add that this comment does not take away from my overall appreciation for the depth and quality of the data and the importance of their conclusions.

Reviewer #2 (Public Review):

Summary:<br /> In this paper, the authors explore the role of the Homeodomain Transcription Factor Bsh in the specification of Lamina neuronal types in the optic lobe of Drosophila. Using the framework of terminal selector genes and compelling data, they investigate whether the same factor that establishes early cell identity is responsible for the acquisition of terminal features of the neuron (i.e., cell connectivity and synaptogenesis).

The authors convincingly describe the sequential expression and activity of Bsh, termed here as 'primary HDTF', and of Ap in L4 or Pdm3 in L5 as 'secondary HDTFs' during the specification of these two neurons. The study demonstrates the requirement of Bsh to activate either Ap and Pdm3, and therefore to generate the L4 and L5 fates. Moreover, the authors show that in the absence of Bsh, L4 and L5 fates are transformed into a L1 or L3-like fates.

Finally, the authors used DamID and Bsh:DamID to profile the open chromatin signature and the Bsh binding sites in L4 neurons at the synaptogenesis stage. This allows the identification of putative Bsh target genes in L4, many of which were also found to be upregulated in L4 in a previous single-cell transcriptomic analysis. Among these genes, the paper focuses on Dip-β, a known regulator of L4 connectivity. They demonstrate that both Bsh and Ap are required for Dip-β, forming a feed-forward loop. Indeed, the loss of Bsh causes abnormal L4 synaptogenesis and therefore defects in several visual behaviors.

The authors also propose the intriguing hypothesis that the expression of Bsh expanded the diversity of Lamina neurons from a 3 cell-type state to the current 5 cell-type state in the optic lobe.

Strengths:

Overall, this work presents a beautiful practical example of the framework of terminal selectors: Bsh acts hierarchically with Ap or Pdm3 to establish the L4 or L5 cell fates and, at least in L4, participates in the expression of terminal features of the neuron (i.e., synaptogenesis through Dip-β regulation).

The hierarchical interactions among Bsh and the activation of Ap and Pdm3 expression in L4 and L5, respectively, are well established experimentally. Using different genetic drivers, the authors show a window of competence during L4 neuron specification during which Bsh activates Ap expression. Later, as the neuron matures, Ap becomes independent of Bsh. This allows the authors to propose a coherent and well-supported model in which Bsh acts as a 'primary' selector that activates the expression of L4-specific (Ap) and L5-specific (Pdm3) 'secondary' selector genes, that together establish neuronal fate.

Importantly, the authors describe a striking cell fate change when Bsh is knocked down from L4/L5 progenitor cells. In such cases, L1 and L3 neurons are generated at the expense of L4 and L5. The paper demonstrates that Bsh in L4/L5 represses Zfh1, which in turn acts as the primary selector for L1/L3 fates. These results point to a model where the acquisition of Bsh during evolution might have provided the grounds for the generation of new cell types, L4 and L5, expanding lamina neuronal diversity for a more refined visual behaviors in flies. This is an intriguing and novel hypothesis that should be tested from an evo-devo standpoint, for instance by identifying a species when L4 and L5 do not exist and/or Bsh is not expressed in L neurons.

To gain insight into how Bsh regulates neuronal fate and terminal features, the authors have profiled the open chromatin landscape and Bsh binding sites in L4 neurons at mid-pupation using the DamID technique. The paper describes a number of genes that have Bsh binding peaks in their regulatory regions and that are differentially expressed in L4 neurons, based on available scRNAseq data. Although the manuscript does not explore this candidate list in depth, many of these genes belong to classes that might explain terminal features of L4 neurons, such as neurotransmitter identity, neuropeptides or cytoskeletal regulators. Interestingly, one of these upregulated genes with a Bsh peak is Dip-β, an immunoglobulin superfamily protein that has been described by previous work from the author's lab to be relevant to establish L4 proper connectivity. This work proves that Bsh and Ap work in a feed-forward loop to regulate Dip-β expression, and therefore to establish normal L4 synapses. Furthermore, Bsh loss of function in L4 causes impairs visual behaviors.

Weaknesses:

● The last paragraph of the introduction is written using rhetorical questions and does not read well. I suggest rewriting it in a more conventional direct style to improve readability.

● A significant concern is the way in which information is conveyed in the Figures. Throughout the paper, understanding of the experimental results is hindered by the lack of information in the Figure headers. Specifically, the genetic driver used for each panel should be adequately noted, together with the age of the brain and the experimental condition. For example, R27G05-Gal4 drives early expression in LPCs and L4/L5, while the 31C06-AD, 34G07-DBD Split-Gal4 combination drives expression in older L4 neurons, and the use of one or the other to drive Bsh-KD has dramatic differences in Ap expression. The indication of the driver used in each panel will facilitate the reader's grasp of the experimental results.

● Bsh role in L4/L5 cell fate:<br /> o It is not clear whether Tll+/Bsh+ LPCs are the precursors of L4/L5. Morphologically, these cells sit very close to L5, but are much more distant from L4.<br /> o Somatic CRISPR knockout of Bsh seems to have a weaker phenotype than the knockdown using RNAi. However, in several experiments down the line, the authors use CRISPR-KO rather than RNAi to knock down Bsh activity: it should be explained why the authors made this decision. Alternatively, a null mutant could be used to consolidate the loss of function phenotype, although this is not strictly necessary given that the RNAi is highly efficient and almost completely abolishes Bsh protein.<br /> o Line 102: Rephrase "R27G05-Gal4 is expressed in all LPCs and turned off in lamina neurons" to "is turned off as lamina neurons mature", as it is kept on for a significant amount of time after the neurons have already been specified.<br /> o Line 121: "(a) that all known lamina neuron markers become independent of Bsh regulation in neurons" is not an accurate statement, as the markers tested were not shown to be dependent on Bsh in the first place.<br /> o Lines 129-134: Make explicit that the LPC-Gal4 was used in this experiment. This is especially important here, as these results are opposite to the Bsh Loss of Function in L4 neurons described in the previous section. This will help clarify the window of competence in which Bsh establishes L4/L5 neuronal identities through ap/pdm3 expression.

● DamID and Bsh binding profile:<br /> ○ Figure 5 - figure supplement 1C-E: The genotype of the Control in (C) has to be described within the panel. As it is, it can be confused with a wild type brain, when it is in fact a Bsh-KO mutant.<br /> ○ It Is not clear how L4-specific Differentially Expressed Genes were found. Are these genes DEG between Lamina neurons types, or are they upregulated genes with respect to all neuronal clusters? If the latter is the case, it could explain the discrepancy between scRNAseq DEGs and Bsh peaks in L4 neurons.

● Dip-β regulation:<br /> ○ Line 234: It is not clear why CRISPR KO is used in this case, when Bsh-RNAi presents a stronger phenotype.<br /> ○ Figure 6N-R shows results using LPC-Gal4. It is not clear why this driver was used, as it makes a less accurate comparison with the other panels in the figure, which use L4-Split-Gal4. This discrepancy should be acknowledged and explained, or the experiment repeated with L4-Split-Gal4>Ap-RNAi.<br /> ○ Line 271: It is also possible that L4 activity is dispensable for motion detection and only L5 is required.

● Discussion: It is necessary to de-emphasize the relevance of HDTFs, or at least acknowledge that other, non-homeodomain TFs, can act as selector genes to determine neuronal identity. By restricting the discussion to HDTFs, it is not mentioned that other classes of TFs could follow the same Primary-Secondary selector activation logic.

Reviewer #2 (Public Review):

Summary:<br /> Desiderio and colleagues investigated the role of the TALE (three amino acid loop extension) homeodomain transcription factor Meis2 during maturation and target innervation of mechanoreceptors and their sensation to touch. They start with a series of careful in situ hybridizations to examine Meis2 transcript expression in mouse and chick DRGs of different embryonic stages. By this approach, they identify Meis2+ neurons as slowly- and rapidly adapting A-beta LTMRs, respectively. Retrograde tracing experiments in newborn mice confirmed that Meis2-expressing sensory neurons project to the skin, while unilateral limb bud ablations in chick embryos in Ovo showed that these neurons require target-derived signals for survival. The authors further generated a conditional knock-out (cKO) mouse model in which Meis2 is selectively lost in Islet1-expressing, postmitotic neurons in the DRG (IsletCre/+::Meis2flox/flox, abbreviated below as cKO). WT and Islet1Cre/+ littermates served as controls. cKO mice did not exhibit any obvious alteration in volume or cellular composition of the DRGs but showed significantly reduced sensitivity to touch stimuli and various innervation defects to different end-organ targets. RNA-sequencing experiments of E18.5 DRGs taken from WT, Islet1Cre/+, and cKO mice reveal extensive gene expression differences between cKO cells and the two controls, including synaptic proteins and components of the GABAergic signaling system. Gene expression also differed considerably between WT and heterozygous Islet1Cre/+ mice while several of the other parameters tested did not. These findings suggest that Islet1 heterozygosity affects gene expression in sensory neurons but not sensory neuron functionality. However, only some of the parameters tested were assessed for all three genotypes. Histological analysis and electrophysiological recordings shed light on the physiological defects resulting from the loss of Meis2. By immunohistochemical approaches, the authors describe distinct innervation defects in glabrous and hairy skin (reduced innervation of Merkel cells by SA1-LTMRs in glabrous but not hairy skin, reduced complexity of A-beta RA1-LTMs innervating Meissner's corpuscles in glabrous skin, reduced branching and innervation of A-betA RA1-LTMRs in hairy skin). Electrophysiological recordings from ex vivo skin nerve preparations found that several, but not all of these histological defects are matched by altered responses to external stimuli, indicating that compensation may play a considerable role in this system.

Strengths:<br /> This is a well-conducted study that combines different experimental approaches to convincingly show that the transcription factor Meis2 plays an important role in the perception of light touch. The authors describe a new mouse model for compromised touch sensation and identify a number of genes whose expression depends on Meis2 in mouse DRGs. Given that dysbalanced MEIS2 expression in humans has been linked to autism and that autism seems to involve an inappropriate response to light touch, the present study makes a novel and important link between this gene and ASD.

Weaknesses:<br /> The authors make use of different experimental approaches to investigate the role of Meis2 in touch sensation, but the results obtained by these techniques could be connected better. For instance, the authors identify several genes involved in synapse formation, synaptic transmission, neuronal projections, or axon and dendrite maturation that are up- or downregulated upon targeted Meis2 deletion, but it is unresolved whether these chances can in any way explain the histological, electrophysiological, or behavioral deficits observed in cKO animals. The use of two different controls (WT and Islet1Cre/+) is unsatisfactory and it is not clear why some parameters were studied in all three genotypes (WT, Islet1Cre/+ and cKO) and others only in WT and cKO. In addition, Meis2 mutant mice apparently are less responsive to touch, whereas in humans, mutation or genomic deletion involving the MEIS2 gene locus is associated with ASD, a condition that, if anything, is associated with an elevated sensitivity to touch. It would be interesting to know how the authors reconcile these two findings. A minor weakness, the first manuscript suffers from some ambiguities and errors, but these can be easily corrected.

Joint Public Review:

Anthoney et al. provide an honorable attempt at furthering our understanding of the different sleep stages that may exist in Drosophila. The establishment of definable sleep stages/state in the fly model should be seen as a central goal in the field and this study represents an important step toward that goal. In particular, managing to draw parallels between sleep stages in flies and humans would make it relevant to use the power of fly genetics to better understand the molecular and cellular basis of these sleep stages. The authors use behavioral, physiological and transcriptomics approaches to describe the differences that exist between sleep triggered by optogenetic stimulation of dFB neurons and sleep induced by consumption of the sleep-promoting drug Gaboxadol (THIP). While there are still concerns regarding the interpretation of the major results, the authors have, in general, adequately responded to the reviewers' concerns.

The strengths of this work are:<br /> 1- The article is easy to read, and the figures are mostly informative.<br /> 2- The authors employ state-of-the-art techniques to measure neuronal activity and locomotion in a single assay.<br /> 3- The analysis of transcriptomic data is appropriate.<br /> 4- The authors identify many new genes regulated in response to specific methods for sleep induction. These are all potentially interesting candidates for further studies investigating the molecular basis of sleep. It would be interesting to know which of these genes are already known to display circadian expression patterns.

Concerns:<br /> 1- The fact that flies with dFB activation seem to keep a basal level of locomotor activity whereas THIP-treated ones don't is quite striking. Is it possible that there is an error with Figure 4C-D? Based on this, it is hard to believe that dFB stimulation and THIP consumption have similar behavioral effects on sleep.<br /> 2- The authors seem satisfied with the 'good correspondence' between their RNA-seq and qPCR results, this is true for only ~9/19 genes in Fig 6G and 2/6 genes in Fig 7G. The variability between the three biological replicates is not represented in the figure.

Comments<br /> 1- The fact that THIP-induced sleep persists long after THIP removal (Fig 3D) is intriguing. This suggests that the drug might trigger a sleep-inducing pathway that, once activated, can continue on its own without the drug.<br /> 2- The claim that induction of the two forms (active/quiet) of sleep produce distinct transcriptomic and physiological effects while producing highly similar behavioral effects makes it difficult to understand the relationships between the former changes with sleep state. In their response the authors argue that sleep behavior, as currently measured using duration of inactivity, is not necessarily expected to allow for a differentiation between active and quiet sleep. This further argues for a need for better physiological/molecular correlates of sleep state in the fly (a laudable goal of this very study). However, until clear behavioral correlates can be strongly associated with physiological/molecular correlates, we will be limited to speculation about this important issue.<br /> 3- The authors suggest that the duration of the periods of inactivity may not be particularly useful for defining sleep states/stages in the fly. If this is the case, it is certainly an important issue as this measurement is the behavioral criteria for defining sleep in the field. In this regard, it raises the question of the relationship between the active and quiet sleep states examined in this study and the growing evidence for a deep sleep state (characterized by, among other things, a lowered metabolism).<br /> 4- Although the methodological concerns regarding the dose of Gaboxadol and the controls for the optogenetic/transcriptomic experiments remain, the authors have explained the rationale for the experimental design they used.<br /> 5- Overall, the authors have managed to clearly illustrate the differences between dFB stimulation and THIP consumption on behavior, neuronal activity, and gene expression. In this regard, they have achieved what they claim in the title of the article. Overall, the results support the conclusions, however the main point to consider is that the methods employed here are artificial, and there is no guarantee at this stage that 'spontaneous' sleep has the same effects on the transcriptome than what is presented here.<br /> 5- This article represents an interesting attempt at addressing very important questions, and some of the data presented here, especially the RNA-seq, can be very useful for others. However, because of the lack of definitive conclusion about whether the results presented are applicable to 'natural' sleep, the impact of this article may remain limited beyond a relatively small field.

Comments to authors

The authors have suitably addressed all comments from this section.

Reviewer #1 (Public Review):

The study describes a new computational method for unsupervised (i.e., non-artificial intelligence) segmentation of objects in grayscale images that contain substantial noise, to differentiate object, no object, and noise. Such a problem is essential in biology because they are commonly confronted in the analysis of microscope images of biological samples and recently have been resolved by artificial intelligence, especially by deep neural networks. However, training artificial intelligence for specific sample images is a difficult task and not every biological laboratory can handle it. Therefore, the proposed method is particularly appealing to laboratories with little computational background. The method was shown to achieve better performance than a threshold-based method for artificial and natural test images. To demonstrate the usability, the authors applied the method to high-power confocal images of the thalamus for the identification and quantification of immunostained potassium ion channel clusters formed in the proximity of large axons in the thalamic neuropil and verified the results in comparison to electron micrographs. 

Strengths: <br /> The authors claim that the proposed method has higher pixel-wise accuracy than the threshold-based method when applied to gray-scale images with substantial noises.

Since the method does not use artificial intelligence, training and testing are not necessary, which would be appealing to biologists who are not familiar with machine learning technology.

The method does not require extensive tuning of adjustable parameters (trying different values of "Moran's order") given that the size of the object in question can be estimated in advance.

Weaknesses:<br /> It is understood that the strength of the method is that it does not depend on artificial intelligence and therefore the authors wanted to compare the performance with another non-AI method (i.e. the threshold-based method; TBM). However, the TBM used in this work seems too naive to be fairly compared to the expensive computation of "Moran's I" used for the proposed method. To provide convincing evidence that the proposed method advances object segmentation technology and can be used practically in various fields, it should be compared to other advanced methods, including AI-based ones, as well.

This method was claimed to be better than the TBM when the noise level was high. Related to the above, TBMs can be used in association with various denoising methods as a preprocess. It is questionable whether the claim is still valid when compared to the methods with adequate complexity used together with denoising. Consider for example, Weigert et al. (2018) https://doi.org/10.1038/s41592-018-0216-7; or Lehtinen et al (2018) https://doi.org/10.48550/arXiv.1803.04189.

The computational complexity of the method, determined by the convolution matrix size (Moran's order), linearly increases as the object size increases (Fig. S2b). Given that the convolution must be run separately for each pixel, the computation seems quite demanding for scale-up, e.g. when the method is applied for 3D image volumes. It will be helpful if the requirement for computer resources and time is provided.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by David et al. describes a novel image segmentation method, implementing Local Moran's method, which determines whether the value of a datapoint or a pixel is randomly distributed among all values, in differentiating pixel clusters from the background noise. The study includes several proof-of-concept analyses to validate the power of the new approach, revealing that implementation of Local Moran's method in image segmentation is superior to threshold-based segmentation methods commonly used in analyzing confocal images in neuroanatomical studies.

Strengths:<br /> Several proof-of-concept experiments are performed to confirm the sensitivity and validity of the proposed method. Using composed images with varying levels of background noise and analyzing them in parallel with the Local Moran's or a Threshold-Based Method (TBM), the study is able to compare these approaches directly and reveal their relative power in isolating clustered pixels.

Similarly, dual immuno-electron microscopy was used to test the biological relevance of a colocalization that was revealed by Local Moran's segmentation approach on dual-fluorescent labeled tissue using immuno-markers of the axon terminal and a membrane-protein (Figure 5). The EM revealed that the two markers were present in terminals and their post-synaptic partners, respectively. This is a strong approach to verify the validity of the new approach for determining object-based colocalization in fluorescent microscopy.

The methods section is clear in explaining the rationale and the steps of the new method (however, see the weaknesses section). Figures are appropriate and effective in illustrating the methods and the results of the study. The writing is clear; the references are appropriate and useful.

Weaknesses:<br /> While the steps of the mathematical calculations to implement Local Moran's principles for analyzing high-resolution images are clearly written, the manuscript currently does not provide a computation tool that could facilitate easy implementation of the method by other researchers. Without a user-friendly tool, such as an ImageJ plugin or a code, the use of the method developed by David et al by other investigators may remain limited.

Reviewer #2 (Public Review):

This manuscript by Muñoz-Reyes et al. presents studies on the molecular mechanisms by which NCS-1 regulates Ric-8A and its interaction with Ga. They have investigated how calcium ions and phosphorylation of Ric-8A affect these interactions. They found that NCS-1 induces a conformational change in Ric-8A that prevents its phosphorylation and subsequent interaction with Ga, and this can be reversed by increasing calcium ion concentration. Using structural biology methods, they determined the interaction surfaces between NCS-1 and Ric-8A. These mechanistic analyses are needed in the field and beneficial to helping us understand specificity in the regulation of G protein signaling.

Overall, this manuscript presents an abundance of data that supports the authors' conclusions. The introduction is thorough and well-written. The structure figures are beautiful and clear - well done. Most of the biochemical and biophysical experiments are convincing. In some cases, further elaborations and explanations of data interpretation are needed. The crystallographic data is solid. However, I have major concerns with the cryo-EM data presented due to its low quality and the conclusions drawn from it.

Reviewer #3 (Public Review):

The current manuscript investigates the molecular basis of calcium-sensitive regulation of the guanine exchange factor Ric8A by the neuronal calcium sensor 1 (NCS-1). The authors provide insight into a number of aspects of this interaction, including high-resolution structures of the NCS1-Ric8A binding interface (using peptides based on Ric8A), low-resolution cryo-EM data that hints at a structural rearrangement, and a biochemical investigation of the influence of calcium binding, sodium binding, and phosphorylation on this interaction. Altogether, this manuscript provides a comprehensive set of experiments that provide insight into this important interaction. In particular, the identification of ions bound to NCS-1 using crystallography and binding assays is very nicely done and convincing. The cryo-EM data is at low resolution and provides only weak support for the proposed mechanism.

Reviewer #1 (Public Review):

The strongest aspect of the study is the identification of the probable Ric-8A/NCS-1 interface through the crystal structures of NCS-1 complexed with candidate peptide mimetics from Ric-8A. However, since the structures involve peptides, it is critical to validate this interface with mutational analysis of the full-length or truncated Ric-8A. Furthermore, the evidence for the complex structure based on cryo-EM reconstruction is weak. The low resolution does not allow for reliable modeling of the complex. Two analyses may support the authors' main conclusions: a) validation of the interface with mutational analysis of Ric-8A, and b) new optimized sample/grid preparation for cryo-EM data collection.

Reviewer #1 (Public Review):

Summary:<br /> In this well-designed study, the authors of the manuscript have analyzed the impact of individually silencing 90 lipid transfer proteins on the overall lipid composition of a specific cell type. They confirmed some of the evidence obtained by their own and other research groups in the past, and additionally, they identified an unreported role for ORP9-ORP11 in sphingomyelin production at the trans-Golgi. As they delved into the nature of this effect, the authors discovered that ORP9 and ORP11 form a dimer through a helical region positioned between their PH and ORD domains.

Strengths:<br /> This well-designed study presents compelling new evidence regarding the role of lipid transfer proteins in controlling lipid metabolism. The discovery of ORP9 and ORP11's involvement in sphingolipid metabolism invites further investigation into the impact of the membrane environment on sphingomyelin synthase activity.

Weaknesses:<br /> There are a couple of weaknesses evident in this manuscript. Firstly, there's a lack of mechanistic understanding regarding the regulatory role of ORP9-11 in sphingomyelin synthase activity. Secondly, the broader role of hetero-dimerization of LTPs at ER-Golgi membrane contact sites is not thoroughly addressed. The emerging theme of LTP dimerization through coiled domains has been reported for proteins such as CERT, OSBP, ORP9, and ORP10. However, the specific ways in which these LTPs hetero and/or homo-dimerize and how this impacts lipid fluxes at ER-Golgi membrane contact sites remain to be fully understood.

Regardless of the unresolved points mentioned above, this manuscript presents a valuable conceptual advancement in the study of the impact of lipid transfer on overall lipid metabolism. Moreover, it encourages further exploration of the interplay among LTP actions across various cellular organelles.

Reviewer #2 (Public Review):

Summary:<br /> The authors set out to determine which lipid transfer proteins impact the lipids of Golgi apparatus, and they identified a reasonable number of "hits" where the lack of one lipid transfer protein affected a particular Golgi lipid or class of lipids. They then carried out something close to a "proof of concept" for one lipid (sphingomyelin) and two closely related lipid transfer proteins (ORP9/ORP11). They looked into that example in great detail and found a previously unknown relationship between the level of phosphatidylserine in the Golgi (presumably trans-Golgi, trans-Golgi Network) and the function of the sphingomyelin synthase enzyme. This was all convincingly done - results support their conclusions - showing that the authors achieved their aims.

Impact:<br /> There are likely to be 2 types of impact:<br /> (I) cell biology: sphoingomyelin synthase, ORP9/11 will be studied in the future in more informed ways to understand (a) the role of different Golgi lipids - this work opens that out and produces more questions than answers (b) the role of different ORPs: what distinguishes ORP11 from its paralogy ORP10?<br /> (ii) molecular biochemistry: combining knockdown miniscreen with organelle lipidomics must be time-consuming, but here it is shown to be quite a powerful way to discover new aspects of lipid-based regulation of protein function. This will be useful to others as an example, and if this kind of workflow could be automated, then the possible power of the method could be widely applied.

Strengths:<br /> Nicely controlled data;<br /> Wide-ranging lipidomics dataset with repeats and SDs - all data easily viewed.<br /> Simple take-home message that PS traffic to the TGN by ORP9/11 is required for some aspect of SMS1 function.

Weaknesses:<br /> Model and Discussion:<br /> No idea about the aspect of SMS1 function that is being affected. Even if no further experiments were carried out, the authors could discuss possibilities. One might speculate what the PS is being used for. For example, is it a co-factor for integral membrane proteins, such as flippases? Is it a co-factor for peripheral membrane proteins, such as yet more LTPs? The model could include the work of Peretti et al (2008), which linked Nir2 activity exchanging PI:PA (Yadav et al, 2015) to the eventual function of CERT. Could the PS have a role in removing/reducing DAG produced by CERT?

Reviewer #3 (Public Review):

Summary:<br /> The authors developed a lipid transfer protein knock-out library to identify lipid transfer proteins with roles in lipid homeostasis/metabolism. They investigated one of their hits, the ORP9/ORP11 dimer, which they found affects sphingomyelin synthesis. Further. they found that ORP9/11 localizes to ER-Golgi contact sites via interactions between a known FFAT motif in ORP9, which can interact with the ER protein VAP, and the PH domains of ORP9 and ORP11 that target PI4P at the Golgi. They showed defects in Golgi PI4P and PS levels when ORP9 or 11 were dysfunctional, supporting but not demonstrating that ORP9/11 might exchange PI4P and PS at these contact sites. Their in vitro data indicates that both ORP9 and 11 can transfer PS. They do not assess whether either protein can transfer PI4P (although there is a very nice recent paper by He et al et You, PMID 36853333, showing that ORP9 can transfer PI4P in vitro), and they do not assess the consequences of heterodimerization on either PS or PI4P transfer. The mechanisms by which PI4P/PS level perturbations affect sphingomyelin synthesis remain unclear.

Strengths:<br /> The authors have developed an LTP knock-out library that might generate hypotheses regarding lipid metabolism, although defects are not unexpected and mechanisms will be difficult to work out--as, in fact, evidenced by this manuscript.

The OPR9/11 localization data and imaging studies are well done; this is the first more comprehensive characterization of the ORP9/11 heterodimer, which was discovered in 2010.

Weaknesses:<br /> A major flaw is that the authors claim to but do not, in fact, provide evidence of PS/PI4P counter exchange in vitro. That the presence of PI4P on the acceptor liposomes accelerates PS transfer in the in vitro assays is not proof that there is a counter exchange. In fact, since the rate-determining step in the transfer reactions is lipid transfer between membrane and transfer protein and this depends on the association of the transfer protein with donor and/or acceptor liposomes, a more likely explanation for the more efficient transfer in the presence of PI4P is that PI4P allows for longer association of lipid transfer protein with acceptor liposomes. To show the plausibility of the counter-exchange idea as applied to the ORP9/ORP11 heterodimer, the authors would need to show that it can transfer PI4P. (The work by He et al et You, 2023, mentioned above, is a very nice study that the authors might use as a model.)

Mechanistic insights from the study are limited. How does a PI4P/PS imbalance affect sphingomyelin synthesis?

The ORP9/11 heterodimer seems to behave very much like ORP9/ORP10 heterodimer, including in its localization and dimerization mode. Is ORP9/11 just another version of 9/10? I wonder whether discussions of whether they are redundant or what their different roles are might be in order. There is little mechanistic or conceptual novelty arising from this study.

A minor point, but the statement (p2., lines 19-20) that "vesicular trafficking contributes only to a small portion of lipid trafficking" is not correct and raises eyebrows. What is more correct is that protein-mediated lipid transfer ALSO plays an important role in lipid transfer. It might even be said that LTP-mediated lipid transfer is critical in fine-tuning membrane lipid composition, including of phosphoinositides.

Reviewer #1 (Public Review):

Summary:<br /> In this study, the authors present a new mouse model with a deletion of the Tmem263 gene, also known as C12orf23, which encodes the transmembrane protein 263.

Strengths:<br /> The study indicates that Tmem263 interacts with growth hormone, and possibly participates in controlling body growth.

Weaknesses (Major):<br /> The current study confirms previous findings using a mouse model of TMEM263 gene deletion. However, it remains descriptive and does not provide critical insights into the mechanism of action of TMEM263 protein. While the study demonstrates Tmem263-mediated reduction in GHR gene expression in the liver and subsequent growth retardation, it does not elucidate the pathway through which Tmem263 affects GHR expression.

Weaknesses (minor):<br /> 1. Since GH-resistant dwarfism is typically associated with increased body adiposity and hepatic lipid accumulation, considering the high expression levels of Tmem263 in adipose tissue (Figure 1C), it would be valuable to measure body adiposity and hepatic lipid content.

2. It would be helpful to specify the age at which the growth plate parameters were tested. Additionally, were there any differences observed between male and female mice (Figure 3 L-N)? Information on the local (growth plate) expression of IGF-1, IGF-1R, and GHR would also be beneficial.

3. Given the low levels of blood glucose and serum insulin, it would be relevant to know if the mice were challenged with ITT or GTT.

4. The liver transcriptomics data presented in the study is impressive. However, there seems to be a missed opportunity to delve into the data and identify potential factors involved in the regulation of GHR expression.

5. The effects of whole-body Tmem263 nullification on osteoblast differentiation and function, as well as on osteoclastogenesis, were not investigated in the study. Considering the potential impact on bone health, these aspects could be explored in future research.

Reviewer #2 (Public Review):

Summary: The study demonstrates that deletion of a small cytoplasmic membrane protein, Tmem263, caused severe impairment of longitudinal bone growth and that the impaired bone growth was caused by suppression of expression and/or protein levels of growth hormone receptors in the liver.

Strengths: The experimental design of the study is sound and the results are in general supportive of the conclusions.

Weaknesses: The study lacks mechanistic investigation into how the deletion of a gene corresponding to a small cytoplasmic membrane protein would lead to a substantial reduction in the gene expression of growth hormone receptor, which takes place in the nuclei. Accordingly, the manuscript is of a largely descriptive nature.

Reviewer #3 (Public Review):

Prior studies in humans and in chickens suggested that TMEM263 could play an important role in longitudinal bone growth, but a definitive assessment of the function and potential mechanism of action of this species-conserved plasma membrane protein has been lacking. Here, the authors create a TMEM263 null mouse model and convincingly show a dramatic cessation of post-natal growth, which becomes apparent by day PND21. They report proportional dwarfism, highly significant bone and related phenotypes, as well as notable alterations of hepatic GH signaling to IGF1. A large body of prior work has established an essential role for GH and its stimulation of IGF1 production in liver and other tissues in post-natal growth. On this basis, the authors conclude that the observed decrease in serum IGF1 seen in TMEM263-KO mice is causal for the growth phenotype, which seems likely. Moreover, they ascribe the low serum IGF1 to the observed decreases in hepatic GH receptor (GHR) expression and GHR/JAK2/STAT5 signaling to IGF1, which is plausible but not proven by the experiments presented.

The finding that TMEM263 is essential for normal hepatic GHR/IGF1 signaling is an important, and unexpected finding, one that is likely to stimulate further research into the underlying mechanisms of TMEM263 action, including the distinct possibility that these effects involve direct protein-protein interactions between GHR and TMEM263 on the plasma membrane of hepatocytes, and perhaps on other mouse cell types and tissues as well, where TMEM263 expression is up to 100-fold higher (Fig. 1C).

An intriguing finding of this study, which is under-emphasized and should be noted in the Abstract, is the apparent feminization of liver gene expression in male TMEM263-KO mice, where many male-biased genes are downregulated, and many female-biased genes are upregulated. Further investigation of these liver gene responses by comparison to public datasets could be very useful, as it could help determine: (1) whether the TMEM263 liver phenotype is similar to that of hypophysectomized male mouse liver, where GH and GHR/STAT5/IGF1 signaling are both totally ablated; or alternatively, (2) whether the phenotype is more similar to that of a male mouse given GH as a continuous infusion, which induces widespread feminization of gene expression in the liver, and is perhaps similar to the gene responses seen in the TMEM263-KO mice. Answering this question could provide critical insight into the mechanistic basis for the hepatic effects of TMEM263 gene KO.

One notable weakness of this study is the conclusion (in the Abstract, and elsewhere), that the low serum IGF-I "is due to a deficit in hepatic GH receptor (GHR) expression, and GH-induced JAK2/STAT5 signaling." This conclusion is speculative in the absence of any experimental assessment of the impact of TMEM 263-KO on GHR/IGF1 signaling in other tissues that contribute to systematic IGF1 production and which likely also impact bone growth. More direct evidence for the impact of hepatic IGF1 production per se in this mouse model could be obtained by liver-specific delivery into the TMEM263-KO mice of a constitutively active. STAT5 construct, which was recently reported to normalize hepatic and serum IGF1 levels in liver-specific GHR-KO mice (PMID: 35396838).

Another weakness is the experiment presented in Fig. 5E, which is presented as evidence for the proposed GH resistance of TMEM263-KO mice. This experiment has several design flaws: 1) It uses human GH, which unlike mouse GH, activates mouse prolactin receptor as well as GH receptor; 2) the dose of hGH used, 3µg GH/g BW, is 100 times higher than is required to activate liver STAT5; and 3) the experiment lacks a set of control livers, which are needed to establish the level of STAT5 tyrosine phosphorylation in the absence of exogenous GH treatment. Moreover, if the mice used in Fig. 5E are males (the sex was not specified), then high variability in the basal phospho-STAT5 levels of control livers is expected, in which case n=6 or more individual control male livers may be required.

Reviewer #1 (Public Review):

In this manuscript, Huang and colleagues explored the role of iron in bacterial therapy for cancer. Using proteomics, they revealed the upregulation of bacterial genes that uptake iron, and reasoned that such regulation is an adaptation to the iron-deficient tumor microenvironment. Logically, they engineered E. Coli strains with enhanced iron-uptake efficiency, and showed that these strains, together with iron scavengers, suppress tumor growth in a mouse model. Lastly, they reported the tumor suppression by IroA-E. Coli provides immunological memory via CD8+ T cells. In general, I find the findings in the manuscript novel and the evidence convincing.

1. Although the genetic and proteomic data are convincing, would it be possible to directly quantify the iron concentration in (1) E. Coli in different growth environments, and (2) tumor microenvironment? This will provide the functional consequences of upregulating genes that import iron into the bacteria.

2. Related to 1, the experiment to study the synergistic effect of CDG and VLX600 (lines 139-175) is very nice and promising, but one flaw here is a lack of the measurement of iron concentration. Therefore, a possible explanation could be that CDG acts in another manner, unrelated to iron uptake, that synergizes with VLX600's function to deplete iron from cancer cells. Here, a direct measurement of iron concentration will show the effect of CDG on iron uptake, thus complementing the missing link.

3. Lines 250-268: Although statistically significant, I would recommend the authors characterize the CD8+ T cells a little more, as the mechanism now seems quite elusive. What signals or memories do CD8+ T cells acquire after IroA-E. Coli treatment to confer their long-term immunogenicity?

4. Perhaps this goes beyond the scope of the current manuscript, but how broadly applicable is the observed iron-transport phenomenon in other tumor models? I would recommend the authors to either experimentally test it in another model or at least discuss this question.

Reviewer #2 (Public Review):

Summary:

The authors provide strong evidence that bacteria, such as E. coli, compete with tumor cells for iron resources and consequently reduce tumor growth. When sequestration between LCN2 and bacterobactin is blocked by upregulating CDG(DGC-E. coli) or salmochelin(IroA-E.coli), E. coli increase iron uptake from the tumor microenvironment (TME) and restrict iron availability for tumor cells. Long-term remission in IroA-E.coli treated mice is associated with enhanced CD8+ T cell activity. Additionally, systemic delivery of IroA-E.coli shows a synergistic effect with chemotherapy reagent oxaliplatin to reduce tumor growth.

Strengths:

It is important to identify the iron-related crosstalk between E. coli and TME. Blocking lcn2-bacterobactin sequestration by different strategies consistently reduces tumor growth.

Weaknesses:

As engineered E.coli upregulate their function to uptake iron, they may increase the likelihood of escaping from nutritional immunity (LCN2 becomes insensitive to sequester iron from the bacteria). Would this raise the chance of developing sepsis? Do authors think that it is safe to administrate these engineered bacteria in mice or humans?

Reviewer #3 (Public Review):

Summary:

Based on their observation that tumor has an iron-deficient microenvironment, and the assumption that nutritional immunity is important in bacteria-mediated tumor modulation, the authors postulate that manipulation of iron homeostasis can affect tumor growth. They show that iron chelation and engineered DGC-E. coli have synergistic effects on tumor growth suppression. Using engineered IroA-E. coli that presumably have more resistance to LCN2, they show improved tumor suppression and survival rate. They also conclude that the IroA-E. coli treated mice develop immunological memory, as they are resistant to repeat tumor injections, and these effects are mediated by CD8+ T cells. Finally, they show synergistic effects of IroA-E. coli and oxaliplatin in tumor suppression, which may have important clinical implications.

Strengths:

This paper uses straightforward in vitro and in vivo techniques to examine a specific and important question of nutritional immunity in bacteria-mediated tumor therapy. They are successful in showing that manipulation of iron regulation during nutritional immunity does affect the virulence of the bacteria, and in turn the tumor. These findings open future avenues of investigation, including the use of different bacteria, different delivery systems for therapeutics, and different tumor types.

Weaknesses:

-- There is no discussion of the cancer type and why this cancer type was chosen. Colon cancer is not one of the more prominently studied cancer types for LCN2 activity. While this is a proof-of-concept paper, there should be some recognition of the potential different effects on different tumor types. For example, this model is dependent on significant LCN production, and different tumors have variable levels of LCN expression. Would the response of the tumor depend on the role of iron in that cancer type? For example, breast cancer aggressiveness has been shown to be influenced by FPN levels and labile iron pools.<br /> -- Are the effects on tumor suppression assumed to be from E. coli virulence, i.e. Does the higher number of bacteria result in increased immune-mediated tumor suppression? Or are the effects partially from iron status in the tumor cells and the TME?<br /> -- If the effects are iron-related, could the authors provide some quantification of iron status in tumor cells and/or the TME? Could the proteomic data be queried for this data?

Reviewer #1 (Public Review):

This work reports the use of pulsed high-intensity (1-3 W/cm2) 1 MHz ultrasonic waves to stimulate the secretion of extracellular vesicles (EVs) from skeletal muscle cells (C2C12 myotubes) through the modulation of intracellular calcium, and that these, in turn, regulate the inflammatory response in macrophages.

The authors first checked that the ultrasonic irradiation did not have any adverse effect on the structure (protein content) and function (proliferation and metabolic activity) of the myotubes, and showed an up to twofold increase in EV secretion, which they attributed to an increase in Ca2+ uptake into the cell. Finally, the authors show that the myotubes exposed to the ultrasonic irradiation wherein the EV concentration was found to be elevated led to a significant decrease in expression of IL-1b and IL-6 pro-inflammatory cytokines, therefore leading the authors to assert the potential of the use of ultrasonic irradiation for promoting anti-inflammatory effects on macrophages.

While the manuscript was reasonably clearly written and the methodology and results sound, it is not clear what the real contribution of the work is. The authors' findings - that ultrasonic stimulation is capable of altering intracellular Ca2+ to effect an increase in EV secretion from cells as long as the irradiation does not affect cell viability-is well established (see, for example, Ambattu et al., Commun Biol 3, 553, 2020; Deng et al., Theranostics, 11, 9 2021; Li et al., Cell Mol Biol Lett 28, 9, 2023). Moreover, the authors' own work (Maeshige et al., Ultrasonics 110, 106243, 2021) using the exact same stimulation (including the same parameters, i.e., intensity and frequency) and cells (C2C12 skeletal myotubes) reported this. Similarly, the authors themselves reported that EV secretion from C2C12 myotubes has the ability to regulate macrophage inflammatory response (Yamaguchi et al., Front Immunol 14, 1099799, 2023). It would then stand to reason that a reasonable and logical deduction from both studies is that the ultrasonic stimulation would lead to the same attenuation of inflammatory response in macrophages through enhanced secretion of EVs from the myotubes.

The authors' claim that 'the role of Ca2+ in ultrasound-induced EV release and its intensity-dependency are still unclear', and that the aim of the present work is to clarify the mechanism, is somewhat overstated. That ultrasonic stimulation alters intracellular Ca2+ to lead to EV release, therefore establishing their interdependency and hence demonstrating the mechanism by which EV secretion is enhanced by the ultrasonic stimulation, was detailed in Ambattu et al., Commun Biol 3, 553, 2020. While this was carried out at a slightly higher frequency (10 MHz) and slightly different form of ultrasonic stimulation, the same authors have appeared to since establish that a universal mechanism of transduction across an entire range of frequencies and stimuli (Ambattu, Biophysics Rev 4, 021301, 2023).

Similarly, the anti-inflammatory effects of EVs on macrophages have also been extensively reported (Li et al., J Nanobiotechnol 20, 38, 2022; Lo Sicco et al., Stem Cells Transl Med 6, 3, 2017; Hu et al., Acta Pharma Sin B 11, 6, 2021), including that by the authors themselves in a recent study on the same C2C12 myotubes (Yamaguchi et al., Front Immunol 14, 1099799, 2023). Moreover, the authors' stated aim for the present work - clarifying the mechanism of the anti-inflammatory effects of ultrasound-induced skeletal muscle-derived EVs on macrophages - appears to be somewhat redundant given that they simply repeated the microRNA profiling study they carried out in Yamaguchi et al., Front Immunol 14, 1099799, 2023. The only difference was that a fraction of the EVs (from identical cells) that they tested were now a consequence of the ultrasound stimulation they imposed.

That the authors have found that their specific type of ultrasonic stimulation maintains this EV content (i.e., microRNA profile) is novel, although this, in itself, appears to be of little consequence to the overall objective of the work which was to show the suppression of macrophage pro-inflammatory response due to enhanced EV secretion under the ultrasonic irradiation since it was the anti-inflammatory effects were attributed to the increase in EV concentration and not their content.

Reviewer #2 (Public Review):

Summary:<br /> The authors embarked on a journey to understand the mechanisms and intensity-dependency of ultrasound (US)-induced extracellular vesicle (EV) release from myotubes and the potential anti-inflammatory effects of these EVs on macrophages. This study builds on their prior work from 2021 that initially reported US-induced EV secretion.

Strengths:<br /> 1. The finding that US-treated myotube EVs can suppress macrophage inflammatory responses is particularly intriguing, hinting at potential therapeutic avenues in inflammation modulation.

Weaknesses:<br /> 1. The exploration of output parameters for US induction appears limited, with only three different output powers (intensities) tested, thus narrowing the scope of their findings.<br /> 2. Their claim of elucidating mechanisms seems to be only partially met, with a predominant focus on the correlation between calcium responses and EV release.<br /> 3. While the intracellular calcium response is a dynamic activity, the method used to measure it could risk a loss of kinetic information.<br /> 4. The inclusion of miRNA sequencing is commendable; however, the interpretation of this data fails to draw clear conclusions, diminishing the impact of this segment.

While the authors have shown the anti-inflammatory effects of US-induced EVs on macrophages, there are gaps in the comprehensive understanding of the mechanisms underlying US-induced EV release. Certain aspects, like the calcium response and the utility of miRNA sequencing, were not fully explored to their potential. Therefore, while the study establishes some findings, it leaves other aspects only partially substantiated.

Reviewer #2 (Public Review):

The manuscript of Akter et al is an important study that investigates the role of astrocytic Gi signaling in the anterior cingulate cortex in the modulation of extracellular L-lactate level and consequently impairment in flavor-place associates (PA) learning. However, whereas some of the behavioral observations and signaling mechanism data are compelling, the conclusions about the effect on memory are inadequate as they rely on an experimental design that does not allow to differentiate acute or learning effect from the effect outlasting pharmacological treatments, i.e. effect on memory retention. With the addition of a few experiments, this paper would be of interest to the larger group of researchers interested in neuron-glia interactions during complex behavior.<br /> • Largely, I agree with the authors' conclusion that activating Gi signaling in astrocytes impairs PA learning, however, the effect on memory retrieval is not that obvious. All behavioral and molecular signaling effects described in this study are obtained with the continuous presence of CNO, therefore it is not possible to exclude the acute effect of Gi pathway activation in astrocytes. What will happen with memory on retrieval test when CNO is omitted selectively during early, middle, or late session blocks of PA learning?<br /> • I found it truly exciting that the administration of exogenous L-lactate is capable to rescue CNO-induced PA learning impairment, when co-applied. Would it be possible that this treatment has a sensitivity to a particular stage of learning (acquisition, consolidation, or memory retrieval) when L-lactate administration would be the most efficacious?<br /> • The hypothesis that observed learning impairments could be associated with diminished mitochondrial biogenesis caused by decreased l-lactate in the result of astrocytic Gi-DREADDS stimulation is very appealing, but a few key pieces of evidence are missing. So far, the hypothesis is supported by experiments demonstrating reduced expression of several components of mitochondrial membrane ATP synthase and a decrease in relative mtDNA copy numbers in ACC of rats injected with Gi-DREADDs. L-lactate injections into ACC restored and even further increased the expression of the above-mentioned markers. Co-administration of NMDAR antagonist D-APV or MCT-2 (mostly neuronal) blocker 4-CIN with L-lactate, prevented L-lactate-induced increase in relative mtDNA copy. I am wondering how the interference with mitochondrial biogenesis is affecting neuronal physiology and if it would result in impaired PA learning or schema memory.

Reviewer #1 (Public Review):

The study by Akter et al demonstrates that astrocyte-derived L-lactate plays a key role in schema memory formation and promotes mitochondrial biogenesis in the Anterior Cingulate Cortex (ACC).

The main tool used by the authors is the DREADD technology that allows to pharmacologically activate receptors in a cell-specific manner. In the study, the authors used the DREADD technique to activate appropriately transfected astrocytes, a subtype of muscarinic receptor that is not normally present in cells. This receptor being coupled to a Gi-mediated signal transduction pathway inhibiting cAMP formation, the authors could demonstrate cell-(astrocyte) specific decreases in cAMP levels that result in decreased L-lactate production by astrocytes.

Behaviorally this pharmacological manipulation results in impairments of schema memory formation and retrieval in the ACC in flavor-place paired associate paradigms. Such impairments are prevented by co-administration of L-lactate.

The authors also show that activation of Gi signaling resulting in L-lactate decreased release by astrocytes impairs mitochondrial biogenesis in neurons in an L-lactate reversible manner.

By using MCT 2 inhibitors and an NMDAR antagonist the authors conclude that the molecular mechanisms underlying the observed effects are mediated by L-lactate entering neurons through MCT2 transporters and involve NMDAR.

Overall, the article's conclusions are warranted by the experimental evidence, but some weak points could be addressed which would make the conclusions even stronger.

The number of animals in some of the experiments is on the low side (4 to 6).<br /> The use of CIN to inhibit MCT2 is not optimal. Authors may want to decrease MCT2 expression by using antisense oligonucleotides.<br /> The experiment using AVP to block NMDAR only partially supports the conclusions. Indeed, blocking NMDAR will knock down any response that involves these receptors, whether L-lactate is necessary or not.<br /> Is inhibition of glycogenolysis involved in the observed effects mediated by Gi signaling? Indeed, L-lactate is formed both by glycolysis and glycogenolysis. The authors could test whether the glycogen metabolism-inhibiting drug DAB would mimic the effects of Gi activation.

Reviewer #3 (Public Review):

Akter et al. investigated how the astroglial Gi signaling pathway in the rat anterior cingulate cortex (ACC) affects cognitive functions, in particular schema memory formation. Using a stereotactic approach they intracranially introduced AAV8 vectors carrying mCherry-tagged hM4Di DREADD (Designer Receptor Exclusively Activated by Designer Drugs) under astrocyte selective GFAP promotor (AAV8-GFAP-hM4Di-mCherry) into the AAC region of the rat brain. hM4Di DREADD is a genetically modified form of the human M4 muscarinic (hM4) receptor insensitive to endogenous acetylcholine but is activated by the inert clozapine metabolite clozapine-N-oxide (CNO), triggering the Gi signaling pathway. The authors confirmed that hM4Di DREADD is selectively expressed in astrocytes after the application of the AAV8 vector by analysing the mCherry signals and immunolabeling of astrocytes and neurons in the ACC region of the rat brain. They activated hM4Di DREADD (Gi signalling) in astrocytes by intraperitoneal administration of CNO and measured cognitive functions in animals after CNO administration. Activation of Gi signaling in astrocytes by CNO application decreased paired-associate (PA) learning, schema formation, and memory retrieval in tested animals. This was associated with a decrease in cAMP in astrocytes and L-lactate in extracellular fluid as measured by immunohistochemistry in situ and in awake rats by microdialysis, respectively. Administration of exogenous L-lactate rescued the astroglial Gi-mediated deficits in PA learning, memory retrieval, and schema formation, suggesting that activation of astroglial Gi signalling downregulates L-lactate production in astrocytes and its transport to neurons affecting memory formation. Authors also show that expression level of proteins involved in mitochondrial biogenesis, which is associated with cognitive functions, is decreased in neurons, when Gi signalling is activated in astrocytes, and rescued when exogenous L-lactate is applied, suggesting the implication of astrocyte-derived L-lactate in the maintenance of mitochondrial biogenesis in neurons. The latter depended on lactate MCT2 transporter activity and glutamate NMDA receptor activity.

The paper is very well written and discussed. The conclusions of this paper are well supported by the data. Although this is a study that uses established and previously published methodologies, it provides new insights into L-lactate signalling in the brain, particularly in AAC, and further confirms the role of astroglial L-lactate in learning and memory formation. It also raises new questions about the molecular mechanisms underlying astrocyte-derived L-lactate-mediated mitochondrial biogenesis in neurons and its contribution to schema memory formation.

• The authors discuss astrocytic L-lactate signalling without considering the recently discovered L-lactate-sensitive Gs and Gi protein-coupled receptors in the brain, which are present in both astrocytes and neurons. The use of nonendogenous L-lactate receptor agonists (Compound 2, 3-chloro-5-hydroxybenzoic acid) would clarify the implication of L-lactate receptor signalling in schema memory formation.

• The use of control animals transduced with an "empty" AAV9 vector (AAV8-GFAP-mCherry) compared with animals transduced with AAV8-GFAP-hM4Di-mCherry throughout the study would strengthen the results of this study, since transfection itself, as well as overexpression of the mCherry protein, may affect cell function.

Reviewer #3 (Public Review):

Summary: This manuscript aims to unravel the mechanisms behind Aquaporin-0 (AQP0) tetramer array formation within lens membranes. The authors utilized electron crystallography and molecular dynamics (MD) simulations to shed light on the role of cholesterol in shaping the structural organization of AQP0. The evidence suggests that cholesterol not only defines the positions and orientations of associated molecules but also plays a crucial role in stabilizing AQP0 tetramer arrays. This study provides valuable insights into the potential principles driving protein clustering within lipid rafts, advancing our understanding of membrane biology.

In this review, I will focus on the MD simulations part, since this is my area of expertise. The authors conducted an impressive set of MD simulations aiming at understanding the role of cholesterol in structural organization of AQP0 arrays. These simulations clearly demonstrate the well-defined localization of cholesterol molecules around a single AQP0 tetramer, aligning with previous computational studies and the crystallographic structures presented in this manuscript. Interestingly, authors identified an unusual position for one cholesterol molecule, located near the center of the lipid bilayer, which was stabilized by the adjacent AQP0 tetramers. The authors showed that these adjacent tetramers can withstand a larger lateral detachment force when deep cholesterol molecules are present at the interface compared to scenarios with sphingomyelin (SM) molecules at the interface between two AQP0 tetramers. Authors interpret that result as evidence that deep cholesterol molecules mechanically stabilize the interface of the AQP0 tetramers. This conclusion has minor weaknesses, and the rigor of the lateral detachment simulations could be increased by establishing a reference point for the detachment force needed to separate AQP0 tetramers in a scenario without lipids at the interface between tetramers, and by increasing the number of repeats for the non-equilibrium steered MD simulations. Thermodynamic integration might be a better approach to compute the stabilization energy in the presence of cholesterol compared to the SM case.

Reviewer #1 (Public Review):

Aquaporin-0 forms 2D crystals in the lens of the eye. This propensity to form 2D crystals was originally exploited to solve the structure of aquaporin-0 reconstituted in membranes. Existing structures do not explain why the proteins spontaneously form these arrays, however. In this work the authors investigate the hypothesis that the main lipids in the native membranes, sphingomyelin and cholesterol, contribute to lattice formation. By titrating the cholesterol: sphingomyelin ratio, the authors identify cholesterol binding sites of increasing stability. The authors identify a cholesterol that interacts with adjacent tetramers and is bound at an unusual membrane depth. Computational simulations suggest that this cholesterol is only stable in the context of adjacent tetramers (ie lattice formation) and that the presence of the cholesterol increases the stability of that interface. The exact mechanism is not clear, but the authors propose that the so-called "deep cholesterol" improves shape complementarity between adjacent tetramers and modulates the kinetics of protein-protein interactions. Finally, the authors provide a reasonable model for the role of cholesterol in

Strengths of this manuscript include the analysis of multiple structures determined with different lipid compositions and lipid:cholesterol ratios. For each these, multiple lipids can be modelled, giving a good sense of the lipid specificity at various favorable lipid binding positions. In addition, multiple hypotheses are tested in a very thorough computational analysis that provides the framework for interpreting the structural observations. The authors also provide a thorough scholarly discussion that connects their work with other studies of membrane protein-cholesterol interactions.

The model presented by the authors is consistent with the data described. Further testing of this model, for example by mutating the deep cholesterol binding site, would strengthen the model. However, such experiments might be challenging due to the relatively non-specific/hydrophobic nature of the deep cholesterol binding site.

Reviewer #2 (Public Review):

Summary:<br /> In the manuscript by Chiu et al., "Structure and dynamics of cholesterol-mediated aquaporin-0 arrays and implications for lipid rafts," the authors address the effect of cholesterol on array formation by AQP0. Using a combination of electron crystallography and molecular dynamics simulations, the authors show binding of a "deep" cholesterol molecule between AQP0 tetramers. Each AQP0 tetramers binds four deep cholesterols to form a crystallographic array of AQP0.

Strengths:<br /> The combined approaches of electron crystallography and MD simulations under different lipid conditions (different sphingomyelin and cholesterol concentrations) are a strength of the study. The authors provide a thorough and convincing assessment of cholesterol binding, protein-protein interactions, and array formation by AQP0. The MD simulations allow the authors to consider the propensity of cholesterol to occupy the observed binding sites in the absence of crystal contacts. The combined methods and the breadth of analyses set a high standard in the field of membrane protein structural biology.

The findings of the authors fit nicely into a growing body of literature on cholesterol binding sites that mediate membrane protein-protein interactions. Cholesterol interacts with a variety of membrane proteins via its smooth alpha face of rough beta face. AQP0 is somewhat unique in that it binds the rough face of cholesterol in a "deep" binding site that places cholesterol in the middle of the membrane bilayer. So-called "deep" cholesterol binding sites have been described for GPCRs and docking studies suggest they may exist on other ion channels and transporters. In the case of AQP0, the deep cholesterol acts as a glue that holds two tetramers together. Since each tetramer has four binding sites for deep cholesterol, the assembly and mechanical stability of an extended two-dimensional array of AQP0 tetramers is a natural consequence in lens membranes.

Weaknesses:<br /> The authors report that the findings generally apply to raft formation in membranes. However, this point is less clear as the lens membrane in which AQP0 resides is rather unique in lipid and protein content and density. Nonetheless, the authors achieve the overall goal of evaluating cholesterol binding to AQP0, and there are many valuable and informative figures in the main manuscript and supplement that provide convincing results and interpretations.

Reviewer #3 (Public Review):

Summary:<br /> This paper by Sabelo et al. describes a new pathway by which lack of IgM in the mouse lowers bronchial hyperresponsiveness (BHR) in response to metacholine in several mouse models of allergic airway inflammation in Balb/c mice and C57/Bl6 mice. Strikingly, loss of IgM does not lead to less eosinophilic airway inflammation, Th2 cytokine production or mucus metaplasia, but to a selective loss of BHR. This occurs irrespective of the dose of allergen used. This was important to address since several prior models of HDM allergy have shown that the contribution of B cells to airway inflammation and BHR is dose dependent.

After a description of the phenotype, the authors try to elucidate the mechanisms. There is no loss of B cells in these mice. However, there is a lack of class switching to IgE and IgG1, with a concomitant increase in IgD. Restoring immunoglobulins with transfer of naïve serum in IgM deficient mice leads to restoration of allergen-specific IgE and IgG1 responses, which is not really explained in the paper how this might work. There is also no restoration of IgM responses, and concomitantly, the phenotype of reduced BHR still holds when serum is given, leading authors to conclude that the mechanism is IgE and IgG1 independent. Wild type B cell transfer also does not restore IgM responses, due to lack of engraftment of the B cells. Next authors do whole lung RNA sequencing and pinpoint reduced BAIAP2L1 mRNA as the culprit of the phenotype of IgM-/- mice. However, this cannot be validated fully on protein levels and immunohistology since differences between WT and IgM KO are not statistically significant, and B cell and IgM restoration are impossible. The histology and flow cytometry seems to suggest that expression is mainly found in alpha smooth muscle positive cells, which could still be smooth muscle cells or myofibroblasts. Next therefore, the authors move to CRISPR knock down of BAIAP2L1 in a human smooth muscle cell line, and show that loss leads to less contraction of these cells in vitro in a microscopic FLECS assay, in which smooth muscle cells bind to elastomeric contractible surfaces.

Strengths:<br /> 1. There is a strong reduction in BHR in IgM-deficient mice, without alterations in B cell number, disconnected from effects on eosinophilia or Th2 cytokine production<br /> 2. BAIAP2L1 has never been linked to asthma in mice or humans

Weaknesses:

1. While the observations of reduced BHR in IgM deficient mice are strong, there is insufficient mechanistic underpinning on how loss of IgM could lead to reduced expression of BAIAP2L1. Since it is impossible to restore IgM levels by either serum or B cell transfer and since protein levels of BAIAP2L1 are not significantly reduced, there is a lack of a causal relationship that this is the explanation for the lack of BHR in IgM-deficient mice. The reader is unclear if there is a fundamental (maybe developmental) difference in non-hematopoietic cells in these IgM-deficient mice (which might have accumulated another genetic mutation over the years). In this regard, it would be important to know if littermates were newly generated, or historically bred along with the KO line.<br /> 2. There is no mention of the potential role of complement in activation of AHR, which might be altered in IgM-deficient mice<br /> 3. What is the contribution of elevated IgD in the phenotype of the IgM-deficient mice. It has been described by this group that IgD levels are clearly elevated<br /> 4. How can transfer of naïve serum in class switching deficient IgM KO mice lead to restoration of allergen specific IgE and IgG1?<br /> 5. Alpha smooth muscle antigen is also expressed by myofibroblasts. This is insufficiently worked out. The histology mentions "expression in cells in close contact with smooth muscle". This needs more detail since it is a very vague term. Is it in smooth muscle or in myofibroblasts.<br /> 6. Have polymorphisms in BAIAP2L1 ever been linked to human asthma?<br /> 7. IgM deficient patients are at increased risk for asthma. This paper suggests the opposite. So the translational potential is unclear.

Reviewer #1 (Public Review):

Summary: The authors of this study sought to define a role for IgM in responses to house dust mites in the lung.

Strengths:

Unexpected observation about IgM biology<br /> Combination of experiments to elucidate function

Weaknesses:

Would love more connection to human disease

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Hadebe and colleagues describes a striking reduction in airway hyperresponsiveness in Igm-deficient mice in response to HDM, OVA and papain across the B6 and BALB-c backgrounds. The authors suggest that the deficit is not due to improper type 2 immune responses, nor an aberrant B cell response, despite a lack of class switching in these mice. Through RNA-Seq approaches, the authors identify few differences between the lungs of WT and Igm-deficient mice, but see that two genes involved in actin regulation are greatly reduced in IgM-deficient mice. The authors target these genes by CRISPR-Cas9 in in vitro assays of smooth muscle cells to show that these may regulate cell contraction. While the study is conceptually interesting, there are a number of limitations, which stop us from drawing meaningful conclusions.

Strengths:<br /> Fig. 1. The authors clearly show that IgMKO mice have striking reduced AHR in the HDM model, despite the presence of a good cellular B cell response.

Weaknesses:<br /> Fig. 2.<br /> The authors characterize the cd4 t cell response to HDM in IGMKO mice.<br /> They have restimulated medLN cells with antiCD3 for 5 days to look for IL-4 and IL-13, and find no discernible difference between WT and KO mice. The absence of PBS-treated WT and KO mice in this analysis means it is unclear if HDM-challenged mice are showing IL-4 or IL-13 levels above that seen at baseline in this assay. The choice of 5 days is strange, given that the response the authors want to see is in already primed cells. A 1-2 day assay would have been better. It is concerning that the authors state that HDM restimulation did not induce cytokine production from medLN cells, since countless studies have shown that restimulation of medLN would induce IL-13, IL-5 and IL-10 production from medLN. This indicates that the sensitization and challenge model used by the authors is not working as it should. The IL-13 staining shown in panel c is also not definitive. One should be able to optimize their assays to achieve a better level of staining, to my mind.

In d-f, the authors perform a serum transfer, but they only do this once. The half life of IgM is quite short. The authors should perform multiple naïve serum transfers to see if this is enough to induce FULL AHR.

The presence of negative values of total IgE in panel F would indicate some errors in calculation of serum IgE concentrations.

Overall, it is hard to be convinced that IgM-deficiency does not lead to a reduction in Th2 inflammation, since the assays appear suboptimal.

Fig. 3. Gene expression differences between WT and KO mice in PBS and HDM challenged settings are shown. PCA analysis does not show clear differences between all four groups, but genes are certainly up and downregulated, in particular when comparing PBS to HDM challenged mice. In both PBS and HDM challenged settings, three genes stand out as being upregulated in WT v KO mice. these are Baiap2l1, erdr1 and Chil1.

Fig. 4. The authors attempt to quantify BAIAP2L1 in mouse lungs. It is difficult to know if the antibody used really detects the correct protein. A BAIAP2L1-KO is not used as a control for staining, and I am not sure if competitive assays for BAIAP2L1 can be set up. The flow data is not convincing. The immunohistochemistry shows BAIAP2L1 (in red) in many, many cells, essentially throughout the section. There is also no discernible difference between WT and KO mice, which one might have expected based on the RNA-Seq data. So, from my perspective, it is hard to say if/where this protein is located, and whether there truly exists a difference in expression between wt and ko mice.

Fig. 5 and 6. The authors use a single cell contractility assay to measure whether BAIAP2L1 and ERDR1 impact on bronchial smooth muscle cell contractility. I am not familiar with the assay, but it looks like an interesting way of analysing contractility at the single cell level.<br /> The authors state that targeting these two genes with Cas9gRNA reduces smooth muscle cell contractility, and the data presented for contractility supports this observation. However, the efficiency of Cas9-mediated deletion is very unclear. The authors present a PCR in supp fig 9c as evidence of gene deletion, but it is entirely unclear with what efficiency the gene has been deleted. One should use sequencing to confirm deletion. Moreover, if the antibody was truly working, one should be able to use the antibody used in Fig 4 to detect BAIAP2L1 levels in these cells. The authors do not appear to have tried this.

Other impressions:<br /> The paper is lacking a link between the deficiency of IgM and the effects on smooth muscle cell contraction.<br /> The levels of IL-13 and TNF in lavage of WT and IGMKO mice could be analysed.

Moreover, what is the impact of IgM itself on smooth muscle cells? In the Fig. 7 schematic, are the authors proposing a direct role for IgM on smooth muscle cells? Does IgM in cell culture media induce contraction of SMC? This could be tested and would be interesting, to my mind.

Reviewer #2 (Public Review):

Summary:

The manuscript by Wohlwend et al. investigates the implications of inhibiting ceramide synthase Cers1 on skeletal muscle function during aging. The authors propose a role for Cers1 in muscle myogenesis and aging sarcopenia. Both pharmacological and AAV-driven genetic inhibition of Cers1 in 18-month-old mice lead to reduced C18 ceramides in skeletal muscle, exacerbating age-dependent features such as muscle atrophy, fibrosis, and center-nucleated fibers. Similarly, inhibition of the Cers1 orthologue in C. elegans reduces motility and causes alterations in muscle morphology.

Strengths:

The study is well-designed, carefully executed, and provides highly informative and novel findings that are relevant to the field.

Weaknesses:

The following points should be addressed to support the conclusions of the manuscript.

1) It would be essential to investigate whether P053 treatment of young mice induces age-dependent features besides muscle loss, such as muscle fibrosis or regeneration. This would help determine whether the exacerbation of age-dependent features solely depends on Cers1 inhibition or is associated with other factors related to age-dependent decline in cell function. Additionally, considering the reported role of Cers1 in whole-body adiposity, it is necessary to present data on mice body weight and fat mass in P053-treated aged-mice.

2) As grip and exercise performance tests evaluate muscle function across several muscles, it is not evident how intramuscular AAV-mediated Cers1 inhibition solely in the gastrocnemius muscle can have a systemic effect or impact different muscles. This point requires clarification.

3) To further substantiate the role of Cers1 in myogenesis, it would be crucial to investigate the consequences of Cers1 inhibition under conditions of muscle damage, such as cardiotoxin treatment or eccentric exercise.

4) It would be informative to determine whether the muscle defects are primarily dependent on the reduction of C18-ceramides or the compensatory increase of C24-ceramides or C24-dihydroceramides.

5) Previous studies from the research group (PMID 37118545) have shown that inhibiting the de novo sphingolipid pathway by blocking SPLC1-3 with myriocin counteracts muscle loss and that C18-ceramides increase during aging. In light of the current findings, certain issues need clarification and discussion. For instance, how would myriocin treatment, which reduces Cers1 activity because of the upstream inhibition of the pathway, have a positive effect on muscle? Additionally, it is essential to explain the association between the reduction of Cers1 gene expression with aging (Fig. 1B) and the age-dependent increase in C18-ceramides (PMID 37118545).

Addressing these points will strengthen the manuscript's conclusions and provide a more comprehensive understanding of the role of Cers1 in skeletal muscle function during aging.

Reviewer #1 (Public Review):

Summary: The authors identified that genetically and pharmacological inhibition of CERS1, an enzyme implicated in ceramides biosynthesis worsen muscle fibrosis and inflammation during aging.

Strengths: the study points out an interesting issue on excluding CERS1 inhibition as a therapeutic strategy for sarcopenia. Overall, the article it's well written and clear.

Weaknesses: Many of the experiments confirmed previous published data, which also show a decline of CERS1 in ageing and the generation and characterization of a muscle specific knockout mouse line. The mechanistic insights of how the increased amount of long ceramides (cer c24) and the decreased of shorter ones (cer c18) might influence muscle mass, force production, fibrosis and inflammation in aged mice have not been addressed.

Reviewer #3 (Public Review):

The valuable work shows some unique characteristics of long-lived PCs in comparison with bulk PCs. In particular, the authors clearly indicated the dependency of CXCR4 in PC longevity and provided a deal of resource of PC transcriptomes. Though CD93 is known as a marker for long-lived PCs, the authors can provide more data related to CD93.

Summary: Long-lived PCs are maintained with low motility and in a CXCR4-dependent manner.

Strengths: The reporter mice for fate-mapping can clearly distinguish long-lived PCs from total PCs and greatly contribute to the identification of long-lived PCs.

Weaknesses: The authors are unable to find a unique marker for long-lived PCs.

Reviewer #1 (Public Review):

The mechanisms underlying the generation and maintenance of LLPCs have been one of the unresolved issues. Recently, four groups have independently generated new genetic tools that allow fate tracing of murine plasma cells and have addressed how LLPCs are generated or maintained in homeostatic conditions or upon antigen immunization or viral infection. Here, Jing et al. have established another, but essentially the same, PC time stamping system, and tried to address the issues above. The question is whether the findings reported here provide significant conceptual advances from what has already been published.

1) Some of the observations in this manuscript have already been made by other studies (Xu et al. 2020, Robinson et al. 2022, Liu et al. 2022, Koike et al. 2023, Robinson et al. 2023). In my opinion, however, genetic analysis of the role of CXCR4 on PC localization or survival in BM (Figure 5) was well performed and provided some new aspects which have not been addressed in previous reports. The motility of CXCR4 cKO plasma cells in BM is not shown, but it could further support the idea that reduced mobility or increased clustering is required for longevity.

2) The combination of the several surface markers shown in Figure 3&4 doesn't seem to be practically applicable to identify or gate on LLPCs, because differential expression of CD81, CXCR4, CD326, CD44, or CD48 on LLPCs vs bulk PCs was very modest. EpCAMhi/CXCR3-, Ly6Ahi/Tigit- (Liu et al. 2022), B220lo/MHC-IIlo (Koike et al. 2023), or SLAMF6lo/MHC-IIlo (Robinson et al. 2023) has been reported as markers for LLPC population. It is unclear that the combination of surface markers presented here is superior to published markers. In addition, it is unclear why the authors did not use their own gene expression data (Fig.6), instead of using public datasets, for picking up candidate markers.

Reviewer #2 (Public Review):

In this study by Jing, Fooksman, and colleagues, a Blimp1-CreERT2-based genetic tracing study is employed to label plasma cells. Over the course of several months post-tamoxifen treatment, the only remaining labeled cells are long-lived plasma cells. This system provides a way to sort live long-lived plasma cells and compare them to unlabeled plasma cells, which contain a range of short-to-long-lived cells. From this analysis, several observations are made: 1) the turnover rate of plasma cells is greater in the spleen than in the bone marrow; 2) the turnover rate is highest early in life; 3) subtle transcriptional and cell surface marker differences distinguish long- from shorter-lived plasma cells; 4) long-lived plasma cells in the bone marrow are sessile and localize in clusters with each other; 5) CXCR4 is required for plasma cell retention in these clusters and in the bone marrow; 6) Repertoire analysis hints that the selection of long-lived plasma cells is not random for any cell that lands in the bone marrow.

Strengths:

1) The genetic timestamping approach is a clever and functional way to separate plasma cells of differing longevities.

2) This approach led to the identification of several markers that could help prospective separation of long-lived plasma cells from others.

3) Functional labeling of long-lived plasma cells allowed for a higher resolution analysis of transcriptomes and motility than was previously possible.

4) The genetic system allowed for a revisitation of the importance of CXCR4 in plasma cell retention and survival.

Weaknesses:

1) Most of the labeling studies, likely for practical reasons, were done on polyclonal rather than antigen-specific plasma cells. The triggers of these responses could vary based on age at the time of exposure, anatomical sites, etc. How these differences might influence markers and transcriptomes, independently of longevity, is not completely known.

2) The fraction of long-lived plasma cells in the unlabeled fraction varies with age, potentially diluting differences between long- and short-lived plasma cells.

3) The authors suggest their data favors a model by which plasma cells compete for niche space. Yet there is no evidence presented here that these niches are limiting.

4) The functional importance of the observed transcriptome differences between long- and shorter-lived plasma cells is unknown. An assessment as to whether these differences are conserved in human long- and short-lived bone marrow plasma cells might provide circumstantial supporting evidence that these changes are important for longevity.

Reviewer #1 (Public Review):

I have a major conceptual problem with this manuscript: How can the full deletion of a gene (PARG) sensitize a cell to further inhibition by its chemical inhibitor (PARGi) since the target protein is fully absent?

The authors state in the discussion section: "The residual PARG dePARylation activity observed in PARG KO cells likely supports cell growth, which can be further inhibited by PARGi". What does this statement mean? Is the authors' conclusion that their PARG KOs are not true KOs but partial hypomorphic knockdowns? Were the authors working with KO clones or CRISPR deletion in populations of cells?

Are there splice variants of PARG that were not knocked down? Are there PARP paralogues that can complement the biochemical activity of PARG in the PARG KOs? The authors do not discuss these critical issues nor engage with this problem.

These issues have to be dealt with upfront in the manuscript for the reader to make sense of their work.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Nie et al investigate the effect of PARG KO and PARG inhibition (PARGi) on pADPR, DNA damage, cell viability, and synthetic lethal interactions in HEK293A and Hela cells. Surprisingly, the authors report that PARG KO cells are sensitive to PARGi and show higher pADPR levels than PARG KO cells, which are abrogated upon deletion or inhibition of PARP1/PARP2. The authors explain the sensitivity of PARG KO to PARGi through incomplete PARG depletion and demonstrate complete loss of PARG activity when incomplete PARG KO cells are transfected with additional gRNAs in the presence of PARPi. Furthermore, the authors show that the sensitivity of PARG KO cells to PARGi is not caused by NAD depletion but by S-phase accumulation of pADPR on chromatin coming from unligated Okazaki fragments, which are recognized and bound by PARP1. Consistently, PARG KO or PARG inhibition shows synthetic lethality with Pol beta, which is required for Okazaki fragment maturation. PARG expression levels in ovarian cancer cell lines correlate negatively with their sensitivity to PARGi.

Strengths:<br /> The authors show that PARG is essential for removing ADP-ribosylation in S-phase.

Weaknesses:<br /> 1) This begs the question as to the relevant substrates of PARG in S-phase, which could be addressed, for example, by analysing PARylated proteins associated with replication forks in PARG-depleted cells (EdU pulldown and Af1521 enrichment followed by mass spectrometry).<br /> 2) The results showing the generation of a full PARG KO should be moved to the beginning of the Results section, right after the first Results chapter (PARG depletion leads to drastic sensitivity to PARGi), otherwise, the reader is left to wonder how PARG KO cells can be sensitive to PARGi when there should be presumably no PARG present.<br /> 3) Please indicate in the first figure which isoforms were targeted with gRNAs, given that there are 5 PARG isoforms. You should also highlight that the PARG antibody only recognizes the largest isoform, which is clearly absent in your PARG KO, but other isoforms may still be produced, depending on where the cleavage sites were located.<br /> 4) FACS data need to be quantified. Scatter plots can be moved to Supplementary while quantification histograms with statistical analysis should be placed in the main figures.<br /> 5) All colony formation assays should be quantified and sensitivity plots should be shown next to example plates.<br /> 6) Please indicate how many times each experiment was performed independently and include statistical analysis.

Reviewer #3 (Public Review):

Here the authors carried out a CRISPR/sgRNA screen with a DDR gene-targeted mini-library in HEK293A cells looking for genes whose loss increased sensitivity to treatment with the PARG inhibitor, PDD00017273 (PARGi). Surprisingly they found that PARG itself, which encodes the cellular poly(ADP-ribose) glycohydrolase (dePARylation) enzyme, was a major hit. Targeted PARG KO in 293A and HeLa cells also caused high sensitivity to PARGi. When PARG KO cells were reconstituted with catalytically-dead PARG, MMS treatment caused an increase in PARylation, not observed when cells were reconstituted with WT PARG or when the PARG KO was combined with PARP1/2 DKO, suggesting that loss of PARG leads to a strong PARP1/2-dependent increase in protein PARylation. The decrease in intracellular NADH+, the substrate for PARP-driven PARylation, observed in PARG KO cells was reversed by treatment with NMN or NAM, and this treatment partially rescued the PARG KO cell lethality. However, since NAD+ depletion with the FK868 nicotinamide phosphoribosyltransferase (NAMPT) inhibitor did not induce a similar lethality the authors concluded that NAD+ depletion/reduction was only partially responsible for the PARGi toxicity. Interestingly, PARylation was also observed in untreated PARG KO cells, specifically in S phase, without a significant rise in γH2AX signals. Using cells synchronized at G1/S by double thymidine blockade and release, they showed that entry into S phase was necessary for PARGi to induce PARylation in PARG KO cells. They found an increased association of PARP1 with a chromatin fraction in PARG KO cells independent of PARGi treatment, and suggested that PARP1 trapping on chromatin might account in part for the increased PARGi sensitivity. They also showed that prolonged PARGi treatment of PARG KO cells caused S phase accumulation of pADPr eventually leading to DNA damage, as evidenced by increased anti-γH2AX antibody signals and alkaline comet assays. Based on the use of emetine, they deduced that this response could be caused by unligated Okazaki fragments. Next, they carried out FACS-based CRISPR screens to identify genes that might be involved in cell lethality in WT and PARG KO cells, finding that loss of base excision repair (BER) and DNA repair genes led to increased PARylation and PARGi sensitivity, whereas loss of PARP1 had the opposite effects. They also found that BER pathway disruption exhibited synthetic lethality with PARGi treatment in both PARG KO cells and WT cells, and that loss of genes involved in Okazaki fragment ligation induced S phase pADPr signaling. In a panel of human ovarian cancer cell lines, PARGi sensitivity was found to correlate with low levels of PARG mRNA, and they showed that the PARGi sensitivity of cells could be reduced by PARPi treatment. Finally, they addressed the conundrum of why PARG KO cells should be sensitive to a specific PARG inhibitor if there is no PARG to inhibit and found that the PARG KO cells had significant residual PARG activity when measured in a lysate activity assay, which could be inhibited by PARGi, although the inhabited PARG activity levels remained higher than those of PARG cKO cells (see below). This led them to generate new, more complete PARG KO cells they called complete/conditional KO (cKO), whose survival required the inclusion of the olaparib PARPi in the growth medium. These PARG cKO cells exhibited extremely low levels of PARG activity in vitro, consistent with a true PARG KO phenotype.

The finding that human ovarian cancer cells with low levels of PARG are more sensitive to inhibition with a small molecule PARG inhibitor, presumably due to the accumulation of high levels of protein PARylation (pADPr) that are toxic to cells is quite interesting, and this could be useful in the future as a diagnostic marker for preselection of ovarian cancer patients for treatment with a PARG inhibitor drug. The finding that loss of base excision repair (BER) and DNA repair genes led to increased PARylation and PARGi sensitivity is in keeping with the conclusion that PARG activity is essential for cell fitness, because it prevents excessive protein PARylation. The observation that increased PARylation can be detected in an unperturbed S phase in PARG KO cells is also of interest. However, the functional importance of protein PARylation at the replication fork in the normal cell cycle was not fully investigated, and none of the key PARylation targets for PARG required for S phase progression were identified. Overall, there are some interesting findings in the paper, but their impact is significantly lessened by the confusing way in which the paper has been organized and written, and this needs to be rectified.

Reviewer #1 (Public Review):

The authors consider data by the Heisenberg group on rheological properties of non-confluent tissue in zebrafish embryos. These data had shown a steep increase and subsequent saturation in viscosity with cell density. The authors introduce a physical agent-based model of such tissues that accounts for the dispersion in cell size and the softness of the cells. The model is inspired by previous models to study glassy dynamics and reveals essential physical features that can explain the observed behavior. It goes beyond previous studies that had analysed the observations in terms of a percolation problem. The numerics is thoroughly done and could have a deep impact on how we describe non-confluent tissues.

Reviewer #2 (Public Review):

This paper explores how minimal active matter simulations can model tissue rheology, with applications to the in vivo situation of zebrafish morphogenesis. The authors explore the idea of active noise, particle softness and size heterogeneity cooperating to give rise to surprising features of experimental tissue rheologies (in particular an increase and then a plateau in viscosity with fluid fraction). In general, the paper is interesting from a theoretical standpoint, by providing a bridge between concepts from jamming of particulate systems and experiments in developmental biology. The idea of exploring a free space picture in this context is also interesting. However, I'm still unsure right now though of how much it can be applied to the specific system that the authors refer to - which could be fixed either by doing theoretical checks or considering other experimental systems/models reported in the recent literature.

Reviewer #3 (Public Review):

The authors successfully explain the sharp rise and subsequent saturation of the viscosity in dependence of cell packing fraction in zebrafish blastoderm with the help of a 2D model of soft deformable, polydisperse and self-propelled (active) disks. The main experimental observations can be reproduced and the unusual dependence of the viscosity on packing fraction can be explained by the available free area and the emergent motility of small sized cells facilitating multi-cell rearrangement in a highly jammed environment.

The paper is very well written, the results (experimental as well as theoretical) are original and scientifically valid. This is an important contribution to understanding the rheological properties of non-confluent tissues linking equilibrium and transport properties.

Reviewer #1 (Public Review):

This paper provides new evidence on the relationship between genetic/chromosome divergence and capacity for asexual reproduction (via unreduced, clonal gametes) in hybrid males or females. Whereas previous studies have focussed just on the hybrid combinations that have yielded asexual lineages in nature, the authors take an experimental approach, analysing meiotic processes in F1 hybrids for combinations of species spanning different levels of divergence, whether or not they form asexual lineages in nature. As such, the findings here are a substantial advance towards understanding how new asexual lineages form.

The quality of the work is high, the analyses are sound, and the authors sensibly link their observations to the speciation continuum. I should also add that the cytogenetic work here is just beautiful!

A key finding is that the precondition for asexual reproduction - the formation of unreduced gametes - is not unusual among hybrid females, so that we have to consider other factors to explain the rarity of asexual species - a major unresolved issue in evolutionary biology. This work also highlights a previously overlooked effect of chromosome organisation on speciation.

Reviewer #2 (Public Review):

The authors investigate the origin of asexual reproduction through hybridization between species. In loaches, diploid, polyploid, and asexual forms have been described in natural populations. The authors experimentally cross multiple species of loaches and conduct an impressively detailed characterization of gametogenesis using molecular cytogenetics to show that although meiosis arrests early in male hybrids, a subset of cells in females undergo endoreplication before meiosis, producing diploid eggs. This only occurred in hybrids of parental species that were of intermediate divergence. This work supports an expanding view of speciation where asexuality could emerge during a narrow evolutionary window where genomic divergence between species is not too high to cause hybrid inviability, but high enough to disrupt normal meiotic processes.

I enjoyed reading this study and I was impressed by the rigorous experiments. The authors provide strong evidence that premeiotic genome endoreplication is the mechanism behind asexually-reproducing females. In addition, I found the evidence convincing that this phenomenon is a consequence of combining two divergent genomes in an F1 hybrid female. The authors did not observe a single incidence of genome duplication in any of the parental species among a large number of surveyed oocytes.

Reviewer #1 (Public Review):

The manuscript "Diffusive lensing as a mechanism of intracellular transport and compartmentalization", explores the implications of heterogeneous viscosity on the diffusive dynamics of particles. The authors analyze three different scenarios:

(i) diffusion under a gradient of viscosity,

(ii) clustering of interacting particles in a viscosity gradient, and

(iii) diffusive dynamics of non-interacting particles with circular patches of heterogeneous viscous medium.

The implications of a heterogeneous environment on phase separation and reaction kinetics in cells are under-explored. This makes the general theme of this manuscript very relevant and interesting. However, the analysis in the manuscript is not rigorous, and the claims in the abstract are not supported by the analysis in the main text.

Following are my main comments on the work presented in this manuscript:

(a) The central theme of this work is that spatially varying viscosity leads to position-dependent diffusion constant. This, for an overdamped Langevin dynamics with Gaussian white noise, leads to the well-known issue of the interpretation of the noise term. The authors use the Ito interpretation of the noise term because their system is non-equilibrium.

One of the main criticisms I have is on this central point. The issue of interpretation arises only when there are ill-posed stochastic dynamics that do not have the relevant timescales required to analyze the noise term properly. Hence, if the authors want to start with an ill-posed equation it should be mentioned at the start. At least the Langevin dynamics considered should be explicitly mentioned in the main text. Since this work claims to be relevant to biological systems, it is also of significance to highlight the motivation for using the ill-posed equation rather than a well-posed equation. The authors refer to the non-equilibrium nature of the dynamics but it is not mentioned what non-equilibrium dynamics to authors have in mind. To properly analyze an overdamped Langevin dynamics a clear source of integrated timescales must be provided. As an example, one can write the dynamics as<br /> Eq. (1) \dot x = f(x) + g(x) \eta , which is ill-defined if the noise \eta is delta correlated in time but well-defined when \eta is exponentially correlated in time. One can of course look at the limit in which the exponential correlation goes to a delta correlation which leads to Eq. (1) interpreted in Stratonovich convention. The choice to use the Ito convention for Eq. (1) in this case is not justified.

(b) Generally, the manuscript talks of viscosity gradient but the equations deal with diffusion which is a combination of viscosity, temperature, particle size, and particle-medium interaction. There is no clear motivation provided for focus on viscosity (cytoplasm as such is a complex fluid) instead of just saying position-dependent diffusion constant. Maybe authors should use viscosity only when talking of a context where the existence of a viscosity gradient is established either in a real experiment or in a thought experiment.

(c) The section "Viscophoresis drives particle accumulation" seems to not have new results. Fig. 1 verifies the numerical code used to obtain the results in the later sections. If that is the case maybe this section can be moved to supplementary or at least it should be clearly stated that this is to establish the correctness of the simulation method. It would also be nice to comment a bit more on the choice of simulation methods with changing hopping sizes instead of, for example, numerically solving stochastic ODE.

A minor comment, the statement "the physically appropriate convention to use depends upon microscopic parameters and timescale hierarchies not captured in a coarse-grained model of diffusion." is not true as is noted in the references that authors mention, a correct coarse-grained model provides a suitable convention (see also Phys. Rev. E, 70(3), 036120., Phys. Rev. E, 100(6), 062602.).

(d) The section "Interaction-mediated clustering is affected by viscophoresis" makes an interesting statement about the positioning of clusters by a viscous gradient. As a theoretical calculation, the interplay between position-dependent diffusivity and phase separation is indeed interesting, but the problem needs more analysis than that offered in this manuscript. Just a plot showing clustering with and without a gradient of diffusion does not give enough insight into the interplay between density-dependent diffusion and position-dependent diffusion. A phase plot that somehow shows the relative contribution of the two effects would have been nice. Also, it should be emphasized in the main text that the inter-particle interaction is through a density-dependent diffusion constant and not a conservative coupling by an interaction potential.

(e) The section "In silico microrheology shows that viscophoresis manifests as anomalous diffusion" the authors show that the MSD with and without spatial heterogeneity is different. This is not a surprise - as the underlying equations are different the MSD should be different. There are various analogies drawn in this section without any justification:<br /> (i) "the saturation MSD was higher than what was seen in the homogeneous diffusion scenario possibly due to particles robustly populating the bulk milieu followed by directed motion into the viscous zone (similar to that of a Brownian ratchet, (Peskin et al., 1993))."<br /> (ii) "Note that lensing may cause particle displacements to deviate from a Gaussian distribution, which could explain anomalous behaviors observed both in our simulations and in experiments in cells (Parry et al., 2014)."<br /> Since the full trajectory of the particles is available, it can be analyzed to check if this is indeed the case.

(f) The final section "In silico FRAP in a heterogeneously viscous environment ... " studies the MSD of the particles in a medium with heterogeneous viscous patches which I find the most novel section of the work. As with the section on inter-particle interaction, this needs further analysis.

To summarise, as this is a theory paper, just showing MSD or in silico FRAP data is not sufficient. Unlike experiments where one is trying to understand the systems, here one has full access to the dynamics either analytically or in simulation. So just stating that the MSD in heterogeneous and homogeneous environments are not the same is not sufficient. With further analysis, this work can be of theoretical interest. Finally, just as a matter of personal taste, I am not in favor of the analogy with optical lensing. I don't see the connection.

Reviewer #2 (Public Review):

Summary:<br /> The authors study through theory and simulations the diffusion of microscopic particles and aim to account for the effects of inhomogeneous viscosity and diffusion - in particular regarding the intracellular environment. They propose a mechanism, termed "Diffusive lensing", by which particles are attracted towards high-viscosity regions where they remain trapped. To obtain these results, the authors rely on agent-based simulations using custom rules performed with the Ito stochastic calculus convention, without spurious drift. They acknowledge the fact that this convention does not describe equilibrium systems, and that their results would not hold at equilibrium - and discard these facts by invoking the fact that cells are out-of-equilibrium. Finally, they show some applications of their findings, in particular enhanced clustering in the high-viscosity regions. The authors conclude that as inhomogeneous diffusion is ubiquitous in life, so must their mechanism be, and hence it must be important.

Strengths:<br /> The article is well-written, and clearly intelligible, its hypotheses are stated relatively clearly and the models and mathematical derivations are compatible with these hypotheses.

Weaknesses:<br /> The main problem of the paper is these hypotheses. Indeed, it all relies on the Ito interpretation of the stochastic integrals. Stochastic conventions are a notoriously tricky business, but they are both mathematically and physically well-understood and do not result in any "dilemma" [some citations in the article, such as (Lau and Lubensky) and (Volpe and Wehr), make an unambiguous resolution of these]. Conventions are not an intrinsic, fixed property of a system, but a choice of writing; however, whenever going from one to another, one must include a "spurious drift" that compensates for the effect of this change - a mathematical subtlety that is entirely omitted in the article: if the drift is zero in one convention, it will thus be non-zero in another in the presence of diffusive gradients. It is well established that for equilibrium systems obeying fluctuation-dissipation, the spurious drift vanishes in the anti-Ito stochastic convention (which is not "anticipatory", contrarily to claims in the article, are the "steps" are local and infinitesimal). This ensures that the diffusion gradients do not induce currents and probability gradients, and thus that the steady-state PDF is the Gibbs measure. This equilibrium case should be seen as the default: a thermal system NOT obeying this law should warrant a strong justification (for instance in the Volpe and Wehr review this can occur through memory effects in robotic dynamics, or through strong fluctuation-dissipation breakdown). In near-equilibrium thermal systems such as the intracellular medium (where, although out-of-equilibrium, temperature remains a relevant and mostly homogeneous quantity), deviations from this behavior must be physically justified and go to zero when going towards equilibrium.

Here, drifts are arbitrarily set to zero in the Ito convention (the exact opposite of the equilibrium anti-Ito), which is the equilibrium equivalent to adding a force (with drift $- grad D$) exactly compensating the spurious drift. If we were to interpret this as a breakdown of detailed balance with inhomogeneous temperature, the "hot" region would be effectively at 4x higher temperature than the cold region (i.e. 1200K) in Fig 1A.

It is the effects of this arbitrary force (exactly compensating the Ito spurious drift) that are studied in the article. The fact that it results in probability gradients is trivial once formulated this way (and in no way is this new - many of the references, for instance, Volpe and Wehr, mention this). Enhanced clustering is also a trivial effect of this probability gradient (the local concentration is increased by this force field, so phase separation can occur). As a side note the "neighbor sensing" scheme to describe interactions is very peculiar and not physically motivated - it violates stochastic thermodynamics laws too, as the detailed balance is apparently not respected. Finally, the "anomalous diffusion" discussion is at odds with what the literature on this subject considers anomalous (the exponent does not appear anomalous).

The authors make no further justification of their choice of convention than the fact that cells are out-of-equilibrium, leaving the feeling that this is a detail. They make mentions of systems (eg glycogen, prebiotic environment) for which (near-)equilibrium physics should mostly prevail, and of fluctuation-dissipation ("Diffusivity varies inversely with viscosity", in the introduction). Yet the "phenomenon" they discuss is entirely reliant on an undiscussed mechanism by which these assumptions would be completely violated (the citations they make for this - Gnesotto '18 and Phillips '12 - are simply discussions of the fact that cells are out-of-equilibrium, not on any consequences on the convention).

Finally, while inhomogeneous diffusion is ubiquitous, the strength of this effect in realistic conditions is not discussed (this would be a significant problem if the effect were real, which it isn't). Gravitational attraction is also an ubiquitous effect, but it is not important for intracellular compartmentalization.

To conclude, the "diffusive lensing" effect presented here is not a deep physical discovery, but a well-known effect of sticking to the wrong stochastic convention.

Reviewer #1 (Public Review):

Summary: Yin Luo and colleagues describe a new regulatory mode of TRAIL (Tumor necrosis factor (TNF)-related apoptosis-inducing ligand) -induced apoptosis of tumor cells. The work is timely because high expectations existed on the possibility to induce tumor-specific apoptosis by activation of TRAIL-receptors DR4 and DR5. So far, however, attempted TRAIL-based anti-tumor therapies failed, and several tumor types were found to resist TRAIL-induced apoptosis. The work is also important because it aims at a better mechanistic understanding of TRAIL-induced apoptosis and TRAIL resistance of some tumor types.

Strengths: The major novel finding of this study is that extracellular heparan sulfate (HS) acts as a positive regulator of TRAIL-induced tumor cell apoptosis, and that HS expression of different tumor cell lines correlates with their capacity to induce cell death. The authors first show by affinity chromatography and SPR that murine and human TRAIL bind strongly to heparin (heparin is a highly sulfated, and thus strongly negatively charged form of HS that is derived from connective tissue type mast cells), and identify three basic amino acids on the TRAIL N-terminus that are required for the interaction. Size exclusion chromatography (SEC) and multiangle light scattering (MALS) revealed that TRAIL exists as a trimer that requires a minimum heparin length of 8 sugar residues for binding, and small angle X-ray scattering (SAXS) showed that TRAIL interaction with longer oligosaccharides induced higher order multimerization of TRAIL. Consistent with these biochemical and biophysical analyses, HS on tumor cells contributes to TRAIL-binding to their cell surface and subsequent apoptosis. Minor novel findings include domain swapping observed by TRAIL trimer crystallization and different degrees of HS core protein and DR receptor expression in different tumor cell types. These findings are well supported and together with the advanced and established methodology used by the authors are the strengths of this paper. The paper will be of great interest to medical biologists studying TRAIL-resistance of tumors, to biologists interested in DR4 and DR5 receptor function and the effects of receptor internalization, and to glycobiologists aiming to understand the multiple important roles that HS plays in development and disease. The authors also raise the important point (and support it well) that routine heparin treatment of cancer patients potentially interferes with TRAIL-based therapies, providing one possible reason for their failure.

Weaknesses: Despite the importance and the clear strengths of the paper, some of its aspects could have been developed further to better support the authors claims and their hypothesis that HS downregulation may represent one strategy to explain tumor resistance to TRAIL-induced apoptosis.

1) The authors demonstrate that HS at the tumor surface promotes TRAIL binding, and that HS promotes TRAIL-induced breast cancer and myeloma cell apoptosis. These findings are based on pre-treatment with heparinase to remove cell-surface HS prior to TRAIL-treatment, or presence of soluble heparin to compete with cell-surface HS for TRAIL binding. A more direct way to establish such new HS function could have been genetic manipulation of cancer cells to overexpress HS (e.g. by Syndecan 1 core-protein transgene expression in resistant cell types, e.g. IM-9 cells) or to express less or undersulfated HS (by interfering with the biosynthetic pathway in apoptosis-prone cells, for example by targeted inactivation/RNAi of the HS co-polymerase or sulfotransferases in RPMI-8226 cells). Changed susceptibility of these cells to TRAIL-induced apoptosis would greatly support the authors claim and suggest one promising new strategy to decrease tumor resistance against TRAIL-induced apoptosis.

2) The mechanistics of TRAIL-induced, HS-modulated tumor cell apoptosis could be more clearly defined. For example, the authors demonstrate convincingly that cell surface HS is essential for TRAIL-induced apoptosis in MDA-MB-453 breast cancer cells, and later show that a tumor cell line (IM-9 cells) that expresses HS and the core protein to which HS is attached to only limited degrees is the most resistant to TRAIL-induced apoptosis. Yet, these findings suggest, but do not prove a dose-dependent role of HS in TRAIL-induced apoptosis. Indeed, the authors later report that cell surface HS promotes TRAIL-induced myeloma cell apoptosis regardless of the sensitivity levels, and that other factors - the degree of TRAIL multimerization or DR4/DR5 receptor internalization - are also important. A cartoon could be added to the final figure to sort through these possible mechanisms and their relative importance.

3) The authors show that RPMI-8226 cell-surface HS promotes DR5 internalization despite the absence of direct DR5/heparin interactions. This is important because, as the authors are certainly aware of, HS manipulation at the cell surface (for example by heparinase treatment) changes a plethora of signaling pathways that may also indirectly affect apoptosis. HS-dependent internalization of TRAIL-receptor complexes, however, provides an important direct link from HS expression to TRAIL-induced apoptosis. To further support this possible link, it would therefore be worthwhile to include the binding characteristics and HS-dependent internalization of DR4 into this study.

Reviewer #2 (Public Review):

Summary:<br /> In the manuscript by Luo et al, the authors investigated the nature and function of TRAIL-HS binding for the regulation of TRAIL-mediated apoptosis in cancer cells. The authors discovered that TRAIL binds to 12mer HS and identified the amino acid residues critical for the binding. The authors further nicely showed that 12mer HS binds to TRAIL homotrimer and larger HS can further promote the formation of larger TRAIL oligomers. Structural analyses were conducted to characterize the binding of TRAIL/HS complexes. At functional level, the authors demonstrated that HS promotes the cell surface binding of TRAIL to enhance TRAIL-mediated apoptosis in a variety of cancer cells. Moreover, the ability of TRAIL to induce apoptosis is correlated with cell surface HS level. Lastly, the authors showed that HS forms complex with TRAIL and its receptor DR5 and promotes DR5 internalization.

Strengths:<br /> Overall, this is a nicely executed study providing both mechanistic and functional insight for TRAIL-mediated apoptosis. It conducted detailed characterization on the direct binding between HS and TRAIL and provided solid evidence supporting the role of such interaction for the regulation of TRAIL-induced apoptosis. The experiments were well-designed with proper controls included. The data interpretation is accurate. The manuscript was clearly written and easy to follow by general readers.

Weaknesses:<br /> There is no major weakness identified from this study. However, the role of HS for the formation of TRAIL homotrimer needs to be further clarified. In addition, the current relationship between cell surface HS level and sensitivity to TRAIL-mediated apoptosis is still correlative, as the authors indicated. Additional evidence to support the regulatory function of HS would further strengthen the significance of the study.

Reviewer #1 (Public Review):

Summary:<br /> Pulfer et al., describe the development and testing of a transformer-based deep learning architecture called ADeS, which the authors use to identify apoptotic events in cultured cells and live animals. The classifier is trained on large datasets and provides robust classification accuracies in test sets that are comparable to and even outperform existing deep learning architectures for apoptosis detection. Following this validation, the authors also design use cases for their technique both in vitro and in vivo, demonstrating the value of ADeS to the apoptosis research space.

Strengths:<br /> ADeS is a powerful tool in the arsenal of cell biologists interested in the spatio-temporal co-ordinates of apoptotic events in vitro, since live cell imaging typically generates densely packed fields of view that are challenging to parse by manual inspection. The authors also integrate ADeS into the analysis of data generated using different types of fluorescent markers in a variety of cell types and imaging modalities, which increases its adaptability by a larger number of researchers. ADeS is an example of the successful deployment of activity recognition (AR) in the automated bioimage analysis space, highlighting the potential benefits of AR to quantifying other intra- and intercellular processes observable using live cell imaging.

Weaknesses:<br /> A major drawback was the lack of access to the ADeS platform for the reviewers; the authors state that the code is available in the code availability section, which is missing from the current version of the manuscript. This prevented an evaluation of the usability of ADeS as a resource for other researchers. The authors also emphasize the need for label-free apoptotic cell detection in both their abstract and their introduction but have not demonstrated the performance of ADeS in a true label-free environment where the cells do not express any fluorescent markers. While Pulfer et al., provide a wealth of information about the generation and validation of their DL classifier for in vitro movies, and the utility of ADeS is obvious in identifying apoptotic events among FOVs containing ~1700 cells, the evidence is not as strong for in vivo use cases. They mention the technical challenges involved in identifying apoptotic events in vivo, and use 3D rotation to generate a larger dataset from their original acquisitions. However, it is not clear how this strategy would provide a suitable training dataset for understanding the duration of apoptotic events in vivo since the temporal information remains the same. The authors also provide examples of in vivo acquisitions in their paper, where the cell density appears to be quite low, questioning the need for automated apoptotic detection in those situations. In the use cases for in vivo apoptotic detection using ADeS (Fig 8), it appears that the location of the apoptotic event itself was obvious and did not need ADeS, as in the case of laser ablation in the spleen and the sparse distribution of GFP labeled neutrophils in the lymph nodes. Finally, the authors also mention that video quality altered the sensitivity of ADeS in vivo (Fig 6L) but fail to provide an example of ADeS implementation on a video of poor quality, which would be useful for end users to assess whether to adopt ADeS for their own live cell movies.

Reviewer #2 (Public Review):

Summary:<br /> Pulfer A. et al. developed a deep learning-based apoptosis detection system named ADeS, which outperforms the currently available computational tools for in vitro automatic detection. Furthermore, ADeS can automatically identify apoptotic cells in vivo in intravital microscopy time-lapses, preventing manual labeling with potential biases. The authors trained and successfully evaluated ADeS in packed epithelial monolayers and T cells distributed in 3D collagen hydrogels. Moreover, in vivo, training and evaluation were performed on polymorphonucleated leukocytes in lymph nodes and spleen.

Strengths:<br /> Pulfer A. et colleagues convincingly presented their results, thoroughly evaluated ADeS for potential toxicity assay, and compared its performance with available state-of-the-art tools.

Weaknesses:<br /> The use of ADeS is still restricted to samples where cells are fluorescently labeled either in the cytoplasm or in the nucleus, which limits its use for in vitro toxicity assays that are performed on primary cells or organoids (e.g., iPSCs-derived systems) that are normally harder to transfect. In conclusion, ADeS will be a useful tool to improve output quality and accelerate the evaluation of assays in several research areas with basic and applied aims.

Reviewer #1 (Public Review):

The prevalence of primary angle closure glaucoma (PACG) is high in Asia compared to all over the world. This study focused on characterizing the metabolite profile associated with PACG, identifying potential blood diagnostic markers, assessing their specificity for PACG, and verifying their applicability to predict the progression of visual field loss. To this end, Li et al. implemented a 5-phases multicenter prospective study to identify novel candidate biomarkers of PACG. A total of 616 individuals were recruited, identifying 1464 distinct metabolites in the serum by metabolomics and chemiluminescence immunoassays. By applying different machine learning algorithms the metabolite androstenedione showed good discrimination between PACG and control subjects, in both the discovery and validation phases. This metabolite also showed alterations in the aqueous humor and higher levels of androstenedione seemed to be associated with faster loss of visual field. Overall, the authors claimed that serum androstenedione levels may provide a new biomarker for early detection and monitoring/predicting PACG severity/progression.

Strengths:<br /> • Omics research on glaucoma is constrained by inadequate sample sizes, a dearth of validation sets to corroborate findings, and an absence of specificity analyses. The 5-phases study was designed to try to overcome these limitations. The study design is very robust, with well well-described discovery set (1 and 2), validation phase (1 and 2), supplemental phase, and cohort phase. Large and well-characterized patients with adequate control subjects contributed to the robustness of the results.<br /> • Combining untargeted and targeted metabolomics using mass spectrometry instruments (high resolution and low resolution) with an additional chemiluminiscence immunoassay determining androstenedione levels<br /> • Androstenedione achieved better diagnostic accuracy across the discovery and validation sets, with AUC varying between 0.85 and 1.0. Interestingly, baseline androstenedione levels can predict glaucoma progression via visual field loss results.<br /> • A positive correlation was observed between levels of androstenedione in serum and aqueous humor of PACG patients.<br /> • A level higher of 1.66 ng/mL of the metabolite androstenedione seems to imply a high risk of visual field loss. Androstenedione may serve as a predictor of glaucomatous visual field progression.

Weakness:<br /> • A single biomarker seems very unlikely to be of much help in the detection of glaucoma due to the etiological heterogeneity of the disease, the existence of different subtypes, and the genetic variability among patients. Rather, a panel of biomarkers may provide more useful information for clinical prediction, including better sensitivity and specificity. The inclusion of additional metabolites already identifying in the study, in combination, may provide more reliable and correct assignment results.<br /> • The number of samples in the supplementary phase is low, larger sample sizes are mandatory to confirm the diagnostic accuracy.<br /> • Cohorts from different populations are needed to verify the applicability of this candidate biomarker.<br /> • Sex hormones seem to be associated also with other types of glaucoma, such as primary open-angle glaucoma (POAG), although the molecular mechanisms are unclear (see doi:10.1167/iovs.17-22708). The inclusion of patients diagnosed with other subtypes of glaucoma, like POAG, may contribute to determining the sensitivity and specificity of the proposed biomarker. Androstenedione levels should be determined in POAG, NTG, or PEXG patients.<br /> • In addition, the levels of androstenedione were found significantly altered during other diseases as described by the authors or by conditions like polycystic ovary syndrome, limiting the utility of the proposed biomarker.<br /> • Uncertainty of the androstenedione levels compromises its usefulness in clinical practice.

Reviewer #2 (Public Review):

Summary:<br /> The objective of authors using metabolomics analysis of primary angle closure glaucoma (PACG) is to demonstrate that serum androstenedione is a novel biomarker that can be used to diagnose PACG and predict visual field progression.

Strengths:<br /> Use of widely targeted and untargeted metabolite detection conditions. Use of liquid chromatography-tandem mass spectrometry and a chemiluminescence method for confirmation of androstenedione.

Weaknesses:<br /> The "predict" part is on much less solid ground. The visual field progression and association with serum androstenedione within the current experimental design eludes to a correlation. It truly cannot be stated as predictive. To predict one needs to put the substance when nothing is there and demonstrate that the desired endpoint is reached. Conversely, the substance (androstenedione) can be removed, and show that the condition regresses. None of these are possible without model system experiments, which have not been done. The authors could put some additional details in the methods, such as: 1) how much sample was collected, 2) whether equal serum volume for analysis had equal serum proteins (or cells). They have used a LC-MS/MS and a Chemiluminescence method, but another independent method such as GC-MS/MS or NMR to detect androstenedione for a subset of patients with different stages of visual field defect would be desirable.

Reviewer #1 (Public Review):

The authors found that nifuroxazide has the potential to augment the efficacy of radiotherapy in HCC by reducing PD-L1 expression. This effect may be attributed to increased degradation of PD-L1 through the ubiquitination-proteasome pathway. The paper provides new ideas and insights to improve treatment effectiveness, however, there are additional points that could be addressed.

-The paper highlights that the combination of nifuroxazide increases tumor cell apoptosis. A discussion regarding the potential crosstalk or regulatory mechanisms between apoptotic pathways and PD-L1 expression would be valuable.

-The benefits and advantages of nifuroxazide combination could be compared to the current clinical treatment options.

Reviewer #2 (Public Review):

Summary:<br /> Zhao et al. aimed to explore an important question - how to overcome the resistance of hepatocellular carcinoma cells to radiotherapy? Given that the immune-suppressive microenvironment is a major mechanism underlying resistance to radiotherapy, they reasoned that a drug that blocks the PD-1/PD-L1 pathway could improve the efficacy of radiation therapy and chose to investigate the effect of Nifuroxazide, an inhibitor of stat3 activation, on radiotherapy efficacy in treating hepatocellular carcinoma cells. From in vitro experiments, they find combination treatment (Nifuroxazide+ radiotherapy) increases apoptosis and reduces proliferation and migration, in comparison to radiotherapy alone. From in vivo experiments, they demonstrate that combined treatment reduces the size and weight of tumors in vivo and enhances mice survival. These data indicate a better efficacy of combination therapy compared to radiotherapy alone. Moreover, they also determined the effect of combination therapy on tumor microenvironment as well as peripheral immune response. They find that combination therapy increases infiltration of CD4+ and CD8+ cells as well as M1 macrophages in the tumor microenvironment. Interestingly, they find that the ratio of Treg cells in spleen is increased by radiotherapy but decreased by Nifuroxazide. Considering the immune-suppressive role of Treg cells, this finding is consistent with reduced tumor growth by combination therapy. However, it is unclear whether the combined therapy affects the ratio of Treg cells in the tumors or not. The most intriguing part of the study is the determination of the effect of Nifuroxazide on PD-L1 expression in the context of radiotherapy. Considering Nifuroxazide is a stat3 activation inhibitor and stat3 inhibition leads to reduced expression of PD-L1, one would expect Nifuroxazide decreases PD-L1 expression through stat3. However, they found that the effect of Nifuroxazide on PD-L1 is dependent on GSK3 mediated Proteasome pathways and independent of stat3, in the given experimental context. To determine the relevance to human hepatocellular carcinoma, they also measured the PD-L1 expression in human tumor tissues of HCC patients pre- and post-radiotherapy. The increased PD-L1 expression level in HCC after radiotherapy is impressive. However, it is unclear whether the patients being selected in the study had resistant disease to radiotherapy or not.

Overall, the data are convincing and supportive to the conclusions.

Strengths:<br /> 1) Novel finding: Identified novel mechanism underlying the effect of Nifuroxazide on PD-L1 expression in hepatocellular carcinoma cells in the context of radiotherapy.<br /> 2) Comprehensive experimental approaches: using different approaches to prove the same finding. For example, in Fig 4, both IHC and WB were used. In Fig 5, both IF and WB were used.<br /> 3) Human disease relevance: Compared observations in mice with human tumor samples.

Weaknesses:<br /> 1. It is hard to tell whether the observed phenotype and mechanism are generic or specific to the limited cell lines used in the study. The in vitro experiments were performed in one human cell line and the in vivo experiments were performed in one mouse cell line.<br /> 2. The study did not distinguish the effect of increased radiosensitivity by nifuroxazide from combined anti-tumor effects by two different treatments.

Reviewer #3 (Public Review):

Summary:<br /> In this study, the authors embarked on an exploration of how nifuroxazide could enhance the responsiveness to radiotherapy by employing both an in vitro cell culture system and an in vivo mouse tumor model.

Strengths:<br /> The researchers conducted an array of experiments aimed at revealing the function of nifuroxazide in aiding the radiotherapy-induced reduction of proliferation, migration, and invasion of HepG2 cells.

Weaknesses:<br /> The authors did not provide the molecular mechanism through which nifuroxazide collaborates with radiotherapy to effectively curtail the proliferation, migration, and invasion of HCC cells. Moreover, the evidence supporting the assertion that nifuroxazide contributes to the degradation of radiotherapy-induced upregulation of PD-L1 via the ubiquitin-proteasome pathway appears to be insufficient. Importantly, further validation of this discovery should involve the utilization of an additional syngeneic mouse HCC tumor model or an orthotopic HCC tumor model.

Reviewer #1 (Public Review):

Summary:<br /> The data clearly demonstrate that arpin is important for vessel barrier function, yet its genetic loss via a CRISPR strategy was not lethality, but led to viable animals in C57Blk strain at 12 weeks of age, albeit with leaky blood vessels. Pharmacological approaches were employed to demonstrate that loss of arpin led to ROCK1-dependent stress fiber formation that promoted increased permeability.

Strengths:<br /> The results clearly demonstrate that arpin is expressed in the endothelium of blood vessels and its deficiency leads to leaky blood vessels in in vivo and in vitro models.

Weaknesses:<br /> They conclude vessel leak was not related to enhanced Arp2/3 function through arpin deficiency, but no direct evidence of Arp2/3 activity is provided to support this conclusion. Instead, the authors concluded that ROCK1 activity was elevated in arpin knockdown cells and caused robust stress fiber formation. This idea could be strengthened by testing if ROCK1 inhibition by pharmacological block in arpin KO mice leads to less vascular leakage while pharmacological inhibition of Arp2/3 does not attenuate increased vessel permeability.

Reviewer #2 (Public Review):

Summary:<br /> The authors have taken their previous finding that arpin is important for epithelial junctions and extended this to endothelial cells. They find that the positive effects of arpin on endothelial junctions are not dependent on Arp2/3 activity but instead on suppression of actinomyosin contractility.

Strengths:<br /> The study uses standard approaches to test each of the components in the model. The quality of the experimental work is good and the amount of experimental evidence is sufficient to support this straightforward story.

Weaknesses:<br /> The major weakness is that the story is a simple extension of the previous work on arpin and junctions in epithelial cells. The additional information is that the effects are not via Arp2/3 directly, but instead through an increase in actinomyosin contractility. However, the connection between arpin and increased ROCK activity is not revealed.

Reviewer #1 (Public Review):

The authors investigate the alpha chain TCR landscape in conventional vs regulatory CD4 T cells. Overall I think it is a very well thought out and executed study with interesting conclusions. The authors have investigated CDR3 alpha repertoires coupled with a transgenic fixed CDR3beta in a mouse system.

Strengths:<br /> - One of a kind evidence and dataset.

- State-of-the-art analyses using tools that are well-accepted in the literature.

- Interesting conclusions on the breadth of immune response to challenges across different types of challenges (tumor, viral and parasitic).

Weaknesses:<br /> - Some conclusions regarding the eCD4->eTreg transition are not so strong using only the data.

- Some formatting issues.

Reviewer #2 (Public Review):

This study investigates T-cell repertoire responses in a mouse model with a transgenic beta chain, such that all T-cells in all mice share a fixed beta chain, and repertoire diversity is determined solely by alpha chain rearrangements. Each mouse is exposed to one of a few distinct immune challenges, sacrificed, and T-cells are sampled from multiple tissues. FACS is used to sort CD4 and Treg cell populations from each sample, and TCR repertoire sequencing from UMI-tagged cDNA is done.

Various analyses using repertoire diversity, overlap, and clustering are presented to support several principal findings: 1) TCR repertoires in this fixed beta system have highly distinct clonal compositions for each immune challenge and each cell type, 2) these are highly consistent across mice, so that mice with shared challenges have shared clones, and 3) induction of CD4-to-Treg cell type transitions is challenge-specific.

The beta chain used for this mouse model was previously isolated based on specificity for Ovalbumin. Because the beta chain is essential for determining TCR antigen specificity, and is highly diverse in wildtype mice, I found it surprising that these mice are reported to have robust and consistently focused clonal responses to very diverse immune challenges, for which a fixed OVA-specific beta chain is unlikely to be useful. The authors don't comment on this aspect of their findings, but I would think it is not expected *a priori* that this would work. If this does work as reported, it is a valuable model system: due to massively reduced diversity, the TCR repertoire response is much more stereotyped across individual samples, and it is much easier to detect challenge-specific TCRs via the statistics of convergent responses.

While the data and analyses present interesting signals, they are flawed in several ways that undermine the reported findings. I summarize below what I think are the most substantive data and analysis issues.

1. There may be systematic inconsistencies in repertoire sampling depth that are not described in the manuscript. Looking at the supplementary tables (and making some plots), I found that the control samples (mice with mock challenge) have consistently much shallower sampling-in terms of both read count and UMI count-compared with the other challenge samples. There is also a strong pattern of lower counts for Treg vs CD4 cell samples within each challenge.

2. FACS data are not reported. Although the graphical abstract shows a schematic FACS plot, there are no such plots in the manuscript. Related to the issue above, it would be important to know the FACS cell counts for each sample.

3. For diversity estimation, UMI-wise downsampling was performed to normalize samples to 1000 random UMIs, but this procedure is not validated (the optimal normalization would require downsampling cells). What is the influence of possible sampling depth discrepancies mentioned above on diversity estimation? All of the Treg control samples have fewer than 1000 total UMIs-doesn't that pose a problem for sampling 1000 random UMIs? Indeed, I simulated this procedure and found systematic effects on diversity estimates when taking samples of different numbers of cells (each with a simulated UMI count) from the same underlying repertoire, even after normalizing to 1000 random UMIs. I don't think UMI downsampling corrects for cell sampling depth differences in diversity estimation, so it's not clear that the trends in Fig 1A are not artifactual-they would seem to show higher diversity for control samples, but these are the very same samples with an apparent systematic sampling depth bias.

4. The Figures may be inconsistent with the data. I downloaded the Supplementary Table corresponding to Fig 1 and made my own version of panels A-C. This looked quite different from the diversity estimations depicted in the manuscript. The data does not match the scale or trends shown in the manuscript figure.

5. For the overlap analysis, a different kind of normalization was performed, but also not validated. Instead of sampling 1000 UMIs, the repertoires were reduced to their top 1000 most frequent clones. It is not made clear why a different normalization would be needed here. There are several samples (including all Treg control samples) with only a couple hundred clones. It's also likely that the noted systematic sampling depth differences may drive the separation seen in MDS1 between Treg and CD4 cell types. I also simulated this alternative downsampling procedure and found strong effects on MDS clustering due to sampling effects alone.

It is not made clear how the overlap scores were converted to distances for MDS. It's hard to interpret this without seeing the overlap matrix.

6. The cluster analysis is superficial, and appears to have been cherry-picked. The clusters reported in the main text have illegibly small logo plots, and no information about V/J gene enrichments. More importantly, as the caption states they were chosen from the columns of a large (and messier-looking) cluster matrix in the supplementary figure based on association with each specific challenge. There's no detail about how this association was calculated, or how it controlled for multiple tests. I don't think it is legitimate to simply display a set of clusters that visually correlate; in a sufficiently wide random matrix you will find columns that seem to correlate with any given pattern across rows.

7. The findings on differential plasticity and CD4 to Treg conversion are not supported. If CD4 cells are converting to Tregs, we expect more nucleotide-level overlap of clones. This intuition makes sense. But it seems that this section affirms the consequent: variation in nucleotide-level clone overlap is a readout of variation in CD4 to Treg conversion. It is claimed, based on elevated nucleotide-level overlap, that the LLC and PYMT challenges induce conversion more readily than the other challenges. It is not noted in the textual interpretations, but Fig 4 also shows that the control samples had a substantially elevated nucleotide-level overlap. There is no mention of a null hypothesis for what we'd expect if there was no induced conversion going on at all. This is a reduced-diversity mouse model, so convergent recombination is more likely than usual, and the challenges could be expected to differ in the parts of TCR sequence space they induce focus on. They use the top 100 clones for normalization in this case, but don't say why (this is the 3rd distinct normalization procedure).

Although interpretations of the reported findings are limited due to the issues above, this is an interesting model system in which to explore convergent responses. Follow-up experimental work could validate some of the reported signals, and the data set may also be useful for other specific questions.

Reviewer #3 (Public Review):

Nakonechnaya et al present a valuable and comprehensive exploration of CD4+ T cell response in mice across stimuli and tissues through the analysis of their TCR-alpha repertoires.

The authors compare repertoires by looking at the relative overlap of shared clonotypes and observe that they sometimes cluster by tissue and sometimes by stimulus. They also compare different CD4+ subsets (conventional and Tregs) and find distinct yet convergent responses with occasional plasticity across subsets for some stimuli.

The observed lack of a general behaviour highlights the need for careful comparison of immune repertoires across cell subsets and tissues in order to better understand their role in the adaptive immune response.

In conclusion, this is an important paper to the community as it suggests several future directions of exploration.

Unfortunately, the lack of code and data availability does not allow the reproducibility of the results.

Joint Public Review:

In this study, Cacho-Navas et al. describe the role of ICAM-1 expressed on the apical membrane of bile canaliculi and its function to control the bile canaliculi (BCs) homeostasis. This is a previously unrecognized function of this protein in hepatocytes. The same authors have previously shown that basolateral ICAM-1 plays a role in controlling lymphocyte adhesion to hepatocytes during inflammation and that this interaction is responsible for the loss of polarity of hepatocytes during disease states.

This new study shows that ICAM-1 is mainly localized in the apical domain of the BC and in association with EBP-50, communicates with the subapical acto-myosin ring to regulate the size and morphology of the BC. They used the well-known immortal cell line of liver cells (HepG2) in which they deleted ICAM-1 gene by CRISPR-Cas9 editing and hepatic organoids derived from WT and ICAM-1-KO mice. alternating KO as well as rescue experiments. They show that in the absence of apical ICAM-1, the BC become dilated.

The data sufficiently support the conclusions of the study.

Reviewer #1 (Public Review):

In this report, Hariharan and colleagues describe a protocol based on machine learning to differentiate wild type and DMD myofibers differentiated on a micropattern. They use images generated by immunofluorescence against the proteins of the DAPC complex, (which is disrupted in absence of dystrophin) to train a classifier to recognize healthy and diseased myofibers. They show that combining images generated with utrophin and alpha-sarcoglycan provide the most effective discrimination. They then validate the approach by applying their pipeline to wild type cells treated with DMD siRNA to mimic the DMD mutation or with antisense oligonucleotides to restore the DMD coding frame by exon skipping. They show that their strategy groups the siRNA treated myofibers with the DMD ones efficiently. Grouping of the oligonucleotide treated DMD myofibers with the healthy also works but is less efficient.

Overall the work is well done and I don't have any significant technical critique. I found this highly technical study interesting for a specialized audience.

Reviewer #2 (Public Review):

Summary:<br /> The authors have developed a Myoscreen platform, which is a scalable and physiologically relevant system for generating and characterizing patient-derived myotubes. The platform can be used to accurately predict the DMD disease phenotype in a disease-relevant cell type and has wide applications in the drug development process.

Strengths:<br /> The Myoscreen platform is scalable, meaning that it can be used to generate and characterize a large number of patient-derived myotubes. This is important for drug discovery, as it allows researchers to test a wider range of potential treatments. The Myoscreen platform also uses a physiologically relevant system for generating and characterizing myotubes. This means that the results obtained from the platform are more likely to be relevant to the human disease. This compared for example to using C2C12 myotubes. The Myoscreen platform has been shown to be effective in predicting the DMD disease phenotype. This means that it can be used to identify potential treatments that are likely to be effective in patients with DMD.

Weaknesses:<br /> The study has several limitations. The method and material section could be improved. The authors rely heavily on UMAP to identify differences between non-DMD and DMD donor myotubes. They do not validate their findings using pharmacological small drugs. Additionally, the biological replicates used are extremely low, which raises concerns about the reproducibility of the findings.

Reviewer #3 (Public Review):

Summary: Hariharan et al. establish an analysis pipeline using automated microscopy to detect features identified by morphological profiling from images of common dystrophin complex proteins present in differentiated diseased and unaffected human myoblasts. Ultimately, using a machine learning algorithm to generate high dimensional phenotypes, the authors can distinguish Duchenne patient myotubes from unaffected patient controls based on the morphological features of several Dystrophin complex proteins. Initially analyzed on their own or in pairs the authors identify an optimal combination of Utrophin and a-sarcoglycan and subsequently test their ability to distinguish perturbations of Dystrophin either by knock down (siRNA) in unaffected controls or following treatment with a splicing modifier, vivo-phosphorodiamidate morpholino oligonucleomer (vivo-PMO) to ameliorate the DMD phenotype. It is unclear whether this methodology will see widespread adoption due to the combination of unique methods (micro-patterned plates and machine learning based image analysis) combined with a lack of detail on the specific features responsible for supporting the high dimensional phenotypes generated using their machine learning algorithm.

Strengths: The overall concept of this paper is interesting in that subtle morphological phenotypes, not readily observable by the eye, exhibited by dystrophin complex associated proteins can distinguish DMD samples from unaffected controls. It is interesting In Fig. 3B to see Utrophin and a-Sarcoglycan distinguish DMD and non-DMD lines from each other. This finding is the core of the paper and yet little information on how or why this is detected by image analysis is presented. An argument could be made that Combinations 1-7 all "work" to a certain degree at segregating DMD from non-DMD lines. This finding is exciting and has broad applicability both within and beyond the muscle field.

Weaknesses: Significantly more detail on the 235 features that are identified would greatly benefit the paper. What are the most critical features that give rise to high F-Scores for Utrophin and a-Sarcoglycan? What do the image masks display for the top ~10 features (or 5)? In Fig. 3B what metric(s) is critical in this segregation? What is the effect on the dimensional display if PCA is conducted as opposed to a tSNE?

Biological replicates are lacking to draw conclusions upon. Non-DMD #4 is present in certain figures and absent from others. With 2 replicates (non-DMD) and 2 replicates (DMD) it is difficult to draw statistical conclusions on the data. Non-DMD #4 is identified as a poor line (37% Desmin compared to the other lines being >88%) in Table 1. If this line is a poor line please remove it from the data analysis.

It is not appropriate to calculate Euclidan distance based on tSNE plots. PCA, MDS or UMAP are the appropriate high dimensional visual representations that allow for Euclidian distance calculations. This brings into question the validity of Fig. 4D and Fig. 5D. The link below outlines the limitations of tSNE plots. https://distill.pub/2016/misread-tsne/

It is unclear why treatment (siRNA) results in a statistically significant F-score (>0.9) when comparing non-DMD samples treated with siRNA against Dystrophin with DMD samples. Given that the siRNA knock-down appears to be quite robust this was unexpected and brings into question whether Dystrophin protein is the primary driver for the high dimensional phenotypes observed.

Joint Public Review:

The study by Ding et al demonstrated that microbial metabolite I3A reduced western diet induced steatosis and inflammation in mice. They showed that I3A mediates its anti-inflammatory activities through AMP-activated protein kinase (AMPK)-dependent manner in macrophages. Translationally, they proposed that I3A could be a potential therapeutic molecule in preventing the progression of steatosis to NASH.

Major strengths<br /> • Authors clearly demonstrated that the Western Diet (WD)-induced steatosis and I3A treatment reduced steatosis and inflammation in pre-clinical models. Data clearly supports these statements.<br /> • I3A treatment rescued WD-altered bile acids as well as partially rescued the metabolome, proteome in the liver.<br /> • I3A treatment reduced the levels of enzymes in fatty acid transport, de novo lipogenesis and β-oxidation<br /> • I3A mediates its anti-inflammatory activities through AMP-activated protein kinase (AMPK)-dependent manner in macrophages.

Minor<br /> I agree with the authors that investigating known other AhR ligands in comparison may be beyond the scope of this study.

Reviewer #1 (Public Review):

Summary:

This study by Lee et al. is a direct follow-up on their previous study that described an evolutionary conservancy among placental mammals of two motifs (a transmembrane motif and a juxtamembrane palmitoylation site) in CD4, an antigen co-receptor, and showed their relevance for T-cell antigen signaling. In this study, they describe the contribution of these two motifs to the CD4-mediated antigen signaling in the absence of CD4-LCK binding. Their approach was the comparison of antigen-induced proximal TCR signaling and distal IL-2 production in 58-/- T-cell hybridoma expressing exogenous truncated version of CD4 (without the interaction with LCK), called T1 with T1 version with the mutations in either or both of the conserved motifs. They show that the T1 CD4 can support signaling to the extend similar to WT CD4, but the mutation of the conserved motifs substantially reduced the signaling. The authors conclude that the role of these motifs is independent of the LCK-binding.

Strengths:<br /> The authors convincingly show that T1 CD4, lacking the interaction with LCK supports the TCR signaling and also that the two studied motifs have a significant contribution to it.

Weaknesses:<br /> The study has several weaknesses.

1. The whole study is based on a single experimental system, genetically modified 58-/- hybridoma. It is unclear at this moment, how the molecular motifs studied here contribute to the signaling in a real T cell. The evolutionary conservancy suggests that these motifs are important for T cell biology. However, the LCK-binding motif is conserved as well (perhaps even more) and it plays a very minor role in their model. Without verifying their results in primary cells, the quantitative, but even qualitative, importance of these motifs for T-cell signaling and biology is unclear. Although the authors discuss this issue in the Discussion, it should be noted in all important parts of the manuscript, where conclusions are made (abstract, end of introduction, perhaps also in the title) that the results are coming from the hybridoma cells.

2. Many of the experiments lack the negative control. I believe that two types of negative controls should be included in all experiments. First, hybridoma cells without CD4 (or with CD4 mutant unable to bind MHCII). Second, no peptide control, i.e., activation of the hybridoma cells with the APC not loaded with the cognate peptide. These controls are required to distinguish the basal levels of phoshorylation and CD4-independent antigen-induced phosphorylation to quantify, what is the contribution of the particular motifs to the CD4-mediated support. Although these controls are included in some of the experiments, they are missing in other ones. The binding mutant appears in some FC results as a horizontal bar (without any error bar/variability), showing that CD4 does not give a huge advantage in these readouts. Why don't the authors show no peptide controls here as well? Why the primary FC data (histograms) are not shown? Why neither of these two controls is shown for the % of responders plots? Although the IL-2 production is a very robust and convincing readout, the phosphoflow is much less sensitive. It seems that the signaling is elevated only marginally. Without the mentioned controls and showing the raw data, the precise interpretation is not possible.

3. The processing of the data is not clear. Some of the figures seem to be overprocessed. For instance, I am not sure what "Normalized % responders of pCD3zeta" means (e.g., Fig. 1C and elsewhere)? Why do not the authors show the actual % of pCD3zeta+ cells including the gating strategy? Why do the authors subtract the two histograms in Fig. 2- Fig.S3? It is very unusual.

4. The manuscript lacks Materials and Methods. It only refers to the previous paper, which is very unusual. Although most of the methods are the same, they still should be mentioned here. Moreover, some of the mutants presented here were not generated in the previous study, as far as I understand. Perhaps the authors plan to include Materials and Methods during the revision...

5. Membrane rafts are a very controversial topic. I recommend the authors stick to the more consensual term "detergent resistant microdomains" in all cases/occurances.

6. Last, but not least, the mechanistic explanation (beyond the independence of LCK binding) of the role of these motifs is very unclear at the moment.

Reviewer #2 (Public Review):

Summary:<br /> The paper by Kuhn and colleagues follows upon a 2022 paper in which they identified residues in CD4 constrained by evolutionary purifying selection in placental mammals and then performed functional analyses of these conserved sequences. They showed that sequences distinct from the CXC "clamp" involved in recruitment of Lck have critical roles in TCR signaling, and these include a glycine-rich motif in the transmembrane (TM) domain and the cys-containing juxtamembrane (JM) motif that undergoes palmitoylation, both of which promote TCR signaling, and a cytoplasmic domain helical motif, also involved in Lck binding, that constrains signaling. Mutations in the transmembrane and juxtamembrane sequences led to reduced proximal signaling and IL-2 production in a hybridoma's response to antigen presentation, despite retention of abundant CD4 association with Lck in the detergent-soluble membrane fraction, presumably mislocalized outside of lipid rafts and distal to the TCR. A major conclusion of that study was that CD4 sequences required for Lck association, including the CXC "clasp" motif, are not as consequential for CD4 co-receptor function in TCR signaling as the conserved TM and JM motifs. However, the experiments did not determine whether the functions of the TM and JM motifs are dependent on the Lck-binding properties of CD4 - the mutations in those motifs could result in free Lck redistributing to associate with CD4 in signaling-incompetent membrane domains or could function independently of CD4-Lck association. The current study addresses this specific question.

Using the same model system as in the earlier paper (the entire methods section is a citation to the earlier paper), the authors show that truncation of the Lck-binding intracellular domain resulted in a moderate reduction in IL-2 response, as previously shown, but there was no apparent effect on proximal phosphorylation events (CD3z, Lck, ZAP70, PLCg1). They then evaluated a series of TM and JM motif mutations in the context of the truncated Lck-nonbinding molecule, and showed that these had substantially impaired co-receptor function in the IL-2 assay and reduced proximal signaling. The proximal signaling could be observed at high ligand density even with a MHC non-binding mutation in CD4, although there was still impaired IL-2 production. This result additionally illustrates that phosphorylation of the proximal signaling molecules is not sufficient to activate IL-2 expression in the context of antigen presentation.

Strengths:<br /> The strength of the paper is the further clear demonstration that the classical model of CD4 co-receptor function (MHCII-binding CD4 bringing Lck to the TCR complex, for phosphorylation of the CD3 chain ITAMs and of the ZAP70 kinase) is not sufficient to explain TCR activation. The data, combined with the earlier paper, further implicate the gly-rich TM sequence and the palmitoylation targets in the JM region as having critical roles in productive co-receptor-dependent TCR activation.

Weaknesses:<br /> The major weakness of the paper is the lack of mechanistic insight into how the TM and JM motifs function. The new results are largely incremental in light of the earlier paper from this group as well as other literature, cited by the authors, that implicates "free" Lck, not associated with co-receptors, as having the major role in TCR activation. It is clear that the two motifs are important for CD4 function at low pMHCII ligand density. The proposal that they modulate interactions of TCR complex with cholesterol or other membrane lipids is an interesting one, and it would be worth further exploring by employing approaches that alter membrane lipid composition. The JM sequence presumably dictates localization within the membrane, by way of palmitoylation, which may be critical to regulate avidity of the TCR:CD4 complex for pMHCII or TCR complex allosteric effects that influence the activation threshold. Experiments that explore the basis of the mutant phenotype could substantially enhance the impact of this study.

Reviewer #1 (Public Review):

Summary: Zai et al test if songbirds can recover the capacity to sing auditory targets without singing experience or sensory feedback. Past work showed that after the pitch of targeted song syllables is driven outside of birds' preferred target range with external reinforcement, birds revert to baseline (i.e. restore their song to their target). Here the authors tested the extent to which this restoration occurs in muted or deafened birds. If these birds can restore, this would suggest an internal model that allows for sensory-to-motor mapping. If they cannot, this would suggest that learning relies entirely on feedback-dependent mechanisms, e.g. reinforcement learning (RL). The authors find that deafened birds exhibit moderate but significant restoration, consistent with the existence of a previously under-appreciated internal model in songbirds.

Strengths:<br /> The experimental approach of studying vocal plasticity in deafened or muted birds is innovative, technically difficult, and perfectly suited for the question of feedback-independent learning. The finding in Figure 4 that deafened birds exhibit subtle but significant plasticity toward restoration of their pre-deafening target is surprising and important for the songbird and vocal learning fields, in general.

Weaknesses:<br /> The evidence and analyses related to the directed plasticity in deafened birds are confusing, and the magnitude of the plasticity is far less than the plasticity observed in control birds with intact feedback. The authors acknowledge this difference in a two-system model of vocal plasticity, but one wonders why the feedback-independent model, which could powerfully enhance learning speed, is weak in this songbird system.

There remains some confusion about the precise pitch-change methods used to study the deafened birds, including the possibility that a critical cohort of birds was not suitably balanced in a way where deafened birds were tested on their ability to implement both pitch increases and decreases toward target restoration.

Reviewer #2 (Public Review):

Summary: This paper investigates the role of motor practice and sensory feedback when a motor action returns to a learned or established baseline. Adult male zebra finches perform a stereotyped, learned vocalization (song). It is possible to shift the pitch of particular syllables away from the learned baseline pitch using contingent white noise reinforcement. When the reinforcement is stopped, birds will return to their baseline over time. During the return, they often sing hundreds of renditions of the song. However, whether motor action, sensory feedback, or both during singing is necessary to return to baseline is unknown.

Previous work has shown that there is covert learning of the pitch shift. If the output of a song plasticity pathway is blocked during learning, there is no change in pitch during the training. However, as soon as the pathway is unblocked, the pitch immediately shifts to the target location, implying that there is learning of the shift even without performance. Here, they ask whether the return to baseline from such a pitch shift also involves covert or overt learning processes. They perform a series of studies to address these questions, using muting and deafening of birds at different time points. learning.

Strengths: The overall premise is interesting and the use of muting and deafening to manipulate different aspects of motor practice vs. sensory feedback is a solid approach.

Weaknesses: One of the main conclusions, which stems primarily from birds deafened after being pitch-shifted using white noise (WNd) birds in comparison to birds deafened before being pitch-shifted with light as a reinforcer (LOd), is that recent auditory experience can drive motor plasticity even when an individual is deprived of such experience. While the lack of shift back to baseline pitch in the LOd birds is convincing, the main conclusion hinges on the responses of just a few WNd individuals who are closer to baseline in the early period. Moreover, only 2 WNd individuals reached baseline in the late period, though neither of these were individuals who were closer to baseline in the early phase. Most individuals remain or return toward the reinforced pitch. These data highlight that while it may be possible for previous auditory experience during reinforcement to drive motor plasticity, the effect is very limited. Importantly, it's not clear if there are other explanations for the changes in these birds, for example, whether there are differences in the number of renditions performed or changes to other aspects of syllable structure that could influence measurements of pitch.

While there are examples where the authors perform direct comparisons between particular manipulations and the controls, many of the statistical analyses test whether each group is above or below a threshold (e.g. baseline) separately and then make qualitative comparisons between those groups. Given the variation within the manipulated groups, it seems especially important to determine not just whether these are different from the threshold, but how they compare to the controls. In particular, a full model with time (early, late), treatment (deafened, muted, etc), and individual ID (random variable) would substantially strengthen the analysis.

The muted birds seem to take longer to return to baseline than controls even after they are unmuted. Presumably, there is some time required to recover from surgery, however, it's unclear whether muting has longer-term effects on syrinx function or the ability to pass air. In particular, it's possible that the birds still haven't recovered by 4 days after unmuting as a consequence of the muting and unmuting procedure or that the lack of recovery is indicative of an additional effect that muting has on pitch recovery. For example, the methods state that muted birds perform some quiet vocalizations. However, if birds also attempt to sing, but just do so silently, perhaps the aberrant somatosensory or other input from singing while muted has additional effects on the ability to regain pitch. It would also be useful to know if there is a relationship between how long they are muted and how quickly they return to baseline.

Reviewer #3 (Public Review):

Summary:<br /> Zai et al. test whether birds can modify their vocal behavior in a manner consistent with planning. They point out that while some animals are known to be capable of volitional control of vocalizations, it has been unclear if animals are capable of planning vocalizations -that is, modifying vocalizations towards a desired target without the need to learn this modification by practicing and comparing sensory feedback of practiced behavior to the behavioral target. They study zebra finches that have been trained to shift the pitch of song syllables away from their baseline values. It is known that once this training ends, zebra finches have a drive to modify pitch so that it is restored back to its baseline value. They take advantage of this drive to ask whether birds can implement this targeted pitch modification in a manner that looks like planning, by comparing the time course and magnitude of pitch modification in separate groups of birds who have undergone different manipulations of sensory and motor capabilities. A key finding is that birds who are deafened immediately before the onset of this pitch restoration paradigm, but after they have been shifted away from baseline, are able to shift pitch partially back towards their baseline target. In other words, this targeted pitch shift occurs even when birds don't have access to auditory feedback, which argues that this shift is not due to reinforcement-learning-guided practice, but is instead planned based on the difference between an internal representation of the target (baseline pitch) and current behavior (pitch the bird was singing immediately before deafening).

The authors present additional behavioral studies arguing that this pitch shift requires auditory experience of the song in its state after it has been shifted away from baseline (birds deafened early on, before the initial pitch shift away from baseline, do not exhibit any shift back towards baseline), and that a full shift back to baseline requires auditory feedback. The authors synthesize these results to argue that different mechanisms operate for small shifts (planning, does not need auditory feedback) and large shifts (reinforcement learning, requires auditory feedback).

The authors also make a distinction between two kinds of planning: covert-not requiring any motor practice and overt-requiring motor practice but without access to auditory experience from which target mismatch could be computed. They argue that birds plan overtly, based on these deafening experiments as well as an analogous experiment involving temporary muting, which suggests that indeed motor practice is required for pitch shifts.

Strengths:<br /> The primary finding (that partially restorative pitch shift occurs even after deafening) rests on strong behavioral evidence. It is less clear to what extent this shift requires practice, since their analysis of pitch after deafening takes the average over within the first two hours of singing. If this shift is already evident in the first few renditions then this would be evidence for covert planning. This analysis might not be feasible without a larger dataset. Similarly, the authors could test whether the first few renditions after recovery from muting already exhibit a shift back toward baseline.

This work will be a valuable addition to others studying birdsong learning and its neural mechanisms. It documents features of birdsong plasticity that are unexpected in standard models of birdsong learning based on reinforcement and are consistent with an additional, perhaps more cognitive, mechanism involving planning. As the authors point out, perhaps this framework offers a reinterpretation of the neural mechanisms underlying a prior finding of covert pitch learning in songbirds (Charlesworth et al., 2012).

A strength of this work is the variety and detail in its behavioral studies, combined with sensory and motor manipulations, which on their own form a rich set of observations that are useful behavioral constraints on future studies.

Weaknesses:<br /> The argument that pitch modification in deafened birds requires some experience hearing their song in its shifted state prior to deafening (Fig. 4) is solid but has an important caveat. Their argument rests on comparing two experimental conditions: one with and one without auditory experience of shifted pitch. However, these conditions also differ in the pitch training paradigm: the "with experience" condition was performed using white noise training, while the "without experience" condition used "lights off" training (Fig. 4A). It is possible that the differences in the ability for these two groups to restore pitch to baseline reflect the training paradigm, not whether subjects had auditory experience of the pitch shift. Ideally, a control study would use one of the training paradigms for both conditions, which would be "lights off" or electrical stimulation (McGregor et al. 2022), since WN training cannot be performed in deafened birds. This is difficult, in part because the authors previously showed that "lights off" training has different valences for deafened vs. hearing birds (Zai et al. 2020). Realistically, this would be a point to add to in discussion rather than a new experiment.

A minor caveat, perhaps worth noting in the discussion, is that this partial pitch shift after deafening could potentially be attributed to the birds "gaining access to some pitch information via somatosensory stretch and vibration receptors and/or air pressure sensing", as the authors acknowledge earlier in the paper. This does not strongly detract from their findings as it does not explain why they found a difference between the "mismatch experience" and "no mismatch experience groups" (Fig. 4).

More broadly, it is not clear to me what kind of planning these birds are doing, or even whether the "overt planning" here is consistent with "planning" as usually implied in the literature, which in many cases really means covert planning. The idea of using internal models to compute motor output indeed is planning, but why would this not occur immediately (or in a few renditions), instead of taking tens to hundreds of renditions? To resolve confusion, it would be useful to discuss and add references relating "overt" planning to the broader literature on planning, including in the introduction when the concept is introduced. Indeed, muddying the interpretation of this behavior as planning is that there are other explanations for the findings, such as use-dependent forgetting, which the authors acknowledge in the introduction, but don't clearly revisit as a possible explanation of their results. Perhaps this is because the authors equate use-dependent forgetting and overt planning, in which case this could be stated more clearly in the introduction or discussion.

Reviewer #3 (Public Review):

Summary:<br /> The neural retina is one of the most energetically active tissues in the body and research into retinal metabolism has a rich history. Prevailing dogma in the field is that the photoreceptors of the neural retina (rods and cones) are heavily reliant on glycolysis, and as oxygen tension at the level of photoreceptors is very low, these specialized sensory neurons carry out aerobic glycolysis, akin to the Warburg effect in cancer cells. It has been found that this unique metabolism changes in many retinal diseases, and targeting retinal metabolism may be a viable treatment strategy. The neural retina is composed of 11 different cell types, and many research groups over the past century have contributed to our current understanding of cell-specific metabolism of retinal cells. More recently, it has been shown in mouse models and co-culture of the mouse neural retina with human RPE cultures that photoreceptors are reliant on the underlying retinal pigment epithelium for supplying nutrients. Chen and colleagues add to this body of work by studying an ex vivo culture of the developing mouse retina that maintained contact with the retinal pigment epithelium. They exposed such ex vivo cultures to small molecule inhibitors of specific metabolic pathways, performing targeted metabolomics on the tissue and staining the tissue with key metabolic enzymes to lay the groundwork for what metabolic pathways may be active in particular cell types of the retina. The authors conclude that rod and cone photoreceptors are reliant on different metabolic pathways to maintain their cell viability - in particular, that rods rely on oxidative phosphorylation and cones rely on glycolysis. Further, their data support multiple mechanisms whereby glycolysis may occur simultaneously with anapleurosis to provide abundant energy to photoreceptors. The data from metabolomics revealed several novel findings in retinal metabolism, including the use of glutamine to fuel the mini-Krebs cycle, the utilization of the Cahill cycle in photoreceptors, and a taurine/hypotaurine shuttle between the underlying retinal pigment epithelium and photoreceptors to transfer reducing equivalents from the RPE to photoreceptors. In addition, this study provides robust quantitative metabolomics datasets that can be compared across experiments and groups. The use of this platform will allow for rapid testing of novel hypotheses regarding the metabolic ecosystem in the neural retina.

Strengths:<br /> The data on differences in the susceptibility of rods and cones to mitochondrial dysfunction versus glycolysis provides novel hypothesis-generating conjectures that can be tested in animal models. The multiple mechanisms that allow anapleurosis and glycolysis to run side-by-side add significant novelty to the field of retinal metabolism, setting the stage for further testing of these hypotheses as well.

Weaknesses:<br /> Almost all of the conclusions from the paper are preliminary, based on data showing enzymes necessary for a metabolic process are present and the metabolites for that process are also present. However, to truly prove whether these processes are happening, C13 labeling or knock-out or over-expression experiments are necessary. Further, while there is good data that RPE cultures in vitro strongly recapitulate RPE phenotypes in vivo, ex vivo neural retina cultures undergo rapid death. Thus, conclusions about metabolism from explants should either be well correlated with existing literature or lead to targeted in vivo studies. This paper currently lacks both.

Reviewer #1 (Public Review):

Summary: In the manuscript by Chen et al. entitled, "The retina uncouples glycolysis and oxidative phosphorylation via Cori-, Cahill-, and mini-Krebs-cycle", the authors look to provide insight on retinal metabolism and substrate utilization by using a murine explant model with various pharmacological treatments in conjunction with metabolomics. The authors conclude that photoreceptors, a specific cell within the explant, which also includes retinal pigment epithelium (RPE) and many other types of cells, are able to uncouple glycolytic and Krebs-cycle metabolism via three different pathways: 1) the mini-Krebs-cycle, fueled by glutamine and branched-chain amino acids; 2) the alanine-generating Cahill-cycle; and 3) the lactate-releasing Cori-cycle. While intriguing if determined to be true, these cell-specific conclusions are called into question due to the ex vivo experimental setup with the inclusion of RPE, the fact that the treatments were not cell-specific nor targeted at an enzyme specific to a certain cell within the retina, and no stable isotope tracing nor mitochondrial function assays were performed. Hence, without significant cell-specific methods and future experimentation, the primary claims are not supported.

Strengths: This study attempts to improve on the issues that have limited the results obtained from previous ex vivo retinal explant studies by culturing in the presence of the RPE, which is a major player in the outer retinal metabolic microenvironment. Additionally, the study utilizes multiple pharmacologic methods to define retinal metabolism and substrate utilization.

Weaknesses: A major weakness of this study is the lack of in vivo supporting data. Explant cultures remove the retina from its dual blood supply. Typically, retinal explant cultures are done without RPE. However, the authors included RPE in the majority of experimental conditions herein. However, it is unclear if the metabolomics samples included the RPE or not. The inclusion of the RPE, which is metabolically active and can be altered by the treatments investigated herein, further confounds the claims made regarding the neuroretina. Considering the pharmacologic treatments utilized with the explant cultures are not cell-specific and/or have significant off-target effects, it is difficult to ascertain that the metabolic changes are secondary to the effects on photoreceptors alone, which the authors claim. Additionally, the explants are taken at a very early age when photoreceptors are known to still be maturing. No mention or data is presented on how these metabolic changes are altered in retinal explants after photoreceptors have fully matured. Likewise, significant assumptions are made based on a single metabolomics experiment with no stable isotope tracing to support the pathways suggested. While the authors use immunofluorescence to support their claims at multiple points, demonstrating the presence of certain enzymes in the photoreceptors, many of these enzymes are present throughout the retina and likely the RPE. Finally, the claims presented here are in direction contradiction to recent in vivo studies that used cell-specific methods when examining retinal metabolism. No discussion of this difference in results is attempted.

Reviewer #2 (Public Review):

Summary: The authors aim to learn about retinal cell-specific metabolic pathways, which could substantially improve the way retinal diseases are understood and treated. They culture ex vivo mouse retinas for 6 days with 2 - 4 days of various drug treatments targeting different metabolic pathways or by removing the RPE/choroid tissue from the neural retina. They then look at photoreceptor survival, stain for various metabolic enzymes, and quantify a broad panel of metabolites. While this is an important question to address, the results are not sufficient to support the conclusions.

Strengths: The questions the authors are exploring at extremely valuable and I commend the authors and working to learn more about retina metabolism. The different sensitivity of the cones to various drugs is interesting and may suggest key differences between rods and cones. The authors also provide a thoughtful discussion of various metabolic pathways in the context of previous publications.

Weaknesses: As the authors point out, ex vivo culture models allow for control over multiple aspects of the environment (such as drug delivery) not available in vivo. Ex vivo cultures can provide good hints as to what pathways are available between interacting tissues. However, there are many limitations to ex vivo cultures, including shifting to a very artificial culture media condition that is extremely different than the native environment of the retina. It is well appreciated that cells have flexible metabolism and will adapt to the conditions provided. Therefore, observations of metabolic responses obtained under culture conditions need to be interpreted with caution, they indicate what the tissue is doing under those specific conditions (which include cells adapting and dying).

Chen et al use pharmacological interventions to the impact of various metabolic pathways on photoreceptor survival and "long term" metabolic changes. The dose and timing of these drug treatments are not examined though. It is also hard to know how these drugs penetrate the tissue and it needs to be validated that the intended targets are being accurately hit. These relatively long-term treatments should be causing numerous downstream changes to metabolism, cell function, and survival, which makes looking at a snapshot of metabolite levels hard to interpret. It would be more valuable to look at multiple time points after drug treatment, especially easy time points (closer to 1 hr). The authors use metabolite ratios to make conclusions about pathway activity. It would be more valuable to directly measure pathway activity by looking a metabolite production rates in the media and/or with metabolic tracers again in time scales closer to minutes and hours instead of days.

It is not clear from the text if the ex vivo samples with RPE/choroid intact are analyzed for metabolomics with the RPE/choroid still intact or if this is removed. If it is not removed, the comparison to the retina without RPE/choroid needs to be re-interpreted for the contribution of metabolites from the added tissue. The composition of the tissue is different and cannot be disentangled from the changes to the neural retina specifically.

While the data is interesting and may give insights into some rod and cone-specific metabolic susceptibility, more work is needed to validate these conclusions. Given the limitations of the model the authors have over-interpreted their findings and the conclusions are not supported by the results. They need to either dramatically limit the scope of their conclusions or validate these hypotheses with additional models and tools.

Reviewer #2 (Public Review):

Erk2 is an essential element of the MAP kinase signaling cascade and directly controls cell proliferation, migration, and survival. Therefore, it is one of the most important drug targets for cancer therapy. The catalytic subunit of Erk2 has a bilobal architecture, with the small lobe harboring the nucleotide-binding pocket and the large lobe harboring the substrate-binding cleft. Several studies by the Ahn group revealed that the catalytic domain hops between (at least) two conformational states: active (R) and inactive (L), which exchange in the millisecond time scale based on the chemical shift mapping. The R state is a signature of the double phosphorylated Erk2 (2P-Erk2), while the L state has been associated with the unphosphorylated kinase (0P-Erk2). Interestingly, the X-ray structures reveal only minimal differences between these two states, a feature that led to the conclusion that active and inactive states are structurally similar but dynamically very different. The Ahn group also found that ATP-competitive inhibitors can steer the populations of Erk2 either toward the R or the L state, depending on their chemical nature. The latter opens up the possibility of modulating the activity of this kinase by changing the chemistry of the ATP-competitive inhibitor. To prove this point, the authors present a set of nineteen compounds with diverse chemical substituents. From their combined NMR and HDX-Mass Spec analyses, fourteen inhibitors drive the kinase toward the R state, while four compounds keep the kinase hopping between the R and L states. Based on these data, the authors rationalize the effects of these inhibitors and the importance of the nature of the substituents on the central scaffold to steer the kinase activity. While all these inhibitors target the ATP binding pocket, they display diverse structural and dynamic effects on the kinase, selecting a specific structural state. Although the inhibited kinase is no longer able to phosphorylate substrates, it can initiate signaling events functioning as scaffolds for other proteins. Therefore, by changing the chemistry of the inhibitors it may be possible to affect the MAP cascade in a predictable manner. This concept, recently introduced as proof of principle, finds here its significance and practical implications. The design of the next-generation inhibitors must be taken into account for these design principles. The research is well executed, and the data support the author's conclusions.

Reviewer #3 (Public Review):

Summary:<br /> Anderson et al utilize an array of orthogonal techniques to highlight the importance of protein dynamics for the function and inhibition of the kinase ERK2. ERK2 is important for a large variety of biological functions.

Strengths:<br /> This is a thorough and detailed study that uses a variety of techniques to identify critical molecular/chemical parameters that drive ERK2 in specific states.

Weaknesses:<br /> No details rules were identified so that novel inhibitors could be designed. Nevertheless, the mode of action of these existing inhibitors is much better defined.

Reviewer #1 (Public Review):

Summary:<br /> The authors set out to determine how chemical variation on kinase inhibitors determines the selection of Erk2 conformations and how inhibitor binding affects ERk2 structure and dynamics.

Strengths:<br /> The study is beautifully presented both verbally and visually. The NMR experiments and the HDX experiments complement each other for the study of Erk2 solution dynamics. X-ray crystallography of Erk2 complexes with inhibitors shows small but distinct structural changes that support the proposed model for the impact of inhibitor binding.

Weaknesses:<br /> A discussion of compound residence time for the different compounds and kinase constructs and how it could affect the very slow HDX rates might be helpful. For example, could any of the observed effects in Figure 4 be due to slow compound dissociation rather than slowed down kinase dynamics? What would be the implications?

Reviewer #1 (Public Review):

This is an elegant didactic exposition showing how dendritic plateau potentials can enable neurons to perform reliable 'binary' computations in the face of realistic spike time jitter in cortical networks. The authors make many good arguments, and the general concept underlying the paper is sound. A strength is their systematic progression from biophiysical to simplified models of single neurons, and their parallel investigation of spiking and binary neural networks, with training happening in the binary neural network.

Reviewer #2 (Public Review):

Summary:

Artificial intelligence (AI) could be useful in some applications and could help humankind. Some forms of AI work on the platform of artificial neural networks (ANN). ANNs are inspired by real brains and real neurons. Therefore understanding the repertoire and logic of real neurons could potentially improve AANs. Cell bodies of real neurons, and axons of real neurons, fire nerve impulses (nerve impulses are very brief ~2 ms, and very tall ~100 mV). Dendrites, which comprise ~80% of the total neuronal membrane (80% of the total neuronal apparatus) typically generate smaller (~50 mV amplitude) but much longer (~100 ms duration) electrical transients, called glutamate-mediated dendritic plateau potentials. The authors have built artificial neurons capable of generating such dendritic plateau potentials, and through computer simulations the authors concluded that long-lasting dendritic signals (plateau potentials) reduce negative impact of temporal jitter occurring in real brain, or in AANs. The authors showed that in AANs equipped with neurons whose dendrites are capable of generating local dendritic plateau potentials, the sparse, yet reliable spiking computations may not require precisely synchronized inputs. That means, the real world can impose notable fluctuations in the network activity and yet neurons could still recognize and pair the related network events. In the AANs equipped with dendritic plateaus, the computations are very robust even when inputs are only partially synchronized. In summary, dendritic plateau potentials endow neurons with ability to hold information longer and connect two events which did not happen at the same moment of time. Dendritic plateaus circumvent the negative impact, which the short membrane time constants arduously inflict on the action potential generation (in both real neurons and model neurons). Interestingly, one of the indirect conclusions of the current study is that neurons equipped with dendritic plateau potentials may reduce the total number of cells (nodes, units) required to perform robust computations.

Strengths:<br /> The majority of published studies are descriptive in nature. Researchers report what they see or measure. A smaller number of studies embark on a more difficult task, which is to explain the logic and rationale of a particular natural design. The current study falls into that second category. The authors first recognize that conduction delays and noise make asynchrony unavoidable in communication between circuits in the real brain. This poses a fundamental problem for the integration of related inputs in real (noisy) world. Neurons with short membrane time constants can only integrate coincident inputs that arrive simultaneously within 2-3 ms of one another. Then the authors considered the role for dendritic plateau potentials. Glutamate-mediated depolarization events within individual dendritic branches, can remedy the situation by widening the integration time window of neurons. In summary, the authors recognized that one important feature of neurons, their dendrites, are built-in to solve the major problems of rapid signal processing: [1] temporal jitter, [2] variation, [3] stochasticity, and [4] reliability of computation. In one word, the dendritic plateau potentials have evolved in the central nervous systems to make rapid CNS computations robust.

Weaknesses:<br /> The authors made some unsupported statements, which should either be deleted, or thoroughly defended in the manuscript. But first of all, the authors failed to bring this study to the readers who are not experts in computational modeling or Artificial Neural Networks. Critical terms (syntax) and ideas have not been explained. For example: [1] binary feature space? [2] 13 dimensions binary vectors? [3] the binary network could still cope with the loss of information due to the binarization of the continuous coordinates? [4] accurate summation?

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Abe and colleagues employ in vivo 2-photon calcium imaging of dopaminergic axons in the mPFC. The study reveals that these axons primarily respond to unconditioned aversive stimuli (US) and enhance their responses to initially-neutral stimuli after classical association learning. The manuscript is well-structured and presents results clearly. The utilization of a refined prism-based imaging technique, though not entirely novel, is well-implemented. The study's significance lies in its contribution to the existing literature by offering single-axon resolution functional insights, supplementing prior bulk measurements of calcium or dopamine release. Given the current focus on neuromodulator neuron heterogeneity, the work aligns well with current research trends and will greatly interest researchers in the field.

However, I would like to highlight that the authors could further enhance their manuscript by addressing study limitations more comprehensively and by providing essential details to ensure the reproducibility of their research. In light of this, I have a number of comments and suggestions that, if incorporated, would significantly contribute to the manuscript's value to the field.

Strengths:<br /> -Descriptive.<br /> -Utilization of a well-optimized prism-based imaging method.<br /> -Provides valuable single-axon resolution functional observations, filling a gap in existing literature.<br /> -Timely contribution to the study of neuromodulator neuron heterogeneity.

Weaknesses:<br /> 1. It's important to fully discuss the fact that the measurements were carried out only on superficial layers (30-100um), while major dopamine projections target deep layers of the mPFC as discussed in the cited literature (Vander Weele et al., 2018) and as illustrated in FigS1B,C. This limitation should be explicitly acknowledged and discussed in the manuscript, especially given the potential functional heterogeneity among dopamine neurons in different layers. This potential across-layer heterogeneity could also be the cause of discrepancy among past recording studies with different measurement modalities. Also, mentioning technical limitations would be informative. For example: how deep the authors can perform 2p-imaging through the prism? was the "30-100um" maximum depth the authors could get?

2. In the introduction, it seems that the authors intended to refer to Poulin et al. 2018 regarding molecular/anatomical heterogeneity of dopamine neurons, but they inadvertently cited Poulin et al. 2016 (a general review on scRNAseq). Additionally, the statement that "dopamine neurons that project to the PFC show unique genetic profiles (line 85)" requires clarification, as Poulin et al. 2018 did not specifically establish this point. Instead, they found at least the Vglut2/Cck+ population projects into mPFC, and they did not reject the possibility of other subclasses projecting to mPFC. Rather, they observed denser innervation with DAT-cre, suggesting that non-Vglut2/Cck populations would also project to mPFC. Discuss the potential molecular heterogeneity among mPFC dopamine axons in light of the sampling limitation mentioned earlier.

3. I find the data presented in Figure 2 to be odd. Firstly, the latency of shock responses in the representative axons (right panels of G, H) is consistently very long - nearly 500ms. It raises a query whether this is a biological phenomenon or if it stems from a potential technical artifact, possibly arising from an issue in synchronization between the 2-photon imaging and stimulus presentation. My reservations are compounded by the notable absence of comprehensive information concerning the synchronization of the experimental system in the method section. Secondly, there appear to be irregularities in Panel J. While the authors indicate that "Significant axons were classified as either reward-preferring (cyan) or aversive-preferring (magenta), based on whether the axons are above or below the unity line of the reward/aversive scatter plot (Line 566)," a cyan dot slightly but clearly deviates above the unity line (around coordinates (x, y) = (20, 21)). This needs clarification. Lastly, when categorizing axons for analysis of conditioning data in Fig3 (not Fig2), the authors stated "The color-coded classification (cyan/magenta) was based on k-means clustering, using the responses before classical conditioning (Figure 2J)". I do not understand why the authors used different classification methods for two almost identical datasets.

4. In connection with Point 3, conducting separate statistical analyses for aversive and rewarding stimuli would offer a fairer approach. This could potentially reveal a subset of axons that display responses to both aversive and appetitive stimuli, aligning more accurately with the true underlying dynamics. Moreover, the characterization of Figure 2J as a bimodal distribution while disregarding the presence of axons responsive to both aversive and appetitive cues seems somewhat arbitrary and circular logic. A more inclusive consideration of this dual-responsive population could contribute to a more comprehensive interpretation.

5. The contrast in initialization to novel cues between aversive and appetitive axons mirrors findings in other areas, such as the tail-of-striatum (TS) and ventral striatum (VS) projecting dopamine neurons (Menegas et al., 2017, not 2018). You might consider citing this very relevant study and discussing potential collateral projections between mPFC and TS or VS.

6. The use of correlation values (here >0.65) to group ROIs into axons is common but should be justified based on axon density in the FOV and imaging quality. It's important to present the distribution of correlation values and demonstrate the consistency of results with varying cut-off values. Also, provide insights into the reliability of aversive/appetitive classifications for individual ROIs with high correlations. Importantly, if you do the statistical testing and aversive/appetitive classifications for individual ROIs with above-threshold high correlation (to be grouped into the same axon), do they always fall into the same category? How many false positives/false negatives are observed?
<br /> "Our results remained similar for different correlation threshold values (Line 556)" (data not shown) is obsolete.

Reviewer #2 (Public Review):

Summary:<br /> This study aims to address existing differences in the literature regarding the extent of reward versus aversive dopamine signaling in the prefrontal cortex. To do so, the authors chose to present mice with both a reward and an aversive stimulus during different trials each day. The authors used high spatial resolution two-photon calcium imaging of individual dopaminergic axons in the medial PFC to characterize the response of these axons to determine the selectivity of responses in unique axons. They also paired the reward (water) and an aversive stimulus (tail shock) with auditory tones and recorded across 12 days of associative learning.

The authors find that some axons respond to both reward and aversive unconditioned stimuli, but overall, there is a strong preference to respond to aversive stimuli consistent with expectations from prior studies that used other recording methods. The authors find that both of their two auditory stimuli initially drive responses in axons, but that with training axons develop more selective responses for the shock associated tone indicating that associative learning led to changes in these axon's responses. Finally, the authors use anticipatory behaviors during the conditioned stimuli and facial expressions to determine stimulus discrimination and relate dopamine axons signals with this behavioral evidence of discrimination. This study takes advantage of cutting-edge imaging approaches to resolve the extent to which dopamine axons in PFC respond appetitive or aversive stimuli. They conclude that there is a strong bias to respond to the aversive tail shock in most axons and weaker more sparse representation of water reward.

Strengths:<br /> The strength of this study is the imaging approach that allows for investigation of the heterogeneity of response across individual dopamine axons, unlike other common approaches such as fiber photometry which provide a measure of the average population activity. The use of appetitive and aversive stimuli to probe responses across individual axons is another strength.

Weaknesses:<br /> A weakness of this study is the design of the associative conditioning paradigm. The use of only a single reward and single aversive stimulus makes it difficult to know whether these results are specific to the valence of the stimuli versus the specific identity of the stimuli. Further, the reward presentations are more numerous than the aversive trials making it unclear how much novelty and habituation account for results. Moreover, the training seems somewhat limited by the low number of trials and did not result in strong associative conditioning. The lack of omission responses reported may reflect weak associative conditioning. Finally, the study provides a small advance in our understanding of dopamine signaling in the PFC and lacks evidence for if and what might be the consequence of these axonal responses on PFC dopamine concentrations and PFC neuron activity.

Reviewer #3 (Public Review):

Summary:

The authors image dopamine axons in medial prefrontal cortex (mPFC) using microprism-mediated two-photon calcium imaging. They image these axons as mice learn that two auditory cues predict two distinct outcomes, tailshock or water delivery. They find that some axons show a preference for encoding of the shock and some show a preference for encoding of water. The authors report a greater number of dopamine axons in mPFC that respond to shock. Across time, the shock-preferring axons begin to respond preferentially to the cue predicting shock, while there is a less pronounced increase in the water-responsive axons that acquire a response to the water-predictive cue (these axons also increase non-significantly to the shock-predictive cue). These data lead the authors to argue that dopamine axons in mPFC preferentially encode aversive stimuli.

Strengths:

The experiments are beautifully executed and the authors have mastered an impressively complex technique. Specifically, they are able to image and track individual dopamine axons in mPFC across days of learning. This technique is used the way it should be: the authors isolate distinct dopamine axons in mPFC and characterize their encoding preferences and how this evolves across learning of cue-shock and cue-water contingencies. Thus, these experiments are revealing novel information about how aversive and rewarding stimuli is encoded at the level of individual axons, in a way that has not been done before. This is timely and important.

Weaknesses:

The overarching conclusion of the paper is that dopamine axons preferentially encode aversive stimuli. This is prevalent in the title, abstract, and throughout the manuscript. This is fundamentally confounded. As the authors point out themselves, the axonal response to stimuli is sensitive to outcome magnitude (Supp Fig 3). That is, if you increase the magnitude of water or shock that is delivered, you increase the change in fluorescence that is seen in the axons. Unsurprisingly, the change in fluorescence that is seen to shock is considerably higher than water reward. Further, when the mice are first given unexpected water delivery and have not yet experienced the aversive stimuli, over 40% of the axons respond [yet just a few lines below the authors write: "Previous studies have demonstrated that the overall dopamine release at the mPFC or the summed activity of mPFC dopamine axons exhibits a strong response to aversive stimuli (e.g., tail shock), but little to rewards", which seems inconsistent with their own data]. Given these aspects of the data, it could be the case that the dopamine axons in mPFC encodes different types of information and delegates preferential processing to the most salient outcome across time. The use of two similar sounding tones (9Khz and 12KHz) for the reward and aversive predicting cues are likely to enhance this as it requires a fine-grained distinction between the two cues in order to learn effectively.

There is considerable literature on mPFC function across species that would support such a view. Specifically, theories of mPFC function (in particular prelimbic cortex, which is where the axon images are mostly taken) generally center around resolution of conflict in what to respond, learn about, and attend to. That is, mPFC is important for devoting the most resources (learning, behavior) to the most relevant outcomes in the environment. This data then, provides a mechanism for this to occur in mPFC. That is, dopamine axons signal to the mPFC the most salient aspects of the environment, which should be preferentially learned about and responded towards. This is also consistent with the absence of a negative prediction error during omission: the dopamine axons show increases in responses during receipt of unexpected outcomes, but do not encode negative errors. This supports a role for this projection in helping to allocate resources to the most salient outcomes and their predictors, and not learning per se. Below are a just few references from the rich literature on mPFC function (some consider rodent mPFC analogous to DLPFC, some mPFC), which advocate for a role in this region in allocating attention and cognitive resources to most relevant stimuli, and do not indicate preferential processing of aversive stimuli.

References:<br /> 1. Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual review of neuroscience, 24(1), 167-202.<br /> 2. Bissonette, G. B., Powell, E. M., & Roesch, M. R. (2013). Neural structures underlying set-shifting: roles of medial prefrontal cortex and anterior cingulate cortex. Behavioural brain research, 250, 91-101.<br /> 3. Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual review of neuroscience, 18(1), 193-222.<br /> 4. Sharpe, M. J., Stalnaker, T., Schuck, N. W., Killcross, S., Schoenbaum, G., & Niv, Y. (2019). An integrated model of action selection: distinct modes of cortical control of striatal decision making. Annual review of psychology, 70, 53-76.<br /> 5. Ridderinkhof, K. R., Ullsperger, M., Crone, E. A., & Nieuwenhuis, S. (2004). The role of the medial frontal cortex in cognitive control. science, 306(5695), 443-447.<br /> 6. Nee, D. E., Kastner, S., & Brown, J. W. (2011). Functional heterogeneity of conflict, error, task-switching, and unexpectedness effects within medial prefrontal cortex. Neuroimage, 54(1), 528-540.<br /> 7. Isoda, M., & Hikosaka, O. (2007). Switching from automatic to controlled action by monkey medial frontal cortex. Nature neuroscience, 10(2), 240-248.

Joint Public Review:

Neuropeptide signaling is an important component of nervous systems, where neuropeptides typically act via G-protein coupled receptors (GPCRs) to regulate many physiological and behavioral processes. Neuropeptides and their cognate GPCRs have been extensively characterized in bilaterian animals, revealing that a core set of neuropeptide signaling systems originated in common ancestors of extant Bilateria. Neuropeptides have also been identified in cnidarians, which are a sister group to the Bilateria. However, the GPCRs that mediate the effects of neuropeptides in cnidarians have not been identified.

In this paper the authors perform a phylogenetic analysis of GPCRs in metazoans and report that the orthologs of bilaterian neuropeptide receptors are not found in cnidarians. This indicates that neuropeptide signaling systems have largely evolved independently in cnidarians and bilaterians. To accomplish this, they generated a library of putative and known neuropeptides computationally identified in the genome of the cnidarian sea anemone Nematostella vectensis. These peptides were systematically screened for their ability to activate any of the 161 putative Nematostella GPCRs.

This work identified 31 validated GPCRs. These, together with GPCRs that cluster with them, were then used to demonstrate the independent expansion of GPCRs in cnidarian and bilaterian lineages. The authors then mapped validated receptors and ligands to the Nematostella single cell data to provide an overview of the cell types expressing these signaling genes. In addition, the authors have begun to analyze neuropeptide signaling networks in N. vectensis by showing potential signaling connections between cell types expressing neuropeptides and cell types expressing cognate receptors.

This work is the most extensive pharmacological characterization of neuropeptide GPCRs in a cnidarian to date and thus represents an important accomplishment, and is one that will improve our understanding of how peptidergic signaling evolved in animals and its impact on evolution of nervous systems."

The reviewers did not detect any weaknesses in the work but ask that the authors comment on the following points:<br /> 1- It was not clear why the phylogenetic analysis included non-validated GPCRs that clustered with the validated peptidergic receptors. Would restricting the phylogenetic analyses only to confirmed peptidergic GPCRs alter the topology of the tree and subsequent conclusions of independent expansion?<br /> 2- Clearly, other neuropeptide signaling systems in cnidarians remain to be discovered but this paper represents a huge step forward.<br /> 3- There are limitations in what can be interpreted from single cell transcriptomic data but the data nevertheless provide the foundations for future studies involving i). detailed anatomical analysis of neuropeptide and neuropeptide receptor expression in N. vectensis using mRNA in situ hybridization and/or immunohistochemical methods and ii). functional analysis of the physiological/behavioral roles of neuropeptide signaling systems in N. vectensis

Reviewer #1 (Public Review):

Summary:

This research study utilizes a realistic motoneuron model to explore the potential to trace back the appropriate levels of excitation, inhibition, and neuromodulation in the firing patterns of motoneurons observed in in-vitro and in-vivo experiments in mammals. The research employs high-performance computing power to achieve its objectives. The work introduces a new framework that enhances understanding of the neural inputs to motoneuron pools, thereby opening up new avenues for hypothesis testing research.

Strengths:<br /> The significance of the study holds relevance for all neuroscientists. Motoneurons are a unique class of neurons with known distribution of outputs for a wide range of voluntary and involuntary motor commands, and their physiological function is precisely understood. More importantly, they can be recorded in-vivo using minimally invasive methods, and they are directly impacted by many neurodegenerative diseases at the spinal cord level.<br /> The computational framework developed in this research offers the potential to reverse engineer the synaptic input distribution when assessing motor unit activity in humans, which holds particular importance.<br /> Overall, the strength of the findings focuses on providing a novel framework for studying and understanding the inputs that govern motoneuron behavior, with broad applications in neuroscience and potential implications for understanding neurodegenerative diseases. It highlights the significance of the study for various research domains, making it valuable to the scientific community.

Weaknesses: The exact levels of inhibition, excitation, and neuromodulatory inputs to neural networks are unknown. Therefore the work is based on fine-tuned measures that are indirectly based on experimental results. However, obtaining such physiological information is challenging and currently impossible. From a computational perspective it is a challenge that in theory can be solved. Thus, although we have no ground-truth evidence, this framework can provide compelling evidence for all hypothesis testing research and potentially solve this physiological problem with the use of computers.

Reviewer #2 (Public Review):

The study presents an extensive computational approach to identify the motor neuron input from the characteristics of single motor neuron discharge patterns during a ramp up/down contraction. This reverse engineering approach is relevant due to limitations in our ability to estimate this input experimentally. Using well-established models of single motor neurons, a (very) large number of simulations were performed that allowed identification of this relation. In this way, the results enable researchers to measure motor neuron behavior and from those results determine the underlying neural input scheme. Overall, the results are very convincing and represent an important step forward in understanding the neural strategies for controlling movement.

Nevertheless, I would suggest that the authors consider the following recommendations to strengthen the message further. First, I believe that the relation between individual motor neuron behavioral characteristics (delta F, brace height etc.) and the motor neuron input properties can be illustrated more clearly. Although this is explained in the text, I believe that this is not optimally supported by figures. Figure 6 to some extent shows this, but figures 8 and 9 as well as Table 1 shows primarily the goodness of fit rather than the actual fit. Second, I would have expected the discussion to have addressed specifically the question of which of the two primary schemes (push-pull, balanced) is the most prevalent. This is the main research question of the study, but it is to some degree left unanswered. Now that the authors have identified the relation between the characteristics of motor neuron behaviors (which has been reported in many previous studies), why not exploit this finding by summarizing the results of previous studies (at least a few representative ones) and discuss the most likely underlying input scheme? Is there a consistent trend towards one of the schemes, or are both strategies commonly used?

In addition, it seems striking to me that highly non-linear excitation profiles are necessary to obtain a linear CST ramp in many model configurations. Although somewhat speculative, one may expect that an approximately linear relation is desired for robust and intuitive motor control. It seems to me that humans generally have a good ability to accurately grade the magnitude of the motor output, which implies that either a non-linear relation has been learnt (complex task), or that the central nervous system can generally rely on a somewhat linear relation between the neural drive to the muscle and the output (simpler task). Following this reasoning, it could be interesting to report also for which input scheme, the excitation profile is most linear. I understand that this is not the primary aim of the study, but it may be an interesting way to elaborate on the finding that in many cases non-linear excitation profiles were needed to produce the linear ramp.

Reviewer #1 (Public Review):

Summary:<br /> I read the paper by Parrotta et al with great interest. The authors are asking an interesting and important question regarding pain perception, which is derived from predictive processing accounts of brain function. They ask: If the brain indeed integrates information coming from within the body (interoceptive information) to comprise predictions about the expected incoming input and how to respond to it, could we provide false interoceptive information to modulate its predictions, and subsequently alter the perception of such input? To test this question, they use pain as the input and the sounds of heartbeats (falsified or accurate) as the interoceptive signal.

Strengths:<br /> I found the question well-established, interesting, and important, with important implications and contributions for several fields, including neuroscience of prediction-perception, pain research, placebo research, and health psychology. The paper is well-written, the methods are adequate, and the findings largely support the hypothesis of the authors. The authors carried out a control experiment to rule out an alternative explanation of their finding, which was important.

Weaknesses:<br /> I will list here one theoretical weakness or concern I had, and several methodological weaknesses.

The theoretical concern regards what I see as a misalignment between a hypothesis and a result, which could influence our understanding of the manipulation of heartbeats, and its meaning: The authors indicate from prior literature and find in their own findings, that when preparing for an aversive incoming stimulus, heartbeats *decrease*. However, in their findings, manipulating the heartbeats that participants hear to be slower than their own prior to receiving a painful stimulus had *no effect* on participants' actual heartbeats, nor on their pain perceptions. What authors did find is that when listening to heartbeats that are *increased* in frequency - that was when their own heartbeats decreased (meaning they expected an aversive stimulus) and their pain perceptions increased.

This is quite complex - but here is my concern: If the assumption is that the brain is collecting evidence from both outside and inside the body to prepare for an upcoming stimulus, and we know that *slowing down* of heartbeats predicts an aversive stimulus, why is it that participants responded in a change in pain perception and physiological response when listened to *increased heartbeats* and not decreased? My interpretation is that the manipulation did not fool the interoceptive signals that the brain collects, but rather the more conscious experience of participants, which may then have been translated to fear/preparation for the incoming stimulus. As the authors indicate in the discussion (lines 704-705), participants do not *know* that decreased heartbeats indicate upcoming aversive stimulus, and I would even argue the opposite - the common knowledge or intuitive response is to increase alertness when we hear increased heartbeats, like in horror films or similar scenarios. Therefore, the unfortunate conclusion is that what the authors assume is a manipulation of interoception - to me seems like a manipulation of participants' alertness or conscious experience of possible danger. I hope the (important) distinction between the two is clear enough because I find this issue of utmost importance for the point the paper is trying to make. If to summarize in one sentence - if it is decreased heartbeats that lead the brain to predict an approaching aversive input, and we assume the manipulation is altering the brain's interoceptive data collection, why isn't it responding to the decreased signal? --> My conclusion is, that this is not in fact a manipulation of interoception, unfortunately.

I will add that the control experiment - with an exteroceptive signal (knocking of wood) manipulated in a similar manner - could be seen as evidence of the fact that heartbeats are regarded as an interoceptive signal, and it is an important control experiment, however, to me it seems that what it is showing is the importance of human-relevant signals to pain prediction/perception, and not directly proves that it is considered interoceptive. For example, it could be experienced as a social cue of human anxiety/fear etc, and induce alertness.

Several additional, more methodological weaknesses include the very small number of trials per condition - the methods mention 18 test trials per participant for the 3 conditions, with varying pain intensities, which are later averaged (and whether this is appropriate is a different issue). This means 6 trials per condition, and only 2 trials per condition and pain intensity. I thought that this number could be increased, though it is not a huge concern of the paper. It is, however, needed to show some statistics about the distribution of responses, given the very small trial number (see recommendations for authors). The sample size is also rather small, on the verge of "just right" to meet the required sample size according to the authors' calculations. Finally, and just as important, the data exists to analyze participants' physiological responses (ECG) after receiving the painful stimulus - this could support the authors' claims about the change in both subjective and objective responses to pain. It could also strengthen the physiological evidence, which is rather weak in terms of its effect. Nevertheless, this is missing from the paper.

I have several additional recommendations regarding data analysis (using an ANOVA rather than multiple t-tests, using raw normalized data rather than change scores, questioning the averaging across 3 pain intensities) - which I will detail in the "recommendations for authors" section.

Conclusion:<br /> To conclude, the authors have shown in their findings that predictions about an upcoming aversive (pain) stimulus - and its subsequent subjective perception - can be altered not only by external expectations, or manipulating the pain cue, as was done in studies so far, but also by manipulating a cue that has fundamental importance to human physiological status, namely heartbeats. Whether this is a manipulation of actual interoception as sensed by the brain is - in my view - left to be proven.<br /> Still, the paper has important implications in several fields of science ranging from neuroscience prediction-perception research, to pain and placebo research, and may have implications for clinical disorders, as the authors propose. Furthermore, it may lead - either the authors or someone else - to further test this interesting question of manipulation of interoception in a different or more controlled manner.

I salute the authors for coming up with this interesting question and encourage them to continue and explore ways to study it and related follow-up questions.

Reviewer #2 (Public Review):

In this manuscript, Parrotta et al. tested whether it is possible to modulate pain perception and heart rate by providing false HR acoustic feedback before administering electrical cutaneous shocks. To this end, they performed two experiments. The first experiment tested whether false HR acoustic feedback alters pain perception and the cardiac anticipatory response. The second experiment tested whether the same perceptual and physiological changes are observed when participants are exposed to a non-interoceptive feedback. The main results of the first experiment showed a modulatory effect for faster HR acoustic feedback on pain intensity, unpleasantness, and cardiac anticipatory response compared to a control (acoustic feedback congruent to the participant's actual HR). However, the results of the second experiment also showed an increase in pain ratings for the faster non-interoceptive acoustic feedback compared to the control condition, with no differences in pain unpleasantness or cardiac response.

The main strengths of the manuscript are the clarity with which it was written, and its solid theoretical and conceptual framework. The researchers make an in-depth review of predictive processing models to account for the complex experience of pain, and how these models are updated by perceptual and active inference. They follow with an account of how pain expectations modulate physiological responses and draw attention to the fact that most previous studies focus on exteroceptive cues. At this point, they make the link between pain experience and heart rate changes, and introduce their own previous work showing that people may illusorily perceive a higher cardiac frequency when expecting painful stimulation, even though anticipating pain typically goes along with a decrease in HR. From here, they hypothesize that false HR acoustic feedback evokes more intense and unpleasant pain perception, although the actual HR actually decreases due to the orienting cardiac response. Furthermore, they also test the hypothesis that an exteroceptive cue will lead to no (or less) changes in those variables. The discussion of their results is also well-rooted in the existing bibliography, and for the most part, provides a credible account of the findings.

The main weaknesses of the manuscript lies in a few choices in methodology and data analysis that hinder the interpretation of the results and the conclusions as they stand. The first peculiar choice is the convoluted definition of the outcomes. Specifically, pain intensity and unpleasantness are first normalized and then transformed into variation rates (sic) or deltas, which makes the interpretation of the results unnecessarily complicated. This is also linked to the definitions of the smallest effect of interest (SESOI) in terms of these outcomes, which is crucial to determining the sample size and gauging the differences between conditions. However, the choice of SESOI is not properly justified, and strangely, it changes from the first experiment to the second.

Furthermore, the researchers propose the comparison of faster vs. slower delta HR acoustic feedback throughout the manuscript when the natural comparison is the incongruent vs. the congruent feedback. This could be influenced by the fact that the faster HR exteroceptive cue in experiment 2 also shows a significant modulatory effect on pain intensity compared to congruent HR feedback, which puts into question the hypothesized differences between interoceptive vs. exteroceptive cues. These results could also be influenced by the specific choice of exteroceptive cue: the researchers imply that the main driver of the effect is the nature of the cue (interoceptive vs. exteroceptive) and not its frequency. However, they attempt to generalize their findings using knocking wood sounds to all possible sounds, but it is possible that some features of these sounds (e.g., auditory roughness or loomingness) could be the drivers behind the observed effects. Finally, it is noteworthy that the researchers divided the study into two experiments when it would have been optimal to test all the conditions with the same subjects in a randomized order in a single cross-over experiment to reduce between-subject variability.

Taking this into consideration, I believe that the conclusions are only partially supported by the evidence. Despite of the outcome transformations, a clear effect of faster HR acoustic feedback can be observed in the first experiment, which is larger than the proposed exteroceptive counterpart. This work could be of broad interest to pain researchers, particularly those working on predictive coding of pain.

Reviewer #3 (Public Review):

Summary:

In their manuscript titled "Exposure to false cardiac feedback alters pain perception and anticipatory cardiac frequency", Parrotta and colleagues describe an experimental study on the interplay between false heart rate feedback and pain experience in healthy, adult humans. The experimental design is derived from Bayesian perspectives on interoceptive inference. In Experiment 1 (N=34), participants rated the intensity and unpleasantness of an electrical pulse presented to their middle fingers. Participants received auditory cardiac feedback prior to the electrical pulse. This feedback was congruent with the participant's heart rate or manipulated to have a higher or lower frequency than the participant's true heart rate (incongruent high/ low feedback). The authors find heightened ratings of pain intensity and unpleasantness as well as a decreased heart rate in participants who were exposed to the incongruent-high cardiac feedback. Experiment 2 (N=29) is equivalent to Experiment 1 with the exception that non-interoceptive auditory feedback was presented. Here, mean pain intensity and unpleasantness ratings were unaffected by feedback frequency.

Strengths:

The authors present interesting experimental data that was derived from modern theoretical accounts of interoceptive inference and pain processing.

1. The motivation for the study is well-explained and rooted within the current literature, whereas pain is the result of a multimodal, inferential process. The separation of nociceptive stimulation and pain experience is explained clearly and stringently throughout the text.

2. The idea of manipulating pain-related expectations via an internal, instead of an external cue, is very innovative.

3. An appropriate control experiment was implemented, where an external (non-physiological) auditory cue with parallel frequency to the cardiac cue was presented.

4. The chosen statistical methods are appropriate, albeit averaging may limit the opportunity for mechanistic insight, see weaknesses section.

5. The behavioral data, showing increased unpleasantness and intensity ratings after exposure to incongruent-high cardiac feedback, but not exteroceptive high-frequency auditory feedback, is backed up by ECG data. Here, the decrease in heart rate during the incongruent-high condition speaks towards a specific, expectation-induced physiological effect that can be seen as resulting from interoceptive inference.

Weaknesses:

Additional analyses and/ or more extensive discussion are needed to address these limitations:

1. I would like to know more about potential learning effects during the study. Is there a significant change in ∆ intensity and ∆ unpleasantness over time; e.g. in early trials compared to later trials? It would be helpful to exclude the alternative explanation that over time, participants learned to interpret the exteroceptive cue more in line with the cardiac cue, and the effect is driven by a lack of learning about the slightly less familiar cue (the exteroceptive cue) in early trials. In other words, the heartbeat-like auditory feedback might be "overlearned", compared to the less naturalistic tone, and more exposure to the less naturalistic cue might rule out any differences between them w.r.t. pain unpleasantness ratings.

2. The origin of the difference in Cohen's d (Exp. 1: .57, Exp. 2: .62) and subsequently sample size in the sensitivity analyses remains unclear, it would be helpful to clarify where these values are coming from (are they related to the effects reported in the results? If so, they should be marked as post-hoc analyses).

3. As an alternative explanation, it is conceivable that the cardiac cue may have just increased unspecific arousal or attention to a larger extent than the exteroceptive cue. It would be helpful to discuss the role of these rather unspecific mechanisms, and how it may have differed between experiments.

4. The hypothesis (increased pain intensity with incongruent-high cardiac feedback) should be motivated by some additional literature.

5. The discussion section does not address the study's limitations in a sufficient manner. For example, I would expect a more thorough discussion on the lack of correlation between participant ratings and self-reported bodily awareness and reactivity, as assessed with the BPQ.<br /> a. Some short, additional information on why the authors chose to focus on body awareness and supradiaphragmatic reactivity subscales would be helpful.

6. The analyses presented in this version of the manuscript allow only limited mechanistic conclusions - a computational model of participant's behavior would be a very strong addition to the paper. While this may be out of the scope of the article, it would be helpful for the reader to discuss the limitations of the presented analyses and outline avenues towards a more mechanistic understanding and analysis of the data. The computational model in [7] might contain some starting ideas.

Some additional topics were not considered in the first version of the manuscript:<br /> 1. The possible advantages of a computational model of task behavior should be discussed.<br /> 2. Across both experiments, there was a slightly larger number of female participants. Research suggests significant sex-related differences in pain processing [1,2]. It would be interesting to see what role this may have played in this data.<br /> 3. There are a few very relevant papers that come to mind which may be of interest. These sources might be particularly useful when discussing the roadmap towards a mechanistic understanding of the inferential processes underlying the task responses [3,4] and their clinical implications.<br /> 4. In this version of the paper, we only see plots that illustrate ∆ scores, averaged across pain intensities - to better understand participant responses and the relationship with stimulus intensity, it would be helpful to see a more descriptive plot of task behavior (e.g. stimulus intensity and raw pain ratings)

[1] Mogil, J. S. (2020). Qualitative sex differences in pain processing: emerging evidence of a biased literature. Nature Reviews Neuroscience, 21(7), 353-365. https://www.nature.com/articles/s41583-020-0310-6<br /> [2] Sorge, R. E., & Strath, L. J. (2018). Sex differences in pain responses. Current Opinion in Physiology, 6, 75-81. https://www.sciencedirect.com/science/article/abs/pii/S2468867318300786?via%3Dihub<br /> [3] Unal, O., Eren, O. C., Alkan, G., Petzschner, F. H., Yao, Y., & Stephan, K. E. (2021). Inference on homeostatic belief precision. Biological Psychology, 165, 108190.<br /> [4] Allen, M., Levy, A., Parr, T., & Friston, K. J. (2022). In the body's eye: the computational anatomy of interoceptive inference. PLoS Computational Biology, 18(9), e1010490.<br /> [5] Stephan, K. E., Manjaly, Z. M., Mathys, C. D., Weber, L. A., Paliwal, S., Gard, T., ... & Petzschner, F. H. (2016). Allostatic self-efficacy: A metacognitive theory of dyshomeostasis-induced fatigue and depression. Frontiers in human neuroscience, 10, 550.<br /> [6] Friston, K. J., Stephan, K. E., Montague, R., & Dolan, R. J. (2014). Computational psychiatry: the brain as a phantastic organ. The Lancet Psychiatry, 1(2), 148-158.<br /> [7] Eckert, A. L., Pabst, K., & Endres, D. M. (2022). A Bayesian model for chronic pain. Frontiers in Pain Research, 3, 966034.

Reviewer #1 (Public Review):

Summary:<br /> The question at hand is whether astrocytes contribute to the mechanism of long-term synaptic potentiation (LTP) at synaptic contacts between excitatory glutamatergic neurons and inhibitory neurons (E-I synapses). This is a legitimate query considering the immense body of work that has now established synaptic plasticity (LTP, LTD and spike-timing dependent plasticity) as an astrocyte-dependent process at excitatory synapses and, by contrast, the lack of knowledge on whether and how astrocytes control IN activity. Taking direct inspiration from that same body of work, authors recapitulate a number of experiments and approaches from prior seminal studies and provide evidence that E-I synapses in the stratum radiatum of the hippocampus display NMDAR-dependent plasticity, which can be suppressed by pharmacologically hindering astrocytes physiology, preventing astrocyte Ca2+ transients or blocking endocannabinoid CB1 receptors. Under any of these conditions, LTP can still be rescued by exogenously applying D-serine, a naturally occurring co-agonist of NMDARs primarily released by astrocytes. Coincidently, authors show that the conditions used to elicit LTP also cause a transient increase in NMDAR co-agonist site occupancy. Lastly, based on some evidence that gamma-CaMKII is predominantly expressed in INs rather than excitatory neurons, authors conducted AAV-mediated IN-specific gamma-CaMKII shRNA experiments and found that this is sufficient to suppress LTP at E-I synapses. They found that this approach also impairs contextual fear learning in behaving mice. Authors conclude that astrocytes gate LTP at E-I synapses via a mechanism wherein neuronal depolarization during LTP induction elicits endocannabinoid release which drives CB1-dependent astrocyte Ca2+ activity, causing the release of the NMDAR co-agonist D-serine (required for NMDAR activation).

Strengths:<br /> This is an important question and the experimental work seems to have been conducted at high standards. The electrophysiology traces are impeccable, the experiments are well powered, including the behavioral testing, and multiple controls and validations are provided throughout. The figures are clear and easy to understand. Overall, the conclusions from the study are consistent, or partially consistent, by the findings.

Main Weaknesses:<br /> 1- A major point of concern is the lack of proper acknowledgment of the seminal studies that were mimicked in this manuscript, notably Henneberger et al, Nature 2010, Adamsky et al, Cell 2018; and Robin et al., Neuron 2017. The entire study design is a replica of these landmark studies: it isn't built upon or inspired from them, it exactly repeats the experiments and methods performed in them, coming dangerously close to being simply a hidden attempt to plagiarize published work. The resemblance goes as far as using an identical figure display (see Fig4.D vs Fig 2D of Ref#4). The issue is that authors frame the problem, scientist logic, reasoning, technical tricks, approaches, and interpretations as their own whereas, in reality, they were taken verbatim out of previous work and applied to a (shockingly) similar problem. The probity of the present study is thus in question. Authors need to clearly acknowledge, in all relevant instances, that the work presented here recapitulates the approach, reasoning and methodology used in past seminal studies that tackled the mechanisms of astrocyte regulation of LTP.

2-Relatedly, in past work, field recordings were used to monitor LTP in hippocampal slices (refs 4, 26 and others). This method captures indiscriminately all excitatory synapses where glutamate is released to cause AMPAR-dependent (and NMDAR) transmembrane flux of cations in the postsynaptic element, including E-I synapses and not just E-E synapse like the authors claim. Therefore, a strong argument can be made that there is no actual ground to differentiate the present results from past ones.

3-There is a general lack of excitement about this study. One reason is that it replicates almost identically past work, as mentioned above. Another is that the scientific question and importance of the findings are not framed appropriately. The work is presented as an astrocyte-focused investigation, but it has very limited value to the astrocyte field. The findings are, in all accounts, identical to those unveiled by previous work especially because E-I synapses are, in fact, excitatory synapses. Where this study does bring value, however, is to the field of interneurons, but it would need to be reframed to shift the emphasis from astrocytes to E-I connections. Authors would need to elevate the text by framing their work around relevant considerations, such as IN diversity, mechanisms of LTP in IN subtypes, role of E-I connections in hippocampal circuit function, information processing, behavior, spatial learning, navigation, or grid cells activity etc...

4-A clear weakness of the study is that it fails to consider the molecular and functional diversity of interneurons in the stratum radiatum and provides no insights or considerations related to it. Authors provide no information on what type of IN were patched, or the location of their cell body in the s.r., effectively treating all patched IN as a homogeneous ensemble of cells - which they are not. Relatedly, the study is extremely evasive on the importance of the results in the context of inhibitory interneurons. This renders the significance of the insights highly uncertain and dampens both the impact of the study and the excitement it generates. Hippocampal interneurons are very diverse in molecular identity, sub-anatomical location, morphology, projections, connectivity and functional importance. Some experts go as far as recognizing 29 subtypes in the CA1, including 9 in the stratum radiatum alone (based on the location of their soma). However, this is neither addressed nor acknowledged by the authors, with the exception of a statement (line 659) where they claim to have "focused on a subpopulation of interneurons in the stratum radiatum" without providing any precision or evidence to corroborate this assertion. This diversity, alone, could explain why not all cells showed LTP, or why the mechanisms authors describe in the radiatum do not seem to be at play in the oriens. Hence, carefully considering the diversity of INs in the present work is necessary. It would refine and augment the conclusions of the paper. Instead of a sub-region specificity, the study might fuel the notion of an IN subtype specificity of LTP mechanisms, which is more useful to the field.

5-Authors take several shortcuts. Some of the conclusions are a leap from the experiments and are only acceptable due to the close analogy with very similar investigations conducted in the past that provided identical results. For instance, the present study provides no evidence of any sort that D-serine is involved - rather, it provides evidence that the pathway at hand contributes to increasing the occupancy of the co-agonist binding site of NMDARs. Considering the absence of work demonstrating that D-serine is the endogenous co-agonist of NMDARs at E-I synapses, most of the authors claims on D-serine are unfounded. This would necessitate using tools such as the canonical D-serine scavengers DAAS or DsDA, serine racemase KO mice etc. Similarly, authors provide no compelling evidence that endocannabinoid CB1 receptors involved in this pathway are located on astrocytes

6-An important caveat in this study is the protocol employed to induce LTP, which includes steps of sustained depolarization of the patched IN to -10mV. Neuronal depolarization is known to induce endocannabinoids production. In several instances, this was shown to 'activate' astrocytes and elicit the release of astrocyte-derived transmitters at nearby synapses. This implies that the endocannabinoid-dependent pathway described in the study is, most likely, artificially engaged by the protocol itself. Hence, the present work only provides evidence that an astrocyte-dependent, CB1-D-serine-pathway can be artificially called upon with this specific LTP protocol, but does not convincingly demonstrate that it is naturally occurring or necessary for plasticity at E-I synapses. Authors would need to thoroughly address this caveat by replicating some of their key findings (AM251, calcium-clamp, D-serine and CaMKII shRNA) using a protocol that does not entail the artificial depolarization of the patched interneuron.

7-Reading and understanding are hindered by a rather vast array of issues with the text itself. It needs thorough editing for typos, misnomers, meaning-altering errors in syntax, and a number of issues with English.

Reviewer #2 (Public Review):

Summary:<br /> This work explores the implication of astrocytes in the regulation of long-term potentiation of excitatory synapses onto inhibitory neurons in CA1 hippocampus. They found that astrocytes of a sub-region of CA1 regulate this plasticity through their activation of endocannabinoids that lead to the release of the NMDA receptor co-agonist, D-serine.

Strengths:<br /> The experiments are well considered and conceptualized, and use appropriate tools to explore the role of astrocytes in the tripartite synapse. The results highlight a novel role of astrocytes in an important aspect of the synaptic regulation of the hippocampal circuit. There are extensive levels of analysis for each experimental group of evidence.

Weaknesses:<br /> The authors underscore and used an oversimplified view of the heterogeneity of interneuron populations and their selective roles in the hippocampal network. Also, there is an uneven level of astrocyte-selective tools used in the different experiments which creates an uneven strength of arguments and conclusions regarding the role of glial cells. Finally, the wording used by the authors often lead to some confusion or sense of overinterpretation.

Reviewer #1 (Public Review):

This paper presents a set of experiments designed to test whether gravity in people's intuitive physics engine is implemented as a simple deterministic representation of gravity or as a Gaussian distribution. The work shows experimentally that the probabilistic representation of gravity does a better job at capturing both human judgments, including biases in stability inferences. The work further shows that Gaussian representations of gravity can evolve in a simple agent-environment reinforcement learning problem setup.

Strengths:<br /> The paper approaches the problem from three different angles in an impressive way. The first is through a direct comparison of human judgments against model predictions. The second is through an analysis of whether the model correctly predicts cognitive illusions. The third is through a computational exploration of how these representations emerge in a reinforcement-learning setup. The idea of approaching the same problem from multiple independent angles, and seeking confirming evidence is laudable.

Weaknesses:<br /> There are two differences between the "natural gravity" account and the "mental gravity" account. The first difference lies in the implementation of gravity. The second, however, is simply that the mental gravity model is integrating more uncertainty into the simulator. In my understanding, adding small amounts of noise to computational models will often increase their fit to human judgments (with softmaxing perhaps being the most common example of this). While counter-intuitive, this is because 'noiseless' models have perfect representations of the stimuli, which is an unrealistic assumption. In the case of intuitive physics, people might have noisy perceptual representations of exactly how flat the table is, the exact location of each block, what small disturbances might be happening in the environment, and so on. The absence of these sources of uncertainty in deterministic models can make them perform in a non-human-like manner.

While all the data presented in the paper is consistent with the possibility that people have a stochastic representation of gravity. It is possible that people have uncertainty over what unobservable forces a block tower might be under (e.g., wind, bumps to the table, etc). Therefore, even if you have a firm belief that gravity goes down, you may want to add noise in your simulations to account for the fact that, in the real world, gravity is almost never the only force acting on an object that has started to move. While the paper acknowledges that such an account would be mathematically equivalent, it does not acknowledge that this raises the question of whether people actually have stochastic representations of gravity.

This alternative account could be particularly important because I believe it might be a more accurate representation of what people believe. I may be wrong, but I believe that it is common to emphasize the probabilistic nature of the models and the importance of implementing forces as distributions (e.g., the concept of 'noisy newtons').

Reviewer #2 (Public Review):

Summary:<br /> Through a set of experiments and model simulations, the authors tested whether the commonly assumed world model of gravity was a faithful replica of the physical world. They found that participants did not model gravity as a single, fixed vector for gravity but instead as a distribution of possible vectors. Surprisingly, the width of this distribution was quite large (~20 degrees). While previous accounts had suggested that this uncertainty was due to perceptual noise or an inferred external perturbation, the authors suggest that this uncertainty simply arises from a noisy distribution of the representation of gravity's direction. A reinforcement learning model with an initial uniform distribution for gravity's direction ultimately converged to a precision in the same order as the human participants, which lends support to the authors' conclusion and suggests that this distribution is learned through experience. What's more, further simulations suggest that representing gravity with such a wide distribution may balance speed and accuracy, providing a potentially normative explanation for the world model with gravity as a distribution.

Strengths:<br /> The authors present surprising findings in a relatively straightforward way in a now classic experimental task. They provide a normative explanation based on a resource-rational framework for why people may have a stochastic world model instead of a deterministic world model.

Weaknesses:<br /> Support for gravity being represented as a Gaussian distribution (stochastic world model), as opposed to perceptual uncertainty or (inferred) external perturbations, is from an RL model simulation. It would be more convincing if the authors could experimentally demonstrate that potential external perturbations did not affect the distribution of gravity.

Reviewer #3 (Public Review):

Summary:<br /> Previous studies suggest that humans may infer objects' stability through a world model that performs mental simulations with a priori knowledge of gravity acting upon objects. In this study, the authors test two alternative hypotheses about the nature of this a priori knowledge. According to the Natural Gravity assumption, the direction of gravity encoded in this world model is straight downwards as in the physical world. According to the alternative Mental Gravity assumption, that gravity direction is encoded in a Gaussian distribution, with the vertical direction as the maximum likelihood. They present two experiments and computer simulations as evidence in support of the Mental Gravity assumption. Their conclusion is that when the brain is tasked to determine the stability of a given structure it runs a mental simulation, termed Mental Gravity Simulation, which averages the estimated temporal evolutions of that structure arising from different gravity directions sampled from a Gaussian distribution.

Weaknesses:<br /> In spite of the fact that the Mental Gravity Simulation (MGS) seems to predict the data of the two experiments, it is an untenable hypothesis. I give the main reason for this conclusion by illustrating a simple thought experiment. Suppose you ask subjects to determine whether a single block (like those used in the simulations) is about to fall. We can think of blocks of varying heights. No matter how tall a block is, if it is standing on a horizontal surface it will not fall until some external perturbation disturbs its equilibrium. I am confident that most human observers would predict this outcome as well. However, the MSG simulation would not produce this outcome. Instead, it would predict a non-zero probability of the block to tip over. A gravitational field that is not perpendicular to the base has the equivalent effect of a horizontal force applied on the block at the height corresponding to the vertical position of the center of gravity. Depending on the friction determined by the contact between the base of the block and the surface where it stands there is a critical height where any horizontal force being applied would cause the block to fall while pivoting about one of the edges at the base (the one opposite to where the force has been applied). This critical height depends on both the size of the base and the friction coefficient. For short objects this critical height is larger than the height of the object, so that object would not fall. But for taller blocks, this is not the case. Indeed, the taller the block the smaller the deviation from a vertical gravitational field is needed for a fall to be expected. The discrepancy between this prediction and the most likely outcome of the simple experiment I have just outlined makes the MSG model implausible. Note also that a gravitational field that is not perpendicular to the ground surface is equivalent to the force field experienced by the block while standing on an inclined plane. For small friction values, the block is expected to slide down the incline, therefore another prediction of this MSG model is that when we observe an object on a surface exerting negligible friction (think of a puck on ice) we should expect that object to spontaneously move. But of course, we don't, as we do not expect tall objects that are standing to suddenly fall if left unperturbed. In summary, a stochastic world model cannot explain these simple observations.

The question remains as to how we can interpret the empirical data from the two experiments and their agreement with the predictions of the stochastic world model if we assume that the brain has internalized a vertical gravitational field. First, we need to look more closely at the questions posed to the subjects in the two experiments. In the first experiment, subjects are asked about how "normal" a fall of a block construction looks. Subjects seem to accept 50% of the time a fall is normal when the gravitational field is about 20 deg away from the vertical direction. The authors conclude that according to the brain, such an unusual gravitational field is possible. However, there are alternative explanations for these findings that do not require a perceptual error in the estimation of the direction of gravity. There are several aspects of the scene that may be misjudged by the observer. First, the 3D interpretation of the scene and the 3D motion of the objects can be inaccurate. Indeed, the simulation of a normal fall uploaded by the authors seems to show objects falling in a much weaker gravitational field than the one on Earth since the blocks seem to fall in "slow motion". This is probably because the perceived height of the structure is much smaller than the simulated height. In general, there are even more severe biases affecting the perception of 3D structures that depend on many factors, for instance, the viewpoint. Second, the distribution of weight among the objects and the friction coefficients acting between the surfaces are also unknown parameters. In other words, there are several parameters that depend on the viewing conditions and material composition of the blocks that are unknown and need to be estimated. The authors assume that these parameters are derived accurately and only that assumption allows them to attribute the observed biases to an error in the estimate of the gravitational field. Of course, if the direction of gravity is the only parameter allowed to vary freely then it is no surprise that it explains the results. Instead, a simulation with a titled angle of gravity may give rise to a display that is interpreted as rendering a vertical gravitational field while other parameters are misperceived. Moreover, there is an additional factor that is intentionally dismissed by the authors that is a possible cause of the fall of a stack of cubes: an external force. Stacks that are initially standing should not fall all of a sudden unless some unwanted force is applied to the construction. For instance, a sudden gust of wind would create a force field on a stack that is equivalent to that produced by a tilted gravitational field. Such an explanation would easily apply to the findings of the second experiment. In that experiment subjects are explicitly asked if a stack of blocks looks "stable". This is an ambiguous question because the stability of a structure is always judged by imagining what would happen to the structure if an external perturbation is applied. The right question should be: "do you think this structure would fall if unperturbed". However, if stability is judged in the face of possible external perturbations then a tall structure would certainly be judged as less stable than a short structure occupying the same ground area. This is what the authors find. What they consider as a bias (tall structures are perceived as less stable than short structures) is instead a wrong interpretation of the mental process that determines stability. If subjects are asked the question "Is it going to fall?" then tall stacks of sound structure would be judged as stable as short stacks, just more precarious.

The RL model used as a proof of concept for how the brain may build a stochastic prior for the direction of gravity is based on very strong and unverified assumptions. The first assumption is that the brain already knows about the force of gravity, but it lacks knowledge of the direction of this force of gravity. The second assumption is that before learning the brain knows the effect of a gravitational field on a stack of blocks. How can the brain simulate the effect of a non-vertical gravitational field on a structure if it has never observed such an event? The third assumption is that from the visual input, the brain is able to figure out the exact 3D coordinates of the blocks. This has been proven to be untrue in a large number of studies. Given these assumptions and the fact that the only parameters the RL model modifies through learning specify the direction of gravity, I am not surprised that the model produces the desired results.

Finally, the argument that the MGS is more efficient than the NGS model is based on an incorrect analysis of the results of the simulation. It is true that 80% accuracy is reached faster by the MGS model than the 95% accuracy level is reached by the NGS model. But the question is: how fast does the NGS model reach 80% accuracy (before reaching the plateau)?

Reviewer #1 (Public Review):

Summary:<br /> The authors made significant updates to Hippacampome.org including 50 new cell types.

Strengths:<br /> The authors have been thorough in basing their views on peer-reviewed literature. They have made the data highly accessible and the user has the ability to control what is included.

Weaknesses:<br /> There are many inconsistencies in the literature regarding cell types and how these are incorporated into hippocampome.org is not clear.

Properties are often a result of modeling and not biological data, and caveats to this approach, and other assumptions are unclear.

Several interneuron subtypes in the dentate gyrus do not appear to be listed, such as neurogliaform cells.

The nomenclature HIPROM should be distinguished or made synonymous with HIPP. Same for MOCAP and MOPP/HICAP.

Dorsal ventral and sex differences are not mentioned.

Reviewer #2 (Public Review):

Summary and strengths:<br /> The authors have developed a helpful resource for the community regarding hippocampal cell types and their interactions from many perspectives. There have been many updates to hippocampome v1.0 to v1.12, that are nicely summarized and explained (e.g., Table 1). The content and impact are also presented (Fig. 4).

Weaknesses:<br /> My main comment is that it is not completely clear and/or it is a bit buried as to what makes this v2.0 (rather than v1.13). The title would seem to encompass it ('... enabling data-driven spiking neural network simulations...), but in the introduction, the authors seem to emphasize "50 newly identified neuron types...". Is it the case that launching network simulations (using CARLsim) was not possible up to v1.12? I don't think so? I think that this research advance is to announce and summarize the various updates and to demonstrate how network simulations can be easily done? If so, this should and could be made more clear so that the reader does not necessarily have to go through all the previous versions to understand what is 'special' or different about v2.0. This could perhaps be achieved by situating their tool and its goals relative to other efforts (e.g., blue brain project) that are mentioned in the Discussion?

Reviewer #3 (Public Review):

Summary:<br /> The authors aim to provide a multidisciplinary resource on the structural and physiological organization of the hippocampal system and make the available experimental data available for further theoretical work, providing tools to do so in a very flexible and user-friendly way. Since this is a new version of an already existing data-resource, the authors certainly reach their aim and fulfil expectations that the reader might have. The content of the database is as good as the original data, collected from the published knowledge-database, sometimes with the help of the original authors, and the overall quality depends further on how the data are curated by the team of authors and many others who helped them. That process is briefly described and more details are available in descriptions of previous versions and on the website. The data extraction, examples of how data can be used, and the part on attempts to model the hippocampus are exciting and open doors to new and exciting research opportunities.

Strengths:<br /> Excellent description with many outlined opportunities. Nicely illustrated and inviting to explore the online database.

Weaknesses:<br /> The figures are complex, containing a heavy information load with many abbreviations. You need some general knowledge of the system in order to grasp the enormous potential of what is provided.

Joint Public Review:

Summary: This study follows up on previous work showing a female-specific enhancer region of PAX1 is associated with adolescent idiopathic scoliosis (AIS). This new analysis combines human GWAS analysis from multiple countries to identify a new AIS-associated coding variant in the COL11A1 gene. Two nonsynonymous variants were found to be significantly associated with AIS: MMP14 p.Asp273Asn and COL11A1 p.Pro1335Leu, the latter of which had the more robust association and remained significant when females were tested independent of males. Using a Pax1 knockout mouse they go on to find that PAX1 and Collagen XI protein are expressed in the intervertebral discs (IVDs) and robustly in the growth plate, showing that COL11A1 expression is reduced in Pax1 mutant growth plate. Moreover, other AIS-associated genes, Gpr126 and Sox6, were also reduced in Pax1 mutant mice, suggesting a common pathway is involved in AIS. The proposed implication of a Pax1-Col11a1-Mmp3 signaling axis modulated by estrogen signaling suggests a potential mechanism by which young women have more severe scoliosis than young men, as is observed in humans.

Strengths: This work integrates a large cohort of human genetic data from AIS patients and controls from diverse ethnic backgrounds, across the globe. This work attempts to functionally test their findings in vivo and by use of cell culture. The authors propose an interesting model which warrants in depth investigation.

Weaknesses: There are concerns regarding the candidacy of COL11A1 p.Pro1335Leu that need to be addressed and clarified. Many of the main functional work was done in cell culture and not in vivo. Moreover, the evidence linking COL11A1 p.Pro1153Leu to AIS is indirect, making unclear whether impaired COL11A1 function can cause scoliosis in the mouse model, thus diminishing the strength of the conclusions regarding the proposed pathogenicity of COL11A1 p.Pro1335Leu.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Seba et al., investigate the mechanism of chromosome organization by the MukBEF complex in E. coli. They use a combination of Hi-C and ChIP analysis to understand the steps of MukBEF regulation: its unloading from DNA (how MukBEF activity is prevented in the terminus regions of the chromosome by MatP), and its loading onto DNA (how DNA replication influences MukBEF association with the chromosome). Seba et al., induce chromosomal rearrangements to flip the sections of the ter region, thus perturbing matS site numbers and position. They find that MukBEF activity is prevented around matS sites, and that higher matS density has greater effect on MukBEF. Separately, using replication mutants and inducible MukBEF expression, they find that MukBEF can associate with the chromosome even in the absence of replication (as seen by the emergence of long-range contacts). However, ChIP data suggests that MukBEF binding to DNA is enriched on newly replicated DNA.

Strengths:<br /> Altogether, this work provides a valuable and comprehensive view of MukBEF-mediated chromosome organization, with insights on the mechanism of the exclusion of MukBEF from the terminus region of the chromosome. The use of the programmed genetic rearrangements is powerful, and allows the authors to provide clear and convincing evidence for MukBEF exclusion from ter by matS sites. It is particularly striking to see that MukBEF can promote long-range contacts even in chromosomal regions between two matS, but the complex is excluded from the matS 'zones'. Experiments using cells blocked for replication show that MukBEF can influence chromosome organization in the absence of replication as well. While previous studies have reported some evidence in support of both of the above conclusions, the experiments described here offer clear and direct demonstration of the same.

Limitations:<br /> A few control experiments are required to strengthen conclusions. Additionally, the discussion section is lacking many references and key papers have not been cited (paragraph 1 of discussion for example has no references). The possibility that SMC-ScpAB and MukBEF can act independent of replication has been suggested previously, but are not cited or discussed. Similarly, there is some evidence for SMC-ScpAB association with newly replicated DNA (PMID 21923769).

Reviewer #2 (Public Review):

Summary:<br /> Chromosome organization in E. coli and related species ('transversal') deviates starkly from the pattern more commonly found in bacteria ('longitudinal'). The underlying mechanisms and the physiological roles, however, are not well understood. This manuscript by Seba et al. investigates the activity and regulation of MukBEF in chromosome folding in E. coli. Using a construct for inducible expression of MukBEF, the authors first demonstrate that the initiation of long-range chromosome contacts (likely by loop extrusion) is not restricted to few positions on the chromosome and rather widely distributed but excluding the replication terminus region. Using ChIP-Seq, the authors show that the distribution of MukBEF over the chromosome is consistent with widely distributed loading and moreover indicate a connection of chromosome folding and DNA replication with newly replicated DNA shower an increased tendency for MukBEF binding. To dissect this further, they then redistribute matS sites on the chromosome by a clever strategy based on large-scale transpositions. The results reveal that matS-free DNA segments undergo MukBEF dependent folding regardless of their position relative to the origin of replication, being consistent with a broad distributed loading of MukBEF. By fine-mapping with smaller transposition events, they show that few matS sites are sufficient to impede MukBEF activity. Surprisingly, however, E. coli and most related genomes harbor many matS sites, which are particularly highly concentrated near the chromosome dimer resolution dif site (Fig. 5).

Strengths:<br /> This is a well-executed and well-presented study. The findings show that the MatP/matS system acts locally and independently of DNA replication to restrict MukBEF in the replication terminus region. Few of the many matS sites are sufficient for MukBEF restriction. The main conclusions of the work are clear and well supported by the data.

Weaknesses:<br /> The biological relevance of MukBEF restriction from the replication terminus region remains unresolved. The authors could speculate on possible functions.

Reviewer #3 (Public Review):

Seba et al. investigate whether chromosomal recruitment of the E. coli SMC complex MukBEF is initiated at a single site, how MukBEF activity is excluded from the replication terminus region, and whether its recruitment and activity depend on DNA replication. Upon induction of MukBEF, the authors find that chromosomal long-range contacts increase globally rather than from a single site. Using large-scale chromosome rearrangements, they show that matS sites can insulate separate areas of high MukBEF activity from each other. This suggests that MukBEF loads at multiple sites in the genome. Finally, the authors propose that MukBEF associates preferentially with newly replicated DNA, based on ChIP-seq experiments after DNA replication arrest.

The conclusions of the paper are mostly well supported by the data. The ratiometric contact analyses and range-of-contact analyses are compelling and nicely show the interplay between MukBEF and its proposed unloader MatP/matS. I particularly enjoyed the chromosome re-arrangement experiments, which lend strong support to the idea that MukBEF activity is independent of a centralized loading site.

The enrichment of MukBEF in newly replicated regions is somewhat less convincing, as the effect sizes are rather small and the background signal is unknown. The conclusion that matS density controls MukBEF activity is appealing, but would likely need additional support from more systematic studies. It is based on a comparison of only two strains (looking at different combinations of three matS sites), and the effect size is small. As it is, differences in matS sequence composition and genomic context cannot be factored out.

Overall, the work is an important advance in our understanding of bacterial chromosome organization. It will be of broad interest to chromosome biologists and bacterial cell biologists.

Reviewer #1 (Public Review):

The authors investigate the role of chirping in a species of weakly electric fish. They subject the fish to various scenarios and correlate the production of chirps with many different factors. They find major correlations between the background beat signals (continuously present during any social interactions) or some aspects of social and environmental conditions with the propensity to produce different types of chirps. By analyzing more specifically different aspects of these correlations they conclude that chirping patterns are related to navigation purposes and the need to localize the source of the beat signal (i.e. the location of the conspecific).

The study provides a wealth of interesting observation of behavior and much of this data constitute a useful dataset to document the patterns of social interactions in these fish. Some data, in particular the high propensity to chirp in cluttered environments, raises interesting questions. Their main hypothesis is a useful addition to the debate on the function of these chirps and is worth being considered and explored further. However, the data they provide does not support strong conclusion statements arguing that these chirps are used for localization purposes and is even less convincing at rejecting previously established hypotheses on the communication purpose of the chirps. I would suggest thoroughly revising the manuscript to provide a neutral description of the results and leaving any speculations and interpretations for the discussion where the authors should be careful to separate strongly supported hypotheses from more preliminary speculations. I detail below several instances where the argumentation and/or the analysis are flawed.

- They analyze chirp patterning and show that, most likely, a chirp by an individual is followed by a chirp in the same individual. They argue that it is rare that a chirp elicits a "response" in the other fish. Even if there are clearly stronger correlations between chirps in the same individual, they provide no statistical analysis that discards the existence of occasional "response" patterns. The fact that these are rare, and that the authors don't do an appropriate analysis of probabilities, leads to this unsupported conclusion.<br /> - One of the main pieces of evidence that chirps can be used to enhance conspecific localization is based on their "interference" measure. The measure is based on an analysis of "inter-peak-intervales". This in itself is a questionable choice. The nervous system encodes all parts of the stimulus, not just the peak, and disruption occurring at other phases of the beat might be as relevant. The interference will be mostly affected by the summed duration of intervals between peaks in the chirp AM. They do not explain why this varies with beat frequency. It is likely that the changes they see are simply an artifact of the simplistic measure. A clear demonstration that this measure is not adequate comes from the observation in Fig7E-H. They show that the interference value changes as the signal is weaker. This measure should be independent of the strength of the signal. The method is based on detecting peaks and quantifying the time between peaks. The only reason this measure could be affected by signal strength is if noisy recordings affect how the peak detection occurs. There is no way to argue that this phenomenon would happen the same way in the nervous system. Furthermore, they qualitatively argue that patterns of chirp production follow patterns of interference strength. No statistical demonstration is done. Even the qualitative appraisal is questionable. For example, they argue that there are relatively few chirps being produced for DFs of 60 or -60 Hz. But these are DF where they have only a very small sample size. The single pair of fish that they recorded at some of these frequencies might not have chirped by chance and a rigorous statistical analysis is necessary. Similarly, in Fig 5C they argue that the position of the chirps fall on areas of the graph where the interferences are strongest (darker blue) but this is far from obvious and, again, not proven.<br /> - They relate the angle at which one fish produces chirps relative to the orientation of the mesh enclosing. They argue that this is related to the orientation of electric field lines by doing a qualitative comparison with a simplified estimate of field lines. To be convincing this analysis should include a quantitative comparison using the exact same body position of the two fish when the chirps are emitted.<br /> -They show that the very vast majority of chirps in Fig 6 occur when the fish are within a few centimeters (e.g. very large first bin in Fig6E-Type2). This is a situation when the other fish signal will be strongest and localization will be the easiest. It is hard to understand why the fish would need a mechanism to enhance localization in these conditions (this is the opposite of difficult conditions e.g. the "cluttered" environment).<br /> - The argumentation aimed at rejecting the well-established role of chirp in communication is weak at best. First, they ignored some existing data when they argue that there is no correlation between chirping and behavioral interactions. Particularly, Hupe and Lewis (2008) showed a clear temporal correlation between chirps and a decrease in bites during aggressive encounters. It could be argued that this is "causal evidence" (to reuse their wording) that chirps cause a decrease in attacks by the receiver fish (see Fig 8B of the Hupe paper and associated significant statistics). Also, Oboti et al. argue that social interactions involve "higher levels of locomotion" which would explain the use of chirps since they are used to localize. But chirps are frequent in "chirp chamber" paradigms where no movement is involved. They also point out that social context covaries with beat frequency and thus that it is hard to distinguish which one is linked to chirping propensity and then say that it is hard to disentangle this from "biophysical features of EOD fields affecting detection and localization of conspecific fish". But they don't provide any proof that beat frequency affects detection and localization so their argument is not clear. Last, they argue that tests in one species shouldn't be extrapolated to other species. But many of the studies arguing for the role of chirps in communication was done on brown ghost. In conclusion of this point, they do not provide any strong argument that rejects the role of chirps as a communication signal. A perspective that would be better supported by their data and consistent with past research would be to argue that, in addition to a role in communication, chirps could sometimes be used to help localize conspecifics.<br /> -The discussion they provide on the possible mechanism by which chirps could help with localization of the conspecific is problematic. They imply that chirps cause a stronger response in the receptors. For most chirps considered here, this is not true. For a large portion of the beat frequencies shown in this paper, chirps will cause a de-synchronization of the receptors with no increase in firing rate. They cannot argue that this represents an enhanced response. They also discuss a role for having a broader frequency spectrum -during the chirp- in localization by making a parallel with pulse fish. There is no evidence that a similar mechanism could even work in wave-type fish.<br /> -They write the whole paper as if males and females had been identified in their experiments. Although EOD frequency can provide some guess of the sex the method is unreliable. We can expect a non-negligible percentage of error in assigning sex.

Reviewer #2 (Public Review):

Studying the weakly electric brown ghost knifefish, the authors provide evidence that 'chirps' (brief modulations in the frequency and amplitude of the ongoing electric signal) function in active sensing (specifically homeoactive sensing) rather than communication. This is a behavior that has been very well studied, including numerous studies on the sensory coding of chirps and the neural mechanisms for chirp generation. Chirps are largely thought to function in communication behavior, so this alternative function is a very exciting possibility that could have a great impact on the field. The authors do provide convincing evidence that chirps may function in homeoactive sensing. However, their evidence arguing against a role for chirps in communication is not as strong, and neglects a large body of research. Ultimately, the manuscript has great potential but suffers from framing these two possibilities as mutually exclusive and dismissing evidence in favor of a communicative function.

(1) The specific underlying question of this study is not made clear in the abstract or introduction. It becomes apparent in reading through the manuscript that the authors seek to test the hypothesis that chirps function in active sensing (specifically homeoactive sensing). This should be made explicitly clear in both the abstract and introduction, along with the rationale for this hypothesis.

(2) My biggest issue with this manuscript is that it is much too strong in dismissing evidence that chirping correlates with context. This is captured in this sentence in the introduction, "We first show that the choice of different chirp types does not significantly correlate with any particular behavioral or social context." This very strong conclusion comes up repeatedly, and I disagree with it, for the following reasons:

In your behavioral observations, you found sex differences in chirping as well as differences between freely interacting and physically separated fish. Your model of chirp variability found that environmental experience, social experience, and beat frequency (DF) are the most important factors explaining chirp variability. Are these not all considered "behavioral or social context"? Beat frequency (DF) in particular is heavily downplayed as being a part of "context" but it is a crucial part of the context, as it provides information about the identity of the fish you're interacting with.

In your playback experiments, fish responded differently to small vs. large DFs, males chirped more than females, type 2 chirps became more frequent throughout a playback, and rises tended to occur at the end of a playback. These are all examples of context-dependent behavior.

Further, you only considered the identity of interacting fish or stimulated fish, not their behavior during the interaction or during playback. Such an analysis is likely beyond the scope of this study, but several other studies have shown correlations between social behavior and chirping. In the absence of such data here, it is too strong to claim that chirping is unrelated to context.

In summary, it is simply too strong to say that chirping does not correlate with context. Importantly, however, this does not detract from your hypothesis that chirping functions in homeoactive sensing. A given EOD behavior could serve both communication and homeoactive sensing. I actually suspect that this is quite common in electric fish. The two are not mutually exclusive, and there is no reason for you to present them as such. I recommend focusing more on the positive evidence for a homeoactive function and less on the negative evidence against a communication function.

(3) The results were generally challenging to follow. In the first 4 sections, it is not made clear what the specific question is, what the approach to addressing that question is, and what specific experiment was carried out (the last two sections of the results were much clearer). The independent variables (contexts) are not clearly established before presenting the results. Instead they are often mentioned in passing when describing the results. They come across as an unbalanced hodgepodge of multiple factors, and it is not made clear why they were chosen. This makes it challenging to understand why you did what you did, the results, and their implications. For each set of major results, I recommend: First, pose a clear question. Then, describe the general approach to answering that question. Next, describe the specifics of the experimental design, with a rationale that appeals to the general approach described. Finally, describe the specific results.

(4) Results: "We thus predicted that, if behavioral meaning can be attributed to different types of chirps, as posed by the prevailing view (e.g., Hagedorn and Heiligenberg, 1985; Larimer and MacDonald, 1968; Rose, 2004)..." It should be made clear why this is the prevailing view, and this description should likely be moved to the introduction. There is a large body of evidence supporting this view and it is important to be complete in describing it, especially since the authors seem to seek to refute it.

(5) I am not convinced of the conclusion drawn by the analysis of chirp transitions. The transition matrices show plenty of 1-2 and 2-1 transitions occurring. Further, the cross-correlation analysis only shows that chirp timing between individuals is not phase-locked at these small timescales. It is entirely possible that chirp rates are correlated between interacting individuals, even if their precise timing is not.

Reviewer #3 (Public Review):

Summary:<br /> This important paper provides the best-to-date characterization of chirping in weakly electric fish using a large number of variables. These include environment (free vs divided fish, with or without clutter), breeding state, gender, intruder vs resident, social status, locomotion state and social and environmental experience, as well as with playback experiments. It applies state-of-the-art methods for reducing dimensionality and finding patterns of correlation between different kinds of variables (factor analysis, K-means). The exceptional strength of the evidence, collated from a large number of trials with many controls, leads to the conclusion that a number of commonly accepted truths about which variable affects chirping must be carefully rewritten or nuanced. Based on their extensive analyses, the authors suggest that chirps are mainly used as probes that help detect beats and objects.

Strengths:<br /> The work is based on completely novel recordings using interaction chambers. The amount of new data and associated analyses is simply staggering, and yet, well organized in presentation. The study further evaluates the electric field strength around a fish (via modelling with the boundary element method) and how its decay parallels the chirp rate, thereby relating the above variables to electric field geometry.

The main conclusions are that the lack of any significant behavioural correlates for chirping, and the lack of temporal patterning in chirp time series, cast doubt on a communication goal for most chirps. Rather, the key determinants of chirping are the difference frequency between two interacting conspecifics as well as individual subjects' environmental and social experience. These conclusions by themselves will be hugely useful to the field. They will also allow scientists working on other "communication" systems to at least reconsider, and perhaps expand the precise goal of the probes used in those senses. There are a lot of data summarized in this paper, and thorough referencing to past work. For example, the paper concludes that there is a lack of evidence for stereotyped temporal patterning of chirp time series, as well as of sender-received chirp transitions beyond the known increase in chirp frequency during an interaction.

The alternative hypotheses that arise from the work are that chirps are mainly used as environmental probes for better beat detection and processing and object localization.

The authors also advance the interesting idea that the sinusoidal frequency modulations caused by chirps are the electric fish's solution to the minute (and undetectable by neural wetware) echo-delays available to it, due to the propagation of electric fields at the speed of light in water.

Weaknesses:<br /> My main criticism is that the alternative putative role for chirps as probe signals that optimize beat detection could be better developed. The paper could be clearer as to what that means precisely. And there is an egg-and-chicken type issue as well, namely, that one needs a beat in order to "chirp" the beating pattern, but then how does chirping optimize the detection of the said beat? Perhaps the authors mean (as they wrote elsewhere in the paper) that the chirps could enhance electrosensory responses to the beat.

A second criticism is that the study links the beat detection to underwater object localization. I did not see a sufficiently developed argument in this direction, nor how the data provided support for this argument. It is certainly possible that the image on the fish's body of an object in the environment will be slightly modified by introducing a chirp on the waveform, as this may enhance certain heterogeneities of the object in relation to its environment. The thrust of this argument seems to derive more from the notion of Fourier analysis with pulse type fish (and radar theory more generally) that the higher temporal frequencies in the beat waveform induced by the chirp will enable a better spatial resolution of objects. It remains to be seen whether this is significant.

I would also have liked to see a proposal for new experiments that could test these possible new roles.

The authors should recall for the readers the gist of Bastian's 2001 argument that the chirp "can adjust the beat frequency to levels that are better detectable" in the light of their current. Further, at the beginning of the "Probing with chirps" section, the 3rd way in which chirps could improve conspecific localization mentions the phase-shifting of the EOD. The authors should clarify whether they mean that the tuberous receptors and associated ELL/toral circuitry could deal with that cue, or that the T_unit pathway would be needed?

On p.17 I don't understand what is meant by most chirps being produced possibly aligned with the field lines, since field lines are everywhere. And what is one to conclude from the comparison of Fig.6D and 7A? Likewise it was not clear what is meant by chirps having a detectable effect on randomly generated beats.

In the section on Inconsistencies between behaviour and hypothesized signal meaning, the authors could perhaps nuance the interpretation of the results further in the context of the unrealistic copy of natural stimuli using EOD mimics. In particular, Kelly et al. 2008 argued that electrode placement mattered in terms of representation of a mimic fish onto the body of a real fish, and thus, if I properly understand the set up here, the movement would cause the mimic to vary in quality. This may nevertheless be a small confounding issue.

Reviewer #1 (Public Review):

Numerous neurodegenerative diseases are thought to be driven by the aggregation of proteins into insoluble filaments known as "amyloids". Despite decades of research, the mechanism by which proteins convert from the soluble to insoluble state is poorly understood. In particular, the initial nucleation step is has proven especially elusive to both experiments and simulation. This is because the critical nucleus is thermodynamically unstable, and therefore, occurs too infrequently to directly observe. Furthermore, after nucleation much faster processes like growth and secondary nucleation dominate the kinetics, which makes it difficult to isolate the effects of the initial nucleation event. In this work Kandola et al. attempt to surmount these obstacles using individual yeast cells as microscopic reaction vessels. The large number of cells, and their small size, provides the statistics to separate the cells into pre- and post-nucleation populations, allowing them to obtain nucleation rates under physiological conditions. By systematically introducing mutations into the amyloid-forming polyglutamine core of huntingtin protein, they deduce the probable structure of the amyloid nucleus. This work shows that, despite the complexity of the cellular environment, the seemingly random effects of mutations can be understood with a relatively simple physical model. Furthermore, their model shows how amyloid nucleation and growth differ in significant ways, which provides testable hypotheses for probing how different steps in the aggregation pathway may lead to neurotoxicity.

In this study Kandola et al. probe the nucleation barrier by observing a bimodal distribution of cells that contain aggregates; the cells containing aggregates have had a stochastic fluctuation allowing the proteins to surmount the barrier, while those without aggregates have yet to have a fluctuation of suitable size. The authors confirm this interpretation with the selective manipulation of the PIN gene, which provides an amyloid template that allows the system to skip the nucleation event.

In simple systems lacking internal degrees of freedom (i.e., colloids or rigid molecules) the nucleation barrier comes from a significant entropic cost that comes from bringing molecules together. In large aggregates this entropic cost is balanced by attractive interactions between the particles, but small clusters are unable to form the extensive network of stabilizing contacts present in the larger aggregates. Therefore, the initial steps in nucleation incur an entropic cost without compensating attractive interactions (this imbalance can be described as a surface tension). When internal degrees of freedom are present, such as the conformational states of a polypeptide chain, there is an additional contribution to the barrier coming from the loss of conformational entropy required to the adopt aggregation-prone state(s). In such systems the clustering and conformational processes do not necessarily coincide, and a major challenge studying nucleation is to separate out these two contributions to the free energy barrier. Surprisingly, Kandola et al. find that the critical nucleus occurs within a single molecule. This means that the largest contribution to the barrier comes from the conformational entropy cost of adopting the beta-sheet state. Once this state is attained, additional molecules can be recruited with a much lower free energy barrier.

There are several considerations in interpreting this result. First, the height of the nucleation barrier(s) comes from the relative strength of the entropic costs compared to the binding affinities. This balance determines how large a nascent nucleus must grow before it can form interactions comparable to a mature aggregate. In amyloid nuclei the first three beta strands form immature contacts consisting of either side chain or backbone contacts, whereas the fourth strand is the first that is able to form both kinds of contacts (as in a mature fibril). This study used relatively long polypeptides of 60 amino acids. This is greater than the 20-40 amino acids found in amyloid-forming molecules like ABeta or IAPP. As a result, Kandola et al.'s molecules are able to fold enough times to create four beta strands and generate mature contacts intramolecularly. This authors make the plausible claim that these intramolecular folds explain the well-known length threshold (L~35) observed in polyQ diseases. The intramolecular folds reduce the importance of clustering multiple molecules together and increase the importance of the conformational states. Similarly, manipulating the sequence or molecular concentrations will be expected to manipulate the relative magnitude of the binding affinities and the clustering entropy, which will shift the relative heights of the entropic barriers.

The authors make an important point that the structure of the nucleus does not necessarily resemble that of the mature fibril. They find that the critical nucleus has a serpentine structure that is required by the need to form four beta strands to get the first mature contacts. However, this structure comes at a cost because residues in the hairpins cannot form strong backbone or zipper interactions. Mature fibrils offer a beta sheet template that allows incoming molecules to form mature contacts immediately. Thus, it is expected that the role of the serpentine nucleus is to template a more extended beta sheet structure that is found in mature fibrils.

A second point of consideration is the striking homogeneity of the nucleus structure they describe. This homogeneity is likely to be somewhat illusory. Homopolymers, like polyglutamine, have a discrete translational symmetry, which implies that the hairpins needed to form multiple beta sheets can occur at many places along the sequence. The asparagine residues introduced by the authors place limitations on where the hairpins can occur, and should be expected to increase structural homogeneity. Furthermore, the authors demonstrate that polyglutamine chains close to the minimum length of ~35 will have strict limitations on where the folds must occur in order to attain the required four beta strands.

A novel result of this work is the observation of multiple concentration regimes in the nucleation rate. Specifically, they report a plateau-like regime at intermediate regimes in which the nucleation rate is insensitive to protein concentration. The authors attribute this effect to the "self-poisoning" phenomenon observed in growth of some crystals. This is a valid comparison because the homogeneity observed in NMR and crystallography structures of mature fibrils resemble a one-dimensional crystal. Furthermore, the typical elongation rate of amyloid fibrils (on the order of one molecule per second) is many orders of magnitude slower than the molecular collision rate (by factors of 10^6 or more), implying that the search for the beta-sheet state is very slow. This slow conformational search implies the presence of deep kinetic traps that would be prone to poisoning phenomena. However, the observation of poisoning in nucleation during nucleation is striking, particularly in consideration of the expected disorder and concentration sensitivity of the nucleus. Kandola et al.'s structural model of an ordered, intramolecular nucleus explains why the internal states responsible for poisoning are relevant in nucleation.

To achieve these results the authors used a novel approach involving a systematic series of simple sequences. This is significant because, while individual experiments showed seemingly random behavior, the randomness resolved into clear trends with the systematic approach. These trends provided clues to build a model and guide further experiments.

There has been discussion in the review process about whether a monomeric nucleus is consistent with established properties of huntingtin aggregation. I do not see a problem with an energetically unfavorable conformational state preceding a concentration-dependent growth step. The authors make the case for this sequence using a schematic free energy landscape (Fig 6) that has many similarities to a free energy landscape derived from models of polyQ nucleation (Phan et al. 2022, see Fig. 6). The theory does not consider molecules large enough to form the conformational state described by Kandola et al., but the transition state is otherwise very similar.

Reviewer #2 (Public Review):

Kandola et al. explore the important and difficult question regarding the initiating event that triggers (nucleates) amyloid fibril growth in glutamine-rich domains. The researchers use a fluorescence technique that they developed, dAMFRET, in a yeast system where they can manipulate the expression level over several orders of magnitude, and they can control the length of the polyglutamine domain as well as the insertion of interfering non-glutamine residues. Using flow cytometry, they can interrogate each of these yeast 'reactors' to test for self-assembly.

In the introduction, the authors provide a fairly thorough yet succinct review of the relevant literature into the mechanisms of polyglutamine-mediated aggregation over the last two decades, as well as a fairly clear description of the experimental techniques they developed.

Their assay shows that the fraction of cells with AmFRET signal increases strongly with an increase in polyQ length, with a threshold around 35-40 glutamines. This roughly correlates with the Q-length dependence of disease. The experiments in which asparagine or other amino acids are inserted at variable positions in the glutamine repeat are creative and thorough, and the data along with the simulations provide compelling support for the proposed Q zipper model. The experiments are strongly supportive of a model where formation of the beta-sheet nucleus is within a monomer. This is a potentially important result, as there are conflicting data in the literature as to whether the nucleus in polyQ is monomer.

The authors present convincing data that there are differences in the structural stability of their "QU" versus "QB" aggregates. However, the conclusion that "QB" must have multilamellar architecture versus "QU" was feasible but less compelling.

The authors present intriguing data showing that amyloid formation does not monotonically increase with increasing concentration, and their conclusion that high concentrations of polyQ can 'self-poison' amyloid growth is supported by the experimental data. The discussion surrounding the mechanism by which 'self-poisoning' occurs is confusing. The authors variously discuss that soluble oligomers must be the inhibitory species, that dead-end products of Q zipper nuclei are the inhibitory species, or that self-poisoning occurs because conformational conversion at the templating surface is slow relative to the rate of arrival of new molecules to the surface. The data seem consistent with an argument that, at high concentrations, non-structured polyQ oligomers form which interfere with elongation into structured amyloid assemblies - but it is not clear why such oligomers would be zippers.

Overall, this is a very valuable and thorough exploration of the fundamental question as to the nature and identity of the nucleating species in polyglutamine aggregation.

Reviewer #2 (Public Review):

Summary:<br /> The EAG family of ion channels is associated with many pathological conditions and are considered a target for the treatment of disease such as cancer. In this study, Abdelaziz et. al. examine the role of interaction between PAS domain and CNBHD in voltage-dependent gating of EAG channels. Based on their data, the authors conclude that they have identified a hidden open state that is only accessible in the mutant channels but not in the wild type. This hidden open state O1 can distinguished from the canonical open state O2 because it exhibits very different voltage-dependence. Although it is clear that the kinetics of these two open states are different, I have concerns about whether the data presented in this manuscript rule out alternate explanations. The idea that PAS domain deletions uncover a hidden open state is an extraordinary claim and if established, it has the potential to open a completely new approach to studying early gating transitions of these channels.

Strengths:<br /> 1. The study has identified a number of potentially interesting mutants that modulate voltage-dependent gating.<br /> 2. The discovery of a hidden open state due to mutations in the cytosolic domains is quite astonishing.

Weaknesses:<br /> 1. WT EAG currents are far right shifted compared to previously published data. It is not clear whether it is the recording conditions but at 0 mV very few channels are open. Compare this with recordings reported previously of the same channel hEAG1 by Gail Robertson's lab ( Zhao et. al. (2017) JGP). In that case, most of the channels are open at 0 mV. There must be at least 25 mV shift in voltage-dependence. These differences are unusually large.

2. In most of the mutants, O2 state becomes more prevalent at potentials above +50 mV. At these potentials, endogenous voltage-dependent currents are often observed in xenopus oocytes. The observed differences between the various mutants might simply be a function of the expression level of the channel versus endogenous currents.

3. Voltage-dependence of the kinetics of WT currents appears a bit strange. Why is the voltage-dependence saturated at 0 mV even though very few channels have activated at that point? I cannot imagine any kinetic model that can lead to such unusual voltage-dependence of kinetics.

4. One of the other concerns I have is that in many cases, it is clear that the pulse is too short to measure steady-state voltage-dependence. For instance, the currents in -160 mV and -100 mV in Figure 6A and 6B are not saturated.

Reviewer #3 (Public Review):

Summary:<br /> The present manuscript by Reham Abdelaziz and colleagues addresses the gating of Kv10.1, which belongs to the KCNH gene family and contains other subfamilies such as Kv11 (ERG) and Kv12 (ELK). They all have fundamental physiological roles, from cardiac repolarization to modulation of neuronal excitability and cancer physiology. They have a non-domain swapped architecture at the molecular level; both voltage and Ca-CaM modulate the channel function. They contain an intracellular gating ring formed by a PAS domain (in the N-term) that interacts intimately with the cNBHD (C-term) of the neighbor subunit but also with the cytosolic part of the voltage sensor domain and the C-linker. Mutations in the N- or C- terminus modify the gating dramatically. This complex network of interactions makes the cytosolic section and the PAS domain in particular, an alluring part of the channel to study as responsible for the coupling between the movements of the voltage sensor and the gating ring.

In this paper, Reham Abdelaziz and colleagues address a fundamental question of how in the Kv10.1 channels, the movement of the voltage sensor is coupled to the intracellular gating ring rotation to make the channel conduct ions. The authors perform a series of deletions and mutations in the N-terminal section of the channel (PAS domain) and in the C-terminus (cNHBD) and observe a biphasic behavior on the modified EAG channels that they interpret as two populations of open states, one of them not visible in the WT and only available because of the mutations introduced. While this is a fascinating hypothesis and it fits with the depolarizing range of potentials of the WT channels, there are some issues that, if addressed, will make this work very valuable for biophysicists and molecular physiologists interested in voltage-gated ion channels.

Strengths:<br /> The work presented addresses one of this channel's most fascinating and challenging features in the KCNH family. The authors use adequate mutations and electrophysiological techniques to address the questions they are trying to answer. They help them explore the behavior of the channels and build a Markov model to understand the underlying mechanism.

Weaknesses:<br /> Although very well established, the experimental conditions used in the present manuscript introduce uncertainties, weakening their conclusions and complicating the interpretation of the results. The authors performed most of their functional studies in Cl-based solutions that can become a non-trivial issue when the range of voltages explored extends to very depolarizing potentials such as +120mV. Oocytes endogenously express Ca2+-activated Cl- channels that will rectify Cl- at very depolarizing potentials -due to an increase in the driving force- and contribute dramatically to the current's amplitude observed at the test pulse in the voltage ranges where the authors identify the second open state.

The authors propose a two-layer Markov model with two open states approximating their results. However, the results obtained with the mutants suggest an inactivated state accessible from closed states and a change in the equilibrium between the close/inactivated/open states that could also explain the observed results; therefore, other models could approximate their data.

That said, if the results obtained by the authors get confirmed under different experimental conditions in the absence of Cl-, this present work could be instrumental in understanding the gating mechanisms of the KCNH family.

Reviewer #1 (Public Review):

Gating of Kv10 channels is unique because it involves coupling between non-domain swapped voltage-sensing domains, a domain-swapped cytoplasmic ring assembly formed by the N- and C-termini, and the pore domain. Recent structural data suggests that activation of the voltage sensing domain relieves a steric hindrance to pore opening, but the contribution of the cytoplasmic domain to gating is still not well understood. This aspect is of particular importance because proteins like Calmodulin interact with the cytoplasmic domain to regulate channel activity. The effects of Calmodulin (CaM) in WT and mutant channels with disrupted cytoplasmic gating ring assemblies are contradictory, resulting in inhibition or activation, respectively. The underlying mechanism for these discrepancies is not understood. In the present manuscript, Reham Abdelaziz and collaborators use electrophysiology, biochemistry, and mathematical modeling to explore the mechanistic effects on gating of various mutations and deletions that disrupt inter-subunit interactions at the cytoplasmic gating ring assembly and the consequences for channel modulation by CaM. From the beginning, it becomes challenging for non-experts to grasp the structural basis of the perturbations that are introduced (ΔPASCap and E600R), because no structural data or schematic cartoons are provided to illustrate the rationale for those deletions or their potential mechanistic effects. In addition, the lack of additional structural information or illustrations, and a somewhat confusing discussion of the structural data, make it challenging for a reader to reconcile the experimental data and mathematical model with a particular structural mechanism for gating, limiting the impact of the work.

By expressing mutants in oocytes and recording currents using Two Electrode Voltage-Clamp (TEV), it is found that both ΔPASCap and E600R mutants have biphasic voltage-activation curves, with two clear components contributing to activation and deactivation kinetics. Notably, the first component involving activation occurs at voltages where WT channels are mostly closed. Larger deletions at the N-terminus that further disrupt the cytoplasmic gating ring assembly accentuate the first component by heavily disfavoring the second one. The data can be well described by three components involving a closed state and two open states O1 and O2, in which the second component O2 is the one affected by the mutations and deletions. Based on the structural data, the first component is hypothesized to be associated with voltage sensor activation, whereas the second component is associated with conformational changes at the cytoplasmic ring. Consistent with this interpretation, a deletion construct where the covalent link between the voltage sensor and pore has been severed is shown to primarily affect that first component. Also consistent with the first component involving voltage-sensor activation, it is found that divalent cations that are known to stabilize the voltage sensor in its most deactivated conformations, shift the occupancy of the first component to more depolarizing potentials. Activation towards and closure from the first component is slow, whereas channels close rapidly from O2. A rapid alternating pulse protocol is used to take advantage of the difference in activation and deactivation kinetics between the two open components in the mutants and thus drive an increasing number of channels toward state O1. Currents activated by the alternating protocol reached larger amplitudes than those elicited by a long depolarization to the same voltage. This finding is interpreted as an indication that the first component (O1) has a larger conductance than the second (O2). It is shown that conditioning pulses to very negative voltages results in currents that are larger and activate more slowly than those elicited at the same voltage but starting from less negative conditioning pulses. In voltage-activated curves, the component corresponding to state O1 is shown to be favored by increasingly negative conditioning voltages as compared to less negative ones. This is interpreted as indicating that the first open component O1 is primarily accessed from so-called 'deeply closed' states in which voltage sensors are in their most deactivated position(s). Consistently, a mutation that destabilizes these deactivated states is shown to largely suppress the first component in voltage-activation curves for both ΔPASCap and E600R channels. It is also shown that stimulating calcium entry into the oocytes with ionomycin and thapsigargin, which is assumed to enhance CaM-dependent modulation, results in preferential potentiation of the first component in ΔPASCap and E600R, and this potentiation is attenuated by including an additional mutation that disfavors deeply closed states where voltage sensors are (mostly) deactivated. Together, these results are interpreted as an indication that calcium-CaM preferentially stabilizes O1 in mutant channels, thus favoring activation, whereas in WT channels lacking occupancy of O1, CaM stabilizes closed states and is therefore inhibitory. Moreover, it is found that the potentiation of ΔPASCap and E600R by CaM is more strongly attenuated by mutations in the channel that disrupt interaction with the C-terminal lobe of CaM than mutations affecting interaction with the N-terminal lobe. Finally, a mathematical model is proposed consisting of two layers involving two activation steps for the voltage sensor, and one conformational change in the cytoplasmic gating ring - completion of both sets of conformational changes is required to access state O2, but accessing state O1 only requires completion of the first voltage-sensor activation step in the four subunits. The model qualitatively reproduces most major findings on the mutants.

There are several concerns associated with the analysis and interpretations that are provided. First, the conductance-voltage (G-V) relations for the mutants do not seem to saturate, and the absolute open probability is not quantified for any mutant under any condition. This makes it impossible to quantitatively compare the relative amplitudes of the two components because the amplitude of the second component remains undetermined. This makes it challenging to interpret results involving perturbations that affect the relative occupancy of O1 and O2, such as those in Figures 2, 6, and 7, and also raises concerns about the extent to which model parameters can be constrained. This issue is made even more serious by the observation that the currents in both key mutants (ΔPASCap and E600R) are extremely slow and do not appear to reach steady-state over the intervals that are studied. This reduces confidence in the parameters associated with G-V relations, as the shape and position of both components might change significantly if longer pulses were used. This is not addressed or acknowledged in the manuscript. Further, because the mutant channel currents do not saturate at the most positive potentials and time intervals examined, the kinetic characterization based on reaching 80% of the maximum seems inappropriate, because the 100% mark is arbitrary. Further, the kinetics for some of the other examined mutants (e.g. those in Fig. 2A) are not shown, making it difficult to assess the extent to which the data could be affected by having been measured before full equilibration. There are additional aspects associated with gating kinetics that are not appropriately explored. For example, I would expect that the enhanced current amplitudes from Figure 5 are only transient, ultimately reaching a smaller steady-state current magnitude that depends only on the stimulation voltage and is independent of the pre-pulse. The entire time course including the rise-time and decay is not examined experimentally. This raises concern on whether occupancy of state O1 might be overestimated under some experimental conditions if a fraction of the occupancy is only transient. The mathematical model is not utilized to examine some of these slower relaxations - this may be because the model does not reproduce these slow processes, which would represent a serious shortcoming given that the slow kinetics appear to be intrinsic to transitions around state O1. The significance of the results with the Δ2-10.L341Split is unclear. First, structural as well as functional data has established that the coupling of the voltage sensor and pore does not entirely rely on the S4-S5 linker, and thus the Split construct could still retain coupling through other mechanisms, which is consistent with the prominent voltage dependence that is observed. If both state O1 and O2 require voltage sensor activation, it is unclear why the Split construct would affect state O1 primarily, as suggested in the manuscript, as opposed to decreasing occupancy of both open states.

The figure legends and text do not describe which solutions exactly were utilized for each experiment, and the rationale for choosing some solutions over others is not properly explained. The reversal potential for solutions used to measure voltage-activation curves falls right at the spot where occupancy of the first component peaks (e.g. see Figure 1B). Because no zero-current levels are shown on the current traces, it becomes very hard to determine which voltages correspond to each of the currents (see Fig. 1A). It is unclear whether any artifacts could have been introduced to the mutant activation curves at voltages close to the reversal potential. One key assumption that is not well-supported by the data pertains to the difference in single-channel conductance between states O1 and O2 - no analysis or discussion is provided on whether the data could also be well described by an alternative model in which O1 and O2 have the same conductance. No additional experimental evidence is provided related to the difference in conductance, which represents a key aspect of the mathematical model utilized to interpret the data. The CaM experiments are potentially very interesting and could have wide physiological relevance. However, the approach utilized to activate CaM is indirect and could result in additional non-specific effects on the oocytes that could affect the results.

The description of the mathematical model that is provided is difficult to follow, and some key aspects are left unclear, such as the precise states from which state O1 can be accessed, and whether there is any direct connectivity between states O1 and O2 - different portions of the text appear to give contradictory information regarding these points. Several rate constants other than those explicitly mentioned to represent voltage sensor activation are also assigned a voltage dependence - the mechanistic basis of that voltage dependence is unclear. Finally, a clear mechanistic explanation for the full range of effects that the ΔPASCap and E600R mutants have on channel function is lacking, as well as a detailed description of how those newly uncovered transitions would influence the activity of the WT channel; this latter point is important when considering whether the findings in the manuscript advance our understanding of the gating mechanism of Kv10 channels in general, or are specific to the particular mutants that are studied. It is unclear, for example, how both the mutation or the deletion at the cytoplasmic gating ring enable conduction by state O1, especially when considering the hypothesis put forward in this study that transition to O1 exclusively involves transitions by the voltage sensor and not the cytoplasmic gating ring. It is also not clearly described whether a non-conducting state with the equivalent state-connectivity as O1 can be accessed in WT channels, or if a state like O1 can only be accessed in the mutant channels. Importantly, if a non-conducting state with the same connectivity to O1 were to be accessed in WT channels, it would be expected that an alternating pulse protocol as in Fig. 4 would result in progressively decreasing currents as the occupancy of the non-conducting state equivalent to O1 is increased. Because this is not the case, it means that mutation and deletion cause additional perturbations on the gating energetics relative to WT, which are not clearly fleshed out.

Reviewer #1 (Public Review):

The current manuscript provides a timely contribution to the ongoing discussion about the mechanism of the apical sodium/bile acid transporter (ASBT) transporters. Recent structures of the mammalian ASBT transporters exhibited a substrate binding mode with few interactions with the core domain (classically associated with substrate binding), prompting an unusual proposal for the transport mechanism. Early structures of ASBT homologues from bacteria also exhibit unusual substrate binding in which the core substrate binding domain is less engaged than expected. Due to the ongoing questions of how substrate binding and mechanism are linked in these transporters, the authors set out to deepen our understanding of a model ABST homolog from bacteria N. meningitidis (ABST-NM).

The premise of the current paper is that the bacterial ASBT homologs are probably not physiological bile acid transporters, and that structural elucidation of a natively transported substrate might provide better mechanistic information. In the current manuscript, the authors revisit the first BASS homologue to be structurally characterized, ABST-NM. Based on bacteriological assays in the literature, the authors identify the coenzyme A precursor pantoate as a more likely substrate for ABST-NM than taurocholate, the substrate in the original structure. A structure of ASBT-NM with pantoate exhibits interesting differences in structure. The structures are complemented with MD simulations, and the authors propose that the structures are consistent with a classical elevator transport mechanism.

The structural experiments are convincing. The binding and molecular dynamics experiments provide intriguing insights into the transporter's conformational changes. However, it is nonetheless a soft spot in the story that a transport assay is not readily available for this substrate. Mechanistic proposals, like the proposed role of T112 in unlocking the transporter, would be better supported by transport data.

Reviewer #2 (Public Review):

The manuscript starts with a demonstration of pantoate binding to ASBTnm using a thermostability assay and ITC, and follows with structure determinations of ASBTnm with or without pantoate. The structure of ASBTnm in the presence of pantoate pinpoints the binding site of pantoate to the "crossover" region formed by partially unwinded helices TMs 4 and 9. Binding of pantoate induces modest movements of side chain and backbone atoms at the crossover region that are consistent with providing coordination of the substrate. The structures also show movement of TM1 that opens the substrate binding site to the cytosol and mobility of loops between the TMs. MD simulations of the ASBT structure embedded in lipid bilayer suggests a stabilizing effect of the two sodium ions that are known to co-transport with the substrate. Binding study on pantoate analogs further demonstrate the specificity of pantoate as a substrate.

Overall, the structural, functional and computational studies are solid and rigorous, and the conclusions are well justified. In addition, the authors discussed the significance of the current study in a broader perspective relevant to recent structures of mammalian BASS members.

Reviewer #3 (Public Review):

The manuscript describes new ligand-bound structures within the larger bile acid sodium symporter family (BASS). This is the primary advance in the manuscript, together with molecular simulations describing how sodium and the bile acids sit in the structure when thermalized. What I think is fairly clear is that the ligands are more stable when the sodiums are present, with a marked reduction in RMSD over the course of repeated trajectories. This would be consistent with a transport model where sodium ions bind first, and then the bile acid binds, followed by a conformational change to another state where the ligands unbind.

While the authors mention that BASS transporters are thought to undergo an elevator transport mechanisms, this is not tested here. In my reading, all the crystal structures belong to the same conformational state in the overall transport cycle, and the simulations do not make an attempt to induce a transition on accessible simulation timescales. Instead, there is a morph between two inward facing states.

The focus is on what kinds of substrates bind to this transporter, interrogating this with isothermal calorimetry together with mutations. With a Kd in the micromolar range, even the best binder, pantoate, actually isn't a particularly tight binder in the pharmaceutical sense. For a transporter, tight binding is not actually desirable, since the substrate needs to be able to leave after conformational change places it in a position accessible to the other side.

The structure and simulation analysis falls into the mainstream of modern structural biology work.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript proposes an alternative method by SDS-PAGE calibration of Halo-Myo10 signals to quantify myosin molecules at specific subcellular locations, in this specific case filopodia, in epifluorescence datasets compared to the more laborious and troublesome single molecule approaches. Based on these preliminary estimates, the authors developed further their analysis and discussed different scenarios regarding myosin 10 working models to explain intracellular diffusion and targeting to filopodia.

Strengths:<br /> Overall, the paper is elegantly written and the data analysis is appropriately presented.

Weaknesses:<br /> While the methodology is intriguing in its descriptive potential and could be the beginning of an interesting story, a good portion of the paper is dedicated to the discussion of hypothetical working mechanisms to explain myosin diffusion, localization, and decoration of filopodial actin that is not accompanied by the mandatory gain/loss of function studies required to sustain these claims.

Reviewer #2 (Public Review):

Summary:<br /> The paper sought to determine the number of myosin 10 molecules per cell and localized to filopodia, where they are known to be involved in formation, transport within, and dynamics of these important actin-based protrusions. The authors used a novel method to determine the number of molecules per cell. First, they expressed HALO tagged Myo10 in U20S cells and generated cell lysates of a certain number of cells and detected Myo10 after SDS-PAGE, with fluorescence and a stained free method. They used a purified HALO tagged standard protein to generate a standard curve which allowed for determining Myo10 concentration in cell lysates and thus an estimate of the number of Myo10 molecules per cell. They also examined the fluorescence intensity in fixed cell images to determine the average fluorescence intensity per Myo10 molecule, which allowed the number of Myo10 molecules per region of the cell to be determined. They found a relatively small fraction of Myo10 (6%) localizes to filopodia. There are hundreds of Myo10 in each filopodia, which suggests some filopodia have more Myo10 than actin binding sites. Thus, there may be crowding of Myo10 at the tips, which could impact transport, the morphology at the tips, and dynamics of the protrusions themselves. Overall, the study forms the basis for a novel technique to estimate the number of molecules per cell and their localization to actin-based structures. The implications are broad also for being able to understand the role of myosins in actin protrusions, which is important for cancer metastasis and wound healing.

Strengths:<br /> The paper addresses an important fundamental biological question about how many molecular motors are localized to a specific cellular compartment and how that may relate to other aspects of the compartment such as the actin cytoskeleton and the membrane. The paper demonstrates a method of estimating the number of myosin molecules per cell using the fluorescently labeled HALO tag and SDS-PAGE analysis. There are several important conclusions from this work in that it estimates the number of Myo10 molecules localized to different regions of the filopodia and the minimum number required for filopodia formation. The authors also establish a correlation between number of Myo10 molecules filopodia localized and the number of filopodia in the cell. There is only a small % of Myo10 that tip localized relative to the total amount in the cell, suggesting Myo10 have to be activated to enter the filopodia compartment. The localization of Myo10 is log-normal, which suggest a clustering of Myo10 is a feature of this motor.

Weaknesses:<br /> One main critique of this work is that the Myo10 was overexpressed. Thus, the amount in the cell body compared to the filopodia is difficult to compare to physiological conditions. The amount in the filopodia was relatively small - 100s of molecules per filopodia so this result is still interesting regardless of the overexpression. However, the overexpression should be addressed in the limitations.<br /> The authors have not addressed the potential for variability in transfection efficiency. The authors could examine the average fluorescence intensity per cell and if similar this may address this concern.<br /> The SDS PAGE method of estimating the number of molecules is quite interesting. I really like this idea. However, I feel there are a few more things to consider. The fraction of HALO tag standard and Myo10 labeled with the HALO tagged ligand is not determined directly. It is suggested that since excess HALO tagged ligand was added we can assume nearly 100% labeling. If the HALO tag standard protein is purified it should be feasible to determine the fraction of HALO tagged standard that is labeled by examining the absorbance of the protein at 280 and fluorophore at its appropriate wavelength. The fraction of HALO tagged Myo10 labeled may be more challenging to determine, since it is in a cell lysate, but there may be some potential approaches (e.g. mass spec, HPLC).<br /> In Figure 1B, the stain free gel bands look relatively clean. The Myo10 is from cell lysates so it is surprising that there are not more bands. I am not surprised that the bands in the TMR fluorescence gel are clean, and I agree the fluorescence is the best way to quantitate.<br /> In Figure 3C, the number of Myo10 molecules needed to initiate a filopodium was estimated. I wonder if the authors could have looked at live cell movies to determine that these events started with a puncta of Myo10 at the edge of the cell, and then went on to form a filopodia that elongated from the cell. How was the number of Myo10 molecules that were involved in the initiation determined? Please clarify the assumptions in making this conclusion.<br /> It is stated in the discussion that the amount of Myo10 in the filopodia exceeds the number of actin binding sites. However, since Myo10 contains membrane binding motifs and has been shown to interact with the membrane it should be pointed that the excess Myo10 at the tips may be interacting with the membrane and not actin, which may prevent traffic jams.

Reviewer #3 (Public Review):

Summary:

The unconventional myosin Myo10 (aka myosin X) is essential for filopodia formation in a number of mammalian cells. There is a good deal of interest in its role in filopodia formation and function. The manuscript describes a careful, quantitative analysis of Myo10 molecules in U2OS cells, a widely used model for studying filopodia, how many are present in the cytosol versus filopodia and the distribution of filopodia and molecules along the cell edge. Rigorous quantification of Myo10 protein amounts in a cell and cellular compartment are critical for ultimately deciphering the cellular mechanism of Myo10 action as well as understand the molecular composition of a Myo10-generated filopodium.<br /> Consistent with what is seen in images of Myo10 localization in many papers, the vast majority of Myo10 is in the cell body with only a small percentage (appr 5%) present in filopodia puncta. Interestingly, Myo10 is not uniformly distributed along the cell edge, but rather it is unevenly localized along the cell edge with one region preferentially extending filopodia, presumably via localized activation of Myo10 motors. Calculation of total molecules present in puncta based on measurement of puncta size and measured Halo-Myo10 signal intensity shows that the concentration of motor present can vary from 3 - 225 uM. Based on an estimation of available actin binding sites, it is possible that Myo10 can be present in excess over these binding sites.

Strengths:

The work represents an important first step towards defining the molecular stoichiometry of filopodial tip proteins. The observed range of Myo10 molecules at the tip suggests that it can accommodate a fairly wide range of Myo10 motors. There is great value in studies such as this and the approach taken by the authors gives one good confidence that the numbers obtained are in the right range.

Weaknesses:

One caveat (see below) is that these numbers are obtained for overexpressing cells and the relevance to native levels of Myo10 in a cell is unclear.<br /> An interesting aspect of the work is quantification of the fraction of Myo10 molecules in the cytosol versus in filopodia tips showing that the vast majority of motors are inactive in the cytosol, as is seen in images of cells. This has implications for thinking about how cells maintain this large population in the off-state and what is the mechanism of motor activation. One question raised by this work is the distinction between cytosolic Myo10 and the population found at the 'cell edge' and the filopodia tip. The cortical population of Myo10 is partially activated, so to speak, as it is targeted to the cortex/membrane and presumably ready to go. Providing quantification of this population of motors, that one might think of as being in a waiting room, could provide additional insight into a potential step-by-step pathway where recruitment or binding to the cortical region/plasma membrane is not by itself sufficient for activation.

Specific comments -

1) It is not obvious whether the analysis of numbers of Myo10 molecules in a cell that is ectopically overexpressing Myo10 is relevant for wild type cells. It would appear to be a significant excess based on the total protein stained blot shown in Fig S1E where a prominent band the size of tagged Myo10 seen in the transfected sample is almost absent in the WT control lane. Ideally, and ultimately an important approach, would be to work with a cell line expressing endogenously tagged Myo10 via genome engineering. This can be complicated in transformed cells that often have chromosomal duplications.

However, even though there is an excess of Myo10 it would appear that activation is still under some type of control as the cytosolic pool is quite large and its localization to the cell edge is not uniform. But it is difficult to gauge whether the number of molecules in the filopodium is the same as would be seen in untransfected cells. Myo10 can readily walk up a filopodium and if excess numbers of this motor are activated they would accumulate in the tip in large numbers, possibly creating a bulge as and indeed it does appear that some tips are unusually large. Then how would that relate to the normal condition?

2) Measurements of the localization of Myo10 focuses in large part on 'Myo10 punctae'. While it seems reasonable to presume that these are filopodia tips, the authors should provide readers with a clear definition of a puncta. Is it only filopodia tips, which seems to be the case? Does it include initiation sites at the cell membrane that often appear as punctae?<br /> Along those lines, the position of dim punctae along the length of a filopodium is measured (Fig 3D). The findings suggest that a given filopodium can have more than one puncta which seems at odds if a puncta is a filopodia tip. How frequently is a filopodium with two puncta seen? It would be helpful if the authors provided an example image showing the dim puncta that are not present at the tip.

3) The concentration of actin available to Myo10 is calculated based on the deduction from Nagy et al (2010) that only 4/13 of the actin monomers in a helical turn are accessible to the Myo10 motor (discussion on pg 9; Fig S4). Subsequent work (Ropars et al, 2016) has shown that the heads of the antiparallel Myo10 dimer are flattened, but the neck is rather flexible, meaning that the motor can a variable reach (36 - 52 nm). Wouldn't this mean that more actin could be accessible to the Myo10 motor than is calculated here?

4) Quantification of numbers of Myo10 molecules in filopodial puncta (Fig 3C) leads the authors to conclude that 'only ten or fewer Myo10 molecules are necessary for filopodia initiation' (pg 7, top). While this is a reasonable based on the assumption that the formation of a puncta ultimately results from an initiation event, little is known about initiation events and without direct observation of coalescence of Myo10 at the cell edge that leads to formation of a filopodium, this seems rather speculative.

Reviewer #1 (Public Review):

Summary: Bloodstream stages of the parasitic protist, Trypanosoma brucei, exhibit very high rates of constitutive endocytosis, which is needed to recycle the surface coat of Variant Surface Glycoproteins (VSGs) and remove surface immune complexes. While many studies have shown that the endo-lysosomal systems of T. brucei BF stages contain canonical domains, as defined by classical Rab markers, it has remained unclear whether these protists have evolved additional adaptations/mechanisms for sustaining these very high rates of membrane transport and protein sorting. The authors have addressed this question by reconstructing the 3D ultrastructure and functional domains of the T. brucei BF endosome membrane system using advanced electron tomography and super-resolution microscopy approaches. Their studies reveal that, unusually, the BF endosome network comprises a continuous system of cisternae and tubules that contain overlapping functional subdomains. It is proposed that a continuous membrane system allows higher rates of protein cargo segregation, sorting and recycling than can otherwise occur when transport between compartments is mediated by membrane vesicles or other fusion events.

Strengths: The study is a technical tour-de-force using a combination of electron tomography, super-resolution/expansion microscopy, immune-EM of cryo-sections to define the 3D structures and connectivity of different endocytic compartments. The images are very clear and generally support the central conclusion that functionally distinct endocytic domains occur within a dynamic and continuous endosome network in BF stages.

Weaknesses: The authors suggest that this dynamic endocytic network may also fulfil many of the functions of the Golgi TGN and that the latter may be absent in these stages. Although plausible, this comment needs further experimental support. For example, have the authors attempted to localize canonical makers of the TGN (e.g. GRIP proteins) in T. brucei BF and/or shown that exocytic carriers bud directly from the endosomes?

Reviewer #2 (Public Review):

The authors suggest that the African trypanosome endomembrane system has unusual organisation, in that the entire system is a single reticulated structure. It is not clear if this is thought to extend to the lysosome or MVB. There is also a suggestion that this unusual morphology serves as a trans-(post)Golgi network rather than the more canonical arrangement.

The work is based around very high-quality light and electron microscopy, as well as utilising several marker proteins, Rab5A, 11 and 7. These are deemed as markers for early endosomes, recycling endosomes and late or pre-lysosomes. The images are mostly of high quality but some inconsistencies in the interpretation, appearance of structures and some rather sweeping assumptions make this less easy to accept. Two perhaps major issues are claims to label the entire endosomal apparatus with a single marker protein, which is hard to accept as certainly this reviewer does not really even know where the limits to the endosomal network reside and where these interface with other structures. There are several additional compartments that have been defined by Rob proteins as well, and which are not even mentioned. Overall I am unconvinced that the authors have demonstrated the main things they claim.

The approaches taken are state-of-the-art but not novel, and because of the difficulty in fully addressing the central tenet, I am not sure how much of an impact this will have beyond the trypanosome field. For certain this is limited to workers in the direct area and is not a generalisable finding.

Reviewer #3 (Public Review):

Summary:<br /> As clearly highlighted by the authors, a key plank in the ability of trypanosomes to evade the mammalian host's immune system is its high rate of endocytosis. This rapid turnover of its surface enables the trypanosome to 'clean' its surface removing antibodies and other immune effectors that are subsequently degraded. The high rate of endocytosis is likely reflected in the organisation and layout of the endosomal system in these parasites. Here, Link et al., sought to address this question using a range of light and three-dimensional electron microscopy approaches to define the endosomal organisation in this parasite.

Before this study, the vast majority of our information about the make-up of the trypanosome endosomal system was from thin-section electron microscopy and immunofluorescence studies, which did not provide the necessary resolution and 3D information to address this issue. Therefore, it was not known how the different structures observed by EM were related. Link et al., have taken advantage of the advances in technology and used an impressive combination of approaches at the LM and EM level to study the endosomal system in these parasites. This innovative combination has now shown the interconnected-ness of this network and demonstrated that there are no 'classical' compartments within the endosomal system, with instead different regions of the network enriched in different protein markers (Rab5a, Rab7, Rab11).

Strengths:<br /> This is a generally well-written and clear manuscript, with the data well-presented supporting the majority of the conclusions of the authors. The authors use an impressive range of approaches to address the organisation of the endosomal system and the development of these methods for use in trypanosomes will be of use to the wider parasitology community.

I appreciate their inclusion of how they used a range of different light microscopy approaches even though for instance the dSTORM approach did not turn out to be as effective as hoped. The authors have clearly demonstrated that trypanosomes have a large interconnected endosomal network, without defined compartments and instead show enrichment for specific Rabs within this network.

Weaknesses:<br /> My concerns are:

i) there is no evidence for functional compartmentalisation. The classical markers of different endosomal compartments do not fully overlap but there is no evidence to show a region enriched in one or other of these proteins has that specific function. The authors should temper their conclusions about this point.

ii) the quality of the electron microscopy work is very high but there is a general lack of numbers. For example, how many tomograms were examined? How often were fenestrated sheets seen? Can the authors provide more information about how frequent these observations were?

iii) the EM work always focussed on cells which had been processed before fixing. Now, I understand this was important to enable tracers to be used. However, given the dynamic nature of the system these processing steps and feeding experiments may have affected the endosomal organisation. Given their knowledge of the system now, the authors should fix some cells directly in culture to observe whether the organisation of the endosome aligns with their conclusions here.

iv) the discussion needs to be revamped. At the moment it is just another run through of the results and does not take an overview of the results presenting an integrated view. Moreover, it contains reference to data that was not presented in the results.

Reviewer #1 (Public Review):

Summary: Planar cell polarity core proteins Frizzled (Fz)/Dishevelled (Dvl) and Van Gogh-like (Vangl)/Prickle (Pk) are localized on opposite sides of the cell and engage in reciprocal repression to modulate cellular polarity within the plane of static epithelium. In this interesting manuscript, the authors explore how the anterior core proteins (Vangl/Pk) inhibit the posterior core protein (Dvl). The authors propose that Pk assists Vangl2 in sequestering both Dvl2 and Ror2, while Ror2 is essential for Dvl to transition from Vangl to Fz in response to non-canonical Wnt signaling. There are several points that affect the strength of the author's conclusions.

Strengths: The strengths of the manuscript are in the very interesting and new concept for a model of how non-canonical Wnt induces Dvl to transition from Vangl to Fz. Prickle and Vangl2 are proposed to play an opposing role to suppress Dvl activity during convergent extension movements, whereas Ror antagonizes Vangl and may be required for the transition.

Weaknesses: The weaknesses are in the clarity and resolution of the data that forms the basis of the model. In addition to whole embryo morphology that is used as evidence for convergent extension (CE) defects, two forms of data are presented, co-expression and IP, as well as a strong reliance on IF of exogenously expressed proteins. Thus, it is critical that both forms of evidence be very strong and clear, and this is where there are deficiencies; 1) For vast majority of experiments general morphology and LWR was used as evidence of effects on convergent extension movements rather than Keller explants or actual cell movements in the embryo. 2) The study would benefit from high or super resolution microscopy, since in many cases the differences in protein localization are not very pronounced. 3) The IP and Western analysis data often show subtle differences, and not apparent in some cases. 4) It is not clear how many biological repeats were performed or how and whether statistical analyses were performed.

Reviewer #2 (Public Review):

The authors use Xenopus embryos to study feedback interactions between the planar cell polarity (PCP) proteins in the context of convergence and extension. They show that binding of the cytoplasmic polarity protein Pk2 to Vangl2 is needed for them to synergistically suppress defects in convergence and extension caused by Dvl overexpression. They then examine protein localizations in animal cap cells, and show that Wnt11-induced accumulation of Fzd7, Ror2 and Dvl into plasma membrane patches is disrupted by the functional Vangl2/Pk complex. This disperses Fzd and causes its endocytosis, while Dvl remains at the plasma membrane.

This is a potentially interesting paper, showing mechanisms by which Vangl2/Pk can functionally antagonize Fzd/Dvl during planar cell polarity.

The protein localization experiments in animal cap assays are for the most part convincing, but with the caveat that the authors assume that the proteins are acting within the same cell. As Fzd and Vangl2 are thought to localize to opposite cell ends in many contexts, can the authors be sure that the effects they observe are not due to trans interactions?

The authors propose a model whereby Vangl2 acts as an adaptor between Dvl and Ror, to first prevent ectopic activation of signaling, and then to relay Dvl to Fzd upon Wnt stimulation. This is based on the observation that Ror2 can be co-IPed with Vangl2 but not Dvl; and secondly that the distribution of Ror2 in membrane patches after Wnt11 stimulation is broader than that of Fzd7/Dvl, while Vangl2 localizes to the edges of these patches. The data for both these points is not wholly convincing. The co-IP of Ror2 and Vangl2 is very weak, and the input of Dvl into the same experiment is very low, so any direct interaction could have been missed. Secondly, the broader distribution of Ror2 in membrane patches is very subtle, and further analysis would be needed to firm up this conclusion.

A final caveat to these experiments is that in the animal cap assays, loss of function and gain of function both cause convergence and extension defects, so any genetic interactions need to be treated with caution i.e. two injected factors enhancing a phenotype does not imply they act in the same direction in a pathway, in particular as there are both cis/trans and positive/negative feedbacks between the PCP proteins.

Joint Public Review:

This paper's strengths are the interesting analysis of TLR signaling in hair follicle stem cell activation and the striking phenotype of the TLR2 cKO mice (but note below). The functional interrogation parts using HFSC-specific TLR2 genetic deletion are solid, and an endogenous regulator, CEP, is identified. The experiments reported in this manuscript are well-designed and presented. The authors provided extensive evidence supporting the roles of TLR2 signaling in regulating hair follicle stem cell functions. Importantly, the findings from this paper may have sustained impacts on our understanding of the roles of innate immunity in regulating tissue regeneration in the absence of inflammation.

The main evidence for the mechanistic analysis is based on fluorescence using immunohistochemistry, and here the expression analysis is not convincing. In addition, additional assays beyond immunolandscaping are needed to confirm the findings. The reviewers felt that your data substantiating the mechanism of interaction between TLR2 and BMP pathway needs bolstering.

Reviewer #1 (Public Review):

Authors performed a meta-analysis of GC concentrations and metabolic rates in birds and mammals. They found close associations for all studies showing a positive association between these two traits. As GCs have been viewed with close links to "stress," authors suggest that this overlooks the importance of metabolism and perhaps GC variation does not relate to "stress" per se but an increase in metabolism instead.

This is an important meta-analysis, as most researchers acknowledge the link between GCs and metabolism, metabolism is often overlooked in studies. The field of conservation physiology is especially focused on GCs being a "stress" hormone, which overlooks the importance of GCs in mediating energy balance, i.e., an animal that has high GC concentrations may not be doing that poorly compared to an animal with low GC concentrations, it might just be expending more energy, e.g., caring for young. The results, with overwhelming directionality and strong effect sizes, support the link for a positive association with these two variables.

My main concern lies in that most of the studies come from a few labs, therefore there may be limited data to test this relationship. I would include lab as a random effect to see how strong this effect might be. Furthermore, I would like to see a test of the directionality of the two variables. Authors suggest that changes in metabolism affect GC levels but likely changes in GC levels would affect metabolism. Why not look into studies that have altered GC levels experimentally and see the effect on metabolism? Based on the close link, authors suggest that GCs may not play a role outside of "stress" beyond the stressor's effect on metabolic rate. However, if they were to investigate manipulations of GCs on metabolic rate, the link may or may not be there, which would be interesting to look at. I firmly believe that GCs are tightly linked to metabolism; however, I also think that GCs have a range of effects outside of metabolism as well, depending on the course and strength of the stressor.

This work helps in the thinking that GCs are not the same as a "stress" hormone or labelling hormones with only one function. As hormones are naturally pleiotropic, the view of any one hormone being X is overly simplistic.

Reviewer #2 (Public Review):

Where this study is interesting is that the authors do a meta-analysis of studies in which metabolic rate was experimentally manipulated and both this rate and glucocorticoid levels were simultaneously measured. Unsurprisingly, there are relatively few such studies and many are from a single lab. More studies are needed. While the results of the analysis are compelling, they are not surprising. That said, this work is important.

Reviewer #1 (Public Review):

Summary: This work by Zhang et al. provides new strategies to improve the efficiency of precise Prime Editing (PE) in zebrafish embryos. The authors test how two simple changes impact PE efficiency: first, by refolding the pegRNA before complexing with Cas9 nickase-reverse transcriptase PE2, and second, by introducing mutations to the pegRNA intended to reduce its autoinhibitory activity by disrupting complementarity between the 5' spacer sequence and the 3' PBS-RTT (Primer Binding Site-Reverse Transcriptase Template).

Strengths: The authors tested multiple loci in the zebrafish genome to determine how pegRNA refolding and point mutations in the RTT would impact overall mutagenesis efficiency and precise PE at the target sites. The impact on efficiency was tested with three types of pegRNAs designed to introduce base substitutions, insertions or deletions. Next-generation sequencing of amplicons from pooled, injected embryos provided robust measurement of mutagenesis and editing. Insertion and deletion pegRNAs were overall more efficient than substitution pegRNAs, which may be useful information in considering experimental design strategy for introducing a specific variant. There is potential for further improvement by combining the authors' methods with previously published strategies to improve pegRNAs through design and chemical modification.

Weaknesses: The observed increases in the frequency of precise PE were relatively minor and inconsistent across the multiple pegRNAs tested. The substitution pegRNAs showed very low precise PE, at levels less than 1 percent, therefore the fold changes reported were still representative of 10 percent or less of overall edits. Overall mutagenesis frequency, as measured by indel formation, increased along with increased precise PE. The approach produces highly genetically mosaic embryos, therefore the utility for transient studies in injected zebrafish embryos is unclear. Data on improved germline transmission frequency of precise PE alleles would strengthen the study and be of wide interest in the zebrafish community.

Reviewer #2 (Public Review):

Prime editing is a major gene editing technique because it allows for the introduction of all possible substitutions, as well as small insertions and deletions, without causing double strand breaks. However, its efficiency is often limited. In a previous study, the authors showed that prime editing could be performed in zebrafish using recombinant PE2 protein and pegRNAs generated by in vitro transcription, but at many of the sites tested, gene editing efficiency remained relatively low.

In this current paper, the authors find that when pegRNAs were combined with Cas9, many induced much less indels than their corresponding guide RNAs and propose that this is due to the complementarity between the 5' and 3' regions of pegRNAs. Two methods aiming to reduce the resulting circularization of pegRNAs were next shown to increase the efficiency of prime editing: a slow refolding protocol (which was previously shown to be useful for inefficient guide RNAs), and the introduction of a substitution at position +2 of the reverse transcriptase template sequence. The data obtained and analyzed is solid and convincing.

These methods are remarkably straightforward and proved beneficial for most of the pegRNAs tested. Consequently, they represent important advances for the prime editing technique.

It should be noted, however, that despite these advances, prime editing activity remained relatively low for a significant proportion of pegRNAs tested (with less than 2% sequencing reads exhibiting the expected sequence change). This shows that further improvements are still needed for this important gene editing technique.

Reviewer #3 (Public Review):

In this study, Weiting Zhang et al., improved the editing efficiency of prime editor by reducing misfolded pegRNA interactions, and the improvement of efficiency for prime editor helped to expand its application range. It is a research paper on technology improvement. This study is somewhat innovative.

Reviewer #1 (Public Review):

Summary:<br /> The preprint by Laganowsky and co-workers describes the use of mutant cycles to dissect the thermodynamic profile of specific lipid recognition by the ABC transporter MsbA. The authors use native mass spectrometry with a variable temperature source to monitor lipid binding to the native protein dimer solubilized in detergent. Analysis of the peak intensities (that is, relative abundance) of 1-3 bound lipids as a function of solution temperature and lipid concentration yields temperature-dependent Kds. The authors use these to then generate van't Hoff plots, from which they calculate the enthalpy and entropy contributions to binding of one, two, and in some cases, three lipids to MsbA.<br /> The authors then employ mutant cycles, in which basic residues involved in headgroup binding are mutated to alanine. By comparing the thermodynamic signatures of single and double (and in one instance triple) mutants, they aim to identify cooperativity between the different positions. They furthermore use inward and outward locking conditions which should control access to the different binding sites determined previously.<br /> The main conclusion is that lipid binding to MsbA is driven mainly by energetically favorable entropy increase upon binding, which stems from the release of ordered water molecules that normally coordinate the basic residues, which helps to overcome the enthalpic barrier of lipid binding. The authors also report an increase in lipid binding at higher temperatures which they attribute to a non-uniform heat capacity of the protein. Although they find that most residue pairs display some degree of cooperativity, particularly between the inner and outer lipid binding sites, they do not provide a structural interpretation of these results.

Strengths:<br /> The use of double mutant cycles and mass spectrometry to dissect lipid binding is novel and interesting. For example, the observation that mutating a basic residue in the inner and one in the outer binding site abolishes lipid binding to a greater extent than the individual mutations is highly informative even without having to break it down into thermodynamic terms (see "weaknesses" section). In this sense, the method and data reported here opens new avenues for the structure/activity relationship of MsbA. The "mutant cycle" approach is in principle widely applicable to other membrane proteins with complex lipid interactions.

Weaknesses:<br /> The use of double mutant cycles to dissect binding energies is well-established, and has, as the authors point out, been employed in combination with mass spectrometry to study protein-protein interactions. Its application to extract thermodynamic parameters is robust in cases where a single binding event is monitored, e.g. the formation of a complex with well-defined stoichiometry, where dissociation constants can be determined with high confidence. It is, however, complicated significantly by the fact that for MsbA-lipid interactions, we are not looking at a single binding event, but a stochastic distribution of lipids across different sites. Even if the protein is locked in a specific conformation, the observation of a single lipid adduct does not guarantee that the one lipid is always bound to a specific site. In some of the complexes detected by MS, the lipid is likely bound somewhere else. Lipid binding Kds from mass spectrometry, although helpful in some instances as a proxy for global binding affinities, should therefore be taken with a grain of salt.

The authors analyze the difference in binding upon mutating binding sites (ddG etc). Here, another complicating factor comes into play, the fact that mutation of a binding site (which the authors show reduces lipid binding) may instead allow the lipid to bind to a lower-affinity site elsewhere. Unfortunately, the authors do not specify the protein concentration, but assuming it is in the single-digit micromolar range, as common for native MS experiments, lipid and protein concentrations are almost equal for most of the data points, resulting in competition between binding sites for free lipids. As a rule of thumb, for Kd measurements, the concentration of the constant component, the protein, should be far below the Kd, to avoid working in the "titration" regime rather than the "binding" regime (see Jarmoskaite et al, eLife 2020). I cannot determine whether this is the case here. The way I understand the double mutant cycle approach, reliable Kd measurements are required to accurately determine dH and TdS, so I would encourage the authors to confirm their Kd values using complementary methods before in-depth interpretations of the thermodynamic components.

It is somewhat counterintuitive that for many double mutants, and the triple mutant, the entropic component becomes more favorable compared to the WT protein. If the increase in entropy upon lipid binding comes from the release of ordered water molecules around the basic residues (a reasonable assumption) why does this apply even more in proteins where several basic residues have been changed to alanine, which coordinate far fewer water molecules?

The authors could devote more attention to the fact that they use detergent micelles as a vehicle for lipid binding studies. To a limited extent, detergents compete with lipids for binding, and are present in extreme excess over the lipid. The micelle likely changes its behavior in response to temperature changes. For example, the packing around the protein loosens up upon heating, which may increase the chance for lipids to bind. In this case, the increase in binding at higher temperatures may not be related to a change in heat capacity. This question could be addressed by MD simulations, if it's not already in the literature.

Reviewer #2 (Public Review):

Summary:<br /> This is a solid study that dissects the thermodynamics of lipopolysaccharide (LPS) transporter MsbA and LPS. Native ESI-MS and the novel strategies developed by the authors were employed to quantify the affinities of LPS-MsbA interactions and its temperature dependence. Here, the equilibrium of lipid-protein interactions occurs in the micellar phase. The double-/triple-mutant cycle analysis and van't Hoff analysis allowed a full thermodynamic description of the lipid-protein interactions and the analysis of thermodynamic coupling between LPS binding sites. The most notable result would be that LPS-MsbA interaction is largely driven by entropy involving the negative heat capacity, a signature of the solvent reorganization effect (here authors attribute the solvent effect to "water" reorganization). The entropy driven lipid binding has been previously reported by the same authors for Kir1,2-PIP2 interactions.

Strengths:

1) This is overall a very thorough and rigorous study providing the detailed thermodynamic principles of LPS-MsbA interaction.

2) The double and triple-mutant cycle approaches are newly applied to lipid-protein interactions, enabling detailed thermodynamics between LPS binding sites.

3) The entropy-driven protein-lipid interaction is surprising. The binding seems to be mainly mediated by the electrostatic interaction between the positively charged residues on the protein and the negatively charged or polar headgroup of LPS, which could be thought of as "enthalpic" (making of a strong bond relative to that with solvent).

Weaknesses:

1. This study is a good contribution to the field, but it was difficult to find novel biological insights or methodological novelty from this study.

1a) Thermodynamic analysis of lipid-protein interactions, an example of entropy-driven lipid-protein interactions, and the cooperativity between lipid binding sites have been reported by the author's group. Also, the cooperativity between binding sites in general have been reported from numerous studies of biomolecular interactions.

1b) It is not clear how this study provides new insights into the understanding of LPS transport mechanisms. Probably, authors could strengthen the Discussion by providing biological insights-how the residue coupling.

2) One to three LPS molecules bind to MsbA, but it is unclear whether bound KDL occupies inner or outer cavities, or both and how a specific mutation affects the affinity of specific LPS (i.e., to inner or to outer cavities). Based on the known structures, the maximal number of LPS is three. It is possible that the inner and outer cavities have different LPS affinities. Also, there can be multiple one-LPS-bound states, two-LPS-bound states if LPS strictly binds to the binding sites indicated by the structures. This aspect is beyond the scope of this study and difficult to address, but without this information, it seems hard to tell what is going on in the system.

3) If a single mutation is introduced to the inner cavity, its effect will be "doubled" because the inner cavity is shared by two identical subunits. This effect needs to be clarified in the result section.

4) In the result section, "Mutant cycle analysis of KDL binding to vanadate-trapped MsbA.":

4a) It seems necessary to show the mass spectra for Msb-ADP-vanadate complex as well as its lipid bound forms.

4b) The rationale of this section (i.e., what mechanistic insights can be obtained from this study) is unclear. For example, it is not sure what meaningful information can be obtained from a single type (ADP/vanadate) of the bound state regarding the ATP-driven function of MsbA.

Reviewer #3 (Public Review):

Summary:<br /> In this paper presented by Liu et al, native MS on the lipid A transporter MsbA was used to obtain thermodynamic insight into protein-lipid interactions. By performing the analyses at different lipid A concentrations and temperatures, dissociation constants for 2-3 lipid A binding sites were determined, as well as enthalpies were calculated using non-linear van't Hoff fitting. Changes in free Gibb's energies were then calculated based on the determined dissociation constants, and together with the enthalpy values obtained via van' t Hoff analysis, the entropic contribution to lipid binding (DeltaS*T) was indirectly determined.

Strengths:<br /> This is an extensive high quality native MS dataset that provides unique opportunities to gain insights into the thermodynamic parameters underlying lipid A binding. In addition, it provides coupling energies between mutations introduced into MsbA, that are implicated in lipid A binding.

Weaknesses:<br /> The data all rely on the accuracy of determining KD values for lipid binding to MsbA. For the weaker binding sites, the range of lipid concentrations probed were in fact too low to generate highly accurate data. Another weakness is a lack of clear evidence, which KD values belong to which of the possible lipid A binding sites.

Reviewer #1 (Public Review):

Summary:<br /> The biogenesis of outer membrane proteins (OMPs) into the outer membranes of Gram-negative bacteria is still not fully understood, particularly substrate recognition and insertion by beta-assembly machinery (BAM). In the studies, the authors present their studies that in addition to recognition by the last strand of an OMP, sometimes referred to as the beta-signal, an additional signal upstream of the last strand is also important for OMP biogenesis.

Strengths:<br /> 1. Overall the manuscript is well organized and written, and addresses an important question in the field. The idea that BAM recognizes multiple signals on OMPs has been presented previously, however, it was not fully tested.

2. The authors here re-address this idea and propose that it is a more general mechanism used by BAM for OMP biogenesis.

3. The notion that additional signals assist in biogenesis is an important concept that indeed needs fully tested in OMP biogenesis.

4. A significant study was performed with extensive experiments reported in an attempt to address this important question in the field.

5. The identification of important crosslinks and regions of substrates and Bam proteins that interact during biogenesis is an important contribution that gives clues to the path substrates take en route to the membrane.

Weaknesses:

Major critiques (in no particular order):

1. The title indicates 'simultaneous recognition', however no experiments were presented that test the order of interactions during OMP biogenesis.

2. Aspects of the study focus on the peptides that appear to inhibit OmpC assembly, but should also include an analysis of the peptides that do not to determine this the motif(s) present still or not.

3. The b-signal is known to form a b-strand, therefore it is unclear why the authors did not choose to chop OmpC up according to its strands, rather than by a fixed peptide size. What was the rationale for how the peptide lengths were chosen since many of them partially overlap known strands, and only partially (2 residues) overlap each other? It may not be too surprising that most of the inhibitory peptides consist of full strands (#4, 10, 21, 23).

4. It would be good to have an idea of the propensity of the chosen peptides to form b-stands and participate in b-augmentation. We know from previous studies with darobactin and other peptides that they can inhibit OMP assembly by competing with substrates.

5. The recognition motifs that the authors present span up to 9 residues which would suggest a relatively large binding surface, however, the structures of these regions are not large enough to accommodate these large peptides.

6. The authors highlight that the sequence motifs are common among the inhibiting peptides, but do not test if this is a necessary motif to mediate the interactions. It would have been good to see if a library of non-OMP related peptides that match this motif could also inhibit or not.

7. In the studies that disrupt the motifs by mutagenesis, an effect was observed and attributed to disruption of the interaction of the 'internal signal'. However, the literature is filled with point mutations in OMPs that disrupt biogenesis, particular those within the membrane region. F280, Y286, V359, and Y365 are all residues that are in the membrane region that point into the membrane. Therefore, more work is needed to confirm that these mutations are in parts of a recognition motif rather than on the residues that are disrupting stability/assembly into the membrane.

8. The title of Figure 3 indicates that disrupting the internal signal motif disrupts OMP assembly, however, the point mutations did not seem to have any effect. Only when both 280 and 286 were mutated was an effect observed. And even then, the trimer appeared to form just fine, albeit at reduced levels, indicating assembly is just fine, rather the rate of biogenesis is being affected.

9. In Figure 4, the authors attempt to quantify their blots. However, this seems to be a difficult task given the lack of quality of the blots and the spread of the intended signals, particularly of the 'int' bands. However, the more disturbing trend is the obvious reduction in signal from the post-urea treatment, even for the WT samples. The authors are using urea washes to indicate removal of only stalled substrates. However a reduction of signal is also observed for the WT. The authors should quantify this blot as well, but it is clear visually that both WT and the mutant have obvious reductions in the observable signals. Further, this data seems to conflict with Fig 3D where no noticeable difference in OmpC assembly was observed between WT and Y286A, why is this the case?

10. The pull down assays with BamA and BamD should include a no protein control at the least to confirm there is no non-specific binding to the resin. Also, no detergent was mentioned as part of the pull downs that contained BamA or OmpC, nor was it detailed if OmpC was urea solubilized.

11. The neutron reflectometry experiments are not convincing primarily due to the lack controls to confirm a consistent uniform bilayer is being formed and even if so, uniform orientations of the BamA molecules across the surface. Further, no controls were performed with BamD alone, or with OmpC alone, and it is hard to understand how the method can discriminate between an actual BamA/BamD complex versus BamA and BamD individually being located at the membrane surface without forming an actual complex. Previous studies have reported difficulty in preparing a complex with BamA and BamD from purified components. Additionally, little signal differences were observed for the addition of OmpC. However, an elongated unfolded polypeptide that is nearly 400 residues long would be expected to produce a large distinct signal given that only the C-terminal portion is supposedly anchored to BAM, while the rest would be extended out above the surface. The depiction in Figure 5D is quite misleading when viewing the full structures on the same scales with one another.

12. In the crosslinking studies, the authors show 17 crosslinking sites (43% of all tested) on BamD crosslinked with OmpC. Given that the authors are presenting specific interactions between the two proteins, this is worrisome as the crosslinks were found across the entire surface of BamD. How do the authors explain this? Are all these specific or non-specific?

13. The study in Figure 6 focuses on defined regions within the OmpC sequence, but a more broad range is necessary to demonstrate specificity to these regions vs binding to other regions of the sequence as well. If the authors wish to demonstrate a specific interaction to this motif, they need to show no binding to other regions.

14. The levels of the crosslinks are barely detectable via western blot analysis. If the interactions between the two surfaces are required, why are the levels for most of the blots so low?

15. Figure 7 indicates that two regions of BamD promote OMP orientation and assembly, however, none of the experiments appears to measure OMP orientation? Also, one common observation from panel F was that not only was the trimer reduced, but also the monomer. But even then, still a percentage of the trimer is formed, not a complete loss.

16. The experiment in Fig 7B would be more conclusive if it was repeated with both the Y62A and R197A mutants and a double mutant. These controls would also help resolve any effect from crowding that may also promote the crosslinks. Further, the mutation of R197 is an odd choice given that this residue has been studied previously and was found to mediate a salt bridge with BamA. How was this resolved by the authors in choosing this site since it was not one of the original crosslinking sites?

17. As demonstrated by the authors in Fig 8, the mutations in BamD lead to reduction in OMP levels for more than just OmpC and issues with the membrane are clearly observable with Y62A, although not with R197A in the presence of VCN. The authors should also test with rifampicin which is smaller and would monitor even more subtle issues with the membrane. Oddly, no growth was observed for the Vec control in the lower concentration of VCN, but was near WT levels for 3 times VCN, how is this explained?

18. While Fig 8I indeed shows diminished levels for FY as stated, little difference was observed for the trimer for the other mutants compared to WT, although differences were observed for the dimer. Interestingly, the VY mutant has nearly WT levels of dimer. What do the authors postulate is going on here with the dimer to trimer transition? How do the levels of monomer compare, which is not shown?

19. In the discussion, the authors indicate they have '...defined an internal signal for OMP assembly', however, their study is limited and only investigates a specific region of OmpC. More is needed to definitively say this for even OmpC, and even more so to indicate this is a general feature for all OMPs.

20. In the proposed model in Fig 9, it is hard to conceive how 5 strands will form along BamD given the limited surface area and tight space beneath BAM. More concerning is that the two proposal interaction sites on BamD, Y62 and R197, are on opposite sides of the BamD structure, not along the same interface, which makes this model even more unlikely. As evidence against this model, in Figure 9E, the two indicates sites of BamD are not even in close proximity of the modeled substrate strands.

Reviewer #2 (Public Review):

Previously, using bioinformatics study, authors have identified potential sequence motifs that are common to a large subset of beta-barrel outer membrane proteins in gram negative bacteria. Interestingly, in that study, some of those motifs are located in the internal strands of barrels (not near the termini), in addition to the well-known "beta-signal" motif in the C-terminal region.

Here, the authors carried out rigorous biochemical, biophysical, and genetic studies to prove that the newly identified internal motifs are critical to the assembly of outer membrane proteins and the interaction with the BAM complex. The author's approaches are rigorous and comprehensive, whose results reasonably well support the conclusions. While overall enthusiastic, I have some scientific concerns with the rationale of the neutron refractory study, and the distinction between "the intrinsic impairment of the barrel" vs "the impairment of interaction with BAM" that the internal signal may play a role in. I hope that the authors will be able to address this.

Strengths:

1. It is impressive that the authors took multi-faceted approaches using the assays on reconstituted, cell-based, and population-level (growth) systems.

2. Assessing the role of the internal motifs in the assembly of model OMPs in the absence and presence of BAM machinery was a nice approach for a precise definition of the role.

Weaknesses:

1. The result section employing the neutron refractory (NR) needs to be clarified and strengthened in the main text (from line 226). In the current form, the NR result seems not so convincing.

What is the rationale of the approach using NR?<br /> What is the molecular event (readout) that the method detects?<br /> What are "R"-y axis and "Q"-x axis and their physical meanings (Fig. 5b)?<br /> How are the "layers" defined from the plot (Fig. 5b)?<br /> What are the meanings of "thickness" and "roughness" (Fig. 5c)?<br /> What are the meanings of the increases in thickness and roughness?<br /> What does "SLD" stand for?

2. In the result section, "The internal signal is necessary for insertion step of assembly into OM"

This section presents an important result that the internal beta-signal is critical to the intrinsic propensity of barrel formation, distinct from the recognition by BAM complex. However, this point is not elaborated in this section. For example, what is the role of these critical residues in the barrel structure formation? That is, are they involved in any special tertiary contacts in the structure or in membrane anchoring of the nascent polypeptide chains?

Reviewer #1 (Public Review):

Summary:<br /> The authors utilize fluid-structure interaction analyses to simulation fluid flow within and around the Cambrian cnidarian Quadrapyrgites to reconstruct feeding/respiration dynamics. Based on vorticity and velocity flow patterns, the authors suggest that the polyp expansion and contraction ultimately develop vortices around the organism that are like what modern jellyfish employ for movement and feeding. Lastly, the authors suggest that this behavior is likely a prerequisite transitional form to swimming medusae.

Strengths:<br /> While fluid-structure-interaction analyses are common in engineering, physics, and biomedical fields, they are underutilized in the biological and paleobiological sciences. Zhang et al. provide a strong approach to integrating active feeding dynamics into fluid flow simulations of ancient life. Based on their data, it is entirely likely the described vortices would have been produced by benthic cnidarians feeding/respiring under similar mechanisms. However, some of the broader conclusions require additional justification.

Weaknesses:

1. The claim that olivooid-type feeding was most likely a prerequisite transitional form to jet-propelled swimming needs much more support or needs to be tailored to olivooids. This suggests that such behavior is absent (or must be convergent) before olivooids, which is at odds with the increasing quantities of pelagic life (whose modes of swimming are admittedly unconstrained) documented from Cambrian and Neoproterozoic deposits. Even among just medusozoans, ancestral state reconstruction suggests that they would have been swimming during the Neoproterozoic (Kayal et al., 2018; BMC Evolutionary Biology) with no knowledge of the mechanics due to absent preservation.<br /> 2. While the lack of ambient flow made these simulations computationally easier, these organisms likely did not live in stagnant waters even within the benthic boundary layer. The absence of ambient unidirectional laminar current or oscillating current (such as would be found naturally) biases the results.<br /> 3. There is no explanation for how this work could be a breakthrough in simulation gregarious feeding as is stated in the manuscript.

Despite these weaknesses the authors dynamic fluid simulations convincingly reconstruct the feeding/respiration dynamics of the Cambrian Quadrapyrgites, though the large claims of transitionary stages for this behavior are not adequately justified. Regardless, the approach the authors use will be informative for future studies attempting to simulate similar feeding and respiration dynamics.

Reviewer #2 (Public Review):

Summary: The authors seek to elucidate the early evolution of cnidarians through computer modeling of fluid flow in the oral region of very small, putative medusozoan polyps. They propose that the evolutionary advent of the free-swimming medusoid life stage was preceded by a sessile benthic life stage equipped with circular muscles that originally functioned to facilitate feeding and that later became co-opted for locomotion through jet propulsion.

Strengths: Assumptions of the modeling exercise laid out clearly; interpretations of the results of the model runs in terms of functional morphology plausible. An intriguing investigation that should stimulate further discussion and research.

Weaknesses: Speculation on the origin of the medusoid life stage in cnidarians heavily dependent on prior assumptions concerning the soft part anatomy and material properties of the skeleton of the modeled fossil organism that may be open to alternative interpretations.

Reviewer #1 (Public Review):

Precision guided sterile insect technology (pgSIT) is a means of mosquito vector control that aims to simultaneously kill females while generating sterile males for field release. These sterile males are expected to mate with 'wild' females resulting in very few eggs being laid or low hatching rates. Repeated releases are expected to result in the suppression of the mosquito population. This method avoids cumbersome sex-sorting while generating the sterile males. Importantly, until release, the two genetic elements that bring about female lethality and male sterility - the Cas9 and the gRNA carrying mosquitoes - are maintained as separate lines. They are crossed only prior to release, and therefore, this approach is considered to be more safe than gene drives.

The authors had made a version of this pgSIT in their 2021 paper where they targeted *β-Tubulin 85D*, which is only expressed in the male testes and its loss-of-function results in male sterility. In that pgSIT, they did not have female lethality, but generated flightless females by simultaneously targeted *myosin heavy chain,* which is expressed only in the female wings. Here the authors argue, that the survival of females is not ideal, and so modify their 2021 approach to achieve female lethality/sterility.

To do this, they target two genes - the female specific isoform of Dsx and intersex. They use multiple gRNAs against these genes and validate their ability to cause female lethality/sterility. Having verified that these do indeed affect female fertility, they combine gRNAs against Dsx and ix to generate female lethality/sterility and use *β-Tubulin 85D* to generate male sterility (previously validated). When these gRNA mosquitoes are crossed to Cas9 and the progeny crossed to WT (the set-up for pgSIT), they find that very few eggs are laid, larval death is high, and what emerges are males or intersex progeny that are sterile.

As this is the requirement for pgSIT, the authors then test if it is able to induce population suppression. To do this, they conduct cage trials and find that only when they use 20:1 or 40:1 ratio of pgSIT:WT cages, does the population crash in 4-5 generations. They model this pgSIT's ability to suppress a population in the wild. Unfortunately, I was not able to assess what parameters from their pgSIT were used in the model and therefore the predicted efficacy of their pgSIT, (though the range of 0-.1 is not great, given that the assessment is between 0-0.15).

Finally, they also develop a SENSR with a rapid fluorescence read-out for detecting the transgene in the field. They show that this sensor is specific and sensitive, detecting low copy numbers of the transgene. This would be important for monitoring any release.

Overall, the data are clear and well presented. The manuscript is well written (albeit likely dense for the uninitiated!). I had concerns about the efficacy of generating the pgSIT animals - the overall number of eggs hatched from the gRNA (X) Cas9 cross appears to be low, therefore, very large numbers of parental animals would have to be reared and crossed to obtain enough sterile males for the SIT. In addition to this, I was concerned about the intersex progeny that can blood-feed. These could potentially contribute to the population and it would be useful to see the data that suggest that these numbers are low and the animals will not be competent in the field.

Reviewer #2 (Public Review):

This is a thorough and convincing body of work that represents an incremental but significant improvement on iterations of this method of CRISPR-based Sterile Insect Technique ('pgSIT'). In this version, compared to previous, the authors target more genes than previously, in order to induce both female inviability (targeting the genes intersex and doublesex, compared to fem-myo previously) and male sterility (targeting a beta-tubulin, as previously in the release generation.<br /> The characterization of the lines is extensive and this data will be useful to the field. However, what is lacking is some context as to how this formulation compares to the previous iteration. Mention is made of the possible advantage of removing most females, compared to just making them flightless (as previously) but there is no direct comparison, either experimental, or theoretical i.e. imputing the life history traits into a model. For me this is a weakness, yet easily addressed. In a similar vein, much is made in alluding to the 'safety concerns of gene drive' and how this is a more palatable half-way house, just because it has CRISPR component within it; it is not. It would be much more sensible, and more informative, to compare this pgSIT technology to RIDL (release of insects carrying a dominant lethal), which is essentially a transgene-based version of the Sterile Insect Technique, as is the work presented here.

The authors achieve impressive results and show that these strains, under a scenario of high levels of release ratios compared to WT, could achieve significant local suppression of mosquito populations. The sensitivity analysis that examines the effect of changing different biological or release parameters is well performed and very informative.

The authors are honest in acknowledging that there are still challenges in bringing this to field release, namely in developing sexing strains and optimizing release strategies - a question I have here is how to actually release eggs, and could variability in the efficiency of this aspect be modelled in the sensitivity analysis? It seems to me like this could be a challenge and inherently very variable.

Reviewer #3 (Public Review):

Summary and Strengths:

The manuscript by Li et al. presents an elegant application of sterile insect technology (pgSIT) utilizing a CRISPR-Cas9 system to suppress mosquito vector populations. The pgSIT technique outlined in this paper employs a binary system where Cas9 and gRNA are conjoined in experimental crosses to yield sterile male mosquitoes. Employing a multiplexed strategy, the authors combine multiple gRNA to concurrently target various genes within a single locus. This approach successfully showcases the disruption of three distinct genes at different genomic positions, resulting in the creation of highly effective sterile mosquitoes for population control. The pioneering work of the Akbari lab has been instrumental in developing this technology, previously demonstrating its efficacy in Drosophila and Aedes aegypti.

By targeting the female-specific splice isoform (exon-5) of doublesex in conjunction with intersex and β-tubulin, the researchers induce female lethality, leading to a predominance of sterile male mosquitoes. This innovation is particularly noteworthy as the deployment of sterile mosquitoes on a large scale typically requires substantial investment in sex sorting. However, this study circumvents this challenge through genetic manipulation.

Weaknesses:

One notable concern arising from this manuscript pertains to the absence of data regarding the potential off-target effects of the gRNA. Given the utilization of multiple gRNA, the risk of unintended mutations in non-target areas of the genome increases. With around 1% of males still capable of producing fertile offspring, understanding the frequency of unintended genome targeting becomes crucial. Such mutations could potentially become fixed within the natural population.<br /> The experiments are well-conceived, featuring suitable controls and repeated trials to yield statistically significant data. However, a primary issue with the manuscript lies in its data presentation. The authors' graphical representations are intricate and demand considerable attention to discern the nuances, especially due to the striking similarity between the symbols representing different genotypes. As it stands, the manuscript primarily caters to experts within the field, thereby warranting improvements in data visualization for broader comprehension.

Reviewer #1 (Public Review):

Despite durable viral suppression by antiretroviral therapy (ART), HIV-1 persists in cellular reservoirs in vivo. The viral reservoir in circulating memory T cells has been well characterized, in part due to the ability to safely obtain blood via peripheral phlebotomy from people living with HIV-1 infection (PWH). Tissue reservoirs in PWH are more difficult to sample and are less well understood. In this small (n=3) autopsy study, Sun and colleagues use an advanced genetic sequencing technique to characterize HIV-1 that persists in human tissues despite antiretroviral therapy. The authors describe isolation and genetic characterization of HIV-1 reservoirs from a variety of tissues including the central nervous system (CNS) obtained from three recently deceased individuals at autopsy. They identified clonally expanded proviruses in the CNS in all three individuals.

Strengths of the work include the study of human tissues that are under-studied and difficult to access, and the sophisticated near-full length sequencing technique that allows for inferences about genetic intactness and clonality of proviruses. The small sample size (n=3) is a drawback. Furthermore, two individuals were on ART for just one year at the time of autopsy and had T cells compatible with AIDS, and one of these individuals had a low-level detectable viral load (Figure S1). This makes generalizability of these results to PWH who have been on ART for years or decades and have achieved durable viral suppression and immune reconstitution difficult.

While anatomic tissue compartment and CNS region accompany these PCR results, it is unclear which cell types these viruses persist in. As the authors point out, it is possible that these reservoir cells might have been infiltrating T cells from blood present at the time of autopsy tissue sampling. Cell type identification would greatly enhance the impact of this work. Overall, this small, thoughtful study contributes to our understanding of the tissue distribution of persistent HIV-1, and informs the ongoing search for viral eradication.

Reviewer #2 (Public Review):

The authors were trying to survey reservoir viral sequences in different anatomical sites in the body, with the brain being of special interest. This is a study that is technically demanding and here is well done, providing insights that prompt new and more sophisticated questions.

The authors use end-point dilution PCR to identify individual proviruses that can then be sequenced with high accuracy. These are high quality data sets but given the technical requirements of this approach the number of sequenced proviruses is limiting given the scope of questions this study addresses. Nonetheless, there is a lot of data here to draw many useful conclusions.

It will be important to realize how clones of infected T cells can move around the body, including into the CNS compartment. It will also be important to remember that there are limits in sampling depth of proviruses in any one tissue meaning the failure to detect something has a limit in sensitivity of detection when trying to interpret a negative result.

As noted in the next section, it is important to emphasize that there is another entry phenotype beyond X4 that will ultimately be important in interpreting these results. Macrophage-tropic viruses are often found in the CNS compartment and it will be important to understand whether these CNS-derived sequences are macrophage-tropic viruses there infecting macrophages and microglia or if they are all T-tropic viruses brought in by wandering infected T cells (or both).

Joint Public Review:

In this manuscript, Xue and colleagues investigate the fundamental aspects of cellular fate decisions and differentiation, focusing on the dynamic behaviour of gene regulatory networks. It explores the debate between static (noise-driven) and dynamic (signal-driven) perspectives within Waddington's epigenetic landscape, highlighting the essential role of gene regulatory networks in this process. The authors propose an integrated analysis of fate-decision modes and gene regulatory networks, using the Cross-Inhibition with Self-activation (CIS) network as a model. Through mathematical modelling, they differentiate two logic modes and their effect on cell fate decisions: requires both the presence of an activator and absence of a repressor (AA configuration) with one where transcription occurs as long the repressor is not the only species on the promoter (OO configuration).

The authors establish a relationship between noise profiles, logic-motifs, and fate-decision modes, showing that defining any two of these properties allows the inference of the third. They also identify, under the signal-driven mode, two fundamental patterns of cell fate decisions: either prioritising progression or accuracy in the differentiation process. The authors apply this analysis to available high-throughput datasets of cell fate decisions in hematopoiesis and embryogenesis, proposing the underlying driving force in each case and utilising the observed noise patterns to nominate key regulators.

The paper makes a substantial contribution by rigorously evaluating assumptions in gene regulatory network modelling. Notably, it extensively compares two model configurations based on different integration logic, illuminating the consequences of these assumptions in a clear, understandable manner. The practical simulation results effectively bridge theoretical models with real biological systems, adding relevance to the study's insights. With its potential to enhance our understanding of gene regulatory networks across biological processes, the paper holds promise. Its implications extend practically to synthetic circuit design, impacting biotechnology. The conclusions stand out, addressing cell fate decisions and noise's role in gene networks, contributing significantly to our understanding. Moreover, the adaptable approach proposed offers versatility for broader applications in diverse scenarios, solidifying its relevance beyond its current scope.

However, the manuscript in its current form also has some important weaknesses, including the lack of clarity in the text and the questionable generality of specific observations. For instance, even when focusing on the CIS network, the effect of alternative model implementations is not discussed. Notably, the input signals are only considered as an additive effect over the differential equations, while signals can potentially affect each of the individual processes. The proposed model allows for a continuum of interactions/competition between transcription factors, yet only very restrictive scenarios are explored (strict AND/OR logic operations). Moreover, how the model parameters are chosen throughout the paper is not clear. Similarly, the concentration and time units are not clearly specified, making their comparison to experimental data troublesome.

Regarding clarity, how the general model (equations 1-2) transforms into the specific cases evaluated in the paper is not clearly stated in the main text, nor are the positive and negative effects of individual transcription factors adequately explained. Similarly, in the main text and Figure 2, the authors refer to a Boolean model. However, they do not clearly explain how this relates to the differential equation model, nor its relevance to understanding the paper. Additionally, the term "noise levels" is generally used to refer to noise introduced in the "noise-driven" analysis (i.e., as an input or parameter in the models). Nonetheless, it is later claimed to be evaluated as an intrinsic property of the network (likely referring to expression level variability measured by the coefficient of variation). Finally, some jargon is introduced without sufficient context about its meaning (e.g., "temporal fully-connected stage").

Additionally, proper discussion of previous work is also missing. For instance, the dynamics of the CIS network investigated by the authors have been extensively characterised (see e.g., Huang et al., Dev Biol, 2007), and how the author's results compare to this previous work should be discussed. In particular, the central assumptions behind the derivation of the model proposed in the manuscript must be assessed in the context of previous work.

Reviewer #1 (Public Review):

Summary:<br /> Human Abeta42 inhibits gamma-secretase activity in biochemical assays.

Strengths:<br /> Determination of inhibitory concentration human Abeta42 on gamma-secretase activity in biochemical assays.

Weaknesses:<br /> Human Abeta42 may concentrate up to microM order in endosomes. If so, production of Abeta42 would be attenuated then lead to less Abeta deposition in the brain. The authors finding is interesting but does not fit the physiological condition in the brain.<br /> It is not clear whether the FRET-based assay in living cells really reflect gamma-secretase activity.<br /> Processing of APP-CTF in living cells is not only the cleavage by gamma-secretase.

Reviewer #2 (Public Review):

Summary:<br /> In the current study, the authors tested the hypothesis that Aβ42 toxicity arises from its proven affinity for γ-secretases. Specifically, the increases in Aβ42, particularly in the endolysosomal compartment, promote the establishment of a product feedback inhibitory mechanism on γ-secretases, and thereby impair downstream signaling events. They showed that human Aβ42 peptides, but neither murine Aβ42 nor human Aβ17-42 (p3), inhibit γ-secretases and trigger accumulation of unprocessed substrates in neurons, including (CTFs of APP, p75 and pan-cadherin. Moreover, Aβ42 dysregulated cellular homeostasis by inducing p75-dependent neuronal death. Because γ-secretases process many other membrane proteins, including NOTCH, ERB-B2<br /> receptor tyrosine kinase 4 (ERBB4), N-cadherin (NCAD) and p75 neurotrophin receptor (p75-NTR), revealing a broad range of downstream signaling pathways, including those critical for neuronal structure and function. Hence, they propose to identification of a selective role for the Aβ42 peptide, and raise the intriguing possibility that compromised γ-secretase activity against the CTFs of APP and/or other neuronal substrates contributes to the pathogenesis of AD. Overall, the data are not very convincing to support the main claim.

Strengths.

Different in vitro and cellular approaches are employed to test the hypothesis.

Weaknesses.

The experimental concentrations for Aβ42 peptide in the assay are too high, which are far beyond the physiological concentrations or pathological levels. The artificial observations are not supported by any in vivo experimental evidence.

Reviewer #1 (Public Review):

In this manuscript, Tian et al. describe a novel modified version of the pro-drug triptolide, CK21, and provide evidence for its improved pharmacokinetics and its safety and efficacy in multiple xenograft models of pancreatic cancer. The authors performed transcriptomic analysis upon CK21 treatment which revealed that downregulation of NF-kB and mitochondrial dysfunction induce apoptosis and therefore lead to tumor regression. Downregulation of NF-kB and induction of apoptosis was then validated in vitro and in vivo. These findings have potential clinical significance as the efficacy of CK21 in preclinical PDAC models is compelling. However, there are also some limitations to their experiments and more validation studies are necessary to strengthen their findings regarding the mechanism of action of the drug. Specifically, the authors suggest that mitochondrial dysfunction is responsible for the observed apoptosis; however, this is not demonstrated. Additionally, side-by-side comparisons to other clinical triptolide analogs to show CK21 is at least as efficacious as other analogs in vivo would be valuable, especially since other analogs have been shown to synergize with conventional chemotherapy in PDAC mouse models, whereas CK21 does not appear to. Moreover, assessing whether CK21 is efficacious in syngeneic orthotopic PDAC models is critical, especially since CK21 was shown to have an impact on NF-KB which plays a major role in the immune compartment and triptolide has been shown to be immunosuppressive.

Reviewer #2 (Public Review):

The authors describe the synthesis and testing of the anti-cancer activity of a new molecule CK21 against pancreatic cancer mouse models. This part of the study is very strong showing regression of pancreatic tumors at non-toxic concentrations, which is very hard to achieve for practically uncurable pancreatic cancer. Authors synthesized CK21 as an analog of a known inhibitor of RNA synthesis which is very toxic. The authors did very little attempt to understand whether the mechanism of anti-cancer efficacy of CK2 is similar to this known inhibitor of transcription or not. One cannot compare gene expression profiles between untreated and CK21-treated cells, taking into account that CK2 may inhibit the expression of all genes. The effect of CK2 on general transcription needs to be tested first, and then based on this data absolute changes in the expression of genes may be considered for the revealing of the mechanism of activity of CK21.

Reviewer #3 (Public Review):

This manuscript describes CK21, a modified version of Triptolide, a natural compound with ant-cancer activities, to improve its bioavailability. The authors tested the compound in two human pancreatic cancer cell lines, in vitro and in vivo. The authors also use two human organoid lines derived from pancreatic cancer, and mouse KC and KPC cell lines. In all models, CK21 treatment induces dose-dependent cytotoxicity. In vivo, CK21 causes tumor regression. The authors perform gene expression analysis and show that treated organoids have generally lower transcription, consistent with cytotoxicity, and a reduction in the KFkB pathway activation.

Key experiments that would strengthen the current manuscript are: the inclusion of normal cell lines and organoids, too, presumably, show no cytotoxic effect. If that is the case, the authors would have the opportunity to compare responses and determine whether a tumor-specific mechanism can be defined.

The authors observe that few gene changes - besides from overall lowering in transcription, occur upon treatment with CK21. They suggest that the drug acts through inhibition of the NFkB pathway and an increase in reactive oxygen species (ROS). However, no experiments to test whether either/both of these findings explain the cytotoxic effect (rescue experiments would be particularly valuable).

In the last figure, the authors text whether CK21 is immunosuppressive by testing immunity against a mis-matched tumor cell line (using KPC tumors, mixed strain, in mixed strain mice). The immunity against HLA mis-matched cells is a very strong immune reaction, and mild immune suppression might be missed, which diminishes the value of these findings.

Reviewer #1 (Public Review):

Ruesseler and colleagues combine careful paradigm design, psychophysical and EEG analyses to determine whether information leakage during decision formation is strategically adjusted to meet changing task demands. Participants made motion direction judgments that required monitoring a continuous stream of dot motion for 'response periods' characterised by a sustained period of coherent motion in a leftward or rightward direction. Coherence was modulated on a frame-to-frame basis throughout the task furnishing a parametric regressor that could be used to interrogate the longevity of sensory samples in the decision process and their influence on corresponding EEG signals. Participants completed the task under varying conditions of response period length and frequency. Psychophysical kernel analyses suggest that sensory samples had a more short-lived impact on the participants' choices when response periods were rare, suggestive of greater information leakage. When the stimulus perturbations were regressed against the EEG data, it highlighted a centro-parietal component that showed increased responsiveness to large shifts in evidence when those shifts were more rare, suggestive of a role in representing surprise. An additional triphasic component was found to correlate with the time constant of integration as estimated from the kernel analyses.

This is a very timely paper that addresses an important and difficult-to-address question in the decision-making field - the degree to which information leakage can be strategically adapted to optimise decisions in a task-dependent fashion. The authors apply a sophisticated suite of analyses that are appropriate and yield a range of very interesting observations. The paper centres on analyses of one possible model that hinges on certain assumptions about the nature of the decision process for this task which raises questions about whether leak adjustments are the only possible explanation for the current data. I think the conclusions would be greatly strengthened if they were supported by the application and/or simulation of alternative model structures.

The behavioural trends when comparing blocks with frequent versus rare response periods seem difficult to tally with a change in the leak. The greater leak should result in a reduction in the rate of false alarms yet no significant differences were observed between these two conditions. Meanwhile, false alarms did vary as a function of short/long target durations which did not show any leak effect in the psychophysical kernel analyses. Are there other models that could reproduce such effects? For example, could a model in which the drift rate varies between Rare and Frequent trials do a similar or better job of explaining the data? This ties in to a related query about the nature of the task employed by the authors. Due to the very significant volatility of the stimulus, it seems likely that the participants are not solely making judgments about the presence/absence of coherent motion but also making judgments about its duration (because strong coherent motion frequently occurs in the inter-target intervals). If that is so, then could the Rare condition equate to less evidence because there is an increased probability that an extended period of coherent motion could be an outlier generated from the noise distribution? Note that a drift rate reduction would also be expected to result in fewer hits and slower reaction times, as observed.

Some adjustment of the language used when discussing FAs seems merited. If I have understood correctly, the sensory samples encountered by the participants during the inter-response intervals can at times favour a particular alternative just as strongly (or more strongly) than that encountered during the response interval itself. In that sense, the responses are not necessarily real false alarms because the physical evidence itself does not distinguish the target from the non-target. I don't think this invalidates the authors' approach but I think it should be acknowledged and considered in light of the comment above regarding the nature of the decision process employed on this task.

The authors report that preparatory motor activity over central electrodes reached a larger decision threshold for RARE vs. FREQUENT response periods. It is not clear what identifies this signal as reflecting motor preparation. Did the authors consider using other effector-selective EEG signatures of motor preparation such as beta-band activity which has been used elsewhere to make inferences about decision bounds? Assuming that this central ERP signal does reflect the decision bounds, the observation that it has a larger amplitude at the response on Rare trials appears to directly contradict the kernel analyses which suggest no difference in the cumulative evidence required to trigger commitment.

P11, the "absolute sensory evidence" regressor elicited a triphasic potential over centroparietal electrodes. The first two phases of this component look to have an occipital focus. The third phase has a more centroparietal focus but appears markedly more posterior than the change in evidence component. This raises the question of whether it is safe to assume that they reflect the same process.

Reviewer #2 (Public Review):

In this manuscript, Ruesseler and colleagues use a continuous task to examine how neural correlates of decision-making change when subjects face conditions with different durations and frequencies of occurrence of signals embedded in noise. The authors develop a novel task where subjects must report the direction of relatively sustained (3 or 5 s) signal changes in average coherence of a random dot kinetogram that are intermittent among relatively transient noise fluctuations (<1 s) of motion coherence that is continuous. Subjects adjust their behavior to changes in the duration of signal events and the frequency of their occurrence. The authors estimate a decay time constant of leaky integration of evidence based on the average coherence leading up to decision responses. Interestingly, there is considerable inter-subject variability in decay time constants even under identical conditions. In addition, the average time constants are shorter when signal periods occur more frequently as opposed to when they are more rare. The authors use EEG to find that a component of the Centroparietal Positivity (CPP) regressed to the magnitude of changes in the noise coherence is larger in conditions when the signal periods occur less frequently. Using a control condition, the authors show that this component of the CPP is not simply based on surprise because it is smaller for changes in motion coherence in irrelevant directions with matched statistics as the changes in relevant directions. The authors also find that a different component of the CPP related to the magnitude of the motion coherence co-varies with the inter-subject variability in decay time constants estimated from behavior.

Overall, the authors use a clever experimental design and approach to tackle an important set of questions in the field of decision-making. The manuscript is easy to follow with clear writing. The analyses are well thought-out and generally appropriate for the questions at hand. From these analyses, the authors have a number of intriguing results. So, there is considerable potential and merit in this work. That said, I have a number of important questions and concerns that largely revolve around putting all the pieces together. I describe these below.

1) Quite sensibly, the authors hypothesize that "decay time constant" for past evidence and "decision threshold" would be altered between the different task conditions. They find clear and compelling evidence of behavioral alterations with the conditions. They also have a method to estimate the decay time constant. However, it is unclear to what extent the decision threshold is changing between subjects and conditions, how that might affect the empirical integration kernel, and how well these two factors can together explain the overall changes in behavior.

To be more specific, the authors state that the lower false alarm rates and slower reaction times for the LONG condition are consistent with a more cautious response threshold for LONG. The empirical integration kernels lead to the suggestion that the decay time constant is not changing between SHORT and LONG, while it is changing between FREQUENT and RARE. Does the lack of change in false alarm rate between FREQUENT and RARE imply no change in the decision threshold? Is this consistent with the behavior shown in Figure 2? I would expect that less decay in RARE would have led to more false alarms, higher detection rates, and faster RTs unless the decision threshold also increased (or there was some other additional change to the decision process). The CPP for motor preparatory activity reported in Fig. 5 is also potentially consistent with a change in the decision threshold between RARE and FREQUENT. If the decision threshold is changing, how would that affect the empirical integration kernel? These are important questions on their own and also for interpreting the EEG changes.

2) The authors find an interesting difference in the CPP for the FREQUENT vs RARE conditions where they also show differences in the decay time constant from the empirical integration kernel. As mentioned above, I'm wondering what else may be different between these conditions. Do the authors have any leverage in addressing whether the decision threshold differs? What about other factors that could be important for explaining the CPP difference between conditions? Big picture, the change in CPP becomes increasingly interesting the more tightly it can be tied to a particular change in the decision process.

I'll note that I'm also somewhat skeptical of the statements by the authors that large shifts in evidence are less frequent in the RARE compared to FREQUENT conditions (despite the names) - a central part of their interpretation of the associated CPP change. The FREQUENT condition obviously has more frequent deviations from the baseline, but this is countered to some extent by the experimental design that has reduced the standard deviation of the coherence for these response periods. I think a calculation of overall across-time standard deviation of motion coherence between the RARE and FREQUENT conditions is needed to support these statements, and I couldn't find that calculation reported. The authors could easily do this, so I encourage them to check and report it.

3) The wide range of decay time constants between subjects and the correlation of this with another component of the CPP is also interesting. However, in trying to interpret this change in CPP, I'm wondering what else might be changing in the inter-subject behavior. For instance, it looks like there could be up to 4 fold changes in false alarm rates. Are there other changes as well? Do these correlate with the CPP? Similar to my point above, the changes in CPP across subjects become increasingly interesting the more tightly it can be tied to a particular difference in subject behavior. So, I would encourage the authors to examine this in more depth.

Reviewer #3 (Public Review):

The authors are designing a novel continuous evidence accumulation task to look at neural and behavioral adaptations of continuously changing evidence. They particularly focus on centroparietal EEG potential that has been previously linked with evidence accumulation. This paper provides a novel method and analysis to investigate evidence accumulation in a continuous task set-up.

I am not familiar with either the EEG or evidence accumulation literature, therefore cannot comment on the strength of the findings related to centroparietal EEG in evidence accumulation. I have therefore commented only on the coherence and details of the method and clarity of the argumentation and results.

The main strength is in the task design which is novel and provides an interesting approach to studying continuous evidence accumulation. Because of the continuous nature of the task, the authors design new ways to look at behavioral and neural traces of evidence. The reverse-correlation method looking at the average of past coherence signals enables us to characterize the changes in signal leading to a decision bound and its neural correlate.<br /> By varying the frequency and length of the so-called response period, that the participants have to identify, the method potentially offers rich opportunities to the wider community to look at various aspects of decision-making under sensory uncertainty.

The main weaknesses that I see lie within the description and rigor of the method. The authors refer multiple times to the time constant of the exponential fit to the signal before the decision but do not provide a rigorous method for its calculation and neither a description of the goodness of the fit. The variable names seem to change throughout the text which makes the argumentation confusing to the reader. The figure captions are incomplete and lack clarity.<br /> The authors claim that the method enables continuous analysis of decision-making and evidence accumulation which is true. The analysis of the signals that come prior to the decision provides a rich opportunity to characterize decision bound in this task. The behavioral and neural analyses globally lack clarity and description and thus do not strongly support the claims of the paper. The interpretation of the figures within the figure caption and the lack of a neutral and exhaustive description of what is being shown prevent the claims to be strongly supported.

The continuous nature of the task and the computation of those evidence kernels are valuable methods to look at evidence accumulation that could be of use within the community. However, due to the lack of rigor in the analysis and description of the method, it is hard to know if the current dataset is under-exploited or whether the choice of the parameters for this set of experiment does not enable stronger claims.

Reviewer #1 (Public Review):

The paper first demonstrates that heat-killed bacteria show little DAF-16 activation compared to live food. Of note, daf-16 survival is longer than WT when fed HK bacteria, giving important insights into the lethality of these mutants. Leakiness of the gut is assessed, which is induced by age and exacerbated by daf-16 mutation. The authors then go on to identify indole as the causal bacterial compound to drive daf-16 nuclear localization. The indole effect is fully daf-16 dependent. In searching for the indole sensor in the worm, TRPA-1 is identified and the authors argue that indole is sensed in neurons to modulate gut DAF-16. Closing the circle, lys genes are identified whose expression is upregulated by daf-16 and indole, and which are required to control bacterial growth in the gut with aging.

Reviewer #2 (Public Review):

The study by Yang et al. examines the interactions between a model host, the nematode C. elegans, and its gut bacteria during aging, focusing on how the host responds to progressing bacterial colonization. In a sense, this work follows up on a previous report describing the activation of DAF-16 in middle-aged worms. Here they test the importance of DAF-16 for aging-dependent accumulation of E. coli in the worm gut, as a model for responses to, and mitigation of, dysbiosis, which in humans is associated with pathology.

The mechanism unraveled in this study includes the sensing of increasing concentrations of indole, a tryptophan metabolite that is secreted by the accumulating gut bacteria, which dependent on the neuronal cation channel TRPA-1 (and NOT through the known indole receptor AHR-1), activates intestinal DAF-16, driving its nuclear translocation and leading to subsequent induction of downstream targets, of which LYS-7 and LYS-8 are essential for diminishing bacterial colonization and mitigating the associated damage.

The authors provide very clean and very strong evidence to support the described mechanism, clean identification of indole as the metabolite responsible for DAF-16 nuclear localization, and good indole supplementation experiments and measurements of indole levels inside of worms to support its function. At the same time, some of the methods are not completely clear - for example, how did the authors obtain pure bioactive fraction to run their NMR analysis and identify indole as the activating molecule (this should be clarified in, or added to the method section); or how were indole supplementation experiments carried out? On solid media, i.e. NGM plates, or in solution; with live bacteria, or heat-killed ones? (this is important for figuring out if indole sensing is from the outside or from the gut); and in a few cases the results appear too clear-cut, like the contribution of lys-7 and lys-8 to controlling gut bacteria - these two lysozymes seem to be sufficient to account for the entire contribution of DAF-16, which is surprising considering the large number of downstream targets this transcription factor has, as well as the very redundant nature of innate immune protection, which would have suggested the partial ability to protect at best; this should be considered and discussed.

Overall, though, the study is strong, and the conclusions are well supported. Given this, its potential impact is high, to inform our understanding of how animals respond to dysbiosis and the mechanisms aimed at mitigating potential detrimental effects of dysbiosis. Here, dysbiosis is manifested as increased colonization of aging worms by bacteria that cannot colonize young adults. In humans, dysbiosis manifests as imbalances in microbiome composition, which may include the proliferation of some gut bacteria at the expense of others. Thus, the mechanisms characterized here, which are conserved in humans, may play similar roles in human pathology and may offer handles to try and mitigate the detrimental effects of dysbiosis.

Reviewer #3 (Public Review):

Dysbiosis has a substantial impact on host physiology. Using the nematode C. elegans and E.coli as a model of host-microbe interactions, Yang et al. defined a mechanism by which the host deals with gut dysbiosis to maintain fitness. They found that accumulation of E. coli in the intestine secreted indole, a tryptophan metabolite, and activated the transcription factor DAF-16. DAF-16 induced the expression of lys-7 and lys-8, which in turn limited E. coli proliferation in the gut of worms and maintained the longevity of worms. Finally, these authors demonstrated that indole-activated DAF-16 via TRPA-1 in neurons of worms.

This study revealed a new mechanism of host-microbe interaction. The concept of their work is of broad interest and the results they present are convincing. However, there are some issues that need to be addressed to support the conclusions.

Major issues<br /> 1. The authors isolated the crude extract from a high-performance liquid chromatograph (HPLC). A candidate compound was detected by activity-guided isolation and further identified as indole with mass spectrometry and NMR data.<br /> The HPLC fractionations and activity-guided isolation experiments should be described in more detail with a schematic figure to reveal how these experiments were performed and how indole was identified. Showing a chemical characterization of indole in Figure 2A is not sufficient for the evaluation of the results. Rather, a figure comparing the fraction 26th with standard indole by MS and NMR is more appealing.

2. DAF-16::GFP was mainly located in the cytoplasm of the intestine in worms expressing daf-16p::daf-16::gfp fed live E. coli OP50 on Day 1 (Figure 1A and 1B). The nuclear translocation of DAF-16 in the intestine was increased in worms fed live E. coli OP50 on Days 4 and 7, but not in age-matched WT worms fed heat-killed (HK)E. coli OP50 (Figure 1A and 1B).<br /> Since DAF-16 functions downstream of DAF-2, have the levels of DAF-2 been tested during aging on OP50 and (HK)OP50, or with and without indole supplementation?

3. In lines 155-157, the author argued that the increase in the levels of indole in worms results from the intestinal accumulation of live E. coli OP50, rather than exogenous indole produced by E. coli OP50 on the NGM plates.<br /> However, the work also showed that supplementation with indole (50-200 μM) could significantly increase the indole levels in young adult worms on Day 1 (Figure 2-figure supplement 3B), which could induce nuclear translocation of DAF-16 in worms (Figure 2B).<br /> This result suggested that worms could take in indole from outside culturing environment. The concentration of indole in OP50 and (HK)OP50 could be measured.

4. Recent work showed that the multicopy DAF-16 transgene acts differently from the single copy GFP knockin DAF-16 transgene. Which DAF-16 transgene was used in this work?

5. In lines 190-193, the author argued that the supplementation with indole (100 M) inhibited the CFU of E. coli K-12 in WT worms, but not daf-16(mu86) mutants, on Days 4 and 7 (Figure 3H and 3I). These results suggest that endogenous indole is involved in maintaining a normal lifespan in worms.<br /> This is overstating. The data here more likely suggest that indole could inhibit the proliferation of E.coli through DAF-16.

6. Sonowal (2017) reported that AHR mediates indole-promoted lifespan extension at 16oC. Yet this work argued that RNAi knockdown of ahr-1 did not affect the nuclear translocation of DAF-16 in worms fed E. coli K12 strain on Day 7 (Figure 4-figure supplement 1A) or young adult worms treated with indole (100 M) for 24 h.<br /> The difference between these two works should be discussed.

7. Sonowal (2017) conducted mRNA profiling for worms growing on K12 and K12△tnaA. Is TRPA1 in their de-regulated gene list? Have other de-regulated genes been tested in this work?

8. How does indole activate TRPA1? In the absence of trpa1, what is the concentration of indole in worms? Since TRPA1 is a channel, is there any possibility that TRPA1 is involved in the transport of indole? It is really interesting and surprising that neuronal TRPA-1, but not intestinal TRPA-1, mediates the beneficial effect of indole. How does indole specifically activate TRPA-1 in neurons to preserve the longevity of worms?

9. How neuronal- and intestinal-specific knockdown of trpa-1 by RNAi was conducted? And what is the tissue-specific expression pattern of trap-1? Speculating how indole was transported to neuron cells is pretty appealing.

10. Supplementation with indole only up-regulated the expression of lys-7 and lys-8 in worms subjected to intestinal-specific (Figure 7-figure supplement 2C), but not neuronal-specific, RNAi of trpa-1 (Figure 7-figure supplement 2D).<br /> If this is the case, should the addition of indole specifically induce the expression of lys-7p::gfp or lys-8p::gfp in neurons?

11. The authors demonstrated that K-12△tnaA strain had undetectable tnaA mRNA or indole levels. Furthermore, the deletion of tnaA significantly inhibited the nuclear translocation of DAF-16 in worms. However, mutations in E. coli still have non-specific effects as there are several transposon insertions or polar mutations influencing downstream genes. The authors should demonstrate that only disruption of TnaA causes the failure of nuclear translocation of DAF-16.

Reviewer #1 (Public Review):

In this study, the authors characterize regulatory control of embryonic genome activation in the allotetraploid, Xenopus laevis. By characterizing transcription from its L and S subgenomes, they determine that homeologous genes are differentially activated in the early embryo. It has recently been appreciated that homeologs may be differentially expressed in later embryonic development (Session and Rokhsar, Nature 2016). However, an unanswered question is whether vertebrate tetraploid genomes undergo differential induction at the onset of the major wave of zygotic genome activation (ZGA). This is a fertile area for research, that enables the study of gene regulatory network adaptations to changes in ploidy, limited by the constraints of gene dosage and an essential early developmental transition. Xenopus laevis, which recently underwent a tetraploidization event, approximately 18 million years ago, provides a very useful model embryonic system for the study of homeologous gene activation during vertebrate ZGA.

To characterize differential subgenome activation the authors focused on the ~ 2600 maternally-regulated genes expressed in the first wave of widespread ZGA. They treated embryos with cycloheximide at Stage 8 to prevent the translation of zygotic factors that would further alter the transcriptome. They found a majority of these maternally-regulated genes have asymmetric expression between the two homeologs, with transcription often occurring from the L or S copy alone. This is a fascinating result from which to dig deeper into gene regulatory mechanisms. To understand whether cis-regulatory networks dictate the biased L/S homeolog expression in the late blastula, the authors performed CUT&RUN to map active chromatin marks, H3K4me3 and H3K27ac. However, they found no differences in promoter sequences of homeologs that would implicate differential recruitment of specific transcription factors. Instead, they focused on distal enhancers and additionally performed ATAC-seq on Stage 8 and 9 animal cap explants. Approximately 70% of enhancers for homeolog pairs exhibited differential H3K27ac enrichment and chromatin accessibility. The authors then searched for transcription factor binding motifs that distinguished active enhancers from their inactive homeolog. They found binding sequences for OCT4 and SOX2/3 were enriched in active L enhancers and active S enhancers. To assess the role of these pluripotency factors, they used antisense morpholinos to block their translation in the early embryo. MOs were complementary to both the L and S homeologs of pou5f3.3 and sox3, but not to their paralogs that are primarily expressed zygotically; pou5f3.1 and pou5f3.2. MO knockdown of both Pou5f3.3 and Sox3 was inhibited leading to significant downregulation of 62% of activated genes compared to embryos injected with a control morpholino. They also analyzed binding to the genome of V5-tagged, injected versions of these 2 transcription factors and found some evidence for differential binding around TSS of homeolog pairs and a correlation between binding and the overall level of transcription at ZGA. Finally, they compare enhancer marks and accessibility in tetraploid X.laevis subgenomes to homologous enhancers in the diploid X.tropicalis. They conclude conservation of active enhancers with X.tropicalis and even zebrafish when considering the combined data from X.laevis L and S subgenome.

There are many strengths of this manuscript. In this interesting study, the authors identify what appears to be an evolutionary divergence of enhancers in a vertebrate tetraploid, that may underlie the differential expression of homeologs during the first major wave of ZGA. They generate CUT&RUN datasets of active chromatin marks during the early and late blastula. Additionally, they provide binding data for pluripotency factors OCT4 and SOX2/3 and demonstrate that their MO knockdown leads to reduced expression at ZGA. Their analyses identify correlations between differential homeolog expression and active or accessible chromatin. Further, they identify that active enhancers are enriched in OCT4 and SOX2/3. Enthusiasm is somewhat dampened by a lack of direct perturbation to differential subgenome activation or an understanding of the functional impacts of differential homeolog expression on subsequent development.

Reviewer #2 (Public Review):

Hybridization events between species are known to result in substantial genomic upheaval, requiring subsequent coordination between gene copies to ensure proper control of gene expression and embryonic viability. An example of such an event happened over 18 million years ago between two frog species that resulted in Xenopus laevis-an allotetraploid that has largely retained copies of both genes from this event, known as L-alleles and S-alleles. Often, the presence of both copies presents an experimental and bioinformatic hurdle for researchers and is a feature of the biology of X. laevis that renders cross-species comparisons difficult. Phelps et al, however, take advantage of this feature of Xenopus biology and use it to their advantage to ask how the hybridization event in this species altered gene regulatory architecture. They find that a handful of pluripotency genes are largely responsible for activating gene expression in the early embryo, but that L and S alleles are differentially activated in many cases. Moreover, they find extensive differences in cis-regulatory architecture between L/S alleles. Despite these differences in alleles, however, they find that their combined gene expression output is largely conserved, possibly reflecting strong selection pressures acting to maintain gene expression output at specific levels. This work represents a significant advance in how hybridization events are something greatly understudied in developmental biology-influence gene regulatory programs and how evolutionary pressures have shaped these programs in response to such events.

Reviewer #1 (Public Review):

Zou et al. employ single-cell RNA sequencing of healthy skin, actinic keratosis (AK), squamous cell carcinoma in situ (SCCIS), and cutaneous squamous cell carcinoma (cSCC) to unravel the molecular events driving the progression of AK into cSCC (n=13 samples from 6 patients), thereby filling a gap of knowledge in skin cancer research. The authors identified several previously unreported candidate genes (including ALDH3A1, IGFBP2, MAGEA4, ITGA6, and LGALS1) involved in different stages of malignant progression, the expression of which was validated in situ in a large cohort. Functional in vitro experiments confirm a possible role for these genes in the transformation from benign to malignant skin lesions.

Moreover, the authors identified epidermal cell subpopulations that may play an important role in the development from AK to cSCC, including an "early malignant cell" subpopulation within SCCIS basal cells with higher mutational load according to CNV analysis, which they characterized in more detail. For example, they found MAGEA4 strongly expressed in basal cells of (most) SCCIS and cSCC, as well as ITGA6. Functional assays in HaCaT and cSCC cell lines revealed that the knock-down of MAGEA4 and ITGA6 reduced proliferation, migration, and invasion but increased apoptosis in the cSCC cell lines.

Finally, they describe the tumor microenvironment of a poorly differentiated cSCC sample, and scATAC sequencing of this poorly differentiated cSCC revealed that the majority of differentially accessible chromatin regions (DARs) were located in basal epidermal cells.

Altogether, the authors provide a comprehensive transcriptional analysis of premalignant (AK, SCCIS) and malignant stages of cSCC. They suggest some key driver genes for each stage, the role of which are addressed in vitro and in situ in a large cohort. Thus, this study may provide novel biomarkers for tumor staging and diagnosis as well as potential targets for the prevention and treatment of cSCC.

Reviewer #2 (Public Review):

Zou et al. presented a comprehensive study where they generated single-cell RNA profiling of 138,982 cells from 13 samples of six patients including AK, squamous cell carcinoma in situ (SCCIS), cSCC, and their matched normal tissues, covering comprehensive clinical courses of cSCC. Using bioinformatics analysis, they identified keratinocytes, CAFs, immune cells, and their subpopulations. The authors further compared signatures within subpopulations of keratinocytes along with the clinical progression, especially basal cells, and identified many interesting genes. They also further validate some of the markers in an independent cohort using IHC, followed by some knockdown experiments using cSCC cell lines.

The strength of this study is the unique data set they have created, providing the community with invaluable resources to study and validate their findings. However, a lot of analyses were not robust enough to support the claims and conclusions in the paper. More clarification and cross-comparison with polished data are needed to further strengthen the study and claims.

1) Stemness markers were used. The authors used COL17A1, TP63, ITGB1, and ITGA3 to represent stemness markers. However, these were not common classic stemness markers used in cSCC. What is the source claiming these genes were stemness markers in cSCC? TP63 is a master regulator and early driver event in SCC, while COL17A1, ITGB1, and ITGA3 are all ECM genes. The authors need to use commonly well-known stem cell markers in cSCC, e.g., LGR5, to mark stem-like cells.

2) Cell proportion analysis. The authors used the mean proportions to compare different clinical groups for subpopulations of keratinocytes, e.g., Figure 2B, and Figure 5B. This is not robust, as no statistics can be derived from this. For example, from Fig 2A, it is clearly shown there is a high level of heterogeneity of cellular compositions for normal samples. One cannot say which group is higher or lower simply based on mean not variance as well.

3) Basal tumour cells in SCCIS and SCC. To make the findings valid, authors need to compare these cells/populations with the keratinocyte cell populations defined by Ji et al. Cell 2020. Do basal-SCCIS-tumours cells, also in SCC samples, resemble any of the population defined in Ji et al. Ji et al. also had 10 match normal, thus the authors need to validate their findings of SCC vs normal analysis using the Ji et al. dataset.

4) Copy number analysis. Authors used inferCNV to perform copy number analysis using scRNA-seq data and identified CNVs in subpopulations of keratinocytes in SCCIS and SCC. To ensure these CNVs were not artefacts, were some of the CNVs identified by inferCNV well-known copy number changes previously reported in cSCC?

5) Pseudotime analysis lines 308-313. Not sure the pseudotime analysis added much as, as it is unclear two distinct subgroups were identified from this analysis. Suggest removing this to keep it neater

6) Selection of candidate genes for validation using IHC and cell line work. For example, lines 205-206, lines 352-356 and lines 437-441, authors selected several genes associated with AK and SCC to further validate using IHC and cell line knockdown work. What are the criteria for selecting those genes for validation? It is unclear to readers how these were selected. It reads like a fishing experiment, then followed by a knockdown. Clear rationale/criteria need to be elaborated.

7) TME. Compared to keratinocytes populations, the investigation of TME cells was weak. (a) can authors produce UMAP files just for T cells, DC cells, and fibroblasts separately? Figure 7B is not easy to see those subclusters. (b) similar to what was done for keratinocytes, can authors find differentially expressed clusters and genes among the different clinical groups, associated with disease progression? (c) where are the myeloid cell populations, also B cells?

8) Heat shock protein genes line 327-329. HSP signature was well-known to be induced via tissue dissociation and library prep during the scRNA experiment. How could the authors be sure these were not artefacts induced by the experiment? If authors regress their gene expression against HSP gene signatures, would this cluster still be identified?

9) Cell-cell communication analysis. The authors claimed that that cell-to-cell interaction was significantly enhanced in poorly-differentiated cSCC, and multiple interaction pathways were significantly active. How was this kind of analysis carried out? How did the authors define significance? what statistical method was used? these were all unclear. Furthermore, it is difficult to judge the robustness of the cell-cell communication analysis. Were these findings also supported by another method, such as celltalker, and cellphoneDB?

10) Statistics and significance. In general, the detail of statistics and significance was lacking throughout the paper. Authors need to specify what statistical tests were used, and the p-values. It is difficult to judge the correctness of the test, and robustness without seeing the stats.

11) Overall, this manuscript needs a lot of re-writing. A lot of discussion was also included in the results, making it really difficult to read overall. The authors should simplify the results sections, remove the discussion bits, and further highlight and streamline with the key results of this paper.

Reviewer #1 (Public Review):

Zhao et al. investigated the molecular nature of the binding site for carbohydrates within the UDP-sugars known to activate the P2Y14 receptor. In order to do so, they built a molecular model of the hP2Y14, docked the corresponding agonists, and performed MD simulation on the resulting complexes. The modeling was used to identify the key molecular interactions with a cluster of charged residues in the extracellular side of the TM region of the receptor, which they show are conserved within the P2Y receptors. The binding site of the UDP region was, not surprisingly, overlapping with the analogous ADP binding site experimentally observed for the P2Y12 receptor, and consequently, the region that recognizes the sugars could be anticipated. Nevertheless, the detailed modeling and simulation work shows the consistency of this hypothesis and provides a quantification of the particular interactions involved, pinpointing specifically the residues candidate to be involved in the recognition of sugars.

It follows the characterization, by functional assays, of the effect of single-point mutations of these residues in the efficacy of the different UDP-sugars. Here the results show a tendency to correlate with the molecular models, however some of the data has very low statistical significance and consequently the interpretation and conclusions extracted from this data should be taken with caution. This pertains to the particular role of the identified residues in the binding of the different sugars, which in some cases should be taken as a suggestion rather than a proof, though the general conclusion of the identification of the binding region for the sugar, its conservation among P2Y receptors and the role of some specific residues in sugar recognition seems convincing and the data are conveniently presented.

Finally, the design of ADP-sugars that activate the P2Y12 receptor, based on the transferability of the observations with the UDP-sugars for the P2Y14 receptor, is a first indication that such a recognition is possible and should happen in an analogous binding region. However, the low potencies exhibited by the ATP-sugars, in the micromolar range, are too far from the ATP agonist and the relevance of this mechanism remains to be proved. The difference between P2Y12 and P2T14, with the last one showing much higher potencies for UDP-sugar derivatives than P2Y12 for the corresponding ADP-sugars, remains an interesting question not explored in this manuscript.

Reviewer #2 (Public Review):

The manuscript employs multiple approaches, including molecular docking, molecular dynamic simulations, and functional experiments to uncover a distinct uridine diphosphate-sugar-binding site on P2Y14 - a key drug target for inflammation and immune responses. Overall, the manuscript is clearly written and the experimental techniques are well-documented. However, it may benefit from further analysis, particularly in terms of validating the binding pose.

Reviewer #1 (Public Review):

Identifying compounds that can selectively inhibit protein kinases is of significant importance. Here, the authors describe a computational method to use existing kinome-wide profiling data to identify sets of compounds that, when combined, are more selective than any of the compounds on their own.

The authors explain the methodology well and the methodology is well-supported. The outcome of the methodology is assessed using an assay orthogonal to the original profiling assays. It is hard to assess whether the methodology works when a different assay is used.

The discussion of using this method for polypharmacology is naively discussed and under-supported.

Reviewer #2 (Public Review):

There currently are several hundreds of kinase inhibitors described and available for purchase. However, most of the target the ATP binding site of the protein kinase domain and, since it is pretty well conserved across the whole protein family, it means that the inhibitors are rarely selective, and most are able to simultaneously inhibit several kinases with, sometimes, different binding affinities. In this m/s, the authors present a strategy to combine kinase inhibitors with the aim of reducing off-target effects while preserving the inhibition potency in the intended target. To develop the methodology, the authors have used a set of publicly available data (protein kinase inhibitor set-2, or PKIS-2) containing affinity data on 406 kinases and 645 inhibitors. The authors run a series of simulations suggesting that, in a few cases, the identified combination of inhibitors is superior to the most specific single kinase inhibitor (i.e. show fewer off-target effects while maintaining the inhibition of the on-target). Finally, they test one of these examples in cells using nanoBRET.

The manuscript tackles an interesting problem (i.e. poor selectivity of kinase inhibitors) that, in some cases, has important clinical bearings. The approach is novel, interesting, and well-executed. However, unfortunately, I am not convinced that the strategy presents a real advantage over the most selective inhibitor.

Reviewer #3 (Public Review):

Seeking a selective inhibitor that precisely inhibits on-target activities and avoids side effects is a major challenge in the field of drug discovery and therapeutics. The authors proposed an alternative method that combines multiple inhibitors to maximize on-target inhibition and minimize off-target inhibition. Focusing on the kinase-inhibitor interaction dataset, the authors developed a quantitative way to measure the selectivity for mixtures of inhibitors by using the Jenson-Sahannon distance metric. The method sounds technical.

From their computation and assays, the multi-compound-multitarget scoring (MMS) method framework was validated to be able to select a combination of inhibitors that is more selective than a single highly selective inhibitor for one kinase target, or for multiple targets. The MMS method is a promising solution to reduce off-target effects and could be applicable to other inhibitor-target interactions. My suggestion is that a comparative analysis of MMS with other similar methods can be conducted to highlight the advantage of MMS over others.

The paper is not well organized and not easily readable. For example, first, the captions of the figures are two long; some of these texts could be moved to methods or results sections. Second, the concept of "penalty distribution" or "penalty prior" is vital to understand the MMS method, thus, at least a brief definition and introduction should be put in the main text rather than supporting method, as well as the rationale to use it. Third, the method section can be divided into several subsections with clear organizations and connections. Fourth, what is the difference between "a less selective inhibitor profile" and "an even less selective inhibitor profile" in Figure 3? Overall, the details of the paper are difficult to understand in the current version. I suggest rewriting<br /> the paper in a more concise and logical style.

Joint Public Review

In this manuscript, the authors develop a multi-scale agent-based model (ABM) capable of reproducing the self-organizing behavior observed in the intestinal crypt. By considering just the signaling pathways -previously reported as regulatory in the intestinal crypt- and local physical cell-to-cell interactions, the proposed model not only explains the emergence of the spatial organization, but also recapitulates cell composition dynamics in the crypt (proliferation, migration, and differentiation of cells), as previously characterized in the complex tissue of the small intestine epithelium in mice. The authors show that the self-organized system resulting from the model displays a stable composition over time. Additionally, the authors show how this model can be effectively used to test different conditions, such as biomedically relevant perturbations (e.g. stem cell ablation, cell cycle inhibition, and toxicity of particular drug treatments) and the posterior recovery, allowing to predict the safety of potential oncotherapies.

In summary, the authors provide a powerful and versatile model, which can be applied to better understand the formation and response of the intestinal crypt, as well as the functional heterogeneity of the intestinal epithelium at multiple scales. The proposed mathematical model simulates features across scales in the intestinal crypt such as multiple signaling pathways, the mechanical environment and its forces, and cell cycle regulation. The model demonstrates the stability of the homeostatic crypt and recovery following stem cell ablation. The model also simulates the cell cycle protein network and demonstrates that CDK1 inhibition creates oversized cells. In sum, the model generated by the authors increases the understanding of how these biological processes take place in vivo, exploring not only healthy cell behavior but also cell response to injury by oncotherapies or other external factors. Additionally, the authors provide a series of fascinating movies that show the spatial organization of the crypt during these processes, and the manuscript has clear applications for the clinics.

Nevertheless, in its current form, the manuscript has some weaknesses that are worth mentioning:

(1) The developed model considers the interaction of multiple signaling networks that are essential for morphogenesis and homeostasis in the intestinal tissue, as well as other elements that had been proposed as relevant in the literature. Nevertheless, the details of how these interactions are modeled couldn't be evaluated in the current revision as the model was not shared with the reviewers and it is not available yet online, nor specified in any detail in the current manuscript. Additionally, how quantitative information from Wnt and BMP signaling pathways is incorporated in a quantitative way in the model is not clear.

(2) Some conclusions by the authors are not properly justified in the text, as "Paneth cells are the main driver behind the differential mechanical environment in the niche", "Wnt-mediated feedback loop prevents the uncontrolled expansion of the niche", the specific effect of p27 in contrast with Wee1 phosphorylation over the cell cycle length, and "their recovery [absorptive progenitors] started before the end of the treatment, driven by a negative feedback loop from mature enterocytes to their progenitors".

(3) Only the results of the "main" model are shown, with no information about its sensitivity to parameter values, and how their conclusions depend on specific decisions on the model. For example, the authors said that "an optimal crypt cell composition is achieved when BMP and Wnt differentiation thresholds result in progenitors dividing approximately four times before differentiating into enterocytes", but the results of alternative scenarios are not shown.

(4) Regarding the construction of the model, the authors used "counts of Ki-67 positive cells recorded by position" while the original data reported "overall cell counts per crypt and villus". Some explanation about how this conversion was made, why it is valid, as well as any potential problems, is needed. Additionally, the model is based on experiments done by others in mouse models; the similarity to the response in human intestinal crypts is not discussed.

(5) The authors imply that their mathematical model of the intestinal crypt is an improvement over those already published but there is no direct comparison or review of the literature to substantiate this claim.

(6) The authors claim that the simulated data and the available mouse data match up. Nevertheless, the data vs the model still appear both quantitatively and qualitatively different (as presented in Figures 2E, F, and 5C, D). This puts in doubt how much the model can actually reproduce the experimental data. In conclusion, the model would benefit from further refinement, particularly if the goal is to use the model for predicting the dynamics of oncogenic drug candidates.

Reviewer #2 (Public Review):

Respiratory chain complexes assemble in higher-ordered structures termed supercomplexes or respirasomes. The functional significance of these assemblies is currently investigated, there are two main hypothesis tested, namely that supercomplexes provide kinetic advantages or structural stability. Here, the authors use the fruitfly to reveal that, while the respiratory chain in the organism normally does not form higher-order assemblies, it does so under conditions when their assembly is impaired. Because the rather moderate increase in supercomplex formation does not change oxygen consumption stimulated by CI or CII substrate, the authors conclude that supercomplex formation has more a structural than a functional role. The main strength of this work is that the technical quality of the experiments is high and that the authors induced defects in respiratory chain assembly through sets of well-controlled genetic models. The obtained data are mostly descriptive using standard approaches and are very well executed. The authors claim that their experiments allow to conclude that the role of supercomplex formation is restricted to a structural role and, hence, exclude a function directly related to electron transport efficiency. However, while the authors can show convincingly that supercomplexes form in the mutants, but not in the wild type, the main questions still remain, namely what is the structural mechanism of supercomplex formation and what is the significance of their formation. Given that the fly system does not show supercomplex formation under normal conditions, it is likely that it evolved functionally to work different than systems having supercomplexes. Because these differences are yet unknown, it remains questionable whether the fly system can be used to inform about the general significance of supercomplexes found in the other systems.

Reviewer #1 (Public Review):

In their manuscript, Brischigliaro et al. show that the disruption of respiratory complex assembly results in Drosophila melanogaster results in the accumulation of respiratory supercomplexes. Further, they show that the change in the supercomplex abundance does not impact respiratory function suggesting that the main role of supercomplex formation is structural. Overall, the manuscript is well written and the results and conclusion are supported. The D. melanogaster system, in which the abundance of supercomplexes can be altered through the genetic disruption of the assembly of the individual complexes, will be important for the field to discover the role of the supercomplexes. This manuscript will be of broad interest to the field of mitochondrial bioenergetics. The findings are valuable and the evidence is convincing.

Strengths<br /> The system developed in which the relative levels of SCs can be varied will be extremely useful for studying SC physiology.

The experiments are clearly described and interpreted.

Weaknesses<br /> The previous weaknesses identified have been addressed.

Reviewer #1 (Public Review):

DMRT1 is essential in testis development in different species. While Dmrt1 is the testis-determining factor in chicken and deletion encompassing this gene lead to gonadal dysgenesis in human, the role of DMRT1 in testis development remains to be clarified. Despite an early expression of Dmrt1 in the mouse gonad and a potential function as a pioneer factor, DMRT1 is only required for the maintenance of the Sertoli cell identity in the postnatal testis. The use of a new animal model could provide new insights into the role of this factor in humans. Here the authors have generated a knockout model of DMRT1 in rabbits. They show that the XY mutant gonads differentiate as ovary indicating that DMRT1 is required for testis differentiation in rabbits. In addition, most of the germ cells remain pluripotent as evidenced by the maintenance of POU5F1 in both XY and XX mutant gonads. These are very important results potentially explaining gonadal dysgenesis associated with the DMRT1 locus in disorders of sex development in humans.

The experiments are meticulous and convincing. I find the arguments of the authors about the role of DMRT1 in germ cells in addition to its function in Sertoli cell differentiation, both comprehensible and compelling. Clearly, this is an important insight in sex determination and gametogenesis.

Reviewer #2 (Public Review):

It is well known that DMRT proteins and more specifically, DMRT1 plays a key role in the sex determination processes of many species. While DMRT1 has been shown to be critical for the sex determination of fish, birds, and reptiles, it seems less crucial at the sex determination stages of the mice. It is important though for adult sex maintenance in mice.

Unlike its minor role in mouse sex determination, it seems that variants in DMRT1 in humans cause 46, XY DSD and sex reversal.

The paper by Dujardin et al. is a beautiful study that provides an answer to this long-lasting discrepancy of the difference between the two common mammal species: human and mouse. It is a really nice example of how working with other mammal species, like the rabbit, could serve as a nice model for understanding mammalian sex determination.

In this study the researchers first described the expression patterns of DMRT1 in the rabbit XY and XX gonads throughout the window of sex determination.

They then used CRISPR/Cas9 to generate DMRT1 KO rabbits and analysed the phenotype in XY and XX rabbits. They show that XY rabbits present with complete XY male-to-female sex reversal, very similar to what observed in human 46, XY DSD patients (but not the mice model). They further show that in the XY sex reversed gonads, germ cells fail to enter meiosis. They next analysed XX gonads and while there is no major effect on sex determination (as expected), the germ cells in these ovaries fail to enter meiosis, highlighting the critical role that DMRT1 has in germ cells.

I think it is really important that we start to embrace other mammal models that are not the mouse as we find many instances that the mouse is not the optimal system for understanding human sex determination.

The study is well explained and presented. The data is clear, and the paper is fluent to read.

Reviewer #3 (Public Review):

This manuscript deal with the sex-related gene, DMRT1, showing that is has a testis-promoting function in the rabbit. Loss-of-function studies the mouse and human, DMRT1 has a role in testis maintenance after birth, although forced expression in mouse can induce testis formation.

The authors used CRISPR/Cas9 genome editing to generate DMRT1-/- rabbit embryos. The gonads of these embryos developed as ovaries. Interestingly, in addition Y-linked SRY, DMRT1 is required for timely up-regulation of SOX9 during Sertoli cell differentiation in the male gonad. This is quite different to the situation in mouse, where Dmrt1 is not required in the testis until after birth (and Sry induced up-regulation of Sox9 hence does not require Dmrt1).

The work adds to the field of sex determination by further broadening our understanding of the DMRT1 gene and the evolution of gonadal sex determination.

In the Discussion section, it is suggested that DMRT1 could act as a pioneering factor to allow SRY action upon Sox9 in the rabbit model. The data show that DMRT1 may be more central to testis formation in mammals than previously considered. The work supports the notion that our understanding that the genetics of gonadal development (and indeed development more generally) should not rest solely on findings in the mouse.

Reviewer #2 (Public Review):

This manuscript by Martin-Flores et al. has examined the role of DKK3 in Alzheimer's disease, focusing on the regulation of synaptic numbers. By using human AD brain databases and tissue samples, the authors showed that DKK3 protein and mRNA levels are increased in the brains of AD patients. DKK3 is expressed in the excitatory neurons in WT mouse brains and accumulates at atrophic neurites around amyloid plaques in AD mouse brains. Interestingly, secretion of DKK3 appears to be regulated by NMDAR antagonist as well as chemical LTD. Through gain and loss of function studies, the authors showed that DKK3 regulates the number of excitatory as well as inhibitory synapses with distinct downstream pathways. Finally, the authors investigated the contribution of DKK3 to synaptic changes in AD and found that DKK3 loss of function rescues both the excitatory and inhibitory synaptic defects, resulting in the improvement of memory function in J20 mice.

Overall, the data is clearly presented and deals with novel roles of DKK3 in controlling excitatory and inhibitory synapses. The finding that shRNA expression of DKK3 in AD model mice rescues synaptic phenotypes and memory impairment is potentially interesting and may provide a new strategy for AD treatment.

Reviewer #1 (Public Review):

In this study, Nuria Martin-Flores, Marina Podpolny and colleagues investigate the role of Dickkopf-3 (DKK3), a Wnt antagonist in synaptic dysfunction in Alzheimer's disease. Loss of synapses is a feature of Alzheimer's and other forms of dementia such as frontotemporal dementia and linked amyotrophic lateral sclerosis (FTD). The authors utilise a broad range of experimental approaches. They show that DKK3 levels are increased in Alzheimer's disease and that this occurs early in disease. This is an important finding since early disease changes are believed to be the most important. They also show increases in DKK3 in transgenic mouse models of Alzheimer's disease and that DKK3 knockdown restores synapse number and memory in one such model. Finally, they link these DKK3 increases to loss of excitatory synapses via the blockade of the Wnt pathway and subsequent activation of GSK3B; GSK3B is strongly linked to both Alzheimer's disease and FTD. The quality of the data is good and the conclusions well supported by these data. There are no major weaknesses. The findings support studies that target the Wnt pathway as a potential therapeutic for Alzheimer's disease.